Fachbereich 4
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The lack of a formal event model hinders interoperability in distributed event-based systems. Consequently, we present in this paper a formal model of events, called F. The model bases on an upper-level ontology and pro-vides comprehensive support for all aspects of events such as time and space, objects and persons involved, as well as the structural aspects, namely mereological, causal, and correlational relationships. The event model provides a flexible means for event composition, modeling of event causality and correlation, and allows for representing different interpretations of the same event. The foundational event model F is developed in a pattern-oriented approach, modularized in different ontologies, and can be easily extended by domain specifific ontologies.
This paper describes a parallel algorithm for selecting activation functionsrnof an artifcial network. For checking the efficiency of this algorithm a count of multiplicative and additive operations is used.
In this article we analyze the privacy aspects of a mobile sensor application used for recording urban travel patterns as part of a travel-survey service. This service has been developed and field-tested within the Live+Gov EU Project. The privacy analysis follows a structured approach established in. Eight privacy recommendations are derived, and have already led to corresponding enhancements of the travel-survey service.
So genannte Risikomanagement-Informationssysteme (RMIS) unterstützen Unternehmen darin, ihr Risiko-Management unternehmensweit durchzuführen. Im vorliegenden Beitrag analysieren wir mit Hilfe der Scoring-Methode die inhaltlichen Anforderungen an ein RMIS und zeigen, wie das zu einer begründeten Auswahl für die Anschaffung eines RMIS führt. Dazu diskutieren wir erstens, welche Anforderungen an ein RMIS gestellt werden, zweitens klassifizieren wir die auf dem Markt existierenden RMIS bezüglich ihrer Anwendungsziele und drittens erstellen wir einen Anforderungskatalog und ein dreistufiges Verfahren zur Handhabung des Auswahlprozesses. Dieses wird im Rahmen einer erfolgreich durchgeführten Fallstudie im Rahmen einer Masterarbeit [11] in einem konkreten Konzern, der Telekommunikations- und Internetzugang anbietet (United Internet AG, Montabaur), erläutert und evaluiert. 1.
Usability experts conduct user studies to identify existing usability problems. An established method is to record gaze behavior with an eye-tracker. These studies require a lot of effort to evaluate the results. Automated recognition of good and bad usability in recorded user data can support usability experts in eye tracking evaluation and reduce the effort. The objective of that bachelor thesis is to identify suitable eye-tracking metrics that correlate with the quality of usability. For this purpose, the central research question is answered: Which eye-tracking metrics correlate with the quality of a web form’s operation? To answer the research question, a quantitative A/B-user-study with eye-tracking was conducted and recorded the
gaze behavior of 30 subjects while filling out the web form. The web form was designed, that each web form page was available as a good and bad variant according to known usability guidelines. The results confirm a significant correlation between the eye-tracking-metric "number of visits to an
AOI" and the quality of the operation of a web form. The eye-tracking-metrics
"number of fixations within an AOI" and "duration of fixations within an AOI" also correlate with the quality of usability. No correlation could be confirmed for the "time of the first fixation within an AOI".
Avoidance of routing loops
(2009)
We introduce a new routing algorithm which can detect routing loops by evaluating routing updates more thoroughly. Our new algorithm is called Routing with Metric based Topology Investigation (RMTI), which is based on the simple Routing Information Protocol (RIP) and is compatible to all RIP versions. In case of a link failure, a network can reorganize itself if there are redundant links available. Redundant links are only available in a network system like the internet if the topology contains loops. Therefore, it is necessary to recognize and to prevent routing loops. A routing loop can be seen as a circular trace of a routing update information which returns to the same router, either directly from the neighbor router or via a loop topology. Routing loops could consume a large amount of network bandwidth and could impact the endtoend performance of the network. Our RMTI approach is capable to improve the efficiency of Distance Vector Routing.
Digital happiness
(2016)
Emotions in the digital world gain more and more importance by the accelerating digitalization of recent years. In everyday life as well as professional and educational environments, the use of media is almost inescapable. This work takes a closer look to the still relatively unknown topic, “Digital Happiness“. In the literature emotions in the digital world are studied increasingly, but concerning the topic of “Digital Happiness” there are not many insights.
In this research the differences between communicating emotions through digital media and face-to-face communications, as well as their impacts, are investigated. The perception and expression of emotions in the real and digital world are considered. Furthermore, a first definition of “Digital Happiness” and a model with the associated determinants that influence “Digital Happiness” is developed.
To achieve these goals, a literature analysis by the method of Webster & Watson (2002) is performed. Therefore, 15 articles are selected and analyzed in more detail to illustrate the current state of research. These articles are organized into a concept matrix. In addition, special phenomena, such as Quantified Self, are closely considered in order to determine other factors. Based on the literature analysis, a qualitative study by the method of Mayring (2014) is performed. It is developed into an interview guideline that serves as the basis for the investigation of the established determinants of the literature analysis. This is confirmed or refuted by 30 interviews with users of information and communication technologies. With the help of the interviews, a large part of the determinants in the literature can be confirmed. Moreover, some new determinants are identified. These results are included into the final model. This model provides a basis for further research in the field of “Digital Happiness“. Finally, different implications for research and practice are found, which reveal the need of further research.
Semantic desktop environments aim at improving the effectiveness and efficiency of users carrying out daily tasks within their personal information management infrastructure (PIM). They support the user by transferring and exploiting the explicit semantics of data items across different PIM applications. Whether such an approach does indeed reach its aim of facilitating users" life and—if so—to which extent, however, remains an open question that we address in this paper with the first summative evaluation of a semantic desktop approach. We approach the research question exploiting our own semantic desktop infrastructure, X-COSIM. As data corpus, we have used over 100 emails and 50 documents extracted from the organizers of a conference-like event at our university. The evaluation has been carried out with 18 subjects. We have developed a test environment to evaluate COSIMail and COSIFile, two semantic PIM applications based on X-COSIM. As result, we have found a significant improvement for typical PIM tasks compared to a standard desktop environment.
Social networks are ubiquitous structures that we generate and enrich every-day while connecting with people through social media platforms, emails, and any other type of interaction. While these structures are intangible to us, they carry important information. For instance, the political leaning of our friends can be a proxy to identify our own political preferences. Similarly, the credit score of our friends can be decisive in the approval or rejection of our own loans. This explanatory power is being leveraged in public policy, business decision-making and scientific research because it helps machine learning techniques to make accurate predictions. However, these generalizations often benefit the majority of people who shape the general structure of the network, and put in disadvantage under-represented groups by limiting their resources and opportunities. Therefore it is crucial to first understand how social networks form to then verify to what extent their mechanisms of edge formation contribute to reinforce social inequalities in machine learning algorithms.
To this end, in the first part of this thesis, I propose HopRank and Janus two methods to characterize the mechanisms of edge formation in real-world undirected social networks. HopRank is a model of information foraging on networks. Its key component is a biased random walker based on transition probabilities between k-hop neighborhoods. Janus is a Bayesian framework that allows to identify and rank plausible hypotheses of edge formation in cases where nodes possess additional information. In the second part of this thesis, I investigate the implications of these mechanisms - that explain edge formation in social networks - on machine learning. Specifically, I study the influence of homophily, preferential attachment, edge density, fraction of inorities, and the directionality of links on both performance and bias of collective classification, and on the visibility of minorities in top-k ranks. My findings demonstrate a strong correlation between network structure and machine learning outcomes. This suggests that systematic discrimination against certain people can be: (i) anticipated by the type of network, and (ii) mitigated by connecting strategically in the network.