TY - THES A1 - Hanafy, Ahmed T1 - API Driven Form Rendering N2 - This master’s thesis investigates the challenges and opportunities associated with dynamic form rendering in user interfaces, specifically in the context of Galeria Karstadt Kaufhof (GKK), a key player in the German retail sector. Collaborating with CODUCT Solutions GmbH, this research aims to enhance GKK’s operational efficiency and user experience in their digital transformation journey, focusing on Project Baldeney, a cloud-native platform that automates content management workflows. The thesis begins by outlining the limitations of traditional, static methods of form rendering, highlighting the implications for development time and error frequency. It identifies the fragmentation in the existing API-driven architectures as a critical issue affecting system reliability and user experience. Against this backdrop, the work proposes a unified, API-driven framework to dynamically render forms for many user actions, such as data input and transactions. The research takes a deep dive into existing systems—particularly Informatica’s Product Information Management (PIM) software and the new software in development Article Workbench to identify user experience issues, inefficiencies, and the complexities involved. Through this examination, it offers a targeted solution to integrate various components of form management, like building, parsing, validation, and rendering, into a cohesive system. The thesis aims to contribute to software development and user experience design substantially, by targeting improved development efficiency, reduced errors, and enhanced system reliability. By achieving these objectives, the research aspires to furnish GKK with a robust solution for dynamic form rendering, thereby enhancing both user satisfaction and system performance in the fast-evolving digital landscape. KW - Dynamic Form Rendering KW - API-Driven Architecture KW - Retail Software Integration KW - User Interface Efficiency KW - Product Information Management Y1 - 2023 ER - TY - THES A1 - Gurung, Purnima T1 - Sentiment Analysis in Nepali Tweets: Leveraging TransformerBased Pre-trained Models N2 - Despite the remarkable achievements of large transformer-based pre-trained models like BERT, GPT in several Natural Language Processing (NLP) tasks including Sentiment Analysis (SA), challenges are still present for subdued source languages like Nepali. Nepali language is written in Devanagari script, has complex grammatical structure and diverse linguistic features. Due to the absence of balanced datasets, and computational resources for Nepali, achieving optimal result with the latest architecture remains challenging. For this reason, publicly available NLP modelsfor Nepali are very less, making research in this area difficult. This paper attempts to addressthis gap through the use of pre-trained transformer models specially tailored for Nepali from Hugging Face including BERT, DistilBERT, ALBERT, and DeBERTa for sentiment analysis in Nepali tweets on relatively balanced datasets. The models are trained on large Nepali datasets and optimized for NLP tasks involving Devanagari scripts. To evaluate the model’s performance, various tokenization strategies are investigated in order to capitalize on transformer-based embedding with the SoftMax function and confusion matrix. The outcomes of models are compared using the same datasets. The study’s results shows that DistilBERT achieved the highest accuracy rate of 88% in Nepali sentiment analysis tasks, followed by BERT and DeBERTa at 83% and 80%, respectively. However, ALBERT showed a low accuracy of 70%. The result of this approach shares valuable viewpoints for the field of sentiment analysis in diverse linguistic contexts. KW - Sentiment Analysis KW - NLP KW - Nepali Tweets KW - Monolingual KW - DistilBERT Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:hbz:1383-opus4-19677 ER - TY - THES A1 - Kottek, Nick T1 - Echtzeit-Erkennung von Gesten des deutschen Fingeralphabets mithilfe eines Convolutional Neural Networks N2 - Sign language is an important factor in the integration of deaf and hard of hearing people into society. Due to the limited number of people who speak sign language, there is a communication barrier that needs to be addressed. In recent years, sign language has been an important field of research. There have been numerous attempts at trying to find a solution to this problem. This thesis focuses on the German finger alphabet, which has not been researched as much. It examines whether it is possible to recognize the gestures of the German finger alphabet in real time with a convolutional neural network. For that, literature is consulted, and a prototype is developed. The prototype includes a newly created dataset with 2,500 images distributed over 25 gestures, a convolutional neural network, and software for real-time translation of a video stream. The prototype demonstrates the feasibility of realizing such a task. The convolutional neural network achieves an accuracy of 99.61%. On a powerful desktop computer, the prediction of a single frame takes between 36 and 40 ms. However, there are some limitations and restrictions to the quality of prediction caused by factors such as lighting and background. Additionally, certain similar gestures, such as M and N, are difficult to distinguish. Based on these results, ideas and suggestions for future studies are presented. KW - convolutional neural network KW - sign language KW - German finger alphabet KW - image classification KW - real-time recognition Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:hbz:1383-opus4-19768 ER - TY - THES A1 - Shrestha, Sabita T1 - Named Entity Recognition for Nepali Text Using Pre-Trained BERT-Based Model N2 - The popularity of using transformer-based models like Bidirectional Encoder Representations from Transformers (BERT) for various Natural Language Processing (NLP) tasks is increasing rapidly. Unfortunately, the research is very limited for low-resource languages like Nepali. This study examines the utilisation of pre-trained BERT-based NERNepal for Named Entity Recognition (NER) tasks in Nepali text. The main goal is to investigate the efficiency of the NERNepal model, which has been pre-trained and fine-tuned on Nepali corpus data for NER. This research provides new insights by evaluating the NERNepal model on two distinct datasets. It addresses unique linguistic challenges specific to Nepali. The study also offers a detailed analysis of the model's strengths and weaknesses. By focusing on diverse datasets, this study shows how adaptable the model is and how its performance varies. These aspects have not been explored extensively before. The EverestNER dataset is one of the largest human-annotated datasets in Nepal so far, and the Nepali_NER dataset is also BIO-annotated for the NER task, which helped to compare the model’s prediction. The performance was better on the Nepali_NER dataset in comparison with another selected dataset. The EverestNER dataset contained many complex words for ORG connected with many tokens for a single entity with different contextual meanings and different annotations for the same word in different tokens as per context. Because of this, it created more confusion for the prediction, especially for the ORG entity. It had a similar issue with another dataset as well, but the label annotation was better in comparison. Furthermore, the research tries to clarify the difficulties and constraints related to utilising pre-trained BERT models for NER in low-resource languages such as Nepali. The study focuses on research areas on the efficacy of the model and its performance on two different datasets. Post-training with the EverestNER train dataset was attempted, but due to computational resource limitations, only a maximum of 3 epochs was possible, which did not improve the evaluation. It also has implications for enhancing language processing tools for Nepali. The results show the ability of a pre-trained BERT-based model to improve NER skills for Nepali text. However, further study is required to overcome the current obstacles to identifying complex words. The availability of high computational resources and the possibility of combining other NER approaches with a transformer-based model could increase the performance and robustness of the model. Keywords: Named Entity Recognition, Natural Language Processing, BERT, low resources language KW - Named Entity Recognition KW - Natural Language Processing KW - BERT KW - low resources language Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:hbz:1383-opus4-19870 ER - TY - THES A1 - Nacke, Marius T1 - Künstliche Intelligenz zur Vorhersage von Kreditentscheidungen N2 - Seit der Verschärfung der Kreditrichtlinien im Jahr 2022 ist es zunehmend schwieriger geworden, einen Kredit in Deutschland und im europäischen Raum zu erhalten. Das Interesse an Krediten ist zuletzt ungeachtet dieser Erschwernisse angestiegen. Vergleichs- und Vermittlungsportale für Kredite können potenziellen Darlehensnehmern aktuell nur in begrenztem Maße dabei unterstützen, eine genehmigte Kreditanfrage zu erhalten. Die Vorhersage der Kreditentscheidungen von Banken kann als Basis für weitere Methoden fungieren, die Kreditnehmern helfen können, die Wahrscheinlichkeit einer Genehmigung zu erhöhen. In der vorliegenden Arbeit wird daher untersucht, welche Verfahren des Machine-Learning am ehesten für die Vorhersage von Kreditentscheidungen geeignet sind. Dazu werden die Daten der Yareto GmbH, eines Vergleichs- und Vermittlungsportals für Fahrzeugkredite, für das Training sowohl eines Logistischen-Regressions- und XGBoost-Modells als auch eines Multilayer-Perceptrons verwendet. Das XGBoost-Modell erreicht dabei die höchste Accuracy und Precision mit 73,6\% bzw. 76,1\% bei einer Trainingszeit von lediglich 55 Minuten. Das Multilayer Perceptron kann eine ähnlich hohe Accuracy erreichen, bedarf allerdings mehr als zehn Stunden für das Training. Demnach ist XGBoost am ehesten von den drei untersuchten Verfahren zur Vorhersage von Kreditentscheidungen geeignet. KW - Kreditvergleichsportale KW - Prognosen KW - Künstliche Intelligenz KW - Ensemble-Modelle KW - Kreditentscheidungen Y1 - 2024 ER - TY - THES A1 - Akter, Most Sarmin T1 - Data Analysis of the "Loyalty Program-Valeo Specialist Club" to Improve the Independent Aftermarket: Designing an Efficient Marketing Strategy N2 - Nowadays, a loyalty program is one of the most significant marketing tools for winning genuine customer loyalty. Valeo, a global automotive supplier, also offers the Valeo Specialist Club loyalty program and rewards garage or workshop members who only purchase Valeo spare parts. The core intent of this study is to understand the importance of the Valeo loyalty application, members’ insights, and their experiences for improving the future planning, aftermarket performance, and management of the Value Specialist Club. In today’s competitive market, products, services, and customer loyalty are valuable assets, so the program was created to enhance member satisfaction and loyalty with the Value Specialist Club. A mixed-method approach was used to answer the study question and findings, improve member satisfaction, and refine marketing strategies, using a survey as primary data and Qlik Sense as secondary data. Besides, using a survey methodology, the study collected 79 responses from different countries (the United Kingdom, Germany, Belgium, and the Netherlands) and analyzed the data with only 58 Specialist Club member's responses. A reliability examination was additionally accomplished to measure the accuracy of the collected survey data. Qlik Sense, Microsoft 365, and Excel 2016 were used for data analysis and visualization, which involved descriptive analysis, correlation coefficients, and text sentiment analysis. The study results show positive trends in member satisfaction across four markets, but a decreasing engagement rate is noticeable. In general, members from all countries were satisfied with Valeo products and services, contrasting with moderate dissatisfaction with the Valeo Specialist Club app and customer service. The study also found a strong correlation between the Valeo Specialist Club app, loyalty service, and customer service, suggesting improvements to meet member expectations and preferences. Nevertheless, the study also emphasizes the need to enhance the Valeo Specialist Club registration process, loyalty program features, and benefits to align with current trends, foster increased member satisfaction, and sustain loyalty within the independent aftermarket. Furthermore, the conclusions of this study will aid in developing upcoming marketing plans. KW - Loyalty Program KW - Insights KW - Member Loyalty KW - Marketing KW - Valeo Specialist Club Y1 - 2024 ER - TY - THES A1 - Grigo, Tobias T1 - Das Homeoffice in der Verwaltung – Eine Zwischenbilanz und Erfahrungsberichte zu Best Practices, Weiterentwicklung und Herausforderungen N2 - The home office has become established in the offices of numerous companies and administrations since the events of the global COVID-19 pandemic and has posed numerous challenges. Particularly in Germany, administrative authorities were confronted with the challenge of quickly responding to the events of the pandemic and taking appropriate measures to curb the spread of the virus in the offices of administrations. This paper examines the use of the home office in administration during the pandemic by combining quantitative and qualitative methods such as statistical analyses, interviews, and case studies. In doing so, it sheds light on the experiences of employees as well as the challenges and potentials of home office use. The context aims to demonstrate that the investigation of home office use in administration during the pandemic was crucial in understanding the effects of the newly designed work practices on administrative organizations to better shape future work models. The aim of this study is to gain insights that contribute to the further development of the home office concept in administration. This includes evaluating the long-term effects on work efficiency, work-life balance, and corporate culture. These insights contribute to assessing the effectiveness and efficiency of the home office in administration and lay the groundwork for how optimized work arrangements can be created. They also provide valuable insight into the adaptability of administrative structures to continuously changing work environments. The results of this study will help develop practical solutions and optimize the implementation of the home office in administration. The findings lay new foundations for future research that could address further aspects of home office use in administration, such as long-term effects on organizational performance and employee satisfaction, as well as the development of guidelines for effective implementation of hybrid work models. KW - Homeoffice KW - Administration KW - COVID-19 pandemic KW - Work practices KW - Efficiency Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:hbz:1383-opus4-20272 ER - TY - THES A1 - Regmi, Khem Raj T1 - Interactive Visualisation Tool for Teaching Environmental Data: A Guideline of how to set up the tool taking user feedback into account N2 - This thesis will study the creation of an interactive data visualization tool for environmental dataset that concentrates specifically on Nitrate concentrations in groundwater. This project is intended to create a tool for exploratory/experiential learning - one that allows learners to investigate regional data and pursue genuine learning opportunities. The plan is to use regional data in a specific user journey to create this interactive learning experience. The project uses open environmental data: Hygris dataset of LANUV(Landesamt für Natur, Umwelt und Verbraucherschutz) related to the regions Kleve and Wesel in Germany, and realizes this with help of python programming language and python streamlit framework, web development tools and data visualization libraries (pandas , plotly.express, streamlite.components.v1). This study explores tailored visualization strategies that address key challenges such as the inherent complexity of environmental datasets and the need for more engaging and comprehensible educational tools. These strategies include deploying interactive visualizations that allow hands-on data exploration, and temporal visualizations. The role of user feedback in refining educational tools for teaching environmental data is examined, particularly in designing effective visualization techniques like line char, bar chart, bubble chart, pie chart, scatter plot and intensity graph for representing groundwater nitrate concentrations. The impact of different visualization techniques on the understanding and interpretation of open environmental data among educators and students is analyzed, with an emphasis on the spatial distribution of groundwater nitrate concentrations over time. This approach aims to increase user engagement and deepen understanding of environmental data, facilitating a more profound embedding of information within learners' cognitive processes. KW - Interactive data visualization KW - Data representation KW - Environmental data KW - Nitrate concentration KW - Groundwater KW - Open data KW - User feedback KW - Education KW - Data accessibility KW - Data inclusivity KW - Educational tools KW - Digital teaching Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:hbz:1383-opus4-21594 ER - TY - THES A1 - Boulmane, Aya T1 - Development of a Web-Based Tool for Estimating Lifecycle CO₂ Emissions of Electric vs. Diesel Vehicles in Germany N2 - Due to rapid technological development, the transport sector has emerged as one of the most difficult areas to reduce decarbonization, balancing its high global greenhouse gas emissions. In Germany, the shift from internal combustion engine vehicles (ICEVs) to electric vehicles (EVs) has become a key focus of national and EU climate policies. Nevertheless, the transition to EVs is associated with a multitude of factors that need to be considered, including emissions from manufacturing, the energy used during operations, and post-operational treatment. This thesis focuses on the design, development, and refinement of a web-based CO₂ Lifecycle Emission Calculation tool that compares cradle-to-grave emissions of EVs and diesel ICEVs based on different driving scenarios in Germany. It is based on Life Cycle Assessment (LCA) Methodology as indicated in ISO 14040/14044. With the tool, the manufacturing, operational, and end-of-life emissions are estimated based on validated datasets from peer-reviewed literature and authoritative bodies (IPCC, IEA, UBA). The tool’s modular structure, which was developed in Python with the Streamlit framework, also allows for other languages to be added, selection of the region’s grid mix, scenario comparisons, and results visualization in multi-level dashboards. Findings of the literature review show that the tool is accurate for both types of vehicles as the known lifecycle emissions ranges for both types are captured. Carbon payback periods for EVs ranged from less than three years to over eight years depending on the grid context, from renewable-rich to coal-intensive. Sensitivity analysis demonstrates that both grid CO₂ intensity and annual mileage hold the greatest influence over lifecycle results. This research contributes to sustainability as it fills the void that exists between academic LCA models and consumer-facing applications with a transparent, reproducible, and user-configurable decision-support tool. Improvements can be made by incorporating real-time grid emission data, expanding the vehicle datasets, and including additional CO₂ environmental impact categories. Y1 - 2025 ER - TY - THES A1 - Okos, Martin T1 - Ethische und rechtliche Rahmenbedingungen des Maschinellen Lernens - eine systematische Analyse zur Konzeptualisierung und Regulation innerhalb der EU N2 - Die Entwicklungen des maschinellen Lernens und damit einhergehend auch der künstlichen Intelligenz umfassen immer mehr Anwendungsfälle im täglichen Leben. Je komplexer und autonomer diese Systeme werden, desto schwieriger lässt sich ihr Verhalten prognostizieren und es ist nicht auszuschließen, dass Situationen entstehen, die ethische und rechtliche Fragen aufwerfen. Das Ziel dieser Arbeit ist die Untersuchung der erforderlichen Rahmenbedingungen für den Umgang mit diesen Technologien. Neben der Erklärung wesentlicher Begriffe aus dem Bereich der KI und Ethik werden durch die Recherche geeigneter Literatur über Pflegeroboter und dem autonomen Fahren zwei Anwendungsbereiche vorgestellt, die einen Bedarf an moralischen Maschinen aufweisen. Maßnahmen zur Regulierung innerhalb der Europäischen Union erfolgen durch das Anwenden bestehender und Erlassen neuer Gesetze sowie über die Definition ethischer Leitlinien, die ebenfalls als Teil der vorliegenden Arbeit behandelt werden. N2 - Developments in machine learning along with artificial intelligence are encompassing increasingly more use cases in everyday life. The more complex and autonomous these systems become, the harder it is to predict their behaviour, and it cannot be ruled out that situations emerge where ethical and legal questions arise. This thesis aims to investigate the necessary framework conditions for dealing with these technologies. In addition to explaining essential terminology from the domain of AI and ethics, two application areas that show a need for moral machines are presented by referencing contemporary literature on care robots and autonomous driving. The European Union provides regulatory measures by applying existing laws and enacting new ones, as well as by defining ethical guidelines, which are also addressed as part of this thesis. KW - Maschinelles Lernen KW - Künstliche Intelligenz KW - Ethik KW - Pflegeroboter KW - Autonomes Fahren Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:hbz:1383-opus4-15170 ER - TY - THES A1 - Salobir, Jan T1 - Relaunch eines Kommunalen Webauftritts beim KRZN N2 - In der Arbeit wird der Prozess des Relaunches eines kommunalen Webauftritts Schritt für Schritt analysiert und besonders darauf geachtet, wie die gesetzlichen Anforderungen für so einen Webauftritt umgesetzt werden. KW - E-Government KW - Onlinezugangsgesetz KW - Webauftritt KW - Verwaltungsinformatik KW - Verwaltungsdigitalisierung Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:hbz:1383-opus4-15214 ER - TY - THES A1 - Ponten, Marvin T1 - Visualisierung von Kulturgütern am Beispiel der römischen Kaiserthermen in Trier als 3D Modell. N2 - This paper is a summary of the “Kaiserthermen Project'' for the “Landesmuseum Trier” and shows in detail how to convert a 3Ds Max 3D model for usage into an open source program like Blender. It tries to explain the basics of 3D modelling and compares it to the 3D modelling of cultural heritages. It should work as a form of manual to further convert different models into the FBX file format. It also aims to explain the high value of cultural heritage as a 3D model and compares it to the 3D model of the “Trier Kaiserthermen”. It furthermore gives examples and reasons for the usage of 3D models in different fields. It also presents the final 3D renderings and shows how they were created. At the end it explains how the perfect model for scientific research should be and how this project and paper improved this for the “Kaiserthermen”. KW - 3D Model KW - Cultural Heritage KW - Converting to FBX KW - 3D Render Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:hbz:1383-opus4-15889 ER - TY - THES A1 - Scheil, Jonathan T1 - Analyse der aktuellen und vergangenen politischen Landschaft Deutschlands im Hinblick auf die aktuelle Bundestagswahl mit Fokus auf die ansteigende Bedeutung von Social-Media im Wahlkampf N2 - Since the last federal election in germany, the CDU is no longer the strongest force and suffered large losses of votes. The SPD, Bündnis 90/Die Grünen and the FDP now make up the german parliament. Parts of the election campaign are taking place via social media. But how do the individual parties use modern media? Do the parties differ in the way they communicate their messages and, as a result, do they generate votes in diffe-rent ways? I will examine these questions in more detail in this bachelor's thesis, starting with the reunification of germany and including the last federal elections. The social me-dia platform I am investigating for political communication is twitter. I presented the past and current parliamentary election results and differences in eastern and western germany. To do this, I used sentiment analysis to examine tweets extracted from twitter at the federal and local/state political level, for their content and the accom-panying reactions. I created a detailed representation of the different social media appearances of politicians and determined whether appropriate conclusions can be drawn based on my results and data. My analysis shows that at the parliamentary level, Annalena Baerbock of Bündnis 90/Die Grünen, followed by Dr. Alice Weidel of the AfD and Christian Lindner of the FDP, have the most likes and retweets. Olaf Scholz, with 826 tweets, is the most active on twitter in 2021. At federal and local/state level, the topics of all parties are often similar. There are differences with regard to the core issues of the respective parties. I have illustrated this in each case. Based on the politicians' use of twitter, I could not draw any concrete conclusions about voter behaviour. For this it would be important to evaluate other media, e.g. facebook. KW - Sentiment-analyse KW - Politik KW - Bundestagswahl KW - Ost-/Westdeutschland KW - Social Media Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:hbz:1383-opus4-13687 ER - TY - THES A1 - Vela, Gianfranco T1 - Anwendbarkeit des Gamification Frameworks Octalysis auf Multibankingapps N2 - Ziel der vorliegenden Abschlussarbeit war es, ausgewählte Multibankingapps anhand des von Yu-Kai Chou entworfenen Gamification Frameworks Octalysis (Y.-k. Chou, 2019) zu analysie- ren, um daraufhin eine Aussage über die Anwendbarkeit des Frameworks auf Multibankingapps treffen zu können. Mithilfe des Design Pattern Canvas (Žavcer u. a., 2015) wurde ein Arte- fakt geschaffen, welches Entwicklern solcher Apps erlaubt, die im Framework beschriebenen Core Drives auf die Anwendung abzustimmen. Die Anwendbarkeit des Frameworks wurde zwar durch die Analyse bestätigt, jedoch ergaben sich weitere Abhängigkeiten, welche grundlegend für eine erfolgreiche Anwendung sind. Darunter zählt beispielsweise die Offenheit der Nutzer gegenüber Finanzthemen. Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:hbz:1383-opus4-11349 ER - TY - THES A1 - Ali, Md Monsur T1 - Multi Languages Fake News Detection N2 - News is one type of information that has the potential to influence a large number of people. People have received news since the beginning of time through various birds, short letters, and other means. When newspapers were invented, information was available everywhere on paper. The news is no longer limited to paper-based platforms, thanks to the digitalization of online platforms. The online news platform is now available to read the news in a matter of seconds. As a result, news can easily connect people, and it is being used to spread fake news. Fake news is spread to gain attention for the wrong reasons. Different languages are used in our world to express our thoughts and feelings. There are specific materials for each language. The English language is the most studied topic when it comes to identifying fake news. Data and research resources are few in other languages, hence there is little research done. Of these, Bengali is one of the most widely spoken. Our ultimate goal is to create a tree that contains elements of both English and Bengali. Research on fake news and web scraping was used to get the language news data. Multilingual transformer models m-BERT and xlm-ROBERTa with long text or tokens are used to detect fake news (512 tokens or any token size). The two models were compared using two different datasets (with stop words and the other without) using three different fine-tuning freeze approaches (Freeze, No Freeze, and Freeze Embed). The results show that the dataset with stop words had a somewhat better performance than the dataset omitting stop words. The xlm-RoBERTa model outperforms the m-BERT model in terms of F1-score and accuracy. KW - NLP KW - Fake news KW - m-BERT KW - Multilingual KW - xlm-RoBERTa Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:hbz:1383-opus4-12762 ER - TY - THES A1 - Westermann, Beke T1 - Kryptowährung als Alternative zu herkömmlichem Geld – Aus ökologischer Sicht N2 - Seit 2009 das erste Mal der Bitcoin als Open-Source-Software veröffentlicht wurde, sind neue Kryptowährungen stetig dazu gekommen und weiterentwickelt worden. Einige Jahre später folgten Währungen wie Litecoin, Ripple und Ethereum. Inzwischen sind Kryptowährungen im Großteil der Welt legal und gelten in einigen Ländern bereits als offizielles Zahlungsmittel. Betrachtet man die weitere Entwicklung, stellt sich die Frage, ob Kryptowährungen eine funktionierende Alternative zu herkömmlichen Währungen bieten können, und ob diese unter aktuellen ökologischen Bedingungen tragbar wäre. Ziel ist es, die Frage zu beantworten, welche Kriterien Kryptowährungen erfüllen müssten, um weiterhin einen hohen Stellenwert einzunehmen. Es wird eine Literaturrecherche durchgeführt, welche die Funktionsweise und Problematik verschiedener Mining-Konzepte erklärt, und ökologische Daten analysiert. Dabei zeigt sich, dass es Ansätze zu ökologischen Kryptowährungen gibt, die noch in der Entwicklung sind. Kryptowährungen, die diese Aspekte nicht berücksichtigen, werden langfristig als Alternative ökologisch nicht tragbar sein. KW - Kryptowährung KW - Bargeld KW - Ökologie KW - Ökologischer Vergleich Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:hbz:1383-opus4-16758 ER - TY - THES A1 - Pramanik, Lukas T1 - Digitale Selbstwirksamkeit als Schlüssel zur Arbeitszufriedenheit im demographischen Wandel. Der Mediierende Effekt digitaler Selbstwirksamkeit auf die Beziehung zwischen Alter und Arbeitszufriedenheit. N2 - Die kontinuierliche Digitalisierung der Arbeitswelt führt zu immer schnelllebigeren und komplexeren Arbeitsumfeldern, welche auf der effektiven Nutzung von Informations- und Kommunikationstechnologien (IKT) beruhen. Arbeitsfelder transformieren und verdichten sich mit rasanter Geschwindigkeit. Parallel steigt das durchschnittliche Alter der arbeitnehmenden Population und die Arbeitszufriedenheit sinkt. Besonders betroffen sind Erwachsene gehobenen Alters. Da die Arbeitszufriedenheit als starker Prädiktor für die physische- und psychische Gesundheit der Arbeitnehmenden wirkt, ist es notwendig zu verstehen, welche Konstrukte auf die Arbeitszufriedenheit wirken. Die vorliegende Studie betrachtet daher die mediierende Wirkung der digitalen Selbstwirksamkeit auf die Beziehung zwischen Alter und Arbeitszufriedenheit. Es wurde eine online-Befragung mit 124 Arbeitnehmenden im Alter von 17-63 Jahren durchgeführt. Es wurde erwartet, dass steigendes Alter in einer negativen Beziehung zu Arbeitszufriedenheit und digitaler Selbstwirksamkeit steht. Zusätzlich wurde angenommen, dass digitale Selbstwirksamkeit positiv auf Arbeitszufriedenheit wirkt. Es wurde eine indirekte Mediation, mit einer negativen Wirkung von Alter auf Digitale Selbstwirksamkeit und einer positiven Wirkung von digitaler Selbstwirksamkeit auf Arbeitszufriedenheit identifiziert. Die Wirkung der Geschlechtsidentifikation als Störvariable konnte ausgeschlossen werden. Praktische und theoretische Implikationen werden diskutiert. KW - Digitale Selbstwirksamkeit KW - Digitalisierung KW - Demographie Wandel KW - Arbeitszufriedenheit Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:hbz:1383-opus4-17339 ER - TY - THES A1 - Akmal, Ali T1 - Development and control of G32 smart gas burner system N2 - Household appliances such as ovens and washing machines are essential in every household, to make it safe for potential users, the machine must be tested under extreme conditions to prove that even in case of malfunction no danger is posed, such tests are carried out after successfully building a system that is stable in essence. This research aims to develop a smart gas burning system built on reliable and secure communication channels bounded with the implemented protocol specifications. A close study of each protocol specifications as well as a bit-by-bit investigation is therefore performed, moreover, a full timing analysis of communicated data is also carried out to ensure validity and integrity of the data transmitted. It was found that logic analysis plays a very important role in constructing data frames that are accurate to the smallest time unit possible, such analysis was not possible using an old model oscilloscope, after successful construction, transmitting a predefined sequence of data successfully initiated the communication channel between all system components. With the implemented safety and security features, the system is safe to use, however, this does not make it ready for end users, this is merely a proof of concept that such system can be made smart. The results show that the microcontroller module implemented is very capable of giving the user the ability to control the system manually with attached knobs and wirelessly through the Access point server. Y1 - 2023 ER - TY - THES A1 - Gooren, Lutz T1 - Künstliche Intelligenz in einer Geodateninfrastruktur N2 - Künstliche Intelligenz in Form von neuronalen Netzen wird in der öffentlichen Verwaltung bislang wenig eingesetzt. Im Zuge der Digitalisierung im Bereich der öffentlichen Verwaltung müssen bestehende Datensätze, welche nicht- oder schwer maschinenlesbar sind, über offene Schnittstellen und Datenstandards bereitgestellt werden. Schätzungsweise 80 % der erfassten Daten sind in der öffentlichen Verwaltung nicht- oder schwer maschinenlesbar. In dieser Arbeit soll geprüft werden, ob ein künstliches neuronales Netz, welches auf der ImageNet Datenbank basiert und durch weitere Beispiele trainiert worden ist, bestehende (nicht-maschinenlesbare) Datensätze in Tabellenform aus dem Bereich der Geoinformatik erkennen und in einer passenden Datei mit offenem Datenstandard (teil-)automatisiert speichern kann, um diese für den Einsatz in einer offenen urbanen Datenplattform vorzubereiten. Zudem werden Optimierungsvorschläge für eine Verbesserung des neuronalen Netzes genannt und umgesetzt. Im Laufe der Arbeit ergibt sich, dass das trainierte Modell für den praktischen Einsatz nicht ausreichend genau funktioniert, aber eine gute Basis für weitere Optimierungen liefert, etwa durch eine Vergrößerung des Trainingsdatensatzes, welche die Anforderung einer Steigerung der Rechenleistung voraussetzt. KW - Geodateninfrastruktur KW - Digitalisierung KW - Künstliche Intelligenz KW - Computer Vision KW - Tabellenerkennung Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:hbz:1383-opus4-17005 ER - TY - THES A1 - Afzal, Umair T1 - AI-Driven Comic Generation: Exploring the Creative Potential of Generative AI in Digital Storytelling N2 - 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. KW - AI-driven comics KW - Generative Adversarial Networks KW - Stable Diffusion KW - Automated storytelling KW - Speech bubble optimization KW - Image synthesis KW - Digital content creation. Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:hbz:1383-opus4-22581 ER - TY - THES A1 - Süyrüge, Eyüp T1 - Vergleich von FPGA und Mikrocontroller für die Echtzeitverarbeitung von Audiosignalen zur Richtungserkennung mittels FFT und TDOA einschließlich LED-basierter Visualisierung N2 - 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 dafür ein Field Programmable Gate Array (FPGA) und ein Mikrocontroller (MCU) eingesetzt. Dabei konzentriert sich die Arbeit auf die Untersuchung der beiden Plattformen, wobei die Leistungsfähigkeit, 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. KW - FPGA KW - Mikrocontroller KW - Echtzeitverarbeitung KW - Audiosignale KW - FFT KW - TDOA Y1 - 2026 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:hbz:1383-opus4-23229 ER - TY - THES A1 - Müsch, Yannick T1 - Kolmogorov-Arnold-Transformer: Untersuchung hybrider KAN-Transformer-Architekturen im Hinblick auf Skalierung, Effizienz und Interpretierbarkeit N2 - 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. KW - Kolmogorov-Arnold Networks KW - Transformer KW - hybrid architectures KW - naturallanguage processing KW - language modeling KW - interpretability KW - scaling KW - sparsity KW - B-splines Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:hbz:1383-opus4-23376 ER -