Refine
Institute
- Fakultät Informatik (597)
- Fakultät Elektro- und Informationstechnik (463)
- THI Business School (412)
Version
- published (858)
The impact of technology on employment and consequently on skills is becoming increasingly apparent, particularly in the use of artificial intelligence.
The aim of this bachelor thesis can therefore be divided into two research questions: On the one hand, the aim is to analyze what impact the use of artificial intelligence will have on the labor market. The second question is concerned with the impact artificial intelligence will have on the labor market in terms of the skills required.
In order to provide a profound answer to the research questions, a wide range of literature was used, including books, research studies and use cases. Based on the research questions, the thesis addresses the worldwide AI driven labor market, identifying both the displacement of human workers and the simultaneous opportunities for new occupations and economic growth. Moreover, a variety of necessary skills are highlighted that are essential for overcoming the
dynamic challenges on the labor market posed by AI. Finally, the subsequent analysis of the financial sector and public administration serves to illustrate and clarify the relevance of these skills. Therefore, both knowledge of artificial intelligence and existing human skills are important. Depending on the occupation and task area, the focus of skills is either on the direct application of artificial intelligence or on developing an awareness and understanding of it. It also shows that a wide range of actors, including companies and educational institutions, have a key role to play in the process of adapting workers' skills.
The future of automated mobility aims to create significant opportunities for growth and prosperity for the population. An appropriate level of understanding of automated driving, especially in the context of automated shuttle buses, is crucial for improving road safety. Nevertheless, there are many constructs that attempt to predict the factors for people’s perception of automated shuttle buses, but there is no known study to date that has directly examined whether people’s personality traits influences the perception and interaction with such vehicles. This study examines the relationship between personality traits and people’s perception with fully automated shuttle buses. We conducted a study with 40 participants in a virtual CAVE to gain an in-depth understanding of the correlation between the Big Five personality dimensions and the factors influencing the perception of automated shuttle buses. We show that certain personality traits have a main effect on the influencing factors for automated shuttle buses. We found that four of the five dimensions of the Big Five have a significant impact on how people perceive the interaction with an automated shuttle bus. This is particularly seen in the context of Trust, Usability and Acceptance. The results showed that Agreeableness, Conscientiousness and Extraversion had a positive effect on Technology Acceptance, while Neuroticism had a negative effect. Conscientiousness also had a positive effect on the Usability and Agreeableness and Extraversion a positive effect on Trust. Furthermore, it was found that for some personality traits (especially for Agreeableness) the presence of the eHMI has a very high moderate impact on the correlation with the influencing factors. The results are consistent with other studies relating to the Big Five and technology. Suggestions for future research are discussed.
The market for unmanned aerial systems (UASs), also known as unmanned aerial vehicles (UAVs) or drones, is growing rapidly, particularly in the field of Vertical Take Off and Landing (VTOL) UASs. The sensor configuration of a UAS varies depending on the specific use case and type of UAS deployed. Because of this, the different systems have different possibilities to detect and act on a wide range of emergencies. However, all these systems require an appropriate emergency landing method to address potential dangers during UAS flights, regardless of whether the UAS is piloted or flies autonomously. A literature review was conducted to analyze existing research on emergency landings for UASs and identify the necessary requirements for safe emergency landing (SEL) operations. Based on these findings, a novel SEL method was developed. This method presented in this thesis involves semantically segmenting images from a ground-facing camera onboard of the UAS to extract information about its environment. The segmented image is then undistorted to project it onto a ground plane, assuming a flat earth model, restoring metric information. The resulting projection is geo-tagged with the UAS’s current position to create an instance map of the current point in time. By filtering consecutive instance maps using majority voting, a stable map is aggregated, which is then further utilized to detect potential SEL spots by using its inherent semantic information, and for navigation. The SEL method is implemented via the middleware Robot Operating System version 2 (ROS2) using a set of packages responsible for landing spot detection and communication with the flight controller. The development of the SEL implementation included continuous testing in software in the loop (SITL) simulations and real-world test flights, which validated both individual elements of the SEL pipeline and the entire method, resulting in successful demonstrated fully autonomous SEL operations. It can be concluded that the developed method meets all the identified requirements for SEL operations.
In der medizinischen Bildgebung ist die Aufnahme durch Magnetresonanztomographie (MRT) wohl eine der gängigsten Methoden, wenn es um die Informationsgewinnung von Gewebestrukturen geht. Vor allem im Gehirn, wo jeder Eingriff ein hohes gesundheitliches Risiko birgt, bietet das MRT eine sichere Methode, dieses zu analysieren. Als Erweiterung davon kann mittels Diffusions-Bildgebung auch die Bewegung von Protonen im Gewebe gemessen und daraus der Verlauf von Nervenfasern rekonstruiert werden. Diese Methode ist als Traktographie oder auch Fiber Tracking bekannt und kann über verschiedene Algorithmen umgesetzt werden.
In dieser Arbeit soll der Fokus auf Fibertracking mit KI-gestützten Methoden gesetzt werden, um eine Pipeline zu schaffen, die auf beliebige rohe Diffusionsdaten anwendbar ist. Der Aufbau setzt sich dabei aus verschiedenen Schritten zusammen. Zunächst werden die Daten vorverarbeitet, um einen Ground Truth zu erzeugen, der die benötigten Koeffizienten zur Traktographie beinhaltet. Diese können dann im zweiten Schritt von einem Transformer-basierten KI-Modell trainiert werden. Damit soll im letzten Schritt dann aus den geschätzten Werten die eigentliche Traktographie umgesetzt werden. Mit der Verwendung einer gut trainierten KI-Architektur soll so Zeit und Rechenleistung im gesamten Prozess eingespart werden können, da das Modell aufwendige Algorithmen zur Berechnung der Koeffizienten ersetzen kann. Es soll dabei gezeigt, werden wie die komplette Anwendung im Trainingsablauf aussieht, und welche Anpassungen und Optimierungen möglich sind. Die resultierende Code-Pipeline soll den Grundstein für weitere Forschung an Daten von MS-Patienten legen.
Als Betreibergesellschaft eines der wichtigsten Flughäfen Europas muss Flughafen München GmbH stets daran arbeiten, ihre Systeme auf dem technisch aktuellsten Stand zu halten. Aktueller Teil dieser Bemühungen ist die konzernweite Einführung eines auf Microsoft 365 aufbauenden cloudbasierten Standardarbeitsplatzes. Diese Arbeit begleitet dieses Programm und hebt dabei mehrere Aspekte hervor, in denen es ein Vorreiter für die Modernisierung des Konzerns ist. Sie kommt dabei zu dem Schluss, dass in mehrerlei Hinsicht positive Grundlagen für eine weitergehende Entwicklung geschaffen wurden. Vor allem im Bezug auf die Strategie, mit der diese Entwicklung an die Belegschaft kommuniziert wird, findet diese Arbeit jedoch Defizite, die hauptsächlich aufgrund zu spät eingeräumter managementseitiger Aufmerksamkeit für dieses Thema entstanden sind.
Virtual Reality (VR) has emerged as a promising and effective tool for education. The serenity of nature and the underlying Biophilic design theory promise positive effects on learning by influencing attention, well-being and immersion in advanced technology. However, the specifics of how and under what contexts learning is most effective in VR with a focus on the abstraction level remains to be elucidated. This study aims to determine how radically different virtual environments (VE) - natural vs. abstract - design approaches affect learning and attention and the underlying interplay of these two constructs with attention, comfort, presence, and immersion. A mixed-method design with a comparative exploratory approach within subjects was adopted to explore the influence of different VR settings, one being natural and one being abstractly designed without elements. The study emphasizes the crucial role of interaction between presence and attention in VE design. However, while there were no significant quantitative differences regarding this data set, naturalistic VR environments significantly influenced learning effectiveness and attention spans according to qualitative data about the same result. Also, biophilic elements facilitate emotional comfort while considering user comfort and engagement during thematic analysis. It is also evident that quantitative measuring within Immersion and Presence effects reveal slight trends towards natural VE, while qualitative data favored the abstract VE, which raises the question of sensitivity on the MPS Questionnaire and incorporating and elevating the perspective of Acceptance of Virtual Reality Environments to be more sensitive and valid. Our research confirms VR’s potential in education and highlights that traditional classroom elements should blend with VR capabilities (educational VR spaces should augment, not replace, conventional methods). The broader explorative approach revealed potential gaps in VR research, new perspectives on abstraction levels, and the impact on VR learning.
In this thesis, the designing and detailing of a patented hydroelectric energy storage system is documented. Hydropower has been one of the oldest sources of electricity for humankind. This thesis is focused on the idea of manufacturing a hydropower plant to a scale that would be feasible and useful for an average household of 4 people. It also includes the processes and guidelines to manufacture the parts of this energy storage. In current times, renewable sources of energy production are increasing, relevant to earlier years, to reduce the dependence of the world energy needs on fossil fuels. Storing this renewable energy is important and due to limited natural resources like Lithium, Nickel etc. for Battery storage, other viable storage technologies need to be developed such as HEES. Hydro-electric Energy Storage (HEES) is an innovative energy storage concept that utilizes hydropower as energy storage. This paper focuses on the design of the Pelton turbine and the nozzle for a prototype of the HEES. Specifically, the runner, the method used to fix the Buckets on a Pelton runner, and the casing for the runner are analyzed in detail. The HEES nozzle is a critical component responsible for precisely directing high-pressure water jets onto the turbine's rotating buckets.
The study explores the intricacies of Pelton turbine design, including considerations for bucket width, depth, and attachment methods. The importance of nozzle technology for creating ultra-thin water jets and the design of a casing for the high-speed Pelton turbine is also examined. Material selection is a critical aspect, involving stainless steels with varying properties, including corrosion resistance, strength, and weldability. The evaluation and comparison of these materials lead to informed decisions for prototype and final designs. In the context of manufacturing, various methods, such as CNC machining, forming, stamping, forging, and powder metallurgy, are assessed. A detailed analysis highlights the strengths and weaknesses of each approach. For the HEES prototype, a manufacturing method is chosen based on cost-effectiveness and suitability for aluminium, while the final design leans toward stainless steel and methods that ensure strength, precision, and durability. In the ever-evolving landscape of renewable energy, this thesis contributes to the development of a promising Hydro-Energy Storage System, laying the foundation for sustainable and efficient household energy storage solutions.
The thermal management systems on military aircraft have become a bottleneck for
deploying novel technologies that produce high-energy, pulsed heat loads. Multiple
approaches for heat rejection of such heat loads have already been considered, but
no meaningful conclusion can be made about which approach is best suited for this
application. This thesis aims to identify the system architecture that is most suited
for dealing with these high-energy pulsed heat loads. This was done by simulating
a Vapor Compression Cycle and two systems using sensible and latent heat storage
using Simcenter Amesim. The systems were assessed regarding their system mass.
The results show that the system utilizing sensible heat storage reduces the overall
system mass by 67% while using latent heat storage increases system mass by 71%
compared to the simple Vapor Compression Cycle. Based on these findings, a clear
recommendation can be made that future research in this field should focus on
developing architectures using sensible heat storage.
The present study investigates the viability of implementing a micro-scale district heating system (DHS) powered by solar energy in the elevated rural regions of Kyrgyzstan. The performance assessment of such a system is achieved through modeling and simulation in Polysun software along with a conducted parametric study to find out the optimal volume of the storage tank to the area of the collectors based on the solar fraction.
A parametric study resulted in the possible system configuration with a solar fraction of 19.4%, achieved with 2,000 collectors (4,060 m2) and a 400 m3 storage tank. The follow-up economic evaluation considers total lifecycle costs, comparing the solar-assisted DHS with an electric and a coal boiler as the auxiliary heater, and an individual stove-based system. The DHS with a coal-fired boiler resulted in a slightly lower levelized cost of heat (LCOH) at 10.03 €-ct/kWh compared to the electric boiler at 11.77 €-ct/kWh, while an individual home coal-fired system is 1.13 €-ct/kWh.
However, LCOH-based energy affordability analysis revealed that the proposed DHS would burden typical households, where the man works and the woman manages the household, exceeding income by 74% (with electric boiler) and 48% (with coal-fired boiler).
Therefore, the study underscores the need for careful economic consideration in solar thermal projects, especially in low-income areas. To facilitate successful implementation in such regions, securing subsidies or financial support during the project's implementation stage is essential to maintain the affordability of these systems for the local population.