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Otakaari 1 grandhall. Photo: Esa Kapila
 

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Recent Submissions

Operating Electrolysers Under Tight Rules for Renewable Fuels of Non-Biological Origin (RFNBOs) and Constrained Green Electricity Supply in Finland
(2025-11-26) Laurén, Albin
School of Electrical Engineering | Master's thesis
The European Union’s REPowerEU strategy targets a substantial increase in renewable hydrogen production, setting ambitious goals for Renewable Fuels of Non-Biological Origin (RFNBOs). However, compliance with the current RFNBO framework, poses operational challenges for hydrogen producers due to the intermittent nature of renewable energy. This thesis examines the operational feasibility of RFNBO-compliant hydrogen production in Finland. The analysis combines historical data from 2019-2024 to evaluate renewable scarcity, compliance risks and portfolio performance for different combinations of wind, solar and hydropower. The results show that while the strong renewable base of Finland offers promising conditions for RFNBO production, compliance risks remain significant during prolonged low-generation periods. Diversified portfolios integrating solar and hydropower reduce both curtailment and downtime compared to wind-only portfolios, improving the utilization ratio and overall stability. The findings highlight how strongly market prices and wind conditions influence compliance. Since these factors are largely uncontrollable, they make electrolyser operation less predictable. The study concludes that although conditions in Finland are generally favourable, maintaining compliance will require careful portfolio design and continued regulatory clarity.
Performance evaluation of L4S in 5G networks
(2025-12-15) Lassila, Robi
School of Science | Bachelor's thesis
This bachelor thesis examines a new technology called Low Latency, Low Loss and Scalable Throughput (L4S) in 5G mobile networks. As the name suggests, L4S allows for a low latency and packet loss with scaling data rates. The topic is important as the number of devices required to have an internet connection rises. In addition, this is important for future applications that require a low latency, for example XR applications. The purpose of this thesis is to evaluate the performance of L4S in 5G mobile networks compared to older congestion control algorithms. This thesis explains the concept of L4S and its functionality based on available literature and the performance is measured with field testing in 5G mobile networks. In the test results, we found a significant difference in the latency when comparing L4S enabled versus disabled. On average, there was a 10 millisecond improvement in the latencies when the network experienced congestion. With L4S disabled the latencies were approximately 20 milliseconds compared to 10 milliseconds when L4S was enabled. The latency improvement is approximately 50 \%, which is quite significant. However, we also found the throughput of the non L4S flow was significantly lower when L4S was enabled. In conclusion, we found that L4S has the capacity and potential to improve latencies, which is important especially for low latency applications. The results suggest further development and improvement of L4S.
Käyttäjän yksityisyyden kokemus puhekäyttöliittymissä
(2026-01-23) Ypyä, Linnea
School of Science | Bachelor's thesis
The increased use of voice user interfaces has raised concerns about users’ privacy. Previous research has shown that users’ subjective experiences of privacy do not always correspond to the objective level of privacy provided by a system. This thesis examines users’ subjective experiences of privacy in voice user interfaces. The aim of the study is to investigate how interface features, interaction, and the usage of environment and context shape the experience of privacy. The study is conducted as a literature review. As a theoretical framework, the thesis draws on Sandra Petronio’s Communication Privacy Management (CPM) theory and Helen Nissenbaum’s theory of Contextual Integrity. In addition, the experience of privacy is examined from the perspective of privacy-supporting design principles. The results indicate that users’ sense of control and the transparency of system operation play a central role in shaping the experience of privacy. By strengthening users’ sense of control and the predictability of system behavior, it is possible to reduce fears of surveillance and the resulting behavioral constraints. The experience of privacy is particularly weakened in situations where data flows, data-sharing practices, and data recipients are unclear. Voice user interfaces should therefore support the experience of privacy through active, dialog-based communication that helps users understand system operations and maintain a sense of control.
Advancing research methodologies in digital phenotyping for mental health
(2026) Ikäheimonen, Arsi
School of Science | Doctoral thesis (article-based) | Defence date: 2026-02-13
Digital phenotyping is an evolving field that fuses the disciplines of data science, behavioral science, and medicine. Digital phenotyping research utilizes data from personal digital devices and online platforms to investigate various behavioral, social, and health-related aspects of an individual's life. By analyzing these data, research aims to find novel insights into behavior, health, and well-being. These insights may lead to new complementary methods and applications for more effective healthcare solutions. As a new field, several factors hinder digital phenotyping from reaching its full potential. This thesis aims to advance the field of digital phenotyping through two perspectives: methodological and practical. From a methodological perspective, the thesis focuses on the barriers due to technical and research methodology-related challenges. In turn, the practical perspective evaluates the potential of using digital phenotyping to monitor and predict depressive symptom severity using data collected from outpatients diagnosed with ongoing depressive episodes. This thesis comprises five research articles, two of which focus on advancing the methodology, and the remaining three focus on practical aspects. The first article introduces Niimpy, an open-source Python toolbox for analyzing behavioral data. The second article outlines a datadriven workflow that facilitates research and improves its generalizability. The third article examines how accurately digital phenotyping, using smartphone-sensed data, can assess depression severity. The fourth article inspects the feasibility of digital phenotyping by analyzing the behavioral differences between the healthy control and patient cohorts. The fifth article explores the inherent variability in depressive symptomology and associated mobile-sensed behaviors. Taken together, these articles provide standardized tools and data analysis pipelines that facilitate behavioral data analysis, thereby lowering the barrier to entry into digital phenotyping research. This thesis proposes concrete, actionable guidelines for improving research replicability and reproducibility through the use of analysis workflows. The work demonstrates that machine learning models, using digital phenotyping data, can predict future depression severity. In addition, the feasibility of using smartphone data is supported by both study groups, healthy controls and patients diagnosed with depression, providing behavioral data with no differences in participation adherence or data quantity. Finally, the thesis demonstrates how behavioral differences, both between and within the participants diagnosed with depression, are connected with their self-reported symptoms. To conclude, this thesis advances digital phenotyping research by introducing tools and workflows to facilitate analysis. Furthermore, by building on previous work in the field, the thesis contributes to the research by presenting research outcomes obtained through the analysis of depressive outpatient behavioral data.
Modifying the structure of microcrystalline cellulose by different drying methods and mechanical treatments
(2026) Lähdeniemi, Annina
School of Chemical Engineering | Doctoral thesis (article-based) | Defence date: 2026-02-13
Recently, wood-derived cellulosic micro- and nanomaterials have shown significant potential for pulp and paper technology. However, their adoption and commercialization have not progressed as expected. Therefore, there is currently an increasing research interest in using cellulosic micro- and nanomaterials in various industries outside pulp- and papermaking, such as pharmaceuticals, cosmetics and the food industry. Microcrystalline cellulose (MCC) is a purified, partially depolymerized nonfibrous form of cellulose, a crystalline powder composed of porous particles. MCC (holding E-code E460i) as such is safe for oral consumption for both human and animal purposes. Reflecting MCC's multiple current applications and future potential, it is important to further investigate the possibility of producing MCC with different cross-sectional shapes to increase the surface area due to its great importance for specific applications. Microfibrillated cellulose (MFC), that can be produced from MCC, consists of microfibril bundles forming a weblike fiber network and providing its multiple uses as thickeners, emulsifiers or additives in food, paints, and coatings, as well as cosmetics and medical products. In addition, MFC is ideal as a reinforcement in composites and, concurrently, to reduce the utilization of petroleum-based components. The modification of the never-dried form of MCC with novel techniques and thus producing new types of micro-sized cellulose products, are the focus of this doctoral research. Firstly, the study investigated the drying of the never-dried MCC with two different solids contents using three different drying methods: high-velocity cyclone drying, spray drying, and fluidized bed drying (Paper 1). The effects of these drying techniques on the geometrical dimensions and morphology of the dried MCC particles and aggregates were studied. The results revealed that the morphology of the dried MCC was highly dependent on the initial raw material properties and the liquid removal mechanism during drying. Fluidized bed drying best preserved the original MCC morphology, yielding discrete particles with high surface area and less aggregation. Spray drying produced small, circular particles with homogeneous size distributions, while high-velocity cyclone drying resulted in the largest, most heterogeneous, and irregularly shaped particles and aggregates. Secondly, the study focused on the production of MFC-hydrogels from never-dried MCC using high-pressure mechanical treatment (Paper 2) and later with a Masuko laboratory grinder with different refining degrees (Paper 3). The effects of the treatments on the crystalline structure, morphology, geometrical dimensions, specific surface area, and rheological properties of the resulting MFC gel were analyzed. Results indicated that both mechanical processes produced partially detached crystalline areas, increasing surface area and porosity, leading to the formation of more stable MFC hydrogels due to enhanced hydrogen bonding between cellulose particles. Additionally, using never-dried MCC as a raw material in refining resulted in a stronger MFC gel with superior storage and loss moduli compared to the ones produced with pre-dried MCC. Specific energy consumption data from Masuko grinder also indicated that mechanical energy is more effectively transferred to the never-dried MCC structure, suggesting that energy can be saved when producing MFC from never-dried MCC via refining.