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Mit dem Erscheinen moderner Virtual Reality (VR) Headsets auf dem Verbrauchermarkt, gab es den bisher größten Aufschwung in der Geschichte der VR Technologie. Damit einhergehend rücken aber auch die Problematiken aktueller VR Hardware immer mehr in den Vordergrund. Insbesondere die Steuerung in VR war schon immer ein komplexes Thema.
Eine mögliche Lösung bietet die Leap Motion: Ein Hand-Tracking Gerät, welches ursprünglich für den Desktop-Einsatz entwickelt wurde, aber mit dem letzten größeren Softwareupdate an üblichen VR Headsets angebracht werden kann. Dieses Gerät ermöglicht ein sehr genaues Tracking beider Hände und aller Finger. Damit ist es möglich, diese vollständig in der VR Welt zu replizieren und zur Steuerung zu verwenden.
Ziel dieser Arbeit ist es, virtuelle Benutzeroberflächen zu entwerfen, die mit der Leap Motion bedient werden können. Dies soll eine natürliche Interaktion zwischen dem Benutzer und der VR-Umgebung ermöglichen. Danach werden mit Hilfe einer Demoanwendung Probanden-Tests durchgeführt, um ihre Leistung zu bewerten und mit herkömmlichen VR-Reglern zu vergleichen.
The Internet of Things is still one of the most relevant topics in the field of economics and research powered by the increasing demand of innovative services. Cost reductions in manufacturing of IoT hardware and the development of completely new communication ways has led to the point of bil-lions of devices connected to the internet. But in order to rule this new IoT landscape a standardized solution to conquer these challenges must be developed, the IoT Architecture.
This thesis examines the structure, purpose and requirements of IoT Architecture Models in the global IoT landscape and proposes an overview across the selected ones. For that purpose, a struc-tured literature analysis on this topic is conducted within this thesis, including an analysis on three existing research approaches trying to frame this topic and a tool supported evaluation of IoT Archi-tecture literature with over 200 accessed documents.
Furthermore, a coding of literature with the help of the specialised coding tool ATLAS.ti 8 is conduct-ed on 30 different IoT Architecture Models. In a final step these Architecture Models are categorized and compared to each other showing that the environment of IoT and its Architectures gets even more complex the further the research goes.
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.
In einem Großteil der Welt wird Grundwasser für die Versorgung von Siedlungen und Agrarflächen genutzt. Organismen, die im Grundwasser leben, erfüllen wichtige Funktionen im Ökosystem und haben positiven Einfluss auf die Grundwasserqualität. Um das Risiko negativer Effekte auf diese wertvollen Ökosysteme zu minimieren muss die entsprechende Sanierungsmethode, im Falle einer Grundwasserbehandlung, mit Vorsicht gewählt werden. In der vorliegenden Thesis wurde das Umweltrisiko von Carbo-Iron untersucht, ein Komposit aus nanoskaligem null-valentem Eisen und Aktivkohle zur in situ-Behandlung von Grundwasser. Des Weiteren wurde eine umfassende Beurteilung des Umweltrisikos und des Nutzens einer Grundwasserbehandlung mit Carbo-Iron durchgeführt.
Zu Beginn der Arbeit an der vorliegenden Thesis existierten noch keine Empfehlungen für Untersuchung der Ökotoxizität von Nanomaterialien. Daher bestanden viele Unsicherheiten hinsichtlich geeigneter Methoden. Im Rahmen dieser Thesis wurde eine Entscheidungshilfe entwickelt, um bei der ökotoxikologischen Untersuchung von Nanomaterialien systematisch geeignete methodische Schritte auszuwählen.
Mögliche Effekte von Carbo-Iron wurden in Tests mit embryonalen, juvenilen und adulten Lebensstadien des Zebrabärblings (Danio rerio) und juvenilen und adulten Amphipoden (Hyalella azteca) untersucht. Die gewählten Testsysteme basierten auf existierenden Testmethoden der OECD und EPA zur ökotoxikologischen Untersuchung von Chemikalien (OECD, 1992a, 2013a, 2013b; US EPA, 2000). Zusätzlich wurde die Aufnahme der Partikel in die genannten Testorganismen untersucht. In Zebrabärblingsembryonen wurden außerdem potentielle Effekte auf die Genexpression mittels Microarrays ermittelt. Die erhaltenen Daten wurden später mit Ergebnissen aus Tests mit dem Wasserfloh Daphnia magna, der Alge Scenedesmus vacuolatus, Larven der Mücke Chironomus riparius und nitrifizierenden Bodenmikroorganismen ergänzt.
In dem Fischembryotoxizitätstest wurde keine Passage der Carbo-Iron-Partikel durch das Chorion in den perivitellinen Raum oder den Embryo beobachtet. Nach der Exposition wurde Carbo-Iron im Darm von H. azteca und D. rerio, aber keinem anderen Gewebe oder Organen detektiert. Carbo-Iron hatte keine signifikanten Effekte auf die Nitrifikationsrate der Bodenmikroorganismen sowie Überleben und Wachstum des Zebrabärblings. Dennoch wurden signifikant negative Effekte auf Wachstum, Fütterungsrate und Reproduktion von H. azteca und auf das Überleben und die Reproduktion von D. magna festgestellt. Des Weiteren war die Entwicklungsrate von C. riparius und das Zellvolumen von S. vacuolatus negativ beeinflusst.
Anhand der durchgeführten Studien wurde basierend auf dem Ergebnis des Reproduktionstests mit D. magna und einem assessment factor von 10 für Carbo-Iron eine predicted no effect concentration von 0,1 mg/L ermittelt. Diese wurde mit modellierten und gemessenen Umweltkonzentrationen von Carbo-Iron verglichen die in einer Studie erhoben wurden, in denen Carbo-Iron zur Behandlung eines mit Chlorkohlenwasserstoffen kontaminierten Aquifers eingesetzt wurde, und Risiko-Quotienten wurden abgeleitet. Zur gesamtheitlichen Betrachtung wurde anschließend ein Schema zur Bewertung des Umweltrisikos vor und nach der Behandlung des Aquifers mit Carbo-Iron entwickelt. Die erhobenen Daten weisen auf ein reduziertes Umweltrisiko nach der Applikation von Carbo-Iron hin. Dementsprechend überwiegen die Vorteile einer Grundwasserbehandlung mit Carbo-Iron die potentiellen negativen Effekte auf die Umwelt.
Eine genaue Schneesimulation ist der Schlüssel zur Erfassung der charakteristischen Visualisierung von Schnee. Aufwendige Methoden existieren, die versuchen Schneeverhalten ganzheitlich zu ergreifen. Die Rechenkomplexität dieser Ansätze hindert sie daran, Echtzeitfähigkeit zu erreichen. Diese Arbeit stellt drei Methoden vor, die unter Verwendung der GPU eine echtzeitfähige Deformation einer Schneeoberoberfläche darstellen. Die Ansätze werden hinsichtlich ihrer wahrheitsgetreuen Schneedarstellung untersucht und nach ihrer Fähigkeit, mit einer zunehmenden Anzahl von schneeverformenden Objekten zu skalieren. Die Ergebnisse zeigen, dass die Methoden bei mehreren hunderten schneeverformenden Objekten ihre Echtzeitfähigkeit beibehalten. Jedoch benachteiligen die charakteristischen Einschränkungen jener Methoden die visuellen Resultate. Ein experimenteller Ansatz ist es, die Anzahl der schneeverformenden Objekte zu reduzieren und durch Zusammenfügen der Methoden ein genaueres, kombiniertes Verformungsmuster zu erzeugen.
While the existing literature on cooperative R&D projects between firms and public research institutes (PRI) has made valuable contributions by examining various factors and their influence on different outcome measures, there has been no investigation of cooperative R&D project success between firms and PRI from a product competitive advantage perspective. However, insights into the development of a meaningful and superior product (i.e., product competitive advantage) are particularly important in the context of cooperative R&D projects between PRI and (mainly small and medium-sized) firms in the biotechnology industry in response to increasing competition to raise capital funds necessary for survival.
The objectives of this thesis are: (1) to elaborate the theoretical foundations which explain the achievement of a product competitive advantage in cooperative R&D projects between biotechnology firms and PRI, (2) to identify and empirically evaluate the determining factors for achieving a product competitive advantage in cooperative R&D projects between biotechnology firms and PRI, and (3) to show how cooperative R&D projects between biotechnology firms and PRI should be designed and executed to support the achievement of a product competitive advantage.
To accomplish these objectives, a model of determinants of product competitive advantage in cooperative R&D projects between biotechnology firms and PRI is developed by drawing from the theoretical foundations of resource-based theory and information-processing theory. The model is evaluated using data from 517 questionnaires on cooperative R&D projects between at least one biotechnology firm and one PRI. The data are analyzed using variance-based structural equation modeling (i.e., PLS-SEM) in order to conduct hypotheses testing. The evaluation of the empirical data includes an additional mediation analysis and the comparison of effects in subsamples.
The results demonstrate the importance of available resources and skills, as well as the proficient execution of marketing-related and technical activities for the achievement of a product competitive advantage in cooperative R&D projects between biotechnology firms and PRI. By identifying project-related and process-related factors affecting product competitive advantage and empirically testing their relationships, the research findings should be valuable for both researchers and practitioners. After discussing contributions and implications for research and practice, the present thesis concludes with limitations and avenues for future research.
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.
Student misbehavior and its treatment is a major challenge for teachers and a threat to their well-being. Indeed, teachers are obliged to punish student misbehavior on a regular basis. Additionally, teachers’ punishment decisions are among the most frequently reported situations when it comes to students’ experiences of injustice in school. By implication, it is crucial to understand teachers’ treatment of student misbehavior vis-à-vis students’ perceptions. One key dimension of punishment behavior reflects its underlying motivation and goals. People generally intend to achieve three goals when punishing misbehavior, namely, retribution (i.e., evening out the harm caused), special prevention (i.e., preventing recidivism of the offender), and general prevention (i.e., preventing imitation of others). Importantly, people’s support of these punishment goals is subject to hierarchy and power, implying that teachers’ and students’ punishment goal preferences differ. In this dissertation, I present three research projects that shed first light on teachers’ punishment and its goals along with the students’ perception of classroom intervention strategies pursuing these goals. More specifically, I first examined students’ (i.e., children’s) general support of each of the three punishment goals sketched above. Furthermore, I applied an attributional approach to understand and study the goals teachers intend to achieve when punishing student misbehavior. Finally, I investigated teachers’ and students’ support of the punishment goals regarding the same student misbehavior to directly compare their views on these goals and reactions pursuing them. In sum, the findings show that students generally prefer retribution and special prevention to general prevention, whereas teachers prefer general prevention and special prevention to retribution. This ultimately translates into a "mismatch" of teachers and students in their preferences for specific punishment goals, and the findings suggest that this may indeed enhance students’ perception of injustice. Overall, the results of the present research program may be valuable for the development of classroom intervention strategies that may reduce rather than enhance conflicts in student-teacher-interactions.
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.
Abstract
This bachelor thesis delivers a comprehensive overview of the topic Internet of Things (IoT). With the help of a first literature review, important characteristics, architectures, and properties have been identified. The main aim of this bachelor thesis is to determine whether the use of IoT in the transport of food, considering the compliance with the cold chain, can provide advantages for companies to reduce food waste. For this purpose, a second literature review has been carried out with food transport systems without the use, as well as with the use of IoT. Based on the literature review, it is possible at the end to determine a theoretical ‘ideal’ system for food transport in refrigerated trucks. The respective used technologies are also mentioned. The findings of several authors have shown that often significant improvements can be achieved in surveillance, transport in general, or traceability of food, and ultimately food waste can be reduced. However, benefits can also be gained using new non-IoT-based technologies. Thus, the main knowledge of this bachelor thesis is that a theoretical ‘ideal’ transport system contains a sensible combination of technologies with and without IoT. This system includes the use of a Wireless Sensor Network (WSN) for real-time food monitoring, as well as an alarm function when the temperature exceeds a maximum. Real-time monitoring with GPS coupled with a monitoring center to prevent traffic jams is another task. Smart and energy-efficient packaging, and finally the use of the new supercooling-technology, make the system significantly more efficient in reducing food waste. These highlights, that when choosing a transport system, which is as efficient and profitable as possible for food with refrigerated transport, companies need not just rely on the use of IoT. On this basis, it is advisable to combine the systems and technologies used so far with IoT in order to avoid as much food waste as possible.