Master Thesis Topics
The Master Thesis is the opportunity to distinguish yourself as an expert and, for example, to initiate an innovation project in the company. Also remember to make it known that you have finished your Master's degree - because all the work has to be seen and celebrated!
Drivers and Inhibitors for Healthcare Organizations to Adopt Federated and Swarm Learning
This thesis closes the gap in scholarly knowledge on adoption drivers and inhibitors for Federated Learning and Swarm Learning in healthcare, which promise the preservation of privacy while complying with legal regulations. Thus, it serves as an enabler for future research as well as for solution providers and healthcare organizations to address adoption drivers and combat inhibiting factors. Ultimately, it helps accelereate the adoption of FL/SL in healthcare, which will enable new forms of collaboration, AI-driven medical advances, and innovation.
Johann Kortsch, Information Systems Engineering and Management, Intake 2020
Automatic assessment of pragmatic quality aspects of executable BPMN models
In literature, various approaches exist to assess the quality of business process models. However, these approaches mostly refer to strategic process models and do not take into account that companies nowadays also use their process models for automation by use of workflow engines. Due to the new scope of use of process models, there are also new requirements for the quality of the process model. In addition, the process model is now part of a software and therefore subject to software development requirements. In this master thesis, pragmatic quality criteria of executable BPMN process models are identified and subsequently, a concept is developed on how these criteria can be assessed. For this purpose, existing evaluation methods are presented and their limitations in terms of executable models are shown. To automate the assessment of the criteria and to integrate it into the software development of process applications, a prototype was developed that can evaluate the pragmatic quality of BPMN models.
Manuel Dittmar, Information Systems Engineering and Management, Intake 2020
Development of a forecast model for the spatial distribution of lion traction batteries in Germany
The purpose of this thesis is to forecast and examine the Electrical Vehicle distribution within the different 16 states in Germany. This research shows how this forecast is crucial, especially that Electrical Vehicles will play a lead role in a more sustainable and environmentally friendly mobility, that is of course assuming that the electricity is provided from renewable sources. In Germany, Electrical Vehicle numbers have dramatically increased, thanks to the attractive government subsidies and financial incentives, the technological advancements in charging infrastructures and battery technology, the increasing individual concerns regarding climate change and more efforts done to encourage the utilization of electrical mobility. For orderly accommodations for this rapid development, it is of utmost importance to get an accurate predication of the Electrical Vehicles that would be on the road in several areas in Germany, as this data would be essential for a timely plan for the electromobility infrastructure, such as the charging stations infrastructure, the expected load on the electricity grid, the impact it would have on the renewable energies requirements and, not to mention, the influence it will have on the manufacturing companies as well. Therefore, this research utilizes the Bass Diffusion model, which is one of the most accredited models to forecast the diffusion of the innovative technologies and products within a social system. This model mathematically predicts the future adoptions using previous sales data, through two combined attributes: Innovators, who adopt the innovation immediately after release, and Imitators, who adopt the innovation based on the word-of-mouth communications with existing adopters. An analytical evaluation of the main model's parameters is carried out, to reveal the interesting simulations findings, which opens the door for more extensive research opportunities in this field.
Jasmin Hariri, Energy Engineering and Managment, Intake 2019
Exploring and Evaluating Sound Design for Percussive Instruments with Deep Variational Autoencoders
Exploration of different Generative Deep Learning Architectures that can be used in the Sound Design process for percussive Instruments. Moreover the development and evaluation of a prototype that showcases the possibilities and advantages of Variational Autoencoders for Sound Engineers.
Data - Driven Automation of API Lifecycle Management for Embedded Systems in the Automotive Industry
The increased digitalization of the vehicle and the upcoming prospect of fully autonomous vehicles give increasing importance to the in-vehicle infotainment system. Furthermore, with new players originating from the consumer electronics industry entering the market, customers expect an increase in feature scope and frequent updates.
The existing development methodologies and software architectures need to be adapted to satisfy the changing consumer demand. Instead of having few monolithic components, the trend is to have many smaller software modules focused on a specific feature and developed independently. The development of these modules can then be distributed across different teams in the company or even opened up to external developers. However, dividing the software does not resolve functional dependencies. Therefore this paradigm shift creates new interfaces between the different modules for cross-functional features.
Compared to a service-oriented architecture, the governance process for the interfaces between the different modules needs to be more flexible. In addition, the interfaces need to be on a higher abstraction level and be easy to consume to accommodate to the new business requirements. At the same time, it is still important to manage the interfaces to ensure consistency and stability.
This thesis covers the lifecycle aspect of interface management. It compares different methodologies from service-oriented architecture to consumer-focused web development methods. Based on this analysis, it proposes a process for managing the lifecycles of embedded application programming interfaces. A concept for an automated and data-driven tool to support and safeguard this process is described. This approach combines data from service providers and service consumers. It can enforce the lifecycle process and support developers by giving insights into the available and used application programming interfaces.
The concept is implemented for the QML language used by the Qt framework. This implementation is successfully applied to a user interface software project in the automotive infotainment field.
Leo Benz, Mobility Systems Engineering and Management, Intake 2019
Development of a material flow cost accounting methodology for remanufacturing processes
The thesis aims to increase the acceptance of remanufacturing industry with a visualization performance of cost results, remanufacturing infrastructure investment appraisal and carbon emission. The modified material flow cost accounting model is based on the digitalization methodology for sustainable further development in industry 4.0 environment.
Zhengchun Zhang, Financial Engineering, Intake 2018
Static Performance Estimation for Embedded Processors based on Compiler Intermediate Representations
The end of single-core processors has come! New processors are increasingly characterized by heterogeneous multi-core processors. This is because only heterogeneous multicore processors can efficiently use the ever-increasing number of transistors to increase performance. However, multicore processors shift the problem of parallelization from hardware to software. As a result, the programmer is responsible for parallelizing the application and has to deal with parallelization issues. Therefore, we at emmtrix are researching automatic parallelization of C code for heterogeneous multicore processors. For automatic parallelization a performance estimation of the sequential input application is important. The previous performance estimation is only based on C code and therefore does not consider the influence of compiler optimizations. With this thesis, a new performance estimation is developed using LLVM compiler intermediate representation (IR).
Pranjal Ranka, Information Systems Engineering and Management, Intake 2019, working as R&D SW Developer at Bruker Ettlingen.
Using ChatOps to Achieve Continuous Certification of Cloud Services
Continuous service certification (CSC) recently emerged as a promising means to provide ongoing assurances and disrupt pertinent certification approaches. CSC involves the consistent gathering and assessing of certification-relevant data by certification authorities about service operation to validate ongoing adherence to certification criteria. While research on CSC is increasing, practitioners still struggle in transferring researchers' suggestions and guidelines into practice. This study provides a tentative design and a prototype of a monitoring-based service certification (MSC) system based on the novel ChatOps approach. Iterative evaluations support our propositions that ChatOps' three key elements, a chat platform, chatbots, and third-party integrations, support the achievement of CSC. We contribute to research and practice by proving the technical feasibility of an MSC system, guiding future research and practitioners on achieving monitoring-based CSC, and validate the applicability and usefulness of extant guidelines on monitoring-based CSC proposed by prior research.
Paul Ohagen, Information Systems Engineering and Management, Intake 2019
other Authors: Sebastian Lins, Scott Thiebes, Ali Sunyaev
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