@misc{Afzal2025, type = {Master Thesis}, author = {Afzal, Umair}, title = {AI-Driven Comic Generation: Exploring the Creative Potential of Generative AI in Digital Storytelling}, url = {http://nbn-resolving.de/urn:nbn:de:hbz:1383-opus4-22581}, school = {Hochschule Rhein-Waal}, pages = {111}, year = {2025}, abstract = {Creative sectors have accepted AI into their industry for establishing modern methods of generating digital content. This study introduces a novel AI-based framework based on AI technology, using GANs along with Stable Diffusion models to automate comic development. This study looks at juxtaposing narrative outlining through text with automated visual generation toward an integrated system that produces adaptable comic panels with appropriate visual structure. The research methodology that the project has followed can be built on three cornerstones: advanced GAN schemes for text generation and pre-processing, followed by image synthesis through Stable Diffusion. A specially developed algorithm for speech bubbles determined the optimal placement of that text, so it would function well and maintain a semblance of beauty. By iteratively refining and tuning the model, this system was evaluated. Initial observations regarding visual coherence and narrative alignment were hopeful, but further tests using quantitative metrics-for instance, FID for images and BLEU for text, as well as broader user feedback-would be needed to validate the efficacy of the model entirely. The impediments were, however, GAN mode collapse, irregular speech-bubble layout, and inconsistent artistic styles. Further research would uncover the potential role of AI systems in easing the comic generation process for creators, educators, and designers of digital content to enhance accessibility and efficiency. This method shows promising applicability in various domains like automated narratives, customizable comics, and educational material. Further along the way, the scientists plan to improve panel storytelling, create an intuitive interface, and expand the dataset to include more artistic styles. Such enhancements could maximize the gain from automated comic conception.}, language = {en} } @masterthesis{Simsek2025, type = {Bachelor Thesis}, author = {Simsek, Seyda}, title = {The Impact of Increasing Use of Artificial Intelligence in Human Resource Management on Employees}, url = {http://nbn-resolving.de/urn:nbn:de:hbz:1383-opus4-22687}, school = {Hochschule Rhein-Waal}, pages = {58}, year = {2025}, abstract = {This study examines the application of artificial intelligence (AI) in human resource management (HRM) and its effects on employees, considering both operational benefits and the ethical, social, and psychological implications. Its analyzes real-world applications of AI in recruiting, performance management, talent development, and HR administration using qualitative secondary data from academic papers, industry publications, and case studies published between 2018 and 2024. To examine employee experiences, organizational issues, and ethical implications, a combined analytical approach is used, which incorporates the Technology Acceptance Model, Job Demand-Control Model, human-centered AI concepts, and the European Commission's Ethics Guidelines for Trustworthy AI. While AI can increase effectiveness, reliability, and strategic HR results, the findings highlight concerns about algorithmic bias, reduced human engagement, and risks to employee autonomy and well-being. This paper addresses the significance of organizational planning, transparency, and responsible oversight in AI implementation, highlighting that technology should supplement rather than replace human judgment. The study offers an understanding of the human-centered and ethical aspects of AI in HRM, as well as insights for organizations seeking to use AI responsibly while maintaining employee trust and engagement.}, language = {en} } @masterthesis{Tariq2025, type = {Bachelor Thesis}, author = {Tariq, Suleman}, title = {Optimising Heat Loss Reduction and Facilitating the Transition to Biogas in Industrial Applications.}, school = {Hochschule Rhein-Waal}, year = {2025}, abstract = {This study has evaluated the heat loss potential and energy consumption at the industrial level. Notably, heat loss on a large scale at the industrial level has been recognized as neither economically nor environmentally sustainable. Moreover, the continued use of fossil fuels (natural gas) has been reviewed as unsustainable due to their adverse effect and limited availability, posing challenges for the present and future. Heat loss is optimized at the continental production site in Villingen-Schwenningen. Heat loss through exhaust fans, which extract heat from inside the building and release it to the environment to maintain the internal temperature, has been analysed. The released heat is lost in the environment. To recover this energy loss, the integration of a plate-to-plate heat exchanger is proposed. This approach recovers the rejected heat to preheat the incoming fresh air supply, replacing the traditional heat coil operated on natural gas. Additionally, the transition of natural gas to biogas has been explored. The district heating twin pipe (DN 80) is considered for the smooth flow of thermal energy. For this project, a financial analysis of return on investment (ROI) for 10 years is conducted, the thermal energy flow rate over 2.1km, and heat loss during the transfer phase are calculated. The results have shown significant importance for the recovered energy by integration of a plate-to-plate heat exchanger; yearly, 1.2 GW of energy can be recovered, reducing the consumption of natural gas and making a complete transition towards biogas, economically and environmentally beneficial.}, language = {en} } @masterthesis{Kumar2025, type = {Bachelor Thesis}, author = {Kumar, Vivek}, title = {Assessing Sustainability Reporting Obligations and Regulatory Compliance for LINEG: An Analysis of EMAS Alignment with Emerging EU Directives.}, school = {Hochschule Rhein-Waal}, year = {2025}, abstract = {This thesis assesses the preparedness of LINEG, a German public water utility, for the Corporate Sustainability Reporting Directive (CSRD). It evaluates the extent to which LINEG's EMAS-based environmental disclosures align with CSRD/ESRS and where extensions are required to meet comprehensive ESG obligations. The analysis is grounded in Stakeholder Theory and Valente's Stage Model to connect accountability expectations with organizational sustainability maturity. Methodologically, a qualitative case study and qualitative content analysis are applied to LINEG's EMAS statements and relevant regulatory texts, using deductive categories derived from CSRD/ESRS and SASB, complemented by inductive coding to capture LINEG-specific themes. Peer utilities are referenced to contextualise findings. Findings show a strong environmental foundation— externally validated data on energy, emissions, water, and biodiversity—indicating partial readiness for ESRS E-standards. However, material gaps remain in social and governance areas (e.g., workforce metrics, affordability and service quality indicators, stakeholder engagement processes, and board-level oversight of sustainability). Applying Valente's model positions LINEG between Defensive and Isolated stages: largely compliancedriven, with initiatives not yet embedded across strategy and governance. The thesis proposes a roadmap to consolidate environmental disclosures into ESRS structures, conduct a double-materiality assessment, expand S and G indicators, formalise stakeholder engagement, and assign clear governance responsibilities. Limitations arise from a single-case, document-based approach and the evolving German transposition of CSRD, which may adjust timelines and specific requirements once fully enacted.}, language = {en} } @misc{Aziz2025, type = {Master Thesis}, author = {Aziz, Sk Tarik}, title = {The Impact of Employee Job Satisfaction on Organization's Long-Term Performance}, url = {http://nbn-resolving.de/urn:nbn:de:hbz:1383-opus4-23053}, school = {Hochschule Rhein-Waal}, pages = {266}, year = {2025}, abstract = {The purpose of the study is to investigate the impact of employee job satisfaction on organizational long-term performance and focus on the key factors that increase satisfaction among employees. Previous research has mostly focused on short-term organizational outcomes, and there is limited evidence about the factors that enhance job satisfaction and ensure long-term performance of an organization. To fill this gap, qualitative research was conducted, and data was collected through semi-structured interviews, and the data was analyzed using MAXQDA software. The findings represent some of the factors that significantly increase job satisfaction, such as positive and supportive work environment, flexibility and autonomy at work, career growth and continuous learning opportunities, and fair compensation with meaningful recognition. The participants repeatedly highlighted these factors as a source of enhancing motivation, dedication, commitment, and employee performance. The study suggests that when organizations actively follow and implement these factors, it is more likely to increase employee satisfaction and satisfied employees improve productivity, achieve organizational goals, and increase a higher level of dedication, which ensures organizational long-term performance.}, language = {en} } @masterthesis{Ustritski, type = {Bachelor Thesis}, author = {Ustritski, Nikita}, title = {Competitiveness of Green vs. Traditional Companies: A Comparative Study in the Automotive, Hospitality, and Fashion Industry}, url = {http://nbn-resolving.de/urn:nbn:de:hbz:1383-opus4-23123}, school = {Hochschule Rhein-Waal}, pages = {80}, abstract = {This thesis compares short-term and long-term competitiveness between green and traditional companies in the automotive, hospitality, and fashion industries. Existing research rarely examines multiple industries together or evaluates competitiveness using both time perspectives, creating a clear research gap. The research question asks how green and traditional companies differ in financial performance, innovation, consumer trust, and regulatory responsiveness. The hypothesis proposes that green companies show lower short-term competitiveness, but higher long-term competitiveness than traditional firms. A qualitative comparative case study approach is applied using secondary data, including annual reports, sustainability disclosures, ESG ratings, and international regulatory frameworks. Six companies are analysed: Tesla and Toyota in the automotive sector, Hilton and Wyndham in hospitality, and Kering and H\&M in fashion. Their competitiveness is assessed through a structured framework that distinguishes between immediate business outcomes and long-term strategic development. The findings show that traditional companies perform better in the short term due to efficient cost structures, established operating models, and stable supply chains. Green companies, however, achieve stronger long-term competitiveness by investing in innovation, transparency, and alignment with tightening regulatory and consumer expectations. Tesla, Hilton, and Kering demonstrate superior long-term performance, while Toyota, Wyndham, and H\&M maintain advantages mainly in the short term. The results support the hypothesis and highlight sustainability as an important driver of long-term competitiveness. The study offers cross-industry insights for academics, managers, and policymakers and identifies opportunities for future research on sustainable business models.}, language = {en} } @masterthesis{Sueyruege2026, type = {Bachelor Thesis}, author = {S{\"u}yr{\"u}ge, Ey{\"u}p}, title = {Vergleich von FPGA und Mikrocontroller f{\"u}r die Echtzeitverarbeitung von Audiosignalen zur Richtungserkennung mittels FFT und TDOA einschließlich LED-basierter Visualisierung}, url = {http://nbn-resolving.de/urn:nbn:de:hbz:1383-opus4-23229}, school = {Hochschule Rhein-Waal}, pages = {57}, year = {2026}, abstract = {Das Ziel dieser Arbeit ist es, ein praxisnahes System zur Echtzeitverarbeitung von Audiosignalen mit dem Fokus auf der Richtungsbestimmung von Schallquellen zu entwickeln. Als Hardwareplattformen werden daf{\"u}r ein Field Programmable Gate Array (FPGA) und ein Mikrocontroller (MCU) eingesetzt. Dabei konzentriert sich die Arbeit auf die Untersuchung der beiden Plattformen, wobei die Leistungsf{\"a}higkeit, Genauigkeit und Ressourceneffizienz verglichen werden. Zu diesem Zweck werden Algorithmen der Signalverarbeitung, besonders die Fast Fourier Transform (FFT) und die Time Difference of Arrival (TDOA), implementiert und ausgewertet.}, language = {de} } @masterthesis{Ko2026, type = {Bachelor Thesis}, author = {Ko, Tin Long}, title = {The advancement of the ball point game}, school = {Hochschule Rhein-Waal}, year = {2026}, abstract = {Lean management concepts are dynamic, yet students often meet them as static definitions. This thesis advances the Ball Point Pen Game into a production simulation that exposes bottlenecks, queues, work-in-process accumulation and defects while keeping the pen-assembly task simple and standardised. Using design-based research, one design-test-reflect cycle was executed: redesign requirements were derived from Lean and lean-game education literature, implemented as roles, control rules and learning objectives, and piloted in class. The revised game increases complexity without adding product difficulty by introducing an explicit order-release rhythm (takt), separated material and information flows, visual control, and progressive pull logic across three rounds. Across rounds, batch size is reduced stepwise, supermarket/Kanban replenishment is introduced, and a simple poka-yoke prevents assembly errors. A pilot execution with seven students evaluated the redesign using a single-group pre-post knowledge test, a post-game perception questionnaire, and in-game KPIs (throughput, lead time, WIP and defects) supported by observation notes. Results are interpreted as exploratory due to the small sample and lack of a control group. Participants reported high engagement and that game discussions helped translate observations into improvement actions, aligning with prior evidence that simulation games can support understanding and transfer in Lean education. However, implementation deviations required by the small group (role merging and ad-hoc facilitation changes) reduced instruction clarity for at least one participant. The thesis delivers a reusable player/instructor manual plus design rationales and measurement procedures to guide the next test and a larger evaluation with stronger internal validity.}, language = {en} } @masterthesis{Muesch2025, type = {Bachelor Thesis}, author = {M{\"u}sch, Yannick}, title = {Kolmogorov-Arnold-Transformer: Untersuchung hybrider KAN-Transformer-Architekturen im Hinblick auf Skalierung, Effizienz und Interpretierbarkeit}, url = {http://nbn-resolving.de/urn:nbn:de:hbz:1383-opus4-23376}, school = {Hochschule Rhein-Waal}, pages = {85}, year = {2025}, abstract = {Transformers have become the de-facto standard architecture in Machine Learning, particularly in Natural Language Processing. However, they are computationally expensive to train, with approximately two-thirds of non-embedding parameters residing in Multi-Layer Perceptrons (MLPs). Liu et al. (2024) revisited the long-disregarded Kolmogorov-Arnold representation theorem and demonstrated promising results in specific domains such as symbolic regression and PDE solving. Whether Kolmogorov-Arnold Networks (KANs) generalize to other domains, particularly NLP, remains an open research question. This work systematically evaluates five architecture configurations: MLP baseline, MLP with B-Spline activation, KAN with B-Spline, KAN with Mean aggregation, and Group-Rational KAN (GR-KAN) - across three model sizes (15M, 41M, 124M parameters). Experiments are conducted on text classification ("AG News") and language modeling ("FineWeb") tasks. Identical components (attention, embeddings) isolate performance differences to the feed-forward topology. Statistical validity is ensured through multiple random seeds and parameter-matched comparisons. KAN-based architectures achieve performance parity with MLPs on classification tasks (±0.5 percentage points accuracy). However, they consistently underperform on language modeling, with perplexity increases of +7 to +28 points. Training efficiency overhead ranges from 1.5-2.0× for KANs, while GR-KAN approaches baseline speed. Notably, KANs exhibit significantly higher sparsity (≈ 90\% vs. ≈ 40\%), enabling compression factors of 1.4-1.6× with minimal performance degradation. The MLP+B-Spline control condition reveals that performance deficits stem from KAN topology rather than activation functions. KANs present a viable alternative for discriminative NLP tasks but do not outperform MLPs for generative language modeling. The postulated interpretability advantage through learnable activation functions could not be empirically confirmed - learned functions degenerate to quasi-linear transformations. Future research should explore alternative basis functions and selective hybridization strategies.}, language = {de} } @misc{ParayilSivan2026, type = {Master Thesis}, author = {Parayil Sivan, Kavya}, title = {Design and Evaluation of a Mobile Application to Support Autistic Passengers in Air Travel. From Identifying User Needs to Assessing its Effectiveness in Reducing Anxiety and Enhancing Travel Preparedness}, url = {http://nbn-resolving.de/urn:nbn:de:hbz:1383-opus4-23492}, school = {Hochschule Rhein-Waal}, pages = {88}, year = {2026}, abstract = {Air travel can present significant accessibility barriers for autistic travellers. This study examined the needs, requirements, and challenges experienced by level 1 and level 2 autistic travellers during air travel and evaluated the effectiveness of a user-centred mobile application in reducing anxiety, improving their travel preparedness, and creating a more predictable air travel experience. A mixed-methods approach was employed for the study. In the beginning, an online survey with 35 participants (21 autistic individuals and 14 support persons) was conducted to understand the need, requirement and challenges of the autistic participants. Findings from the survey showed generally low satisfaction among autistic travellers who has prior air travel experience. The major challenges were related to unpredictability, sensory overstimulation, complex airport procedures, difficulty finding sensory-friendly spaces, and in-flight discomforts. Based on the insights from the survey, a high-fidelity mobile application prototype was designed to work across different airlines and airports providing real-time flight updates, airport and airline specific accessibility information, navigation support, communication cards, and travel checklists. The prototype was then evaluated with 5 autistic participants through a moderated remote usability test followed by a post-test interview and questionnaire. The results showed that features such as real-time flight updates, travel checklists, navigation support, and accessibility information were effective and perceived as helpful in reducing anxiety and increasing preparedness but some discoverability issues were identified in the prototype showing the need to iterate it. Overall, the findings suggest that the application is functionally effective and usable but only partially effective in improving overall travel experience as external environmental factors like airport procedures, in-flight discomforts are beyond the scope of the application. The study also highlights that a thoughtfully designed mobile application can partially support autistic travellers by improving the predictability and helping them prepare for the journey. This study contributes to the growing research on accessibility for autistic individuals by examining air travel challenges and evaluating a user-centred mobile application.}, language = {en} }