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Bringing Quality and Service Management to Start-Ups: Implementing a Framework for Service Development
No full textThe thesis focuses on developing a structured service development model tailored
for a Swedish start-up (referred to as The Company) that supports non-profit sports
organizations. The core aim is to help these organizations operate more efficiently
and sustainably by offering services that reduce operational costs and increase revenue.
The study explores three main research questions, focusing first on assessing
the current service development of the company; second, on identifying the actors
involved in value creation; and third, on how a model for new service development
(NSD) can be tailored and designed to support the needs of sport organizations.
The study integrates theories on value co-creation theory, service creation and
use of new service development models, and applies them to the context of sport
organizations. It includes empirical data from interviews with various stakeholders
(club managers, volunteers, members, and sponsors) and results in actionable insights
and managerial implications for implementing the proposed conceptual NSD
framework. The conceptual NSD framework focus on structured feedback loops
and club segmentation, ensuring services are adapted to varying needs of amateur,
semi-elite and elite sport organizations. The study showed that in the context of
sport organizations, value co-creation and new service development requires engaging
volunteers, members, and partners by relations building and focusing continuous feedback
Time-Series Forecasting for Industrial Demand: A Comparative Study
No full textAccurate demand forecasting is critical for industrial manufacturers to optimize production planning and resource allocation. This study evaluates state-of-the-art time series forecasting models on a real-world dataset of monthly order intake for commercial vehicles from Company X, organized hierarchically by market, product group, and power supply.
In this study, classical statistical methods (AutoETS, AutoARIMA) and gradientboosting trees (XGBoost, LightGBM) are implemented and compared with recently developed state-of-the-art deep learning architectures (Temporal Fusion Transformer, TimeXer, TiDE, N-HiTS, SOFTS). Expanding-window cross-validation is employed to generate multi-horizon forecasts up to 12 months and accuracy is evaluated using RMSE and sMAPE. Models are compared with and without the utilization of exogenous variables to highlight their robustness in processing external signals to aid forecasting accuracy.
The results indicate that tree-based and statistical models, particularly LightGBM and AutoARIMA when augmented with exogenous variables, achieve the lowest average errors, suggesting that state-of-the-art models are not competitive in this setting. However, while these models are less accurate on aggregate metrics, they tend to produce forecasts with richer temporal dynamics, capturing trends and seasonality more effectively.
Overall, the findings suggest that no single approach consistently outperforms others; model effectiveness varies depending on the forecast horizon, aggregation level, and the availability of external covariates. These results highlight the importance of selecting models based on forecasting context, particularly in data-scarce industrial environments. An interesting direction for future research could be to explore hybrid or ensemble approaches to combine accuracy with actionable temporal structure
Designing Infotainment Interfaces to Enhance Electric Taxi Drivers Charging Understanding
No full textAs the shift toward battery electric vehicles (BEVs) accelerates, electric taxi drivers are facing new challenges, with long operating hours having a direct impact on the number of times the vehicle needs to be charged. The achievement of optimal charging is influenced by a variety of factors, such as the state of charge of the battery, the temperature, and the charging capacity, which are not necessarily common knowledge for many drivers. This thesis investigates how in-car user interfaces can better support electric taxi drivers in understanding and managing the charging process to achieve efficient fast charging.
A user-centered research approach was used to explore the barriers to efficient fast BEV charging. The process involved literature reviews, interviews with taxi drivers and technical experts, surveys, and benchmarking of existing vehicle interfaces. Personas, user journey maps, and a requirement list were developed to ground the design process in real world needs. Based on this foundation, initial concepts were conceived through collaborative brainstorming and their feasibility was evaluated with experts. These concepts were further developed into low-fidelity prototypes and refined in three design iterations, incorporating user feedback from both electric taxi drivers and regular BEV drivers.
Through the findings, eight design recommendations were formulated aimed at guiding the development of user interfaces designed for BEV charging. These include principles such as providing contextual and transparent information, reducing cognitive load by unifying and prioritizing key charging metrics, and ensuring interface flexibility. Although the proposed solutions were tailored for electric taxi drivers, the insights reflect broader challenges relevant to the larger BEV user base.
This thesis contributes to research on the user experience of electric vehicles, highlighting how interface design can enable drivers to make informed charging decisions. The resulting recommendations can serve as a foundation for future infotainment interface development, both in commercial and private BEV contexts
Serenity for seniors; a small-scale housing community for pensioners in Sweden
No full textThe population in Sweden is constantly growing older. At the same time, the
amount of senior housing is stagnant as “ageing in place” prevails. But for now, this
is not a long-term solution. Issues like bad accessibility, movement impairment
and loneliness are three examples of why we need to find more answers on how
to create a living situation adapted for the seniors in Sweden. Answers regarding
the possibility of combining attractive and functional accommodations with the
familiar and safe feeling of your old neighbourhood.
This thesis presents a new form of senior living consisting of a small-scale housing
community with shared facilities such as gardens, common rooms and activity
areas. By providing these innovative, health promotive living solutions as an
alternative to the urban apartments, it offers the residents existing connections
to nature and community. This way, a social and active lifestyle can be established
for people not yet in need of the services of retirement homes.
With the concept of creating a housing community adaptable to multiple sites in
Sweden, it can be placed in areas with high senior population where the wish to
move away from your hometown is low, bringing the solution the solution to the
people.
This project includes drawings, models and diagrams of two different sizes of
houses adapted for seniors, along with a programming for shared common
areas. It also presents the site, showing the communication between homes
and common areas and their connection with surrounding nature and context.
Through literature reviews, case studies, interviews and problem investigations,
this thesis establishes the theoretical foundation for accommodations that benefits
seniors’ health.
Presenting two housing models, drawn to fit the accessibility needs of senior
citizens but also to fulfil many of the qualities needed to be called ’a good
accommodation’, this thesis shows that senior housing does not have to look
or feel different than any other home. It is important that we see our senior
population not just as seniors but people of our society, with the same dreams
and wishes as anyone else
Echoes of the past: Exploring collective memory in public space through scenographic methods
No full textThis thesis explores how scenography can serve as a spatial strategy to activate, engage and represent collective memory in public spaces. By examining the interplay between design and narrative, the research aims to uncover methods for creating immersive, participatory elements that reveal historical narratives, foster collective dialogue and create connections between people and place.
Grounded in Marice Halwachs’ theories of collective memory and drawing from practices in scenography and urban design, the thesis investigates the potential of temporary architectural interventions to trigger memory recall and reinterpret historical layers. These ideas are tested through a spatial proposal at Näckrosdammen in Gothenburg - one of the few remaining sites from the 1923 Jubilee Exhibition - where three poems by Karin Boye form the dramaturgical structure of the installation.
The design process has been informed by scenographic methods such as rhythm mapping, material dramaturgy and emotional composition. A dual reading - from both an architectural and scenographic perspective - has shaped the investigation. While the architect’s voice has focused on constructional clarity, permanence and technical feasibility, the scenographer has explored presence, atmosphere and embodied experience.
The result is a site-specific installation that stages memory through spatial rhythm, contrasts and material narratives. Elements such as floating granite slabs, submerged oak and reflexive textiles are composed to evoke past and present simultaneously. The work illustrates how temporary design can become a performative medium for storytelling, enabling emotional resonance and layered interpretation. By bridging scenography and architecture, the thesis contributes to current discourse on public memory and ephemeral placemaking, offering an alternative methodology for how design can both reflect and rewrite our shared cultural landscapes
Characterization Of Oxidative Stressinduced Genomic Structural Variations In Saccharomyces cerevisiae Through Optical Genome Mapping
No full textThe genome of every known organism is composed of deoxyribonucleic acid (DNA). The DNA in organisms like humans, is organized into chromosomes and encodes the genetic instruction necessary for survival. When alterations occur in the genome, they can lead to disease. Structural variations (SVs) are large-scale genomic rearrangements, which can span several megabases, and are difficult to detect using traditional short-read sequencing methods. SVs have been observed in the widely used eukaryotic model organism Saccharomyces cerevisiae (S. cerevisiae). Particularly in strains with a compromised defense system against endogenous reactive oxygen species (ROS). In this project, optical genome mapping (OGM) was used to study SVs in a ROS-sensitive S. cerevisiae strain lacking the TSA1 gene. OGM is a technique that enables sequence-related information to be extracted across long DNA segments. OGM was performed using competitive binding of YOYO-1 and netropsin to fluorescently label DNA, followed by stretching od DNA via a nanofluidic approach. The DNA was then imaged using fluorescence microscopy. A cultivation scheme was developed for both wild-type and ROS-sensitive S. cerevisiae strains suitable for the purpose of this study. Additionally, chromosomal DNA extraction methods were evaluated to obtain long DNA fragments suitable for OGM. Fluorescence imaging data was processed to generate single molecule intensity profiles (barcodes). Barcodes where then compared to theoretical intensity profiles of the S. cerevisiae reference genome to assess coverage and detect structural changes. Amongst the samples, enough data was obtained to cover the entirety of the S. cerevisiae genome approximately 4-11 times. By focusing on chromosome II, comparisons between non-stressed and oxidatively stressed strains revealed intensity profile differences that may indicate SVs. However, further validation, preferably with higher coverage, is necessary to further characterize the genomic changes
Zooming into Comics: Region-Aware RL Improves Fine-Grained Comic Understanding in Vision-Language Models
No full textComplex visual narratives, such as comics, present a significant challenge to Vision-
Language Models (VLMs). Despite excelling on natural images, VLMs often struggle
with stylized line art, onomatopoeia, and densely packed multi-panel layouts.
To address this gap, we introduce AI4VA-FG, the first fine-grained and comprehensive
benchmark for VLM-based comic understanding. It spans tasks from
foundational recognition and detection to high-level character reasoning and narrative
construction, supported by dense annotations for characters, poses, and depth.
Beyond that, we evaluate state-of-the-art proprietary models, including GPT-4o
and Gemini-2.5, and open-source models such as Qwen2.5-VL, revealing substantial
performance deficits across core tasks of our benchmarks and underscoring that
comic understanding remains unsolved. To enhance VLMs’ capabilities in this domain,
we systematically investigate post-training strategies, including supervised
fine-tuning on solutions (SFT-S), supervised fine-tuning on reasoning trajectories
(SFT-R), and reinforcement learning (RL). Beyond that, inspired by the emerging
“Thinking with Images” paradigm, we propose Region-Aware Reinforcement
Learning (RARL) for VLMs, which trains models to dynamically attend to relevant
regions through zoom-in operations. We observe that when applied to the
Qwen2.5-VL model, RL and RARL yield significant gains in low-level entity recognition
and high-level storyline ordering, paving the way for more accurate and efficient
VLM applications in the comics domain
Evaluating an Automated Approach for Groundwater Model Setup in Sweden
No full textGroundwater modelling is a complex and time-consuming process, especially in re gions with detailed topography and heterogeneous geology. Therefore, this thesis
evaluates and compares two modelling approaches - a traditional MODFLOW-based
workflow using ModelMuse, and an automated framework using HydroModPy. The
comparison is applied to a real-world case study of the Kolmården Tunnel, a section
of the Ostlänken high-speed railway project in Sweden.
The aim was to evaluate whether HydroModPy can replicate key behaviours of an
expert-built MODFLOW model and assess its adaptability to Swedish input formats
and modelling practices. Both models were implemented from the same input data,
and their development, calibration, and outputs were systematically compared based
on hydraulic head, boundary flows, and model performance at selected observation
points. HydroModPy offered valuable automation for pre-processing and grid gen eration but lacked flexibility for custom geological layering, user-defined grids, and
site-specific boundary conditions unless custom code modifications were made. In
contrast, ModelMuse-based workflow provided full control over model architecture
and produced more stable simulation results.
The study concludes that HydroModPy is a promising tool for automated model
development and is capable of handling complex groundwater systems - provided
the user has sufficient programming expertise. Without this, its application in de tailed studies remains limited. The project further highlights the importance of early
expert involvement in data interpretation and model design. These findings are rel evant to model developers aiming to streamline model construction and researchers
evaluating automation tools for hydrogeological impact assessments in complex i
Signal-Generation Hardware for the Next Generation Chalmers Hyperthermia System
No full textMicrowave hyperthermia is a promising complementary cancer treatment alongside
conventional treatments such as chemotherapy and radiotherapy. By heating a target
area to 40 − 44◦ C using an antenna array, cytotoxic effects from traditional
methods are enhanced in targeted cells. There are multiple versions of hyperthermia
but the focus of this thesis is microwave hyperthermia, specifically the Chalmers
Ultra Wideband Hyperthermia System. The purpose is to create a more compact
version of the first hyperthermia system with frequency control per channel while
also keeping correct documentation for future work and regulatory adherence. The
project was divided into two phases. The first phase involved analyzing the legacy
system to establish the requirements for its successor. This resulted in direct digital
synthesis (DDS) being chosen as the new signal generation method and a overview
for a 17 DDS-based system, alongside extra designed parts for control, calibration
and amplification. A Quality Management System was also set up within the documentation
for potential future work on the system. This newly developed system
would be more compact, have a higher phase-shift resolution while incorporating
frequency control per channel. The second part of the project consisted of validating
and testing the DDS using a third party DDS Shield for Arduino Mega
2560. By comparing the DDS’s frequency accuracy, stability, amplitude flatness
and edge quality to the previous analog wave oscillator it was confirmed that the
DDS would be a suitable replacement. Finally a Two-Channel Proof of Concept was
implemented to prove that two DDS boards could be synchronized using a single
reference clock. Although there was a random phase shift between the two boards,
it was shown that synchronization was possible as they reliably were able to get in
phase with each other. While the current DDS board could be used to replace the
wave oscillator of the current system without further changes, there are many future
developments available. The main one is to finish up the 17-DDS system hardware
and testing it, introducing changes to the calibration system and following up on
the regulatory pathway are all possible options