@misc{SarmientoGonzalez2025, type = {Master Thesis}, author = {Sarmiento Gonzalez, Maria Angelica}, title = {Sustainable commercialization of Baru in the Cerrado: mapping its Value Chain for rural livelihood enhancement}, school = {Hochschule Rhein-Waal}, year = {2025}, abstract = {Land-use transformation and insufficiently protected areas have led to extensive deforestation and conversion of native vegetation for croplands and pastures in the Cerrado, Brazil's second-largest ecosystem and one of the world's biggest biodiversity hotspots. The sustainable harvesting and commercialization of non-timber forest products (NTFPs) offer a potential alternative, contributing to sustainable development by enhancing rural livelihoods, promoting environmental conservation, fostering economic diversification, empowering vulnerable socio-economic groups, and encouraging sustainable resource management. Among Cerrado's promising NTFPs is the Baru nut (Dipteryx alata), a nutrient-dense product rich in protein, fiber, zinc, and healthy oils, with potential therapeutic applications for various health issues. Its unique composition and versatility present an opportunity for sustainable commercialization that enhances rural livelihoods while promoting health benefits. Incorporating Baru-related products into local, national, and international markets could diversify economic opportunities while maintaining environmentally sustainable practices in both production and commercialization. Despite its potential, research on Baru remains scarce, creating a knowledge gap in the dynamics and challenges of its value chain. This study addresses this gap by employing a mixed-methods approach to evaluate the financial performance of each stage of the Baru value chain and identify existing challenges and market opportunities. Focused on Arinos, Minas Gerais, the research incorporates 29 interviews with local value chain actors, 14 supplementary interviews with institutional stakeholders, and secondary data analysis. The findings reveal a fragmented and predominantly informal value chain at the local level, faced with challenges such as physically intensive work, unreliable demand, power imbalances, low-profit margins, and limited institutional support. This research proposes strategies to foster collaboration, equity, transparency, and sustainable development of Baru's value chain and contributes to a deeper understanding of this NTFP.}, language = {en} } @misc{Yarram2025, type = {Master Thesis}, author = {Yarram, Sunnyvijay}, title = {Investigation of Anaerobic Digestion of Selected Bioplastics in Pilot-Scale Biodigesters}, url = {http://nbn-resolving.de/urn:nbn:de:hbz:1383-opus4-21673}, school = {Hochschule Rhein-Waal}, pages = {102}, year = {2025}, abstract = {Concerns have been raised about the end-of-life management of bioplastics as their demand increasing as a sustainable alternative to conventional plastics. The fate of bioplastic waste, especially packaging waste, remains largely unexplored in existing waste management systems. Anaerobic digestion (AD) is considered as a viable end-of-life option for bioplastics, however, current research has been primarily limited to lab-scale studies. This study investigated the anaerobic digestion of film samples made from Bioplast 106, PBAT, PLA and Ecovio (PLA/PBAT blend) under mesophilic and thermophilic conditions in pilot-scale biodigesters. The results of 90-day thermophilic AD demonstrated that PLA and Ecovio exhibited significant biodegradation of 36\% and 50\% by dry mass loss, respectively, while Bioplast 106 exhibited moderate biodegradation of 22.22\%. The collective methane yield from these three bioplastics was 322.86 mL CH4/g VS, indicating their potential for biogas production. SEM and FT-IR analyses confirmed structural degradation of Bioplast 106, PLA, and Ecovio, while no degradation was observed for PBAT. PBAT showed high resistance to AD in pure and blended form (Bioplast 106, Ecovio). Bioplast 106 exhibited diverse degradation patterns, influenced by feedstock type, digester temperature, and processing conditions. This study might serves as valuable reference for assessing the anaerobic biodegradability of Bioplast 106 in pilot-scale biodigesters. This study further highlights the necessity of optimization of pilot-scale AD conditions to enhance the anaerobic biodegradability of slow-degrading bioplastics.}, language = {en} } @misc{Pozdnyakova2025, type = {Master Thesis}, author = {Pozdnyakova, Olga}, title = {Exploring the Impact of Ecolabel Elements on Consumer Product Perception and Purchase Intention}, school = {Hochschule Rhein-Waal}, year = {2025}, abstract = {Ecolabelling is a tool that aims to engage consumers in making more sustainable choices, by communicating the environmental characteristics of a product. Previous studies have emphasized the significant impact of design and ecolabel elements in capturing consumers' attention and influencing their preferences. However, only a limited number of studies have explored the effect of individual ecolabel elements and their orchestration in regard to visual attention and consumers perception, particularly in the context of textile products. The aim of the present study was to provide new insights into effective ecolabel design practices by investigating the influence of color, visual symbol, and text on consumers' visual attention, environmental product perception and purchase intention. The current study employed a mixed method approach, combining quantitative and qualitative methods. The integrated methods included a review of existing ecolabels in the textile industry, an eye tracking experiment with sixteen custom-designed ecolabels, questionnaires, interviews, and a card sorting task. Visual attention was measured with the eye tracking, while other methods were employed to deepen the understanding of consumers' perception and reasoning behind their decision-making. The results of the study revealed that the green ecolabels with natural symbols, such as Cotton and Leaf, received the highest environmental friendliness and purchase intention ratings, with the green Cotton ecolabel demonstrating the highest rate of visual attention engagement. In contrast, blue ecolabels were perceived as less environmentally friendly, particularly those with the visual symbols unrelated to nature. In addition, precise environmental claims with numerical data, such as "90\% Organic cotton", in combination with a website link, had a positive impact on trust and environmental perception. However, their role in visual attention and environmental perception was found to be less significant compared to the color and visual symbol. The findings contribute to textile research, highlighting the importance of the ecolabel context, visual symbol and color in ecolabel design, and providing new insights about visual attention patterns. The study outlines practical recommendations that can be utilized by professionals developing or redesigning ecolabels, in order to effectively communicate the characteristics of sustainable products.}, language = {en} } @misc{Rostalski2025, type = {Master Thesis}, author = {Rostalski, Sarah-Maria}, title = {Radio Astronomy Essentials: Calibration Techniques with the 2.3m Radio Telescope at Rhine-Waal University}, url = {http://nbn-resolving.de/urn:nbn:de:hbz:1383-opus4-21533}, school = {Hochschule Rhein-Waal}, pages = {88}, year = {2025}, abstract = {This thesis discusses calibration and, in this context, multiple ways of determining the system temperature of the 2.3-metre radio telescope at Rhine-Waal University of Applied Sciences in Kamp-Lintfort. Two methods for determining the system temperature are described here: the hot/cold-method and the derivation from the radiometer equation using measurement data from a source with a known brightness temperature, in this case, S7. Both methods deliver different results, depending on the measurements and assumptions on which they are based. The results show that the data basis and uncertainties should always be considered when analysing the observational data to be able to evaluate the results correctly. Overall, the telescope is quite suitable for educational observations, especially of the 21-cm line of neutral hydrogen. Furthermore, instructions have been created for the various tasks so that the results are reproducible and comprehensible. The entire process is made transparent, from planning the observations and setting up the telescope to measuring and analysing the data. In addition, basic concepts of radio astronomy are described in theory to provide valuable background knowledge. On this basis, the use of the telescope enables students and amateur astronomers to understand and apply the basic principles of radio astronomy and to plan and carry out their own observations.}, language = {en} } @misc{Syed2025, type = {Master Thesis}, author = {Syed, Zaid Saleem}, title = {Development of an ML-based multivariate anomaly detection model for beehive monitoring using sensor and environmental data.}, school = {Hochschule Rhein-Waal}, year = {2025}, abstract = {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.}, language = {en} } @misc{Bhattarai, type = {Master Thesis}, author = {Bhattarai, Anish}, title = {Digitizing the Bait Lamina Method: Facilitating Autonomous Learning and Data Processing in Ecological Research}, school = {Hochschule Rhein-Waal}, abstract = {In recent years, digital tools in soil science have evolved to modernize and streamline traditional approaches by fostering greater learning engagement and enhancing accessibility. The primary goal of this research is to create an application that intends to facilitate autonomous learning while streamlining data processing, visualization, and reporting for the Bait Lamina Method (BLM). Advanced technologies such as React.js, Tailwind CSS, Vite.js, and several Node.js modules were used to implement essential functionalities. Moreover, to ensure smooth and scalable app delivery, Docker was employed. Furthermore, thorough usability testing was carried out with students from both the school and university to create a sturdy app that satisfies the needs and standards of users. This research utilized a mixed-methods approach to evaluate the app's overall usability, emphasizing efficiency, learnability, dependability, and overall satisfaction. Quantitative analysis included phi coefficient correlation, chi-square testing, and multiple ordinary least squares (OLS) regression to measure overall usability and user satisfaction. Meanwhile, qualitative approaches such as theme and sentiment analysis were used to get insight into user experiences, preferences, difficulties, and ideas for improvement. The study demonstrated that understanding the method is a key driver influencing student satisfaction. Therefore, the Bait Lamina App (BLA) immensely facilitated autonomous learning while speeding up data processing, visualization, and administration for the BLM. However, a few small faults and student comments were integrated into the BLA, which improved its use and satisfaction.}, language = {en} } @misc{Mandal, type = {Master Thesis}, author = {Mandal, Prashant}, title = {Comparative Lifecycle Assessment (LCA) Of Tomato Production in Spain and Northern Germany}, school = {Hochschule Rhein-Waal}, abstract = {The environmental impact of year-round greenhouse vegetable production, particularly in high latitude region such as the Emsland district in Lower Saxony, Germany, has raised concerns. It has latitude 52,362324 and longitude 7,269548 with temperature from 10°C to 25 in summer and temperature ranges from -1°C to 7°C in winter. In this context, two gardens with different climatic conditions, represented by the gardeners DE from Germany and ES from Spain, were considered. The latter is located at latitude 41,39467 and longitude 2,157998, with summer temperatures ranging from 20 to 30°C and winter temperatures from 10 to 15°C. Greenhouse vegetable production requires significant energy inputs for heating and lighting, particularly during the winter months. However, the environmental implications of using renewable energy sources like hydroelectricity and the effects of other production strategies on the environment have not been adequately investigated. To address this knowledge gap, a life cycle assessment (LCA) of greenhouse tomato production for year-round production in 2022 has been conducted, including processes from seedling planting in a pre-build greenhouse structure to distribution at two locations: the ES Gardner in Spain and the DE Gardner in Germany. The study used the OpenLCA software and followed the ReCipe 2016 Mid-Point (H) impact assessment methodology. Our analysis revealed that, across the two main production seasons, the highest global warming potential (GW) was observed during year-round production in Spain. The following aspects were discovered to have a significant influence on the environmental impact: Packaging material, transportation, heating systems, electricity, land usage, and irrigation methods. Overall, it was determined that year-round production in Germany had the least detrimental environmental impact among the examined production types. The use of packaging material, electricity for heating the greenhouse and transportation was the primary contributor to most of the impact categories. Conversely, the application of fertilizers and manures during extended seasonal and year-round production had a lower environmental impact.}, language = {en} } @misc{Teresa, type = {Master Thesis}, author = {Teresa, Z{\"o}bel}, title = {Die Rolle individueller Copingstrategien und Resilienz f{\"u}r die mentale Gesundheit im Kontext der Wahrnehmung der Klimakrise: Eine systematische Untersuchung empirischer Studien}, school = {Hochschule Rhein-Waal}, abstract = {Hintergrund: Der Klimawandel ist ein globales Problem, welches bereits weltweit sp{\"u}rbar ist und sich zuk{\"u}nftig weiter versch{\"a}rfen wird. Neben den damit einhergehenden physischen Auswirkungen f{\"u}r die Gesundheit, steigt auch die Relevanz mentaler Belastungen. Nicht nur das Erleben von Naturkatastrophen und extremen Wetterereignissen, sondern auch die Wahrnehmungen der Ver{\"a}nderungen wirkt bedrohlich und kann eine mentale Belastung f{\"u}r Menschen darstellen. Ziel der Masterarbeit war es zu untersuchen, welche Rolle individuelle Copingstrategien und Resilienz f{\"u}r die mentale Gesundheit und das Wohlbefinden im Kontext der Wahrnehmung der Klimakrise haben. Wesentlich war daher die Identifikation potenzieller Schutz- und Risikofaktoren sowie die Untersuchung von Copingstrategien im Kontext des Klimawandels, um gezielte Empfehlungen zur St{\"a}rkung der Resilienz und Verbesserung des psychischen Wohlbefindens abzuleiten. Methoden: Eine systematische Literaturrecherche wurde durchgef{\"u}hrt, um relevante, empirische Studien zu identifizieren. Das methodische Vorgehen orientierte sich an den Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). Die Suche erfolgte auf den Datenbanken Web of Science, ScienceDirect, PubPsych, PubMed und PsycArticles. Zur Bewertung der methodischen Qualit{\"a}t und Bewertung des Verzerrungspotenzials der eingeschlossenen Studien, wurden die Critical Appraisal Checklisten des Joanna Briggs Instituts (JBI) verwendet. Die Ergebnisse der Studien wurden anhand zweier Evidenztabellen nach Studiendesign und Studienergebnissen synthetisiert und narrativ beschrieben. Ergebnisse: Insgesamt erf{\"u}llten 19 von 1.676 gepr{\"u}ften Studien die Einschlusskriterien. Die Studien untersuchten unterschiedliche Copingstrategien und -stile, wie Verhaltensweisen des umweltfreundlichen Handelns sowie problem-, emotions- und bedeutungsorientierte Bew{\"a}ltigungsstrategien. Verschiedene Faktoren wurden ber{\"u}cksichtigt, darunter emotionale Reaktionen, psychologische, soziale und kognitive Aspekte sowie soziodemografische Eigenschaften. Zun{\"a}chst wurde untersucht, wie Copingstrategien in Verbindung mit den einbezogenen Faktoren stehen. Darauf aufbauend wurde analysiert, wie diese Copingstrategien die mentale Gesundheit beeinflussen und ob die Faktoren im Kontext des Klimawandels als Schutz- oder Risikofaktoren wirken. Beispielsweise zeigten leichte Auspr{\"a}gungen der Angst vor dem Klimawandel sowohl aktivierende Effekte, in Form von umweltfreundlichen Verhaltensweisen, als auch die Neigung zu mentalen Beeintr{\"a}chtigungen, bei starker Auspr{\"a}gung. Sorgen zeigten im Studienvergleich gemischte Auswirkungen, indem sie teilweise problemorientiertes Coping beg{\"u}nstigten, teilweise jedoch auch belastend wirkten. Wut zeigte vorwiegend aktivierende Effekte und weniger Beeintr{\"a}chtigungen f{\"u}r die mentale Gesundheit. Naturverbundenheit, Geschlecht und Alter standen oftmals mit problemorientiertem Coping in Verbindung, jedoch gleichzeitig mit einer erh{\"o}hten Anf{\"a}lligkeit f{\"u}r mentale Beeintr{\"a}chtigung. Daneben wurden zwei Studien identifiziert, die unterschiedliche Maßnahmen zur Reduktion der mentalen Belastungen durch den Klimawandel evaluierten und bei relevanten Parametern der mentalen Gesundheit positive Ergebnisse erzielten. Schlussfolgerung: Es besteht verst{\"a}rkter Forschungsbedarf, um die mentalen Auswirkungen im Kontext der Wahrnehmung des Klimawandels besser zu verstehen und wirksame Maßnahmen zur F{\"o}rderung der mentalen Gesundheit zu entwickeln. Ein einheitliches Verst{\"a}ndnis der untersuchten Konstrukte ist dabei entscheidend, um eine Vergleichbarkeit zwischen den Studien zu gew{\"a}hrleisten und gesicherte Erkenntnisse zu gewinnen. Damit kann die Entwicklung zielgerichteter Maßnahmen und die F{\"o}rderung von pers{\"o}nlichen Ressourcen sowie adaptives Coping im Zusammenhang mit der Klimakrise unterst{\"u}tzt werden.}, language = {de} } @misc{Mashaba, type = {Master Thesis}, author = {Mashaba, Ismat Jahan}, title = {Comparative Analysis of Waste Management Challenges and Strategies: A Case Study of Dhaka, Bangladesh, and Beijing.}, school = {Hochschule Rhein-Waal}, abstract = {The paper emphasizes the importance of effective waste management for sustainable development, highlighting the challenges faced by Dhaka, mainly due to inadequate infrastructure, poor public awareness, and insufficient governmental support. The rapid urbanization and population growth in Dhaka exacerbate these issues, leading to severe environmental and public health risks. The study compares the waste management systems of Dhaka and Beijing. A survey was conducted to understand the attitude and awareness of the residents of Dhaka, and secondary data was considered to provide an overview of the existing waste management policies and practices of both Dhaka and Beijing. The findings of the paper outline several recommendations for improving waste management in Dhaka. However, the study also identifies several challenges, including inadequate infrastructure, insufficient governmental support and so on. In summary, the research highlights the significance of efficient waste management systems in metropolitan regions, especially in developing nations, and promotes a comprehensive strategy to tackle the difficulties encountered by cities such as Dhaka.}, language = {en} } @misc{Bongers, type = {Master Thesis}, author = {Bongers, Lena}, title = {{\"U}ber die Gesundheitskompetenz als individuelle Ressource f{\"u}r das Gesundheitsverhalten und Stresserleben von Akteurinnen und Akteuren in Gesundheitsfachberufen in Deutschland mit Handlungsempfehlung}, url = {http://nbn-resolving.de/urn:nbn:de:hbz:1383-opus4-20848}, school = {Hochschule Rhein-Waal}, pages = {193}, abstract = {Einleitung: Gesundheitskompetentes Personal bildet die Grundlage f{\"u}r gesundheitskompetente Ge-sundheitsorganisationen. Im Rahmen der Vorbildfunktion wird erwartet, dass Berufst{\"a}tige der Ge-sundheitsprofessionen eine hohe Gesundheitskompetenz aufweisen und sich entsprechend gesund-heitsf{\"o}rderlich verhalten. In einer zunehmend belastenden Arbeitswelt sind individuelle Ressourcen entscheidend f{\"u}r die Gesundheit und das Stresserleben des Gesundheitsfachpersonals. In der vorlie-genden Arbeit soll untersucht werden, inwieweit die Faktoren „gesundheitsbezogenes Verhalten" und „Stresserleben" durch das Level der Gesundheitskompetenz in Gesundheitsfachberufen beeinflusst wird. Da das berufliche Belastungsspektrum von Physiotherapeut:innen und Pflegekr{\"a}ften teilweise vergleichbar ist, wird in dieser Masterarbeit im Sinne einer quasi-explorativen Querschnittsstudie ein Vergleich zwischen diesen Gesundheitsfachberufen gezogen. Methodik: Zur Erhebung der Daten wurde vom 12.02.2024 bis 11.03.2024 eine quantitative Online-Umfrage durchgef{\"u}hrt. Dazu wurden aktuell t{\"a}tige und examinierte Pflegekr{\"a}fte und Physiotherapeut:innen ab 18 Jahren mittels Schnee-ballverfahren rekrutiert. Zur Erhebung der Gesundheitskompetenz wurde der Fragebogen HLS19-Q12-DE verwendet, sowie einzelne Skalen des COPSOQ und dem SOC-L9 zur Erfassung des Stres-serlebens und des Koh{\"a}renzgef{\"u}hls. Dar{\"u}ber hinaus wurden einzelne Items aus der GEDA-Studie 2019 des Robert Koch- Instituts zur Erfassung des gesundheitsbezogenen Verhaltens einbezogen. Zur Datenauswertung wurden uni- und bivariate deskriptive Analysen vorgenommen, aber keine R{\"u}ck-schl{\"u}sse auf die Grundgesamtheit gezogen. Ergebnisse: Im Rahmen der Fragebogenerhebung konnte eine Stichprobengr{\"o}ße von n = 124 erzielt werden, welche sich in 62,1 \% Physiotherapeut:innen und 37,9 \% Pflegekr{\"a}fte teilt. Es zeigt sich eine durchschnittlich problematische Gesundheitskompetenz der Stichprobe und dichotomisiert weisen 68,6 \% der Befragten eine geringe Gesundheitskompetenz auf, wobei mehr Pflegekr{\"a}fte eine hohe Gesundheitskompetenz aufweisen als die Physiothera-peut:innen. Das Stresserleben beider Berufsgruppen ist vergleichbar und insgesamt setzt die Mehrzahl aller Befragten mindestens drei von f{\"u}nf gesundheitsf{\"o}rderlichen Verhaltensweisen um (mind. T{\"a}gli-cher Obst- und Gem{\"u}severzehr, aktuelles Nichtrauchen, risikoarmer Alkoholkonsum, K{\"o}rpergewicht im Normalbereich, k{\"o}rperliche Bet{\"a}tigung nach WHO-Empfehlung), wobei dies mehr Physiothera-peut:innen als Pflegekr{\"a}ften gelingt. Im Rahmen der bivariaten Analyse zeigten sich in beiden Berufs-gruppen nur schwache Korrelationen zwischen der Gesundheitskompetenz und den Variablen des Stresserlebens sowie des gesundheitsbezogenen Verhaltens, wobei Letzteres lediglich das Bewe-gungsverhalten und den Alkoholkonsum umfasst. Schlussfolgerung: In der hier vorliegenden Arbeit kann die Gesundheitskompetenz als personale- bzw. als Handlungsressource interpretiert werden, die problemzentrierte Bew{\"a}ltigungsans{\"a}tze unterst{\"u}tzt und als prototypische Selbststeuerungsaufgabe das Stresserleben und das gesundheitsbezogene Verhalten der Fachkr{\"a}fte in geringer Weise beeinflusst. Das reine Wissen {\"u}ber gesundheitsbezogene Aspekte reicht jedoch nicht aus, um das Stresserleben und das Gesundheitsverhalten der Fachkr{\"a}fte zu verbessern. An dieser Stelle kann die Gesundheits-kompetenz somit nicht als alleinige unabh{\"a}ngige Variable identifiziert werden, sondern stellt lediglich den Teil eines Ganzen aller Einflussfaktoren auf die abh{\"a}ngigen Variablen dieser Arbeit dar. Die Er-gebnisse legen nahe, dass zuk{\"u}nftige Bem{\"u}hungen zur Steigerung der Gesundheitskompetenz der Fachkr{\"a}fte erforderlich sind und dabei sowohl die individuelle, organisatorische und politische Ebene ber{\"u}cksichtigt werden sollte.}, language = {de} } @misc{Akter, type = {Master Thesis}, author = {Akter, Most Sarmin}, title = {Data Analysis of the "Loyalty Program-Valeo Specialist Club" to Improve the Independent Aftermarket: Designing an Efficient Marketing Strategy}, school = {Hochschule Rhein-Waal}, abstract = {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.}, language = {en} } @misc{Gurung, type = {Master Thesis}, author = {Gurung, Purnima}, title = {Sentiment Analysis in Nepali Tweets: Leveraging TransformerBased Pre-trained Models}, url = {http://nbn-resolving.de/urn:nbn:de:hbz:1383-opus4-19677}, school = {Hochschule Rhein-Waal}, abstract = {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.}, language = {en} } @misc{Shrestha, type = {Master Thesis}, author = {Shrestha, Sabita}, title = {Named Entity Recognition for Nepali Text Using Pre-Trained BERT-Based Model}, url = {http://nbn-resolving.de/urn:nbn:de:hbz:1383-opus4-19870}, school = {Hochschule Rhein-Waal}, abstract = {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}, language = {en} } @misc{Wissigkeit, type = {Master Thesis}, author = {Wissigkeit, Tobias}, title = {Interaction design strategies for conversational video games to accommodate for anomalous user- and AI behaviors: A case study on integration strategies for interaction-based AI technologies in games using participatory design methods.}, url = {http://nbn-resolving.de/urn:nbn:de:hbz:1383-opus4-19710}, school = {Hochschule Rhein-Waal}, pages = {51}, abstract = {The recent development of generative artificial intelligence (AI) has inspired some game developers to try and integrate it into games. Anomalous behavior by generative AI or users seems undesirable and effort is being made to find ways on how to prevent anomalous responses by generative AI. However, these responses are a unique trait of generative AI and in our project, we explore strategies on how the negative effects of anomalous user and AI behavior can be mitigated, instead of trying to prevent them from appearing. We want to leverage their uniqueness as an intended game mechanic and see in what context these strategies can work. To achieve these goals, we researched already existing integrations of generative AI features in games and entertainment as well as possible connections to game mechanics and systems that are not related to AI. Based on this, we created 4 prototypes of conversational games with generative AI characters, which allowed the AI to create anomalous responses and did not limit the player freedom of what they may input. In our 36 participatory design sessions, we found that anomalous user and AI behavior can have a positive influence on the player's experience if a game's story is set up in a way that it can allow new and diverging story threads, that are created by the player and AI, to be integrated and if there are supplementary game mechanics, that allow the player to follow the intended story and complete the game.}, language = {en} } @misc{Hoetger, type = {Master Thesis}, author = {H{\"o}tger, Marvin}, title = {Evaluation of the potential of a silphie supply chain for fiber production and CO2 binding in East-Westphalia Lip}, school = {Hochschule Rhein-Waal}, abstract = {The present thesis focuses on the potential of the alternative fiber plant Silphie (Silphium perfoliatum) in East Westphalia-Lippe. To assess its potential, three expert interviews were conducted in the beginning with the key stakeholders of a Silphie supply chain. These stakeholders included the fiber producer OutNature, the seed distributor Donau-Silphie, and the CO2 certification company Positerra. Through these interviews, the necessary conditions for establishing a Silphie cultivation region for paper production were determined. Subsequently, the attitudes of local farmers towards cultivation and further use of the plant were surveyed. Additionally, the potential for CO2 sequestration of Silphie was assessed and compared with the opinions of the farmers. The results from the interviews and the survey were used to identify patterns using explorative data analysis and descriptive statistics methods, enabling the prioritization of potential farmers in the future. The evaluation of the methods revealed an interest in cultivation and fiber production under certain conditions. The most important prerequisites include profitability, secured take-off agreements, and the suitability of using the plant as fodder. Consequently, farmers with a larger farm size who cultivate silage maize for biogas production are most willing to grow Silphie. By geographically mapping potential Silphie areas, two preferred catchment areas were identified where the chance for a cultivation region is favorable due to existing infrastructure and farmer interest. Furthermore, a comparison of the required environmental conditions with those present in OWL was conducted and mostly deemed accurate. Based on these findings and the development of further utilization possibilities for Silphie, this thesis serves as a motivation for additional studies aimed at increasing the potential of Silphie in OWL.}, language = {en} } @misc{ShujaUdDin, type = {Master Thesis}, author = {Shuja Ud Din, Aneeba}, title = {"SCHOOL FEEDING AND PUBLIC FOOD PROCUREMENT PROGRAMS AS A POLICY INSTRUMENT TO PROMOTE SMALLHOLDER FARMING AND SUSTAINABLE FOOD SYSTEMS - A SYSTEMATIC LITERATURE REVIEW}, school = {Hochschule Rhein-Waal}, abstract = {Family farms and smallholders have been kept out of the market niche due to their competition with larger multinational corporations. Smallholder farmers can enter the food market easily by linking them with school feeding programs. National school feeding programs exist globally. However, food quality is a major factor in the success of these programs in enhancing student nutrition. This offers opportunities for family farms to supply nutritious, local organic produce to regional schools and gain access to the food market in urban areas. Students and farmers can benefit from this integration along with all supply chain contributors. Nevertheless, proper management of these supply chains, programs, and farms is a necessity. In this review, the impacts of local procurement for school meal programs are discussed with data from different national programs. Perspectives of farmers, distributors, school management, students, and parents are discussed to assess the advantages of buying from family farms. Challenges faced in the process of procurement from smallholders and associated risks are also examined. Social actors including producers, distributors, consumers, and government that participated in these studies give their opinions on school feeding programs. The main problems arise from the lack of budget and incentives available to farms and faulty logistics that can affect quality and quantity of school meals. Organizational strategies to promote sustainable supply chains and investment in agriculture policies are practical solutions for these challenges.}, language = {en} } @misc{Zimmermann, type = {Master Thesis}, author = {Zimmermann, Laura}, title = {Matching im Gesundheitswesen: Eine Analyse relevanter Faktoren zur erfolgreichen Besetzung {\"a}rztlicher Positionen im Krankenhaus mit Handlungsempfehlungen}, school = {Hochschule Rhein-Waal}, abstract = {Hintergrund - Seit Jahren steigt in Deutschland der Bedarf an {\"a}rztlichem Personal. Krankenh{\"a}user haben immer mehr offene Stellen, {\"A}rzte ein zunehmend großes Jobangebot. Fraglich ist jedoch, wie {\"A}rzte in dieser F{\"u}lle an Optionen die f{\"u}r sie ideale Stelle finden k{\"o}nnen. Ein Stellenportal soll die Br{\"u}cke zwischen Stellensuche und Stellenbesetzung bilden. Ziel - Das Ziel dieser Masterarbeit ist es, relevante Faktoren und gegenw{\"a}rtige Herausforderungen im {\"a}rztlichen Bewerbungsprozess zu identifizieren. In Anlehnung daran soll entschieden werden, inwiefern ein digitales Stellenportal den bestehenden {\"a}rztlichen Stellenmarkt verbessern kann, und welche Alternativen bestehen, um die Effizienz und Qualit{\"a}t im {\"a}rztlichen Bewerbungsprozess zu verbessern. Methodik - Um die Forschungsfrage zu beantworten, wurde eine qualitative Studie zu Bewerbungsprozessen im Krankenhaussektor durchgef{\"u}hrt. Im Rahmen dessen wurden Experteninterviews mit {\"A}rzten sowie Personalverantwortlichen in Krankenh{\"a}usern gef{\"u}hrt. Daneben wurde auch eine quantitative Befragung mit {\"A}rzten durchgef{\"u}hrt, um die qualitativen Aussagen der Interviews mit quantitativen Daten zu untermauern. Ergebnisse - {\"A}rzte bewerben sich {\"u}berwiegend initiativ oder nutzen ihr pers{\"o}nliches Netzwerk, um eine Neuanstellung zu finden. Dabei sind vor allem das Team und die Lage des Krankenhauses relevant. Krankenh{\"a}user ver{\"o}ffentlichen Stellenausschreibungen {\"u}berwiegend auf ihrer Webseite und im Deutschen {\"A}rzteblatt. Digitale medizinische Stellenportale werden bislang weder von {\"A}rzten noch von Krankenh{\"a}usern in hohem Maße genutzt. In nahezu allen Krankenh{\"a}usern sind derzeit {\"a}rztliche Stellen unbesetzt, die mit langen Nachbesetzungszeiten verbunden sind. Daher halten Krankenh{\"a}user ihre Anforderungen an Bewerber m{\"o}glichst gering und beschr{\"a}nken ihre Einstellungsvoraussetzungen h{\"a}ufig auf ausreichende Sprachkenntnisse und eine stellengerechte Qualifikation. Schlussfolgerungen - Der demografische Wandel und der Fachkr{\"a}ftemangel erfordern ein Umdenken seitens der Krankenh{\"a}user im {\"a}rztlichen Bewerbungsprozess. Die Entwicklung eines digitalen Stellenportals f{\"u}r {\"a}rztliches Personal kann den bestehenden Herausforderungen nur geringf{\"u}gig entgegenwirken. Vielmehr bedarf es interner Ver{\"a}nderungen und politischer Anpassungen, um wirksame Prozessverbesserungen zu erreichen.}, language = {de} } @misc{Kubin, type = {Master Thesis}, author = {Kubin, Nathalie}, title = {Universit{\"a}res Gesundheitsmanagement an der Rheinischen Friedrich-Wilhelms-Universit{\"a}t Bonn - Eine Netzwerkanalyse des Studentischen Gesundheitsmanagements mit Handlungsempfehlungen}, school = {Hochschule Rhein-Waal}, abstract = {Die Bedeutung der Hochschulen im Gesundheitsbereich ergibt sich unter anderem aus ihrem bildungspolitischen Auftrag. Im Rahmen dessen sind Hochschulen, neben der Wissens- und Kompetenzvermittlung, auch als Sozialisationsraum zu sehen. Mit gesundheitsf{\"o}rdernden Angeboten entwickeln, pr{\"a}gen und festigen die Hochschulen w{\"a}hrend dieser Zeit gesundheitsbezogene Einstellungen sowohl bei Mitarbeitenden als auch bei Studierenden im Hochschulumfeld. Die vorliegende Masterthesis gibt einen {\"U}berblick {\"u}ber die Bedeutung und Relevanz organisatorischer Beziehungen von Netzwerkakteur*innen eines Studentischen Ge-sundheitsmanagements (SGM) am Beispiel des Managements der Rheinischen-Friedrich-Wilhelms-Universit{\"a}t Bonn. Damit ist das Ziel dieser Arbeit zu beantworten, welche Akteur*innen f{\"u}r das SGM an der Universit{\"a}t Bonn eine wesentliche Rolle einnehmen und wie diese mit- oder untereinander kooperieren und kommunizieren. Des Weiteren sollen Schwachstellen in diesem Netzwerk ermittelt und durch Hand-lungsempfehlungen optimiert werden. Um diese Forschungsfragen zu beantworten, wird als methodisches Vorgehen die Netzwerkanalyse genutzt, um die Positionen und Merkmale der Netzwerkak-teur*innen zu visualisieren, zu beschreiben und die organisatorischen Beziehungen zu bestimmen. Im Rahmen dieser Netzwerkanalyse wurden semistrukturierte Inter-views mit ausgew{\"a}hlten Akteur*innen auf pers{\"o}nlicher Ebene durchgef{\"u}hrt. Die Ana-lyse und Darstellung der Ergebnisse erfolgte mit verschiedenen Software-Programmen wie EXCEL, SPSS, UCINET 6 und GEPHI. Die Analyse zeigt, dass sowohl das Kooperations- als auch das Kommunikations-netzwerk eine flache, nicht-hierarchische Struktur aufweisen, die sich in niedrigen Zentralisierungsgraden, kurzen durchschnittlichen Entfernungen mit geringen Stan-dardabweichungen, einem kleinen Durchmesser und dem Nichtvorhandensein von Untergruppen widerspiegelt. Diese Ergebnisse bringen neue Erkenntnisse zu der Debatte, dass eine Netzwerkanalyse an Hochschulen eine neue Form der Struktur-bewertung in der Gesundheitsf{\"o}rderung repr{\"a}sentieren kann, bei der der Schwer-punkt weniger auf einfachen Z{\"a}hlungen von Programmaktivit{\"a}ten liegt und vielmehr auf der Dokumentation struktureller Ver{\"a}nderungen.}, language = {de} } @misc{Hoffmann, type = {Master Thesis}, author = {Hoffmann, Julia}, title = {„Betriebliches Eingliederungsmanagement - Optimierung des bestehenden Verfahrens zur gleichzeitigen Steigerung der Mitarbeiterakzeptanz und Handlungsempfehlungen f{\"u}r mittelst{\"a}ndige Unternehmen"}, school = {Hochschule Rhein-Waal}, pages = {1}, abstract = {Die vorliegende Masterarbeit untersucht den bestehenden Prozess des Betrieblichen Eingliederungsmanagements (BEM) bei der Kao Chemicals GmbH. Das BEM beschreibt ein Instrument, welches Unternehmen dazu dient, fr{\"u}hzeitig auf die Herausforderungen von Langzeiterkrankungen zu reagieren. So sollen das Fachwissen im Betrieb gehalten und die Arbeitsplatzsicherung gew{\"a}hrleistet werden. Der Arbeitgeber ist nach Paragraf 167 SGB IX gesetzlich verpflichtet, dem Arbeitnehmer ein BEM anzubieten und bei dessen Einverst{\"a}ndnis, dieses durchzuf{\"u}hren. Die rechtlichen Grundlagen sind im Sozialgesetzbuch IX geregelt. Obwohl hinter dem Prozess eine positive Intention liegt, besteht bei Mitarbeitenden der Anschein, dass das BEM als Vorwand zur krankheitsbedingten K{\"u}ndigung dient. Dabei liegt das tats{\"a}chliche Ziel des Prozesses darin, den Arbeitsplatz ressourcenorientiert zu gestalten und Ausfallzeiten zu minimieren. Mit dieser Arbeit soll ermittelt werden, ob Vorbehalte seitens der Mitarbeitenden gegen{\"u}ber dem BEM-Prozess bei der Kao Chemicals GmbH bestehen. Zus{\"a}tzlich wird evaluiert, ob die Mitarbeitenden ausreichend {\"u}ber die Ziele und Absichten des Betrieblichen Eingliederungsmanagements informiert sind. Zur Datenerhebung erfolgen eine Ist-Analyse im Unternehmen, eine Mitarbeiterbefragung und Experteninterviews mit ausgew{\"a}hlten Mitgliedern des Integrationsteams der Kao Chemicals GmbH. Der Fokus liegt auf der Akzeptanz der Mitarbeitenden und der Effektivit{\"a}t des aktuell umgesetzten Prozesses. Es wird untersucht, ob und welche Ver{\"a}nderungen in der Gestaltung des BEM-Ablaufs erfolgen m{\"u}ssen sowie der Frage nachgegangen, ob die gesetzlichen Vorgaben umgesetzt werden. Die rechtlichen Verpflichtungen des BEM sollen nicht nur erf{\"u}llt, sondern m{\"o}glichst gewinnbringend f{\"u}r das Unternehmen eingesetzt werden. Die gewonnenen Ergebnisse sollen dazu beitragen, den aktuellen BEM-Ablauf zu bewerten und Maßnahmen zu dessen Optimierung zu benennen. Die Auswertung der Daten ergab, dass zur zielf{\"u}hrenden und nachhaltigen Durchf{\"u}hrung des BEM die Evaluation und Qualit{\"a}tssicherung des Prozesses von Bedeutung sind. Die in der Thesis formulierten Handlungsempfehlungen k{\"o}nnen als Grundlage zur zielgerichteten Verbesserung des BEM-Prozesses dienen.}, language = {de} } @misc{Sharma, type = {Master Thesis}, author = {Sharma, Neetu}, title = {Analyzing Customer Behvior Patterns \& Predicting Online Product Return Intentions: A Data Mining Approach}, url = {http://nbn-resolving.de/urn:nbn:de:hbz:1383-opus4-19240}, school = {Hochschule Rhein-Waal}, pages = {74}, abstract = {During the past years, it is noticeable that the e-commerce industry has emerged drastically, offering accessibility to a variety of products to the customer where they can buy products from the comfort of their home. However, it is associated with a lot of new challenges for e-commerce businesses, particularly in understanding and managing the customer behavior patterns with the rising online product returns. Since the accessibility of online shopping has risen, assessing the critical factors related to product return and prediction has become a really challenging task for e-commerce vendors. This study also aims to segment the customers based on customer behavior prediction into two categories, i.e., high return risk and low return risk customers, and further develop strategies to reduce the online returns. This study is rather structured into four integral parts, where each part provides the comprehensive analysis. The first aspect involves analyzing and identifying the customer behavior patterns leading to product returns. The second aspect predicts the online product return based on selected features and the third is to segment the customers based on online product return prediction and categorize them into high return risk, and low return risk customers. The final step involves development of strategies to reduce the product return based on the intense analysis conducted. To achieve this meaningful research outcome, data analysis is conducted to understand the customer behavior patterns, and a Random Forest feature selector is used to identify the customer behavior patterns that lead to product return. Based on the identified features, classification models were applied to classify and predict whether the customer is going to return product or not. Furthermore, in these seven classification models such as Logistic Regression, Ada Boost, Decision Tree, Naive Bayes, XG Boost, K-Nearest Neighbors, and Random Forest were implemented and used to compare the performance of the classification models to find out the best performing model. Lastly, the segmentation of customers is carried out based on the online product prediction using Logistic regression with classification threshold method into high return risk and low return risk customer categories. The results obtained help in understanding the customer behavior and reduce the online product return by developing the strategies. This study will eventually help the online businesses in reducing returns which will also enhance the customer satisfaction.}, language = {en} }