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“Did I say something wrong?” A word-level analysis of Wikipedia articles for deletion discussions
(2016)
This thesis focuses on gaining linguistic insights into textual discussions on a word level. It was of special interest to distinguish messages that constructively contribute to a discussion from those that are detrimental to them. Thereby, we wanted to determine whether “I”- and “You”-messages are indicators for either of the two discussion styles. These messages are nowadays often used in guidelines for successful communication. Although their effects have been successfully evaluated multiple times, a large-scale analysis has never been conducted. Thus, we used Wikipedia Articles for Deletion (short: AfD) discussions together with the records of blocked users and developed a fully automated creation of an annotated data set. In this data set, messages were labelled either constructive or disruptive. We applied binary classifiers to the data to determine characteristic words for both discussion styles. Thereby, we also investigated whether function words like pronouns and conjunctions play an important role in distinguishing the two. We found that “You”-messages were a strong indicator for disruptive messages which matches their attributed effects on communication. However, we found “I”-messages to be indicative for disruptive messages as well which is contrary to their attributed effects. The importance of function words could neither be confirmed nor refuted. Other characteristic words for either communication style were not found. Yet, the results suggest that a different model might represent disruptive and constructive messages in textual discussions better.
This scientific paper deals with the question to which extend the increasing digitization has an impact on work-life balance. Answering this question is the main goal of this study.
To reach this goal a literature review is made, in which it is possible to create a direct correlation between the subjective feel of work-life balance and the perceived stress level. With the help of Antonovsky’s salutogenesis model (1997) from the stress research field, factors are ascertained which determine the perceived stress level and linked with that the perceived work-life balance. These stress-influencing factors are examined through a qualitative content analysis by Mayring (2014) on a base of a problem-centered interview.
The results suggest that the digitization has impact on all these ascertained factors and linked to them on the work-life balance. This shows, that the digitization influences us in almost every aspect of work or private life. Whether this impact is positive or negative towards the work life balance depends on the individual, that assesses this factor. Clear distinctions can be made between people working in an IT-based job and those that do not. In comparison, people with IT-based jobs perceive a substantial better impact of digitization on work-life balance.
Willingness to pay and willingness to accept on a two-sided platform - The use case of DoBeeDo
(2019)
It is widely known that especially for technology-based start-ups, entrepreneurs need to set up the boundaries of the business and define the product/service to offer in order to minimize the risk of failure. The goal of this thesis is to not only emphasize the importance of the business model development and evaluation but also show an example customer validation process for an emerging start-up named DoBeeDo, which is a mobile app operating on a two-sided market. During the process of customer validation a survey has been conducted to evaluate the interest of the target groups as well as the fit of their expectations using the Willingness to Pay and Willingness to Accept measures. The paper includes an analysis and evaluation of the gathered results and assesses whether the execution of the Customer Development Model can be continued.
Diese Arbeit soll das von Dietz und Oppermann entwickelte Planspiel „Datenschutz 2.0“ an den heutigen Alltag der Schüler anpassen, die Benutzung in der Sekundarstufe II ermöglichen und die technischen und gesetzlichen Problematiken des Planspiels beheben. Das mit dem Planspiel aufgegriffene Thema Datenschutz ist im rheinland-pfälzischen Informatik-Lehrplan für die Sekundarstufe II verankert. Hier wird der Begriff Datenschutz in der Reihe „Datenerhebung unter dem Aspekt Datenschutz beurteilen“ genannt. Jedoch werden in dem Planspiel keine Daten erhoben, sondern die selbst hinterlassenen Datenspuren untersucht. Diese Form des Datenschutzes ist im Grundkurs in der vorgeschlagenen Reihe „Datensicherheit unter der Berücksichtigung kryptologischer Verfahren erklären und beachten“ unter dem Thema Kommunikation in Rechnernetzen zu finden. Im Leistungskurs steht die Datensicherheit in gleichbenannter Reihe und Thema und in der Reihe „Datenerhebung unter dem Aspekt Datenschutz beurteilen“ im Thema Wechselwirkung zwischen Informatiksysteme, Individuum und Gesellschaft.
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.
Es wird ein Augmented-Reality Ansatz zur Erforschung modularer OSGi-Softwaresysteme präsentiert. Der Prototyp wird unter der Verwendung der Microsoft HoloLens implementiert. Module, wie Komponenten und Packages, werden in einer virtuellen Stadt dargestellt. Dieser Ansatz ermöglicht es dem Anwender, die Software-Architektur mittels intuitiver Navigation zu erkunden: Spracheingabe, Blickpunkt- und Gestenkontrolle. Eine multifunktionale Benutzeroberfläche wird vorgestellt, die für verschiedene Zielgruppen adaptiert werden kann. Viele veröffentlichte Visualisierungen weisen keine klare Zielgruppendefinition auf. Das Konzept kann leicht auf andere Darstellungsformen, wie beispielsweise der Inselmetapher übertragen werden. Erste Ergebnisse einer Evaluierung, die mittels kleiner strukturierter Interviews gewonnen werden konnten, werden präsentiert. Die Probanden mussten vier Programm-verständnis Aufgaben lösen und ihren Aufwand, sowie ihre Arbeitsbelastung einschätzen. Die Ergebnisse bilden eine gute Grundlage für weitere Forschung im Bereich der Software- Visualisierung in Augmented Reality.
Die vorliegende Arbeit beschäftigt sich mit der Betrachtung der Rolle von Vertrauen zwischen den Kapitalnehmern und Kapitalgebern auf einer der größten Crowdfunding-Plattformen, Kickstarter. Kernthema ist die Beantwortung der Forschungsfragen, wie das Vertrauen zwischen den Kapitalgebern und Kapitalnehmern im Kontext von Crowdfunding entsteht, welche Faktoren das Maß von Vertrauen in dieser Beziehung beeinflussen und welche Signale für die Vertrauensbildung verantwortlich sind. Das Ziel dieser Arbeit besteht darin, das von Zerwas, Kilian und von Kortzfleisch 2015 vorgestellte konzeptuelle Modell der Einflussfaktoren von Vertrauen im Kontext von Crowdfunding aus Sicht der Kapitalgeber zu überprüfen und gegebenenfalls zu erweitern.
Auf Grundlage einer Literaturrecherche und qualitativer, leitfadenorientierter Interviews werden die gesammelten Daten diskutiert, bestehende Faktoren verifiziert und weiterführend neue Faktoren und Signale identifiziert, die die Bildung von Vertrauen auf Crowdfunding-Plattformen beeinflussen.
Als Ergebnis werden die Überarbeitung sowie Erweiterung des Ausgangsmodells um die neuen Faktoren geographische Nähe, Vermittlerqualität und Verständnis vom Konzept Crowdfunding vorgeschlagen. Anhand der Häufigkeit der Erwähnung und Relevanz der Faktoren und beeinflussenden Signale in den durchgeführten Interviews wird weiterführend eine Gewichtung der Einzelfaktoren vorgenommen. Abschließend werden Implikationen und Bedeutung für Wissenschaft und Forschung diskutiert.
Remote rendering services offer the possibility to stream high quality images to lower powered devices. Due to the transmission of data the interactivity of applications is afflicted with a delay. A method to reduce delay of the camera manipulation on the client is called 3d-warping. This method causes artifacts. In this thesis different approaches of remote rendering setups will be shown. The artifacts and improvements of the warping method will be described. Methods to reduce the artifacts will be implemented and analyzed.
This master thesis is about the possibilities of supporting local corporate sales with the help of current mobile applications. The internet already has served in order to make the trading market more dynamic. The conditions for long-term local corporate sales have become more challenging. Because of smaller cost structures online-retailer offer prizes on which local point of sales can hardly keep up with. Another point is that more customers decide to order online because the service in e-shops enhanced; therefore, the digital transactions become more attractive for consumers. Today smartphones and tablets have brought the digitalization to a whole new level. With the possibility of Mobile Web the effects that the internet already showed us in the past have been intensified. The question that proposes here is: In which way do the conditions of competitions for local corporate sales change? This paper follows the outline of putting together various mobile services, their functions, and their practical usage, as well as the process of integrating them successfully into marketing. With that one should be able to find out if Mobile Web can be seen as an advantage for local corporates sales.
Tractography on HARDI data
(2011)
Diffusion weighted imaging is an important modality in clinical imaging and the only possibility to gain insight into the human brain noninvasively and in-vivo. The applications of this imaging technique are diversified. It is used to study the brain, its structure, development and the functionality of the different areas. Further, important fields of application are neurosurgical planning, examinations of pathologies, investigation of Alzheimer-, strokes, and multiple sclerosis. This thesis gives a brief introduction to MRI and diffusion MRI. Based on this, the mostly used data representation in diffusion MRI in clinical imaging, the diffusion tensor, is introduced. As the diffusion tensor suffers from severe limitations new techniques subsumed under the term HARDI (high angular resolution diffusion imaging) are introduced and discussed in detail. Further, an extensive introduction to tractography, approaches that aim at reconstructing neuronal fibers, is given. Based on the knowledge fromthe theoretical part established tractography algorithms are redesigned to handle HARDI data and, thus, improve the reconstruction of neuronal fibers. Among these algorithms, a novel approach is presented that successfully reconstructs fibers on phantom data as well as on human brain data. Further, a novel global classification approach is presented to cluster voxels according to their diffusion properties.
Topic models are a popular tool to extract concepts of large text corpora. These text corpora tend to contain hidden meta groups. The size relation of these groups is frequently imbalanced. Their presence is often ignored when applying a topic model. Therefore, this thesis explores the influence of such imbalanced corpora on topic models.
The influence is tested by training LDA on samples with varying size relations. The samples are generated from data sets containing a large group differences i.e language difference and small group differences i.e. political orientation. The predictive performance on those imbalanced corpora is judged using perplexity.
The experiments show that the presence of groups in training corpora can influence the prediction performance of LDA. The impact varies due to various factors, including language-specific perplexity scores. The group-related prediction performance changes for groups when varying the relative group sizes. The actual change varies between data sets.
LDA is able to distinguish between different latent groups in document corpora if differences between groups are large enough, e.g. for groups with different languages. The proportion of group-specific topics is under-proportional to the share of the group in the corpus and relatively smaller for minorities.
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.
Im Bereich Augmented Reality ist es von großer Bedeutung, dass virtuelle
Objekte möglichst realistisch in ein Kamerabild eingebettet werden. Nur
so ist es möglich, dem Nutzer eine immersive Erfahrung zu bieten. Dazu
gehört unter anderem, Verdeckung dieser Objekte korrekt zu behandeln.
Während schon verschiedene Ansätze existieren, dieses Verdeckungsproblem
zu beheben, wird in dieser Arbeit eine Lösung mittels Natural Image
Matting vorgestellt. Mit Hilfe einer Tiefenkamera wird das Kamerabild in
Vorder- und Hintergrund aufgeteilt und anschließend das virtuelle Objekt
im Bild platziert. Für Bereiche, in denen die Zugehörigkeit zu Vorder- oder
Hintergrund nicht eindeutig ist, wird anhand bekannter Pixel ein Transparenz-
Wert geschätzt. Es werden Methoden präsentiert, welche einen
Ablauf des Image Matting in Echtzeit ermöglichen. Zudem werden
Verbesserungsmöglichkeiten dieser Methoden präsentiert und gezeigt, dass
durch diese eine höhere Bildqualität für schwierige Szenen erreicht wird.
Digital transformation is a prevailing trend in the world, especially in dynamic Asia. Vietnam has recorded remarkable changes in the economy as domestic enterprises have made new strides in the digital transformation process. MB Bank, one of the prestigious financial groups in Vietnam, also takes advantage of digital transformation to have the opportunity to break through to become a large-scale technology enterprise with many factors such as improving customer experience, increasing customer base and increasing customer satisfaction. enhance competitiveness, build trust and loyalty for customers. However, in the process of converting MB, there are also many challenges that require banks to have appropriate policies to handle. It can be said that MB Bank is a typical case study of digital transformation in the banking sector in Vietnam.
Tracking is an integral part of many modern applications, especially in areas like autonomous systems and Augmented Reality. For performing tracking there are a wide array of approaches. One that has become a subject of research just recently is the utilization of Neural Networks. In the scope of this master thesis an application will be developed which uses such a Neural Network for the tracking process. This also requires the creation of training data as well as the creation and training of a Neural Network. Subsequently the usage of Neural Networks for tracking will be analyzed and evaluated. This includes several aspects. The quality of the tracking for different degrees of freedom will be checked as well as the the impact of the Neural Network on the applications performance. Additionally the amount of required training data is investigated, the influence of the network architecture and the importance of providing depth data as part of the networks input. This should provide an insight into how relevant this approach could be for its adoption in future products.
Data visualization is an effective way to explore data. It helps people to get a valuable insight of the data by placing it in a visual context. However, choosing a good chart without prior knowledge in the area is not a trivial job. Users have to manually explore all possible visualizations and decide upon ones that reflect relevant and desired trend in the data, are insightful and easy to decode, have a clear focus and appealing appearance. To address these challenges we developed a Tool for Automatic Generation of Good viSualizations using Scoring (TAG²S²). The approach tackles the problem of identifying an appropriate metric for judging visualizations as good or bad. It consists of two modules: visualization detection: given a data-set it creates a list of combination of data attributes for scoring and visualization ranking: scores each chart and decides which ones are good or bad. For the later, an utility metric of ten criteria was developed and each visualization detected in the first module is evaluated on these criteria. Only those visualizations that received enough scores are then presented to the user. Additionally to these data parameters, the tool considers user perception regarding the choice of visual encoding when selecting a visualization. To evaluate the utility of the metric and the importance of each criteria, test cases were developed, executed and the results presented.
Mit dieser Arbeit werden die folgenden Ziele verfolgt: Eine repräsentative Auswahl und Sammlung von Beispielen für Mobile Ticketing Systeme (insbesondere aus dem deutschsprachigen Raum) zu recherchieren, die sich im praktischen Einsatz befinden. Eine Zusammenstellung sinnvoller Kategorien (Charakteristika) zu erarbeiten, anhand derer sich Mobile Ticketing Systeme unterscheiden oder strukturieren lassen. Eine Gegenüberstellung der Beispiele und Kategorien zu erstellen, um zu untersuchen, welche typischen Klassen bei Mobile Ticketing Systemen identifiziert werden können.
The status of Business Process Management (BPM) recommender systems is not quite clear as research states. The use of recommenders familiarized itself with the world during the rise of technological evolution in the past decade.Ever since then, several BPM recommender systems came about. However, not a lot of research is conducted in this field. It is not well known to what broad are the technologies used and how are they used. Moreover, this master’s thesis aims at surveying the BPM recommender systems existing. Building on this, the recommendations come in different shapes. They can be positionbased where an element is to be placed at an element’s front, back or to autocomplete a missing link. On the other hand, Recommendations can be textual, to fill the labels of the elements. Furthermore, the literature review for BPM recommender systems took place under the guides of a literature review framework. The framework suggests 5stages of consecutive stages for this sake. The first stage is defining a scope for the research. Secondly, conceptualizing the topic by choosing key terms for literature research. After that in the third stage, comes the research stage.As for the fourth stage, it suggests choosing analysis features over which the literature is to be synthesized and compared. Finally, it recommends defining the research agenda to describe the reason for the literature review. By invoking the mentioned methodology, this master’s thesis surveyed 18 BPM recommender systems. It was found as a result of the survey that there
are not many different technologies for implementing the recommenders. It was also found that the majority of the recommenders suggest nodes that are yet to come in the model, which is called forward recommending. Also, one of the results of the survey indicated the scarce use of textual recommendations to BPM labels. Finally, 18 recommenders are considered less than excepted for a developing field therefore as a result, the survey found a shortage in the number of BPM recommender systems. The results indicate several shortages in several aspects in the field of BPM recommender systems. On this basis, this master’s thesis recommends the future work on it the results.