The 100 most recently published documents
Positron Emission Tomography (PET) is becoming more and more important in clinical routine
applications. One of the major limitations is the sensitivity to patient motion especially in the thorax
to periodic respiratory movement. Another open point of discussion is the method how to define the
tumor volume, especially when the precise knowledge of the tumor borders is important as in
radiation treatment planning. Therefore, in this work these two topics to improve quantification in
PET imaging have been addressed. First a new motion correction algorithm was implemented using
image deblurring including movement information of a 4D Computed Tomography (CT). This method,
which has the advantage of not increasing the PET acquisition time as other motion correction
techniques, was applied to phantom and patient data and showed promising result in improvement of lesion quantification. In phantom studies an improvement of up to 49% in lesion volume and in
patient studies of up to 33.3% could be demonstrated.
In the second part of this work, a new segmentation method based on textural parameters was
implemented and validated as well in phantom and patient data. In the latter a validation with
histopathological data was performed showing a very good performance of the new algorithms,
especially in larger lesions. Best result could be shown in phantom data and patient data for the
segmentation algorithm based in the local entropy.
In summary, two algorithms were implemented and validated which can improve quantification of
PET imaging furthermore
Seit mehr als 10 Jahren forscht und lehrt das Team des Centers for Enterprise Research (CEIR) an der Universität Koblenz im Bereich der digitalen Unterstützung kollaborativer Arbeit in Unternehmen (Enterprise Collaboration) und untersucht den Aufbau und die Nutzung von Kollaborationstechnologie für den Digitalen Arbeitsplatz.
Der vorliegende CEIR Report mit dem Titel „Collaborative Actions on Documents Ontology (ColActDOnt)“ beschreibt die Entwicklung einer Ontologie für Benutzeraktionen an Content in Kollaborationssystemen (englisch: Enterprise Collaboration Systems). Die Arbeit an der Ontologie erfolgte im Rahmen eines DFG-Projekts mit dem Titel „Social Process Mining“. In diesem Projekt wurde eine Methode für das sogenannte „Cross-System Process Mining“ entwickelt. Cross-System Process Mining erlaubt die Analyse von Arbeitsprozessen, deren Ablauf von mehreren, heterogenen Kollaborationslösungen (z.B. HCL Connections, Alfresco, Skype) unterstützt werden. Aufgrund der Heterogenität der involvierten Systeme müssen die Logfiles der unterschiedlichen Softwaresysteme zunächst in einen gemeinsamen, harmonisierten Event-Log überführt werden. Die ColActDOnt stellt die notwendige Systematik für diese Harmonisierung zur Verfügung.
Die Ontologie wurde entwickelt in einer Reihe von interaktiven Workshops mit den Projektbeteiligten (Prof. Dr. Petra Schubert, Dr. Florian Schwade, Julian Mosen) unter der Leitung von Martin Just, der die Ergebnisse anschließend im Rahmen seiner Masterarbeit dokumentierte. Anschließend wurden die wichtigsten Teile in gekürzter Form in dem vorliegenden CEIR-Report veröffentlicht.
Mit den CEIR-Reports möchten wir ausgewählte wissenschaftliche Ergebnisse einem breiteren Publikum zur Verfügung stellen. Die in dieser Arbeit dargestellten Informationen sind für Unternehmen interessant, die an einer gezielten (Weiter-)Entwicklung ihrer Enterprise Collaboration Platform interessiert sind.
Satzung der Studierendenschaft der Universität Koblenz zur Änderung
von Vorschriften der Studierendenschaft der Universität Koblenz
Fünfundzwanzigste Ordnung zur Änderung der Prüfungsordnung
für die Prüfung im Zwei-Fach-Bachelorstudiengang an der Universität Koblenz
Erste Ordnung zur Änderung der Masterprüfungsordnung für
den weiterbildenden Fernstudiengang „Master of Business Administration“
des Fachbereichs 4: Informatik der Universität Koblenz
Erste Ordnung zur Änderung der Masterprüfungsordnung für
den weiterbildenden Fernstudiengang Energiemanagement
des Fachbereichs 3: Mathematik / Naturwissenschaften der
Universität Koblenz
Prüfungsordnung für den Bachelorstudiengang „Angewandte
Naturwissenschaften“ und den Masterstudiengang „Material
Science“ an der Universität Koblenz (Studiengangs-PO Angewandte
Naturwissenschaften / Material Science)
Prüfungsordnung für das Studienmodell uk-Master an der
Universität Koblenz (Studiengangs-PO uk-Master)
Einschreibeordnung der Universität Koblenz
This thesis tackles a common bottleneck in data-science courses: students struggle
to turn a broad interest into a focused, workable project idea. This thesis set out to
design and evaluate a compact assistant—EduIDEAtor—that makes this first mile
simpler and more intentional. The tool uses a text-first interface with plain inputs,
a small set of clearly different directions, and quick, reversible edits so students can
steer ideas without losing momentum. After building and iterating the web appli-
cation, The thesis evaluated how students experienced it and how it compared with
familiar, non-AI brainstorming. The findings are consistent: navigation and input
clarity were strong; students felt more able to generate and shape ideas; overall sat-
isfaction and willingness to continue using the tool were high. Two practical refine-
ments emerged—make back navigation clearly visible and give users finer control
over how broad or specific the suggestions are both achievable without changing
the core design. The contribution is a concrete pattern for first-mile ideation and a
set of actionable guidelines for course-level adoption.
Globally billions of dollars are invested on information systems and technology (IS/IT) to achieve business change. Understanding how value is generated and captured from these investments has been a key theme in information systems (IS) research for over 25 years. However, despite significant theoretical progress, organisations are still failing to achieve the full value of their investments and identifying and realising the benefits of IS/IT-enabled business change remains a challenge for both research and practice.
Our research is concerned with the business change associated with the introduction and use of new forms of enterprise collaboration system (ECS) that incorporate social software functionality (e.g. social profiles, blogs, wikis, activity streams, collaborative tagging etc). ECS represent a significant business investment; however, there remains uncertainty around the benefits and value arising from the introduction of these new types of ECS. Existing research studies on IS/IT benefits are focused primarily on traditional enterprise systems such as ERP systems. This article summarises the existing work that directly, or indirectly addresses IS benefits, to reveal four broad themes (i) evaluations of IS/IT investments (ii) measuring IS success (iii) classifying and measuring IS benefits and (iv) benefits realisation management.
The article concludes with an overview of the research on benefits management conducted in the Center for Enterpise Information Research at the University of Koblenz and the current research project investigating the benefit of enterprise collaboration systems (BECS).
The BECS project investigates the benefits arising from the adoption and use of Enterprise Collaboration Systems (ECS).
ECS are large-scale collaboration technology infrastructures that provide the software functionality to enable workgroups to organise online team meetings, to create and share information, to coordinate workflows and to collaborate on joint projects, regardless of the location and timing of work activities.
When ECS are introduced into organisations there are initial expectations about what can be gained from the system, e.g. improved collaboration, improved communication across silos, etc. Over time, as users gain experience using the system, ideas about what can be achieved change and the ECS become embedded into organisational work practices. However, identifying and understanding the expected benefits of ECS, how they evolve over time, and how they contribute to organisational performance is challenging due to a lack of suitable methods and tools to describe (profile), measure and monitor ECS benefits.
The BECS project addresses this challenge; the primary focus is on identifying, measuring and monitoring the benefits that arise from ECS implementation and use over time. Through the development of in-depth longitudinal case studies of ECS adoption in leading organisations in the DACH region and empirical analyses of collaboration system use, the research:
i) developed practical tools and methods for the measurement of ECS benefits and benefits profiling;
ii) provides greater insights into how benefits management is experienced and constituted in practice; and
iii) developed a novel and integrated framework that assists researchers and practitioners to coordinate their efforts in developing, implementing and evaluating ECS benefits.
The project delivered both practical and theoretical outcomes. The methods and tools developed in the BECS project have been applied in organisations and delivered useful and useable results enabling organisations to understand and monitor the evolving benefits of their ECS. Following the COVID-19 pandemic, this work became of even greater importance as new uses of ECS emerged when organisations adopted large-scale support for hybrid and remote working initiatives.
The research findings also provide key theoretical concepts and analytical methods, including the MoBeC framework, Social Collaboration Analytics and Benefits Scorecards. These provide the foundation for subse-quent research projects to examine transformation to digital work and the development of a new stream of research into trace analysis and collaboration analytics more broadly.
The rapid evolution of wireless communication technologies, particularly the introduction
of Fifth-Generation (5G) networks and the anticipated transition to Sixth-Generation (6G)
systems, ushers in a new era of connectivity, enabling transformative applications across
industrial automation, the Internet of Everything (IoE), and the Industrial Internet of Things
(IIoT). However, the exponential growth in the number of connected devices, stringent reliability
requirements, and increasing security challenges pose significant hurdles for current network
architectures. This dissertation addresses these challenges by proposing innovative frameworks
and mechanisms that enhance reliability, optimize resource utilization, and strengthen security
and trust management in next-generation mobile networks.
The first contribution of this dissertation focuses on reliability enhancements in 5G networks.
While existing mechanisms, such as Dual Connectivity (DC) and Network Function (NF)
redundancy, provide partial solutions, they do not fully resolve application-layer reliability
and dynamic server failover. To bridge this gap, this work introduces the Make-Before-Break-
Reliability (MBBR) and enhanced Make-Before-Break-Reliability (eMBBR) mechanisms. These
frameworks proactively establish redundant communication paths, ensuring seamless failovers
with minimal latency and service disruption. By extending reliability to the application layer
and integrating adaptive path selection and dynamic failover capabilities, these mechanisms
offer robust solutions for latency-sensitive and mission-critical applications.
The second major contribution addresses bandwidth optimization for industrial networks.
The black channel paradigm, widely adopted for industrial safety applications, relies heavily on
cyclic keep-alive messages to detect connection loss, leading to significant signaling overhead.
This dissertation proposes a novel solution leveraging 5G Channel State Information (CSI)
to replace cyclic messaging with real-time connection quality monitoring. By exposing CSI
metrics, such as Signal-to-Noise Ratio (SNR) and Channel Quality Indicator (CQI), to the
application layer, the proposed mechanism reduces bandwidth consumption while maintaining
the safety and reliability requirements of industrial networks.
Addressing the growing complexity of security requirements in IIoT, the third contribution
introduces the AF-based Security Framework (AERO) framework. This framework empowers
application providers to dynamically apply cryptographic mechanisms to the user plane,
overcoming the limitations of legacy protocols and eliminating the need for redundant security
layers. By ensuring backward compatibility and enabling both static and dynamic configuration
of user plane encryption, AERO enhances security while minimizing computational overhead
and reducing transmission delays.
The fourth and final contribution redefines trust management in mobile networks through
the SecUre deleGAtion of tRust (SUGAR) framework. Traditional trust models, which rely
on identity chips for each connected device, are becoming increasingly impractical in the
IoE era, where billions of devices require connectivity. The SUGAR framework introduces a
delegation-based trust model, allowing Parent Devices (PaDs) to delegate trust to multiple
Child Devices (ChDs) securely. This approach eliminates the need for individual identity chips,
significantly reducing costs and enhancing scalability. Integration with System-on-a-Chip
(SoC)-based identity enclaves further strengthens the security of trust credentials.
The findings of this dissertation offer substantial contributions to both academia and
industry. The proposed frameworks effectively address critical gaps in current 5G standards
and provide valuable contributions for developing the 6G framework. By enhancing reliability,
optimizing bandwidth, and redefining security and trust management, this dissertation provides
a comprehensive foundation for the design and deployment of next-generation mobile networks.
Furthermore, the solutions presented are adaptable to a wide range of applications, including
industrial automation, autonomous systems, and smart city infrastructures.
In conclusion, this dissertation represents a significant step toward realizing the full
potential of next-generation mobile networks. By addressing key challenges in reliability,
resource optimization, security, and trust management, the proposed frameworks pave the way
for scalable, secure, and efficient mobile ecosystems that are essential for the dynamic and
interconnected world of the future.
This thesis investigates the potential of LLMs to provide personalized and context aware feedback in data science education. Traditional automated feedback systems often face challenges related to adaptiveness, scalability, and pedagogical alignment. To address these limitations, an experimental study was conducted using a custom-built AI tutor based on GPT-4o, which guided students through six clustering assignments designed around k-means and DBSCAN concepts. Data were collected from pre- and post experiment questionnaires and 516 dialogue exchanges recorded across ten individual tutoring sessions. A mixed-methods approach was adopted. Quantitative analysis compared pre and post-survey results to measure normalized learning gain (g = 0.375), effect size (Cohen’s d = 0.321), and statistical significance (t(9) = 0.811, p > 0.05). Qualitative analysis involved manual coding of AI responses for feedback type, adaptiveness, and student engagement. Results showed that students generally perceived the AI tutor positively, emphasizing its clear explanations, step-by-step guidance, and timely feedback. While moderate conceptual improvement was observed, statistical effects remained small, suggesting that perceived learning gains may exceed measured performance improvements. Conversational analysis revealed that adaptive responses and interactive questioning supported engagement, though occasional inconsistencies and reliance on predefined solutions limited deeper adaptiveness. The study contributes to educational technology research by providing empirical insight into both the capabilities and current constraints of LLM-based tutoring. Although student satisfaction was high, findings highlight the need for more sophisticated scaffolding, enhanced contextual adaptiveness, and hybrid human-AI feedback frameworks. Overall, this research demonstrates the promise of LLMs in delivering scalable, personalized support in data science education, while emphasizing the importance of continued evaluation to ensure pedagogical reliability and meaningful learning outcomes.
This study examines student housing experiences in Koblenz through a mixed-methods approach that integrates surveys, geospatial analysis, and quantitative modeling to explore affordability, accessibility, satisfaction, and equity. By analyzing both objective factors—like rent, distance to campus, and travel times—and subjective measures such as satisfaction and sentiment, it identifies disparities across student groups, especially affecting international students. The findings suggest that housing outcomes stem from both structural conditions and lived experiences, revealing possible biases within the housing system. The study advocates for targeted interventions, including expanding affordable residences, enhancing transport connectivity, and promoting transparency in housing allocation to ensure equitable access in Germany’s higher education context.
Improving patient care is an ongoing process, evolving from early evidence-based practices to modern AI-driven approaches. This thesis explores three key research directions aimed at improving clinical decisionmaking through AI. Adverse events, defined as negative and harmful outcomes that occur during medical care, present major challenges for hospitals. Most data-driven research using electronic health records relies on data from tertiary referral hospitals, but their patient population differs from those in hospitals of medium level of care. The first major contribution of this thesis is a data-driven Trigger Tool for predicting adverse events trained on data from a hospital of medium level of care. This tool uses a concise set of laboratory values measured within the first 24 hours of hospitalization. In addition to models using numerical features, we devised models using dichotomized features that indicate whether a laboratory value falls below or above a reference threshold. Our findings show that models using numerical features achieve high accuracy in predicting acute kidney injury and the COVID-19 associated adverse events in-hospital mortality and transfer to the ICU. Models using dichotomous features performonly slightly worse but offer better interpretability.
The second major contribution is the online-updateable AI model OptAB for selecting optimal antibiotics in sepsis patients. OptAB aims to minimize the sepsis-related organ failure score (SOFA-Score) while accounting for nephrotoxic and hepatotoxic side effects. OptAB relies on a hybrid neural network differential equation algorithm tailored to the special properties of patient data, including irregular measurements, missing values, and time-dependent confounding. Time-dependent confounding describes a dependence between time-varying covariates and treatment decisionsmade by physicians, often leading to biased treatment effect estimates. OptAB generates disease course forecasts for (combinations of ) the antibiotics vancomycin, ceftriaxone, and piperacillin/tazobactam and learns realistic treatment effects on the SOFA-Score and side effect indicative laboratory values. Results indicate that OptAB’s recommendations achieve faster efficacy than the administered antibiotics while reducing side effects.
The third major contribution is DoseAI, an online-updateable AI model that extends OptAB to optimize dosing regimens. DoseAI mitigates time-dependent confounding in dosage selection by minimizing the absolute spearman correlation between predicted and future treatment dosages. It forecasts disease progression under alternative dosing regimens and proposes optimal chemotherapy and radiotherapy dosing regimens for synthetic cancer patients. These regimens effectively reduce the tumor volume while adhering to varying maximum allowed weight loss constraints, used as a measure of toxicity.
Mathematiklehrkräfte sind bisher unzureichend auf die Digitalisierung des Mathematikunterrichts vorbereitet. Daher ist es notwendig bereits im Studium passende Lernangebote zur Entwicklung professioneller Kompetenzen für den Einsatz digitaler Mathematikwerkzeuge zu schaffen. Im Rahmen der vorliegenden Arbeit wird eine fachdidaktische Lehrveranstaltung für angehende Mathematiklehrkräfte der Sekundarstufen
konzipiert, um deren professionellen Kompetenzen mit Blick auf den Einsatz digitaler Mathematikwerkzeuge im Kontext der Leitidee Strukturen und funktionaler Zusammenhang zu fördern. Neben Werkzeugkompetenzen zur Nutzung der digitalen Mathematikwerkzeuge sollen die Kompetenzen zur Planung und Gestaltung von Mathematikunterricht entwickelt werden. Für das Themenfeld funktionale Zusammenhänge sind die beiden digitalen Mathematikwerkzeuge GeoGebra und Tabellenkalkulationsprogramm besonders relevant. Deren Potentiale für das funktionale Denken werden insbesondere in Bezug auf Darstellungsformen und Repräsentationswechsel sowie Lernschwierigkeiten thematisiert. Ergänzend zu den genannten Kompetenzen werden zudem Überzeugungen zum Einsatz digitaler Mathematikwerkzeuge in den Blick genommen. Diese haben einen erheblichen Einfluss darauf, ob die erworbenen Kompetenzen im eigenen Unterricht eingesetzt werden oder nicht.
Zur Ermittlung des Ist-Zustands bei Kompetenzen und Überzeugungen der angehenden
Mathematiklehrkräfte vor dem Besuch der Lehrveranstaltung wurden zwei Erhebungsinstrumente entwickelt und eingesetzt. Neben einem Fragebogen zur Selbsteinschätzung erfolgte die Datenerhebung mittels eines neu entwickelten Kompetenztests
im Sinne eines Leistungstests. Es zeigte sich, dass die professionellen Kompetenzen und Vorerfahrungen bei den Studierenden äußerst heterogen sind.
Um Rückschlüsse auf die Wirksamkeit der Lehrveranstaltung ziehen zu können, wurden die beiden Erhebungsinstrumente im Pre-Post-Design eingesetzt. Die Ergebnisse nach Besuch der Lehrveranstaltung lassen auf positive Effekte schließen. Gleichzeitig wird deutlich, dass eine einzelne Lehrveranstaltungen im Studium nicht ausreicht. Zudem besteht Bedarf an weiterer Forschung in diesem Bereich, insbesondere was die Untersuchung langfristiger Effekte und die Zusammenhänge zwischen den verschiedenen Kompetenzfacetten und Überzeugungen betrifft.
In view of the requirement that students (e.g. in Rhineland-Palatinate) from grade 7 onwards
have to work independently with dynamic geometry software (e.g. GeoGebra) and a
spreadsheet program, teachers have a special role in the integration of digital mathematics
toolsin mathematics lessons. For example this can be implemented, with regard to the guiding
idea L4 (Functional connection), since the use of digital mathematics tools is recommended to
promote functional thinking. Within the qualitive offensive for pre-service-teacher training,
which has been established by the Ministry of Education, the project MoSAiK provided a
Digital Research Workshop Multiple Representations in Mathematics Education using the
topic of elementary functions on secondary school level. On the one hand this workshop
examined tool skills of students in relation to the two softwares GeoGebra and spreadsheets
that apply for secondary schools, high schools and vocational schools. On the other hand
(technology-related) beliefs of the students were researched according to the function
concept.
For that reason a specific didactic workshop, which included on the one hand the fostering of
operating skills for the tools GeoGebra and spreadsheet and on the other hand the
subsequent planning and teaching of lessons had been conceived. Before and after attending
the workshop the operating and selection skills in both tools have been measured in a sample
of 55 students using a self-developed competency test. In addition, the sub-areas TK, TPK and
TCK of the TPACK-framework, self-efficacy beliefs and technology-related beliefs regarding
the advantages and disadvantages of using digital mathematics tools were collected using a
student questionnaire. The workshop intervention achieved a significant effect on the
development of the students' operating skills for both tools – GeoGebra and spreadsheet. The
results of a qualitative content analysis with quantitative elements show that in particular the
visualizing of functions and the checking of results were viewed as advantages of the digital
tools when teaching functional thinking. The most frequently cited disadvantage was a danger
to manual calculation methods. With regard to the time required, on the one hand, savings
were expected when using digital tools, but on the other hand, there were fears of high
expenditure if pupils do not have the necessary tool skills.
Mit der Demographischen Dividende (DD) wird ein wirtschaftlicher Vorteil beschrieben, der aus einer Verschiebung der Altersstruktur einer Gesellschaft hin zu einem höheren Anteil erwerbsfähiger Bevölkerung resultiert. Ursprünglich am Beispiel der so genannten ‚Tigerstaaten‘ Südostasiens entwickelt, gilt die DD als ein Modell für wirtschaftliches Wachstum durch Fertilitätsrückgänge. Die vorliegende Dissertation befasst sich diskursanalytisch mit der Verwendung des Konzepts in Entwicklungszusammenarbeit, Politikberatung und Bevölkerungsforschung sowie dessen Übertragung auf den Globalen Süden als ein leitendes Paradigma in der internationalen Entwicklungszusammenarbeit. Hierzu wurden teilstrukturierte Interviews mit Expertinnen und Experten geführt.
Die Debatte um die DD ist von uneinheitlichen Definitionen darüber geprägt, was die DD genau ist. Eine technisch-mathematische Perspektive sieht die DD als reine Folge der Altersstrukturverschiebung, während eine behavioristische Sicht zusätzlich die Auswirkungen individueller Faktoren wie Bildung, Emanzipation und wirtschaftlichen Handelns mit einbezieht. Ein Wachstumseffekt durch Altersstrukturverschiebungen wird im Globalen Südens voraussichtlich weniger stark ausfallen als in Südostasien. Gründe hierfür sind langsamere Fertilitätsrückgänge, geringere Arbeitsmarktanteile und unterschiedliche sozioökonomische Rahmenbedingungen. Hinzu kommt, dass heute die Prinzipien von sexueller und reproduktiver Gesundheit und Rechte (SRGR) zu respektieren sind, die während des südostasiatischen Wirtschaftswunders nicht etabliert waren. Dieses Leitbild wurde im Jahr 1994 auf der Konferenz für Bevölkerung und Entwicklung in Kairo hegemonial. Faktoren wie Bildung, soziale Sicherungssysteme, politische Stabilität und globale Abhängigkeiten sind jedoch ebenso entscheidend für den sozialen und wirtschaftlichen Fortschritt.
Entwicklungspolitische Programme propagieren vielfach Familienplanung als Schlüssel zur DD, doch stoßen diese Programme auch auf Kritik. Denn die Institutionen, welche den Diskurs um die DD dominieren, haben zum Teil eine problematische historische Verbindung zu eugenischen oder rassistischen Programmen, was der Glaubwürdigkeit ihrer Positionen schaden kann. Zudem werden die Programme in großen Teilen von eben diesen privaten Stiftungen und Initiativen mit fragwürdiger Historie finanziert, so dass die Macht über die Ausgestaltung derartiger Programme von staatlichen Akteurinnen und Akteuren hin zu privaten Akteuren verschoben wird. Die Interviews und die weiterhin verwendete Literatur zeigen auf, dass langfristige Investitionen in Bildung, Gesundheitsversorgung und soziale Sicherungssysteme größere und nachhaltigere wirtschaftliche Fortschritte bewirken als rein demographische Ansätze. Und trotz ihrer Einschränkungen bleibt die DD ein nützliches Konzept, sofern sie in einen breiteren Kontext eingebettet wird. Die Herausforderung besteht darin das Konzept so anzuwenden, dass es nicht nur in einem technokratischen Verständnis hegemonial wird, sondern dass die Verbindungen zwischen der Verschiebung von Bevölkerungsanteilen, Bildung, Stärkung des Gesundheitswesens und Wirtschafts- wie Arbeitsmarktpolitik verstanden werden.
The integration of the different stakeholder needs and environmental constraints is the key goal of requirements engineering. This demands collaborations between involved parties, to reach “understandability of the system”, what is particularly challenging for collaborations over different organisations. High quality requirements engineering is the key factor to address these challenges. Requirements are input to all development steps and carry the knowledge to exchange—requirements engineering is an overall life-cycle spanning and in its essence a knowledge management task.
The main goal of the T-Reqs framework presented in this thesis is to enable semantic interoperability and to sustain the knowledge by conceptualization of the requirements engineering process applied to European space projects. T-Reqs’ objective is to formally capture the information carried by the requirements to provide top-shelf inputs for the consecutive system and discipline-specific development tasks, in particular within model-based systems engineering. Emphasis is placed on the nature of relationships that exist among requirements and requirement documents. The T-Reqs formalism addresses the structuring of requirements as well as their potential reuse, e.g., in product line development or even between different projects. This implies an overall System Requirements Specification that is distributed in many specifications documents and involves requirements of different levels of abstractions from abstract goals to implementation details. This thesis especially focuses the specification and validation of such requirements documents.
The T-Reqs traceability model provides a means to trace not only individual requirements,
but also consider relations among views such as documents, taking into account the role
they play for stakeholders, especially in reuse. It is shown, how formalization of dependencies, such as for tailoring of standards, enables automated quality checks to facilitate reviews and enhance completeness and consistency of the overall specification.
Towards the structuring of requirements itself, different syntactic template systems aim to
increase the quality of requirement documentation. Within this thesis a comparative evaluation of these notations is conducted, supporting that claim and differentiating the strength and weaknesses of different approaches. Special emphasis is not only laid on documentation quality, but also the usefulness of these semi-formal notations for integration with model-based development methods. This is achieved through the representation of concepts, which can be managed in special contextualised glossaries.
Overall it can be shown that conceptualization of requirements engineering knowledge can support requirements engineering in different aspects and a holistic approach to integrate different tasks lays the foundation for semantic interoperability spanning organizations and life cycle phases.
The production and use of polymeric materials have been increasing continuously for
years. At the same time, the entry of microplastics (MP) – tiny particles resulting from the
wear and tear of these materials – into our environment is growing as well. By now,
awareness of MP has reached broad sections of the population and also research and
development on this field are similarly becoming increasingly important. However,
insufficient standardization and the lack of suitable analytical methods still make
recording and tracking of MP difficult, so that it remains largely unregulated. Mass-based
analytical methods are particularly advantageous for the establishment of legal
regulations. Apart from thermogravimetric methods, however, there are currently few
alternatives in this field. In this context, the use of nuclear magnetic resonance
spectroscopy (NMR), previously only qualitatively applied to MP, has now also been
examined for its quantitative benefits. This work deals with the current state of
quantitative NMR spectroscopy (qNMR) and tests possibilities for optimization and further
development for this purpose. Initially, the reduction of sample volumes and thus
minimized effort and measurement time of the method will be examined by combining
different polymer types into simultaneously measurable groups, as well as the suitability
of homopolymer calibrations for the detection of copolymers. Existing restrictions during
measurement will be adopted, and thus extractive procedures for sample preparation are
implemented. Finally, the influence of real environmental samples will be assessed, and
measures to reduce interfering factors will be taken in to account. As a result, the method
encompasses at least six polymer types, from PMMA, PS, BR, and PVC to PA and PET, as
well as separate approaches for polymers such as PAN and LDPE. A modular sample
preparation protocol, including extractive fractionation into measurement groups and a
chemical digestion method for matrix reduction, will be established and expanded to
include options for diffusion measurement and application to low-field instruments.
Practical application will be presented using real-world examples, such as freshwater
biofilms, as well as the use for quality control of certified reference materials.
Furthermore, initial insights into future development possibilities, like for the detection of
tire abrasion, will be provided.
Many factors predict adolescents' school grades, two of which may be character strengths and physical activity. We investigated 339 adolescents (130 boys, 185 girls, two diverse, 22 missing data) between 10 and 21 years old (M =14.92, SD =2.28). They filled out questionnaires regarding their character strengths, extracurricular physical activity, math, language, and sports grades. The 24 character strengths were summarized into the
virtues of wisdom, courage, humanity, justice, temperance, and transcendence. Math grades were positively predicted by the virtues of courage and temperance and negatively by age and justice. Girls and younger pupils reported better language grades. Sports grades were predicted by extracurricular physical activity and courage. Better sports grades were found in pupils who were members of a sports club and practiced their sports longer. In particular, courage, which consists of bravery, perseverance, honesty, and zest, is an essential predictor of adolescents' math and sports grades.
The presence of synthetic chemicals in the environment can affect both ecosystems and
human health. In particular, the increasing contamination of the aquatic environment by
complex mixtures of anthropogenic trace substances has become a major global concern.
Once released into the environment, these compounds can undergo diverse
transformation processes to form a wide range of transformation products (TPs), which
are commonly unknown. Transformation inevitably alters the pattern of contamination and
exposure, as new substances are formed with frequently different physicochemical
properties, environmental behavior and toxicity in comparison to their precursor
compounds. For instance, TPs can exhibit significantly greater persistence and mobility in
the aquatic environment, posing a threat to both aquatic ecosystems and drinking water
resources. Therefore, TPs need to be considered in the risk assessment and authorization
process of chemicals. However, due to a combination of predictive, analytical, and
regulatory challenges, TPs currently remain largely unrecognized and unregulated. By
addressing these challenges, this thesis comprehensively characterizes the entry paths,
occurrence, fate, and (eco)toxicological relevance of selected TPs in the aquatic system in
Germany. These TPs have been largely overlooked in environmental studies and aquatic
monitoring programs for decades, despite their precursors being produced and used in
large quantities on a global scale.
The highly persistent and mobile substance trifluoroacetate (TFA) has garnered
significant attention in recent years due to its diverse sources, widespread occurrence in
the aquatic environment, and the lack of economically viable options to remove TFA from
contaminated waters. One of the most frequently discussed diffuse sources is the
formation of TFA in the atmosphere through the oxidation of volatile precursors and its
subsequent scavenging from the atmosphere by wet deposition. Despite the previously
reported occurrence of TFA in precipitation, the lack of recent and comprehensive data
has severely limited the understanding of the significance of wet deposition as a source of
TFA to the (aquatic) environment. Thus, in the present work, a nationwide field monitoring
campaign covering all precipitation events over a one-year sampling period was
conducted at eight sites across Germany. Samples were analyzed for TFA using ion
exchange chromatography (IC) coupled to negative-ion electrospray tandem mass
spectrometry (ESI-MS/MS). Of the analyzed samples, 16% exhibited TFA concentrations
≥ 1 μg/L. The precipitation-weighted average TFA concentration of 0.34 μg/L highlighted
that wet deposition alone is responsible for approximately 0.3 to 0.4 μg/L of TFA in
surface waters in Germany. The annual wet deposition fluxes ranged from 91 to
400 μg/m², with the highest fluxes observed in densely populated regions. The annual wet
deposition of TFA for Germany during the observation period was estimated to be 68 t.
The sampling revealed a pronounced seasonality, with the highest concentrations and wet
deposition fluxes of TFA observed in summer. Pearson correlation analyses indicated that
the transformation of TFA precursors in the troposphere is enhanced in summer due to
elevated concentrations of photochemically generated oxidants, primarily •OH, which
ultimately results in increased atmospheric TFA deposition. Overall, the study provided the
first published data on TFA in precipitation in Germany since 1995/96. The derived data
serves as a benchmark for future studies. In addition, it allows for the establishment of
mass balances and can be used to develop models to predict the loads of TFA entering
the aquatic environment from multiple sources.
The lack of robust historical data on the wet deposition fluxes of TFA also impeded long-
term trend analyses. Specifically, a postulated increase in atmospheric formation and
deposition of TFA due to substantial emission increases of numerous volatile TFA
precursors in recent decades remained unquantified. To address this knowledge gap,
archived plant samples were analyzed to evaluate the long-term temporal trends in the
atmospheric deposition of TFA in Germany. A robust and highly sensitive analytical
method for TFA in plant matrices was developed and validated. The method
encompassed a three-step sequential extraction procedure followed by the analysis of the
diluted sample extracts using IC-ESI-MS/MS. Subsequently, archived leaf samples of
various tree species and sampling sites from the German Environmental Specimen Bank
(observation period: 1989−2020) were analyzed for TFA. Statistical analysis revealed
significant (p < 0.05) positive trends in TFA concentrations in plant leaves, which is likely
the result of both phytoaccumulation and increasing emissions of gaseous TFA precursors
over the observation period. The concentrations increased by factors of up to 12 from
1989 to 2020. The highest concentrations (up to ∼1,000 μg/kg dry weight) were found in
Lombardy poplar leaves. Overall, the study presents the first trend analysis of TFA in biota
and raises awareness of the escalating atmospheric deposition of TFA over the past three
decades.
Sulfamate has previously been identified as a TP of the artificial sweeteners cyclamate
and acesulfame in wastewater and drinking water treatment. The preliminary results
indicated that sulfamate concentrations in wastewater treatment plant (WWTP) effluent
are substantially higher than those of other wastewater-borne contaminants. However,
despite its high global production and usage, no information was available on the sources,
occurrence, and environmental significance of sulfamate in the aquatic system in
Germany. To close this knowledge gap, a quantitative monitoring approach of different
urban water cycle compartments was conducted. Target analysis based on IC-ESI-MS/MS
revealed exceptionally high concentrations of sulfamate in wastewater (up to 1,900 μg/L),
surface water (up to 580 μg/L), and finished drinking water (up to 140 μg/L) in Germany.
Considering the limited data on short-term ecotoxicity, approximately 30% of the
sulfamate concentrations detected in groundwater and surface water samples exceeded
the derived predicted no-effect concentration (PNEC) of sulfamate. Therefore, the
potential impact of sulfamate on the aquatic ecosystem in Germany cannot be excluded.
Municipal WWTP effluent was identified as the primary source of sulfamate for the aquatic
system, as its concentrations correlated positively (r > 0.77) with the municipal wastewater
tracer carbamazepine in samples from different waterbodies. Ozonation and activated
sludge experiments demonstrated that sulfamate can be formed through chemical and
biological degradation of various precursors containing a sulfonamide group.
Nevertheless, the transformation of precursors to sulfamate in WWTPs and receiving
waters was found to be quantitatively insignificant, due to the substantial direct use of
sulfamic acid as a descaling agent in domestic and industrial applications. Laboratory
batch experiments, in conjunction with the findings from the sampling conducted at full-
scale waterworks, demonstrated that the commonly applied drinking water treatment
techniques, including ozonation and activated carbon filtration, are largely ineffective in
removing sulfamate. Bank filtration was identified as the only option to efficiently eliminate
sulfamate from contaminated raw water resources (removal: 62% to 99%). Overall, the
study presents the first comprehensive analysis of sulfamate in the urban water cycle and
suggests that there may be other high production volume inorganic chemicals that are
currently overlooked in environmental studies and monitoring programs.
Despite pantoprazole (PPZ) being one of the most widely prescribed human
pharmaceuticals globally, consistently low concentrations of this proton-pump inhibitor in
environmental water samples have been documented. This can be attributed to the
extensive metabolism of PPZ within the human body, with only minor amounts of the
parent compound being excreted. Since environmental monitoring and risk assessment
for regulatory purposes focus on the parent substances of pharmaceuticals, it was
assumed that the current environmental exposure associated with the use of PPZ is
considerably underestimated. In the presented thesis, 4′-O-demethyl-PPZ sulfide (M1)
was identified as the most relevant PPZ metabolite for environmental analysis. This was
achieved by applying reversed-phase high-performance liquid chromatography (RP-
HPLC) coupled to high-resolution mass spectrometry (HRMS) to urine samples of a PPZ
user, as well as to municipal wastewater. M1, which had not been investigated in previous
monitoring studies, was found to be ubiquitous in WWTP influent and effluent (max.:
3 μg/L, detention frequency: 100%) as well as in surface water (max.: 1.2 μg/L; detection
frequency: 97%) in Germany. Its average surface water concentration was approximately
30 times higher than that of the parent compound PPZ. Moreover, quantitative structure-
toxicity relationship (QSTR) modeling indicated a lower preliminary freshwater PNEC for
M1 (4.8 μg/L) compared to PPZ (28 μg/L). The analysis of archived suspended particulate
matter (SPM) samples from the Rhine at Koblenz revealed that the concentrations of M1
increased significantly from 2005 to 2015 and were positively correlated with the
prescription volume of PPZ. Conventional biological wastewater treatment was found to
be insufficient to remove M1 (average removal: 22%). Laboratory-scale experiments and
the analysis of samples taken after different treatment steps of an advanced full-scale
WWTP demonstrated that post-treatment with activated carbon as well as ozonation can
significantly improve the removal of M1 and PPZ during wastewater treatment, thereby
reducing their release to the aquatic environment. During ozonation, a rapid oxidation of
M1 was observed, accompanied by the formation of several ozonation products, which
were proposed for the first time. The identity of the main ozonation TPs of M1 was
confirmed through the synthesis of reference compounds. Their detection in samples
collected after the ozonation step of a full-scale WWTP demonstrated the transferability of
the laboratory-scale ozonation experiments. M1 was found to be sufficiently removed from
contaminated source waters (max. raw water concentration: 0.25 μg/L) by bank filtration
under different redox conditions (removal ≥ 80 %) and by other commonly applied
purification processes in drinking water production. In summary, this study revealed that
the environmental exposure and risk associated with the use of PPZ have been previously
underestimated, which likely extends to other human pharmaceuticals. Therefore, these
findings call for more sophisticated approaches to environmental monitoring and risk
assessment of pharmaceuticals that take TPs into account.
This thesis provides an in-depth understanding of the entry paths, occurrence, fate, and
environmental significance of selected TPs in the aquatic system in Germany. It
significantly advances our understanding of the introduction of TFA into the water cycle,
by characterizing the source of wet deposition and elucidating long-term temporal trends
of atmospherically deposited TFA. Additionally, the thesis gives comprehensive insights
into the formation, behavior, removability, and potential (eco)toxicological risks of
sulfamate, PPZ and its TPs. The thesis addresses key challenges in assessing and
integrating TPs into chemical management and presents solutions to overcome these
challenges. Finally, it highlights the urgent need for increased focus on TPs in research,
aquatic monitoring, and regulation to safeguard the environment and human health.
Age-structure changes are an intrinsic feature of the demographic transition from high mortality and
fertility to low mortality and fertility. Initially, the demographic transition increases the share of the
working-age population, creating opportunities for economic boosts through demographic dividends.
Particularly some Asian countries have benefited greatly from such demographic dividends in the past.
Overtime, however, the demographic transition leads to population ageing, which brings various
implications for economies and societies worldwide. In Asia, many countries are ageing rapidly, while
others continue to maintain a relatively young age structure. These differences may also be related to
migration. Migration is also often discussed as a possible policy response to counteract population
ageing. This thesis identifies global patterns in changes in the share of working-age population and
examines associated demographic factors. With a specific focus on Asian countries, it assesses the
impact of migration on population ageing in the past and its potential impact in the future.
All analyses in this thesis are based on data from the United Nations’ World Population Prospects 2022.
First, past, present and projected age-structure changes are analyzed in the context of demographic
dividends, covering 148 countries worldwide. Cluster analyses are conducted to identify patterns of
age-structure changes between 1950 and 2100, while linear regression models are used to detect
associations between these changes and relevant demographic factors. Second, the impact of
migration on past age-structure changes is assessed for the period 1990-2020 in 51 Asian countries
using decomposition analysis. An existing decomposition approach is extended to incorporate the
concept of prospective age, which accounts for differences in life expectancy when assessing
population ageing. Third, the potential impact of migration on population ageing between 2022 and
2050 is analyzed in eleven Asian countries by adopting the United Nations’ replacement migration
concept. In this analysis, both chronological and prospective indicators of population ageing are
applied.
The results underline the heterogeneity of global age-structure changes in the course of the
demographic transition. This underscores the need to take into account a country’s specific
demographic development when assessing its potential for a demographic dividend. The experience
of some Asian countries, where rapid fertility declines in the past have been followed by sharp
increases in the share of the working-age population, is only one of several global patterns. Differences
in age-structure changes are associated with differences in fertility, but also with migration and
population momentum – two factors that have so far received relatively little attention in the
discussion of demographic dividends. Focusing on Asian countries, this thesis reveals that differences
in population ageing across countries are at least partly driven by migration. However, the volume of
migration potentially required to offset population ageing over the next decades seems unrealistically
high in most countries. The results emphasize that migration can play a role in age-structure changes,
but population ageing can barely be halted by immigration alone. Thus, comprehensive policies seem
to be a key factor in ensuring further development in ageing countries in Asia and beyond.
As digital elements become integrally embedded in everyday social life (Kaptan et al., 2022), their effects are particularly evident in the lives of children and adolescents. Up to 94% of to-day's students regularly use social media (Medienpädagogischer Forschungsverbund Südwest, 2023). Its influence on identity formation, information processing, and opinion development among young people is substantial (Höger, 2021; Pürgstaller, 2023), directly intersecting with the school’s task of preparing students for reflective participation in (digital) society.
Physical education contributes significantly to this goal through its physical, cognitive, and social dimensions (Gogoll, 2020). The themes of fitness and health are core components of the subject. Especially the COVID-19 pandemic and developments in recent years have shown that digital offerings in the field of fitness and health are gaining importance. However, problematic information and influences, particularly through social media, are frequently disseminated in this context. Addressing these issues is a responsibility of physical education and, not least, of physical education teachers, who must be equipped with the necessary (digital) competencies (Teutemacher et al., 2023).
This thesis conceptually develops a self-learning module based on foundational terminology and theories concerning (digitalizationrelated) competency models for physical education teachers, effective continuing education concepts, and the purposeful design of digital learning environments. The self-learning module can be used independently or as the initial component of a modular continuing education concept for physical education teachers within the joint project “Professional Networks for Promoting Adaptive, Action-Oriented, Digital Innovations in Teacher Education in Art, Music, and Physical Education (KuMuS-ProNeD).”
The well-founded presentation of this concept shows that an asynchronous digital format with an open structure is well-suited to address the heterogeneous needs of teachers in terms of individual learning requirements, interests, and time management. The interactive, multimodal digital learning environment-created using the widely used Microsoft Office application Power-Point in the form of an “Edubreakout” has the potential to foster selfdirected learning through an engaging gameplay experience and an individualized feedback structure. This approach blurs the boundaries between gameplay and the intended learning outcomes. Additionally, the module successfully connects to the practical teaching environment of physical education teachers and to the other components of the continuing education series. Building upon this work, the remaining research task is to evaluate the intended effectiveness using qualitative and/or quan-titative research methods.
The master's thesis examines how university open spaces influence students’ sense of place and social networking. Using the Mikadoplatz at the University of Koblenz as a case study, a quantitative online survey of 234 students was conducted, focusing on usage patterns, satisfaction, and perception of the space. Regression analyses reveal that both satisfaction with the design and time spent in the open space are significantly associated with sense of place and social networking. Furthermore, social networking mediates the relationship between time of use and sense of place. The findings provide practical insights for the design of campus open spaces.
Die qualitatitve Bedarfsanalyse untersucht die Fortbildungsbedarfe von Sportlehrkräften hinsichtlich einer digitalisierungssensiblen Gesundheitsbildung im Sportunterricht, um Schüler:innen zu einem reflektierten und gesundheitsförderlichen Umgang mit digitalen Medien zu befähigen. Die Bedarfsanalyse erfolgte mittels N=23 leitfadengestützter Interviews und zeigt, dass die befragten Sportlehrkräfte zwar Potenziale digitaler Medien erkennen, dabei die reflexive Ebene der Mediennutzung jedoch weniger präsent ist als die anwendungsorierte Ebene. Fortbildungsangebote in der Schnittstelle von Gesundheit, Sport und Digitalisierung existieren laut der befragten Lehrkräfte bislang kaum. Basierend auf den ermittelten Bedarfen wird ein modulares Fortbildungskonzept entwickelt, das ein Selbstlernmodul, ein praxisorientiertes Präsenzmodul sowie ein Online-Reflexionsmodul umfasst.
Dieses Whitepaper stellt die Grundlagen eines KI-Kompetenzmodells vor, welches im Rahmen des Projektes IH-evrsKI an der Universität Koblenz entwickelt wurde. Es dient der Beschreibung und Operationalisierung von KI-Kompetenzen auf unterschiedlichen, aufsteigenden Niveaustufen, inspiriert vom Modell von Dreyfus und Dreyfus (Neuling bis Experte). Das Modell ist als Baumstruktur angelegt (Wurzel, Stamm, Baumkrone). Es fokussiert sich auf die fachunabhängigen Grundlagen-Kompetenzen der „Wurzel“ und die fachübergreifenden Kompetenzen des „Stammes“, die unabhängig von der eigenen Fachlichkeit jede*r KI-Anwender*in besitzen soll. Es ist bewusst offen, dynamisch und anpassbar gestaltet und dient der Beschreibung und Klassifizierung von Lehr- und Lerninhalten, primär im Kontext der Hochschullehre.
In der Dissertation Freiheit und Werte bei Jean-Paul Sartre wird das Verhältnis zwischen
Freiheit und Werten in der Philosophie von Jean-Paul Sartre analysiert. Es wird untersucht, auf
welche Weise die existenzielle Freiheit des Menschen mit seinen moralischen und
außermoralischen Werten nach Sartre zusammenhängt. Ziel der Untersuchung ist es, einen
Beitrag zum Verständnis von Sartres Wertlehre sowie seiner Ethik der Authentizität zu leisten.
Grundlage für die Untersuchung bilden neben Sartres philosophischen Werken, seine
literaturtheoretischen sowie politisch-gesellschaftlichen Schriften. Ausgehend von einer
Analyse der existenziellen Freiheit bei Sartre wird der vielschichtige Zusammenhang zwischen
Freiheit und Werten bei Sartre analysiert und in den Gesamtkontext seiner Philosophie gestellt.
Die Dissertation zeigt, dass sich in Sartres Werk sowohl eine subjektivistische als auch eine
objektivistische Wertlehre ausmachen lässt. Während Sartre in vielen Passagen seines Werkes
die subjektivistische Position vertritt, dass alle moralischen und außermoralischen Werte auf
das bewertende Subjekt zurückgehen, präsentiert er an anderen Stellen seines Werkes den
moralischen Wert der Freiheit sowie den außermoralischen Wert des An-sich-für-sich.
Abgesehen von jenem Spannungsverhältnis macht die Untersuchung deutlich, dass der
moralische Wert der Freiheit für Sartre innerhalb seiner gesamten Philosophie von großer
Bedeutung ist. Eine Verwirklichung jenes Wertes ist nach Sartre nicht nur zentraler Bestandteil
einer engagierten Literatur, sondern auch für eine gerechte Gesellschaft wesentlich.
Eisenbahnunternehmen setzen Condition Monitoring Systeme (CMS) zur Überwachung ihrer Anlagen und Komponenten ein. CMS sind im Risikomanagement der Branche relevant, aber ihr Einsatz leidet unter einem Präventionsparadoxon: Sie werden oft erst nach Schäden oder Richtlinien eingeführt. CMS können auch den Instandhaltungsaufwand reduzieren. Bei den streckenseitigen WTMS tragen Infrastrukturbetreiber die Kosten, während Verkehrs-unternehmen den Nutzen durch effizientere Instandhaltung sehen. Um fundierte Geschäftsmodelle zu entwickeln, muss deshalb der Nutzen von CMS quantifiziert werden. Die Informationsqualität, einschließlich der Sensoren und der Symptomaussagekraft, beeinflusst diesen Nutzen. Diese Verbindung von Anwendungswert und Nutzen ist bisher unzureichend erforscht. Aufgrund dessen ist das Forschungsziel folgendermaßen gesetzt worden: Entwicklung eines systemdynamischen Modells und eines Verfahrens zur Erfassung des Informationswertes von Condition Monitoring Systems, anhand des Fallbeispiels der Radsatzlagerüberwachung im Eisenbahnverkehr.“
Das Forschungsziel dieser Arbeit umfasst als Erkenntnisziel das Verständnis der Zusammenhänge und Wechselwirkungen im CMS und dabei den Nutzen des Einsatzes der Systeme zu bewerten. Das Gestaltungsziel beinhaltet die Untersuchung der Eignung des systemdynamischen Verfahrens. Zur Erreichung dieser Ziele sollen folgende Forschungsfragen beantwortet werden:
1. Welche Ziele verfolgen die Eisenbahnorganisationen in Bezug auf den Betrieb ihrer Radsatzlager und inwiefern können die Informationen aus den Messdaten der heutzutage eingesetzten Radsatzlagerüberwachungssysteme zur Zielerreichung beitragen?
2. Lassen sich mit der systemdynamischen Vorgehensweise, die für die Bewertung von CMS relevanten Wechselwirkungen im Eisenbahnsystem abbilden?
3. Lässt sich anhand der systemdynamischen Vorgehensweise untersuchen, welche Informationen für die Erhöhung des Nutzens der Radsatzlagerüberwachungssysteme relevant sind?
Die Ergebnisse der Arbeit erwirken die Erkenntnis, dass die Methodik dazu geeignet ist, die relevanten Zusammenhänge und Wechselwirkungen darzustellen und mithilfe der Simulationsergebnisse relevante Instandhaltungsstrategien und der Nutzen von RDMT zu bewerten. Damit sind die Ergebnisse sowohl für die Forschung als auch für Entscheidungsträger in der Eisenbahnbranche relevant.
Water is the basis of all life, a biotope for a variety of organisms and an important component of the
natural balance. For this reason, it is essential to protect water from contamination by anthropogenic
organic micropollutants (MPs) and to develop various innovative strategies for the treatment and reuse
of wastewater. Conventionally biologically treated municipal wastewater contains many organic MPs
that pose a potential threat to aquatic ecosystems and drinking water resources. To date, the focus has
been on physicochemical processes such as activated carbon treatment or ozonation to improve the
removal of MPs in wastewater treatment plants (WWTPs), while knowledge of biological removal
processes and ways to optimize the biological removal of organic MPs is comparatively limited.
Especially in arid and semi-arid regions, treated wastewater is also an important resource for wastewater
reuse for irrigation or drinking water treatment. In consequence of increasing droughts due to climate
change, the reuse of treated wastewater is also increasingly being discussed in Germany. Often the water
is reused after targeted groundwater recharge, while concepts for optimizing the removal of MPs during
soil passages are still scare. In order to assess the potential and limitations of biological wastewater
treatment as well as targeted groundwater recharge for the removal of organic MPs, a better knowledge
of the biological biotransformation processes and the environmental conditions influencing them is
required. Microbial communities and their enzyme pools play a key role in these processes. However,
the influence of environmental conditions on the composition and functional characteristics of microbial
communities, and how this in turn affects the biotransformation potential of MPs with different
structural characteristics, has been little studied. In addition, knowledge about MP-biotransforming
bacteria is often derived from enrichment or even pure culture studies, which are not directly transferable
to the environment.
Against this background, this dissertation focuses on the systematic investigation of the
biotransformation of MPs in contact with activated sludge (simulation of biotransformation processes
in biological treatment stages of WWTPs) and filter materials (simulation of processes in groundwater
recharge systems) under defined laboratory conditions. The aim is to elucidate relationships between
the composition and functional characteristics of microbial communities, microbiologically determined
biotransformation processes and their optimal process conditions, as well as the chemical structure and
primary enzymatically catalyzed biotransformation reactions of MPs.
The first part of the work focuses on the composition of microbial communities and the
biotransformation of MPs depending on defined process parameters in five differently operated
wastewater reactors, divided into two reactor cascades at pilot scale and one full-scale WWTP. The first
cascade consisted of three reactors, the first of which served as a reference reactor with conventional
activated sludge (CAS) treatment. The following reactors operate under anoxic to anaerobic and strictly
anaerobic conditions, respectively. The other cascade consists of two reactors, the first anaerobic and the second aerobic, followed by a simplified vessel to prevent nitrate output, as half of the effluent was
recirculated to the first anaerobic reactor. All five reactors and the WWTP were analyzed for the
biotransformation of 33 MPs and the composition of the microbial community by LC-MS/MS and 16S
rRNA gene sequencing, respectively. The results showed a slight but significant improvement in the
overall biotransformation of MPs in the reactor cascades (about 20%) compared to the WWTP. In
particular, the biotransformation of compounds that are not or only slightly degradable (< 30%) in
conventional wastewater treatment, such as diatrizoate, venlafaxine and diclofenac, was significantly
improved (about 70%). Twelve of the 33 MPs showed an increase in biotransformation of at least 30%
compared to the reference reactor and the WWTP. In detail, the reactor cascade consisting of the
anaerobic pre-treatment showed three times more MPs than the reactor cascade with the anaerobic post-
treatment. Although the environmental conditions (nutrient availability and redox conditions) differed
considerably between the reactors, molecular analysis of the microbial community revealed a core
community of 143 genera, with 54% of the taxa belonging to the phylum Proteobacteria, with the beta
subdivision as the most dominant class. On the other hand, a specialized community consisting of 90
genera was identified that contributed most to the differences between the reactor communities. These
genera were shown to reflect the prevailing nutrient, redox and operating conditions of each treatment.
It was also found that the relative abundances of several genera of the specialized community correlated
with the biotransformation of certain MPs as well as with process parameters (especially redox
conditions). These genera may not necessarily be directly involved in the biotransformation of MPs, but
could be promising biological indicators for the establishment and control of operating conditions
favorable to the biotransformation of certain MPs. For the two reactor cascades analyzed, it was
concluded that the redox conditions as well as the carbon supply were essential factors for the
composition of the specialized community and the biotransformation of the MPs. In addition, the 16S
rRNA gene amplicon sequencing proved to be a complementary tool to confirm process conditions by
correlation. In conclusion, the efficiency of MP biotransformation in conventional WWTPs depends on
key parameters such as redox conditions, biodiversity or the presence of several genera of specialized
microbial communities identified as indicator organisms.
Against the background of previous knowledge that biofilms from moving bed biofilm reactors
(MBBRs), which have been used so far in a few WWTPs, are more efficient in biotransforming certain
MPs, the second study used laboratory batch experiments to investigate the extent to which the
biotransformation potential of carrier-attached biofilms and suspended sludge from hybrid MBBRs
differ between three WWTPs, and whether these differences were also reflected in the composition of
the bacterial communities. The 31 MPs investigated were grouped according to their biotransformation
rates and examined for relationships between the biotransformation behavior and the known primary
biotransformation reactions are discernible. In general, the study confirmed the potential of hybrid
MBBRs for improved biotransformation of a variety of MPs. This could be attributed to an increased
biotransformation potential of the carrier-attached biofilms, especially for oxidatively degradable substances such as trimethoprim, diclofenac and mecoprop. Correlation analyses showed statistically
significant relationships between the occurrence of certain bacterial genera (e.g. Acidibacter, Nitrospira
or Rhizomicrobium) and the biotransformation rates of certain MPs. Thus, some of the identified genera
were also discussed as suitable indicators for the biotransformation potential of suspended sludge or
carrier-attached biofilm.
In the third part of the work, the biotransformation of up to 78 MPs was investigated under different
redox and substrate conditions in a defined column system at laboratory scale as well as ex situ under
uniform incubation conditions by incubating the column filter material in batch experiments. MPs were
categorized based on their biotransformation behavior and how well these categories matched primary
transformation reactions known from the literature or predicted using the Eawag pathway prediction
system for modelling microbial biotransformation pathways. The column system investigated consisted
of two large columns filled with technical sand, an intermediate aeration and four smaller columns, all
connected in series. In the first column, characterized by a carbon-rich environment with high biomass
and strong oxygen depletion, 23 MPs were efficiently removed (>80% removal), while 19 substances
were better or exclusively removed under carbon-limited oligotrophic conditions in the columns after
re-aeration. While the MPs removed predominantly in the first column were mostly attributed to
biotransformation by comparatively ubiquitous and fast transformation reactions such as the oxidation
of alcohols or amide hydrolysis, the biotransformation of MPs removed more efficiently under the oxic
and oligotrophic conditions in the rear columns was characterized by slower transformation reactions
such as N-dealkylation of primary and secondary amines or the hydroxylation of aromatic rings. In
addition, several specific reactions described in the literature, such as the cleavage of C-Cl and C-O
bonds, could only be identified under oligotrophic conditions. The results suggest that conditions of
limited carbon availability may favor the development of alternative metabolic biotransformation
pathways. Furthermore, the observed association between system-specific MP removal and the expected
primary biotransformation reactions from the literature and prediction systems could serve as a basis for
accurately identifying the relevant enzymes in future studies, using metagenomic or metatranscriptomic
data.
Based on these considerations, molecular biological investigations were carried out in the fourth part of
this work by generating sequence-based data complementary to the biotransformation rate constants
during the batch experiments carried out in the third study. A first aim was to identify a statistical relation
between the microbial composition, the process conditions and the nutrient availability as well as the
biotransformation potential of 42 MPs depending on the biomass in the columns of the system.
Furthermore, the metabolic activities of the microbial communities of the first two columns of the
system were analyzed and the identified active enzymes were assigned to known metabolic pathways
and the activities were compared. In addition, the extent to which the biotransformation potential of the
columns was also reflected in the activity of enzymes that have been proven to belong to biotransformation pathways of MPs was investigated. To this end, modern sequencing methods were
used to generate data on the composition of the microbial community (16S rRNA gene sequencing) and
its actual activity in the form of expressed genes (metatranscriptome sequencing). The biotransformation
rates from the batch experiments of the third study were used by normalizing them with the gene copy
numbers (kbio), which were representative of the biomass. For half of the MPs, the highest normalized
kbio values were identified in the rear columns with increased carbon-limiting conditions. Furthermore,
most of the MPs investigated, such as sulfathiazole, sulfamethoxazole or rufinamide, showed an
improved biotransformation potential in these columns. The higher biotransformation potential under
carbon-limiting conditions was also confirmed by metatranscriptomic analysis, where an increased
metabolic capability and a higher functional activity to degrade MPs were observed in the carbon-
limiting column compared to the first nutrient-rich column. Taxonomic analysis revealed a decreasing
trend in biodiversity with a simultaneous increase in carbon-limiting conditions. Furthermore, the
microbial community differed depending on the nutrient and process conditions of the column materials
analyzed. However, within the carbon-limiting columns, the microbial community was similar and were
dominated by the genus Pseudomonas. By relating the biotransformation of MPs to the relative
abundance of taxa in the carbon-limiting columns, the genera of the phylum Acidobacteria and the
classes Alpha- and Gammaproteobacteria showed particularly high associations. In addition, four genera
showed a statistically positive correlation with the two structurally similar MPs sulfamethoxazole and
sulfathiazole.
Overall, no general improvement in biotransformation could be found for all MPs under the conditions
considered, with system- and condition-specific changes observed for individual compounds. However,
the studies indicated favorable environmental conditions for groups of MPs that showed increased
biotransformation linked with high abundant taxa, especially under carbon-limiting conditions and in
carrier-attached biofilms.
Within the scope of this work, new test methods were developed to determine the characteristic product properties of ladle well filler sands. Background is that up to now, there are no approved test methods for these product properties such as pourability, sintering behavior and infiltration behavior.
To substantiate this deficiency in testing methods, the general state-of-the-art testing methods of cohesionless bulk materials is presented and a variety of publications on ladle well filler sands are reviewed for their applied testing methodology.
The development of new test methods for the characterization of ladle well filler sands was based on test methods that were in part already standardized, such as the permeability measurement (infiltration) according to DIN 18130-1 from the field of geotechnics, the determination of the flow time with flow cups for coating materials (flowability) according to DIN EN ISO 2431:2011 and the monotonic heating method (MMH) according to ASTM E2584-20 for determining the thermal conductivity.
Since these test methods were not designed for examining free-flowing, non-cohesive bulk materials and therefore not for examining ladle well filler sand, it was necessary to adapt the parameters of the standardized test methods for use with well filler.
The parameters of the test methods mentioned (DIN 18130-1; DIN EN ISO 2431 and ASTM E2584-20) were checked for applicability and transferability to ladle well filler sand and new suitable parameters were added. The reproducibility of the results of the test methods was checked by a series of tests and the decisive influencing factors of ladle well filler sand on the results were determined.
The relevance of the results of the newly developed test methods was verified based on results from the European research project ILORA ("Improvement of Ladle Opening Rates", funded by the "Research Fund for Coal and Steel" RFCS, 2013-2016) and numerous publications with results from other research projects.
From the results of the newly developed test methods, key figures for the pourability, sintering behavior and infiltration behavior of ladle well filler sands were derived. The combination of these key figures was converted into a holistic analysis of ladle well filler sands, finally leading to an evaluation grid for well fillers. It is exactly that grid respectively network, that now allows for the first time to make qualified and reliable statements about the suitability for use of ladle well filler sands prior to industry application, which significantly facilitates the new development of such well fillers.
Microplastics (MP), i.e., plastic particles < 5 mm, are perceived as a threatening envi-
ronmental and human health issue. Growing public interest in this class of contaminants
requires standardized and harmonized methods for their quantification. While an abun-
dance of analytical methods (both particle-based and mass-based) for the detection of
microplastics is available, existing studies on the quantity of MP in the environment lack
comparability. Therefore, the aim of this work was to establish a fast, reliable screen-
ing method for the quantification of the most common synthetic polymers in complex
environmental samples.
This was accomplished by a two-step pressurized liquid extraction (PLE) followed by
analysis via pyrolysis coupled to gas chromatography and mass spectrometry (Py–GC–
MS). In the first extraction step, a large part of the organic matrix was removed with
methanol at 100 ∘C and 100 bar, followed by a second step with tetrahydrofuran at
185 ∘C and 100 bar to extract the polymers that were subsequently adsorbed to silica
gel and measured with Py–GC–MS. With the developed method, limits of quantification
in an environmentally relevant concentration range of 7–8 μg g−1 for the most common
thermoplastic polymers polyethylene (PE), polypropylene (PP), and polystyrene (PS)
were achieved.
In order to improve the robustness of the method, poly(styrene-d5) (PSd5) was initially
applied as internal standard. However, further analyses revealed a deuterium–hydrogen
exchange during Py–GC–MS measurement, which was catalyzed by the inorganic ma-
trix. This effect was thereupon systematically investigated and poly(4-fluorostyrene) was
established as a new, stable internal standard.
While the developed method enabled the quantification of PE, PP, and PS, several other
polymers had to be excluded. In particular, the quantification of poly(ethylene tereph-
thalate) (PET) proved challenging via Py–GC–MS. A variety of catalytic effects by the
inorganic matrix was revealed and systematically investigated, e.g., changes in pyrolysis
product distribution. Several different sample preparation approaches failed to resolve
these issues. PLE led to a depolymerization of PET which was also catalyzed by the
inorganic sample matrix.
After further optimization and reduction of false positives, the developed method has
the potential to be included in future standardized procedures for MP quantification. It
provides a fast, robust analysis of MP in complex samples, while also considering widely overlooked matrix effects. Potential quantification approaches for other polymers that are
not included in the developed method (e.g., tire wear particles, paint particles) are also
discussed in this thesis.
Invasive crayfish are a serious threat and ecosystem engineers that compete with native species for shelter and food resources, show combative interactions against native species, and negatively affect species diversity. In this work, I used two North American invasive crayfish species that have successfully spread across Europe spinycheek crayfish (Faxonius limosus) and signal crayfish (Pacifastacus leniusculus) as models to assess their potential Impacts on native benthic fish, stone loach (Barbatula barbatula) and bullhead (Cottus gobio), which are among the most common benthic fish in Europe. I have investigated the competition for shelter and agonistic interactions between these invasive crayfish species and the native benthic fish species under laboratory conditions have employed a multi-object tracking algorithm to monitor and visualize the fish's and crayfish's activity inside the experimental tank. Spinycheek and signal crayfish successfully displaced both benthic fish species from their shelter. Both crayfish species attected the behaviour of stone loach, reducing its activity and increasing its hiding outside the shelter. Although bullheads did not reduce shelter use, they displayed similar behavioural changes, if less intense, In addition, I demonstrated remarkable aggressive interactions by both crayfish species against stone loaches and bullheads. Further investigations were performed to assess how variations in crayfish density influence the structure of invertebrate communities. I conducted comparative analyses of community composition across nine stream sites with varying densities of signal crayfish in Wied Stream, Germany. These findings revealed a correlation between crayfish density and diversity and evenness of invertebrates, suggesting that signal crayfish pose a substantial threat to Invertebrate biodiversity
In conclusion, this thesis reveals that these invasive crayfish species not only compete with native biota for essential resources but also fundamentally alter the ecological dynamics of freshwater habitats. This thesis emphasises the urgent need to manage and mitigate the potential consequences of crayfish invasion and to preserve native aquatic ecosystems.
In sowohl den Kulturwissenschaften als auch den Kognitionswissenschaften haben sich neuere
Theorien etabliert, welche verstärkt die Verkörperung und Materialität unseres Denkens, Fühlens und
Handelns betonen. Diese Dissertation untersucht aus der Perspektive der philosophischen
Anthropologie, wie die ‚material culture studies‘ sowie die ‚embodied cognition‘-Forschungen
zusammengedacht werden können. Im Fokus liegt hier der Phänomenbereich der Musik: Denn nicht
nur spielen bei dieser eine Vielzahl von Gegenständen der materiellen Kultur eine zentrale Rolle
(Instrumente, Tonträger, etc.), sondern auch der Körper des hörenden oder musizierenden Subjekts.
Die philosophische Reflexion erfolgte vor allem aus der Perspektive des Enaktivismus, einer
spezifischen Strömung der ‚embodied cognition‘, ergänzt durch Konzepte und Ansätze aus den
Traditionen der Phänomenologie und des Pragmatismus. Diese wurden nicht nur herangezogen, um
zusammen mit dem enaktivistischen Denken auf der Sachebene die verkörperte Natur der Musik
darzustellen, sondern auch um die methodische Problemstellung zu behandeln: Der
phänomenologische Gedanke des Doppelaspekts von Leib und Körper (Fuchs) und die pragmatistische
Anthropologie der Artikulation (Jung) dienten eben dazu, das Zusammendenken von Kognitions- und
Kulturwissenschaften in Bezug auf Musik zu ermöglichen.
So ließen sich verschiedene Detailfragen zu den beiden größeren Themenkomplexen der
Wahrnehmung von und des Umgangs mit Musik(-kultur) beantworten, inklusive solche bezüglich der
Rolle des Affektiven und des Sozialen sowie nach der möglichen Ausdehnung von Kognition und Leib.
Zusätzlich ergab sich so auch eine exemplarische Demonstration der methodologischen Gedanken, da
diese Fragestellungen anhand der genannten Konzepte untersucht wurden und so deren Fruchtbarkeit
für das Verbinden von natur- und kulturwissenschaftlichen Forschungen dargelegt werden konnte.
This habilitation thesis compiles research on the challenges of complex networks in com-
puter science and their applications. It includes case studies on interdisciplinary research
in life sciences, computational social sciences, and digital humanities. In the life sciences,
knowledge graph approaches are commonly used for clinical and biomedical data. This
thesis focuses on context mining, algorithmic challenges, and link prediction. In social
sciences network approaches, the goal is to connect social network analysis with ontology-
driven research on the labor market. Although data sets are frequently available in social
sciences, this is not always the case in the humanities. Therefore, when applying complex
network approaches such as social network analysis to textual data, hermeneutical and
methodological considerations are necessary. Once these considerations are addressed,
data science methods such as text mining can be used to construct networks from texts.
This thesis presents two case studies on social network analysis, in addition to addressing
the challenges of interdisciplinary research on complex networks in computer science. By
describing three different domains, it demonstrates the existence of a common toolbox that
utilizes methods from data science and graph theory. Consequently, this thesis argues for
more interdisciplinary exchange
Schülerinnen und Schülern eine wirkungsvolle Begegnung mit Literatur zu ermöglichen, stellt hohe Anforderungen an die Unterrichtsvorbereitung: Material muss ausgewählt und gestaltet, Lernaufgaben müssen vorbereitet und eingesetzt und Unterrichtsgespräche müssen antizipiert und moderiert werden. Gerade von Referendarinnen und Referendaren können die damit verbundenen Anforderungen als sehr herausfordernd – auch als überfordernd – empfunden werden.
Mit dem Ziel, den auszubildenden Lehrerinnen und Lehrern ein erstes handhabbares Instrumentarium zur Planung und Gestaltung des Literaturunterrichts an die Hand zu geben und ihnen dadurch zu frühen ‚Gelingenserfahrungen‘ zu verhelfen, wurde am Studienseminar für das Lehramt an Gymnasien in Koblenz ein Ausbildungsmodell entwickelt. Der Erörterung, wie die Implikationen dieses Modells auch auf den Literaturunterricht übertragen werden können, widmet sich die Dissertation.
Auf die verschiedenen Faktoren zur Steuerung des Unterrichts – die Phasierung der Stunde, die Formulierung von Lernaufgaben, die Darbietung des Materials und die Moderation der Unterrichtsgespräche – blickend, werden unterschiedliche Handlungsoptionen vorgestellt und didaktisch ausdifferenziert. Stichprobenuntersuchungen aus zwei Unterrichtsstunden – zu Rilkes Gedicht ‚Natur ist glücklich‘ (Klasse 9) und zu Bettina Wegners Lied ‚Gebote‘ (Klasse 12) – veranschaulichen und konkretisieren die Positionen.
Aus der Verbindung der didaktischen Überlegungen mit den empirischen Stichprobenuntersuchungen entsteht der Entwurf eines neu nuancierten Ausbildungsmodells für den hermeneutisch-diskursiven Literaturunterricht.
For most humanoid robots, falls are the predominant limiting factor affecting their applications and autonomy to move in irregular environmental conditions. A similar susceptibility to falls can also be observed in humans during various daily activities due to balance control deficits or neuromusculoskeletal disorders. Despite the remarkable adaptability of the human locomotor system, as well as recent developments in robotics, balance loss and falls persist. To gain new insights into the complex interactions between bipedal locomotion and balance loss, we linked humanoid robots and humans into humanoid systems and focused on the accurate monitoring of the locomotor segment’s kinematics. This is an essential component for detecting and assessing balance disturbances, thereby improving the robustness during bipedal locomotion. Therefore, this thesis focused on the development of an inertial measurement cluster for direct kinematic measurements of, i.e. omitting numerical differentiation, a mathematical process that greatly amplifies single noise. However, despite the aim to increase the resilience of the bipedal locomotion and thereby reduce the fall risk in humanoid systems, the methods applied in this thesis had to differ in addressing the detection and assessment of balance disturbances. Therefore, the thesis comprises three sets of studies concerning the fields of humanoid robotics, humans, and sensor uncertainty assessment. In the first theoretical study, we introduced the mathematical concept of the inertial measurement cluster with special emphasis on its impact on providing sensory feedback on detected situational loss of balance during bipedal locomotion in humanoid robots. This was achieved through a kinematics-driven framework based on robust inverse dynamics evaluation and the reduction of numerical differentiation in critical terms by directly measuring the angular acceleration vector. Subsequently, we proposed a sensor fusion algorithm to estimate both the magnitude and application line of externally applied forces on robots in theory. In the second set of studies about humans, we addressed the remote detection and assessment of trip and slip events. Therefore, the sensitivity of the proposed wearable sensor-framework system (inertial measurement cluster combined with an evaluation framework) to automatically detect balance disturbances was examined. We were able to automatically assess the balance recovery performance of individuals and resolved the well-known adaptation phenomena to repeated trip-like perturbations. Subsequently, we expanded the functional scope of the wearable sensor-framework system and provided evidence of its high accuracy in detecting and classifying balance disturbances during simulated activities of daily life. In the third set of studies, we established a multi-method framework to provide an experimental angular acceleration reference to objectively quantify the measurement uncertainty of the proposed inertial measurement cluster. Moreover, we confirmed the reference can serve as a measurement standard. Finally, based on the measurement standard, we proposed a concept for an adjustment routine to compensate for the deterministic errors of the inertial measurement cluster and confirmed a measurement uncertainty reduction. In conclusion, we established a sensor suitable for humans and humanoid robots, omitting numerical differentiation, and confirmed its significantly reduced measurement uncertainty. The proposed framework approaches based on the inertial measurement cluster were the key factors for the accurate detection of balance disturbances in humanoid robots as well as humans, highlighted by comparisons to conventional methods based on numerical differentiation. Consequently, the proposed sensor and frameworks have the potential to provide new insights into the causes of balance disturbances or factors that lead to insufficient reactive actions to prevent falls in humanoid robots and humans.
Enhancing AI Telephony System with
Large Language Models: A Comparative
Study on ’Telegra KIT’
(2025)
Nowadays, artificial intelligence (AI) has been widely used in telephony systems. It
allows telephony systems to automate customer interactions without any human in-
tervention. However, traditional approaches used across various tasks in telephony
systems has some limitations. To address these limitations, this thesis investigates
the potential of Large Language Models (LLMs) to enhance AI-driven telephony
systems by improving intent recognition, entity extraction, inquiry question gener-
ation, and synthetic training data creation.
We have conducted a comparative study to evaluate the performance of LLM-
based methods and traditional methods across above mentioned tasks. This study
is conducted on Telegra-KIT, an AI-based telephony platform. We have used real-
world data of Telegra-KIT to assess the performance. The results show that LLMs
outperformed traditional approaches by improving intent recognition accuracy from
18.42% to 39.71% and entity extraction accuracy from 52.69% to 82.21%. LLM-based
approach was also able to create effective inquiry questions when a caller’s intent is
uncertain. The results also demonstrated the ability of LLM to create high-quality
synthetic training data to address data scarcity issues and enhance model general-
ization.
The findings of this thesis contribute to the advancement of AI telephony sys-
tems by offering a more context-aware, adaptable approach for important tasks in
telephony.
Feuerfestmaterialien nehmen in industriellen Prozessen, die hohe Temperaturen erfordern, eine maßgebliche Rolle ein. Eine vollständige Charakterisierung ihrer Eigenschaften ist erforderlich, um potentielle Defizite zu identifizieren und adäquate Struktur-Eigenschafts-Korrelationen prognostizieren zu können. Die vorliegende Arbeit evaluiert anhand von drei exemplarischen Anwendungsbeispielen die Eignung der Röntgen-Computertomographie (engl.: X-Ray Computertomography, XRT) als Analysemethode zur Untersuchung feuerfester Materialien. Der Schwerpunkt liegt hierbei auf Strategien zur Untersuchung des Gefüges hinsichtlich seiner Strukturen, Defekte sowie Porosität bzw. Porenverteilung und -morpho-logie und darüber hinaus auch auf der Analyse von Rissen. Die XRT ermöglicht die hochauflösende, zerstörungsfreie, dreidimensionale (3D) und reproduzierbare Untersuchung innerer und äußerer Strukturen des Körpers. Die im Rahmen dieser Arbeit durchgeführten Studien verdeutlichen, welches Potential sich insbesondere bei der Kombination der XRT mit konventionellen Methoden ergibt.
The proliferation of online abuse on social media platforms has emerged as a significant concern, negatively impacting users' mental health and online experiences. While the Natural Language Processing (NLP) community has developed various computational methods for abuse detection, including Support Vector Machines (SVMs) and Convolutional Neural Networks (CNNs), existing approaches predominantly focus on identifying explicit forms of abuse. This narrow focus overlooks subtle and contextual forms of online harassment, which can be equally damaging to users' wellbeing.
This thesis presents a novel approach to online abuse detection by integrating contextual embeddings with sentiment analysis features through the fine-tuning of Large Language Models (LLMs). Our methodology leverages a comprehensive dataset of 47,000 annotated tweets for training, combined with sentiment analysis capabilities developed using 50,000 IMDB movie reviews. The system employs DistilBERT architecture to develop a sophisticated detection framework capable of identifying six distinct categories of abuse: ethnicity-based, age-based, gender-based, religion-based, other cyberbullying, and non-cyberbullying content. The author established a rigorous evaluation framework employing multiple metrics, including accuracy, recall, and F1 score, to assess the model's performance in detecting both explicit and nuanced forms of online abuse.
The integrated system achieved an overall accuracy of 85\% across 6 categories on the cyberbullying dataset, outperforming other methodologies applied to the same data. In direct comparison, our approach— which uniquely combines contextual embeddings with sentiment analysis—demonstrated significant improvements over traditional fine-tuning methods, such as those using only BERT or RoBERTa, particularly in detecting subtle forms of abuse. Most notably, our system was more effective at identifying passive-aggressive content and context-dependent harassment, challenges that often cause conventional detection methods to fall short. This enhanced performance can be attributed to the model's ability to capture nuanced linguistic cues through its integrated analysis of both contextual information and sentiment, thereby offering a more refined interpretation of potentially harmful content.
This research emphasizes the critical importance of incorporating subtle abuse detection into online content moderation systems. By developing more sophisticated detection methods that can identify both overt and nuanced forms of harassment, this work contributes to the creation of safer and more inclusive online spaces that facilitate constructive dialogue. The findings of this study have significant implications for the development of more effective content moderation tools and the broader goal of fostering healthier online communities.
Analyse und Bewertung der Resilienz von Unternehmen und Geschäftsprozessen aus Ressourcensicht
(2025)
Companies can be affected by events that adversely impact their business operations. These events can originate from corporate environments or within companies themselves. The effects of these events may be quite diverse and can threaten the survival of companies in the worst case. To deal with events that can adversely impact business operations of companies, the concept of resilience can be used. The concept of resilience relates to the ability of companies to handle adverse circumstances. It encompasses different aspects from measuring to restoring and strengthening the resilience of companies. This dissertation deals with the concept of resilience within the corporate context. It considers the concept of resilience from a company and business process perspective and provides different research contributions for this contexts. From a company perspective, a concept and a model are presented that serve as the basis to analyse the resilience of companies. The concept shows essential elements that are important for considering the resilience of companies. The model outlines the range that can be used to analyse the resilience of companies. Furthermore, a corporate maturity model is introduced to assess the resilience of companies. It encompasses different attributes and resilience levels to determine and improve the resilience of compannies. From a business process perspective, a lifecycle and metrics for business process resilience are presented. The lifecycle shows different phases relating to resilience considerations of business processes. The metrics are used to measure the resilience of business processes.
Die vorliegende Arbeit untersucht die Forschungsfrage Welche fachspezifischen Faktoren beeinflussen den Einsatz digitaler Medien in der sportlichen Lehre von rheinland-pfälzischen Sportlehrkräften und Lehrkräftebildner:innen? Grundlage der Untersuchung bildet das Will-Skill-Tool-Modell zur Technologieintegration von Knezek et al. (2003), das drei zentrale Einflussfaktoren differenziert: (1) Die individuellen Haltungen und Einstellungen der Lehrperson gegenüber digitalen Medien (Will), (2) die subjektiv wahrgenommenen digitalisierungsbezogenen Kompetenzen (Skill) und (3) der Zugang zu technischer Infrastruktur (Tool).
Im Rahmen der Studie wurden 55 problemzentrierte leitfadengestützte Interviews mit rheinland-pfälzischen Sportlehramtsstudierenden, Lehramtsanwärter:innen, Lehrkräften, Seminarleiter:innen des Unterrichtsfaches Sport und Hochschuldozierenden, welche in der universitären Ausbildung von Sportlehrkräften involviert sind, durchgeführt.
Die Ergebnisse zeigen, dass die Beteiligten digitale Medien maßvoll einsetzen, wobei der Schwerpunkt auf der Nutzung von Videos und der Entlastung der Lehrperson liegt. Die Befragten stehen dem Einsatz digitaler Medien in der sportlichen Lehre überwiegend positiv gegenüber, empfinden jedoch häufig ein Spannungsfeld zwischen Mediennutzung und einem potenziellen Verlust an Bewegungszeit. Die erforderlichen digitalisierungsbezogenen Kompetenzen sollen aus Sicht der Be-fragten das Lernen mit Medien als Unterrichtswerkzeuge unterstützen, während kritisch und reflexive Aspekte kaum thematisiert werden. Im Vergleich zu Schulen wird die technische Ausstattung von Sporthallen als verbesserungswürdig wahrgenommen, was den Medieneinsatz hemmt. Die COVID-19-Pandemie hatte laut den Befragten einen signifikanten Einfluss auf den Medieneinsatz, die persönlichen Einstellungen und die individuellen digitalisierungsbezogenen Kompetenzen.
Die Ergebnisse deuten darauf hin, dass der Medieneinsatz nicht mehr ausschließlich als abhängige Variable betrachtet werden kann, sondern selbst Einfluss auf die Aspekte Will und Skill ausübt. Die spezifische Betrachtung der Modellkategorien legt nahe, dass dem Aspekt Tool für die sportliche Lehre eine besondere Bedeutung zukommt. Handlungsempfehlungen zur Förderung eines nachhaltigen und effektiven Einsatzes digitaler Medien in der sportlichen Lehre umfassen die verbindliche Integration digitaler Medien in Fachcurricula, die Gestaltung niederschwelliger Fortbildungen, die adäquate Ausstattung von Sporthallen und den Ausbau von Unterstützungsstrukturen.
Gender disparities in STEM (Science, Technology, Engineering, and Mathematics) fields remain a significant challenge, with women often underrepresented. Spatial abilities, particularly mental rotation (MR), are crucial for success in STEM, yet significant gender differences in these skills persist. This research aims to explore the factors contributing to these differences, focusing on emotional reactivity, self-concept, anxiety, and their impact on performance in mathematical and spatial tasks among primary school children. This research synthesizes findings from three related studies involving N=303 primary school students, consisting of 146 girls and 155 boys with a mean age=8.70 (SD=1.11) years. Data were collected through standardized questionnaires assessing self-concept, spatial and maths anxiety, and preferences for STEM subjects. Cognitive performance was evaluated using a computerized, novel Mental Rotation Task (nMRT) incorporating gender-congruent and neutral stimuli and various maths tasks correlating with mental rotation. Physiological responses were measured using galvanic skin response (GSR) to assess the impact of emotional reactivity on task performance. All data were collected in the classroom environment to increase ecological validity and generalizability of findings. Across studies, girls demonstrated higher maths and spatial anxiety, lower maths self-concept, and a lower preference for maths as a STEM subject compared to boys. These factors were significantly associated with performance differences in both maths and MR tasks. Higher emotional reactivity, as evidenced by GSR, and increased response time were associated with better scores on difficult items, that is, abstract stimuli rotated in-depth. Emotional reactivity also affected maths task completion times, with girls demonstrating lower physiological arousal linked to shorter processing time. Gender, subject preference, math self-concept and anxiety levels emerged as significant predictors of task performance on both maths and spatial tasks. The results underscore the influence of self concept, anxiety and physiological responses on cognitive performance, highlighting significant gender differences. Girls demonstrated higher subjective anxiety and physiological arousal during maths tasks. However, in the same group, lower emotional reactivity and maths anxiety served as protective influences, leading to improved scores and shorter completion times. Moreover, girls and tweens demonstrated lower maths self-concept and preference for maths, indicating that stereotype effects are already impacting their interest during primary school. These findings suggest that psychological factors play a crucial role in learning outcomes, particularly in STEM subjects. This integrated research contributes to a deeper understanding of how psychological factors such as self-concept, subjective anxiety but also physiological arousal and subject preferences affect mathematical and spatial performance in primary school children. The findings have practical implications for educators and policymakers, advocating for the development of strategies to enhance self-concept, manage anxiety and support emotional regulation, particularly in girls, fostering a supportive learning environment that mitigates the impact of stereotype threat. Enhanced self-efficacy and reduced anxiety thereby increase the likelihood of their engagement with maths, subsequently improving their performance and expanding their future career options
in STEM fields.
Population genetics investigates genetic diversity and its changes within and between populations over space and time. Genetic diversity is important for fitness, adaptive capacity, and the survival of populations and is influenced by several factors, such as mutation, selection, genetic drift and gene flow. Copper butterflies (Lycaena) are suitable for analysing structures influencing population connectivity as they potentially form more or less closed populations. However, very little is known about their genetic diversity and what influences it. Therefore, this thesis (1) provides newly developed microsatellite markers and uses genetic markers (2) to investigate genetic diversity across four different Lycaena species in the European Alps and to determine (3) which geographic and species specific factors influence population structure, (4) which large- and small-scale structures impact the population structure, (5) how natural and anthropogenic structures influence the population structure within an Alpine valley, and (6) whether and how genetic diversity changes over time. It was shown that the postglacial relict species L. helle has a relatively high genetic diversity compared to the other three species investigated. This suggests that L. helle is still able to adapt to environmental changes. Low genetic diversity was found in L. tityrus subalpinus, although high gene flow was found within one population of this species. High mountain ridges and large river valleys can act as dispersal barriers for Copper butterflies and thus have an impact on population structures. Here, dispersal ability as a species-specific factor also plays an important role, as some barriers are less likely to affect the population structure in the more mobile species L. virgaureae. Furthermore, forests, ravines and roads, but not small rivers, represent dispersal barriers for L. tityrus subalpinus within an Alpine valley. Finally, over ten years, the genetic diversity of L. hippothoe eurydame has decreased, whereas that of L. helle has remained stable. Against the backdrop of increasing global changes, it is important to understand the genomic underpinning of population structure and adaptation as well as to investigate and monitor whether populations are able to adapt to changing environmental conditions.
The digital transformation of the public sector and the development of suitable implementation mechanisms are currently major challenges in the area of E-Government. While Germany is one of the leading countries in the private sector in terms of digital offerings, the digital transformation processes in the public sector are progressing only slowly. In particular, compared to other European countries, German administrations offer few digital and interoperable services, which prevents them from catching up with a government-wide dig-ital transformation.
The aim of this dissertation is to investigate the reasons for the slow progress of digital transformation in the public sector and to understand why Germany is not making significant progress in the digitization of administrative services compared to other European member states. Furthermore, it aims to gradually build a comprehensive understanding of why digital transformation is not being driven, supported or applied in the public sector and what positive or negative factors ultimately prevent cross-organizational exchange.
The focus of this dissertation is on organizational and interdisciplinary collaboration in socio-technical systems and its influence on the digital transformation of public administrations. The investigation of science and practice is based on the principles of qualitative social research and qualitative content analysis according to Mayring. Deductive categories are systematically derived and supplemented by further inductive categories along the empirical investigation in the five case studies.
The identified phenomena are analyzed in a scientific explanatory model and described with the help of the holistic approach and the actor-network theory. On this basis, solutions are developed that can either prevent or at least reduce the influencing factors. An interdiscipli-nary approach that combines theoretical foundations from business informatics, administrative informatics/e-government and organizational science not only creates a comprehensive understanding of the problem, but also develops approaches for the scientific description of informatics phenomena with the help of social constructivist approaches.
During the development phase of plastic components, simulations are being used to an increasing extent. Against the background of product requirements and the inevitable necessity of conserving resources, the expanded use of simulation tools is an essential part of the solution. Among available methods, but so far underutilized with respect to real-life processes, is the molecular dynamics simulation. By the use of this method it is possible to visualize the physical processes occurring on the microscopic level, as e.g. those that arise during plastics processing. This thesis examines how boundary conditions, which mimic the extrusion blow molding process, affect the behavior of polyethylene on the microscopic level. A mesoscopic model (coarse-graining) is applied to describe the polymer. Initially, this model is verified by determining material properties. The uniaxial tensile test is modeled on the micro-scale to identify parameters such as the elastic modulus, yield stress, and Poisson’s ratio. Additionally, thermal properties, particularly those characterizing the crystallization behavior, are identified. The objective of these investigations is the microscopic observation and quantification of effects that occur during dynamic stretching and crystallization processes. The calculated properties show good agreement with the experimental data, especially regarding the thermal parameters. Qualitatively, the stress-strain behavior is reproduced in alignment with experimentally observed results. However, the short time scale of the simulation models leads to micromechanical behavior that is more extreme than what is monitored on a macroscopic level. By extending the simulation models, biaxial stretching processes are simulated. These stretching processes resemble the situation during the inflation of the parison in the extrusion blow molding process. The examination of various cooling conditions, particularly by the use of mold constraints, is another focus of the investigations. The analysis of the biaxially stretched simulations reveals that disentanglement processes during stretching dominate the further development of polymer systems. It is possible to quantify the dynamics of crystallization processes depending on the degree of stretching and cooling conditions through various parameters (distribution of entanglement points, local orientations). The results indicate that coarse-grained molecular dynamics simulations are able to significantly enhance the micromechanical understanding of local events occurring during plastic processing.
The literature contains very few publications on the application of Process Mining methods for the analysis of event logs in Enterprise Collaboration Systems (ECS). This is not surprising because the analysis of digital support for collaborative work is extremely intricate due to various challenges relating to a lack of data access, poor data quality, unstructured processes and a lack of descriptive models. This article reports on the findings from an Action Design Research (ADR) project. The ADR team had access to a large instance of an operational ECS with more than 3000 users. The event log contains several million entries. Together with the platform’s operating team, intensive research was carried out over a period of six years on ways of analysing user activities on the platform. Several cycles were run to develop new methods and computational techniques to decipher the event logs and meaningfully describe the processes recorded in them. Thanks to the close collaboration between the researchers and the operators of the collaboration platform, it was possible to compare the real-world processes carried out in the platform with the processes discovered using a novel method for Social Process Mining (SPM). The result is a pattern analysis that discovers patterns in processes that have a high degree of correspondence with the real-world scenes of collaborative work. The research work has now reached a point where other software products are included (multi-system analysis) and a catalogue of collaborative work situations (scenes) has been developed to describe the process patterns that result from the Process Mining and graph-based analysis techniques.
Cross Cultural Adaptation of Design Thinking in Entrepreneurship Higher Education in Indonesia
(2024)
Entrepreneurship and entrepreneurship education have expanded together, and their conceptual and methodological challenges do not prevent the implementation of entrepreneurial education in educational contexts. The desire for a global workforce that can handle uncertainties and solve problems that cannot be solved by pure analytical inquiry drives the rapidly expanding number of educational programs and activities that are design-based. A growing number of educational programs for entrepreneurs increasingly incorporate design-based methods. However, design thinking-based theoretical assumptions may also be lacking. Despite growing academic interest in design thinking and entrepreneurship education, little is known about design thinking in higher entrepreneurship education, especially in Eastern nations. A Western teaching method, entrepreneurial design thinking may be adapted to many cultures. In this instance, the West has established entrepreneurship education as a respectable study subject and teaching practice in higher education over the past 40 years. The Eastern nations' occurrence varies, including Indonesia. Indonesia is an intriguing research subject since it has over 50% youth due to its abundant natural resources. However, it needs more opportunity-based entrepreneurs and requires assistance in implementing entrepreneurship education with a more innovative, design-based, and successful method. Entrepreneurial design thinking fulfills this demand. Indonesian students and teachers' norm-based attitudes and cultural mindsets towards a new western creative method may hinder entrepreneurial design thinking's acceptance. The literature review found that Indonesian university students are collaborative, compassionate, and practical, like design thinkers. However, they may also be risk-averse, self-restrained, and dependent on teachers as stereotypical Asians. Classroom space, educators' design thinking competence, and university or institution support are further barriers. Additional study into these challenges is needed to adapt design thinking to Indonesian entrepreneurial higher education culturally.
Based on the above research needs, the purpose of this research endeavor is to look into the cultural nuances of the design thinking technique for entrepreneurial higher education and postulate how it could be adapted to other cultures, especially in Indonesia. This thesis uses deductive and qualitative case-study research methods. In particular, the latter used thematic analysis (Braun & Clarke, 2006; Terry & Hayfield, 2021) as the data analysis technique to provide a means and tools for understanding from interviews, class observation, and literature studies. Since this thesis follows the constructivist-relativist research paradigm, it explores contextual and cultural differences in Indonesian entrepreneurship education and its potential and obstacles to adapt the Western teaching methodology of entrepreneurial design thinking in higher education. In summary, this study searches for elements that might aid or hinder the cross-cultural adaption of entrepreneurial design thinking. This research wants to understand how cross-cultural adaptability fits into entrepreneurial design thinking research, especially for Indonesia. This thesis aims to provide new theoretical insights and practical advice on adapting entrepreneurial design thinking from Western to Eastern cultures.
From the findings, this thesis concluded at least seven educational value differentials before adaptation from the exhaustive literature and case study evaluations. For Indonesian entrepreneurship higher education institutions to use entrepreneurial design thinking, they must consider educational culture, technological infrastructure, language, primary audience, learning and teaching style, reasoning patterns, and social-cultural environment. This study provides four practical adaptation recommendations: socialization, externalization, combination, and internalization. Finally, this research demonstrated that cross-cultural adaption of entrepreneurial design thinking in Indonesia might be difficult but worthwhile. This thesis' case study, "School of Business Management – Bandung Institute of Technology (SBM ITB)", showed that Indonesian entrepreneurial higher education might use design thinking as a teaching approach. All stakeholders must improve internally and publicly. Thus, this study recommended integrating most Indonesian higher education institutions' entrepreneurship teaching approaches with a "student-centered" approach that stresses business mentorship, uses design thinking tools and processes, and links them to students' entrepreneurial initiatives.
To summarize, this research contributes to the field since it draws on and combines the findings of several other fields of study, including entrepreneurial education, design thinking, and cross-cultural adaptation. This study stepped out of the "usual and proper" pedagogical ruts to investigate "non-human" cross-cultural adaptability. It has attempted to apply these ideas to a real-world, unique case study in a developing nation (in this case, Indonesia).
This thesis deals with the conception and implementation of a prototype emulator software that can be used to play a broad range of Game Boy games on a conventional desktop computer. The development of such an application is a technically demanding task defined by various challenges such as the correct interpretation of machine instructions, graphics emulation, as well as playability and correctness. As there is no accessible official documentation of Game Boy hardware, the emulator was developed based on the knowledge amassed by Game Boy reverse engineers. Nevertheless, an emulator was developed that can already run a large selection of games. The correctness of the implemented components was verified using dedicated test programs.
Enterprise Collaboration Systems (ECS) sind essentielle Werkzeuge für die Unterstützung der digitalen Zusammenarbeit und ad hoc Projektarbeit in Unternehmen. Mit der zunehmenden Nutzung von ECS steigen auch die Bedeutung und der Bedarf an Analysen zur Schaffung eines verbesserten Verständnisses von digitaler Arbeit. Da Kollaboration sich regelmäßig über mehr als ein System erstreckt, stellt die Heterogenität der Daten verschiedener Systeme für Analysen eine Herausforderung dar, insbesondere weil plattformübergreifende Nutzungsmuster nicht ohne Weiteres nachverfolgbar und vergleichbar sind. Daher wurde die „Collaborative Actions on Documents Ontology“ (ColActDOnt) entwickelt, um Konzepte aus ECS (z. B. Events und Dokumente) einheitlich zu beschreiben. Basierend auf der ColActDOnt wurde ein Datastore implementiert, in welchem die Daten verschiedener Systeme in der Struktur der Ontologie gespeichert werden. Durch den ontologiebasierten Datastore stehen die Daten für Analysen in einheitlicher Form zur Verfügung. In die Datenebene wurden Daten aus dem ECS HCL Connections (CNX), welches somit das initiale Quellsystem darstellt, importiert. Mittels der ColActDOnt wurde außerdem eine abstrakte Ontologieebene mit den Elementen der Ontologie geschaffen. Die Elemente beider Ebenen sind über Beziehungen innerhalb einer Graphdatenbank miteinander und untereinander verknüpft.
Der ontologiebasierte Datenzugriff ermöglicht es dem Benutzer ohne Kenntnisse über die Datenstrukturen des Quellsystems, lediglich mit Domänenwissen über die ColActDOnt, Inhalte abzufragen.
Der Datastore ist als Graphdatenbank (Neo4j) implementiert und somit können Abfragen nativ als Graphenstrukturen visualisiert werden. Weiterhin kann der Prototyp an Business Intelligence Tools wie Microsoft PowerBI angebunden werden und bietet somit die Möglichkeit für tiefergehende Analysen. Die erste Version des Datastores stellt einen wichtigen Schritt in Richtung der Harmonisierung von Trace Data aus ECS dar. In Zukunft sollen weitere Kollaborationssysteme an den Datastore angeschlossen werden, um systemübergreifende Analysen von komplexen Kollaborationsplattformen zu ermöglichen.
The political targets for CO2 reduction in industrial processes are leading to a technological change in the area of pig iron production. In future, pig iron will be produced by using the direct reduction process instead of the blast furnace process. Direct reduction plants are currently operated with natural gas, this is to be replaced by hydrogen in the future in order to meet the climate targets. Within this work, the influence of hydrogen-containing atmospheres on currently used refractory materials from the Al2O3-SiO2 system was investigated. An experiment was developed to simulate the corrosion of refractory materials in the laboratory under realistic test conditions. Taking into account the atmosphere, the temperature and the sample material, a variety of practical corrosion tests were carried out. By applying a comprehensive analysis strategy, relevant corrosion effects on the materials were subsequently described as a result of the gas composition. The test temperature was in the range of 716 °C < T < 1150 °C. Physical and chemical-mineralogical tests were used to investigate the corrosion effects. In addition, the intensity of the corrosion effects was evaluated based on the gas compositions used. Pure hydrogen atmospheres in particular led to strong gas corrosion, while the presence of water vapor inhibited the chemical reactions. The mixture of methane and hydrogen can create an aggressive H2 / CO atmosphere, which also can lead to the formation of solid carbon. This phenomenon changes the possible causes of damage to refractory material; the crystallization pressure of carbon inside the structure of the refractory can also contribute to material failure. Furthermore, the corrosion reactions could be described by coupling imaging analysis methods and element determination. It was shown that, in contrast to the general opinion in the state of the art, there was not exclusively a decrease in SiO2-amount. Several reactions took place in the investigated, industrially used materials, which led to the local chemical attack of SiO2 (silicate glass phase) and caused a parallel crystallization of cristobalite. The chemical attack of hydrogen on the silicate glass phase can be defined as the primary corrosion reaction in the range of 716 °C < T < 1150 °C in a pure hydrogen atmosphere. In addition, the reaction kinetics as a function of temperature were experimentally investigated and described. Based on these analyses, material properties can be defined that are particularly suitable for the future use of defined refractory qualities within reduction processes.
Zweiunddreißigste Ordnung zur Änderung der Prüfungsordnung für die Prüfung im lehramtsbezogenen Bachelorstudiengang an der Universität Koblenz
Achtundzwanzigste Ordnung zur Änderung der Prüfungsordnung für die Prüfung in den Masterstudiengängen für das Lehramt an Grundschulen, das Lehramt an Realschulen plus sowie das Lehramt an Gymnasien an der Universität Koblenz
Neunundzwanzigste Ordnung zur Änderung der Ordnung für die Prüfung im lehramtsbezogenen Zertifikatsstudiengang (Erweiterungsprüfung) an der Universität Koblenz und der Hochschule Koblenz
Vierte Ordnung zur Änderung der Gemeinsamen Prüfungsordnung für die Bachelor- und Masterstudiengänge des Fachbereichs Informatik an der Universität Koblenz
Gemeinsame Prüfungsordnung für den Masterstudiengang Master of Engineering „Ceramic Science and Engineering“ an der Hochschule Koblenz und der Universität Koblenz (Kooperativer Masterstudiengang)
Wahlordnung der Studierendenschaft der Universität Koblenz
Satzung zur Festsetzung von Zulassungszahlen an der Universität Koblenz für das Studienjahr 2024/2025
Satzung zur Festsetzung der Normwerte für den Ausbildungsaufwand (Curricularnormwerte) der Universität Koblenz
Zweite Ordnung zur Änderung Ordnung für die Prüfung im Masterstudiengang Applied Physics an der Hochschule Koblenz und der Universität Koblenz (Kooperativer Masterstudiengang)
The findings of this study demonstrate that the Random Forest (RF) algorithm provided the most accurate predictions in comparison with other boosting machine learning algorithms. Key drivers of energy consumption identified through XAI techniques such as SHAP and LIME include energy star rating, facility type, and floor area. These XAI methods helped enhance the interpretability of the models, making them more accessible for non-expert users, such as building managers and policymakers. By leveraging machine learning and XAI, this research provides a transparent and actionable framework for optimizing building energy efficiency and supporting sustainable energy management.
In the realm of education, the timely identification of students who need further support to succeed in their respective courses, plays a pivotal role in fostering aca- demic success and preventing potential setbacks. This thesis thus aims to contribute to this critical area by focusing on the development of predictive models for the early detection of at-risk students in their academic journey. The primary dataset used for this thesis is provided by kaggle, encompassing diverse student informa- tion, including demographic, socio-economic factors, and academic performance categorized into three different classes, presenting an imbalanced nature that poses a significant challenge.
Thus the primary objectives of this thesis are to address the problem of imbal- anced data, explore and assess the performance of multiple classification methods such as, logistic regression, decision tress, random forests and support vector ma- chines (SVM), neural networks, and create a comprehensive end-to-end processing pipeline which includes the systematic steps of balancing the data, model training and evaluation. Additionally the developed pipeline is tested on two additional datasets to assess its generalizability and robustness. This research aims to provide a comprehensive understanding of addressing the challenges of imbalanced data and how different classification methods and regression can be optimally applied to early detection of at-risk students. The findings are expected to aid educational institutions in supporting their students and enhancing academic success through timely interventions.
Key findings demonstrates the robustness of SVM SMOTE balancing technique acro- ss the datasets used in this study, where it consistently achieved best results when combined with various models, particularly highlighting the success of the combi- nation of Random Forest model with SVM SMOTE, and Decision tree model with SVM SMOTE in achieving notable accuracy rates. This emphasizes the adaptability of the balancing techniques employed, providing a strong foundation for predictive intervention educational settings.
Die vorliegende Dissertation hat sich unter dem Titel >>„Woher soll ich denn vorher wissen, ob ich den Job liebe?“ – Eine qualitative Längsschnitt-Studie zur Differenzierung der Phasenstruktur vorliegender Modelle beruflicher Orientierung anhand von Jugendlichen aus drei kontrastierenden institutionellen Ausgangslagen<< dem Erkenntnisinteresse gewidmet, Modelle zur beruflichen Orientierung anhand eines ethnografischen Zugangs aus der Perspektive unterschiedlicher institutioneller Settngs weiterzuentwickeln, um der Komplexität gegenwärtiger Lebenswelten besser gerecht zu werden. Dabei wurde unter Betrachtung von Berufsorientierungsaspekten als Forschungsgegenstand sowie unter Betrachtung der Gestalt der Berufsorientierung als Forschungsfeld der Fragestellung nachgegangen, inwiefern sich das in der Debatte zentrale Sechs-Phasenmodell der Berufswahl nach Herzog et. al. (2006) im Licht ethnografischer Forschung, welche die Perspektiven Jugendlicher eines allgemeinbildenden Gymnasiums, eines beruflichen Gymnasiums sowie eines Freiwilligen Sozialen Jahres umfasst, ausdifferenzieren lässt. Dabei wurde die Grounded Theory-Methodologie als Forschungsstil zugrunde gelegt, der wiederum im Rahmen der Datenerhebung die Ethnografie, im Rahmen der Datenanalyse die Grounded Theory untergeordnet wurde.
Als zentrales Untersuchungsergebnis lässt sich zum einen aufführen, dass das bestehende Berufswahlmodell deutlich modifiziert, ausdifferenziert und folglich erweitert werden konnte. Mit dieser Erweiterung ist eine Spezifikation dahingehend verbunden, dass viele Komponenten und Ebenen hinzugekommen sind, die bei dem ursprünglichen Modell nicht bedacht waren, im Gegenzug jedoch auch solche Komponenten gestrichen und als irrelevant deklariert wurden, die sich anhand der Untersuchungsdaten nicht zu bestätigen wussten. So konnte ein Neun-Phasenmodell der Berufsorientierung in Gestalt eines Ablaufdiagramms
entstehen, das den Prozessverlauf beruflicher Orientierung anschaulich in Phasen eingebettet darzustellen vermag. Dabei ist es gelungen, das Modell derart auszugestalten, dass es institutionsübergreifend anwendbar und nicht lediglich auf eine bestimmte institutionelle Ausgangslage beschränkt ist. Zum anderen kann statuiert werden, dass das vorliegende neunphasige Modell vor allem Phasen der Orientierungslosigkeit und der Desorientierung, des Entscheidungsaufschubs, der Überprüfung und der Überbrückung sowie der Um- und Neuorientierung explizit zu nutzen weiß, um diejenigen Situationen zu berücksichtigen, die den beruflichen Orientierungsprozess der Untersuchungsteilnehmenden aus allen drei
institutionellen Ausgangslagen maßgeblich geprägt haben.
Assessing ChatGPT’s Performance in Analyzing Students’ Sentiments: A Case Study in Course Feedback
(2024)
The emergence of large language models (LLMs) like ChatGPT has impacted fields such as education, transforming natural language processing (NLP) tasks like sentiment analysis. Transformers form the foundation of LLMs, with BERT, XLNet, and GPT as key examples. ChatGPT, developed by OpenAI, is a state-of-the-art model and its ability in natural language tasks makes it a potential tool in sentiment analysis. This thesis reviews current sentiment analysis methods and examines ChatGPT’s ability to analyze sentiments across three labels (Negative, Neutral, Positive) and five labels (Very Negative, Negative, Neutral, Positive, Very Positive) on a dataset of student course reviews. Its performance is compared with fine tuned state-of-the-art models like BERT, XLNet, bart-large-mnli, and RoBERTa-large-mnli using quantitative metrics. With the help of 7 prompting techniques which are ways to instruct ChatGPT, this work also analyzed how well it understands complex linguistic nuances in the given texts using qualitative metrics. BERT and XLNet outperform ChatGPT mainly due to their bidirectional nature, which allows them to understand the full context of a sentence, not just left to right. This, combined with fine-tuning, helps them capture patterns and nuances better. ChatGPT, as a general purpose, open-domain model, processes text unidirectionally, which can limit its context understanding. Despite this, ChatGPT performed comparably to XLNet and BERT in three-label scenarios and outperformed others. Fine-tuned models excelled in five label cases. Moreover, it has shown impressive knowledge of the language. Chain-of-Thought (CoT) was the most effective technique for prompting with step by step instructions. ChatGPT showed promising performance in correctness, consistency, relevance, and robustness, except for detecting Irony. As education evolves with diverse learning environments, effective feedback analysis becomes increasingly valuable. Addressing ChatGPT’s limitations and leveraging its strengths could enhance personalized learning through better sentiment analysis.
Exploring Academic Perspectives: Sentiments and Discourse on ChatGPT Adoption in Higher Education
(2024)
Artificial intelligence (AI) is becoming more widely used in a number of industries, including in the field of education. Applications of artificial intelligence (AI) are becoming crucial for schools and universities, whether for automated evaluation, smart educational systems, individualized learning, or staff support. ChatGPT, anAI-based chatbot, offers coherent and helpful replies based on analyzing large volumes of data. Integrating ChatGPT, a sophisticated Natural Language Processing (NLP) tool developed by OpenAI, into higher education has sparked significant interest and debate. Since the technology is already adapted by many students and teachers, this study delves into analyzing the sentiments expressed on university websites regarding ChatGPT integration into education by creating a comprehensive sentiment analysis framework using Hierarchical Residual RSigELU Attention Network (HR-RAN). The proposed framework addresses several challenges in sentiment analysis, such as capturing fine-grained sentiment nuances, including contextual information, and handling complex language expressions in university review data. The methodology involves several steps, including data collection from various educational websites, blogs, and news platforms. The data is preprocessed to handle emoticons, URLs, and tags and then, detect and remove sarcastic text using the eXtreme Learning Hyperband Network (XLHN). Sentences are then grouped based on similarity and topics are modeled using the Non-negative Term-Document Matrix Factorization (NTDMF) approach. Features, such as lexico-semantic, lexico structural, and numerical features are extracted. Dependency parsing and coreference resolution are performed to analyze grammatical structures and understand semantic relationships. Word embedding uses the Word2Vec model to capture semantic relationships between words. The preprocessed text and extracted features are inputted into the HR-RAN classifier to categorize sentiments as positive, negative, or neutral. The sentiment analysis results indicate that 74.8% of the sentiments towards ChatGPT in higher education are neutral, 21.5% are positive, and only 3.7% are negative. This suggests a predominant neutrality among users, with a significant portion expressing positive views and a very small percentage holding negative opinions. Additionally, the analysis reveals regional variations, with Canada showing the highest number of sentiments, predominantly neutral, followed by Germany, the UK, and the USA. The sentiment analysis results are evaluated based on various metrics, such as accuracy, precision, recall, F-measure, and specificity. Results indicate that the proposed framework outperforms conventional sentiment analysis models. The HR-RAN technique achieved a precision of 98.98%, recall of 99.23%, F-measure of 99.10%, accuracy of 98.88%, and specificity of 98.31%. Additionally, word clouds are generated to visually represent the most common terms within positive, neutral, and negative sentiments, providing a clear and immediate understanding of the key themes in the data. These findings can inform educators, administrators, and developers about the benefits and challenges of integrating ChatGPT into educational
settings, guiding improvements in educational practices and AI tool development.
Die Untersuchung der Erwartungen und Anforderungen der Generation Z an Führungskräfte ist sowohl praktisch als auch wissenschaftlich von hoher Relevanz. Praktisch gesehen erfordert der Fachkräftemangel in Deutschland und die veränderten Vorstellungen der Generation Z ein Umdenken bei Führungskräften. Wissenschaftlich besteht eine Forschungslücke, da traditionelle Führungstheorien oft nicht mehr zeitgemäß sind und spezifische Studien zu den Präferenzen der Generation Z fehlen.
Ziel der Masterthesis ist es, diese Lücke durch qualitative Experteninterviews zu schließen und neue Erkenntnisse über die Ansichten der Generation Z zu gewinnen. Dabei sollen Unternehmen unterstützt werden, junge Fachkräfte langfristig zu gewinnen.
Die Methode umfasst eine qualitative Studie mit 14 Interviewpartnern, darunter Mitarbeiter der Generation Z und Führungskräfte. Die semistrukturierten Interviews wurden transkribiert und mithilfe der qualitativen Inhaltsanalyse nach Mayring und der Software MAXQDA ausgewertet. Induktiv wurden Kategorien aus dem Material gebildet.
Die Ergebnisse zeigen, dass die Generation Z authentische, empathische Führung und klare Perspektiven erwartet. Hauptkategorien wie Organisation, soziale Kompetenz, Teamfähigkeit und zukunftsfähige Wege wurden identifiziert. Beide Gruppen betonen die Bedeutung von Befähigung, regelmäßiger Kommunikation, Fairness und Transparenz.
Praktisch implizieren die Ergebnisse, dass Unternehmen praktische Maßnahmen und Weiterentwicklungen vornehmen müssen, um den Bedürfnissen der jungen Generation gerecht zu werden. Für die Forschung bietet die Studie eine Basis für weiterführende quantitative Untersuchungen und ein konzeptionelles Framework zur Darstellung der wichtigsten Kategorien und ihrer Zusammenhänge.
Recent studies show that biofilm substances in contact with nanoplastics play an important role in the aggregation and sedimentation of nanoplastics. Consequences of these processes are changes in biofilm formation and stability and changes in the transport and fate of pollutants in the environment. Having a deeper understanding of the nanoplastics–biofilm interaction would help to evaluate the risks posed by uncontrolled nanoplastic pollution. These interactions are impacted by environmental changes due to climate change, such as, e.g., the acidification of surface waters. We apply fluorescence correlation spectroscopy (FCS) to investigate the pH-dependent aggregation tendency of non-functionalized polystyrene (PS) nanoparticles (NPs) due to intermolecular forces with model extracellular biofilm substances. Our biofilm model consists of bovine serum albumin (BSA), which serves as a representative for globular proteins, and the polysaccharide alginate, which is a main component in many biofilms, in solutions containing Na+ with an ionic strength being realistic for fresh-water conditions. Biomolecule concentrations ranging from 0.5 g/L up to at maximum 21 g/L are considered. We use non-functionalized PS NPs as representative for mostly negatively charged nanoplastics. BSA promotes NP aggregation through adsorption onto the NPs and BSA-mediated bridging. In BSA–alginate mixtures, the alginate hampers this interaction, most likely due to alginate–BSA complex formation. In most BSA–alginate mixtures as in alginate alone, NP aggregation is predominantly driven by weaker, pH-independent depletion forces. The stabilizing effect of alginate is only weakened at high BSA contents, when the electrostatic BSA–BSA attraction is not sufficiently screened by the alginate. This study clearly shows that it is crucial to consider correlative effects between multiple biofilm components to better understand the NP aggregation in the presence of complex biofilm substances. Single-component biofilm model systems based on comparing the total organic carbon (TOC) content of the extracellular biofilm substances, as usually considered, would have led to a misjudgment of the stability towards aggregation.
The goal of this PhD thesis is to investigate possibilities of using symbol elimination for solving problems over complex theories and analyze the applicability of such uniform approaches in different areas of application, such as verification, knowledge representation and graph theory. In the thesis we propose an approach to symbol elimination in complex theories that follows the general idea of combining hierarchical reasoning with symbol elimination in standard theories. We analyze how this general approach can be specialized and used in different areas of application.
In the verification of parametric systems it is important to prove that certain safety properties hold. This can be done by showing that a property is an inductive invariant of the system, i.e. it holds in the initial state of the system and is invariant under updates of the system. Sometimes this is not the case for the condition itself, but for a stronger condition it is. In this thesis we propose a method for goal-directed invariant strengthening.
In knowledge representation we often have to deal with huge ontologies. Combining two ontologies usually leads to new consequences, some of which may be false or undesired. We are interested in finding explanations for such unwanted consequences. For this we propose a method for computing interpolants in the description logics EL and EL⁺, based on a translation to the theory of semilattices with monotone operators and a certain form of interpolation in this theory.
In wireless network theory one often deals with classes of geometric graphs in which the existence or non-existence of an edge between two vertices in a graph relies on properties on their distances to other nodes. One possibility to prove properties of those graphs or to analyze relations between the graph classes is to prove or disprove that one graph class is contained in the other. In this thesis we propose a method for checking inclusions between geometric graph classes.
In international business relationships, such as international railway operations, large amounts of data can be exchanged among the parties involved. For the exchange of such data, a limited risk of being cheated by another party, e.g., by being provided with fake data, as well as reasonable cost and a foreseeable benefit, is expected. As the exchanged data can be used to make critical business decisions, there is a high incentive for one party to manipulate the data in its favor. To prevent this type of manipulation, mechanisms exist to ensure the integrity and authenticity of the data. In combination with a fair exchange protocol, it can be ensured that the integrity and authenticity of this data is maintained even when it is exchanged with another party. At the same time, such a protocol ensures that the exchange of data only takes place in conjunction with the agreed compensation, such as a payment, and that the payment is only made if the integrity and authenticity of the data is ensured as previously agreed. However, in order to be able to guarantee fairness, a fair exchange protocol must involve a trusted third party. To avoid fraud by a single centralized party acting as a trusted third party, current research proposes decentralizing the trusted third party, e.g., by using a distributed ledger based fair exchange protocol. However, for assessing the fairness of such an exchange, state-of-the-art approaches neglect costs arising for the parties conducting the fair exchange. This can result in a violation of the outlined expectation of reasonable cost, especially when distributed ledgers are involved, which are typically associated with non-negligible costs. Furthermore, the performance of typical distributed ledger-based fair exchange protocols is limited, posing an obstacle to widespread adoption.
To overcome the challenges, in this thesis, we introduce the foundation for a data exchange platform allowing for a fully decentralized fair data exchange with reasonable cost and performance. As a theoretical foundation, we introduce the concept of cost fairness, which considers cost for the fairness assessment by requesting that a party following the fair exchange protocol never suffers any unilateral disadvantages. We prove that cost fairness cannot be achieved using typical public distributed ledgers but requires customized distributed ledger instances, which usually lack complete decentralization. However, we show that the highest unilateral cost are caused by a grieving attack.
To allow fair data exchanges to be conducted with reasonable cost and performance, we introduce FairSCE, a distributed ledger-based fair exchange protocol using distributed ledger state channels and incorporating a mechanism to protect against grieving attacks, reducing the possible unilateral cost that have to be covered to a minimum. Based on our evaluation of FairSCE, the worst-case cost for data exchange, even in the presence of malicious parties, is known, which allows an estimate of the possible benefit and, thus, the preliminary estimate of economic utility. Furthermore, to allow for an unambiguous assessment of the correct data being transferred while still allowing for sensitive parts of the data to be masked, we introduce an approach for the hashing of hierarchically structured data, which can be used to ensure integrity and authenticity of the data being transferred.
Well-being is essential for all people. Therefore, important factors influencing people’s well-being must be investigated. Well-being is multifaceted and defined as, for example, psychological, emotional, mental, physical, or social well-being. Here, we focus on psychological well-being. The study aimed to analyze different aspects of connectedness as potential predictors of psychological well-being. For this purpose, we conducted a study examining the psychological well-being of 184 participants (130 women, 54 men, age: M = 31.39, SD = 15.24) as well as their connectedness with oneself (self-love), with others (prosocialness), with nature (nature connectedness), and with the transcendent (spirituality). First, significant positive correlations appeared between psychological well-being and self-love, nature connectedness, and spirituality. Furthermore, correlations between the four aspects of connectedness were significant, except for the relationship between self-love and prosocialness. A regression analysis revealed that self-love and nature connectedness positively predicted participants’ psychological well-being, while spirituality and prosocialness did not explain any incremental variance. The strong relationship between self-love and well-being was partly mediated by nature connectedness. Hence, self love, understood as a positive attitude of self-kindness, should be considered in more detail to enhance psychological well-being. Besides this, a more vital connectedness to the surrounding nature could benefit people’s well-being.
Examining the role of post-event processing in test anxiety—Pilot testing in three student samples
(2024)
This work investigates the occurrence of post-event processing (PEP) in the context of test anxiety; PEP involves rumination and self-critical thinking following an event and commonly observed in social anxiety. Three short-term longitudinal studies in student samples examined whether PEP occurs after exams and how it is associated with test anxiety. University students (N =35 in Study 1, N =146 in Study 2, and N =37 in Study 3) completed measures of trait and state test anxiety before an actual exam; PEP related to the exam was assessed at various time points afterward. Results revealed that PEP occurred to a meaningful extent after exam situations. Overall, it was positively associated with trait and state test anxiety, although some variations in the relations were found across the three studies. These findings underscore the relevance of PEP in the context of test anxiety, as PEP might contribute to maintaining test anxiety in the long term. Implications for future studies are discussed.
Degenerative changes in the spine as well as back pain can be considered a common ailment. Incorrect loading of the lumbar spine structures is often considered as one of the factors that can accelerate degenerative processes, leading to back pain. For example, a degenerative change could be the occurrence of spinal stenosis following spondylolisthesis. Surgical treatment of spinal stenosis mainly focuses on decompressing the spinal canal with or without additional fusion through dorsal spondylodesis. There are differing opinions on whether fusion along with decompression provides potential benefits to patients or represents an overtreatment. Both conventional therapies and surgical methods aim to restore a “healthy” (or at least pain-free) distribution of load. Surprisingly little is known about the interindividual variability of load distribution in “healthy” lumbar spines. Since medical imaging does not provide information on internal forces, computer simulation of individual patients could be a tool to gain a set of new decision criteria for these cases. The advantage lies in calculating the internal load distribution, which is not feasible in in-vivo studies, as measurements of internal forces in living subjects are ethically and partially technically unfeasible. In the present research, the forward dynamic approach is used to calculate load distribution in multi-body models of individual lumbar spines. The work is structured into three parts: (I) Load distribution is quantified depending on the individual curvature of the lumbar spine. (II) Confidence intervals of the instantaneous center of rotation over time are determined, with which the motion behavior of healthy lumbar spines can be described. (III) Lastly, the effects of decompression surgeries on the load distribution of lumbar spines are determined.
The biodegradable polymers polylactic acid (PLA) and polyhydroxybutyrate (PHB) produced from renewable raw materials were coated with hydrogenated amorphous carbon layers (a-C:H) at different deposition angles with various thicknesses as part of this thesis. Similar to conventional polymers, biopolymers often have unsuitable surface properties for industrial purposes, e.g. low hardness. For some applications, it is therefore necessary and advantageous to modify the surface properties of biopolymers while retaining the main properties of the substrate material. A suitable surface modification is the deposition of thin a-C:H layers. Their properties depend essentially on the sp² and sp³ hybridization ratio of the carbon atoms and the content of hydrogen atoms. The sp²/sp³ ratio was to be controlled in the present work by varying the coating geometry. Since coatings at 0°, directly in front of the plasma source, contain a higher percentage of sp³ and indirectly coated (180°) a higher amount of sp², it is shown in this work that it is possible to control the sp²/sp³ ratio. For this purpose, the samples are placed in front of the plasma source at angles of 0, 30, 60, 90, 120, 150 and 180° and coated for 2.5, 5.0, 7.5 and 10.0 minutes. For the angles 0°, the layer thicknesses were 25, 50, 75 and 100 nm. The a-C:H layers were all deposited using radio-frequency plasma-enhanced chemical vapor deposition and acetylene as C and H sources after being pretreated with an oxygen plasma for 10 minutes. Following the O₂ treatment and the a-C:H deposition, the surfaces are examined using macroscopic and microscopic measurement methods and the data is then analyzed. The surface morphology is recorded using scanning electron microscopy and atomic force microscopy. In addition, data on the stability of the layer and the surface roughness can be collected. Contact angle (CA) measurements are used to determine not only the wettability, but also the contact angle hysteresis by pumping the drop volume up and down. By measuring the CA with different liquids and comparing them, the surface free energy (SFE) and its polar and disperse components are determined. The changes in barrier properties are verified by water vapor transmission rate tests (WVTR). The chemical analysis of the surface is carried out on the one hand by Fourier transform infrared spectroscopy with specular reflection and on the other hand by synchrotron-supported techniques such as near-edge X-ray absorption fine structure and X-ray photoelectron spectroscopy. When analyzing the surfaces after the O₂ treatment, which was initially assumed to serve only to clean and activate the surface for the a-C:H coating, it was found that the changes were more drastic than originally assumed. For example, if PLA is treated at 0° for 10 minutes, the roughness increases fivefold. As the angle increases, it decreases again until it returns to the initial value at 180°. This can be recognized to a lesser extent with PHB at 30°. For both polymers, it can be shown that the polar fraction of the SFE increases. In the WVTR, a decrease in permeability can be observed for PLA and an increase in the initial value for PHB. The chemical surface analysis shows that the O₂ treatment has little effect on the surface bonds. Overall, it can be shown in this work that the O₂ treatment has an effect on the properties of the surface and cannot be regarded exclusively as a cleaning and activation process. With direct a-C:H coating (at 0°), a layer failure due to internal stress can be observed for both PLA and PHB. This also occurs with PHB at 30°, but to a lesser extent. Permeability of the polymers is reduced by 47% with a five-minute coating and the layer at 10.0 minutes continues to have this effect despite cracks appearing. The application of a-C:H layers shows a dominance of sp³ bonds for both polymer types with direct coating. This decreases with increasing angle and sp² bonds become dominant for indirect coatings. This result is similar for all coating thicknesses, only the angle at which the change of the dominant bond takes place is different. It is shown that it is possible to control the surface properties by an angle-dependent coating and thus to control the ratio sp²/sp³.
Reducing gender bias in STEM is key to generating more equality and contributing to a more balanced workforce in this field. Spatial ability and its components are cognitive processes crucial to success in STEM education and careers. Significant gender differences have consistently been found in mental rotation (MR), the ability to mentally transform two- and three-dimensional objects. The aim of this pilot study is to examine factors in psychological assessment which may contribute to gender differences in MR performance. Moreover, findings will inform the development of the new approaches to assessment using computer adaptive testing (CAT). (1) Background: The study examines the impact of emotional regulation on MR performance in primary school children whose mean age was 9.28 years old. (2) Methods: Skin conductance was measured to assess the impact of emotional reactivity (ER) on performance during an MR task. (3) Results: Patterns of ER influence response time (RT) on specific items in the task. (4) Conclusions: Identifying the effects of emotional arousal and issues of test construction such as stereotyped stimuli and item difficulty in tests of spatial ability warrants ongoing investigation. It is vital to ensure that these factors do not compromise the accurate measurement of performance and inadvertently contribute to the gender gap in STEM.
The title compound, [Fe(C5H5)(C21H24NO2)], which is produced by the oxidation of 1-(4-tert-butylphenyl)-2-ethyl-3-ferrocenylpyrrole, crystallizes as a racemic mixture in the centrosymmetric space group P21/n. The central heterocyclic pyrrole ring system subtends dihedral angles of 13.7 (2)° with respect to the attached cyclopentadienyl ring and of 43.6 (7)° with the major component of the disordered phenyl group bound to the N atom. The 4-tert-butylphenyl group, as well as the non-substituted Cp ring are disordered with s.o.f. values of 0.589 (16) and 0.411 (16), respectively. In the crystal, molecules with the same absolute configuration are linked into infinite chains along the b-axis direction by O—H···O hydrogen bonds between the hydroxy substituent and the carbonyl O atom of the adjacent molecule.
Herein, the particle size distributions (PSDs) and shape analysis of in vivo bioproduced particles from aqueous Au3+ and Eu3+ solutions by the cyanobacterium Anabaena sp. are examined in detail at the nanoscale. Generally, biosynthesis is affected by numerous parameters. Therefore, it is challenging to find the key set points for generating tailored nanoparticles (NPs). PSDs and shape analysis of the Au and Eu-NPs were performed with ImageJ using high-resolution transmission electron microscopy (HR-TEM) images. As the HR-TEM image analysis reflects only a fraction of the detected NPs within the cells, additional PSDs of the complete cell were performed to determine the NP count and to evaluate the different accuracies. Furthermore, local PSDs were carried out at five randomly selected locations within a single cell to identify local hotspots or agglomerations. The PSDs show that particle size depends mainly on contact time, while the particle shape is hardly affected. The particles formed are distributed quite evenly within the cells. HR-PSDs for Au-NPs show an average equivalent circular diameter (ECD) of 8.4 nm (24 h) and 7.2 nm (51 h). In contrast, Eu-NPs preferably exhibit an average ECD of 10.6 nm (10 h) and 12.3 nm (244 h). Au-NPs are classified predominantly as “very round” with an average reciprocal aspect ratio (RAR) of ~0.9 and a Feret major axis ratio (FMR) of ~1.17. Eu-NPs mainly belong to the “rounded” class with a smaller RAR of ~0.6 and a FMR of ~1.3. These results show that an increase in contact time is not accompanied by an average particle growth for Au-NPs, but by a doubling of the particle number. Anabaena sp. is capable of biosorbing and bioreducing dissolved Au3+ and Eu3+ ions from aqueous solutions, generating nano-sized Au and Eu particles, respectively. Therefore, it is a low-cost, non-toxic and effective candidate for a rapid recovery of these sought-after metals via the bioproduction of NPs with defined sizes and shapes, providing a high potential for scale-up.
How to begin? This short question addresses a problem that is anything but simple, especially when regarding something as sophisticated and multilayered as musical theatre. However, scholars of this vast research area have mostly neglected this question so far. This study analyses and compares the initial sections of late Victorian popular musical theatre and is therefore a contribution to several fields of research: the analysis of initial sections of musical theatre in general, the analysis of the music of popular musical theatre in particular, and therefore operetta studies. The 1890s are especially interesting times for popular musical theatre in London: The premiered works include the last collaborations of Gilbert and Sullivan as well as offshoots of Savoy opera; but the so-called ‘naughty nineties’ also saw the emergence of a new genre, musical comedy, which captured the late Victorian zeitgeist like no other. This new form of theatrical entertainment was carefully and consciously constructed and promoted as modern and fashionable, walking a fine line between respectability and mildly risqué excitement.
Because a deep understanding of the developments and new tendencies concerning popular musical theatre in the 1890s is crucial in order to interpret differences as well as similarities, the analyses of the opening numbers are preceded by a detailed discussion of the relevant genres: comic opera, musical comedy, musical play and operetta. Since the producers of the analysed works wanted to distance themselves from former and supposedly old-fashioned traditions, this book also considers influences from their British predecessors, but also from Viennese operetta and French opéra bouffe.
Coat color and pattern are a distinguished feature in mammalian carnivores, shaped by climatic cycles and habitat type. It can be expressed in various ways, such as gradients, polymorphisms, and rare color variants. Although natural selection explains much of the phenotypic variation found in the wild, genetic drift and heterozygote deficiency, as prominent in small and fragmented populations, may also affect phenotypic variability through the fixation of recessive alleles. The aim of this study was to test whether rare color variants in the wild could relate to a deficiency of heterozygotes, resulting from habitat fragmentation and small population size. We present an overview of all rare color variants in the order Carnivora, and compiled demographic and genetic data of the populations where they did and did not occur, to test for significant correlations. We also tested how phylogeny and body weight influenced the presence of color variants with phylogenetic generalized linear mixed models (PGLMMs). We found 40 color-variable species and 59 rare color variants. In 17 variable phenotypic populations for which genetic diversity was available, the average AR was 4.18, HO = 0.59, and HE= 0.66, and FIS= 0.086. We found that variable populations displayed a significant reduction in heterozygosity and allelic richness compared to non-variable populations across species. We also found a significant negative correlation between population size and inbreeding coefficients. Therefore, it is possible that small effective size had phenotypic consequences on the extant populations. The high frequency of the rare color variants (averaging 20%) also implies that genetic drift is locally overruling natural selection in small effective populations. As such, rare color variants could be added to the list of phenotypic consequences of inbreeding in the wild.
The production of isolated metallic nanoparticles with multifunctionalized properties, such as size and shape, is crucial for biomedical, photocatalytic, and energy storage or remediation applications. This study investigates the initial particle formations of gold nanoparticles (AuNPs) bioproduced in the cyanobacteria Anabaena sp. using high-resolution transmission electron microscopy images for digital image analysis. The developed method enabled the discovery of cerium nanoparticles (CeNPs), which were biosynthesized in the cyanobacteria Calothrix desertica. The particle size distributions for AuNPs and CeNPs were analyzed. After 10 h, the average equivalent circular diameter for AuNPs was 4.8 nm, while for CeNPs, it was approximately 5.2 nm after 25 h. The initial shape of AuNPs was sub-round to round, while the shape of CeNPs was more roundish due to their amorphous structure and formation restricted to heterocysts. The local PSDs indicate that the maturation of AuNPs begins in the middle of vegetative cells and near the cell membrane, compared to the other regions of the cell.
X-ray computed tomography (XRT) is a three-dimensional (3D), non-destructive, and reproducible investigation method capable of visualizing and examining internal and external structures of components independent of the material and geometry. In this work, XRT with its unique abilities complements conventionally utilized examination methods for the investigation of microstructure weakening induced by hydrogen corrosion and furthermore provides a new approach to corrosion research. The motivation for this is the current inevitable transformation to hydrogen-based steel production. Refractories of the system Al2O3-SiO2 are significant as lining materials. Two exemplary material types A and B, which differ mainly in their Al2O3:SiO2 ratio, are examined here using XRT. Identical samples of the two materials are measured, analyzed, and then compared before and after hydrogen attack. In this context, hydrogen corrosion-induced porosity and its spatial distribution and morphology are investigated. The results show that sample B has an higher resistance to hydrogen-induced attack than sample A. Furthermore, the 3D-representation revealed a differential porosity increase within the microstructure.
This thesis explores and examines the effectiveness and efficacy of traditional machine learning (ML), advanced neural networks (NN) and state-of-the-art deep learning (DL) models for identifying mental distress indicators from the social media discourses based on Reddit and Twitter as they are immensely used by teenagers. Different NLP vectorization techniques like TF-IDF, Word2Vec, GloVe, and BERT embeddings are employed with ML models such as Decision Tree (DT), Random Forest (RF), Logistic Regression (LR) and Support Vector Machine (SVM) followed by NN models such as Convolutional Neural Network (CNN), Recurrent Neural Network (RNN) and Long Short-Term Memory (LSTM) to methodically analyse their impact as feature representation of models. DL models such as BERT, DistilBERT, MentalRoBERTa and MentalBERT are end-to-end fine tuned for classification task. This thesis also compares different text preprocessing techniques such as tokenization, stopword removal and lemmatization to assess their impact on model performance. Systematic experiments with different configuration of vectorization and preprocessing techniques in accordance with different model types and categories have been implemented to find the most effective configurations and to gauge the strengths, limitations, and capability to detect and interpret the mental distress indicators from the text. The results analysis reveals that MentalBERT DL model significantly outperformed all other model types and categories due to its specific pretraining on mental data as well as rigorous end-to-end fine tuning gave it an edge for detecting nuanced linguistic mental distress indicators from the complex contextual textual corpus. This insights from the results acknowledges the ML and NLP technologies high potential for developing complex AI systems for its intervention in the domain of mental health analysis. This thesis lays the foundation and directs the future work demonstrating the need for collaborative approach of different domain experts as well as to explore next generational large language models to develop robust and clinically approved mental health AI systems.
Nanoparticles are sensitive and robust systems; they are particularly reactive due to their large surface area and have properties that the bulk material does not have. At the same time, the production of nanoparticles is challenging, because even with the same parameters and conditions, the parameters can vary slightly from run to run. In order to avoid this, this work aims to develop a continuous synthesis in the microjet reactor for nanoceria. The aim is to obtain monodisperse nanoparticles that can be used in biosensors.
This work focuses on two precipitation syntheses with the intermediate steps of cerium carbonate and cerium hydroxide, as well as a microemulsion synthesis for the production of nanoceria. The cerium oxide nanoparticles are compared using different characterisation and application methods. The synthesised nanoparticles will be characterised with respect to their size, stability, chemical composition and catalytic capabilities, by electron microscopy, X-ray diffraction, Raman spectroscopy and photoelectron spectroscopy.
The biosensor systems to evaluate the nanoceria are designed to detect histamine and glucose or hydrogen peroxide, which are resulting from the oxidation of histamine and glucose. Hydrogen peroxide and glucose are detected by an electrochemical sensor and histamine by a colorimetric sensor system.
In dieser wiederkehrenden Zeitschriftenreihe wollen wir die Arbeit junger Wissenschaftlerinnen und Wissenschaftler an der Universität Koblenz kommunizieren und Studierenden Austausch- und Publikationsmöglichkeiten für den wissenschaftlichen Werdegang eröffnen.
In dieser Ausgabe:
Christin Robrecht: Helfen kommt nach der Flut: Über die Ambivalenz situativ-nichtalltäglicher Dynamiken im Kontext der Flutkatastrophe im Ahrtal
Theresa Josephine Fischbach: Kontrollüberzeugung und Job Strain: Eine empirische Analyse verschiedener Ausprägungen von Job Strain aufgrund individueller Unterschiede der Kontrollüberzeugung
Rebekka Jachmig: Der Ukraine-Krieg im rechtspopulistischen Diskurs: Eine Analyse der Deutungsmuster von AfD-Politiker*innen
Hanna Schroer: Am Rande Galliens, inmitten der Welt: Eine Comicanalyse interkultureller Fremderfahrung am Beispiel der Comicserie Asterix
Lisa-Marie Schwab: Koloniale Spuren des Handels in Koblenz: Eine kritische Aufarbeitung
Jana Semrau: Okey-Doke: Political Critique in Spike Lee’s "BlacKkKlansman" (2018)
Anna Mira Olszewski: Of Wardrobes and Closets. A Lesson Plan on "Simon vs. Homo Sapiens Agenda" (2015) by Becky Albertalli
Marina Neuwert: Projektive Kommunikation von (Berufs-)Identität: Promotionsinteresse und Zukunftskarrieren bei Lehramtsstudierenden
Jan-Lukas Löwen: Zur Möglichkeit und Notwendigkeit der ästhetischen Erfahrung im Literaturunterricht
Malin Britz: Wearable Devices: Ein systemisches Review
This work addresses the challenge of calibrating multiple solid-state LIDAR systems. The study focuses on three different solid-state LIDAR sensors that implement different hardware designs, leading to distinct scanning patterns for each system. Consequently, detecting corresponding points between the point clouds generated by these LIDAR systems—as required for calibration—is a complex task. To overcome this challenge, this paper proposes a method that involves several steps. First, the measurement data are preprocessed to enhance its quality. Next, features are extracted from the acquired point clouds using the Fast Point Feature Histogram method, which categorizes important characteristics of the data. Finally, the extrinsic parameters are computed using the Fast Global Registration technique. The best set of parameters for the pipeline and the calibration success are evaluated using the normalized root mean square error. In a static real-world indoor scenario, a minimum root mean square error of 7 cm was achieved. Importantly, the paper demonstrates that the presented approach is suitable for online use, indicating its potential for real-time applications. By effectively calibrating the solid-state LIDAR systems and establishing point correspondences, this research contributes to the advancement of multi-LIDAR fusion and facilitates accurate perception and mapping in various fields such as autonomous driving, robotics, and environmental monitoring.
In der vorliegenden Dissertation mit dem Titel "Blickanalysen bei mentalen Rotationsaufgaben" wird eine Analyse der visuellen Verarbeitungsprozesse bei mentalen Rotationsaufgaben mittels Eye-Tracking-Technologie durchgeführt, um die zugrundeliegenden kognitiven Prozesse und Strategien, die bei der Lösung dieser Aufgaben angewandt werden, zu untersuchen. Ein Anliegen dieser Arbeit ist es, die Problemstellung zu adressieren, wie individuelle Unterschiede, insbesondere geschlechtsspezifische Differenzen in den Blickmustern, die visuelle Verarbeitung und Leistung bei mentalen Rotationsaufgaben beeinflussen. Hierzu wurden drei Studien durchgeführt, die nicht nur die Identifikation von Blickmustern und die Analyse der Leistungsunterschiede in Bezug auf Geschlecht umfassen, sondern auch die Korrelation zwischen Blickverhalten und Leistung untersuchen. Die Ergebnisse dieser Forschung bieten Einblicke in die Mechanismen der visuellen und kognitiven Verarbeitung bei mentalen Rotationsaufgaben und heben die Bedeutung des Eye-Tracking als Forschungsinstrument in der kognitiven Psychologie hervor, um ein umfassendes Verständnis der Einflussfaktoren auf räumliches Denken und Problemlösungsstrategien zu erlangen.
Classical music has played a central role in German music education since at least the second half of the 20th century. However, in more recent music pedagogical discourse, classical music remains a controversial topic. But what do music teachers think about classical music as a subject for music education? This topic has not yet been systematically researched in German-speaking music education.
In this qualitative-empirical study, eight semi-structured interviews were conducted to address the question of how music teachers perceive classical music in music education. The data was evaluated using the Grounded Theory Methodology. The theory developed from the study indicates that music teachers have varying objectives when using classical music in music education. However, they generally consider it unfamiliar to their students. To address this situation, music teachers develop various methods and strategies. These can be categorized into three approaches for dealing with the unfamiliarity of classical music: avoidance, reduction/relativization, and utilization.
The study's findings are contextualized within the framework of foreignness theory, music didactics, and transformational educational theory. This dissertation contributes to the field of music education in classical music, laying the groundwork for further theoretical, empirical, and didactic research.
Diese Dissertation widmet sich der inhaltsanalytischen, quantitativen Analyse der Kompilation Disney Princess durch die Anwendung der Theorie des male gaze von Laura Mulvey, welche sie in Visual Pleasure and Narrative Cinema (1975) sowie Afterthoughts on `Visual Pleasure and Narrative Cinema‘ inspired by King Vidor´s Duel in the Sun (1946) (1981) darstellte.
Die Autorin der Dissertation nutzt die quantitative Inhaltsanalyse nach Patrick Rössler, um die Filme der Kompilation Disney Princess aus den Jahren 1937 bis 2016 sowie den Film Die Eiskönigin (2013) auf die Darstellung der weiblich und männlich gelesenen Filmfiguren im Hinblick auf die Körperproportionen, den Grad ihrer Aktivität und den Umfang ihrer Präsenz sowie das Geschlecht der Filmmitarbeiter:innen zu untersuchen.
Focusing on the triangulation of detective fiction, masculinity studies and disability studies, "Investigating the Disabled Detective – Disabled Masculinity and Masculine Disability in Contemporary Detective Fiction" shows that disability challenges common ideals of (hegemonic) masculinity as represented in detective fiction. After a theoretical introduction to the relevant focal points of the three research fields, the dissertation demonstrates that even the archetypal detectives Dupin and Holmes undermine certain nineteenth-century masculine ideals with their peculiarities. Shifting to contemporary detective fiction and adopting a literary disability studies perspective, the dissertation investigates how male detectives with a form of neurodiversity or a physical impairment negotiate their masculine identity in light of their disability in private and professional contexts. It argues that the occupation as a detective supports the disabled investigator to achieve ‘masculine disability’. Inversing the term ‘disabled masculinity’, predominantly used in research, ‘masculine disability’ introduces a decisively gendered reading of neurodiversity and (acquired) physical impairment in contemporary detective fiction. The term implies that the disabled detective (re)negotiates his masculine identity by implementing the disability in his professional investigations and accepting it as an important, yet not defining, characteristic of his (gender) identity. By applying this approach to five novels from contemporary British and American detective fiction, the dissertation demonstrates that masculinity and disability do not negate each other, as commonly assumed. Instead, it emphasises that disability allows the detective, as much as the reader, to rethink masculinity.
Im Rahmen der Masterthesis „Analyse des Managements invasiver gebietsfremder Arten am Beispiel des Roten Amerikanischen Sumpfkrebses (Procambarus clarkii) während und im Anschluss an notwendige Sanierungsarbeiten am Hochwasserrückhaltebecken Breitenauer See östlich von Heilbronn“ wurde das Vorkommen des invasiven Roten Amerikanischen Sumpfkrebses am Breitenauer See umfangreich kartiert. Auch die nahegelegene Sulm mit bekanntem Vorkommen des Signalkrebses sowie das Nonnenbachsystem mit bekanntem Vorkommen des Steinkrebses wurden erfasst. Der Fokus lag auf der Beantwortung dreier Kernfragen. Zunächst wurde untersucht, ob und wie ein dauerhaftes IAS-Management (invasive alien species) des Roten Amerikanischen Sumpfkrebses am Breitenauer See nachhaltig durchgeführt werden kann, um inakzeptable ökologische Effekte zu vermeiden. Die zweite Fragestellung bezog sich auf die Wirksamkeit ergriffener Risikomanagementmaßnahmen während der Ablassaktion des Breitenauer Sees. Abschließend war fraglich, wie sich der Rote Amerikanische Sumpfkrebs verhält, wenn sein besiedeltes Gewässer trockenfällt.
Empirical studies in software engineering use software repositories as data sources to understand software development. Repository data is either used to answer questions that guide the decision-making in the software development, or to provide tools that help with practical aspects of developers’ everyday work. Studies are classified into the field of Empirical Software Engineering (ESE), and more specifically into Mining Software Repositories (MSR). Studies working with repository data often focus on their results. Results are statements or tools, derived from the data, that help with practical aspects of software development. This thesis focuses on the methods and high order methods used to produce such results. In particular, we focus on incremental methods to scale the processing of repositories, declarative methods to compose a heterogeneous analysis, and high order methods used to reason about threats to methods operating on repositories. We summarize this as technical and methodological improvements. We contribute the improvements to methods and high-order methods in the context of MSR/ESE to produce future empirical results more effectively. We contribute the following improvements. We propose a method to improve the scalability of functions that abstract over repositories with high revision count in a theoretically founded way. We use insights on abstract algebra and program incrementalization to define a core interface of highorder functions that compute scalable static abstractions of a repository with many revisions. We evaluate the scalability of our method by benchmarks, comparing a prototype with available competitors in MSR/ESE. We propose a method to improve the definition of functions that abstract over a repository with a heterogeneous technology stack, by using concepts from declarative logic programming and combining them with ideas on megamodeling and linguistic architecture. We reproduce existing ideas on declarative logic programming with languages close to Datalog, coming from architecture recovery, source code querying, and static program analysis, and transfer them from the analysis of a homogeneous to a heterogeneous technology stack. We provide a prove-of-concept of such method in a case study. We propose a high-order method to improve the disambiguation of threats to methods used in MSR/ESE. We focus on a better disambiguation of threats, operationalizing reasoning about them, and making the implications to a valid data analysis methodology explicit, by using simulations. We encourage researchers to accomplish their work by implementing ‘fake’ simulations of their MSR/ESE scenarios, to operationalize relevant insights about alternative plausible results, negative results, potential threats and the used data analysis methodologies. We prove that such way of simulation based testing contributes to the disambiguation of threats in published MSR/ESE research.
Sind Menschen von einer Pflegebedürftigkeit in Deutschland betroffen, so regelt der durch § 14 SGB XI festgeschriebene Pflegebedürftigkeitsbegriff den Zugang zu Leistungen der Pflegeversicherung. Der Pflegebedürftigkeitsbegriff ist dabei ein normativ gesetzter und basiert bislang nicht auf empirischen Studien aus dem Bereich der Pflege und der Pflegewissenschaft. Durch seine gesetzliche Fundierung lenkt er die Bedingungen und Strukturen, unter welchen Pflegeleistungen in Deutschland von Pflegefachpersonen erbracht werden. Weiterhin ist davon auszugehen, dass die Pflegefachpersonen durch ihre professionelle Sozialisierung einen fachlichen Fokus auf das Konstrukt der Pflegebedürftigkeit legen, welcher sich vom Pflegebedürftigkeitsbegriff unterscheidet und strukturell nicht in die Leistungsbemessung einfließt. Daraus ergeben sich Aspekte einer pflegerischen Unter- und Überversorgung.
Die vorliegende Ph.D.-Thesis verfolgt das Anliegen, die Herausforderungen des Pflegebedürftigkeitsbegriffs in Deutschland aufzuzeigen, indem die Aspekte der Pflegebedürftigkeit von Pflegefachpersonen im ambulanten Setting im Hinblick auf deren Interaktion mit pflegebedürftigen Menschen empirisch erfasst und zu einem theoretischen Konzept ausgearbeitet werden. Zur methodischen Bearbeitung des Forschungsinteresses werden problemzzentrierte Interviews mit ambulanten Pflegefachpersonen geführt, die mit Rückbezug auf den Symbolischen Interaktionismus nach Herbert Blumer unter methodologischen und methodischen Gesichtspunkten mittels einer Grounded Theory nach Kathy Charmaz sowie Juliet Corbin und Anselm Strauss erhoben und ausgewertet werden. Dabei kommt ein reflexives-konstruktivistisches Forschen und Schreiben als Konsequenz der epistemologisch-methodologischen Fundierung der Autorin zur Anwendung.
Die erarbeitete Theorie beschreibt die Herausforderungen der Pflegebedürftigkeit aus Sicht der befragten Pflegefachpersonen. So werden in der Kernkategorie Aushandlungsprozesse in den Bereichen Nähe und Distanz, Anwaltschaft und Verantwortungsüberlassung sowie Ethos und Technokratie beschrieben. Sämtliche Aspekte zeigen auf, inwiefern der gesetzliche Pflegebedürftigkeitsbegriff zu Herausforderungen innerhalb der pflegerischen Arbeit führt. Die Ph.D.-Thesis liefert mit ihren Ergebnissen einen Beitrag zur Einordnung und Relevanz pflegerischer Beziehungsarbeit im Hinblick auf herrschende Rahmenbedingungen der Pflegebedürftigkeit und zeigt auf, inwiefern sich Interaktion und Kommunikation der Akteur*innen vor dem Anspruch individueller Pflege und dem deutschen ambulanten Pflegesystem wechselseitig bedingen. Sie liefert damit einen professionell und empirisch begründeten Ansatz für die Einschätzung und Bearbeitung von pflegefachlich erlebter Pflegebedürftigkeit.
In the last years, the public interest in epidemiology and mathematical modeling of disease spread has increased - mainly caused by the COVID-19 pandemic, which has emphasized the urgent need for accurate and timely modelling of disease transmission. However, even prior to that, mathematical modelling has been used for describing the dynamics and spread of infectious diseases, which is vital for developing effective interventions and controls, e.g., for vaccination campaigns and social restrictions like lockdowns. The forecasts and evaluations provided by these models influence political actions and shape the measures implemented to contain the virus.
This research contributes to the understanding and control of disease spread, specifically for Dengue fever and COVID-19, making use of mathematical models and various data analysis techniques. The mathematical foundations of epidemiological modelling, as well as several concepts for spatio-temporal diffusion like ordinary differential equation (ODE) models, are presented, as well as an originally human-vector model for Dengue fever, and the standard (SEIR)-model (with the potential inclusion of an equation for deceased persons), which are suited for the description of COVID-19. Additionally, multi-compartment models, fractional diffusion models, partial differential equations (PDE) models, and integro-differential models are used to describe spatial propagation of the diseases.
We will make use of different optimization techniques to adapt the models to medical data and estimate the relevant parameters or finding optimal control techniques for containing diseases using both Metropolis and Lagrangian methods. Reasonable estimates for the unknown parameters are found, especially in initial stages of pandemics, when little to no information is available and the majority of the population has not got in contact with the disease. The longer a disease is present, the more complex the modelling gets and more things (vaccination, different types, etc.) appear and reduce the estimation and prediction quality of the mathematical models.
While it is possible to create highly complex models with numerous equations and parameters, such an approach presents several challenges, including difficulties in comparing and evaluating data, increased risk of overfitting, and reduced generalizability. Therefore, we will also consider criteria for model selection based on fit and complexity as well as the sensitivity of the model with respect to specific parameters. This also gives valuable information on which political interventions should be more emphasized for possible variations of parameter values.
Furthermore, the presented models, particularly the optimization using the Metropolis algorithm for parameter estimation, are compared with other established methods. The quality of model calculation, as well as computational effort and applicability, play a role in this comparison. Additionally, the spatial integro-differential model is compared with an established agent-based model. Since the macroscopic results align very well, the computationally faster integro-differential model can now be used as a proxy for the slower and non-traditionally optimizable agent-based model, e.g., in order to find an apt control strategy.
Artificial neural networks is a popular field of research in artificial intelli-
gence. The increasing size and complexity of huge models entail certain
problems. The lack of transparency of the inner workings of a neural net-
work makes it difficult to choose efficient architectures for different tasks.
It proves to be challenging to solve these problems, and with a lack of in-
sightful representations of neural networks, this state of affairs becomes
entrenched. With these difficulties in mind a novel 3D visualization tech-
nique is introduced. Attributes for trained neural networks are estimated
by utilizing established methods from the area of neural network optimiza-
tion. Batch normalization is used with fine-tuning and feature extraction to
estimate the importance of different parts of the neural network. A combi-
nation of the importance values with various methods like edge bundling,
ray tracing, 3D impostor and a special transparency technique results in a
3D model representing a neural network. The validity of the extracted im-
portance estimations is demonstrated and the potential of the developed
visualization is explored.
Leichte Sprache (LS, easy-to-read German) is a simplified variety of German. It is used to provide barrier-free texts for a broad spectrum of people, including lowliterate individuals with learning difficulties, intellectual or developmental disabilities (IDD) and/or complex communication needs (CCN). In general, LS authors are proficient in standard German and do not belong to the aforementioned group of people. Our goal is to empower the latter to participate in written discourse themselves. This requires a special writing system whose linguistic support and ergonomic software design meet the target group’s specific needs. We present EasyTalk a system profoundly based on natural language processing (NLP) for assistive writing in an extended variant of LS (ELS). EasyTalk provides users with a personal vocabulary underpinned with customizable communication symbols and supports in writing at their individual level of proficiency through interactive user guidance. The system minimizes the grammatical knowledge needed to produce correct and coherent complex contents by intuitively formulating linguistic decisions. It provides easy dialogs for selecting options from a natural-language paraphrase generator, which provides context-sensitive suggestions for sentence components and correctly inflected word forms. In addition, EasyTalk reminds users to add text elements that enhance text comprehensibility in terms of audience design (e.g., time and place of an event) and improve text coherence (e.g., explicit connectors to express discourse-relations). To tailor the system to the needs of the target group, the development of EasyTalk followed the principles of human-centered design (HCD). Accordingly, we matured the system in iterative development cycles, combined with purposeful evaluations of specific aspects conducted with expert groups from the fields of CCN, LS, and IT, as well as L2 learners of the German language. In a final case study, members of the target audience tested the system in free writing sessions. The study confirmed that adults with IDD and/or CCN who have low reading, writing, and computer skills can write their own personal texts in ELS using EasyTalk. The positive feedback from all tests inspires future long-term studies with EasyTalk and further development of this prototypical system, such as the implementation of a so-called Schreibwerkstatt (writing workshop)
In a world where language defines the boundaries of one's understanding, the words of Austrian philosopher Ludwig Wittgenstein resonate profoundly. Wittgenstein's assertion that "Die Grenzen meine Sprache bedeuten die Grenzen meiner Welt" (Wittgenstein 2016: v. 5.6) underscores the vital role of language in shaping our perceptions. Today, in a globalized and interconnected society, fluency in foreign languages is indispensable for individual success. Education must break down these linguistic barriers, and one promising approach is the integration of foreign languages into content subjects.
Teaching content subjects in a foreign language, a practice known as Content Language Integrated Learning (CLIL), not only enhances language skills but also cultivates cognitive abilities and intercultural competence. This approach expands horizons and aligns with the core principles of European education (Leaton Gray, Scott & Mehisto 2018: 50). The Kultusministerkonferenz (KMK) recognizes the benefits of CLIL and encourages its implementation in German schools (cf. KMK 2013a).
With the rising popularity of CLIL, textbooks in foreign languages have become widely available, simplifying teaching. However, the appropriateness of the language used in these materials remains an unanswered question. If textbooks impose excessive linguistic demands, they may inadvertently limit students' development and contradict the goal of CLIL.
This thesis focuses on addressing this issue by systematically analyzing language requirements in CLIL teaching materials, emphasizing receptive and productive skills in various subjects based on the Common European Framework of Reference. The aim is to identify a sequence of subjects that facilitates students' language skill development throughout their school years. Such a sequence would enable teachers to harness the full potential of CLIL, fostering a bidirectional approach where content subjects facilitate language learning.
While research on CLIL is extensive, studies on language requirements for bilingual students are limited. This thesis seeks to bridge this gap by presenting findings for History, Geography, Biology, and Mathematics, allowing for a comprehensive understanding of language demands. This research endeavors to enrich the field of bilingual education and CLIL, ultimately benefiting the academic success of students in an interconnected world.
The trends of industry 4.0 and the further enhancements toward an ever changing factory lead to more mobility and flexibility on the factory floor. With that higher need of mobility and flexibility the requirements on wireless communication rise. A key requirement in that setting is the demand for wireless Ultra-Reliability and Low Latency Communication (URLLC). Example use cases therefore are cooperative Automated Guided Vehicles (AGVs) and mobile robotics in general. Working along that setting this thesis provides insights regarding the whole network stack. Thereby, the focus is always on industrial applications. Starting on the physical layer, extensive measurements from 2 GHz to 6 GHz on the factory floor are performed. The raw data is published and analyzed. Based on that data an improved Saleh-Valenzuela (SV) model is provided. As ad-hoc networks are highly depended onnode mobility, the mobility of AGVs is modeled. Additionally, Nodal Encounter Patterns (NEPs) are recorded and analyzed. A method to record NEP is illustrated. The performance by means of latency and reliability are key parameters from an application perspective. Thus, measurements of those two parameters in factory environments are performed using Wireless Local Area Network (WLAN) (IEEE 802.11n), private Long Term Evolution (pLTE) and 5G. This showed auto-correlated latency values. Hence, a method to construct confidence intervals based on auto-correlated data containing rare events is developed. Subsequently, four performance improvements for wireless networks on the factory floor are proposed. Of those optimization three cover ad-hoc networks, two deal with safety relevant communication, one orchestrates the usage of two orthogonal networks and lastly one optimizes the usage of information within cellular networks.
Finally, this thesis is concluded by an outlook toward open research questions. This includes open questions remaining in the context of industry 4.0 and further the ones around 6G. Along the research topics of 6G the two most relevant topics concern the ideas of a network of networks and overcoming best-effort IP.
Gemeinsame Prüfungsordnung für den Bachelorstudiengang „Gewässerkunde und Wasserwirtschaft“ an der Hochschule Koblenz und der Universität Koblenz (Kooperativer Bachelorstudiengang)
Gemeinsame Prüfungsordnung für den Masterstudiengang „Gewässerkunde und Wasserwirtschaft“ an der Universität Koblenz und der Hochschule Koblenz (Kooperativer Masterstudiengang)
Satzung zur Sicherung guter wissenschaftlicher Praxis an der Universität Koblenz
Erste Ordnung zur Änderung der Wahlordnung für die Wahlen der Organe der Universität Koblenz
Prüfungsordnung für die Prüfung im Bachelorstudiengang Computational Social Science an der Universität Koblenz
Einunddreißigste Ordnung zur Änderung der Prüfungsordnung für die Prüfung im lehramtsbezogenen Bachelorstudiengang an der Universität Koblenz
Siebenundzwanzigste Ordnung zur Änderung der Prüfungsordnung für die Prüfung in den Masterstudiengängen für das Lehramt an Grundschulen, das Lehramt an Realschulen plus, das Lehramt an Förderschulen sowie das Lehramt an Gymnasien an der Universität Koblenz
Achtzehnte Ordnung zur Änderung der Ordnung für die Prüfung im lehramtsbezogenen Bachelorstudiengang berufsbildende Schulen an der Universität Koblenz und der Hochschule Koblenz
Siebzehnte Ordnung zur Änderung der Ordnung für die Prüfung im Masterstudiengang für das Lehramt an berufsbildenden Schulen an der Universität Koblenz und der Hochschule Koblenz
Achtundzwanzigste Ordnung zur Änderung der Ordnung für die Prüfung im lehramtsbezogenen Zertifikatsstudiengang (Erweiterungsprüfung) an der Universität Koblenz und der Hochschule Koblenz
Dritte Ordnung zur Änderung der Gemeinsamen Prüfungsordnung für die Bachelor- und Masterstudiengänge des Fachbereichs Informatik an der Universität Koblenz
Vierundzwanzigste Ordnung zur Änderung der Prüfungsordnung für die Prüfung im Zwei-Fach-Bachelorstudiengang an der Universität Koblenz
Satzung zur Festsetzung von Zulassungszahlen an der Universität Koblenz für das Studienjahr 2023/2024
Satzung zur Festsetzung der Normwerte für den Ausbildungsaufwand (Curricularnormwerte) der Universität Koblenz
Satzung der Universität Koblenz über das Auswahlverfahren in zulassungsbeschränkten Studiengängen
Qualitätssicherungskonzept für das Promotions- und Habilitationswesen der Universität Koblenz (Satzung über die Genehmigung von Promotions- und Habilitationsordnungen)
Dritte Ordnung zur Änderung der Prüfungsordnung für Studierende des Bachelorstudiengangs „Pädagogik“ (B.A.) und des Masterstudiengangs „Erziehungswissenschaft mit dem Schwerpunkt Forschung und Entwicklung in Organisationen“ (M.A.) des Fachbereichs 1: Bildungswissenschaften an der Universität Koblenz
Ordnung zum Betrieb eines Forschungsinformationssystems an der Universität Koblenz (FIS-Ordnung)
Organic binder mixtures and process additives have been used in refractory materials for a long time due to their property-improving effect. Coal tar pitches in particular can contain thousands of chemical compounds, of which especially polycyclic aromatic hydrocarbons (PAHs) are known to be carcinogenic and mutagenic and thus pose a risk to both the environment and human health. However, despite intensive research, the exact structure of these carbon mixtures is still not fully clarified. This is becoming an increasing problem, especially with regard to more stringent legal requirements arising from REACH, the European Chemicals Regulation for the Registration, Evaluation, Authorization and Restriction of Chemicals. Furthermore, the knowledge of the structural and chemical composition is also of great importance for optimal processing of the carbon mixtures to high-quality technical products. In the present work, an analytical strategy for the investigation of complex carbon mixtures containing PAHs is developed. Due to their complexity, a combination of different methods is used, including elemental analysis, solvent extraction, thermogravimetry, differential thermal analysis, raman and infrared spectroscopy as well as high-resolution mass spectrometry. In addition, a procedure for the evaluation of mass spectrometric data based on multivariate statistical methods such as hierarchical cluster analysis and principal component analysis is developed. The application of the developed analytical strategy to various industrially used carbon-based binder mixtures allowed the elucidation of characteristic properties, including aromaticity, molecular mass distribution, degree of alkylation and elemental composition. It was also shown that combining high-resolution time-of-flight mass spectrometry with multivariate statistical data analysis is a fast and effective tool for the classification of complex binder mixtures and the identification of characteristic molecular structures. In addition, the analytical strategy was applied to manufactured refractory products. Despite the small amount of the contained organic phase, characteristic structural features of each sample could be identified and extracted, which enabled an unambiguous classification of the refractory products.
Die Geometrie unseres Anschauungsraumes – die euklidische Geometrie – ist für einen allgemeinbildenden Mathematikunterricht elementar. Seitens der Mathematiklehrkraft stellt grundsätzlich ihr Fachwissen das Fundament des Unterrichtens dar. Als Teil ihres Professionswissens sollten Mathematiklehrkräfte prinzipiell über ein Fachwissen verfügen, das in Bezug zur akademischen Mathematik den unterrichtlichen Anforderungen der schulischen Mathematik gerecht wird.
Die im Rahmen der Dissertation entwickelte Theorie des metrisch-normalen euklidischen Raumes charakterisiert sich in ihrer perspektivischen Dualität, der mathematischen Stringenz eines axiomatisch-deduktiven Vorgehens auf der einen und der Berücksichtigung der fachdidaktischen Anforderungen an Mathematiklehrkräfte auf der anderen Seite; sie hebt sich darin von bestehenden Theorien ab.
With the increasing importance and urgency of climate change, companies are challenged to contribute to sustainable development, especially by younger generations. However, existing corporate contributions have been criticized as insufficient, which could be particularly caused by a lack of employee engagement in corporate sustainability. In this context, gamification has been proposed and increasingly investigated in recent years as a promising, innovative tool to motivate sustainable employee behaviors in the workplace. However, there are few studies and applicable gamification solutions that address more than one specific sustainability issue and thus take a holistic perspective on sustainable behaviors in the workplace. Moreover, previous research lacks a comprehensive understanding of how different gamification elements elicit specific psychological effects, how these manifest in behavioral changes, and how these, in turn, cumulatively result in measurable corporate outcomes. The path from gamification as ”input” to corporate sustainability as ”output” thus remains unexplored.
This dissertation fills this gap by conceptualizing, designing, and evaluating a holistic gamified intervention that supports employees in various sustainable behaviors in their daily activities. The project uses a design science research approach that closely involves employees in the incremental development of the solution. As part of the iterative design process, this dissertation presents six studies to extend the theoretical understanding of gamification for sustainable employee behaviors. First, a comprehensive review of existing research on gamification for sustainable employee behavior is provided, analyzing gamification designs and results of previous studies and outlining an agenda for further research (Study 1). Theoretical foundations of research on gamification, serious games, and game-based learning (Study 2) and empirical design principles for gamification and persuasive systems (Study 3) are then systematically reviewed as a basis for the successful design of gamified applications. Subsequently, empirical studies explore employees’ motivations for sustainable behavior and illuminate their expectations for design features (Study 4), and identify contextual challenges and design dilemmas when implementing gamification in an organizational context (Study 5). Finally, a quantitative field study (Study 6) explores how different gamification designs influence sustainable employee behavior and corporate sustainability in organizations. Based on the findings, this dissertation presents a comprehensive framework of gamification for sustainable employee behavior that incorporates design, individual behavior, and organizational perspectives. Finally, building on these insights, it provides practical recommendations for designing gamification to encourage sustainable employee behavior at work.
Sustainable Leadership
(2023)
Thematik:
Die vorliegende Forschungsarbeit befasst sich mit dem Thema Sustainable Leadership. Dieses Forschungsgebiet der nachhaltigkeitsorientierten Forschung hat in den letzten Jah- ren durch die immer stärker werden Auswirkungen des Klimawandels erheblich an Bedeutung gewonnen. In diesem Zusammenhang rücken Unternehmen immer mehr in den Fokus. Diese müssen nun Wege und Methoden finden, die ihre Arbeitsweise und Prozesse nachhaltiger und umweltschonender gestalten. Die in der vorliegenden Arbeit zu untersuchende Forschungsfrage lautet: „Wie gestaltet sich ein Sustainable Leadership Ansatz in Unternehmen?“ Aufbauend auf dieser übergeordneten Forschungsfrage werden in untergeordneten Forschungsfrage insbesondere Merkmale, Kompetenzen und Verhaltensweisen eines nachhaltigkeitsorientierten Führungsstils betrachtet.
Methodik:
Die Forschungsmethodik der vorliegenden Arbeit ist eine qualitative Inhaltsanalyse nach Mayring (2019). Mittels semistrukturierter Interviews wurden Führungspersönlichkeiten aus Großunternehmen befragt. Auf Grundlage dieses Datenmaterials wurden induktive Kategorien abgeleitet und qualitativ analysiert und interpretiert.
Ergebnisse:
Die Ergebnisse der empirischen Forschung wurden in insgesamt fünf Oberkategorien mit jeweils zwei Unterkategorien zusammengefasst. Es wurden die theoretischen Erkennt- nisse des Forschungsbereichs mit den praktischen Erkenntnissen aus den durchgeführten Interviews ergänzt und interpretiert. Des Weiteren wurden die Ergebnisse aus Sicht einer holistischen Unternehmensperspektive in einem konzeptionellen Ansatz modelliert. Ab- schließend wurden aus den Praxiserfahrungen einige Handlungsempfehlungen formuliert und die Merkmale, Kompetenzen, Verhaltensweisen und Auswirkungen eines nachhal- tigkeitsorientierten Führungsstils diskutiert.
Bauxite is, among other raw materials, an important material for the production of refractories. However, the availability of refractory raw material grades is limited worldwide. As high iron contents have a negative influence on the temperature resistance of the refractory material produced, a maximum iron oxide content of 2 wt.-% in the bauxite is acceptable. This means that only native raw materials from a few deposits can be used. In order to counteract the problem of too high iron oxide contents in natural bauxites, the possibility of processing bauxite for the refractory industry by using an acid leaching process was to be investigated within the scope of this work. In previous studies on this topic, some investigations on iron leaching have already been carried out on individual bauxites. However, the resulting bauxite composition was mostly neglected in its entirety and only the influences of individual leaching parameters on the leaching result were investigated independently. Moreover, the results and procedures generated are not generally valid and cannot be transferred to bauxites of other chemical or mineralogical compositions.
In order to clarify the open questions in the processing of natural bauxites, leaching tests with hydrochloric acid were carried out on five different bauxites within this work. By using computerized statistical design of experiments, an individual model was generated for each bauxite to predict the optimal factor settings. The factors investigated were acid concentration, solid-acid ratio, leaching temperature, leaching time and grain fraction. The general planning method for bauxite processing developed in this context contains all necessary factors, useful factor settings and the effects to be considered during planning and evaluation. It could be shown that, based on this planning method, a significant, individual model can be created for each of the bauxites investigated, which predicts the optimal leaching settings for the corresponding bauxite. Furthermore, it was found that the transfer of an already created model to another bauxite of similar composition is possible. Based on the results obtained from the leaching tests and model fittings, in combination with further results on the structural analysis of the bauxites, insights into the leachability of various aluminium and iron minerals from bauxite could be gained.
To develop a sustainable acid leaching process, the possibility of regenerating the contaminated acid produced was also tested as an example. It was shown that liquid-liquid extraction can extract more than 99 % of the iron present in the solution and that the regenerated acid can then be reused for the leaching process.