Offshore wind energy is receiving increased attention as a promising renewable energy source day by day, and the research in the field of designing the floating platforms to support floating offshore wind turbine (FOWT) has become very important. The evaluation of the dynamic stability of a FOWT in a challenging marine environment is the platform's capacity to maintain its initial position. These ...

Belt conveyor systems play a crucial role in the continuous transportation of bulk materials across varying distances. However, ensuring the reliability of these systems remains a significant concern for operators due to the potential financial losses incurred from system downtime, which not only impacts revenue from material conveying but also disrupts subsequent material processing facilities. The ...

This study explores the changing dynamics of power systems in the context of the global shift to renewable energy, focusing on inertia and its influence on frequency stability. Traditional stability mechanisms, centered around rotating masses like synchronous generators, face challenges due to the integration of renewables and frequency converters, resulting in a reduction in overall system inertia. ...

Music recommendation systems are crucial in guiding listeners to the extensive selection of music accessible today. However, these recommendation algorithms frequently encounter challenges such as the cold start problem, including less popular tracks, and comprehending the semantic substance of music. This thesis investigates the incorporation of Large Language Models (LLMs) and embeddings to tackle ...

This thesis explores the effectiveness of Large Language Models (LLMs) in enhancing educational methodologies, particularly focusing on personalized learning experiences in music education. Initially, a comprehensive literature review was conducted to establish the theoretical foundation and identify gaps in the current application of Large Language Models in education. Subsequently, employing a ...

This master’s thesis investigates alternative control methodologies for unmanned aerial vehicles (UAVs), focusing on integrating advanced human-machine interaction techniques. Traditional remote-controlled and sensor-based systems pose limitations, particularly for users with physical disabilities. This study explores the potential of virtual keyboards, hand gesture recognition, and eye movement ...

This thesis assesses the impact of fine-tuning and rag on llms in accurately assigning icd-10 codes to historical causes of death. Using funeral records from Trondheim, Norway (1830-1920), we fine-tuned Llama 3 and Mistral on 2000 records. Twelve experiments were conducted on 2000 additional records to evaluate the accuracy of each knowledge-injection technique, as well as a combination of the ...

3D-printing of polymers come in a large variety of methods and materials, each configuration with its own strengths and weaknesses. To compute and estimate mechanical properties of 3D-printed parts, good knowledge to the geometry of the internal structures is important to obtain. This will vary between different printers and slicers. As 3D-printed parts are anisotropic, it is often challenging to ...

Thanks to technical improvements, drones may now perform more than simply visual inspections of structures and buildings. An Unmanned Aerial Vehicle (UAV) drone can be equipped with a robotic arm or an attachment with sensors to check and test the structures and buildings. Designing a robotic arm with a modular end-effector that can be attached to a drone was the focus of this master's thesis research. ...

Generating structured music using deep learning methods with symbolic representation is challenging due to the complex relationships between musical elements that define a musical composition. Symbolic representation of music, such as MIDI or sheet music, can help overcome some of these challenges by encoding the music in a format that allows manipulation and analysis. However, the symbolic ...