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  <doc>
    <id>289</id>
    <completedYear/>
    <publishedYear>2018</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>bachelorthesis</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2018-09-19</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>2018-08-29</thesisDateAccepted>
    <title language="eng">FinTechs in Germany - Current Status and Potential Impact on the Financial System</title>
    <abstract language="eng">The development of technologies that created FinTechs have brought new possibilities for customers into life that provide a quick and convenient handling of operations by covering various segments of the financial industry. However, the innovations also implicate drawbacks: Traditional banks may be threatened due to a loss of customers. This thesis evaluates to which extent this case can be measured by executing quantitative research methods as well as qualitative research methods for the purpose of gaining information from a bank’s perspective as well as opinions from customers. The result of this empirical study is that there is a certain correlation between the development of FinTechs and a threat caused by FinTechs although the latter is rather weak. Furthermore, this thesis indicates the knowledge of customers regarding FinTechs and their willingness to face said innovations.</abstract>
    <licence>CC BY-ND 4.0 International - Namensnennung-Keine Bearbeitungen</licence>
    <author>Nina Tangyue Schlossarek</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>FinTech</value>
    </subject>
    <collection role="institutes" number="">Fakultät Kommunikation und Umwelt</collection>
    <thesisPublisher>Hochschule Rhein-Waal</thesisPublisher>
    <thesisGrantor>Hochschule Rhein-Waal</thesisGrantor>
  </doc>
  <doc>
    <id>189</id>
    <completedYear/>
    <publishedYear>2017</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>masterthesis</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2017-12-05</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>2017-10-27</thesisDateAccepted>
    <title language="eng">Workload Prediction using Apache Spark and R in a Mainframe Operating System</title>
    <abstract language="eng">This master thesis presents a machine learning approach using the distributed data- processing framework Apache Spark and the programming language R. The aim is to predict the time series of the Appl Percentage (ApplPerc) from the workload manager of the z/OS mainframe system using SMF 72.3 and SMF 70.1 records as input. System Management Facility (SMF) data are binary log files that are used to collect system performance data and information about system behaviour. The SMFs show how Apache Spark can be used for the pre-processing. This includes data collection, data extraction, and data selection. The machine learning algorithms are implemented in R. The input SMF datasets will be split into training and test data, and thereby applied to different machine learning and deep learning models such as random forest regression, recurrent neural network, and k-nearest neighbor regression to predict the ApplPerc. The validation of the prediction models will be proved by using cross-validation techniques to evaluate the best applied parameters for each model and therefore to locate the model with the best performance. The process of data analysis is followed by a data-mining methodology called Cross-Industry Standard Process for Data Mining (CRISP-DM), which outlines the steps involved in performing the analysis.</abstract>
    <author>Daniel Röchert</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Machine learning</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Deep learning</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Prediction</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Workload management</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Apache Spark</value>
    </subject>
    <collection role="ddc" number="004">Datenverarbeitung; Informatik</collection>
    <collection role="institutes" number="">Fakultät Kommunikation und Umwelt</collection>
    <thesisPublisher>Hochschule Rhein-Waal</thesisPublisher>
    <thesisGrantor>Hochschule Rhein-Waal</thesisGrantor>
  </doc>
  <doc>
    <id>1821</id>
    <completedYear/>
    <publishedYear>2023</publishedYear>
    <thesisYearAccepted/>
    <language>deu</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>bachelorthesis</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2023-10-30</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>2023-09-11</thesisDateAccepted>
    <title language="deu">Künstliche Intelligenz und nachhaltiger Fast Fashion im E-Commerce - Machbarkeitsanalyse und qualitative Analyse zur kognitiven Dissonanz der Konsumenten</title>
    <abstract language="eng">This thesis deals with the consumer purchasing behavior in the fast fashion segment. The central focus includes analyzing factors such as purchase intention, e-commerce trade, consequences and environmental impacts. The first section defines terms and compares current studies to each other. This is followed by a methodical discussion. In order to assess consumer purchasing behavior, semi-structured interviews were conducted, and digital diary entries were written by participants from generation Y and Z. Based on these results shopper types were identified.</abstract>
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    <licence>CC BY 4.0 International - Namensnennung</licence>
    <author>Harriha Krishnamoorthy</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Fast Fashion</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Consumption</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>E-commerce</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Generation Y and Z</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Environment</value>
    </subject>
    <collection role="institutes" number="">Fakultät Kommunikation und Umwelt</collection>
    <thesisPublisher>Hochschule Rhein-Waal</thesisPublisher>
    <thesisGrantor>Hochschule Rhein-Waal</thesisGrantor>
  </doc>
  <doc>
    <id>2181</id>
    <completedYear>2025</completedYear>
    <publishedYear>2025</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>bachelorthesis</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Opportunities and challenges for the solar industry in Lebanon.</title>
    <abstract language="eng">Lebanon faces a significant energy crisis characterized by unreliable electricity supply, political instability, and outdated infrastructure. This thesis explores the potential of solar energy as a sustainable solution to address these challenges, focusing on economic, technical, and regulatory barriers while drawing comparative insights from Cyprus’s renewable energy model.&#13;
&#13;
The research examines three primary questions regarding the economic and technical challenges hindering solar energy adoption in Lebanon, the lessons that can be learned from Cyprus to inform solutions, and the comprehensive strategies that can support the development of Lebanon’s solar energy sector.&#13;
&#13;
The findings reveal that while Lebanon has experienced rapid growth in solar energy adoption, the sector is undermined by systemic issues such as low-quality imports, skill gaps, insufficient grid infrastructure, and the dominance of diesel generators. Comparative analysis with Cyprus underscores the importance of robust regulatory frameworks, financial accessibility, public-private partnerships, and accreditation systems for solar installers. Additionally, the analysis highlights the critical role of improving capacity factors in Lebanon, with findings showing that even a 1% increase could supply power to over 16,000 homes, emphasizing the potential efficiency gains for Lebanon’s solar energy sector.&#13;
&#13;
The thesis also evaluates Lebanon’s progress toward its 2030 renewable energy targets, noting that while the country appears to have met these targets in percentage terms, the achievement is largely a result of reduced electricity generation rather than genuine renewable capacity growth.&#13;
&#13;
Recommendations include enforcing quality standards, establishing national accreditation systems, addressing corruption, and leveraging international funding for infrastructure modernization and workforce development.&#13;
&#13;
This research emphasizes that Lebanon’s transition to renewable energy is not only a technical and economic endeavor but also a pathway to greater energy independence and environmental sustainability.</abstract>
    <enrichment key="opus.import.date">2025-04-02T14:07:50+00:00</enrichment>
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    <licence>CC BY 4.0 International - Namensnennung</licence>
    <author>Ziad Helou</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Solar energy</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Renewable energy</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Capacity factor</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Grid modernization</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Energy policy</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Lebanon energy crisis</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Solar photovoltaics</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Energy transition</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Distributed energy systems</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Solar market regulation</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Energy storage</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Microgrid integration</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Power grid stability</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Reverse current flow</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Islanding effect</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Net metering</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Sustainable development</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Public-private partnerships</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Solar waste management</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Energy infrastructure</value>
    </subject>
    <collection role="institutes" number="">Fakultät Kommunikation und Umwelt</collection>
    <collection role="Import" number="import">Import</collection>
    <thesisPublisher>Hochschule Rhein-Waal</thesisPublisher>
    <thesisGrantor>Hochschule Rhein-Waal</thesisGrantor>
  </doc>
  <doc>
    <id>2144</id>
    <completedYear>2025</completedYear>
    <publishedYear>2025</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>masterthesis</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Development of an ML-based multivariate anomaly detection model for beehive monitoring using sensor and environmental data.</title>
    <abstract language="eng">Anomaly detection is an important aspect of beehive monitoring, enabling beekeepers to take timely action and preventing economic losses caused by the decline of the bee population. Most existing beehive monitoring systems lack machine learning (ML) capabilities for anomaly detection and rely on threshold-based methods or expensive, complex designs. This thesis utilized the DigiBee prototype, a cost- effective monitoring system, to develop an ML-based anomaly detection model using Isolation Forest. Data on temperature, humidity, sound, vibration, and weight from four active beehives was collected between May 1, 2024, and July 25, 2024, alongside environmental data—temperature, relative humidity, and precipitation—from nearby meteorological stations. Exploratory data analysis revealed several limitations: uniform outputs from vibration sensors, calibration errors in weight sensors, and multiple gaps during the data collection period. Correlation analysis indicated a limited influence of external weather variables on internal beehive conditions, while internal sensor parameters displayed stronger correlations with each other. Five models were developed, using either beehive data alone or a combination of beehive and weather data. Results showed that beehive-specific models achieved higher accuracy in detecting localized anomalies, whereas models combining data from multiple beehives generalized better but underrepresented hive-specific issues. Models incorporating weather parameters, especially precipitation, introduced noise and unnecessary dimensions, which, when excluded, improved the model’s prediction by focusing on hive-specific patterns and ensuring anomaly detection remained contextually relevant.</abstract>
    <enrichment key="opus.import.date">2025-02-12T12:37:19+00:00</enrichment>
    <enrichment key="opus.source">sword</enrichment>
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    <licence>Bestimmungen des deutschen Urheberrechts</licence>
    <author>Zaid Saleem Syed</author>
    <collection role="Import" number="import">Import</collection>
    <thesisPublisher>Hochschule Rhein-Waal</thesisPublisher>
    <thesisGrantor>Hochschule Rhein-Waal</thesisGrantor>
  </doc>
  <doc>
    <id>1864</id>
    <completedYear/>
    <publishedYear>2023</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>masterthesis</type>
    <publisherName/>
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    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2024-01-08</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>2023-11-17</thesisDateAccepted>
    <title language="eng">API Driven Form Rendering</title>
    <abstract language="eng">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.&#13;
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.&#13;
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.&#13;
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.&#13;
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&#13;
a robust solution for dynamic form rendering, thereby enhancing both user satisfaction and system performance in the fast-evolving digital landscape.</abstract>
    <enrichment key="opus.source">publish</enrichment>
    <licence>CC BY-NC 4.0 International - Namensnennung-Nicht kommerziell</licence>
    <author>Ahmed Hanafy</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Dynamic Form Rendering</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>API-Driven Architecture</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Retail Software Integration</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>User Interface Efficiency</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Product Information Management</value>
    </subject>
    <collection role="institutes" number="">Fakultät Kommunikation und Umwelt</collection>
    <thesisPublisher>Hochschule Rhein-Waal</thesisPublisher>
    <thesisGrantor>Hochschule Rhein-Waal</thesisGrantor>
  </doc>
  <doc>
    <id>2091</id>
    <completedYear/>
    <publishedYear>2024</publishedYear>
    <thesisYearAccepted/>
    <language>deu</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>bachelorthesis</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2024-11-05</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>2024-09-09</thesisDateAccepted>
    <title language="deu">Künstliche Intelligenz zur Vorhersage von Kreditentscheidungen</title>
    <abstract language="deu">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.</abstract>
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    <licence>CC BY-NC-ND 4.0 International - Namensnennung-Nicht kommerziell-Keine Bearbeitungen</licence>
    <author>Marius Nacke</author>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Kreditvergleichsportale</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Prognosen</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Künstliche Intelligenz</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Ensemble-Modelle</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Kreditentscheidungen</value>
    </subject>
    <collection role="institutes" number="">Fakultät Kommunikation und Umwelt</collection>
    <thesisPublisher>Hochschule Rhein-Waal</thesisPublisher>
    <thesisGrantor>Hochschule Rhein-Waal</thesisGrantor>
  </doc>
  <doc>
    <id>2025</id>
    <completedYear/>
    <publishedYear>2024</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>masterthesis</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2024-08-16</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>2024-06-05</thesisDateAccepted>
    <title language="eng">Data Analysis of the "Loyalty Program-Valeo Specialist Club" to Improve the  Independent Aftermarket: Designing an Efficient Marketing Strategy</title>
    <abstract language="eng">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.</abstract>
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    <licence>CC BY-NC-ND 4.0 International - Namensnennung-Nicht kommerziell-Keine Bearbeitungen</licence>
    <author>Most Sarmin Akter</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Loyalty Program</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Insights</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Member Loyalty</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Marketing</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Valeo Specialist Club</value>
    </subject>
    <collection role="institutes" number="">Fakultät Kommunikation und Umwelt</collection>
    <thesisPublisher>Hochschule Rhein-Waal</thesisPublisher>
    <thesisGrantor>Hochschule Rhein-Waal</thesisGrantor>
  </doc>
  <doc>
    <id>2249</id>
    <completedYear>2025</completedYear>
    <publishedYear>2025</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
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    <issue/>
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    <publisherName/>
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    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Development of a Web-Based Tool for Estimating Lifecycle CO₂ Emissions of Electric vs. Diesel Vehicles in Germany</title>
    <abstract language="eng">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.&#13;
&#13;
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.&#13;
&#13;
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.&#13;
&#13;
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.</abstract>
    <enrichment key="opus.import.date">2025-08-26T10:36:02+00:00</enrichment>
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    <licence>Bestimmungen des deutschen Urheberrechts</licence>
    <author>Aya Boulmane</author>
    <collection role="institutes" number="">Fakultät Kommunikation und Umwelt</collection>
    <collection role="Import" number="import">Import</collection>
    <thesisPublisher>Hochschule Rhein-Waal</thesisPublisher>
    <thesisGrantor>Hochschule Rhein-Waal</thesisGrantor>
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    <publishedYear>2023</publishedYear>
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    <language>eng</language>
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    <type>bachelorthesis</type>
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    <completedDate>2023-05-04</completedDate>
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    <title language="eng">Development and control of G32 smart gas burner system</title>
    <abstract language="eng">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.</abstract>
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    <licence>CC BY-NC-SA 4.0 International - Namensnennung-Nicht kommerziell-Weitergabe unter gleichen Bedingungen</licence>
    <author>Ali Akmal</author>
    <collection role="institutes" number="">Fakultät Kommunikation und Umwelt</collection>
    <thesisPublisher>Hochschule Rhein-Waal</thesisPublisher>
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