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Most social media platforms allow users to freely express their opinions, feelings, and beliefs. However, in recent years the growing propagation of hate speech, offensive language, racism and sexism on the social media outlets have drawn attention from individuals, companies, and researchers. Today, sexism both online and offline with different forms, including blatant, covert, and subtle lan- guage, is a common phenomenon in society. A notable amount of work has been done over identifying sexist content and computationally detecting sexism which exists online. Although previous efforts have mostly used peoples’ activities on social media platforms such as Twitter as a public and helpful source for collecting data, they neglect the fact that the method of gathering sexist tweets could be biased towards the initial search terms. Moreover, some forms of sexism could be missed since some tweets which contain offensive language could be misclassified as hate speech. Further, in existing hate speech corpora, sexist tweets mostly express hostile sexism, and to some degree, the other forms of sexism which also appear online was disregarded. Besides, the creation of labeled datasets with manual exertion, relying on users to report offensive comments with a tremendous effort by human annotators is not only a costly and time-consuming process, but it also raises the risk of involving discrimination under biased judgment.
This thesis generates a novel sexist and non-sexist dataset which is constructed via "UnSexistifyIt", an online web-based game that incentivizes the players to make minimal modifications to a sexist statement with the goal of turning it into a non-sexist statement and convincing other players that the modified statement is non-sexist. The game applies the methodology of "Game With A Purpose" to generate data as a side-effect of playing the game and also employs the gamification and crowdsourcing techniques to enhance non-game contexts. When voluntary participants play the game, they help to produce non-sexist statements which can reduce the cost of generating new corpus. This work explores how diverse individual beliefs concerning sexism are. Further, the result of this work highlights the impact of various linguistic features and content attributes regarding sexist language detection. Finally, this thesis could help to expand our understanding regarding the syntactic and semantic structure of sexist and non-sexist content and also provides insights to build a probabilistic classifier for single sentences into sexist or non-sexist classes and lastly find a potential ground truth for such a classifier.
Knowledge-based authentication methods are vulnerable to Shoulder surfing phenomenon.
The widespread usage of these methods and not addressing the limitations it has could result in the user’s information to be compromised. User authentication method ought to be effortless to use and efficient, nevertheless secure.
The problem that we face concerning the security of PIN (Personal Identification Number) or password entry is shoulder surfing, in which a direct or indirect malicious observer could identify the user sensitive information. To tackle this issue we present TouchGaze which combines gaze signals and touch capabilities, as an input method for entering user’s credentials. Gaze signals will be primarily used to enhance targeting and touch for selecting. In this work, we have designed three different PIN entry method which they all have similar interfaces. For the evaluation, these methods were compared based on efficiency, accuracy, and usability. The results uncovered that despite the fact that gaze-based methods require extra time for the user to get familiar with yet it is considered more secure. In regards to efficiency, it has the similar error margin to the traditional PIN entry methods.
Wir analysieren versionsbasierte Softwareprojekte, um den Entwicklern API- und Domänen-Wissen zuzuordnen. Genauer gesagt analysieren wir die einzelnen Commits in einem Repository in Hinblick auf die API-Nutzung. Auf dieser Grundlage können wir APIs (oder Teile davon) den Entwicklern zuordnen und dadurch auf die API-Erfahrung der Entwickler schließen. Im transitiven Schluss können wir auf Domänen-Erfahrung schließen, da jeder API eine Programmierdomäne zugewiesen wird.
Predictive Process Monitoring setzt sich als Hilfsmittel zur Unterstützung der betrieblichen Abläufe in Unternehmen immer mehr durch Die meisten heute verfüg-baren Softwareanwendungen erfordern jedoch ein umfangreiches technisches Know-how des Betreibers und sind daher für die meisten realen Szenarien nicht geeignet. Daher wird in dieser Arbeit eine prototypische Implementierung eines Predictive Process Monitoring Dashboards in Form einer Webanwendung vorgestellt. Das System basiert auf dem von Bartmann et al. (2021) vorgestellten PPM-Camunda-Plugin und ermöglicht es dem Benutzer, auf einfache Weise Metriken, Visualisierungen zur Darstellung dieser Metriken und Dashboards, in denen die Visualisierungen angeordnet werden können, zu erstellen. Ein Usability-Test mit Testnutzern mit unterschiedlichen Computerkenntnissen wird durchgeführt, um die Benutzerfreundlichkeit der Anwendung zu bestätigen.
Öffentliche elektronische Beschaffung (eProcurement), bzw. strategischer elektronischer Einkauf (eSourcing), sind mit hoher Wahrscheinlichkeit Thema sobald eGovernment Experten aufeinander treffen. So ist es nicht überraschend, dass eProcurement im aktuellen Aktionsplan der EU als "high-impact service" eingestuft wurde. Dies lässt sich zum Großteil durch den großen Einfluss vom öffentlichen Einkauf auf die Staatskasse erklären. So macht eProcurement in der Regel bis zu 20% des BIP aus und beherbergt somit ein enormes Einsparpotenzial. Dieses Potenzial liegt zum Teil im gemeinsamen Europäischen Wirtschaftsraum, da effizientes länderübergreifendes eSourcing neue Möglichkeiten für Einkäufer sowie Lieferanten eröffnen kann. Um diese Möglichkeiten ausschöpfen zu können, müssen Prozesse und Tools in der Lage sein, miteinander zu kommunizieren, sich aufeinander abzustimmen oder transferierbar sein. In einem Wort, sie müssen interoperabel sein. In vielen wichtigen Bereichen ist Interoperabilität sehr weit fortgeschritten, in anderen hingegen muss noch viel verändert werden. Daher ist es von wesentlicher Bedeutung Interoperabilitätsanforderungen zu definieren, sowie den aktuellen Forschungs- und Entwicklungsstand zu evaluieren.
This thesis explores the possibilities of probabilistic process modelling for the Computer Supported Cooperative Work (CSCW) systems in order to predict the behaviour of the users present in the CSCW system. Toward this objective applicability, advantages, limitations and challenges of probabilistic modelling are excavated in context of CSCW systems. Finally, as a primary goal seven models are created and examined to show the feasibilities of probabilistic process discovery and predictions of the users behaviour in CSCW systems.
Implementation of Agile Software Development Methodology in a Company – Why? Challenges? Benefits?
(2019)
The software development industry is enhancing day by day. The introduction of agile software development methodologies was a tremendous structural change in companies. Agile transformation provides unlimited opportunities and benefits to the existing and new developing companies. Along with benefits, agile conversion also brings many unseen challenges. New entrants have the advantage of being flexible and cope with the environmental, consumer, and cultural changes, but existing companies are bound to rigid structure.
The goal of this research is to have deep insight into agile software development methodology, agile manifesto, and principles behind the agile manifesto. The prerequisites company must know for agile software development implementation. The benefits a company can achieve by implementing agile software development. Significant challenges that a company can face during agile implementation in a company.
The research objectives of this study help to generate strong motivational research questions. These research questions cover the cultural aspects of company agility, values and principles of agile, benefits, and challenges of agile implementation. The project management triangle will show how benefits of cost, benefits of time, and benefits of quality can be achieved by implementing agile methodologies. Six significant areas have been explored, which shows different challenges a company can face during implementation agile software development methodology. In the end, after the in depth systematic literature review, conclusion is made following some open topics for future work and recommendations on the topic of implementation of agile software development methodology in a company.
Das Ziel dieser Masterarbeit war es ein CRM System für das Assist Team der CompuGroup Medical zu entwickeln, welches Open Innovation in die Entwicklung der Minerva 2.0 Software integriert. Um dies zu erreichen wurden CRM Methoden mit Social Networ- king Systemen kombiniert, basierend auf der Forschung von Lin und Chen (2010, S. 11 – 30). Um die definierten Ziele zu erreichen wurde Literatur analysiert, wie ein CRM System und eine Online Community erfolgreich implementiert werden können und dies auf die Entwicklung der Minerva Community angewendet. Dabei wurde sich an den Design Science Richtlinien von Hevner u. a. (2004, S. 75 – 104) orientiert. Das fertige Produkt wurde basierend auf Kunden- und Managementanforderungen entworfen und wurde an- schließend aus Kunden- und Firmenperspektive evaluiert.
In scientific data visualization huge amounts of data are generated, which implies the task of analyzing these in an efficient way. This includes the reliable detection of important parts and a low expenditure of time and effort. This is especially important for the big-sized seismic volume datasets, that are required for the exploration of oil and gas deposits. Since the generated data is complex and a manual analysis is very time-intensive, a semi-automatic approach could on one hand reduce the time required for the analysis and on the other hand offer more flexibility, than a fully automatic approach.
This master's thesis introduces an algorithm, which is capable of locating regions of interest in seismic volume data automatically by detecting anomalies in local histograms. Furthermore the results are visualized and a variety of tools for the exploration and interpretation of the detected regions are developed. The approach is evaluated by experiments with synthetic data and in interviews with domain experts on the basis of real-world data. Conclusively further improvements to integrate the algorithm into the seismic interpretation workflow are suggested.