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Dissertation
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Explaining and Visualizing Structural Knowledge in Bipartite Graphs
(2023)
Bipartite graphs are an important model for the representation and analysis of relationships between two different types of entities. Datasets in this form are commonly found in many fields, such as social networks, biology, and economics. Formal concept analysis is a research approach that allows for the analysis of such bipartite graphs by clustering the data into so-called concepts and ordering those in a lattice structure.
In this thesis we propose multiple approaches for the extraction and visualization of ...
Dissertation
![Open Access](/themes/Mirage2/images/Open_Access_logo_PLoS_transparent.svg)
Attribute Exploration with Multiple Experts
(2023)
Attribute exploration is a knowledge acquisition method from the realm of formal concept analysis that allows a domain expert to efficiently uncover the dependencies in a domain. It is based on a question-answering scheme where the exploration algorithm generates questions about dependencies in the domain that are then answered by a domain expert. Even though many variants and extension to this were developed, only few attempts to incorporate multiple experts were made. The overarching goal of this thesis is to extend ...
Dissertation
![Open Access](/themes/Mirage2/images/Open_Access_logo_PLoS_transparent.svg)
Situative Teams in Cooperative Autonomous Systems
(2023)
Distributed systems have been established in many areas of IT and will play an even more significant role in the future. Such systems are no longer limited to specific fields of application but interconnect many different domains. They encompass, e. g. Cloud Computing, Internet of Things, service robotics, and autonomous vehicles. The integrated sub-systems communicate in order to exchange information and, if necessary, perform tasks together. Moreover, the number of interconnected sub-systems is constantly growing. ...
Dissertation
![Open Access](/themes/Mirage2/images/Open_Access_logo_PLoS_transparent.svg)
Context Awareness for Smartphone-Based Cooperative VRU Collision Avoidance
(2024)
Nach Angaben der Weltgesundheitsorganisation sterben weltweit noch immer jährlich rund 1,35 Millionen Menschen bei Verkehrsunfällen. Ungefähr 54% dieser Todesfälle ereignen sich unter ungeschützten Verkehrsteilnehmern wie Fußgängern, Radfahrern und Motorradfahrern. Fußgänger und Radfahrer machen dabei zusammen rund 26% aller Verkehrstoten aus. Im Gegensatz zu fahrzeugbasierten Kollisionsvermeidungssystemen setzen kooperative Systeme die Verwendung von mobilen Geräten wie Smartphones zur kontinuierlichen Erfassung von ...
Dissertation
![Open Access](/themes/Mirage2/images/Open_Access_logo_PLoS_transparent.svg)
Effektive Integration von heterogenen Produktkatalogen im schnelllebigen Umfeld des E-Commerce
(2023)
Online-Marktplätze generieren von Jahr zu Jahr einen größeren Anteil des Einzelhandelsumsatzes. Ein wichtiger Faktor für den Erfolg von Online-Marktplätzen ist die korrekte Darstellung der Produktdaten für ihre Kunden. Diese Daten werden häufig von Zulieferern in Form von Produktkatalogen zur Verfügung gestellt, die in den Online-Marktplatz integriert werden müssen. Um dies zu erreichen, sind insbesondere kleine und mittelständische Unternehmen häufig auf aufwändige manuelle Arbeitsschritte bei der Datenintegration ...
Dissertation
![Open Access](/themes/Mirage2/images/Open_Access_logo_PLoS_transparent.svg)
Object Detection for Automotive Radar Perception
(2024)
Automated vehicles are among the biggest trends in the automotive industry. The desired level of automation slowly progresses from advanced driver assistance system functions to fully autonomous driving. Excellent environmental perception is a critical requirement in this development. This thesis focuses on solutions to the challenges that come with the utilization of automotive radar systems for road user recognition. Therefore, several machine learning techniques are applied and compared to detect and classify ...
Dissertation
Algorithms for Emotion Recognition
(2023)
Technological advancements have increasingly facilitated emotion recognition through physiological sensors integrated into intelligent devices, such as earables and wristbands. People commonly wear these devices in their everyday lives (i.e., in the wild). Patterns can be extracted from various physiological signals, enabling the recognition of emotions. This capability can be integrated into diverse applications, such as attention management systems, human-robot interaction, and stress detection, enhancing them to ...
Dissertation
Investigation and Elimination of Substructures in Formal Concept Analysis focusing on Boolean Suborders and Subcontexts
(2023)
In the field of Formal Concept Analysis, data is mainly presented in so-called formal contexts, which assign to a set of objects their respective attributes. From those concept lattices can be generated, where the objects are grouped with respect to their common attributes to represent the relationships in the data in a way that enhances the understandability for humans. However, since a concept lattice can be of exponential size compared to its associated formal context, the presented relationships often become hard ...
Dissertation
A Language Ecosystem for Modeling Microservice Architecture
(2022)
The ongoing digital transformation of our economy and society poses significant challenges towards modern software systems. Application areas like Smart Cities and Industry 4.0 set high requirements on software quality attributes like scalability and reliability. At the same time, IT companies face an ever-growing demand in flexibility and continuous improvements of delivery cycles. Microservice Architecture (MSA) is a novel approach to the realization of software architectures that aims to foster their scalability, ...
Dissertation
Trajectory Mapping in Physical and Topical Spaces
(2023)
In this dissertation, two different types of trajectories are investigated. In the engfirst part of this work, we investigate methods for the analysis of physical trajectories. We focus on scenarios, in which signal strengths ofWiFi access points are recorded. In detail, they are recorded through smartphone devices by people moving through a building. By means of theWiFi signal strengths, (physical) trajectories of humans are reconstructed, which reflect the locations visited over time. Accurate localization based ...