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Auf dieser Webseite befindet sich eine Übersicht der aktuell von uns ausgeschriebenen Abschlussarbeiten. Sollte sich unter den Themen kein passendes befinden, dann guck einfach mal in unseren Forschungsthemen nach einem interessanten Bereich und wende dich an die Kontaktperson. Bitte schreib in deiner Anfrage auch gleich etwas über deine aktuellen Vorkenntnisse in dem Bereich.

Development and Evaluation of Augmented / Virtual Reality Applications

Motivation

Cognitive assistance systems offer a variety of possible use cases especially in the context of learning environments in artificial reality (AR/VR) scenarios. In our project it‘s OWL AWARE, we are researching new application scenarios, development methods and new forms of interaction to support the development of novel assistance systems.

In this subject area there are various open Bachelor and Master thesis topics, which deal with the systematic development and evaluation of AR/VR applications.

Possible Topics

  • Systematic literature survey for AR/VR development methods
  • Prototypical development of AR/VR applications for different scenarios (assembly, maintenance, navigation, …)
  • Development of new modeling languages to capture AR/VR specific aspects
  • Development of model-driven or component-based development methods for AR/VR applications
  • Usability Evaluation of AR/VR applications in terms of efficiency, effectiveness, and user satisfaction
  • Data-driven UX Evaluation of AR/VR applications through user feedback (human-in-the-loop, digital-twin approaches)
  • Conception and development of context-adaptive AR/VR applications
  • Continuous quality assurance and software testing for AR/VR applications

If you are interested in one of the above mentioned topics or have your own topic suggestions, feel free to contact us!

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Enes Yigitbas

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Conception and Implementation of a Development Framework for Cross-Device AR/VR Applications

Motivation

Augmented Reality (AR) and Virtual Reality (VR) Developers face a proliferation of new platforms, devices, and frameworks. This often leads to applications and interactions being limited to a single platform and makes it hard to support collaborative AR/VR scenarios involving multiple different devices such as HTC Vive, HoloLens and smartphones. For supporting a seamless interaction across various AR/VR platforms, the main goal of this thesis is to design and implement a framework for cross-device AR/VR experience. Based on previous work in this area [1] relevant cross-device interaction scenarios for AR/VR should be identified. The derived requirements should form the basis to create a development framework for cross-device AR/VR applications. An evaluation of the framework should be performed by implementing exemplary cross-device AR/VR scenarios.

Description of the task

  • Systematic literature survey on cross-device AR/VR interfaces
  • Conception of a development framework for cross-device AR/VR applications
  • Prototypical implementation of a development framework for cross-device AR/VR applications
  • Evaluation by implementing and experimenting with exemplary cross-device AR/VR scenarios

Contact

Enes Yigitbas

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Continuous Adaptation of Business Models based on Feature Models

Motivation

The continuous innovation of its business models is an important task for a company to stay competitive. During this process, the company has to validate various hypotheses about its business models by adapting to uncertain and changing customer needs. To represent business models for idea generation, the Business Model Canvas [1] is mostly used. In the past, we have used the concept of feature models to represent the variability of a business model [2]. The goal of this thesis is to conceptualize and implement a tool in Angular, which can (1) mine a feature model out of a set of existing business models, (2) derive new business models from the feature model, (3) learn validated and disapproved business decisions (see Figure 1). To do this standard-techniques like Feature Model Mining [3] or Questionnaire-based Variability Modeling [4] can be applied to the new context of business models.

Tasks

  • Literature Review on Business Models & Feature Models
  • Conception and Design of the Algorithms and the Tool
  • Implementation of the Algorithms and the Tool in Angular
  • Evaluation in a Case Study

Sources

  • [1] Osterwalder et al.: Business Model Generation (2010)
  • [2] Gottschalk et al.: Intertwined Development of Business Model and Product Functions: A Twin Peak Feature Modeling Approach (2019)
  • [3] She: Feature Model Mining (2008)
  • [4] La Rosa et al.: Questionare-based Variability Modeling for System Configuration (2008)

Further Information

The topic can be taken as a bachelor- or master thesis. It is possible to write this thesis in German or English. The requirements for the topic are passed courses of Data Mining (bachelor) or Machine Learning I (master). Please write in your application shortly why you are interested in the topic and what further experience you have in the field. Before the proposal process, there will be a short test (consisting of general questions, your understanding of the topic and a small programming task) to see if you are the right person for the topic.

 

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Decision Support System for Business Modeling based on Feature Models

Motivation     

The continuous generation of new business model ideas is an important task for a company to stay competitive. During this process, the company can use various best practice examples of other companies in form pattern cards [1]. To represent business models for idea generation, the Business Model Canvas [2] is mostly used. In the past, we have used the concept of feature models to represent the variability of a business model [3]. Moreover, we have developed a first version of a feature model editor [4] for business models in Angular (see Figure 1). The goal of this thesis is to conceptualize and implement a decision support tool, which can support business developers by automatically applying the various business pattern for improving feature selection during the ideation phase. These patterns can be generalizable to all business models or depending on the context of the business.

Tasks

  • Literature Review on Business Models & Feature Models
  • Conception and Design of the Algorithms and the Tool
  • Implementation of the Algorithms and the Tool in Angular
  • Evaluation in a Case Study

Sources

Further Information

The topic can be taken as a bachelor- or master thesis. It is possible to write this thesis in German or English. The requirements for the topic are passed courses of Data Mining (bachelor) or Machine Learning I (master). Please write in your application shortly why you are interested in the topic and what further experience you have in the field. Before the proposal process, there will be a short test (consisting of general questions, your understanding of the topic and a small programming task) to see if you are the right person for the topic.

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