Enabling Scalable High-Performance Integrated Sensing and Communications for Next-Generation Wireless Systems

Wireless communications technology has gone through a significant evolution since its inception in the late 19th century, integrating itself as a critical pillar of modern society and the functions of the world. Successive generations of the mobile network systems since the first generation (1G) until the present have seen an ever-increasing demand of the key performance indicators (KPIs), such as data rate, reliability, spectral effciency, device connectivity, and more – outlined by the scope of the current fifth generation (5G) systems as enhanced mobile broadband (eMBB), ultra-reliable low-latency communications (URLLC), and massive machine- type communications (mMTC), to support the emergent use cases such as autonomous and intelligent networks, extended reality (XR) applications, and Internet-of-Things (IoT), under the enabling technologies such as millimeter-wave (mmWave)/Terahertz (THz) bands, massive multiple-input multiple-output (mMIMO), cell-free MIMO (CF-MIMO), reconfigurable intelligent surface (RIS), and more. Furthermore, the imminent beyond fifth generation (B5G) and sixth-generation (6G) systems anticipate even higher requirements and ambitious paradigms in wireless technologies, aiming to improve upon the performance of 5G but also addressing other challenges which have assumed greater importance for the future, such as resource effciency (spectrum, energy, and hardware), physical layer security, system scalability, and high-mobility. In summary, this thesis entails a comprehensive investigation into the realisation of beyond fifth generation (B5G), underpinned by the two major topics of resource-effciency and low-complexity within the frameworks of the two selected enabling technologies, index modulation (IM) and integrated sensing and communications (ISAC), thereby proposing novel methods and analyses from unique yet complementary perspectives of the addressed problem of achieving scalable and high-performance next-generation wireless systems

Advancing Environmental, Social, and Governance (ESG) Assessment and Reporting: A Hybrid Framework of Semantic Modeling, Multi-Criteria Analysis, and Maturity Models

Environmental, Social, and Governance (ESG) reporting is increasingly critical for corporate transparency and accountability as demands from investors, regulators, and the public grow. Despite its importance, ESG reporting faces persistent challenges, including fragmented standards, inconsistent metrics, misalignment with global goals like the UN SDGs, and limited relevance for stakeholders. These issues weaken benchmarking, data reliability, and decision-making, raising the risk of greenwashing. Although previous studies have explored drivers of ESG performance, there is still a clear need for technical solutions that enhance the quality and usefulness of ESG disclosures through integrated approaches. This dissertation addresses these critical gaps by developing and proposing a novel, integrated framework that leverages the strength of semantic technologies, MCDM methods, and ESG maturity models. The research is structured through several interconnected studies, exploring specific industry applications using multi-criteria analysis techniques to identify and prioritize relevant ESG KPIs. A systematic literature review (SLR) provides a foundational understanding of existing ontology-driven solutions and their limitations in addressing reporting challenges and integrating quantitative methods. Based on these insights, the core contribution is the design of an ontology-based framework called ESGOnt. This framework utilizes a modular ESG ontology to standardize terminology, integrate fragmented data sources, and explicitly map ESG metrics to SDG targets. This research contributes by addressing critical challenges in ESG reporting through a novel, integrated framework. It advances the understanding of how semantic models can be combined with quantitative methods to create robust, transparent, and actionable sustainability reporting systems, strengthening corporate accountability and supporting more effective contributions to global sustainable development

Advanced Beamforming Techniques for Enhanced Flexibility, Accessibility, and Multi-functionality in Wireless Communications Systems

This dissertation contributes to three distinct focuses of BF design as: BF for flexible connectivity, BF for enhanced connectivity, and BF for over-the-air-computating (AirComp). The first objective is the “BF for flexible connectivity”. In order to realize flexibility for preserving connectivity regardless of the user position in the coverage area, the recent cell-free MIMO (CF-MIMO) system is considered. For the BF design, a flexible design is proposed, which is directly adaptable not only for both uplink (UL) and downlink (DL) communication modes but also for both under-loaded and over-loaded scenarios. As for the second focus, termed “BF for enhanced connectivity,” a novel BF design compatible with three distinct power allocation schemes is proposed. For the sake of connectivity enhancement, a DL MIMO-rate splitting multiple access (RSMA) system is considered. Even though the proposed BF design is assumed to be used only for under-loaded or fully-loaded scenarios, the computational complexity required to design BF is significantly less than that of the state-of-the-art (SotA) alternative. Finally, the ”BF for Over the Air Computing” is considered for envisioning the realization of integrated AI and communication. In this focus, novel receiver (RX) BF designs compatible with uniform-forcing (UF) precoding for a multi-user UL multiple-input single-output (MISO)-AirComp system are considered for higher performance or lower complexity. Toward higher performance design, while the proposed design sacrifices computational complexity in the BF, the resulting AirComp has a lower mean square error(MSE) performance. On the other hand, the proposed BF design for lower complexity realizes equivalent MSE performance achieved by the high-performance BF design with significantly lower complexity thanks to the combination of recent convex optimization and Bayesian optimization (BO) methods

The Decision to Start a Business: Determinants of Business Formation and Differences between Entrepreneurs and Employees

Entrepreneurship is vital in driving innovation, economic growth, and societal transformation. Due to its growing relevance, this dissertation examines the factors that motivate individuals to engage in entrepreneurial endeavors, grounded in the Theory of Planned Behavior (TPB) and enriched by supplementary theoretical perspectives. The research combines qualitative and quantitative methods to explore how attitudes, subjective norms, and perceived behavioral control interact with these diverse aspects. The first study identifies key influences on entrepreneurial intention through qualitative interviews with entrepreneurs, thereby revealing ten critical determinants. The second study expands upon these findings by employing a quantitative approach to validate these parameters through a survey among entrepreneurs in Germany. It demonstrates the central importance of economics-oriented education, materialistic values, and resilience while refining the theoretical assumptions of the TPB in entrepreneurial contexts. Lastly, the third study extends the analysis by comparing the personality traits of entrepreneurs and employees utilizing the OCEAN model. This research delineates substantial differences across all five traits, underscoring the psychological dimensions of entrepreneurial behavior. By amalgamating the three studies and their respective findings, this dissertation contributes to the theoretical understanding of entrepreneurship by enhancing the predictive validity of the TPB for research on entrepreneurship and highlighting differences in personality traits among entrepreneurs and employees. Through the integration of qualitative insights and quantitative validation, this dissertation provides a comprehensive and nuanced perspective on the complex nature of entrepreneurship

Neurocognitive and psychological dimensions associated with gait and balance in older adults

This Ph.D. dissertation investigates the neurobehavioral, psychological, and cognitive factors influencing postural control and its age-related changes through four studies. Postural control is essential for daily activities, and its decline with age increases fall risk, leading to autonomy loss and reduced quality of life. The first study (Imani & Godde, 2021) explores how self-efficacy mediates the relationship between falls and autonomy in older adults. While falls negatively impact autonomy, higher self-efficacy reduces this effect. Cognitive function predicts autonomy but does not moderate the relationship between falls and autonomy. The second study examines the bidirectional link between cognitive and physical function. Results show that cognitive decline affects physical abilities over time and vice versa, highlighting the strong connection between executive function and motor control. This reinforces how cognitive decline, falls, and depressive mood contribute to reduced social participation. The third study investigates the effects of transcranial direct current stimulation (tDCS) combined with balance training in younger adults. Targeting the sensorimotor cortex and dorsolateral prefrontal cortex (DLPFC), the study assesses how anodal tDCS enhances balance. Resting-state EEG is also explored as a predictor of training effects. The fourth study extends this research to older adults, revealing age-related differences in neural activation during balance training. Results suggest individualized stimulation protocols may improve balance outcomes. Overall, these studies emphasize the cognitive-motor link in postural control and propose targeted interventions to enhance balance and autonomy, particularly in older adults at risk of falls

Modelling plankton dynamics and community compositions in temperate lakes

In recent years, lakes have faced rising pressure from anthropogenic activities and climate warming, and the aquatic communities of some lake ecosystems are reshaping in ways that can form harmful algal blooms. It is crucial to understand how lake phytoplankton communities respond to environmental stressors under varying environmental conditions. The cell size of phytoplankton has multiple important implications for the dynamics, diversity, and productivity of a phytoplankton community. Empirical investigations in lakes showed that the size composition of phytoplankton communities differs with inorganic nutrient conditions, grazing pressure (usually quantified by zooplankton abundance), and water temperature. However, it is not clear how these three factors interact to shape the size composition of lake phytoplankton. In this thesis, I use size-based plankton modelling to elucidate how a trade-off mechanism, dependent on inorganic nutrient availabilities and zooplankton size-specific grazing strategies, shapes the dynamics, the size composition, and the exclusion pattern of phytoplankton in a generic temperate lake. Lastly, I recast the model to a specific Swiss lake, Greifensee, by using high-frequency data comprising phytoplankton cell size (biovolume) and plankton abundances. In summary, this thesis investigates the interactive effects of inorganic nutrient regimes and zooplankton grazing strategies on the community dynamics and compositions of lake phytoplankton and offers a glimpse into the future size compositions of phytoplankton and nutrient and plankton dynamics of Greifensee. The results not only advance our understanding of plankton communities in temperate lakes, but they also identify hypotheses related to zooplankton grazing strategies that can be further tested experimentally. The data-driven modelling approach presented here can contribute to strategic conservation and management plans for mitigating the effects of ongoing environmental change

The Structure and Dynamics of Groups in Open Source Software Development: A Computational Social Science Approach to Understanding Online Collaboration

This dissertation examines Free/Libre Open Source Software (FLOSS) development groups through three interconnected studies, each applying computational social science methods to understand different aspects of online collaboration. The first study analyzes group interactions via pull requests, identifying five organizational structures ranging from hierarchical to collaboratively governed networks. This typology moves beyond the traditional "bazaar-cathedral" dichotomy and reveals how group structure impacts outcomes such as popularity, stability, and productivity. The second study employs an agent-based model informed by Affect Control Theory to explore how cultural dynamics shape roles, status, power distribution, and gender biases within FLOSS communities. Findings illustrate the interplay between cultural norms and social structures, highlighting pathways toward gender equality through cultural norm shifts. The third study investigates macro-level project dynamics, examining how repository fitness, preferential attachment, and aging influence project popularity. It compares the meritocratic nature of scientific research and FLOSS development, employing generative probabilistic models based on stochastic processes to understand the mechanisms driving popularity. Together, these studies demonstrate how platform design, cultural norms, and social structures collectively shape FLOSS projects, advancing our understanding of digital collaborative systems

Applying co-creation to develop behaviour change interventions: Analysing the design, build and evaluation of digital health interventions

Chronic and non-communicable diseases present ongoing challenges for healthcare systems worldwide. Digital Health Interventions (DHIs) provide a promising solution by empowering patients to engage in health-related decisions and manage their behaviours. At present, many DHIs suffer from low user adoption or fail to progress beyond research. This thesis analyses the design, build, and evaluation of such tools to guide the effective co-creation of DHIs. Across five studies, this thesis examines the design, build, and evaluation of DHIs. The first two studies explore how to effectively plan the co-creation of DHIs, identifying both facilitators and challenges. The second study applies co-creation methods to incorporate end users in developing design specifications for a DHI. The third study evaluates the impact of including end users in the build phase, whilst the final two studies assess evaluation strategies, demonstrating how synthetic data and machine learning can be used to manage missing data and predict intervention outcomes. Findings highlight the importance of adaptive, inclusive design processes, careful planning of co-creator involvement, and the application of behavioural science across all phases. The thesis offers practical guidance for future researchers, emphasising the value of empowering patients, addressing attrition, and applying predictive analytics to maximise the real-world impact of DHIs

Pectinolytic waste valorization – Fermentation of D-galacturonic acid by Saccharomyces cerevisiae using glycerol as a co-substrate

Utilizing agro-industrial waste as a raw material for the production of chemicals, fuels and materials could support a circular bioeconomy, helping to minimize carbon and energy loss. Pectin-rich biomass is a generally under-utilized feedstock, and includes residues such as citrus peel, apple pomace and sugar beet pulp. It offers itself as a feedstock for biotechnological production processes using microorganisms as a cell factory. Unlike other biomass residues, this waste is advantageous due to its high sugar and low lignin content. One key component of pectin is D-galacturonic acid (D-GalUA), an oxidized substrate that S. cerevisiae cannot metabolize naturally. To enable its consumption, S. cerevisiae was equipped with the catabolic pathway naturally present in filamentous fungi. However, this did not allow D-GalUA to serve as sole carbon and energy source. The inability to grow on D-GalUA was thought to be due to a lack of electrons, as the pathway requires NAD(P)H. In this work, this problem was addressed by providing a co-substrate - glycerol - a by-product of the biodiesel industry. The electrons provided in this way were supposed to not only enable D-GalUA utilization but also support its fermentation to ethanol. Therefore, S. cerevisiae was equipped with both the fungal pathway for D-GalUA catabolism and the ‘DHA pathway’ for glycerol utilization – the latter channeling electrons from glycerol oxidation into cytosolic NADH. The resulting strain not only consumed D-GalUA at a high specific rate, but also co-fermented the substrates into ethanol, achieving a maximum yield of 71% of the theoretical maximum. Additionally, the native Gcy1, a non-specific aldo-keto reductase, was found to convert D-GalUA into L-galactonate, an intermediate of the D-GalUA catabolic pathway. By providing valuable insights into the co-utilization of glycerol and D-GalUA, this study lays the foundation for future endeavors towards the valorization of these two industrial by-products

Towards Sustainable Fisheries Management: Understanding Territorial Use Rights in Fisheries (TURF) and Environmental Stewardship Actions

Local fishers have historically been subjected to the detrimental effects of overfishing, a consequence of open access practices that are likely to persist in the coming decades. The open-access nature of many fisheries is a significant driver of overfishing, which poses a substantial threat to marine ecosystems and their livelihoods that depend on them. The concept of common property theory provides a theoretical framework that can be used to explain the phenomenon of overfishing due to open access practices. Fishery resources are regarded as examples of a common property, implying that these resources belong to all fishers. This assumption gives rise to intense competition among fishers to exploit the fishery resources. One potential solution to this problem is to establish a territorial use rights system (TURF) that would prevent open-access practices. This thesis argues that all relevant stakeholders in small-scale fisheries management should prioritize environmental stewardship, regardless of the system used to address the overfishing problem caused by open-access practices, as this constitutes a principal factor in determining sustainability. This perspective is particularly relevant in the context of TURF implementation as numerous studies have demonstrated that TURF is an effective means of fostering stewardship. This thesis presents a collection of three studies that address the two primary topics of TURF and stewardship. While this thesis is primarily based on a case study of TURF implementation and stewardship actions (fishing logbook) in Kepulauan Seribu, Indonesia, I hope that the resulting publications will serve as additional references and contribute to the global discussion on TURF and stewardship