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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.
When Benoît Assou-Ekotto’s former coach Harry Redknapp announced that the Cameroonian international had decided to end his professional football career and become an adult movie actor, the story generated astonishment and amusement in social media networks and received widespread attention from the mass media. Although the French-born footballer denied the story’s validity shortly afterward, claiming Redknapp was joking, it entertained football fans and the wider public during the spring of 2017. However, while this was one of the very few occasions on which an African footballer’s postcareer trajectory was a matter of public debate, it also revealed that former African professional footballers’ whereabouts, occupations, and living conditions are widely unknown and remain an underresearched topic.
Offering learning opportunities for developing digital competencies in pre-service teacher education remains challenging despite its growing importance in preparing future educators. This study investigates the effectiveness of integrative learning opportunities, called “digitally enhanced courses”, which combine subject-specific and digital learning objectives. Implemented at a German university (2019–2023). These courses aimed to promote digital competencies required for technology-supported teaching. Using survey data from 312 pre-service teachers, the research examined students’ self-assessed digital competencies, technology acceptance, and value–cost assessments through multiple measurement instruments, including TPACK scales, the Technology Acceptance Model, and Expectancy–Value beliefs. Results revealed significantly higher self-assessed digital competencies in private contexts compared to teaching situations. While mere course participation showed no significant impact, both the frequency and number of attended courses positively correlated with higher self-assessed digital skills across all TPACK dimensions. Additionally, increased technology acceptance and higher success expectations were associated with enhanced teaching-related digital competencies. The findings emphasize that the effectiveness of digitally enhanced courses is contingent upon systematic implementation and student engagement, highlighting the need for structured curricular integration of digital competency development in teacher education through comprehensive, spiral-curriculum approaches rather than isolated interventions. However, this study’s reliance on self-reported data may introduce social desirability and subjective estimation bias, and its cross-sectional design limits causal interpretations. Future research should employ longitudinal approaches to examine competency development over time, incorporate objective performance-based assessments, and explore how instructional design and curricular integration influence digital competency acquisition.
Smart Grids are electrical grids that require a decentralised way of controlling electric power conditioning and thereby control the production and distribution of energy. Yet, the integration of Distributed Renewable Energy Sources (DRESs) in the Smart Grid introduces new challenges with regards to electrical grid balancing and storing of electrical energy, as well as additional monetary costs. Furthermore, the future smart grid also has to take over the provision of Ancillary Services (ASs). In this paper, a distributed ICT infrastructure to solve such challenges, specifically related to ASs in future Smart Grids, is described. The proposed infrastructure is developed on the basis of the Smart Grid Architecture Model (SGAM) framework, which is defined by the European Commission in Smart Grid Mandate M/490. A testbed that provides a flexible, secure, and low-cost version of this architecture, illustrating the separation of systems and responsibilities, and supporting both emulated DRESs and real hardware has been developed. The resulting system supports the integration of a variety of DRESs with a secure two-way communication channel between the monitoring and controlling components. It assists in the analysis of various inter-operabilities and in the verification of eventual system designs. To validate the system design, the mapping of the proposed architecture to the testbed is presented. Further work will help improve the architecture in two directions; first, by investigating specific-purpose use cases, instantiated using this more generic framework; and second, by investigating the effects a realistic number and variety of connected devices within different grid configurations has on the testbed infrastructure.
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.
We study the Markov chain Monte Carlo estimator for numerical integration for func-
tions that do not need to be square integrable with respect to the invariant distribution.
For chains with a spectral gap we show that the absolute mean error for L^p functions,
with p ∈ (1, 2), decreases like n^(1/p)−1 , which is known to be the optimal rate. This
improves currently known results where an additional parameter δ > 0 appears and the
convergence is of order n^((1+δ)/p)−1 .
We study the parameterized complexity of the problem to decide whether a given natural number n satisfies a given Δ0-formula ϕ(x); the parameter is the size of ϕ. This parameterization focusses attention on instances where n is large compared to the size of ϕ.We show unconditionally that this problem does not belong to the parameterized analogue of AC0. From this we derive that certain natural upper bounds on the complexity of our parameterized problem imply certain separations of classical complexity classes. This connection is obtained via an analysis of a parameterized halting problem. Some of these upper bounds follow assuming that IΔ0 proves the MRDP theorem in a certain weak sense.
In this paper, we study discrepancy questions for spanning subgraphs of k-uniform hypergraphs. Our main result is that, for any integers k ≥ 3 and r ≥ 2, any r-colouring of the edges of a k-uniform n-vertex hypergraph G with minimum (k−1)-degree δ(G) ≥ (1/2+o(1))n contains a tight Hamilton cycle with high discrepancy, that is, with at least n/r +(n) edges of one colour. The minimum degree condition is asymptotically best possible and our theorem also implies a corresponding result for perfect matchings.
Our tools combine various structural techniques such as Turán-type problems and hypergraph shadows with probabilistic techniques such as random walks and the nibble method. We also propose several intriguing problems for future research.
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.
Archival collections contain an underutilized wealth of biodiversity data, encapsulated in government files and other historical documents. In 1845, the Bavarian government conducted a comprehensive national survey on the occurrence of 44 selected vertebrate species across the country. The detailed expert responses from 119 forestry offices, totalling 520 handwritten pages, have been preserved in the Bavarian State Archives. In this study, we digitized, annotated, geographically referenced, and published these historical records, making them widely available as data for research and conservation planning. Our dataset, openly accessible through the Global Biodiversity Information Facility (GBIF) and Zenodo, contains 5,467 species occurrence records from 1845. Besides the binary presence/absence data, we have also published the original textual survey responses, which contain rich qualitative information, such as species abundances, population trends, habitats, forest management practices, and human-nature relationships. This information can be further processed and interpreted to address a range of questions in historical and contemporary ecology.