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.

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.

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.

The paper studies the digital transformation maturity in the context of the aviation industry in Vietnam. Digital transformation can mean enhancing existing processes, finding new opportunities within existing business domains, or finding new opportunities outside existing business domains. In the era of post Covid-19, digital transformation will play a vital role in the recovery with the support from digital technology to leverage the communication and implementation of new projects or changes. Digital transformation and digital transformation maturity sometimes are used indistinguishing, but they are two different definitions. This paper will further explain the differences and will apply digital transformation maturity as a scale for the digital transformation in the report. Due to the lack of experiment in the relationship between digital transformation maturity and the organizational readiness, the study will explore four components of organizational readiness, including digital leadership, digital culture, digital capabilities, and digital partnering.

For many decades, one of the most important focuses of research has been on determining whether or not there is a correlation between the size of an organization and its level of innovation. Unlike small companies, large companies often have well-established structure that are hard to change and change managements seems to be much more difficult especially related to innovation. Nevertheless, there are many examples to prove the opposites. Some large organization like Apple, Amazon... always show great innovation efforts and keep changing in a much positive way. Therefore, the aim of this thesis is to discuss of how large organization can be able to implement innovation when having much drawbacks compare to SMEs. Through the use of a qualitative research approach, researcher was able to explore essential information on the innovation strategies that large companies are using in order to innovate and how they could overcome existing challenges by studying the working process of Lotte Group – one of the biggest companies in Korea.

Predictive Process Monitoring is becoming more prevalent as an aid for organizations to support their operational processes. However, most software applications available today require extensive technical know-how by the operator and are therefore not suitable for most real-world scenarios. Therefore, this work presents a prototype implementation of a Predictive Process Monitoring dashboard in the form of a web application. The system is based on the PPM Camunda Plugin presented by Bartmann et al. (2021) and allows users to easily create metrics, visualizations to display these metrics, and dashboards in which visualizations can be arranged. A usability test is with test users of different computer skills is conducted to confirm the application’s user-friendliness.

The growing numbers of breeding rooks (Corvus frugilegus) in the city of Landau (Rhineland- Palatinate, Germany) increase the potential for conflict between rooks and humans, which is mainly associated with noise and faeces. Therefore, the aim of this work is a better understanding of the breeding tree selection of the rook in order to develop options for action and management in the future. Part I of this thesis provides general background information on the rook and includes mapping of the rookeries in the Anterior Palatinate and South Palatinate including Landau in the year 2020. That mapping revealed that the number of rural colonies has decreased, while the number of urban colonies has increased in the study area in the last few years. In line with current literature, tree species and tree size were important criteria for breeding tree selection. However, the mapping showed that additional factors must be important as well. Therefore, as rooks seem to often breed along traffic axes, Part II of this thesis examines how temperature, artificial light and noise, which are all linked to traffic axes, affect the breeding tree selection of the rook in the city of Landau. The following three hypotheses are developed: (1) manually selected breeding trees (Bm) have a warmer microclimate than manually selected non-breeding trees (Nm) or randomly selected non-breeding trees (Nr), (2) Bm are exposed to a higher light level than Nm or Nr and (3) Bm are exposed to a higher noise level than Nm or Nr. To test these hypotheses, 15 Bm, 13 Nm and 16 Nr are investigated. The results show that Bm were exposed to more noise than both types of non-breeding trees (μBm, noise = 36.52481 dB, μNm, noise = 31.27229 dB, μNr, noise = 29.17417 dB) where the difference between Bm and Nr was significant. In addition, there was a tendency for Bm to be exposed to less light (μBm, light = 0.356 lx) than Nm (μNm, light = 0.4107692 lx) and significantly less light than Nr (μNr, light = 1.995 lx), while temperature did not differ between the groups (μBm, temp = 16.90549 °C, μNm, temp = 16.93118 °C, μNr, temp = 17.28639 °C). This study shows for the first time that rooks prefer trees which are exposed to low light levels and high noise levels, i.e. more intense traffic noise, for breeding. It can only be speculated that the cause of this is lower enemy pressure at such sites. The fact that temperature does not seem to have any influence on breeding tree selection may be due to only small temperature differences at nest height, which might be compensated by breeding behaviour. Consequently, in the long term one management approach could be to divert traffic from inner-city areas, especially schools and hospitals, to bypasses. If tree genera suitable for rooks, such as plane trees, are planted along the bypasses, those sites could provide suitable alternative habitats to inner-city breeding locations, which become less attractive for breeding due to noise reduction. In the short term in addition to locally implemented repellent measures the most effective approach is to strengthen rook acceptance among the population. However, further research is needed to verify the results of this thesis and to gain further insights into rook breeding site selection in order to develop effective management measures.

Der Zweck dieser Arbeit ist es, sich auf die kritischen Forschungsherausforderungen und -themen zu konzentrieren, die UI/UX-Designprinzipien umgeben, mit einem Schwerpunkt auf kulturübergreifenden Konzepten aus der Perspektive von E-Learning-Plattformen. Zu diesem Zweck betrachten wir zunächst die kulturellen Dimensionen auf der Grundlage des Hofstede-Rahmens mit dem Ziel, wichtige kulturelle Werte zu identifizieren. Als zweites Ziel der Forschung erleichtert eine Reihe von Kriterien, die so genannte Usability-Heuristik von Nielsen, die Erkennung von Usability Problemen bei der Gestaltung von Benutzeroberflächen (UI). Die Usability-Heuristiken umfassen zehn Variablen, die die Interaktion zwischen dem Benutzer und einem Produkt oder System beeinflussen. Wenn wir uns näher mit diesen Themen befassen, werden wir in der Lage sein, eine Matrix mit Beziehungen zwischen der heuristischen Bewertung von Nielsen und dem kulturellen Rahmen von Geert Hofstede aufzudecken. Abschließend erörtern wir das mögliche Potenzial kultureller Werte zur Beeinflussung von Benutzeroberflächen für E-Learning-Plattformen. In der Tat gibt es einige Funktionen in E-Learning-Plattformen, die aufgrund der Kultur weniger diskutiert werden, obwohl sie sehr praktisch in die Plattformen integriert werden können.

Rudolf Virchows Vorstellungen von einer human-bürgerlichen Krankenpflege in der Zeit des preußischen Kulturkampfes Über die Auseinandersetzungen im Preußischen Haus der Abgeordneten zwischen Rudolf Virchow, dem Kultusministerium und der Zentrumspartei über die katholischen Kranken-pflegeorden – von Hilmar Conrad Der Mediziner und liberale Abgeordnete des Preußischen Hauses der Abgeordneten Rudolf Virchow ist vielen bekannt für den Satz „‹Omnis cellula e cellula›“1, aus seinem Werk ‚Die Zellularpathologie‘. Er wies mit diesem Lehrsatz und der zugrundeliegenden Forschung nach, dass Zellen in Morphologie und Funktion die kleinste Einheit des menschlichen Körpers sind.2 Der spätere Medizinprofessor wurde am 13. Oktober 1821 in Schivelbein geboren und verstarb am 5. September 1902 in Berlin. Das Jahr 1848 ist in zweierlei Hinsicht als Schicksalsjahr für Virchow zu betrachten. Er war in dieser Zeit Militärarzt und wurde in diesem Winter 1847/48 von der preußischen Regierung nach Ober-schlesien entsendet, wo eine Typhus-Epidemie wütete. Sein Auftrag war die wissenschaftliche Analyse der Geschehnisse. An seinem 80. Geburtstag sagte er über diese Reise: „Jene 16 Tage in Oberschlesien, 1848, waren das entscheidende Ereignis meines Lebens.“3 Es war Revolution in Berlin und dort zurück, nahm er an den Kämpfen für Demokratie teil.4 Im Bericht über seine Reise schlussfolgerte er, dass zur Prävention einer solchen Seuche in Oberschlesien Demokratisierung und Bildung für die Bevölkerung notwendig seien – das war der Beginn der Sozialmedizin. Ab 1859 war er Berliner Stadtverordneter und ab 1861 Mitglied des Preußischen Abgeordnetenhauses für die linksliberale Deutsche Fortschrittspartei, die er zusammen mit Mitstreitern gegründet hatte. Von 1880 bis 1893 war er Abgeordneter im Deutschen Reichstag.5 Für ihn war „[d]ie Medizin […] eine soziale Wissenschaft, und die Politik ist weiter nichts als Medizin im Großen.“6 Was diese Person also so spannend macht, ist, dass sie gleich zwei relevanten Gruppen angehörte, welche einflussreich über die Krankenpflege sprachen: die der Politik und die der Ärzte. Rudolf Virchow forderte am 9. November 1869 auf dem Kongress der deutschen Frauenvereine in Berlin eine Pflege, die sich außerhalb der Kirchen organisieren solle: „Organisiren wir ganz und gar ausserhalb der kirchlichen Organisation, organisiren wir ganz innerhalb der bürgerlichen Gesellschaft als solcher, nach rein menschlichen Aufgaben, ohne irgend einen weiteren Nebenzweck.“7 Was Virchow hier forderte ist eine Hinwendung zum ‚Humanen‘8, wie er es nannte und auch in mehreren Debatten im Abgeordnetenhaus erläuterte. Dies überrascht nicht, war er doch maßgeblich am Kulturkampf im Parlament beteiligt und ein vehementer Verfechter der Säkularisierung.9 Das wissenschaftlich relevante Problem an dieser Stelle ist Virchows zentrale Äußerungen über die Krankenpflege im Kontext der geführten Debatten im Preußischen Abgeordnetenhaus darzustellen. Die wissenschaftliche Literatur geht hierbei, nur sehr oberflächlich auf das vor- und hinterher Gesagte ein, obwohl es sich um Debatten handelt. Und hier zeigt sich auch die Relevanz der Arbeit. Natürlich liegt das Interesse darauf, Virchows Vorstellungen über die Krankenpflege anhand seiner Beiträge im Preußischen Haus der Abgeordneten nachzuvollziehen, aber eben auch nachzuzeichnen, wie sich die gesamten Debatten um die Krankenpflege, in denen sich Virchow bewegte, zugetragen hatten. Demnach ist das Erkenntnisinteresse dieser Arbeit herauszuarbeiten, welche Ansichten Rudolf Virchow über die Krankenpflege seiner Zeit hatte, wie er sie im Preußischen Haus der Abgeordneten verteidigte, wie sich die Ansichten seiner politischen Gegner und der preußischen Regierung dazu verhielten sowie daraus folgend, wie die Debatten über die Krankenpflege im Preußischen Abgeordnetenhaus verliefen. 1 Virchow, zit. n. Schipperges (1994): Rudolf Virchow, S. 58. 2 Schipperges (2008): Virchow, Rudolf (Ludwig Carl), S. 257. 3 Andree (2006): Rudolf Virchow (1821–1902) im Spannungsfeld von Glauben, Kirche und Staat, S. 99. 4 Vgl. ebd., S. 99–100. 5 Vgl. Schipperges (2008): Virchow, Rudolf (Ludwig Carl), S. 257–258. 6 Schipperges (1994): Rudolf Virchow, S. 113. Im Original kursiv. 7 Virchow (1879): Die berufsmässige Ausbildung zur Krankenpflege, auch ausserhalb der kirchlichen Organisationen, S. 49. Im Original gesperrt. 8 Vgl. Virchow (1875): Rede im Preußischen Abgeordnetenhaus, Berlin. 8. Mai 1875, S. 207. 9 Vgl. Virchow (1873): Rede im Preußischen Abgeordnetenhaus, Berlin. 17. Januar 1873, S. 359.

In this thesis different methods for rendering point data are shown and compared with each other. The methods can be divided into two categories. For one visual methods are introduced that strictly deal with the displaying of point primitves. The main problem here lies in the depiction of surfaces since point data, unlike traditional triangle meshes, doesn't contain any connectivity information. On the other hand data strucutres are shown that enable real-time rendering of large point clouds. Point clouds often contain large amounts of data since they are mostly generated through 3D scanning processes such as laser scanning and photogrammetry.

Soziale Netzwerke spielen im Alltagsleben der Schülerinnen und Schüler eine entscheidende Rolle. Im Rahmen der vorliegenden Masterarbeit wurde ein Konzept für die Anzeige von Profilvorschlägen innerhalb des sozialen Netzwerks „InstaHub“, welches ein speziell für den Informatikunterricht programmiertes Werkzeug zum Thema „Datenbanken“ darstellt, entwickelt. Als Hürde stellte sich dabei dar, dass von den etablierten sozialen Netzwerken nur wenig bis gar keine Informationen über die Berechnung von Profil- oder Freundschaftsvorschlägen preisgegeben werden. Daher wurde zunächst das Wesen von Beziehungen zwischen Menschen in nicht-internetbasierten und in internetbasierten sozialen Netzwerken sowie die Gründe für Beziehungen zwischen Menschen in diesen Netzwerken dargelegt. Anhand der Beobachtung von Vorschlägen in anderen sozialen Netzwerken sowie der in InstaHub gespeicherten Nutzerdaten wurde ein Algorithmus für Profilvorschläge in InstaHub entworfen und mitsamt einer passenden Visualisierung entsprechend implementiert. Den zweiten Teil der Arbeit bildete eine Unterrichtseinheit für die Sekundarstufe II mit dem Thema Gefahren der Erzeugung und Verarbeitung von personenbezogenen Daten. In der Unterrichtseinheit dienen die Profilvorschläge in InstaHub, die auf von InstaHub über dessen Nutzer gesammelten Daten aufbauen, als Einstieg in die Thematik. Anschließend wird der Fokus von sozialen Netzwerken auf andere Online-Dienste erweitert und auf die Verarbeitung und Weitergabe dieser Daten eingegangen.

The Material Point Method (MPM) has proven to be a very capable simulation method in computer graphics that is able to model materials that were previously very challenging to animate [1, 2]. Apart from simulating singular materials, the simulation of multiple materials that interact with each other introduces new challenges. This is the focus of this thesis. It will be shown that the self-collision capabilities of the MPM can naturally handle multiple materials interacting in the same scene on a collision basis, even if the materials use distinct constitutive models. This is then extended by porous interaction of materials as in[3], which also integrates easily with MPM.It will furthermore be shown that regular single-grid MPM can be viewed as a subset of this multi-grid approach, meaning that its behavior can also be achieved if multiple grids are used. The porous interaction is generalized to arbitrary materials and freely changeable material interaction terms, yielding a flexible, user-controllable framework that is independent of specific constitutive models. The framework is implemented on the GPU in a straightforward and simple way and takes advantage of the rasterization pipeline to resolve write-conflicts, resulting in a portable implementation with wide hardware support, unlike other approaches such as [4].

The industry standard Decision Model and Notation (DMN) has enabled a new way for the formalization of business rules since 2015. Here, rules are modeled in so-called decision tables, which are defined by input columns and output columns. Furthermore, decisions are arranged in a graph-like structure (DRD level), which creates dependencies between them. With a given input, the decisions now can be requested by appropriate systems. Thereby, activated rules produce output for future use. However, modeling mistakes produces erroneous models, which can occur in the decision tables as well as at the DRD level. According to the Design Science Research Methodology, this thesis introduces an implementation of a verification prototype for the detection and resolution of these errors while the modeling phase. Therefore, presented basics provide the needed theoretical foundation for the development of the tool. This thesis further presents the architecture of the tool and the implemented verification capabilities. Finally, the created prototype is evaluated.

The underlying characteristics of blockchain can facilitate data provenance, data integrity, data security, and data management. It has the potential to transform the healthcare sector. Since the introduction of Bitcoin in the fintech industry, the blcockhain technology has been gaining a lot of traction and its purpose is not just limited to finance. This thesis highlights the inner workings of blockchain technology and its application areas with possible existing solutions. Blockchain could lay the path for a new revolution in conventional healthcare systems. We presented how individual sectors within the healthcare industry could use blockchain and what solution persists. Also, we have presented our own concept to improve the existing paper-based prescription management system which is based on Hyperledger framework. The results of this work suggest that healthcare can benefit from blockchain technology bringing in the new ways patients can be treated.

Constituent parsing attempts to extract syntactic structure from a sentence. These parsing systems are helpful in many NLP applications such as grammar checking, question answering, and information extraction. This thesis work is about implementing a constituent parser for German language using neural networks. Over the past, recurrent neural networks have been used in building a parser and also many NLP applications. In this, self-attention neural network modules are used intensively to understand sentences effectively. With multilayered self-attention networks, constituent parsing achieves 93.68% F1 score. This is improved even further by using both character and word embeddings as a representation of the input. An F1 score of 94.10% was the best achieved by constituent parser using only the dataset provided. With the help of external datasets such as German Wikipedia, pre-trained ELMo models are used along with self-attention networks achieving 95.87% F1 score.

Weiterentwicklung des Newsfeeds von InstaHub und Entwicklung einer Unterrichtsreihe zum Thema „Algorithmen in sozialen Netzwerken“ für die Sekundarstufe II

Current political issues are often reflected in social media discussions, gathering politicians and voters on common platforms. As these can affect the public perception of politics, the inner dynamics and backgrounds of such debates are of great scientific interest. This thesis takes user generated messages from an up-to-date dataset of considerable relevance as Time Series, and applies a topic-based analysis of inspiration and agenda setting to it. The Institute for Web Science and Technologies of the University Koblenz-Landau has collected Twitter data generated beforehand by candidates of the European Parliament Election 2019. This work processes and analyzes the dataset for various properties, while focusing on the influence of politicians and media on online debates. An algorithm to cluster tweets into topical threads is introduced. Subsequently, Sequential Association Rules are mined, yielding wide array of potential influence relations between both actors and topics. The elaborated methodology can be configured with different parameters and is extensible in functionality and scope of application.

Belief revision is the subarea of knowledge representation which studies the dynamics of epistemic states of an agent. In the classical AGM approach, contraction, as part of the belief revision, deals with the removal of beliefs in knowledge bases. This master's thesis presents the study and the implementation of concept contraction in the Description Logic EL. Concept contraction deals with the following situation. Given two concept C and D, assuming that C is subsumed by D, how can concept C be changed so that it is not subsumed by D anymore, but is as similar as possible to C? This approach of belief change is different from other related work because it deals with contraction in the level of concepts and not T-Boxes and A-Boxes in general. The main contribution of the thesis is the implementation of the concept contraction. The implementation provides insight into the complexity of contraction in EL, which is tractable since the main inference task in EL is also tractable. The implementation consists of the design of five algorithms that are necessary for concept contraction. The algorithms are described, illustrated with examples, and analyzed in terms of time complexity. Furthermore, we propose an new approach for a selection function, adapt for the concept contraction. The selection function uses metadata about the concepts in order to select the best from an input set. The metadata is modeled in a framework that we have designed, based on standard metadata frameworks. As an important part of the concept contraction, the selection function is responsible for selecting the best concepts that are as similar as possible to concept C. Lastly, we have successfully implemented the concept contraction in Python, and the results are promising.

Commonsense reasoning can be seen as a process of identifying dependencies amongst events and actions. Understanding the circumstances surrounding these events requires background knowledge with sufficient breadth to cover a wide variety of domains. In the recent decades, there has been a lot of work in extracting commonsense knowledge, a number of these projects provide their collected data as semantic networks such as ConceptNet and CausalNet. In this thesis, we attempt to undertake the Choice Of Plausible Alternatives (COPA) challenge, a problem set with 1000 questions written in multiple-choice format with a premise and two alternative choices for each question. Our approach differs from previous work by using shortest paths between concepts in a causal graph with the edge weight as causality metric. We use CausalNet as primary network and implement a few design choices to explore the strengths and drawbacks of this approach, and propose an extension using ConceptNet by leveraging its commonsense knowledge base.

Business Process Querying (BPQ) is a discipline in the field of Business Process Man- agement which helps experts to understand existing process models and accelerates the development of new ones. Its queries can fetch and merge these models, answer questions regarding the underlying process, and conduct compliance checking in return. Many languages have been deployed in this discipline but two language types are dominant: Logic-based languages use temporal logic to verify models as finite state machines whereas graph-based languages use pattern matching to retrieve subgraphs of model graphs directly. This thesis aims to map the features of both language types to features of the other to identify strengths and weaknesses. Exemplarily, the features of Computational Tree Logic (CTL) and The Diagramed Modeling Language (DMQL) are mapped to one another. CTL explores the valid state space and thus is better for behavioral querying. Lacking certain structural features and counting mechanisms it is not appropriate to query structural properties. In contrast, DMQL issues structural queries and its patterns can reconstruct any CTL formula. However, they do not always achieve exactly the same semantic: Patterns treat conditional flow as sequential flow by ignoring its conditions. As a result, retrieved mappings are invalid process execution sequences, i.e. false positives, in certain scenarios. DMQL can be used for behavioral querying if these are absent or acceptable. In conclusion, both language types have strengths and are specialized for different BPQ use cases but in certain scenarios graph-based languages can be applied to both. Integrating the evaluation of conditions would remove the need for logic-based languages in BPQ completely.

Clubs, such as Scouts, rely on the work of their volunteer members, who have a variety of tasks to accomplish. Often there are sudden changes in their organization teams and offices, whereby planning steps are lost and inexperience in planning occurs. Since the special requirements are not covered by already existing tools, ScOuT, a planning tool for the organization administration, is designed and developed in this work to support clubs with regard to the mentioned problems. The focus was on identifying and using various suitable guidelines and heuristic methods to create a usable interface. The developed product was evaluated empirically by a user survey in terms of usability. The result of this study shows that already a high degree of the desired goal could be reached by the inclusion of the guidelines and methods. From this it can be concluded that with the help of user-specific concept ideas and the application of suitable guidelines and methods, a suitable basis for a usable application to support clubs can be created.

The erosion of the closed innovation paradigm in conjunction with increasing competitive pressure has boosted the interest of both researchers and organizations in open innovation. Despite such rising interest, several companies remain reluctant to open their organizational boundaries to practice open innovation. Among the many reasons for such reservation are the pertinent complexity of transitioning toward open innovation and a lack of understanding of the procedures required for such endeavors. Hence, this thesis sets out to investigate how organizations can open their boundaries to successfully transition from closed to open innovation by analyzing the current literature on open innovation. In doing so, the transitional procedures are structured and classified into a model comprising three phases, namely unfreezing, moving, and institutionalizing of changes. Procedures of the unfreezing phase lay the foundation for a successful transition to open innovation, while procedures of the moving phase depict how the change occurs. Finally, procedures of the institutionalizing phase contribute to the sustainability of the transition by employing governance mechanisms and performance measures. Additionally, the individual procedures are characterized along with their corresponding barriers and critical success factors. As a result of this structured depiction of the transition process, a guideline is derived. This guideline includes the commonly employed actions of successful practitioners of open innovation, which may serve as a baseline for interested parties of the paradigm. With the derivation of the guideline and concise depiction of the individual transitional phases, this thesis consequently reduces the overall complexity and increases the comprehensibility of the transition and its implications for organizations.

Data flow models in the literature are often very fine-grained, which transfers to the data flow analysis performed on them and thus leads to a decrease in the analysis' understandability. Since a data flow model, which abstracts from the majority of implementation details of the program modeled, allows for potentially easier to understand data flow analyses, this master thesis deals with the specification and construction of a highly abstracted data flow model and the application of data flow analyses on this model. The model and the analyses performed on it have been developed in a test-driven manner, so that a wide range of possible data flow scenarios could be covered. As a concrete data flow analysis, a static security check in the form of a detection of insufficient user input sanitization has been performed. To date, there's no data flow model on a similarly high level of abstraction. The proposed solution is therefore unique and facilitates developers without expertise in data flow analysis to perform such analyses.

In dieser Arbeit wird eine Unterrichtsreihe beschrieben, welche aus den drei Bereichen „mathematische Relationen“, „Datenbanken in Sozialen Netzwerken“ und „Datenschutz“ zusammengesetzt ist. Zu jedem Bereich wird ein eigener Unterrichtsentwurf präsentiert. Außerdem wurde im Rahmen der vorliegenden Arbeit ein Programm zur Visualisierung der Relationen des Sozialen Netzwerks Instahub entworfen, welches im Anschluss an die Beschreibung der Unterrichtsreihe aufgeführt wird.

The Internet of Things (IoT) is a fast-growing, technological concept, which aims to integrate various physical and virtual objects into a global network to enable interaction and communication between those objects (Atzori, Iera and Morabito, 2010). The application possibilities are manifold and may transform society and economy similarly to the usage of the internet (Chase, 2013). Furthermore, the Internet of Things occupies a central role for the realisation of visionary future concepts, for example, Smart City or Smart Healthcare. In addition, the utilisation of this technology promises opportunities for the enhancement of various sustainability aspects, and thus for the transformation to a smarter, more efficient and more conscious dealing with natural resources (Maksimovic, 2017). The action principle of sustainability increasingly gains attention in the societal and academical discourse. This is reasoned by the partly harmful consumption and production patterns of the last century (Mcwilliams et al., 2016). Relating to sustainability, the advancing application of IoT technology also poses risks. Following the precautionary principle, these risks should be considered early (Harremoës et al., 2001). Risks of IoT for sustainability include the massive amounts of energy and raw materials which are required for the manufacturing and operation of IoT objects and furthermore, the disposal of those objects (Birkel et al., 2019). The exact relations in the context of IoT and sustainability are insufficiently explored to this point and do not constitute a central element within the discussion of this technology (Behrendt, 2019). Therefore, this thesis aims to develop a comprehensive overview of the relations between IoT and sustainability. To achieve this aim, this thesis utilises the methodology of Grounded Theory in combination with a comprehensive literature review. The analysed literature primarily consists of research contributions in the field of Information Technology (IT). Based on this literature, aspects, solution approaches, effects and challenges in the context of IoT and sustainability were elaborated. The analysis revealed two central perspectives in this context. IoT for Sustainability (IoT4Sus) describes the utilisation and usage of IoT-generated information to enhance sustainability aspects. In contrast, Sustainability for IoT (Sus4IoT) fo-cuses on sustainability aspects of the applied technology and highlights methods to reduce negative impacts, which are associated with the manufacturing and operation of IoT. Elaborated aspects and relations were illustrated in the comprehensive CCIS Framework. This framework represents a tool for the capturing of relevant aspects and relations in this context and thus supports the awareness of the link between IoT and sustainability. Furthermore, the framework suggests an action principle to optimise the performance of IoT systems regarding sustainability. The central contribution of this thesis is represented by the providence of the CCIS Framework and the contained information regarding the aspects and relations of IoT and sustainability.