Examensarbeten för masterexamen
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- PostRare Events in Reaction-Diffusion Systems Field-theoretical Approximations and Monte Carlo Simulations(2025) Manoni, Edoardo Maria; Chalmers tekniska högskola / Institutionen för fysik; Chalmers University of Technology / Department of Physics; Hofmann, Johannes; Hofmann, JohannesRare events are events that have near-zero probability of occurring. Despite their apparent irrelevance, when they do occur, they can have substantial, and even catastrophic, repercussions. In this thesis, we study rare events in reaction-diffusion systems, a class of mathematical models that finds various applications in physics and life sciences. We employ both theoretical and computational methods to determine the tails of the probability distribution describing the state of system. Firstly, we follow existing literature to derive a quantum-mechanical description for entirely classical reaction-diffusion systems, called the Doi-Peliti formalism. We express the time evolution of the systems as a Feynman path integral, which we then evaluate at the saddle point to obtain a semiclassical approximation for the probability distribution, and a closed-form leading-order expression for the tails. Secondly, we tailor a lesser-known Monte Carlo algorithm for rare probability estimation, called adaptive multilevel splitting, to compute the probability distribution of reaction-diffusion processes. We derive some theoretical results regarding its efficiency, discuss practical implementation choices, and benchmark its performance against well-understood examples. Lastly, we compare the semiclassical approximation to the computational results, determining under which conditions the former succeeds or fails.
- PostDesigning a modular binding system for alpine skiing(2025) Steninger, Johanna; Chalmers tekniska högskola / Institutionen för fysik; Chalmers University of Technology / Department of Physics; Karlsteen, Magnus; Karlsteen, MagnusThe master’s thesis, "Designing a modular binding system for alpine skiing" explores the development of a versatile ski binding system that allows skiers to exchange binding parts depending on user preferences. The thesis contains various work procedures and processes related to the project. The research concerns the collection and interpretation of information obtained through patent research, market research, interviews, brainstorming, and the narrowing down of ideas, and a conceptualization phase to be able to design a digital model of a modular alpine binding system for skiing. The project stems from Alpine skiing being a popular sport that can be performed in various ways. The skier can ski downhill in the ski resorts, off-piste, and tour up the mountain (ski-touring). Within these styles of skiing, there are also different levels of skiing depending on skill, some extreme examples are alpine race skiing, park skiing, and freeriding. Nowadays many skiers are very versatile and ski in many different ways, hence bindings that also enable ski-touring have been available on the market for some time. In recent years the ski-touring aspect of skiing has grown increasingly popular. The options on the market are either expensive or a trade-off compared to a specified binding for a specific purpose dedicated to skiing downhill in the resorts, skiing off-piste, or solely dedicated to ski-touring. The interest in a modular binding system has therefore grown, a modular binding can provide a dedicated binding for either choice of skiing as the binding parts could be exchanged to best meet the demands placed on it for different types of skiing without compromising the performance of the binding. Provided the methodology used in the study, existing solutions and gaps in the market could be analyzed, and a digital model of a modular alpine binding system was developed using CATIA software (Computer-Aided-Design). The concept was iteratively refined and evaluated through prototyping, assembly, and testing of 3Dprinted components, to ensure its feasibility. The findings of this study indicate that the modular binding system offers increased versatility with attachable and detachable binding parts, making it possible for users to use a single platform for multiple types of binding systems to accommodate their various needs. However, challenges remain in material selection to achieve a balance between weight, durability, and performance, as well as real-world testing of the prototype to ensure safety standards and reliability. The study concludes that the proof of concept is feasible and has the potential to transition into a commercial product. The modular binding system could offer skiers greater flexibility while maintaining high performance and safety, however further work is needed regarding refinements of technical aspects, real-world testing of functionality and performance, and exploration of the product scalability. The research provides a solid foundation for future development of the modular binding system that can bridge the market gaps without compromising the performance of the modular binding system.
- PostPrivacy Risks in Text Masking Models for Anonymization(2025) Reimer, Amandus; Chalmers tekniska högskola / Institutionen för fysik; Chalmers University of Technology / Department of Physics; Volpe, Giovanni; Östman, JohanLarge Language Models (LLMs) are increasingly employed to anonymize texts containing Personal Identifiable Information (PII), often relying on Named Entity Recognition (NER) to identify and remove sensitive data. This thesis explores the privacy risks associated with such text masking models by evaluating their vulnerability to Membership Inference Attacks (MIAs) and extraction attacks. MIAs are attempting to identify whether or not a data point was part of the training dataset, knowledge of the membership can in certain scenarios be a breach of privacy. Two state-of-theart MIAs have been used to conduct attacks on text masking models. This study also proposes a framework based on multi-armed bandits for performing extraction attacks and evaluates two different strategies within this framework. The results from the MIAs indicate that there is some risk of revealing information regarding the training data. The extraction attacks did not yield great results in terms of performance but indicate that the concept could possibly be useful if developed further.
- PostDeveloping data analysis methods for Nanofluidic Scattering Microscopy(2024) DOMENZAIN DEL CASTILLO CERECER, AARÓN; Chalmers tekniska högskola / Institutionen för fysik; Chalmers University of Technology / Department of Physics; Langhammer, Christoph; Albinsson, DavidNanofluidic Scattering Microscopy (NSM) is a label-free technique that allows the simultaneous measurement of molecular weight and size of single molecules and nanoparticles flowing through a nanochannel. Assuming free diffusion, the diffusivity coefficient derived from the trajectory of a particle can be utilized to determine its hydrodynamic radius via the Stokes-Einstein relation. However, non-specific atractive interactions between biological nanoparticles and the inner walls of the nanochannel, known as biofouling, immobilize the particle, invalidating the assumption of free diffusion and making impossible to accurately determine the particle size. This study introduces a computational method to detect biofouling in NSM, based on the statistical analysis of instantaneous kinetic energy in discrete Brownian motion. The method sets a probability threshold to either accept or reject the hypothesis of free diffusion, allowing for the exclusion of biofouled segments from diffusivity calculations, thereby enhancing the accuracy of hydrodynamic radius determination.
- PostEvaluation of Neural-Network and Large-Language Model Approaches for Generating Instructions for Animations(2025) BARLETTARO, ELISABETTA; ERIKSSON, EMMA; Chalmers tekniska högskola / Institutionen för fysik; Chalmers University of Technology / Department of Physics; Mehlig, Bernhard; Fröjd, MartinConversational agents are used more and more in customer service, health care, for educational purposes. The fundamental problems of conversational agents are many, including limitations in interpretation of complex queries and lack of emotional intelligence. Despite this, there are distinct advantages of conversational agents, such as efficient data analysis, reduction of operational costs and aid in interactive learning for personalized teaching. The most significant challenge this project aims to undertake is to generate realistic and complex animations in the context of interactive learning with a real-time constraint. The investigation includes how to select machine learning tools and models to aid in the advancement of animation generation, by using both Large-Language Models and purposely constructed Neural Networks. While Large-Language Models are convenient when used in straightforward conditions, Neural Networks are more dependable in an operative application thanks to their consistent format, adaptability and specifically developed purpose.