TY - THES A1 - Ertel, Florence Laura Louise T1 - Europapolitische Themen in Wahlkämpfen: Chancen und Herausforderungen der Anwendung von Blended Reading-Verfahren für die Europäische Integrationsforschung N2 - Durch fortschreitende Digitalisierung wächst die Verfügbarkeit digitaler Textdaten europapolitischer Diskurse. Gleichzeitig werden algorithmusbasierte Verfahren zur Analyse dieser großen Menge an Textdaten stetig weiterentwickelt. Für die europäische Integrationsforschung bietet die Vielfalt der Kommunikationsarten und -formen die Möglichkeit, gesellschaftliche, mediale und politische Diskurse zur europäischen Integration auf den verschiedensten Ebenen nachzuvollziehen. Chancen birgt dies insbesondere aus der integrationstheoretischen Perspektive des Postfunktionalismus. Dieser Ansatz rückt die vermehrte Politisierung der europäischen Integration in den Mittelpunkt. Denn mit der zunehmenden Vertiefung der europäischen Integration wächst zugleich der europäische Einfluss auf nationale Policies und wirkt sich immer unmittelbarer auf das Leben der Europäer:innen aus. Dies führt zu verstärkter Polarisierung und Mobilisierung innerhalb der Gesellschaft und spiegelt sich in einer wachsenden Spaltung zwischen proeuropäischen und antieuropäischen politischen Lagern wider. So werden Einstellung zur EU zu einer wichtigen strukturellen Spaltungslinie zwischen Parteien. Folgt man der GAL/TAN-These von Hooghe und Marks (2009), können Parteien in grüne, alternative, libertäre und grundsätzlich proeuropäische sowie traditionalistische, autoritäre, nationalistische und eher euroskeptische Parteien unterteilt werden. Letztere nutzen insbesondere digitale Kommunikationsräume verstärkt und effektiv. Dies unterstreicht die Notwendigkeit, Datengrundlagen für Analysen auf den digitalen Raum auszuweiten und zu archivieren, um den Diskurs in seiner Breite erfassen zu können. Mit der Menge an digital verfügbaren Textdaten wächst allerdings auch die Unübersichtlichkeit. Dies führt zu methodischen Herausforderungen in Bezug auf die Art der Daten, die Datensammlung und -speicherung sowie die Datenvorverarbeitung und -analyse. Angesichts großer Textdatenmengen stoßen in der europäischen Integrationsforschung übliche qualitative Analyseverfahren an ihre Grenzen. Quantitative Analyseverfahren verändern das Verhältnis von Textdatenmaterial und Forscher:in. Die wissenschaftliche Debatte setzt sich mit der Frage auseinander, wie sich Analysen angesichts der wachsenden Textdatenmengen gestaltet und steuern lassen, damit das Verhältnis von Textdatenmaterial und Forscher:in nicht durch Algorithmen, die einen Black-Box-Effekt in der Datenanalyse erzeugen können, verzerrt wird. Daraus ergibt sich die Notwendigkeit einer Verbindung von quantitativen und qualitativen Analysenmethoden auf epistemologischer und methodologischer Ebene, um reliable und valide Forschungsergebnisse zu gewährleisten. Dies impliziert die Überwindung der so häufig diskutierten Gegensätze von qualitativen und quantitative Analysen, datengeleiteten und theoriegeleiteten Analysen oder Close und Distant Reading. Allerdings existiert in der Politikwissenschaft bislang kein Best Practice-Workflow für die Analyse großer Textdatenmengen webbasierter Daten, mit dem intersubjektive Nachvollziehbarkeit und Reliabilität im Forschungsprozess gewährleistet werden können. An diese Forschungslücke knüpft die kumulative Dissertation an. In sechs aufeinander aufbauenden Publikationen in deutscher, englischer und französischer Sprache wird ein Best Practice-Workflow für Blended Reading entwickelt. Dieser Ansatz verbindet die Vorteile von quantitativer und qualitativer Forschung. Der starke methodische Schwerpunkt wird durch Fallstudien zu europäischen und nationalen Wahlkämpfen in Deutschland, Frankreich und Österreich kontextualisiert. Dafür wird die Rolle europapolitischer Themen in der Wahlkampfkommunikation der vergangenen zwei Jahrzehnte aus postfunktionalistischer Perspektive analysiert. Y1 - 2026 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-20504 ER - TY - THES A1 - Wirth, Olivia T1 - Digital Platforms and Mobile Technologies for Development: Essays on Firm Formalization, Financial Inclusion, and Agricultural Resilience in Sub-Saharan Africa N2 - Mobile technologies and digital platforms have expanded rapidly across sub-Saharan Africa, creating opportunities to strengthen state capacity, broaden financial inclusion, and build agricultural resilience. This dissertation examines their development impacts across three settings. Chapter 1 combines novel administrative tax records with high resolution data on mobile network rollout in Uganda to estimate the effects of mobile internet access on firm tax behavior and public revenue. Exploiting plausibly exogenous rollout timing, we find that improved access increases firm formalization and expands the tax base, strengthening revenue collection. Chapter 2 presents a randomized controlled trial in Niger—the world’s most financially excluded country—to identify barriers to adoption of a mobile money platform. Information provision raises awareness but not use, consistent with information being necessary but insufficient for diffusion. By contrast, a modest financial incentive significantly increases both adoption and usage. Chapter 3 uses a household panel collected before and after a severe drought in northern Ghana and exploits variation in rainfall in a differences-in-differences framework to estimate effects on production, income sources and adaptation plans. We find that increasing drought severity lowers soybean yields and revenues and decreases reliance on own-business income and remittances, reflecting broader livelihood impacts. Farmers who use mobile phones to access agricultural information make different input choices and adaptation plans. Taken together, these findings highlight the promise of mobile technologies and digital platforms for development. Their effectiveness, however, depends on complementary infrastructure and local capacity, underscoring the need for scalable, context-specific strategies to harness these tools for inclusive growth and resilience. KW - Digitalisierung KW - Mobilität KW - Landwirtschaft KW - Afrika Y1 - 2026 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-20049 ER - TY - THES A1 - Khosravi, Mohammad T1 - Hard Instances, Improved Algorithms and New Interdiction Models for Robust Optimization N2 - Robust combinatorial optimization seeks solutions that remain effective across all possible realizations of an uncertainty set, making the choice of this set a crucial factor in both the complexity and practical applicability of robust models. A key challenge in this field is striking a balance between computational tractability and solution quality, particularly when dealing with large uncertainty sets. This dissertation advances the field of robust optimization by addressing three central themes: (i) methods for generating hard instances and establishing a benchmark library, (ii) high-quality exact solution methods and approximation algorithms, and (iii) the modeling of uncertainty sets and their impact on problem complexity. The absence of a benchmark library for robust optimization problems makes it difficult to conduct fair and effective comparisons of different solution methods. As a result, researchers often rely on randomly generated instances, which may hinder meaningful evaluations. To address this issue, this work develops optimization-based and heuristic methods for generating challenging instances of robust problems. Additionally, to facilitate more consistent and insightful comparisons of solution algorithms with minimal effort, we introduce a standardized benchmark library for use by the research community. To tackle the computational challenges posed by large uncertainty sets, this dissertation proposes scenario reduction techniques specifically designed for robust optimization. These methods aim to reduce the size of the uncertainty set while preserving the objective value as accurately as possible. Unlike traditional clustering approaches, this formulation treats scenario reduction as an optimization problem independent of the underlying decision-making model, enabling structured reductions with theoretical performance guarantees. Experimental results demonstrate that this approach produces solutions of comparable or superior quality compared to those obtained through general-purpose clustering techniques. Building on this framework, we further refine scenario reduction by incorporating information about the structure of feasible solutions. While previous reduction methods focused exclusively on the uncertainty set, we show that integrating knowledge of feasible solutions leads to improved uncertainty sets and more accurate robust models. Through a combination of theoretical analysis and computational experiments, we establish the effectiveness of this approach in enhancing both tractability and solution quality in robust combinatorial optimization. Finally, we introduce a novel variant of discrete budgeted uncertainty for cardinality-based constraints or objectives, incorporating a weight vector into the budget constraint. Our theoretical analysis reveals that while the adversarial problem can be solved in linear time, the robust problem becomes NP-hard and non-approximable. Nonetheless, we propose and evaluate alternative modeling approaches that demonstrate promising scalability in practice. This dissertation contributes to robust optimization by offering new perspectives on uncertainty modeling, algorithmic techniques for scenario reduction, and complexity analyses of key robust problems. The proposed methods provide both theoretical guarantees and practical advancements, paving the way for more efficient and scalable robust optimization models. Y1 - 2026 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-20399 ER - TY - THES A1 - Rolvering, Geske T1 - Empirical Essays in Public Economics N2 - This dissertation exploits quasi-experimental methods and rich microdata to identify causal effects of public interventions that speak directly to the goals outlined in the 2030 Agenda for Sustainable Development. Specifically, the first chapter analyzes the effect of public child care provision on mothers’ career trajectories, focusing on the timing of labor market re-entry and the quality of occupational outcomes. It thereby contributes to the Sustainable Development Goals of "Gender Equality", "Reducing Inequalities", and "Decent Work and Economic Growth". The second chapter investigates the impact of all-day school programs on juvenile property, violent, and drug-related crime. By providing evidence on how school schedules can be structured to promote safe learning environments, it contributes in particular to the goal of "Quality Education". In addition, it also contributes to broader objectives related to "Good Health and Well-Being" as well as "Peace, Justice and Strong Institutions". The third chapter examines public attitudes toward climate change and carbon pricing in Germany and analyzes whether different types of information shift people’s policy views. By exploring measures to reduce resistance to effective but politically unpopular environmental policies, this chapter contributes to the goal of "Climate Action". KW - Public Economics KW - Applied Microeconomics Y1 - 2026 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-20186 ER - TY - THES A1 - Hosseini, Amir T1 - Integrated Scheduling and Material Handling: Theory and Applications in Manufacturing Systems N2 - Scheduling concerns the allocation of limited resources to competing tasks over time and is central to manufacturing systems. In practice, production scheduling is tightly linked to material handling, as jobs must be transported between machines, buffers, and storage locations. However, transportation decisions have often been simplified or decoupled from classical scheduling models. This dissertation investigates the problem of Integrated Scheduling and Material Handling (ISMH), where processing and transportation decisions are jointly optimized to improve overall system performance. The thesis develops this objective in three steps. First, it provides a structured and unified classification of scheduling problems with transportation elements, organizing a fragmented body of literature and clarifying methodological foundations. Second, it studies scheduling in AGV-based material handling systems under battery constraints, proposing a novel mixed-integer programming formulation and an exact solution approach based on logic-based Benders decomposition. Third, it extends integrated models to a buffer-constrained flow shop setting with mobile buffering, introducing a decomposition-based algorithm that significantly improves scalability. Together, these contributions advance conceptual understanding, modeling frameworks, and exact solution methods for integrated production and internal logistics planning in modern manufacturing systems. KW - Scheduling KW - Material Handling KW - Mixed Integer Programming-MIP KW - Logic Based Benders Decomposition Y1 - 2026 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-20249 ER - TY - THES A1 - Ryzhova, Anna T1 - The Transnational News Diets of Russian Speakers in Germany: what news they use and trust N2 - The present cumulative dissertation consists of four articles, and is based on more than 70 semi-structured interviews with the Russian speakers in Germany. Forty two interviews were conducted before of the start of Russia’s full-scale invasion of Ukraine, and the other twenty nine right after its beginning (out of which I used only twenty five for the final analysis, as I focused only on the Russian speakers, associated with agressor or neutral countries in Russia’s war in Ukraine). The dissertation addresses a variety of issues, related to the media use of the Russian speakers in Germany, which was previously understudied both in general and from political communication perspective (Panagiotidis, 2023). In the strand of migrants and media research, scholars point the following gaps: the lack of political element in studies of how migrants use media (Leurs and Smets, 2018), the lack of studies how homeland and host society media are used simultaneously, not in isolation from each other, and the lack of studies on the influence of homeland media on migrants as such (Ramasubramanian et al., 2017), and finally, communication scholars not using migration studies frameworks in their research on migrants, which leads to fields existing in parallel (Leurs & Smets 2018). This dissertation addresses all these gaps. Being the first study to apply the concepts of “news repertoires” and the latest theorization of “news literacy” for studying the migrant populations, as well as looking in-depth in the mechanisms of trust, I analyze the media diets of Russian speakers in Germany in their entirety, considering the contexts and roles, attributed to the German quality, Russian opposition, Russian state sponsored and other types of media, i.e. not analying them in isolation, and also looking at the motivations to use different media for different domains of their lives. Besides, for analysing the transformations of media diets of the Russian speakers in the aftermath of Russia’s full-scale invasion of Ukraine, I use the concept of “sense of belonging” to Russia to examine the deep, underlying reasons for why news repertoires of these audiences changed, or did not change in the light of Russia’s war crimes. As for the contribution to the German-language and Germany-focused literature on the Russian speakers, this is the first comprehensive study to scrutinize the media diets of Russian speakers in-depth with a special emphasis on their motivations, political affiliations and differentiating between the media these audiences “use” and the media they “trust”, as previous research on Russian speakers in Germany and their media use was largely focused on integration, largely ignoring the political aspect and Russia’s repetitive attempts to influence Russian speakers abroad (e.g.Hepp et al., 2011) or lacked nuance in their results (e.g. Boris Nemtsov Foundation Survey, which posed questions about “Russian media” without defining what it is, i.e. is that opposition media, Kremlin-sponsored media, etc. Finally, this thesis provides a comprehensive case study of audiences from an authoritarian context (or a former authoritarian context, for those, who migrated from Ukraine, but were socialized in the Soviet Union) who migrated to democracy and their media use, and also sheds light on the spectrum of motivations of audiences abroad to continue consuming media from an authoritarian homeland (in our case, Kremlin-sponsored media), which can provide important foundation for future research on other migrant groups from authoritarian contexts in democracies, such as Chinese migrants in Europe. Among the results of the present dissertation is an article on three types of news repertoires that these audiences have, and how political beliefs underpin them; an article on how they view the “truth” in media and why it is a concept of crucial importance for their news trust patterns; an article on news literacy and how migrant audiences need transnational news literacy knowledge in order to navigate complex media landscapes, in which authoritarian states actively try to reach them with their narratives; and finally, how a major crisis event, such as war in Ukraine, changed (or did not change) the news repertoires of the Russian speaking audiences in Germany and why the “sense of belonging” is at the core of these changes. KW - news use KW - Russian media KW - Kremlin media KW - propaganda Y1 - 2026 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-19867 ER - TY - THES A1 - Kochendörfer, Laura T1 - Rethinking systems use in information systems research – theories on individuals’ use of multiple information systems N2 - While individuals use multiple information systems (IS) every day, research on IS use predominantly investigates use with respect to only one information system at a time. In light of this “single-IS paradigm” (Gerlach & Cenfetelli, 2022), theoretical and empirical insights into the nature and behavioral manifestations of multiple IS use remain limited. To advance the discipline’s understanding of the multiple IS use reality, this dissertation theorizes mechanisms that are idiosyncratic to the context of individuals’ multiple IS use. Based on grounded theory methodology and interview data from individuals using multiple IS, this dissertation contributes two theories on multiple IS use in two essays. The first essay introduces an analytical theory of eight different interdependencies-in-use as core mechanisms that emerge as users engage with multiple IS. The second essay builds on these interdependencies-in-use and examines how one type of interdependency manifests in behavior. The resulting process theory explains a behavioral phenomenon resulting from multiple IS use: users transferring usage behaviors from one IS to another. This dissertation contributes a theoretical framework for conceptualizing multiple IS use with its underlying mechanisms that enable future research to systematically investigate multiple IS use and related phenomena. It further enriches insights on usage behavior by a multiple IS perspective, indicating that multiple IS use contexts give rise to unique behavioral dynamics. With that, the current conversation in IS use research that focuses on single IS use is extended with new theoretical insights on the use of multiple IS. The dissertation offers additional recommendations for practitioners to consider the interdependent way individuals use multiple IS. KW - Information systems KW - IS use KW - Interdependence KW - multiple IS use Y1 - 2026 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-20164 ER - TY - THES A1 - Wallenborn-Weiß, Benjamin T1 - Quo vadis Spruchverfahren? – Eine Evaluation der Reform durch das UmRUG sowie des verbleibenden Reformbedarfs des Spruchverfahrensgesetzes N2 - Die Arbeit beschäftigt sich mit einem Thema an der Schnittstelle zwischen dem Unternehmensrecht und dem Zivilverfahrensrecht, dem Spruchverfahrensgesetz (SpruchG). Hierbei wird der Status Quo de lege lata nach dem Gesetz zur Umsetzung der Umwandlungsrichtlinie und zur Änderung weiterer Gesetze (UmRUG) dargestellt. Anschließend nimmt der Autor eine Analyse der Ursachen für die lange Verfahrensdauer von Spruchverfahren vor, wobei er die Ergebnisse seiner eigens konzipierten Umfrage einfließen lässt. Nach einem Rechtsvergleich nach Österreich und die Schweiz werden Reformvorschläge und eigene Konzeptionierungen de lege lata und de lege ferenda diskutiert. KW - Spruchverfahren KW - UmRUG KW - Reformbedarf KW - Spruchverfahrensgesetz KW - SpruchG Y1 - 2026 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-20099 ER - TY - THES A1 - Min, Yufei T1 - Informationelle Rechtspositionen von Unternehmensträgern in Deutschland und China – unter besonderer Berücksichtigung der registergestützten Informationsversorgung N2 - Im Zeitalter der Digitalisierung und der Leistungssteigerung von Registern zur weiteren Wertschöpfung gewinnt die rechtliche Gestaltung der Informationslage über Unternehmensträger eine wichtige Bedeutung. Die Arbeit konzentriert sich primär auf staatliche Register sowie auf rein private Auskunfteien. Dabei wird die Rechtslage in Bezug auf die informationellen Rechtspositionen von Unternehmen als Registersubjekten in Deutschland und China untersucht. Auf dieser Grundlage wird ein Rechtsvergleich vorgenommen und abschließend ein internationales Registerrecht skizziert. KW - Unternehmensregistrierung KW - Informationsversorgung KW - Unternehmensnummer Y1 - 2026 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-20081 ER - TY - THES A1 - Frank, Florian T1 - Integrating physical unclonable functions from novel nanomaterials, circuit elements, and memory technologies into future hardware architectures N2 - Cryptographic keys are fundamental components for ensuring security in digital systems. To ensure reliable key generation and management, various technical concepts have been developed, primarily based on dedicated hardware components such as Trusted Platform Modules (TPMs). However, many modern systems, especially small resource-constrained devices, typically lack hardware support for secure key generation and management. To address these limitations, Physical Unclonable Functions (PUFs) have proven to be an effective solution for key generation, device authentication, and identification tasks. PUFs leverage inherent variations in hardware components to produce unique, device-specific keys. For a well-designed PUF, these keys can be reproduced reliably on the same device but are practically impossible to clone. Various types of PUFs exist, including those that exploit slight delay differences in circuits with symmetric paths. Others rely on physical characteristics of components already present in the computing system, such as SRAM or DRAM. However, many of these constructions rely on technologies that could be replaced by emerging ones in the future. Such a replacement may involve a transition from traditional memory technologies, such as SRAM, DRAM, and flash memory, to emerging Non-Volatile Memories (NVMs), including Ferroelectric RAM (FRAM), Magnetoresistive RAM (MRAM), and Resistive RAM (ReRAM). These new technologies, in turn, necessitate innovative hardware security solutions for generating intrinsic hardware fingerprints, ensuring security for next-generation embedded devices. Furthermore, the integration of nanomaterials, such as carbon nanotubes, into processor architectures and the adoption of reconfigurable hardware platforms like Field-Programmable Gate Arrays (FPGAs) require the development of specifically tailored cybersecurity solutions. This dissertation aims to develop hardware-based security mechanisms for these types of devices by designing new PUF constructions and demonstrating their practical applications. One focus lies on PUFs extracted from nanomaterials and emerging circuit elements, particularly memristive devices and Carbon NanoTube Field-Effect Transistors (CNT-FETs). For memristive devices, which form the basis of ReRAM memory, this work analyzes methods ranging from simple binary quantization to advanced techniques exploiting device-specific response patterns. In the case of CNT-FETs, custom-fabricated wafers are developed to construct PUFs with optimal properties, such as high robustness, uniformity, and entropy, even under varying environmental conditions. These conditions include fluctuations in ambient temperature. Based on an analysis of fundamental system components, this work evaluates the feasibility of deriving PUFs from fully integrated circuits. A specific focus is placed on emerging non-volatile memory technologies, assessing their potential for PUF applications. To achieve PUF behavior in these memory devices, techniques such as intentional timing manipulation, induced bit flips through row hammering, and variations in supply voltage are examined. These resulting bit flips can be exploited as PUF responses. Additionally, transforming raw PUF responses into cryptographically usable keys and integrating specific PUFs into practical applications are core components of this work. The demonstrated practical applications include an innovative architecture for encrypting and binding data to non-volatile memory modules, implemented on Multiprocessor System-on-Chips (MPSoCs) incorporating FPGAs. This architecture enables the storage of confidential data on non-volatile memory while simultaneously using the same module as a PUF, without requiring separate memory partitions solely for the PUF functionality. Finally, practical applications of hardware fingerprints in the automotive sector are demonstrated, including an FPGA-based implementation to maintain security while preserving the temporal determinism of time-critical messages. These goals are met through the use of hardware-implemented cryptographic algorithms coupled with an FPGA-based ring oscillator PUF. To summarize, this work presents new types of PUF implementations, starting with nanomaterials and emerging circuit elements, extending to PUFs derived from integrated circuits, and demonstrates innovative solutions for their integration into MPSoC-based architectures. N2 - Kryptografische Schlüssel bilden die Grundlage nahezu aller Verfahren zur Gewährleistung der IT-Sicherheit in digitalen Systemen. Um deren Generierung und Verwaltung zuverlässig zu ermöglichen, wurden verschiedene technische Konzepte entwickelt, allen voran dedizierte Hardware-Komponenten wie Trusted Platform Modules (TPMs). Ein Nachteil solcher Konzepte ist jedoch, dass diese Module nicht in allen Systemen integrierbar sind, weshalb Mikrocontroller in kleinen eingebetteten Systemen häufig keine Unterstützung für hardwaregestützte Schlüsselverwaltung bieten. Um dennoch eine sichere Kommunikation zu gewährleisten, haben sich kryptografische Schlüssel, die aus sogenannten Physical Unclonable Functions (PUFs) abgeleitet werden, als effektive Lösung bewährt. PUFs nutzen hardwarebedingte physikalische Abweichungen, die häufig durch den Produktionsprozess verursacht werden, um daraus einen unklonbaren, gerätespezifischen kryptografischen Schlüssel zu erzeugen. Ein Beispiel sind verzögerungsbasierte PUFs, die minimale Signalverzögerungen aufgrund geringfügiger Abweichungen in den Leitungslängen sowie weiteren elektrischen Parametern nutzen, um eine unklonbare, gerätegebundene Charakteristik zu extrahieren. Des Weiteren haben sich PUFs, die auf bereits in einem Rechensystem vorhandenen Hardwarekomponenten wie DRAM oder SRAM basieren, als kostengünstige Möglichkeit eines Hardware-Sicherheitsankers erwiesen. Der Großteil der derzeit verfügbaren PUF-Implementierungen basiert jedoch nahezu ausschließlich auf älterer Hardware, wie den oben erwähnten Speichertechnologien. In Zukunft könnten diese jedoch durch neuartige nichtflüchtige Speichertechnologien, insbesondere Ferroelectric RAM (FRAM), Magnetoresistive RAM (MRAM) und Resistive RAM (ReRAM), ersetzt werden. Bei diesen Technologien besteht ebenfalls die Notwendigkeit zur Ableitung von kryptografisch sicheren Schlüsseln, um den Schutz zukünftiger eingebetteter Systeme zu gewährleisten. Weitere zukunftsgerichtete Entwicklungen werden die Integration von Nanomaterialien, beispielsweise in Prozessoren, sowie der vermehrte Einsatz neuer Hardwarearchitekturen, wie etwa solcher auf Basis von Field-Programmable Gate Arrays (FPGAs), umfassen. Diese Dissertation hat sich zum Ziel gesetzt, diese Probleme zu adressieren. Sie umfasst die Entwicklung und Analyse verschiedener Arten neuartiger PUFs sowie deren Integration in praktische Anwendungen. Zunächst wird eine Analyse bestimmter Nanomaterialien durchgeführt, insbesondere die Untersuchung neuartiger, auf Kohlenstoffnanoröhrchen basierender Feldeffekttransistoren. Hierfür wurden speziell gefertigte Siliziumwafer entwickelt, um PUFs mit optimalen Eigenschaften wie hoher Robustheit, Uniqueness und Entropie zu realisieren. Dies soll selbst unter variierenden Umgebungsbedingungen, einschließlich Schwankungen der Umgebungstemperatur, gewährleistet werden. Darüber hinaus wird das Verhalten von memristiven Bauelementen, den Basiselementen von ReRAM Modulen, im Hinblick auf mögliche PUF-Implementierungen untersucht. Dabei werden Lösungen zur binären Klassifikation entwickelt und spezifische Response-Pattern beim Anlegen verschiedener elektrischer Signale untersucht. Im nächsten Schritt wurde die Erzeugung von PUFs in integrierten Schaltkreisen betrachtet, insbesondere in den oben genannten nichtflüchtigen Speichern. Hierzu werden Methoden genutzt, die sich bereits bei älteren Speichermodulen als erfolgreich erwiesen haben. Dazu gehören unter anderem die Variation der Versorgungsspannung, das absichtliche Unterschreiten der Zugriffszeiten sowie das Erzeugen von Bit-Flips mittels Row Hammering. Im letzten Teil dieser Dissertation wird die Integration verschiedener PUFs in praktische Anwendungen untersucht. Zu diesem Zweck wird eine FPGA-basierte Architektur entwickelt, die unter Verwendung von intrinsischen speicherbasierten PUFs das Speichermodul gleichzeitig zum Ablegen vertraulicher Daten nutzt und diese Daten zusätzlich durch einen vom gleichen Modul abgeleiteten Schlüssel an dieses bindet. Dies ist möglich, ohne zusätzlichen Speicherplatz für die PUF-Erzeugung zu reservieren. Ein weiterer praktischer Anwendungsfall im Automotive-Kontext wird demonstriert. Hier wird ebenfalls eine FPGA-basierte Lösung vorgestellt, die Authentizität und Integrität im Fahrzeug gewährleistet und gleichzeitig den zeitlichen Determinismus der Kommunikation im Fahrzeug bewahrt. Dies wird durch den Einsatz hardwaregestützter kryptografischer Algorithmen in Verbindung mit einem FPGA-basierten Ring-Oszillator-PUF erreicht. Zusammenfassend stellt diese Arbeit neuartige PUF-Implementierungen vor, die auf Konstruktionen mit Nanomaterialien und innovativen Schaltungselementen basieren. Aufbauend darauf werden Methoden zur Extraktion von PUFs aus neuartigen nichtflüchtigen Speichertechnologien untersucht. Abschließend werden praxisnahe, innovative Anwendungen auf MPSoC-Plattformen vorgestellt, die den Einsatz von PUFs demonstrieren. KW - Physical Unclonable Functions KW - Hardware Security KW - Nanomaterials KW - Emerging Memory Technologies KW - FPGAs Y1 - 2026 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-20104 ER - TY - THES A1 - Grüner, Alina T1 - Stranger Danger? Three Essays on Consumer Trust and Data Disclosure in Multi-Actor Environments T1 - Stranger Danger? Drei Essays über Konsumentenvertrauen und Datenpreisgabe in Multi-Akteurs-Umgebungen N2 - Technological advancements and digitalization in recent decades have led an increasing number of firms to recognize the value of multi-actor business models. Integrating third parties into business processes provides firms with several benefits, including access to additional resources, skills, and information. However, from the consumer’s perspective, the involvement of third parties, often unknown to the consumer, is frequently associated with uncertainty, privacy concerns, and, thus, a reluctance to engage with multi-actor business models. Such concerns are not unfounded: In many multi-actor environments, privacy-related misbehavior is common, whether caused by third-party firms, network users, or other actors. Incidents range from unauthorized data sharing to illegal surveillance, identity theft, and financial fraud. Consumers’ skepticism poses challenges for firms, requiring strategic measures that not only foster consumer engagement with the network but also help build trust in the presence of third-party involvement and manage the consequences of trust erosion following negative third-party experiences. While privacy research recognizes consumer concerns in multi-actor environments, the literature does not offer specific business strategies to encourage data disclosure in the context of third-party involvement. Instead, research on multi-actor business models has largely focused on the benefits of shared value creation, while the broader impact of negative third-party privacy-related incidents on the overall actor-network remains underexplored. This dissertation addresses this research gap through three independent essays, aiming to identify business strategies that enhance consumer trust and willingness to disclose data in multi-actor environments and counteract the negative effects of (potential) third-party misbehavior on the actor-network. It focuses on preventive measures that address consumers’ concerns before interacting with the actor-network, as well as reactive strategies that are designed to maintain consumers’ engagement with an actor-network after a negative experience with one of the actors. As a first step toward identifying effective business strategies in multi-actor environments, Essay 1 examines two mechanisms: transparency and control, commonly used to foster consumers’ willingness to disclose data. While not explicitly framed as a multi-actor study, Essay 1 investigates how firms’ implementation of transparency and control features regarding data practices influences consumers’ willingness to disclose data. Two online scenario experiments compare a proactive approach, where consumers receive all relevant information and control options upfront, with an upon-request approach, where they access details by clicking for more information. The results show that the proactive approach increases cognitive effort and reduces data disclosure, while perceptions of procedural fairness do not significantly differ between the approaches. This pattern also holds in high-sensitivity conditions involving third-party data sharing, suggesting that the upon-request approach is effective across both single-actor and multi-actor environments. Building on these findings, Essay 2 analyzes how the representation of actor-networks influences consumers’ willingness to disclose data. Drawing on social psychology research on perceived entitativity, three online scenario experiments show that consumers trust firm networks more when they perceive them as highly entitative - as cohesive and integrated entities - rather than as low entitative, meaning a loose collection of independent firms. This greater trust, in turn, enhances their willingness to disclose personal data. Moreover, the analyses reveal that consumers process information about highly entitative firm networks more fluently and experience lower uncertainty than when engaging with low-entitativity networks. This essay also holds substantial practical significance by identifying concrete design recommendations to enhance perceived entitativity. In Essay 3, a platform is conceptualized as a multi-actor environment that enables peer-to-peer interactions. This essay investigates how consumers’ negative experiences with other users in multi-actor environments affect trust in the platform as a whole. Two studies were conducted in the home-sharing context, where consumers grant deep access to their privacy by allowing others into their homes or by sharing images of their private living spaces, addresses, and payment details. This openness entails inherent risks when interacting with other users and may facilitate misbehavior. The findings reveal a negative bottom-up trust transfer, whereby a negative experience with another user leads to diminished trust in the misbehaving user and, subsequently, in the platform. Although the platform does not directly control user behavior, consumers attribute part of the responsibility for negative incidents to the platform, which in turn reduces loyalty. This effect is stronger for negative outcome-related incidents, which pertain to the core service itself, than for negative process-related incidents, which relate to the service delivery process. To effectively mitigate this erosion of loyalty, Essay 3 identifies high prior relationship satisfaction between the consumer and the platform as a key buffering mechanism in which firms should actively invest. The insights from my dissertation extend privacy research by examining multi-actor environments and analyzing how firms can encourage consumers to disclose personal data, which psychological mechanisms guide their decision-making, and how trust is established and transferred within the network. Furthermore, this dissertation raises corporate awareness of the risks associated with the involvement of third parties in multi-actor settings. It provides practical strategies to mitigate these risks, fostering consumer acceptance and ensuring the long-term success of such business models. N2 - Technologische Fortschritte und die zunehmende Digitalisierung der letzten Jahrzehnte haben dazu geführt, dass immer mehr Unternehmen den Wert von Multi-Akteurs-Geschäftsmodellen erkennen. Die Integration von Drittakteuren in Geschäftsprozesse bietet Unternehmen zahlreiche Vorteile, darunter den Zugang zu zusätzlichen Ressourcen, Kompetenzen und Informationen. Aus Konsumentensicht ist die Einbindung von Drittparteien, die den Konsumenten häufig unbekannt sind, jedoch oftmals mit Unsicherheit und Datenschutzbedenken verbunden und führt folglich zu einer geringeren Bereitschaft, mit Multi-Akteurs-Geschäftsmodellen zu interagieren. Diese Bedenken sind nicht unbegründet: In vielen Multi-Akteurs-Umgebungen ist datenschutzbezogenes Fehlverhalten weit verbreitet, unabhängig davon, ob es von Drittunternehmen, Netzwerknutzern oder anderen Akteuren ausgeht. Die Vorfälle reichen von unautorisierter Datenweitergabe über illegale Überwachung und Identitätsdiebstahl bis hin zu finanziellem Betrug. Die Skepsis der Konsumenten stellt Unternehmen vor erhebliche Herausforderungen und erfordert strategische Maßnahmen, die nicht nur die Interaktion der Konsumenten mit dem Netzwerk fördern, sondern auch Vertrauen trotz der Einbindung von Drittakteuren aufbauen und die Folgen von Vertrauensverlusten nach negativen Erfahrungen mit Drittparteien abfedern. Zwar erkennt die Datenschutzforschung Konsumentenbedenken in Multi-Akteurs-Umgebungen an, die bestehende Literatur bietet jedoch kaum konkrete unternehmerische Strategien zur Förderung der Datenpreisgabe im Kontext von Drittparteien. Stattdessen konzentriert sich die Forschung zu Multi-Akteurs-Geschäftsmodellen bislang überwiegend auf die Vorteile gemeinsamer Wertschöpfung, während die umfassenderen Auswirkungen negativer, datenschutzbezogener Vorfälle durch Drittakteure auf das gesamte Akteursnetzwerk weitgehend unerforscht bleiben. Diese Dissertation adressiert diese Forschungslücke in drei eigenständigen Essays mit dem Ziel, unternehmerische Strategien zu identifizieren, die das Vertrauen der Konsumenten und ihre Bereitschaft zur Datenpreisgabe in Multi-Akteurs-Umgebungen stärken sowie die negativen Effekte (potenziellen) Fehlverhaltens von Drittakteuren auf das Akteursnetzwerk abmildern. Der Fokus liegt dabei sowohl auf präventiven Maßnahmen, die Konsumentenbedenken bereits vor der Interaktion mit dem Akteursnetzwerk adressieren, als auch auf reaktiven Strategien, die darauf abzielen, das Engagement der Konsumenten nach einer negativen Erfahrung mit einem der Akteure aufrechtzuerhalten. Als ersten Schritt zur Identifikation wirksamer Strategien in Multi-Akteurs-Umgebungen untersucht Essay 1 zwei etablierte Mechanismen zur Förderung der Datenpreisgabebereitschaft von Konsumenten: Transparenz und Kontrolle. Obwohl Essay 1 nicht explizit als Multi-Akteurs-Studie konzipiert ist, analysiert er, wie die Umsetzung von Transparenz- und Kontrollmechanismen in Bezug auf Datenpraktiken die Bereitschaft der Konsumenten zur Datenpreisgabe beeinflusst. Zwei Online-Szenarioexperimente vergleichen einen proaktiven Ansatz, bei dem Konsumenten alle relevanten Informationen und Kontrollmöglichkeiten unmittelbar erhalten, mit einem Upon-Request-Ansatz, bei dem weiterführende Informationen erst durch aktives Anklicken zugänglich sind. Die Ergebnisse zeigen, dass der proaktive Ansatz den kognitiven Aufwand erhöht und die Datenpreisgabe reduziert, während sich die Wahrnehmung prozeduraler Fairness zwischen den Ansätzen nicht signifikant unterscheidet. Dieses Muster zeigt sich auch in Hochsensitivitätsbedingungen, die eine Datenweitergabe an Drittparteien beinhalten, was darauf hindeutet, dass der Upon-Request-Ansatz sowohl in Single-Actor- als auch in Multi-Akteurs-Umgebungen effektiv ist. Aufbauend auf diesen Ergebnissen analysiert Essay 2, wie die Darstellung von Akteursnetzwerken die Bereitschaft der Konsumenten zur Datenpreisgabe beeinflusst. In Anlehnung an sozialpsychologische Forschung zur wahrgenommenen Entitativität zeigen drei Online-Szenarioexperimente, dass Konsumenten Netzwerken von Unternehmen stärker vertrauen, wenn sie diese als hoch entitativ – also als kohäsive und integrierte Einheiten – wahrnehmen, im Vergleich zu niedrig entitativen Netzwerken, die als lose Zusammenschlüsse unabhängiger Unternehmen erscheinen. Dieses erhöhte Vertrauen steigert wiederum die Bereitschaft zur Preisgabe persönlicher Daten. Darüber hinaus zeigen die Analysen, dass Konsumenten Informationen über hoch entitative Unternehmensnetzwerke fließend verarbeiten und geringere Unsicherheit empfinden als bei niedrig entitativen Netzwerken. Dieser Essay besitzt zudem eine hohe praktische Relevanz, da er konkrete Gestaltungsempfehlungen zur Erhöhung der wahrgenommenen Entitativität identifiziert. In Essay 3 wird eine Plattform als Multi-Akteurs-Umgebung konzeptualisiert, die Peer-to-Peer-Interaktionen ermöglicht. Der Essay untersucht, wie negative Erfahrungen von Konsumenten mit anderen Nutzern in Multi-Akteurs-Umgebungen das Vertrauen in die Plattform als Ganzes beeinflussen. Zwei Studien wurden im Kontext der privaten Wohnraumvermietung durchgeführt, in dem Konsumenten tiefgehenden Zugang zu ihrer Privatsphäre gewähren, indem sie anderen Personen Zutritt zu ihren Wohnungen erlauben oder Bilder privater Wohnräume, Adressdaten und Zahlungsinformationen teilen. Diese Offenheit ist mit inhärenten Risiken verbunden und kann Fehlverhalten durch andere Nutzer begünstigen. Die Ergebnisse zeigen einen negativen Bottom-up-Vertrauenstransfer: Eine negative Erfahrung mit einem anderen Nutzer führt zu einem Vertrauensverlust gegenüber dem fehlhandelnden Nutzer und in der Folge auch gegenüber der Plattform. Obwohl die Plattform das Verhalten der Nutzer nicht direkt kontrolliert, schreiben Konsumenten ihr dennoch eine Mitschuld an negativen Vorfällen zu, was die Loyalität gegenüber der Plattform verringert. Dieser Effekt ist stärker bei ergebnisbezogenen Vorfällen, die den Kern der Dienstleistung betreffen, als bei prozessbezogenen Vorfällen, die sich auf die Leistungserbringung beziehen. Um dieser Loyalitätserosion wirksam entgegenzuwirken, identifiziert Essay 3 eine hohe vorherige Beziehungszufriedenheit zwischen Konsument und Plattform als zentralen Puffermechanismus, in den Unternehmen gezielt investieren sollten. Die Erkenntnisse dieser Dissertation erweitern die Datenschutzforschung, indem sie Multi-Akteurs-Umgebungen in den Fokus rücken und analysieren, wie Unternehmen Konsumenten zur Preisgabe persönlicher Daten motivieren können, welche psychologischen Mechanismen ihre Entscheidungsprozesse steuern und wie Vertrauen innerhalb von Netzwerken entsteht und übertragen wird. Darüber hinaus schärft die Dissertation das Bewusstsein von Unternehmen für die Risiken, die mit der Einbindung von Drittakteuren in Multi-Akteurs-Konstellationen verbunden sind. Sie liefert praxisnahe Strategien zur Reduktion dieser Risiken, fördert die Akzeptanz solcher Geschäftsmodelle bei Konsumenten und trägt damit zu deren langfristigem Erfolg bei. KW - Privacy Research KW - Marketing KW - Multi-Actor Environment KW - Trust KW - Transparency KW - Verbraucherverhalten KW - Marketing KW - Privatsphäre KW - Vertrauen KW - Transparenz Y1 - 2026 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-19957 ER - TY - THES A1 - Hackl, Veronika T1 - The Literate Human in the Loop: AI Feedback in Higher Education N2 - This cumulative dissertation, titled "The Literate Human in the Loop: AI Feedback in Higher Education," investigates the integration of Artificial Intelligence (AI) feedback systems within academic settings and the critical role of user competence. KW - AI Literacy Y1 - 2026 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-19982 ER - TY - THES A1 - Wendlinger, Lorenz T1 - Structure-aware Deep Learning N2 - Graph structures permeate the digital landscape in explicit and implicit forms. They connect or construct artifacts by combining semantic and structural information. We also observe them in the systems designed to process this data, in their learning algorithms and the very nature of the tasks they solve. At the same time, machine learning methods are extremely data-hungry, requiring petabytes of data for training. Due to their complexity, graphs remain an under-utilized resource in this regard. Many approaches cannot incorporate them due to being fully structurally unaware or not suited to the specific flavour of graphs encountered in some domains. This disconnect is sub-optimal from an effectiveness and efficiency perspective. We present methods that extend the scope of structure-aware deep learning through structural knowledge integration and enrichment, structural performance prediction, and synergistic transfer learning. Knowledge graphs organize information and make it directly available for querying. They provide a structured inference interface for manual and automated inspection, though they can suffer from data quality issues and require careful schema design. We rephrase the reconciliation of knowledge in knowledge graphs as a link prediction task, making it tractable with adapted graph neural networks, while also benefiting conventional link prediction tasks. We further combine textual semantics and structural expression for legal reference prediction via adapted heterogeneous graph neural networks operating on complex meta-information enriched graphs. Additionally, we explore methods for the integration of intermediary expressions in strongly typed heterogeneous graphs, improving prediction via meta-path-based processing. We also develop methods for automated machine learning workflow analysis and performance prediction. This includes the learning of salient representations for management as well as improvement of workflows through automatic suggestion and refinement of components. These are then extended to the prediction of Neural Architecture Search performance prediction, including adaptation to operation-on-edge spaces. Finally, we investigate the transfer capability of pre-trained attention structures for text-based prediction tasks and find it to be both inferior to directly optimized attention masks as well as highly dependent on inherent domain knowledge. We also show that the exploitation of hierarchical task formulation can improve prediction performance through joint learning in diverse learning domains, including link prediction, performance prediction, and specialized and general argumentation mining. The dissertation contains previously published or submitted texts: Wendlinger, L., Hübscher, G., Ekelhart, A., Granitzer, M. (2022). Reconciliation of Mental Concepts with Graph Neural Networks. In: Strauss, C., Cuzzocrea, A., Kotsis, G., Tjoa, A.M., Khalil, I. (eds): Database and Expert Systems Applications. DEXA 2022. Lecture Notes in Computer Science, vol 13427, p 133-146. Springer, Cham. https://doi.org/10.1007/978-3-031-12426-6_11; Wendlinger, L., Granitzer M. (2024). Informed Heterogeneous Attention Networks for Metapath Based Learning. In: SAC '24: Proceedings of the 39th ACM/SIGAPP Symposium on Applied Computing, p 458-465, ACM, New York. https://doi.org/10.1145/3605098.3635890; Wendlinger, L., Nonn, S.A., Al Zubaer, A., Granitzer, M. (2026). The Missing Link: Joint Legal Citation Prediction Using Heterogeneous Graph Enrichment. In: Wrembel, R., Kotsis, G., Tjoa, A.M., Khalil, I. (eds) Database and Expert Systems Applications. DEXA 2025. Lecture Notes in Computer Science, vol 16047, p 197-211. Springer, Cham. https://doi.org/10.1007/978-3-032-02088-8_14; Wendlinger, L., Stier, J., Granitzer, M. (2021). Evofficient: Reproducing a Cartesian Genetic Programming Method. In: Hu, T., Lourenço, N., Medvet, E. (eds) Genetic Programming. EuroGP 2021. Lecture Notes in Computer Science, vol 12691, p 162-178. Springer, Cham. https://doi.org/10.1007/978-3-030-72812-0_11; Wendlinger, L., Berndl, E., Granitzer, M. (2021). Methods for Automatic Machine-Learning Workflow Analysis. In: Dong, Y., Kourtellis, N., Hammer, B., Lozano, J.A. (eds) Machine Learning and Knowledge Discovery in Databases. Applied Data Science Track. ECML PKDD 2021. Lecture Notes in Computer Science, vol 12979, p 52-67. Springer, Cham. https://doi.org/10.1007/978-3-030-86517-7_4; Wendlinger, L., Granitzer, M., Fellicious, C. (2023). Pooling Graph Convolutional Networks for Structural Performance Prediction. In: Nicosia, G., et al. (eds) Machine Learning, Optimization, and Data Science. LOD 2022. Lecture Notes in Computer Science, vol 13811, p 1-16. Springer, Cham. https://doi.org/10.1007/978-3-031-25891-6_1; Wendlinger, L., Braun, C., Zubaer, A., Nonn, S., Großkopf, S., Fellicious, C., Granitzer, M.: On the Suitability of pre-trained foundational LLMs for Analysis in German Legal Education, submitted to the proceedings of the International Conference on Machine Learning, Optimization, and Data Science 2025, preprint published: https://doi.org/10.48550/arXiv.2412.15902; Wendlinger, L., Kuhn, R., Mitrovic, J., Granitzer, M. (2025). Joint Learning for Efficient German Argument Mining. In: 2025 IEEE 37th International Conference on Tools with Artificial Intelligence (ICTAI), Athens, Greece, 2025, p 770-777. IEEE, Los Alamitos. https://doi.org/10.1109/ICTAI66417.2025.00111. N2 - Graphenstrukturen durchdringen die digitale Landschaft in expliziten und impliziten Formen. Sie verbinden oder konstruieren Artefakte, indem sie semantische und strukturelle Informationen kombinieren. Wir beobachten sie auch in den Systemen, die zur Verarbeitung dieser Daten entwickelt wurden, in ihren Lernalgorithmen und in der Art der Aufgaben, die sie lösen. Gleichzeitig sind die Methoden des maschinellen Lernens extrem datenhungrig und benötigen Petabytes an Daten für das Training. Aufgrund ihrer Komplexität bleiben Graphen in dieser Hinsicht eine unzureichend genutzte Ressource. Viele Ansätze können sie nicht einbeziehen, weil sie die Struktur der Graphen nicht kennen oder nicht für die spezielle Art von Graphen geeignet sind, die in einigen Bereichen vorkommen. Diese Trennung ist aus Sicht der Effektivität und Effizienz suboptimal. Wir stellen Methoden vor, die den Anwendungsbereich des strukturbewussten Deep Learning durch strukturelle Wissensintegration und -anreicherung, strukturelle Leistungsvorhersage und synergetisches Transferlernen erweitern. Wissensgraphen organisieren Informationen und machen sie direkt für Abfragen verfügbar. Sie bieten eine strukturierte Inferenzschnittstelle für die manuelle und automatische Überprüfung, obwohl sie unter Problemen der Datenqualität leiden können und ein sorgfältiges Schemadesign erfordern. Wir formulieren den Abgleich von Wissen in Wissensgraphen als eine Aufgabe der Kantenvorhersage um, die mit angepassten neuronalen Netzen für Graphen durchführbar ist und auch konventionellen Kantenvorhersageaufgaben zugute kommt. Darüber hinaus kombinieren wir Textsemantik und strukturelle Ausdrücke für die Vorhersage rechtlicher Verweise mit Hilfe angepasster heterogener Graph neuronaler Netze, die auf komplexen, mit Metainformationen angereicherten Graphen arbeiten. Darüber hinaus erforschen wir Methoden zur Integration von intermediären Ausdrücken in stark typisierten heterogenen Graphen und verbessern die Vorhersage durch metapfadbasierte Verarbeitung. Wir entwickeln auch Methoden für die automatische Analyse von Prozessbeschreibungen und Leistungsvorhersagen für maschinelles Lernen. Dies beinhaltet das Lernen von bedeutungsvollen Repräsentationen für das Management sowie die Verbesserung von Prozessbeschreibungen durch automatische Vorschläge und Verfeinerung von Komponenten. Diese Methoden werden dann auf die Leistungsvorhersage der neuronalen Architektursuche ausgeweitet, einschließlich der Anpassung an die Operation-on-Edge-Räume. Schließlich untersuchen wir die Transferfähigkeit von vortrainierten Aufmerksamkeitsstrukturen für textbasierte Vorhersageaufgaben und stellen fest, dass diese sowohl den direkt optimierten Aufmerksamkeitsmasken unterlegen sind als auch in hohem Maße vom inhärenten Domänenwissen abhängen. Wir zeigen auch, dass die Ausnutzung hierarchischer Aufgabenformulierung die Vorhersageleistung durch gemeinsames Lernen in verschiedenen Lernbereichen verbessern kann, einschließlich Kantenvorhersage, Leistungsvorhersage und spezialisierter und allgemeiner Argumentationsanalyse. Die Dissertation beinhaltet bereits veröffentlichte oder zur Veröffentlichung vorgesehene Texte: Wendlinger, L., Hübscher, G., Ekelhart, A., Granitzer, M. (2022). Reconciliation of Mental Concepts with Graph Neural Networks. In: Strauss, C., Cuzzocrea, A., Kotsis, G., Tjoa, A.M., Khalil, I. (Hgg.): Database and Expert Systems Applications. DEXA 2022. Lecture Notes in Computer Science, vol 13427, S. 133-146. Springer, Cham. https://doi.org/10.1007/978-3-031-12426-6_11; Wendlinger, L., Granitzer M. (2024). Informed Heterogeneous Attention Networks for Metapath Based Learning. In: SAC '24: Proceedings of the 39th ACM/SIGAPP Symposium on Applied Computing, S. 458-465, ACM, New York. https://doi.org/10.1145/3605098.3635890; Wendlinger, L., Nonn, S.A., Al Zubaer, A., Granitzer, M. (2026). The Missing Link: Joint Legal Citation Prediction Using Heterogeneous Graph Enrichment. In: Wrembel, R., Kotsis, G., Tjoa, A.M., Khalil, I. (Hgg.) Database and Expert Systems Applications. DEXA 2025. Lecture Notes in Computer Science, vol 16047, S. 197-211. Springer, Cham. https://doi.org/10.1007/978-3-032-02088-8_14; Wendlinger, L., Stier, J., Granitzer, M. (2021). Evofficient: Reproducing a Cartesian Genetic Programming Method. In: Hu, T., Lourenço, N., Medvet, E. (Hgg.) Genetic Programming. EuroGP 2021. Lecture Notes in Computer Science, vol 12691, S. 162-178. Springer, Cham. https://doi.org/10.1007/978-3-030-72812-0_11; Wendlinger, L., Berndl, E., Granitzer, M. (2021). Methods for Automatic Machine-Learning Workflow Analysis. In: Dong, Y., Kourtellis, N., Hammer, B., Lozano, J.A. (Hgg.) Machine Learning and Knowledge Discovery in Databases. Applied Data Science Track. ECML PKDD 2021. Lecture Notes in Computer Science, vol 12979, S. 52-67. Springer, Cham. https://doi.org/10.1007/978-3-030-86517-7_4; Wendlinger, L., Granitzer, M., Fellicious, C. (2023). Pooling Graph Convolutional Networks for Structural Performance Prediction. In: Nicosia, G., et al. Machine Learning, Optimization, and Data Science. LOD 2022. Lecture Notes in Computer Science, vol 13811, S. 1-16. Springer, Cham. https://doi.org/10.1007/978-3-031-25891-6_1; Wendlinger, L., Braun, C., Zubaer, A., Nonn, S., Großkopf, S., Fellicious, C., Granitzer, M.: On the Suitability of pre-trained foundational LLMs for Analysis in German Legal Education, eingereicht für die Proceedings der International Conference on Machine Learning, Optimization, and Data Science 2025, vorab veröffentlicht: https://doi.org/10.48550/arXiv.2412.15902; Wendlinger, L., Kuhn, R., Mitrovic, J., Granitzer, M. (2025). Joint Learning for Efficient German Argument Mining. In: 2025 IEEE 37th International Conference on Tools with Artificial Intelligence (ICTAI), Athens, Greece, 2025, S. 770-777. IEEE, Los Alamitos. https://doi.org/10.1109/ICTAI66417.2025.00111. KW - graph neural networks KW - knowledge graphs KW - structural knowledge integration KW - structural performance prediction KW - synergistic transfer learning KW - link prediction tasks Y1 - 2026 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-19892 ER - TY - THES A1 - Neuwirth, Daniel T1 - Einbettung und Charakterisierung von aligned bar 1-visibility Graphen und outer fan free Graphen N2 - In dieser Arbeit werden drei verschiedene Klassen von Graphen untersucht. Die Klassen sind die bar (1;1)-visibilty Graphen, die aligned bar 1-visibility Graphen und die outer fan free Graphen. Die Klassen werden durch ihre möglichen Einbettungen charakterisiert. Die Repräsentation der bar (1; j)-visibility Graphen ist, dass jeder Knoten als horizontaler Strich und jede Kante als vertikaler Strich gezeichnet wird. Eine Kante kann einen Knoten genau einmal schneiden und ein Knoten kann j-mal geschnitten werden. Wir erweitern die Ergebnisse von Dean et. al. und geben Beispiele mit einer maximalen Dichte an für bar (1; 2)-visibility, bar (1; 3)-visibility und bar (1; 4)-visibility Graphen und geben einen maximal dünnen Graphen für die Klasse der bar (1;1) visibility Graphen an. Wir zeigen, dass die Klassen der bar (1; j)-visibility Graphen für 1 < j < 1eine unendliche Hierarchie bilden. Abschließend beweisen wir, dass das Erkennungsproblem ob ein Graph eine bar (1;1)-visibility Repräsentation hat, NP-vollständig ist. Die Klasse der aligned bar 1-visibility Graphen (AB1V ) erhält man, indem man die bar (1;1)-visibility Repräsentation um 90 Grad dreht und alle Knoten verlängert, so dass diese alle mit der y-Koordinate 0 starten. Die relative Position bzgl. der x-Koordinate wird mit der t-Ordnung beschrieben und mit der r-Ordnung die relative Position bzgl. der y-Koordinate. Wir erweitern die Erkenntnisse von Felsner und Massow für die Klasse der AB1V Graphen bzgl. ihrer maximalen Dichte, der minimale Grad eines Knotens. Wir führen die Methode Pfadaddition ein, um anhand deren Abschlusseigenschaften zu unterscheiden, ob ein Graph in einer Klasse liegt oder nicht. Diese Methode nutzen wir, um die Beziehung der Klasse der AB1V Graphen mit anderen Klassen zu untersuchen. Für die Klasse der maximalen Graphen geben wir einen dünnen Graphen und eine untere Schranke bzgl. der Dichte an. Wir geben einen Algorithmus an, welcher eine Bucheinbettung aus einer AB1V Einbettung berechnet. Für die Klassen der optimalen AB1V Graphen geben wir einen Einbettungsalgorithmus an. Wir verbessern den Erkennungsalgorithmus von Felsner und Massow, ob ein Graph mit einer gegebenen t-Ordnung eine AB1V Einbettung besitzt. Für die Klasse der distinkt strong AB1V Graphen, Graphen in der jeder Knoten ein unterschiedliche r-Ordnung hat und maximal für die r-Ordnung ist, geben wir einen Algorithmus an, der in O(n6) eine mögliche Einbettung berechnet. Zum Schluss zeigen wir für diese Klasse, dass es exponentiell viele verschiedene Einbettungen gibt. Ein Graph hat eine outer fan free Einbettung, wenn alle Knoten inzident zu einer Fläche sind und keine Kante von zwei Kanten geschnitten wird, die adjazent zu einem Knoten sind. Wir untersuchen diese Klasse zuerst auf die Dichte. Weiter erforschen wir die Beziehung zwischen den Klassen der AB1V , RAC und k-planaren Graphen. Abschließend geben wir eine Reduktion von NAE-3-SAT auf das Erkennungsproblem von outer fan free Graphen an. KW - Graph Drawing Y1 - 2026 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-19930 ER - TY - THES A1 - Fischer, Liliann T1 - An exploration of professional self concepts in science communication N2 - The dissertation explores emerging professional self concepts in the field of science communication. It integrates theories and concepts from a diverse range of disciplines from the sociology of professions to science and technology studies. It also considers organisational contexts and country specifics as major influencing factors and includes these in comparative frameworks. By triangulating data from different sources the dissertation offers broad insights not only into science communication but professionalisation more widely. T2 - eine Untersuchung beruflicher Selbstverständnisse in der Wissenschaftskommunikation KW - science communication KW - professionalisation KW - professional identity Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-19817 ER - TY - THES A1 - Schiermeier, Kathrin T1 - Multidimensional Wavelets and Neural Networks N2 - The construction of scaling functions and wavelets in multiple dimensions and for arbitrary scaling matrices is a challenging task entailing some complexities. Existing approaches mainly focus on the two-dimensional case using dyadic or quincunx sampling. This thesis aims to develop a method to construct multidimensional scaling and wavelet filters yielding orthogonal scaling functions and wavelets under the usage of convolutional neural networks. We start by recalling substantial fundamentals of ideals, modules, Fourier analysis, filterbanks and multiresolution analyses, where the mentioned concepts are already considered in an arbitrary dimensional setting to prepare the proof of the main result. There, we show the connection between multivariate scaling functions and multidimensional filters possessing certain properties. This enables us to construct scaling functions and corresponding wavelets by discrete filter design. Exploiting the link between the discrete wavelet decomposition, filterbanks and neural networks, we utilize the latter to do so. Being the main difficulty of this process, we especially focus on the Cohen criterion, which concerns the zeros of the Fourier transform of the scaling filter in modulus representing a multivariate trigonometric polynomial. After transferring the Bernstein inequality for univariate trigonomic polynomials to multiple dimensions, we present a method to derive a finite set of inequality constraints implying that the Cohen criterion holds true for a given multivariate cosine sum. Afterwards, we introduce neural networks and TensorFlow as the main tools to execute the described approach, formulate the described objective as an optimization problem and present some smaller numerical experiments and their results. A second objective of this thesis is the construction of filters possessing a unimodular modulation vector and therefore the ability to be completed to a perfect reconstruction filterbank. Both - the construction and the filterbank completion - can also be considered in a neural network framework as we will detail in the last section of this thesis alongside with the presentation of corresponding numerical experiments. In the context of filterbank completion, a further observation which allows to complete any given interpolatory filter to a perfect reconstruction filterbank in a very intuitive and simple way is presented. Furthermore, we explain that any given unimodular filter can be rendered interpolatory through prefiltering. KW - Wavelets KW - Filterbanks KW - Convolutional Neural Networks Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-19742 ER - TY - THES A1 - Henle, Mona T1 - Multi-Leader Congestion Games with an Adversary N2 - In this thesis, we introduced a congestion game with multiple leaders and a single follower (adversary) which is motivated by security applications with congestion effects. Our objective was to understand the result and the impact of selfish acting individuals in these games. In this regard, we analyzed the existence, the computation and the quality of (approximate) pure Nash equilibria. First, we observed that an exact pure Nash equilibrium always exists in the resulting strategic game among the leaders if the resource cost coefficients are identical and the underlying congestion game is a matroid congestion game. If one of these two conditions is not fulfilled, the existence of PNE is not ensured anymore in general. Consequently, we focused on approximate equilibria. For the case of symmetric singleton strategies, one of our main result established that K ≈ 1.1974, the unique solution of a cubic polynomial equation, is the smallest possible factor such that the existence of a K-approximate equilibrium is guaranteed for all instances of the game. To this end, we presented an efficient algorithm which computes a K-approximate PNE. Furthermore, we showed that the factor K is tight by providing an instance where no α-approximate PNE with α < K exists. However, for a specific symmetric singleton instance there might be a better α-approximate PNE, i.e., with α < K. A given instance could even admit an exact PNE. We provided therefore a polynomial time procedure that computes a best approximate PNE of a given instance. In particular, this procedure can verify the existence of an exact PNE in a given instance efficiently and, if it exists, can also determine the corresponding load vector. Finally, for symmetric singleton instances with two resources, we compared the total cost of a best (cheapest) and worst (most expensive) PNE to the total cost of an optimal outcome, termed by the price of stability and the price of anarchy, respectively. In particular, we verified that the PoS and the PoA are 4/3. KW - Congestion Games KW - Game Theory KW - Adversary KW - Spieltheorie Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-19683 ER - TY - THES A1 - Ellinger, Simon T1 - On optimal error rates for strong approximation of stochastic differential equations with irregular drift coefficients N2 - In this dissertation we study strong approximation of stochastic differential equations (SDEs) with irregular drift coefficients at the final time point or globally in time by methods that use only finitely many evaluations of the driving Brownian motion. We show the optimality of well-known methods, such as the Euler-Maruyama scheme or a transformed Milstein scheme, for classes of piecewise Lipschitz continuous, Hölder continuous and Sobolev regular drift coefficients. To do this, we derive the optimal error rates for the different classes of irregular drift coefficients. Furthermore, we show that the solution of an SDE with piecewise Hölder continuous drift coefficient has a regular local density, which is used in the proofs of the lower bounds. KW - Complexity KW - Error rates KW - Stochastic differential equations KW - Non-Lipschitz drift coefficient KW - Strong approximation KW - Lower error bounds Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-19634 ER - TY - THES A1 - Kling, Julia T1 - Social Networking Sites as Intermediaries of Authoritarian State Propaganda: How Facebook and VK Disseminated Predominantly Kremlin-Friendly Political Content Before and During Russia’s Full-Scale Invasion of Ukraine N2 - Previous research on Russia’s use of social networking sites to influence foreign audiences has primarily focused on US-based platforms, such as Twitter and Facebook, the activities of Russia’s “troll farms”, as well as Russia’s foreign broadcasters, RT and Sputnik, and their audiences. By contrast, little research has examined the global reach of Russia’s state-aligned domestic news content, specifically on US- and Russia-based social networking sites that significantly differ in the level of the Kremlin’s control over information flows, and how the activities of novel Russian disinformation production organizations support this reach. In my dissertation, I addressed these gaps in the extant research literature in the fields of political communication, social media, and Russia studies in four distinct research papers focusing on the reach of and engagement with Russian-speaking political content, including Russia’s domestic news content, and the activities of ANO Dialog, Russia’s novel disinformation production organization with close links to the Russian government, on US-based Facebook and Russia-based VK. To do so, I used innovative qualitative, quantitative, and computational research methods to create knowledge on Russia’s informational influence on the two platforms before and after the start of Russia’s full-scale invasion of Ukraine in February 2022. The findings highlight that, despite differing levels of Kremlin control, both of the social networking sites studied functioned as conduits for the dissemination of Russian-speaking, predominantly Kremlin-friendly political content, including state-aligned domestic news. This content reached audiences both within Russia and abroad in the lead-up to and during the full-scale war in Ukraine. While VK primarily served Russia’s users, Facebook disseminated Russia’s state-aligned news mostly to audiences outside Russia, particularly in former Soviet countries, in the lead-up to the invasion. During the war, Facebook continued to host critical perspectives on Russia’s war crimes, in contrast to VK, where such content was blocked. However, Facebook was banned in Russia in March 2022, limiting domestic access to dissenting views. With the war ongoing as of May 2025 and organizations such as ANO Dialog intensifying their efforts to influence both domestic and foreign audiences on platforms such as VK and Facebook, it is likely that Russia will further strengthen its information control. KW - social networking site KW - Russia KW - propaganda KW - platform governance Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-19601 ER - TY - THES A1 - Prummer, Michael T1 - Asset Tokenization and Authentication in the Industrial Metaverse N2 - The Industrial Revolution is a crucial development step in human history that started three centuries ago and is still ongoing. It continually influences and shapes the globalized world. Today, industries account for 20% of carbon dioxide emissions worldwide and require more than a third of global energy consumption. Current problems, such as climate change, increasing waste, and pollution, require simultaneous optimization across all industrial domains, infrastructure, and systems as they depend on each other. The global industry faces the immense challenges of providing for a surging world population expected to peak in the mid-2080s with 10.4 billion people, as reported by the United Nations. Hence, industries are expected to become less resource-intensive, sustainable, and more resilient to disrupted supply chains while producing for a growing population for the next decades. The Fourth Industrial Revolution, or Industry 4.0 (I4.0), started around 2010 and is still an ongoing transformation of industrial processes towards digitalization, creating smart factories referring to the digital data integration of the entire manufacturing cycle. I4.0 is incredibly information-intensive and requires immense data to simulate and predict essential operations based on a digital shadow of the factory, a so-called digital twin. The Metaverse is considered a digitalization megatrend merging digital and physical worlds, creating immersive experiences and new opportunities for interaction and innovation across various sectors and industries. The vision of the Metaverse promotes interconnected and interoperable real-time 3D virtual worlds that can be frictionlessly traversed while sustaining ownership of one's assets under a self-sovereign identity in a decentralized environment without platform lock-ins to a specific ecosystem. Therefore, the Metaverse creates an immersive parallel reality with collective virtually shared spaces for entertainment, social interactions, education, and a new working environment. The Industrial Metaverse synthesizes Metaverse concepts with current industrial automation, such as I4.0, to deepen the digital-physical convergence by interconnecting internal and external systems to enable decision-making and predictions based on significantly broader knowledge. An Industrial Metaverse factory is entirely mirrored to integrate digital twins of all types of equipment, assets, and other entities that can communicate vertically and horizontally, as well as the knowledge about relevant external systems and industrial core sectors. Through the comprehensive data integration of the Industrial Metaverse, AI-driven applications can predict future events, reducing system and hardware failures. Furthermore, the interconnected virtual environments create a meta-ecosystem for global collaboration, providing spaces for solving complex problems such as engineering and product design tasks, simulation of product twins, and reduced development time and costs. The connected industrial ecosystems create a token-based digital economy for exchanging data, assets, and services cross-metaverse connecting isolated data silos. Sharing digital twin resources and services with other systems enables new innovative applications and growing ecosystems. The theoretical part of this thesis defines the essential characteristics and key technologies of the Industrial Metaverse to derive a reference architecture for a decentralized system of systems, outlining the fundamental Industrial Metaverse building blocks. Interoperable data exchange, access management, and system communication are critical challenges. Especially interoperability of assets such as 3D files that come in different formats and identities must be ensured to move between virtual environments. The unique fusion of technologies leverages interconnected digital twins in the context of immersion, interaction, and collaboration for secure, autonomous-governed, decentralized industrial applications. Hence, the Industrial Metaverse requires the possibility of exchanging assets, products, and services across all systems in a secure manner. Distributed ledger technology enables tamper-proof transactions of assets and value in a decentralized token economy. Therefore, we investigate the feasibility of current tokenization methods for industrial assets, in particular, Printed Circuit Board (PCB) designs and 3D models. We contribute methods to create unique fingerprints of PCB designs to enable their exchange in the token economy. We investigate how to bind files in different formats and quality representations to the same token. A robust multi-file binding based on the copper layers of a PCB design was achieved by calculating an adaptive perceptual hash of all files. The adaptive perceptual hash was evaluated against numerous tamperings of the routing layout of a PCB, showing decent resistance to layout changes. The resulting adaptive perceptual hash can be used as an additional identification attribute in a tokenized asset. Furthermore, assets must be authenticatable and verifiable by marketplaces, manufacturers, and other participants to create trust in a decentralized environment. While assets can be tampered with to manipulate, for example, cryptographic hashes that link the file to the token, perceptual hashes can compute a perceived or functional similarity of two objects instead of the plain file integrity. Without the possibility of verifying and protecting intellectual property, mass adoption of the Metaverse and Industrial Metaverse is unlikely. Therefore, we contribute to detecting tampering attacks on 3D models by introducing a 3D perceptual hash that is robust to a set of mesh manipulations, enabling the trusted exchange and authentication of 3D data in the Metaverse. KW - 3D Perceptual hash KW - Industrial Metaverse Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-19566 ER - TY - THES A1 - Danner, Julian T1 - SAT Solving Using XOR-OR-AND Normal Forms and Cryptographic Fault Attacks N2 - The Boolean satisfiability problem (SAT) lies at the core of computational logic and has found many applications in verification, cryptography, and artificial intelligence. While conflict-driven SAT solvers (CDCL) excel on large industrial instances, they struggle with XOR-rich instances arising frequently in cryptanalysis, due to the inefficiency of CNF encodings of linear constraints. Conversely, algebraic approaches can work with linear XOR constraints naturally but fail to scale to relevant sizes. Bridging these complementary paradigms with a focus on cryptographic problems is at the heart of this thesis. On one hand, this dissertation advances SAT solving by introducing the XOR-OR-AND normal form (XNF) as a generalization of the conjunctive normal form (CNF), where literals are replaced by XOR chains of literals. This allows for a native representation of XOR constraints. We generalize the CDCL architecture to the richer language of XNFs. The underlying reasoning based on the proof system SRES which is shown to be exponentially stronger than classical resolution. An implementation demonstrates competitive performance and often surpasses state-of-the-art algebraic and logic solvers on random and cryptographic benchmarks. Furthermore, we prove that every XNF formula can be converted in polynomial time to a formula in 2-XNF, enabling a graph-based approach similar to 2-SAT. Building on this, we propose advanced in- and pre-processing techniques, and construct a simple DPLL-based solving framework. Our implementation, 2-Xornado, outperforms modern algebraic and logic solving approaches on many random and some structured cryptographic problems. On the other hand, we apply combined algebraic and logical techniques to cryptanalysis of stream ciphers. We introduce a formal guess-and-determine (GD) framework using a logical abstraction of the information flow in the internal state. From an algebraic point of view, we can then find optimal GD attacks utilizing a Gröbner basis. As a case study, we apply this method to aid in the construction of novel fault attacks on the ciphers KCipher-2 and Enocoro-128v2. Using ad hoc methods combining algebraic and logical approaches, we show that both ciphers are vulnerable to active side-channel attacks under rather weak fault models. Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-19171 ER - TY - THES A1 - Hagen, Pamina T1 - The 2008 Beijing Olympic Games as a City and Nation Branding Tool: An Interdisciplinary Analysis of the Image of International Opinion Leaders N2 - This dissertation examines the 2008 Beijing Olympic Games as a tool of city and nation branding, analyzing their role within China's broader soft power strategy and their impact on international perceptions of Beijing and China. Drawing from urban geography, political geography, international relations, and marketing theory, the study explores how mega-events contribute to the construction of national identity and global image. Using a mixed-methods approach, the research combines qualitative interviews with 16 international diplomats in Beijing and an online survey of 40 foreign journalists who lived and worked in China during the Olympiad. The analysis focuses on two dimensions of image: the city of Beijing and the nation of China. The findings indicate that the 2008 Summer Olympic Games did not fundamentally alter China's international image. While the event successfully projected an image of modernization, efficiency, and confidence, pre-existing concerns about political control and human rights persisted. For Beijing, the Olympics enhanced its visibility as a global city but also highlighted tensions between its traditional identity and its modern aspirations. The media's framing played a decisive role in shaping these perceptions. Overall, the study concludes that the Beijing Olympics functioned as a significant yet limited instrument of soft power. They reinforced China's global presence and urban development goals but fell short of transforming its international reputation. The research contributes to understanding how mega-events operate as strategic tools of geopolitical communication and branding in the context of globalization. KW - Beijing 2008 Summer Olympic Games KW - Nation Branding KW - City Branding KW - International Image KW - Public Diplomacy Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-19052 ER - TY - THES A1 - Pirwitz, Anne T1 - Migrationsfilme als ‚kritische Heimatfilme‘? BT - eine interdisziplinäre Untersuchung semantischer Räume und Chronotopoi der Migration im neuen rumänischen Film (1996–2022) N2 - Seit dem Zusammenbruch des Kommunismus ist die Anzahl im Ausland arbeitender Rumän*innen stark angestiegen. Inzwischen leben fast 20 % der Bevölkerung jenseits der Landesgrenzen. Transnationale Familien­strukturen mit in Rumänien zurückgelassenen Kindern oder Eltern und pluri-lokale Lebensweisen der Migrant*innen sind in kürzester Zeit zu einem alltäglichen Phänomen der rumänischen Gesellschaft geworden. Die Auswirkungen dieser Migration sind von gesamtgesellschaftlicher Relevanz und finden daher immer wieder Eingang in Literatur, Musik und Film. Diese Medien werden dabei von realen Ereignissen inspiriert, greifen aktuelle Diskurse auf und konstruieren eigene fiktionale Wirklichkeiten. Dabei vermitteln sie bestimmte Weltbilder und bieten verschiedene Sichtweisen auf die von ihnen verhandelten Themen an. Zwischen dem Ende der kommunistischen Diktatur 1989 und 2022 entstanden 52 rumänische fiktionale Kurz- und Spielfilme, die explizit Migration ins Zentrum ihrer erzählten Geschichten stellen. Der vorliegende Band untersucht, auf welche Weise die rumänische Arbeitsmigration im postkommunistischen Film verarbeitet wird, welches Bild der rumänischen Heimat und des ‚Westens‘ vermittelt wird, wie diese Räume durch filmische Mittel ästhetisch konstruiert werden und ob es sich bei diesen Werken um eine neue Form des ‚kritischen Heimatfilms‘ handelt. KW - Rumänien KW - Film KW - Migration Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:101:1-2409191636377.506847991255 PB - Akademische Verlagsgemeinschaft München CY - München ER - TY - THES A1 - Fellicious, Christofer T1 - Bridging the gap: Applying machine learning techniques in digital forensics N2 - With the increasing adoption of virtualization technologies across various industries, virtual machines (VMs) offer cost-effective solutions for obtaining computing power without the burden of initial investment or ongoing maintenance. However, the widespread use of VMs also increases the risk of malicious actors attempting to gain unauthorized access due to the possibility of accessing the VMs via standard internet protocols. Virtual Machine Introspection (VMI) and Forensic Memory Analysis (FMA) are two key cybersecurity methods for addressing these threats. While FMA leverages digital forensic techniques to extract and analyse information from system memory to explain security incidents, VMI typically works with live systems, analysing running processes to detect real-time threats. Both approaches face a significant challenge known as the ”semantic gap,” which arises from the need to infer high-level system information from low-level data such as physical memory and CPU registers. This dissertation explores using machine learning to bridge the semantic gap in FMA and VMI applications. The research uses OpenSSH process heap dumps as a use-case to extract high-level structures, such as OpenSSH encryption keys, from raw process memory dumps. The study employs various techniques to isolate relevant memory sections, from basic memory chunking and entropy analysis to more advanced methods utilizing pointers and malloc headers. During this research study, we also identified the need for a foundation model in memory forensics. Foundation models are general purpose models trained on large amounts of data and users can later use these models to perform different tasks by finetuning the model. This research also addresses the challenge of detecting malware by analysing system-level API calls and employing custom feature engineering techniques. Given that the threat landscape is constantly evolving, we also investigate concept drift — a phenomenon where input data distribution changes affect predictive models’ performance. To mitigate the degradation in performance due to concept drift, we introduce a concept drift detection algorithm complemented by a custom sampling method that optimizes training data selection. This approach reduces the training dataset size by one-third, enhancing the efficiency of model training while maintaining high performance. KW - semantic gap KW - virtual machine introspection KW - forensic memory analysis Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-18473 ER - TY - THES A1 - Zerhoudi, Saber T1 - User Simulation in Interactive Information Retrieval : methods and frameworks for simulating complex search behavior N2 - Modern information retrieval (IR) systems, including web search engines and digital libraries, face challenges in simulating realistic user search behavior. Evolving interaction patterns and the integration of AI-powered interfaces make these challenges even harder. Traditional evaluation methods struggle to capture the dynamic nature of user interactions, particularly in complex search tasks and multi-stage information-seeking processes. User simulation offers a promising solution, providing a controlled environment for experimentation and allowing customization to model specific user behaviors and task contexts. This research develops advanced techniques for user simulation in IR, creating more realistic and dynamic models than were previously possible. Key contributions include new methods for representing query reformulation, modeling how information needs change, and measuring the impact of different search environments on simulated user behavior. Specifically, this work introduces contextual Markov models, cognitive state models, and embedding space alignment techniques to accurately represent interactive search behavior. Beyond model development, new evaluation methods and metrics are proposed for assessing the quality of simulated search sessions. These include statistical comparisons of session characteristics and classification-based approaches to distinguish between simulated and real user behavior. Additionally, this work leverages emerging technologies, such as large language models (LLMs) and retrieval-augmented generation, to improve the realism of user search behavior simulation. The practical outcome of this research is a modular and extensible simulation framework. This framework incorporates advanced techniques like user type-specific Markov models, advanced query generation using LLMs, and conversational user models. KW - Information retrieval KW - user simulation KW - evaluation KW - simulation framework Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-18936 N1 - Die Leerseiten iii, iv, vi(i), x, xi sind nicht Teil des Dokuments. ER - TY - THES A1 - Klement, Felix T1 - Strengthening Security Foundations in Next-G Wireless Telecommunication Systems N2 - Digital transformation fundamentally impacts our everyday lives and creates significant efficiency gains in the economy. At the same time, however, it is also increasing the complexity of wireless networks, particularly in the case of the sixth generation (6G) mobile communications standard. The use of different technologies in these networks poses an increasing challenge and increases the risk of security threats and vulnerabilities. Wireless communication networks are particularly vulnerable to cyber attacks as they are an integral part of critical infrastructures. Robust methods must, therefore, be developed to overcome these challenges. Consequently, this dissertation is focused on the security fundamentals of next-generation (Next-G) wireless telecommunication systems. It addresses the security challenges resulting from emerging and innovative concepts within these systems. We use case studies for in-depth investigation and analysis, with a particular focus on the Open Radio Access Network (O-RAN) approach. The aim of this concept is to enable open and interoperable network architectures, in contrast to traditional RAN systems, which are often proprietary and manufacturer-specific. In this respect, it is essential to address fundamental questions, like the efficient assessment of the threat landscape, the impact of potential attacks, and the mechanisms that can be used to ensure security at the system level. Initially, an empirical approach is developed to analyze threats within telecommunications systems, such as the O-RAN. The procedure we have developed enables automated, programmatically executable vulnerability management. This methodology is further enhanced by integrating Natural Language Processing (NLP), leading to the creation of a fully automated, iteratively executable framework for security analysis within O-RANs. The framework allows for the direct incorporation of our methods into the deployment process, facilitating rapid and efficient comparison of all components against the latest security vulnerabilities. The current approach of fully deploying all components in virtualized environments, such as cloud infrastructures, introduces new and unprecedented security challenges. In response, we investigate current deployment strategies within the O-RAN infrastructure and establish best practices to mitigate these security issues. In the course of the dissertation, we identify security vulnerabilities in wireless telecommunication systems by executing different attack scenarios. We present a detailed procedure for carrying out the attacks as well as effective methodologies for detecting or avoiding the vulnerabilities we have identified. In the first study, we analyze the security of a key component, the Near-Real-Time RAN Intelligent Controller (Near-RT RIC), within O-RAN. We show how a subscription Denial of Service (DoS) attack can render current implementations of this component unusable. In the second analysis, we investigate the robustness of new standards in wireless networks against jamming attacks using the open-source connectivity standard Matter. The final section of this dissertation explores innovative security research approaches for enhancing the system security of future communication systems. Initially, a novel concept is introduced that facilitates the comprehensive and efficient management and assurance of security within O-RAN systems through the use of Security Platforms (SPs). Furthermore, two developed methodologies for this approach are presented: firstly, a method for programmatically analyzing eXtended Applications (xApps) to identify vulnerabilities, and secondly, an approach for conducting comparative assessments of these vulnerabilities. Additionally, a strategy is proposed to ensure that only secure xApps, such as those that have been pre-tested, are deployed for use in Near-RT RIC. Overall, this dissertation makes an important contribution to the research of security principles for next-generation wireless telecommunication systems. With the help of our approaches for a better and more concrete assessment of threats in such networks, we directly contribute to a clearer and better manageable picture of the vulnerability landscape. Our two publications on vulnerability research also provide valuable insights for securing future problems in the respective areas. In summary, with our approaches to system security, with which security principles can be implemented and integrated into modern system approaches such as O-RAN, we contribute to ensuring a secure transition to 6G. KW - Security KW - Next-G KW - 6G KW - Open RAN Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-18669 ER - TY - THES A1 - Lehner, Constanze T1 - Three Essays on the Interpretability of Random Forests: Methods, Insights, and Innovations N2 - This thesis examines the interpretability of random forests in three essays, focusing on the discussion of established methods, the presentation of new insights and the provision of innovations. The research aims to bridge the gap between traditional statistical methods and random forests, a data-driven machine learning algorithm, by investigating the ability of random forests to adequately model theoretical concepts compared to parametric methods and developing a new approach for statistical hypothesis testing. The results have implications for various areas of research in which interpretability is crucial for applications. The next three paragraphs summarize the studies presented in this thesis. The ability of random forests to automatically model interactions without the need for pre-specification is mentioned prominently in many articles and book chapters. Promising empirical results from early work on random forests have substantiated this property, which has led to an increasing popularity of using random forests in the presence of interactions as an alternative to traditional parametric methods. This study reviews the literature of the last 20 years on random forests and interactions. We explore the discussion from its origin in the decision tree literature to early applications of random forests and current research. We identify key research areas and illustrate random forest applications to highlight similarities and differences between disciplines. We also provide a critical examination of the arguments in favor of random forests being able to model interactions automatically. Since the term ``interaction'' is associated with different theoretical concepts, we explain and illustrate the definition of interaction for each research area. The variable importance of random forests is an easy-to-understand metric that intends to make the predictions of random forests more transparent by assessing the contribution of each covariate to the prediction of the response. However, due to its data-driven nature, the variable importance of random forests may over- or underestimate the importance of a covariate, so that the role of the covariate in the underlying data generating process is not correctly reflected. We present an example of underestimation of importance in the case of interacting covariates. We define an interaction in terms of effect modification, which assumes that the effect of one covariate on the response is modified by values of another covariate. We show that the variable importance of random forests is influenced by the interaction form and the measurement scale of the interacting covariates, so that in some cases the importance of one or even both interacting covariates is underestimated. We illustrate how the split decisions of random forests affect the variable importance values of the interacting covariates. Variable importance estimates the contribution of a covariate to the performance of a predictive algorithm. Defined as the increase in loss after the random permutation of a covariate, permutation variable importance makes it possible to rank the covariates by importance, but in the absence of a threshold, the distinction between important and unimportant covariates is inherently arbitrary. We show that recent approaches of non-parametric permutation tests for variable importance exceed their nominal type I error level for mutually dependent covariates. As an alternative we propose a combined variable importance estimate on a sequence of permutations and employ a computationally more efficient bootstrap to derive the respective null distribution and $p$-values. The proposed test can be applied to any predictive algorithm and is remarkably fast. We investigate the control of type I error level and the power of the proposed variable importance test in simulation studies. Even for mutually dependent covariates, our test is conservative and provides power comparable to recent advances in non-parametric permutation tests of variable importance. This study was conducted in collaboration with Matthias Wild. KW - Random Forests KW - Interactions KW - Variable Importance KW - Permutation Test Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-18608 ER - TY - THES A1 - Dietrich, Philip T1 - Moralische Entscheidung in virtuellen Handlungswelten. Verantwortliche Vermittlung gesellschaftlich relevanter Themen im Videospiel N2 - Die vorliegende Arbeit untersucht die verantwortliche Vermittlung gesellschaftlich relevanter Themen im Medium des digitalen Spiels. Als generationenübergreifendes und interaktives Medium eröffnen digitale Spiele durch die Verknüpfung von Narration und Interaktion die Möglichkeit, alternative Perspektiven einzunehmen und neue Rollen zu erproben. Auf Basis von vier Teilstudien wird der Frage nachgegangen, wie gesellschaftlich bedeutsame Inhalte in digitalen Spielen verantwortungsvoll gestaltet und vermittelt werden können. Die erste Teilstudie identifiziert zentrale Nutzungsmotive und weist Spielende als potenzielle moralische Handlungsträger (Moral Agents) aus. Sie zeigt auf, dass moralische Dilemmata, die innerhalb virtueller Spielwelten erfahren werden, Relevanz für moralische Urteilsbildungsprozesse in der realen Welt entfalten können. Die zweite Teilstudie knüpft an diese Erkenntnisse an und untersucht anhand von Expert:inneninterviews das Potenzial digitaler Spiele für eine digitale Erinnerungskultur. Die dritte Teilstudie entwickelt ein Modell für die gelingende Vermittlung gesellschaftlich relevanter Themen im digitalen Spiel. Hierbei wird insbesondere die integrative Funktion von Narration und Interaktion als zentrales Gestaltungsprinzip herausgestellt. Die vierte Teilstudie erweitert dieses Modell um die Dimension der Ästhetik, die als konstitutives Element der Wirklichkeitswahrnehmung und Sinnkonstitution innerhalb virtueller Spielräume fungiert. Die Ergebnisse verdeutlichen, dass für eine verantwortungsvolle Vermittlung gesellschaftlich relevanter Inhalte im digitalen Spiel eine digitale Moral Agency erforderlich ist. Diese befähigt Spielende dazu, moralisch zu handeln und das eigene Handeln kritisch zu reflektieren. Die Verbindung von Narration und Interaktion erweist sich dabei als zentrales Mittel zur Initiierung von Perspektivwechseln, zur Übernahme fremder Rollen und zur Förderung reflexiver Prozesse. Ästhetisierungsprozesse innerhalb der Spielwelten tragen wesentlich dazu bei, diese kognitiven und affektiven Auseinandersetzungen anzustoßen und zu vertiefen. KW - Game Studies KW - Medienethik KW - Videospielforschung KW - Kommunikationswissenschaft KW - Digitales Lernen KW - Spielwissenschaft KW - Medien KW - E-Learning KW - Videospiel KW - Ethik Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-18481 ER - TY - THES A1 - Rutter, Eva T1 - Berufswahlmotivation Lehramt: Ein weltweit ähnliches Phänomen? Eine international vergleichende Studie N2 - Im Angesicht eines weltweiten Lehrkräftemangels (OECD, 2018b; UNESCO, 2023) wird in der empirischen Forschung der Berufswahlmotivation Lehramtsstudierender ein großer Stellenwert beigemessen (Butler, 2017). Es handelt sich beim Lehrkräftemangel aktuell um ein weltweites Phänomen, das weder nur Deutschland oder nur westliche Länder betrifft (UNESCO, 2023). In den letzten zwanzig Jahren haben sich einige theoretische Modelle zur Berufswahlmotivation spezifisch für das Lehramt etabliert, dazu zählen das FIT-Choice-Projekt (Richardson und Watt, 2007), Femola (Retelsdorf und Möller, 2012) und STeaM (Weiß und Kiel, 2013). In dieser Arbeit wird das FIT-Choice-Modell (Richardson und Watt, 2007) verwendet, um die Berufswahlmotive eines internationalen Samples Lehramtsstudierender zu zwei Zeitpunkten zu betrachten. Das Modell stellt mit seinen Bezugstheorien (Eccles und Wigfield, 2002; Ryan und Deci, 2000) sowohl die theoretische als auch die empirische Fundierung dieser Arbeit dar. Neben diesem werden Professionalisierungstheorien (vor allem der kompetenztheoretische Ansatz nach Baumert und Kunter, 2011a) und die Habitustheorie (Bourdieu, 1982) zur Interpretation der Ergebnisse herangezogen. Strukturmerkmale der einzelnen Länder ermöglichen ein kultursensitives Vorgehen. Zu zwei Zeitpunkten (Studienbeginn und Studienende) wurden an 5 Universitäten in Deutschland, Österreich, der Schweiz, Südafrika und Israel mit einem Skalenfragebogen insgesamt n= 1157 Studierende (Studienbeginn n= 835, Studienende n= 322) zu ihren Berufswahlmotiven und Einstellungen befragt. Diese wurden in Zusammenhang gebracht mit der Länderzugehörigkeit, ihrer sozialen Herkunft sowie ihren pädagogischen Vorerfahrungen. Zudem wurden im deutschen Sample zum Ende des Studiums offene Fragen ergänzt, um Begründungslinien für die Berufswahl in Erfahrung zu bringen. Mit dem spezifischen Sample wurde das Desiderat der Ländererweiterung um nicht- westliche Länder (Watt, Richardson und Smith, 2017) bearbeitet, ebenso mit den offenen Fragen das Desiderat nach der Verbindung von quantitativen und qualitativen Ansätzen (Watt und Richardson, 2015). Mit der Arbeit können die Hauptergebnisse der Forschung mit den FIT-Choice-Skalen bestätigt werden. Die Betrachtung von Subgruppen innerhalb der Länder gab einen Einblick zu Berufswahlmotiven marginalisierter Gruppen und den Grenzen von global anzuwen-denden (westlichen) Erhebungsinstrumenten. Die Arbeit leistet außerdem einen Beitrag zum Diskurs um den Einfluss von pädagogischen Vorerfahrungen in der Berufswahlmotivationsforschung, zudem werden Ergänzungen für den FIT-Choice-Fragebogen für die „Gen Z“ vorgeschlagen. KW - Berufswahlmotivation KW - internationaler Vergleich KW - FIT-Choice-Modell Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-18464 ER - TY - THES A1 - Poliakoff, Serge T1 - From Faking Online Content to Orchestrating Its Creation by Public Workers: Examining Russian Disinformation Production Organisations through Curriculum Vitae Analysis (2013-2024) N2 - This dissertation examines the evolution of Russian digital authoritarianism, focusing on its organisations that produce disinformation, the transition from the Internet Research Agency to the Patriot Media Group and the emergence of ANO Dialog. It shows how the Internet Research Agency operated as a sophisticated "troll farm" during the early stages of the Russo-Ukrainian war, with activities similar to those of a PR firm. The Patriot Media Group absorbed these activities, blurring the lines between media and disinformation and prioritising metrics-driven propaganda over journalistic professionalism. This dissertation identifies the organisation ANO Dialog as a new model, heavily integrated with state structures, combining digital surveillance, repression, and Soviet-style agitation adapted to the digital age. Using a novel methodology of career profile collection and analysis, my research illustrates the institutionalisation and regional expansion of disinformation tactics in Russian digital authoritarianism, highlighting its operational adaptability and evolving infrastructure. KW - disinformation KW - disinformation-for-hire KW - troll farm KW - troll factory KW - propaganda KW - propaganda organisations KW - disinfromation production organisations KW - CV analysis Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-16100 ER - TY - THES A1 - Springer, Simone Maria T1 - Lehramtsstudierende auf ihrem Weg der Professionalisierung BT - subjektive Vorstellungen von Professionalisierung aus der Sichtweise Studierender des Lehramts Grundschule an der Universität Passau mit unterschiedlichen Praktika - eine qualitative Studie N2 - Die vorliegende Studie untersucht subjektive Vorstellungen von Professionalisierung aus Sicht Studierender des Lehramts Grundschule an der Universität Passau im Rahmen unterschiedlicher Praktikumsformen: Pädagogisch-didaktisches Praktikum (PDP), Exercitium Paedagogicum (ExPaed) und Modellcurriculum (MC). Aus der Theorie heraus wurden zwei Hauptkategorien der Studie abgeleitet: Kategorie I - Inwiefern unterscheiden sich die subjektiven Sichtweisen Studierender unterschiedlicher Praktika (PDP, ExPead, MC) auf Professionalisierung? Und Kategorie II - Inwiefern unterscheidet sich die systematische Reflexion der individuellen Professionalisierung von Studierenden unterschiedlicher Praktika (PDP, ExPaed, MC)? Durch diese drei Gruppierungen ist es möglich, verschiedene Perspektiven zu berücksichtigen und Unterschiede herauszuarbeiten. Die leitfaden-gestützten ExpertInneninterviews (n = 27: 8 PDP, 10 ExPaed, 9 MC) wurden mit dem Programm f4 transkribiert und mit Hilfe der Datenanalyse-Software MAXQDA (2020/2022) inhaltsanalytisch nach Mayring (2015) ausgewertet. Ergebnisse der Studie zeigen Abweichungen der einzelnen Studierendengruppen bezüglich biografischer Ausgangslagen für Professionalisierung. StudentInnen der einzelnen Gruppierungen nehmen Professionalisierung im systemisch-strukturellen Rahmen in Form von Praktika anders war, zeigen Unterschiede im professionellen Selbstverständnis und in den subjektiven Einflussfaktoren für Professionalisierung. Auch in der systematischen Reflexion der eigenen Professionalisierung können Diskrepanzen eruiert werden. KW - Professionalisierungsforschung KW - Profigrafiemodell KW - Lehramtsstudium KW - Modellcurriculum Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-16120 ER - TY - THES A1 - Sawhney, Udit T1 - Incentivizing Sustainable Agriculture in Indonesia: Empirical Essays on the Role of Social Norms and Information Provision N2 - The Green Revolution (GR) was one of the most transformative events in modern agricultural history. It was characterized by the widespread adoption of high-yield crop varieties, synthetic fertilizers and pesticides, and advanced irrigation systems. By significantly increasing agricultural productivity, the GR responded to global food shortages and hence played a crucial role in educing hunger, particularly in developing economies. However, while the GR alleviated food insecurity and stimulated economic development, it also brought about several unintended consequences like environmental degradation, as well as, widening socio-economic inequalities. Farmers, particularly in South and Southeast Asia, indulged heavily in fertilizer overapplication, which led to declining soil health and long-term sustainability concerns. Recognizing these challenges, the United Nations’ Sustainable Development Goals (SDGs) placed significant emphasis on sustainable agriculture, particularly through SDG - 2, which seeks to end hunger and promote sustainable food production. In line with these efforts, there has been a growing movement by several countries and international organizations towards promoting sustainable agricultural practices that balances agricultural productivity with environmental conservation. This dissertation contributes to this discourse on sustainable agriculture by examining key socio-economic factors that influence the adoption of sustainable farming practices among smallholder farmers in Indonesia. Indonesia’s agricultural landscape, particularly its rice farming sector, has been shaped by decades of Green Revolution policies, with Java serving as a focal point for agricultural intensification. While these policies led to impressive yield increases and national self-sufficiency in rice production by the mid-1980s, they also resulted in several environmental and economic challenges, including excessive use of chemical fertilizers, soil nutrient imbalances, and long-term land degradation. In response, the Indonesian government introduced several sustainability-focused policies, including Integrated Pest Management (IPM), Farmer Field Schools (FFS), and the “Go Organic 2010” initiative. Despite these efforts, adoption of sustainable farming practices remains limited, raising critical questions about the barriers that prevent smallholder farmers from transitioning away from intensive chemical input use. The dissertation focuses on three interrelated research questions that explore the role of social networks, information provision, and economic incentives in shaping farmers’ decisions regarding sustainable agriculture. These questions are addressed through a combination of mixed-methods research and randomized controlled trials (RCTs) conducted in Java, specifically in the regions of Yogyakarta and Tasikmalaya. The first research question investigates whether and how social networks and peer effects influence farmers’ input decisions, particularly regarding fertilizer application. This study builds on existing literature on social networks in agriculture and examines the extent to which perceptions of farming norms - the visible greenness levels of rice plants - affect farmers’ willingness to adopt more sustainable practices. Using a mixed-methods approach, including survey experiments and social network analysis, the study finds that personal opinions about the importance of plant greenness significantly influence farmers’ input decisions. However, second-order perceptions - farmers’ beliefs about how others in their farming network think about their farming choices - do not play a decisive role in shaping actual adoption behaviour. This finding contrasts with previous studies that emphasize the role of social pressure in agricultural decision-making, suggesting that while social learning plays an important role, it does not always operate through peer-effect mechanisms. The results highlight the complexity of social influences in agricultural adoption decisions and the need for more nuanced approaches to integrating behavioural insights into policy interventions. The second research question investigates the role of information provision, particularly about site-specific nutrition, in promoting sustainable soil management practices among smallholder farmers. A large-scale RCT was conducted in 69 villages to assess whether targeted agricultural extension trainings, along with soil testing services, can drive farmers’ adoption of sustainable soil management practices. Villages were randomly assigned to - a treatment group (T1) that received one-day training on soil health management, a second treatment group that received both training and soil tests (T2), and a control group. The study reveals that while training sessions increased awareness and adoption of simple sustainable practices - such as the use of the Leaf Colour Chart (LCC) - there was limited impact on broader behavioural changes, such as the adoption of organic fertilizers or precision fertilizer application. However, the additional provision of soil testing led to measurable reductions in nitrogen fertilizer use while simultaneously increasing yields, demonstrating the potential for personalized, site-specific soil nutrient recommendations to improve both economic and environmental outcomes. A cost-benefit analysis reveals that additional day of soil testing training resulted in an average economic gain of USD 15.71 per farmer and also reduced CO2 emissions by approximately 2 kg per farmer. These findings highlight the potential for scalable, information-based interventions as well as the need for sustained follow-up support to reinforce behavioural changes among farmers. The third research question explores farmers’ willingness to pay (WTP) for soil testing services and compares two different market-dissemination models - a private service model (where farmers purchase individual soil tests) and a collective (club good) model (where farmer groups collectively purchase a soil testing kit). Using an incentive-compatible auction based on the Becker- eGroot-Marschak (BDM) method, the study finds that farmers are willing to pay approximately 43% of the actual cost of soil tests, indicating strong demand for personalized soil fertility information. Furthermore, there is no significant difference in WTP between the private and club good models, suggesting minimal free-riding behaviour within farmer groups. The qualitative data further suggests that group-based models foster a sense of joint responsibility and knowledge-sharing, making them a viable alternative to individual service provision. A deeper analysis reveals that while private service models are more effective in low-subsidy environments, club good models become preferable when subsidies are higher, offering valuable insights into cost-sharing mechanisms for agricultural policy design. Taken together, the findings of this dissertation have important implications for policymakers seeking to promote sustainable agricultural practices in developing economies. First, the dissertation highlights the nuanced role of social networks in shaping farmers’ adoption decisions, suggesting that interventions targeting social learning should account for the complexity of social networks and peer influence mechanisms. Second, the dissertation underscores the importance of integrating soil testing and personalized information into agricultural extension programs, as site-specific soil nutrient recommendations can enhance both farming productivity as well as environmental sustainability. Third, the study provides empirical evidence on cost-effective ways to scale up soil testing services, demonstrating that well- esigned market-dissemination strategies can increase farmers’ access to sustainability-enhancing technologies while maintaining financial viability. Beyond its immediate policy relevance, this dissertation also contributes to broader theoretical debates in development economics, agricultural economics, and environmental sustainability. By integrating experimental research methods, the dissertation advances understanding of how farmers make technology adoption decisions under conditions of uncertainty and social influence. Additionally, the study provides a methodological contribution by demonstrating the effectiveness of combining RCTs with qualitative approaches to capture the complexities of real-world decision-making. Despite its contributions, the dissertation also identifies several avenues for future research. One key limitation is that the analysis focuses primarily on short - to medium-term impacts, leaving open questions about the long-term sustainability of behaviour change. Future studies should explore whether farmers continue to adopt sustainable practices once external support is removed. Additionally, further research is needed to examine the role of digital agricultural advisory services, mobile-based soil testing platforms, and remote sensing technologies in complementing traditional extension services. Finally, more work is needed to explore the broader policy ecosystem surrounding agricultural sustainability, including the role of subsidies, market linkages, and certification schemes in incentivizing long-term adoption. In conclusion, this dissertation provides a comprehensive analysis of the social, informational, and economic factors that drive sustainable agricultural transitions in Indonesia. By offering evidence-based insights into the design of more effective extension programs, market dissemination strategies, and cost- haring mechanisms, it contributes to ongoing efforts to create more resilient and environmentally sustainable food systems. The findings are not only relevant for Indonesia but also offer valuable lessons for other developing economies that are facing the challenge of balancing agricultural productivity with sustainability. KW - Economics KW - Development Economics KW - Agricultural Economics KW - Randomized Controlled Trials Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-16095 ER - TY - THES A1 - Patil, Amit Dilip T1 - Towards Resilient Protection of Interconnected ICT and Power Systems N2 - Due to the increasing number of distributed renewable energy sources, the distribution grid faces new operational challenges. Information and Communication Technology (ICT) systems can resolve these challenges through grid services that use automation, monitoring, and real-time decision-making, helping maintain an acceptable operational state of the distribution grid. However, the reliance of the power system on the ICT system and vice versa in the so-called smart grid creates interdependencies between the systems, which present new pathways for failure propagation. Therefore, these interdependencies require special attention to ensure stable system operation in the face of these challenges. However, these interdependencies have not been studied extensively in the literature. This thesis investigates approaches to model, quantify and improve the performance and resilience of the smart grid infrastructure. The interdependencies are formalised as interconnectors, entities that exist in all the connected systems. These interconnectors consist of components from both systems, where the components are modelled as state variables. These state variables determine the interconnector state and the service delivered. Failures represented by a change in state variables may impact the state. These state variables are deployed in a discrete event simulation framework to determine the system performance over time. The simulation result is represented on a two-dimensional state-space diagram depicting the operational state and service delivered. This allows for the resilience analysis of a system under various scenarios. The interdependencies are further investigated by exploring the role of ICT-based grid services in power grids, whose state is defined based on ICT properties, such as latency. These properties are formalised using property graphs. The ICT properties obtained from these graphs are used to parameterise a finite state automaton model of a grid service states, which are then used to determine the state of the entire smart grid. Case studies of state estimation and adaptive protection highlight the application of this approach. The use of ICT in state estimation allows the distinction of a global and perceived view of the power grid, which influences decision-making in the face of challenges. This thesis further investigates the protection system in detail. The overcurrent protection system is adversely impacted by distributed generation, resulting in undesired phenomena such as protection blinding. This thesis characterises this phenomenon by proposing two indices that capture the protection trip time under the influence of distributed generation. These indices consider the electrical distance between faults, protection and distributed generation. These indices and simulation results identify the worst-impacted locations in the power grid in terms of protection trip time. They also identify fault locations under given assumptions that do not cause protection blinding. ICT can resolve protection blinding by adapting the sensitivity of protection relays. However, since faults must be cleared in a short timeframe, communication delays may adversely impact the fault-clearing time. A discrete event simulation model is proposed to study protection performance in distribution grids. Investigation of time distribution assumptions reveals that the lognormal distribution accurately captures the circuit breaker trip time. The impact of the distributed generation and communication delay on the protection system is determined by measuring fault-clearing times using discrete event simulation. Results show that for the system studied, protection blinding is critical for low impedance faults in grids with high fault levels, while high impedance faults are critical in grids with low fault levels. Moreover, sympathetic tripping is seen at increased distribution grid fault levels and fault impedance. Furthermore, while communication systems reduce fault clearing times, increased delays harm protection systems. Finally, communication system components like sensors can fail, preventing fault detection. This thesis proposes a genetic algorithm-based approach to optimally place redundant sensors, minimising protection blinding under communication uncertainty within a redundancy budget. Results demonstrate the algorithm's effectiveness in optimising redundant sensor locations, reducing system costs, and improving fault tolerance. For the system and scenarios investigated, an average of 60% redundant sensors are relocated, reducing the average protection trip time by 36.65% compared to a baseline approach that does not consider communication uncertainty. This encourages incorporating communication component failure considerations in power system planning. KW - information and communication technology KW - smart grid KW - discrete event simulation KW - property graphs KW - protection blinding KW - genetic algorithm Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-16088 ER - TY - THES A1 - Luick, Karen T1 - Reisebegegnungen in Marokko BT - multiperspektivische Betrachtungen zeitgenössischer deutschsprachiger und französischer Reiseberichte N2 - Die Arbeit beleuchtet Marokko als Reiseziel für Individualreisende aus landeskundlicher und tourismusgeographischer Perspektive. Darauf aufbauend erfolgt eine Analyse der touristischen Praxis anhand von Begegnungsrepräsentationen in verschiedenen medialen Formaten von Reiseberichten, mit Fokus auf interkulturelle Begegnungen. Diese zeigen sich in ihrer Darstellung als vielfältig und differenziert. Durch eine multiperspektivische Betrachtung des Phänomens werden komplexe Spielarten interkultureller Begegnung in Bezug auf Darstellung, Pragmatik und Funktionalität herausgearbeitet. Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-16024 ER - TY - THES A1 - Julka, Sahib T1 - Towards Data Efficiency and Controllable Representations for Deep Learning in Resource-Constrained Domains N2 - The deployment of artificial intelligence (AI) in specialised domains such as planetary science and healthcare, as well as in low-resource NLP settings, faces two fundamental challenges: label scarcity and data scarcity. Label scarcity stems from the high cost of expert annotation, the scarcity of domain experts, and the infeasibility of crowdsourcing, particularly in complex tasks requiring specialised knowledge. In parallel, data scarcity stems from the inherent difficulty of acquiring sufficient raw data, whether due to limited observational opportunities, environmental and technical barriers, or stringent privacy constraints. Together, these limitations impede the broader adoption of AI in these fields. Many existing approaches to label efficiency, such as active learning, rely on problem-specific heuristics and often, as a design choice, employ naive uncertainty estimations—typically at the instance level. However, such methods can lead to redundant or suboptimal sample selection by ignoring structural data properties and failing to account for representational diversity. In practice, they often perform no better than random sampling. For data synthesis, generative models face their own set of challenges. Despite their promise for synthetic data generation, these models frequently lack mechanisms to disentangle generative factors at the representation level, limiting their controllability. Additionally, standardised evaluation metrics to assess the quality of disentanglement remain underdeveloped, limiting their practical utility. These limitations highlight the need for advancements in data-efficient machine learning and controllable generative modelling, focusing on domain-specific validity and rigorous evaluation. This thesis contributes to addressing these challenges by proposing tailored solutions in two key directions. First, for data-efficient learning, a deep active learning (DAL) framework is introduced to enhance label efficiency by prioritising the most informative samples for annotation. Unlike traditional per-sample approaches, this framework aggregates uncertainty across larger data segments—such as orbital intervals in planetary science—allowing it to capture contextual variations. This method reduces labelled data requirements by up to 90% in the case of boundary crossing detection at Mercury’s magnetosphere. To further improve sampling diversity, a GAN-based concept drift detection method is integrated into the DAL framework, leveraging uncertainty and diversity together to offer a sampling method that outperforms random sampling. Additionally, foundation models such as the Segment Anything Model (SAM) are employed for zero-shot annotation to generate high-quality pseudo-labels, which are subsequently used to train a domain-specific model via knowledge distillation. This approach significantly enhances data efficiency, reducing the need for annotated samples several times over in the tested scenario of image segmentation for geological mapping. Furthermore, large language models (LLMs) are explored as active annotators for linguistic tasks in low-resource languages, achieving near-baseline performance while reducing annotation costs by up to 40x. Second, the thesis investigates methods to induce controllability in generative models, enabling the production of high-fidelity, controllable synthetic data. Conditional generative adversarial networks (CGANs) and disentangled representation learning techniques (DRL) are explored, particularly in the context of pedestrian trajectory prediction in the mobility domain, where controlled synthesis of diverse motion patterns is critical. Additionally, the work examines existing metrics for evaluating disentanglement and identifies critical limitations in them. A novel metric, the Exclusivity Disentanglement Index (EDI), is proposed as an improved standardised measure. Based on the principle of exclusivity in factor-code relationships, this metric offers advantages over existing alternatives in terms of efficiency and robustness. By advancing data-efficient learning and controllable generation strategies, this thesis aims to bridge the gap between AI’s vast potential and its practical adoption in resource-constrained environments. These contributions pave the way for transformative applications in planetary science, healthcare, and beyond, where label and data scarcity have long been barriers to progress. KW - artificial intelligence KW - deep active learning KW - label scarcity KW - data scarcity Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-16030 ER - TY - THES A1 - Baak, Werner T1 - Advanced Ordered Weighted Averaging Methods in Robust Optimization N2 - In decision-making under uncertainty, robust optimization is a critical tool across various fields, providing solutions that perform effectively across a range of scenarios where precise probabilities are unavailable or unreliable. Traditional approaches, such as min-max and min-max regret, focus on minimizing the worst-case outcomes and worst-case regret, respectively, often resulting in highly conservative solutions. To address this limitation, this dissertation investigates the Ordered Weighted Averaging (OWA) operator, which offers a flexible framework for aggregating outcomes according to varying risk preferences, from risk-averse to risk-neutral, encompassing traditional robust approaches as special cases. This work is organized around three primary contributions that expand the application and understanding of OWA in robust optimization. The first contribution develops a preference elicitation framework for OWA weights, enabling decision-makers to derive weighting schemes based on observed historical decisions, thereby aligning aggregation strategies with specific risk attitudes. The second contribution introduces a novel variant of OWA for robust optimization, integrating OWA into a regret minimization framework to generalize both robust min-max and min-max regret approaches. This model is complemented by new complexity results, including insights into the inapproximability and approximability of OWA regret, providing stronger approximation bounds that asymptotically improve on previously established results for classic OWA models. These advancements position the OWA regret model as a powerful alternative to min-max regret, offering a more adaptable approach to risk-sensitive decision-making. The third contribution addresses interval uncertainty, extending the OWA framework to scenarios where outcomes are represented as bounded intervals instead of discrete points. This interval-based OWA model accommodates real-world decision-making needs, where scenario data are uncertain or costly to specify. By using Value-at-Risk (VaR) in our definition, we provide a natural way to handle continuous ranges of uncertainty while maintaining computational tractability for large-scale problems. Together, these contributions advance both the theoretical and practical applications of OWA in decision making, establishing OWA-based methods as versatile tools for addressing complex uncertainties across a variety of decision-making environments. KW - decision-making KW - uncertainty KW - risk Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-15879 ER - TY - THES A1 - Wilhelm, Sebastian T1 - Emergency Detection in Private Households Utilizing Existing Data Sources for Human Activity Event Recognition N2 - In an aging society, the need for efficient emergency detection systems in smart homes is becoming increasingly important. Over 30% of those aged 65 and older experience at least one fall per year, often resulting in the inability to rise without assistance, leading to ‘long lies’ lasting hours or even days. Systems for detecting such emergency events usually rely on wearable sensors or specific installations of ambient sensors, which can be intrusive and complex, hindering acceptance. This thesis proposes a novel approach that utilizes existing digital data sources within the residential infrastructure to detect human activities and identify potential emergencies. A survey identifies 44 potential data sources in private households for recognizing human activity. However, extracting activity information often requires complex preprocessing. In this thesis, methodologies are developed for three of these data sources to highlight practical applications: Smart Power Meters, Smart Water Meters, and Home Weather Stations. It is shown that detecting human activities using these sources is feasible in a practical environment, although accuracy and reliability vary. Notably, Smart Water Meters demonstrate high reliability, with a precision of 0.86 and a recall of 1.00, making them particularly suitable for emergency detection. Existing emergency detection methods are not designed to handle uncertain activity data. This thesis introduces a novel approach based on probabilistic activity information, employing an Inactivity Score that provides a probabilistic weighting of inactivity periods based on the reliability of sensor measurements. By analyzing historical Inactivity Scores, anomalies that potentially represent an emergency can be identified. Evaluations across seven datasets show this approach outperforms existing methods, achieving a mean time to detect emergencies of approximately 05:23:28 hours and producing 0.09 false positives per day under noise-free conditions. Moreover, unlike related approaches, the proposed method remains effective with noisy data. This thesis demonstrates that emergencies in private households can be detected using existing data sources from the home infrastructure, offering a cost-effective and non-intrusive solution to enhance the safety and autonomy of the elderly at home. Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-15992 ER - TY - THES A1 - Stoffels, Dominik T1 - Advancing Pattern Detection, Theory Development and Decision Making with Explainable AI N2 - The application of explainable artificial intelligence (XAI) methods in data-driven decision-making and computationally intensive theory development (CTD) is a subject of ongoing debate, particularly concerning how and whether these methods can be effectively employed, and how the reliability of their explanations can be ensured. This dissertation addresses these issues by systematically analyzing the usability of XAI for pattern detection, CTD, and decision-making, drawing on various real-world and synthetic datasets and employing different empirical methods and perspectives. The dissertation consists of four studies, each addressing distinct issues in the field of XAI application. KW - Explainable Artificial Intelligence KW - Machine Learning KW - Computationally Intensive Theory Development Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-15975 ER - TY - THES A1 - Kravets-Meinke, Daria T1 - Search Engines and Foreign Influence: How Google and Yandex Mediate Russia’s Propaganda Abroad N2 - This cumulative dissertation examined how the US-based Google and Russia-based Yandex mediate the propaganda efforts of Russia’s ruling elites abroad on a case study of Belarus. The findings presented here contribute to a nuanced understanding of how algorithmic gatekeepers, particularly search engines, can be strategically appropriated or manipulated to reinforce and export state narratives beyond national borders. The main conclusion of this dissertation is that both Yandex and Google, albeit through different mechanisms and to varying extents, can serve as mediators of Russia’s propaganda efforts abroad. KW - search engines KW - Russia KW - propaganda Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-15953 ER - TY - THES A1 - Hasenpflug, Mareike T1 - Slice sampling on Riemannian manifolds N2 - This thesis is concerned with hybrid slice samplers for approximate sampling of distributions on Riemannian manifolds. First for distributions on the Euclidean unit sphere, and then for distributions on general Riemannian manifolds we introduce a geodesic-based hybrid slice sampler, called geodesic slice sampler. Under mild regularity assumptions, we establish reversibility with respect to the target distribution for this sampler and positive semi-definiteness of the corresponding operator. Moreover, on compact Riemannian manifolds we show uniform ergodicity with explicit constants for the geodesic slice sampler if the target distribution has a bounded density with respect to the Riemannian measure. As an important building block of this sampler, we provide an explicit expression for the shrinkage procedure proposed in (Neal, 2003) in terms of a Markov kernel. We establish that this kernel is reversible with respect to the uniform distribution on the target set and that its corresponding operator is positive semi-definite. Beyond the geodesic slice sampler, we apply these results also to elliptical slice sampling (Murray, Adams, MacKay, 2010) to obtain a proof for its reversibility with respect to the target distribution and positive semi-definiteness of the corresponding operator. KW - Markov chain Monte Carlo KW - Slice sampling KW - Riemannian manifolds Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-15903 ER - TY - THES A1 - Prakash, Jyoti T1 - Static Analyses of Interlanguage Interoperations N2 - Software Developers are moving towards a multilingual development where they combine two languages in a single application to harness the strengths of each language. For example, performance-critical components of a Java application can be implemented in C language. It provides flexibility, at the same time, it becomes difficult to statically analyze these applications. The amalgamation of two languages in a single application may introduce bugs ranging from type-mismatch to security vulnerabilities. Therefore, it is necessary to develop static analysis techniques to aid developers in multilingual development. In this thesis, we develop techniques to study and analyze these applications. In the first part of the thesis, we study the prevalence of security and privacy vulnerabilities in hybrid apps. Hybrid apps are Android apps that combine both Java and Javascript components, where the Android part is secured (on the device), while the JavaScript part is exposed to web. Additionally, some of the Java functions are available to JavaScript component through an interface called as bridge interface. In the pursuit of the goal, we adopt a static backtracking of data dependencies to determine the flow of information from the android component to the web component. Our study revealed the potential sources of unsoundness in the existing static analyses. Static backtracing also induces imprecision in the analysis, i.e., there might be some flows that are not possible during runtime albeit are reported by the analysis. These were mitigated through a manual verification. This work reveals that the android-web hybridization can lead to (potential) vulnerabilities that might impact the confidentiality as well as the integrity properties of these apps. From the communication patterns occurring in Android WebView, we noticed that its is feasible for an attacker to jeopardize the integrity of apps by corrupting some value, say an input on the web through bridge interfaces. Motivated by this, we define a information flow analysis of the bridge interfaces and the associated data flows in hybrid apps. In the first step, we propose a novel threat model where we model the attacker as someone who wants to influence the behavior of android app as an integrity violation. Based on this threat model, we then propose a demand-driven analysis technique to detect confidentiality and integrity violations. Our analysis leverages, a demand-driven technique, where it only analyzes the relevant part of app for the information flow analysis with the help of function summaries --- escaping the need of a whole-program analysis. In the second part of the thesis, we generalize the approach to static analysis of multilingual applications. To this end, we investigate into the question of combining existing single language analyses to analyze multilingual programs. To provide an affirmative answer, we define an analysis to leverage single language analyses for call-graph and pointer analysis of multilingual programs. Our analysis takes two existing unilingual analyses and analyzes the complete multilingual program. It uses a novel summary specialization technique that resolves the information flows at the bridge interfaces by utilizing independent pre-analyses (modulo foreign function interfaces) of each language component. We apply this technique to analyze Android-NDK and GraalVM Java-Python multilingual applications for generating call-graphs. In summary, we have developed novel techniques for information flow and call-graph analysis for multilingual programs. With this, we motivate the need of static analyses for multilingual applications and its applications which includes, vulnerability detection, program understanding, amongst others. Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-15736 ER - TY - THES A1 - Still, Enid T1 - Affective Roots: Memory, emotions and viscerality within organic agri-food networks in Tamil Nadu, India N2 - For activists I met in Chennai, the capital city of Tamil Nadu in India, organic food and farming was a ‘way of life’. Stemming from my curiosity about this statement and what it meant for different actors in the regional organic agri-food networks, this research explores the interconnected lives and livelihoods of organic farmers and activists in Tamil Nadu. To engage with the social dynamics of these agri-food networks, the research focuses in on the role of the affective, feeling body. The emphasis on affect emerged in the form of memories, emotions and visceral experience, from empirical data collected between 2020 and 2022. And as the thesis demonstrates, affective dimensions, or what moves people, are important because, unlike economic, statistical or structural perspectives, they make visible the ways different actors feel socio-ecological change. Adopting the lens of Feminist Political Ecology and drawing on the fields of historical anthropology and feminist ethics, this thesis highlights: (1) the enduring nature of epistemic injustice within agri-food relations, (2) how social boundaries are built, maintained and remade through affective encounters, circumscribing what I call the ‘affective roots’ of socio-ecological change and (3) how ambiguous affective relations co-constitute organic agri-food networks, shaping anxious environmental subjectivities, that stem from socially mediated encounters with agro-chemicals, the market, the landscape and the other. Deepening our understanding of socio-ecological and agrarian change through empirical inquiry into how people feel matters, I argue, because it sheds light on injustices that are often concealed beneath the clouds of crisis. KW - Affect KW - Organic Agriculture KW - Tamil Nadu KW - Feminist Political Ecology KW - Epistemic injustice Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-15838 ER - TY - THES A1 - Jakob, Dietmar Friedrich T1 - Teilhabegerechtigkeit bei der digitalen Inklusion älterer Erwachsener: Eine Potenzialanalyse von Sprachassistenten T1 - Equity of participation in digital inclusion of older adults: A potential analysis of voice assistants N2 - This cumulative dissertation delves into the complexities and opportunities surrounding older adults’ adoption and use of Voice Assistants (VAs), focusing on digital participation equity from theologic-ethical and social perspectives. Through an extensive series of methodologically diverse studies—including systematic literature reviews, laboratory experiments, surveys, and field studies—the research aims to uncover how older adults perceive, interact with, and are impacted by technologies, such as the particular model “Amazon Echo Show 10, 3rd generation with integrated voice interface ALEXA”. The investigation also seeks to pinpoint the obstacles that impede the adoption of these technologies among this demographic. The research initially demonstrates that older adults can recognize the utility of VAs in various applications, including information retrieval, entertainment, and health management. The findings underscore the importance of these devices in enhancing the quality of life by providing easier access to essential services and facilitating social interaction, even among those who may be physically isolated. However, the dissertation identifies significant concerns among older adults regarding privacy and data security, influencing their willingness to embrace VAs. The devices’ complexity and occasional interaction difficulties—such as command formulation and speech recognition issues—further challenge their usability for this group. A notable and unique aspect of the study is the anthropomorphization of devices by some older adults. This behavior, where users attribute human-like characteristics or emotional connections to VAs, suggests deeper psychological and social dimensions in the user-technology relationship. This phenomenon is examined to understand its implications for technology acceptance and the potential for these devices to mitigate feelings of loneliness and social isolation. In summary, this dissertation provides practical recommendations for enhancing the design, communication, and functionality of VAs to better cater to the needs and preferences of older adults. It underscores the importance of technology development that respects the dignity and autonomy of older individuals, ensuring their digital participation and equity. The work advocates for a comprehensive approach that integrates ethical considerations into technology design and dissemination, thereby promoting a framework that supports the full inclusion of older adults in the digital world. N2 - Diese kumulative Dissertation untersucht die Komplexität und die Möglichkeiten, die mit der Annahme und Nutzung von Sprachassistenten durch ältere Erwachsene verbunden sind, und konzentriert sich auf die digitale Teilhabegerechtigkeit aus theologisch-ethischer und sozialer Sicht. Durch eine umfangreiche Reihe methodisch unterschiedlicher Studien - darunter systematische Literaturauswertungen, Laborexperimente, Umfragen und Feldstudien - zielt diese Forschung darauf ab herauszufinden, wie ältere Erwachsene Technologien wie kommerzielle Sprachassistenten, wie z. B. das spezielle Modell "Amazon Echo Show 10, 3. Generation mit integriertem Sprachinterface Alexa" wahrnehmen, mit ihnen interagieren und von ihnen beeinflusst werden. Die Untersuchung versucht auch, die Hindernisse aufzuzeigen, die die Annahme dieser Technologien in dieser Bevölkerungsgruppe behindern und geht auch auf Tendenzen von Antropomorphisierung der Geräte ein. Die Untersuchung zeigt zunächst, dass ältere Erwachsene den Nutzen von Sprachassistenten in verschiedenen Anwendungen erkennen können, darunter für die Informationsbeschaffung, Unterhaltung und das Gesundheitsmanagement. Die Ergebnisse unterstreichen die Bedeutung dieser Geräte für die Verbesserung der Lebensqualität, indem sie den Zugang zu wichtigen Dienstleistungen erleichtern und die soziale Interaktion fördern, selbst bei Personen, die körperlich isoliert sind. Die Dissertation zeigt jedoch auch, dass ältere Menschen Bedenken hinsichtlich des Schutzes der Privatsphäre und der Datensicherheit haben, was ihre Bereitschaft, Sprachassistenten zu nutzen, deutlich beeinflusst. Die Komplexität der Geräte und gelegentliche Schwierigkeiten bei der Interaktion - wie etwa Probleme bei der Befehlsformulierung und der Spracherkennung - stellen eine weitere Herausforderung für die Benutzerfreundlichkeit dieser Gruppe dar. Ein bemerkenswerter und einzigartiger Aspekt der Studie ist die Anthropomorphisierung der Geräte durch einige ältere Erwachsene. Dieses Verhalten, bei dem die Benutzer Sprachassistenten menschenähnliche Eigenschaften oder emotionale Verbindungen zuschreiben, deutet auf tiefere psychologische und soziale Dimensionen in der Beziehung zwischen Benutzer und Technologie hin. Dieses Phänomen wird untersucht, um seine Auswirkungen auf die Technologieakzeptanz und das Potenzial dieser Geräte, Gefühle von Einsamkeit und sozialer Isolation zu mildern, zu verstehen. Abschließend bietet die Dissertation gezielte Empfehlungen zur Verbesserung von Design, Kommunikation und Funktionalität von Sprachassistenten, um den Bedürfnissen und Vorlieben älterer Menschen besser gerecht zu werden. Sie unterstreicht die Notwendigkeit einer Technologieentwicklung, die die Würde und Autonomie älterer Menschen in den Vordergrund stellt und ihre digitale Teilhabe und Gleichberechtigung gewährleistet. Die Arbeit fordert einen ganzheitlichen Ansatz, der ethische Überlegungen in die Entwicklung und Verbreitung von Technologien einbezieht, und setzt sich für einen Rahmen ein, der die vollständige Einbeziehung älterer Menschen in die digitale Welt unterstützt. KW - Human Computer Interation KW - Voice Assistants KW - Older Adults KW - Digital Equity Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-15849 ER - TY - THES A1 - Weishäupl, Andreas T1 - Zur Bedeutung der maximalen Laktatbildungsrate in Diagnostik und Training am Beispiel Skilanglauf und Radsport T1 - The relevance of the maximal lactate accumulation rate in diagnostics and training: The example of cross-country skiing and cycling N2 - Die Arbeit beleuchtet die Bedeutung der maximalen Laktatbildungsrate (V̇Lamax) für die Leistungsdiagnostik und die Trainingspraxis. Für die Sportart Skilanglauf wurde ein neuer Sprinttest zur Bestimmung der V̇Lamax am Skiergometer entwickelt, der sich als reliabel und valide erwiesen hat. Dabei wurden verschiedene Ansätze zur Bestimmung der alaktaziden Zeit genauer betrachtet. Außerdem wurde der Sprinttest am Skiergometer mit dem etablierten Sprinttest am Radergometer verglichen, wobei festgestellt werden konnte, dass die V̇Lamax sportart- und extremitätsspezifisch getestet werden sollte. Zudem wurde die Auswirkung von Intervalltraining unterschiedlicher Intensität im Radsport untersucht. Hochintensives Ausdauertraining scheint dabei die V̇Lamax zu steigern, wohingegen submaximales Sweetspot-Training die V̇Lamax zu senken scheint. KW - Maximale Laktatbildungsrate KW - maximal lactate accumulation rate KW - Intervalltraining KW - cross-country skiing KW - cycling KW - Leistungsdiagnostik KW - Training KW - Lactate KW - Skilanglauf KW - Radsport Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-15801 ER - TY - THES A1 - Hering, Robin T1 - Protection of Civilians in Armed Conflict: Safe Areas and the Silencing of Mass Atrocities N2 - This publication-based thesis approaches the topic of the protection of civilians in armed conflict by ‘zooming in‘ on two specific sub-topics: safe areas as well as the silencing of mass atrocities. The thesis consists of five publications (four of them published in double-blind peer reviewed journals) and of an introductory chapter that presents the overall argument and contextualises the publications. Two publications argue that mass atrocities are silenced, or at least not politicised, in the discourses and debates of Germany as an exemplary UN member state. It is argued that ‘silencing’ is a structural feature of an ‘identity-mismatch’ with the domestic ideational structure that inhibits debates and freezes the possibility space for foreign policy. Empirically, the first publication assesses the rhetoric of the German chancellor, foreign ministers and parliamentary group leaders vis-à-vis the mass atrocities committed in Yemen, Myanmar and South Sudan. The second publication widens the scope and looks at German political, media and societal debates in twelve cases of mass atrocities between 1992 and 2019. The remaining three publications focus on the topic of safe areas. The first publication systematically collects and assesses the existing conceptual literature on safe areas. The second publication presents a comprehensive definition, a four-fold typology based on a distinction by size and the logic of protection as well as an extensive empirical dataset of safe areas. By analysing case studies from Iraq and South Sudan, the third publication argues that safe areas have a very limited potential to provide an alternative to flight, especially from the perspective of the protection-seeking civilians themselves. KW - Protection of Civilians KW - Mass Atrocities KW - Foreign Policy Analysis KW - Safe Areas KW - Silencing KW - Zivilbevölkerung KW - Schutzzone KW - Außenpolitik KW - Schweigen KW - Völkermord Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-15765 ER - TY - THES A1 - Soller, Sebastian T1 - Anomaly Detection and Forecasting Techniques and their Applications Scenarios, Challenges and Limits in Industrial Production Settings N2 - What needs to be done to get machine learning and artificial intelligence from the lab to the shop floor? This work and its affiliated publications focus on challenges and solutions to apply machine learning applications inside industrial setups and what steps are needed to improve those setups. In industrial setups it is easy to run into a "hen and egg" problem. To gather data, the information which data to gather is ideally given beforehand and these information are not available when studying new setups and machines. In this work setups and concepts are created to dynamically connect to a network and start gathering data from available endpoints inside a manufacturing setup. The data streams of these endpoints are further analyzed to give an initial analysis of the data and advise further processing. To further analyze these data streams with the current advances in the machine learning field and AI, plug and play solutions are presented by manufacturers and scientific research. Limits are determined for this plug and play capability and solutions are provided to further improve upon the base solutions. The capability to apply commonly applied methods was analyzed and initially provided non-sufficient results. In the sub-fields of anomaly detection, regression analysis, forecasting and classification the addition of context information, such as production specific information and time dependent analysis were used to improve the results. Context information, especially periodic information, were further conceptualized and integrated into the initial data analysis. Difficulties with correct labeling of ground truth due to differing biases of participants were encountered, and counter measurements were proposed. Results of the classification, regression, forecast and context information extraction were investigated for their influence on the human operator. A significant change could be measured in multiple cases, just by providing information about underlying problems and errors. The Aforementioned machine learning methods further improved the performance of machine and operator. KW - Anomalieerkennung KW - Künstliche Intelligenz KW - Maschinelles Learning KW - Plug-and-Play Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-15659 ER - TY - THES A1 - Frühwirth, Lorenz T1 - The Asymptotic Behavior of Birkhoff- and Lacunary Sums N2 - This doctoral thesis consists of three independently published research articles on the asymptoic behaviour of Lacunary- and Birkhoff sums. The former are sums formed by periodic functions and exponentially growing sequences of natural numbers. The corresponding summands often exhibit behavior typical of independent and identically distributed random variables. The methods used are of an analytical and probabilistic nature. The Birkhoff sums considered in this work are generated by the Kronecker sequence and by discontinuous functions. The methods employed are from the field of metric number theory, specifically classical results from continued fraction theory are utilized. Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-15677 ER - TY - THES A1 - Lorenz, Catherine T1 - Studies on optimization problems with dynamically arriving information N2 - In today’s fast-paced world, transportation planning, e-commerce, smart manufacturing, emergency services, and financial markets operate in real-time environments where dynamically arriving information must be integrated on-the-fly into decision-making. Research produced online algorithms ranging from myopic reoptimization (Reopt) to learning-based anticipation methods. However, given the complexity of real-world problems, optimal decision policies remain unknown, and effectiveness is often assessed through simulations against simple benchmarks, leaving improvement potential and robustness uncertain. This dissertation proposes effective online policies using classical and innovative analytical and computational evaluation methods, establishing performance bounds and comparisons to optimal solutions. It designs algorithmic frameworks for two dynamic optimization problems: the Online Order Batching, Sequencing, and picker Routing Problem (OOBSRP) in warehousing and the Traveling Salesman Problem with a Truck and a Drone under Incomplete Information (TSP-DI), for disaster relief. Given the importance of automation in real-time environments, a strong emphasis is placed on robotic solutions. For the OOBSRP with manual and robotic carts, we prove that Reopt is asymptotically optimal with probability one under broad stochastic conditions. From a worst-case perspective, no policy can improve Reopt by more than 50%, as it is shown to be asymptotically two-competitive. A computational study confirms that Reopt’s gaps to the complete-information optimum are small, e.g. averaging less than 5% for a cost-minimization objective. A pattern analysis of Complete-Information Optimal Solutions (CIOSs), generated with dynamic programming algorithms, identifies simple algorithmic enhancements – like eliminating waiting, intervention, or strategic relocation – that further reduce costs and delivery times. These findings suggest limited benefits of anticipatory (including AI-based) algorithms in OOBSRP. Conversely, for TSP-DI, where road blockages reveal dynamically, Reopt performs poorly in the worst case, as we reveal its exponentially growing competitive ratio. We show that policies delaying deliveries for drone surveillance are significantly superior in competitive ratio. A proposed hybrid policy achieves best average and worst-case results in experiments. Using battery-limited drones introduces a challenging static subproblem within these policies, classified as Drone Routing Problems with Energy Replenishment (DRP-E). We develop a Very Large-Scale Neighborhood Search (VLNS) and an exact method for generic DRP-Es. VLNS searches an exponential-sized neighborhood of a promising solution entirely in polynomial runtime, making it ideal for real-time policies or intensification in metaheuristics. This dissertation underscores the importance of analytical guarantees and comparisons to the optimum in online algorithm design, as policy effectiveness often diverges from intuition and varies significantly across problems. KW - Dynamic optimization KW - Online algorithms KW - Competitive analysis KW - Probabilistic performance guarantees KW - Very large-scale neighborhood search Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-15649 N1 - According to § 11 FPromO, Abs. 1, Satz 5 of the Promotionsordnung and with the agreement of the Chair of the Board of Examiners for Doctoral Awards, the following minor revisions have been made for the publication of the dissertation compared to the version submitted for grading. These changes result from comments and requests by the external reviewer, Prof. Dr. Stefan Irnich, as well as the author’s own observations during the revision process: - Corrected minor typos in grammar and mathematical notation. - Implemented wording improvements. - Reorganized and updated the list of abbreviations alphabetically. - Updated the publication status of the list of papers to the submission date and added the affiliation of the University of Bologna. - Page 13: Corrected the reduction of the average observed gap to CIOS of Reopt (16.6 percentage points) and provided clarification. - Pages 23 and 58: Added an inequality of indices k and l in definitions of a partition of batches in an optimal solution. - Page 24, "because the cart- and picker equipment is order-specific for each batch" changed to "because of pick-lists that are printed out " - Page 55: Added and corrected a statement (one sentence) regarding the reference Wahlen and Geschwind (2023). - Page 71: Added the statement: "Note that an increase in batching capacity significantly impacts the runtime of the DP approaches for both objectives." - Page 80: Replaced and corrected Figure 3.8 (statement remains unchanged). - Page 79: Corrected column names in Table 3.12. - Standardized the abbreviation "VLNS" instead of "VLSN" throughout Chapter 5. - Unified the written-out problem names of OOBSRP and OBSRP-R throughout the dissertation ER - TY - THES A1 - Schwind, Mara T1 - „Insgesamt sah ich wirklich die Wellen an mir vorbeirauschen, mich darin befindend“ - Die Folgen negativer Reaktionen gegen Wissenschaftler*innen in den sozialen Medien N2 - Wissenschaftler*innen werden immer häufiger zum Ziel von Kritik, Anfeindungen und Ähnlichem in den sozialen Medien. Die Studie nimmt die reziproken Effekte dieser negativen Reaktionen in den Blick. Konkret wird untersucht, mit welchen Arten negativer Reaktionen Wissenschaftler*innen konfrontiert werden, welche mentalen Verarbeitungs- und Bewertungsprozesse in diesem Kontext relevant sind und wie die Betroffenen mit den negativen Reaktionen anschließend umgehen, um die entstandene Belastungssituation zu bewältigen. Neben der theoretischen Aufarbeitung der Thematik wird dafür auf qualitative Leitfadeninterviews mit betroffenen Wissenschaftler*innen zurückgegriffen. Die Erkenntnisse der Studie werden in einem „Modell der Konfrontation mit negativen Reaktionen in den sozialen Medien“ zusammengeführt. Das Modell ermöglicht zum einen die strukturierte Beschreibung entsprechender Vorfälle und kann zum anderen als theoretisch-konzeptionelle Grundlage für weitere empirische Untersuchungen dienen. KW - qualitative Leitfadeninterviews KW - Hate Speech KW - Wissenschaftler*innen in den sozialen Medien KW - Kritik, Anfeindungen und Hass gegenüber Wissenschaftler*innen Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-15627 ER - TY - THES A1 - Gruber, Martin T1 - Tackling Test Flakiness: Understanding the Problem and Providing Practical Mitigations N2 - "Software is eating the world". With this phrase from his 2011 Wall Street Journal interview, Marc Andreessen predicted a decade of disruptive software-based innovations affecting various industries. Today, over ten years later, many of his predictions have come true: six of the seven most valuable companies worldwide are computer technology firms, and more than half of the world's population has access to the internet and owns a smartphone, with numbers still growing rapidly. The increasing importance of software has also changed software development. To ensure product quality despite high complexity and fast product cycles, software developers started to adopt continuous integration and regression testing practices: each change to an existing system is automatically tested and reverted in case it breaks any existing functionality. As a result, large software projects are conducting millions of test executions each day. One obstacle to such extensive testing are non-deterministic tests that can pass and fail without any changes to the underlying system or the test itself. These tests are commonly referred to as flaky tests. Flaky tests break regression testing, as they cause test failures that are unrelated to the changes that are being tested. Developers are forced to investigate these intermittent failures, wasting their time and decreasing their trust in testing. This thesis presents our research that aims at understanding and mitigating test flakiness. To comprehend the nature of flaky tests, we conducted both code-based studies on open-source projects, as well as a developer survey. All our investigations confirmed that flakiness is a frequently occurring and severe issue. The causes of flakiness, however, depend on the domain of the project and the source of the test: while asynchronous waiting and concurrency are overall the most prevalent causes aside from test order dependencies, Python projects tend to experience more flakiness caused by networking and randomness. Flaky tests that were not written by developers but generated automatically tend to be more often caused by randomness or unspecified behavior. To avoid test flakiness in generated tests, developers can use existing flakiness suppression mechanisms of test generation frameworks, which we found to be effective. In general, however, most developers currently address the issue of test flakiness by rerunning failing tests. Nevertheless, they would like more support when dealing with test flakiness, namely better visualizations, automated detection and debugging techniques, and education on the topic. In response to this feedback, we developed and evaluated a generic flakiness prediction approach, as well as an automated flakiness debugging technique. Our flakiness prediction method is easy to use and widely applicable. In contrast to previous techniques, it avoids any form of static or dynamic analysis. Instead, it relies solely on a test's execution result history and version control information, two commonly available artifacts. Additionally, it aims to classify real-world failures as either caused by flakiness or a regression. Previous techniques mainly focused on identifying potential flaky test cases in test suites, a related but less actionable question. An evaluation on a large-scale automotive software project yielded positive results. Our approach showed a strong predictive performance (95.5% F1-score), outperforming the previously used heuristic. We also introduced Spectrum-based Flaky Fault Localization (SFFL), an automated debugging technique that aims to pinpoint the specific lines in the source code that cause a flaky test's non-deterministic behavior. SFFL extends traditional Spectrum-based Fault Localization (SFL) by considering multiple coverage behaviors of the same test case, a highly common phenomenon among flaky tests. Our evaluation on 101 flaky Python tests showed that SFFL outperforms traditional SFL and was able to narrow down the flaky fault's location to 3.5% of a project's code base on average. KW - Test Flakiness KW - Flaky Test KW - Softwareentwicklung KW - Softwaretest KW - Qualitätssicherung KW - Testen Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-15549 ER -