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With the appearance of modern virtual reality (VR) headsets on the consumer market, there has been the biggest boom in the history of VR technology. Naturally, this was accompanied by an increasing focus on the problems of current VR hardware. Especially the control in VR has always been a complex topic.
One possible solution is the Leap Motion, a hand tracking device that was initially developed for desktop use, but with the last major software update it can be attached to standard VR headsets. This device allows very precise tracking of the user’s hands and fingers and their replication in the virtual world.
The aim of this work is to design virtual user interfaces that can be operated with the Leap Motion to provide a natural method of interaction between the user and the VR environment. After that, subject tests are performed to evaluate their performance and compare them to traditional VR controllers.
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.
To construct a business process model manually is a highly complex and error-prone task which takes a lot of time and deep insights into the organizational structure, its operations and business rules. To improve the output of business analysts dealing with this process, different techniques have been introduced by researchers to support them during construction with helpful recommendations. These supporting recommendation systems vary in their way of what to recommend in the first place as well as their calculations taking place under the hood to recommend the most fitting element to the user. After a broad introduction into the field of business process modeling and its basic recommendation structures, this work will take a closer look at diverse proposals and descriptions published in current literature regarding implementation strategies to effectively and efficiently assist modelers during their business process model creation. A critical analysis of presentations in the selected literature will point out strengths and weaknesses of their approaches, studies and descriptions of those. As a result, the final concept matrix in this work will give a precise and helpful overview about the key features and recommendation methods used and implemented in previous research studies to pinpoint an entry into future works without the downsides already spotted by fellow researchers.
Despite the inception of new technologies at a breakneck pace, many analytics projects fail mainly due to the use of incompatible development methodologies. As big data analytics projects are different from software development projects, the methodologies used in software development projects could not be applied in the same fashion to analytics projects. The traditional agile project management approaches to the projects do not consider the complexities involved in the analytics. In this thesis, the challenges involved in generalizing the application of agile methodologies will be evaluated, and some suitable agile frameworks which are more compatible with the analytics project will be explored and recommended. The standard practices and approaches which are currently applied in the industry for analytics projects will be discussed concerning enablers and success factors for agile adaption. In the end, after the comprehensive discussion and analysis of the problem and complexities, a framework will be recommended that copes best with the discussed challenges and complexities and is generally well suited for the most data-intensive analytics projects.
Unterschiedliche Quellen (Print-Medien, Fernsehberichte u. Ä.) berichten immer wieder davon, dass es mit der Datenschutzkompetenz bei Kindern und Jugendlichen schlecht bestellt ist. Daher ist dem Thema Datenschutz im Informatikunterricht eine besondere Bedeutung zuzuschreiben.
Im Rahmen der Dissertation von Herrn Hug wird ein Datenschutzkompetenzmodell [Quelle INFOS17] entwickelt, anhand dessen die Datenschutzkompetenz von Schülerinnen und Schülern im Altern von 10 bis 13 Jahren gemessen werden kann.
Im Rahmen dieser Masterarbeit werden existierende Unterrichtsmaterialien zum Thema Datenschutz gesammelt und dazu eine Unterrichtsreihe entwickelt. Hierbei werden auch eigene Zugänge aufzeigt, um ein kohärentes und abgeschlossenes Projekt zu entwerfen, bei dem aktuelle Gefahren für Schülerinnen und Schüler aufgezeigt werden. Ziel ist es, dass die Schülerinnen und Schüler dazu befähigt werden, ihr Verhalten bezüglich Datenschutz besser einzuschätzen und verantwortungsvoller mit ihren persönlichen Daten umzugehen. Im Rahmen eines Feldversuches in einer 6. Klasse eines Gymnasiums wurde die Unterrichtsreihe erprobt.
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.
A gonioreflectometer is a device to measure the reflection properties of arbitrary materials. In this work, such an apparatus is being built from easily obtainable parts. Therefore three stepper-motors and 809 light-emitting diodes are controlled by an Arduino microcontroller. RGB-images are captured with an industrial camera which serve as refelction data. Furthermore, a control software with several capture programs and a renderer for displaying the measured materials are implemented. These allow capturing and rendering entire bidirectional reflection distribution functions (BRDFs) by which also complex anisotropic material properties can be represented. Although the quality of the results has some artifacts due to shadows of the camera, these artifacts can be largely removed by using special algorithms like inpainting. In addition, the goniorefelctometer is applied to other use cases. One can perform 3D scans, light field capturing and light staging without altering the construction. The quality of these processes also meet the expectations in a positive way. Thus, the gonioreflectometer built in this work can be seen as a widely applicable and economical alternative to other publications.
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.
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.