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  • Kuivaniemi, Esa (2024)
    Machine Learning (ML) has experienced significant growth, fuelled by the surge in big data. Organizations leverage ML techniques to take advantage of the data. So far, the focus has predominantly been on increasing the value by developing ML algorithms. Another option would be to optimize resource consumption to reach cost optimality. This thesis contributes to cost optimality by identifying and testing frameworks that enable organizations to make informed decisions on cost-effective cloud infrastructure while designing and developing ML workflows. The two frameworks we introduce to model Cost Optimality are: "Cost Optimal Query Processing in the Cloud" for data pipelines and "PALEO" for ML model training pipelines. The latter focuses on estimating the training time needed to train a Neural Net, while the first one is more generic in assessing cost-optimal cloud setup for query processing. Through the literature review, we show that it is critical to consider both the data and ML training aspects when designing a cost-optimal ML workflow. Our results indicate that the frameworks provide accurate estimates about cost-optimal hardware configuration in the cloud for ML workflow. There are deviations when we dive into the details: our chosen version of the Cost Optimal Model does not consider the impact of larger memory. Also, the frameworks do not provide accurate execution time estimates: PALEO estimates our accelerated EC2 instance to execute the training workload with half of the time it took. However, the purpose of the study was not to provide accurate execution or cost estimates, but we aimed to see if the frameworks estimate the cost-optimal cloud infrastructure setup among the five EC2 instances that we chose to execute our three different workloads.
  • Hämäläinen, Nette (2024)
    Tutkielman tavoitteena oli selvittää, minkälaisia virheitä lukiolaiset tekevät kertolaskusäännön tehtävissä sekä tutkia, tunnistavatko he toisistaan riippuvat ja riippumattomat tapahtumat. Aihetta on tärkeä tutkia, sillä kertolaskusääntö on yksi todennäköisyyden laskusäännöistä ja luo siten perustan todennäköisyyksien laskuille. Tutkielma alkaa teoriaosuudella, jossa ensiksi käydään läpi todennäköisyyslaskennan teoriaa ja tämän jälkeen virheiden sekä virhekäsitysten teoriaa. Teoriaosuuden jälkeen esitellään lyhyesti pitkän matematiikan ylioppilaskoe. Tutkimuksessa käydään läpi viisi pitkän matematiikan ylioppilaskokeen tehtävää ja ne analysoidaan. Työn lopuksi esitellään tehtäväpaketti tukemaan kertolaskusäännön opiskelua. Tutkimustuloksista havaittiin, että yleisimmät kertolaskusäännön virheet johtuivat vaikeuksista erottaa toisistaan riippuvat ja riippumattomat tapahtumat toisistaan. Virheistä noin 14% johtui tästä. Toinen yleinen virhe, mikä tuloksista nousi esille, oli sekaannukset kerto- ja yhteenlaskusäännön välillä. Virheistä noin 9% johtui tästä. Opettajan on tärkeä tiedostaa nämä yleiset virhetyypit, jotta voi osaltaan ennaltaehkäistä niiden syntymistä.
  • Hämäläinen, Jussi (2024)
    In this thesis, we aim to introduce the reader to profinite groups. Profinite groups are defined by two characteristics: firstly, they have a topology defined on them (notably, they are compact). Secondly, they are constructed from some collection of finite groups, each equipped with a discrete topology and forming what is known as an inverse system. The profinite group emerges as an inverse limit of its constituent groups. This definition is, at this point, necessarily quite abstract. Thus, before we can really understand profinite groups we must examine two areas: first, we will study topological groups. This will give us the means to deal with groups as topological spaces. Topological groups have some characteristics that differentiate them from general topological spaces: in particular, a topological group is always a homogeneous space. Secondly, we will explore inverse systems and inverse limits, which will take us into category theory. While we could explain these concepts without categories, this thesis takes the view that category theory gives us a useful “50000-feet view” by giving these ideas a wider mathematical context. In the second chapter, we will go through preliminary information concerning group theory, general topology and category theory that will be needed later. We will begin with some basic concepts from group theory and point-set topology. These sections will mostly contain information that is familiar from the introductory university courses. The chapter will then continue by introducing some basic concepts of category theory, including inverse systems and inverse limits. For these, we will give an application by showing how the Cantor set is homeomorphic to an inverse limit of a collection of finite sets. In the third chapter, we will examine topological groups and prove some of their properties. In the fourth chapter, we will introduce an example of profinite groups: Zp, the additive group of p-adic integers. This will be expanded into a ring and then into the field Qp. We will discuss the uses of Zp and Qp and show how to derive them as an inverse limit of finite, compact groups.
  • Niska, Päivö (2024)
    This thesis delves into the complex world of multi-model database migration, investigating its theoretical foundations, strategic implementation, and implications for modern data management. The research utilizes a mixed-methods approach, combining quantitative benchmarking tests with qualitative insights from industry practitioners to give a comprehensive knowledge of the migration process. The importance of smart migration techniques, as well as the crucial function of schema mapping in assuring data consistency are highlighted as key results. Success examples from a variety of industries highlight the practical relevance and advantages of multi-model database migration, while implications for theoretical advances and practical issues in organizational contexts are discussed. The strategic implementation framework leads businesses via rigorous project planning, schema mapping, and iterative optimization, stressing the joint efforts of multiple stakeholders. Future concerns include the influence of developing technologies, the dynamic interaction between migration and data security, and industry-specific subtleties impacting migration tactics as the technological environment advances. The synthesis of ideas leads to a common knowledge base, defining the data management strategy discourse. This investigation serves as a road map for informed decision-making, iterative optimization, and continual adaptation in database management, developing a better knowledge of multi-model database migration in the context of modern data ecosystems.
  • Pesonen, Linda (2024)
    Grass biomass has many important and diverse roles for ecosystems functioning, the carbon cycle, rangeland productivity and local livelihoods. Quantifying and understanding grass biomass in dynamic savanna ecosystems during dry season is important for sustainable land management and monitoring grazing pressures, especially amidst climate change. Traditional ground-based methods to assess vegetation are subjective and time consuming, while remote sensing provides efficiency in monitoring grass biomass at large scales. Grass biomass assessments using remote sensing data have been extensively conducted worldwide, but such research in African savannas remains rare. This study aimed to study connections between dry season grass biomass measured in savanna rangelands and airborne hyperspectral imagery data obtained simultaneously in LUMO Conservancy area of South-Eastern Kenya. Two modelling techniques were compared: averaged plot values (n=24) and individual sample values (n=96). Three vegetation indices (RSI, NDSI, RDSI) were computed and Generalised Additive Models (GAM) were applied to portray the relationship between measured grass biomass and VIs. The highest explanatory power for both modelling techniques was found with RSI and NDSI indices with averaged plot level values having the highest performance (D2 = 0.79, RMSE = 40.15 g/m2), with the band combination of B78 and B43 (908 nm / 667 nm). The best performing vegetation index (RSI) was used to predict grass biomass in the study area, which indicated a biomass range of 0 to 2894 g/m2. The study highlights the potential of using hyperspectral imagery to assess grass biomass in the savanna environments. However, challenges and limitations were faced related to the heterogeneous nature of savannas, varying weather conditions affected by rainfall, the temporal limits of the study, and disturbances in spectral information caused by heavily grazed areas, dead material, and preprocessing techniques. It is suggested that future research considers these factors by incorporating a broader set of variables, extending the duration of the study, exploring various preprocessing techniques, increasing the sample size, and employing additional data sources, such as active sensors and hyperspectral satellite imagery, to enhance model performance and improve accuracy.
  • Pekkala, Minttu (2024)
    There has been a major decreasing trend in the amount of sea ice in the Arctic since the 1990s. The Arctic amplification (AA) warms the Arctic climate as a result of the global warming, strengthened by the ice albedo feedback loop. The ice albedo feedback loop is caused by melting of snow and ice surfaces. Melting of snow and ice causes changes to the surface albedo, which is a measure of the amount of incident solar radiation that is reflected. Melting snow and ice surface types and revealed open water or terrain have significantly lower albedo than the original snow and ice surfaces. Therefore more radiation is absorbed, which has a warming effect. CLARA-A3 dataset is analyzed in this thesis. Surface albedo (SAL) and top of atmosphere (ToA) albedo values are compared. Data from June and July of the years 2012 and 2014 are analyzed. The objective is to check the consistency of these data records. The surface albedo values are also modelled with the Simplified Model for Atmospheric Correction (SMAC) to further validate the data. The relationship between SAL and ToA is also studied. This is achieved by analysing snow and ice optical properties, interaction of solar radiation with Earth’s atmosphere and the effect of illumination and viewing geometry. The results of data analysis indicate consistency between the observed values for SAL and ToA albedo differences within the observed period. The results are also in line with predictions made based on previous studies on the seasonal trends in the Arctic albedo. Furthermore results modelled with SMAC show dependency with the observed results and thereby validate the data. However data from June 2012 and July 2014 are unfortunately contaminated, which means that there are less usable data and therefore of reduced accuracy. Data analysis conducted for a larger SAL and ToA dataset would be needed to provide a basis for studying the decadal and seasonal trend of the Arctic SAL and ToA albedo difference. The whole melting season beginning in March and ending in September is important to study to better understand seasonal variability and trends as well as decadal trends in the Arctic.
  • Lempiäinen, Hanna (2024)
    Particle dark matter (DM) as a solution to the missing mass problem in astronomy has been examined widely and with different models. Among the most studied are weakly interacting massive particles, WIMPs, for short. As dark matter constitutes roughly a quarter of the energy budget of the universe, and due to its vital role in galaxy structures through gravitational interaction, the motivation to uncover the nature and properties of it is strong. In this master’s thesis, a specific particle dark matter model is examined. The model consists of a hidden dark sector added to the Standard Model of Particle Physics (SM). The dark sector introduces a new SU(2) gauge field that acts as a vector dark matter candidate, as well as a complex SU(2) scalar field and interactions between the two. Due to spontaneous symmetry breaking, the dark vector gains a non-zero mass. This relocation of degrees of freedom allows us to write the dark scalar field as having only one real degree of freedom. The dark scalar field also experiences mass mixing with the SM Higgs field, leaving the two propagating scalar mass eigenstates as superpositions of the dark scalar field and the Higgs field. One of these is then identified as the observed Higgs field with a mass of 125 GeV. The four free parameters of the model can be chosen as the masses of the dark matter candidate and the propagating dark scalar field, the angle of the rotation between mass and gauge eigenbasis in the scalar sector and the dark gauge coupling constant. To produce the observed relic density of dark matter, the DM particles need to pair-annihilate with a cross section of order 1.64 × 10^(−9) GeV^(−2). Further constraints are given by collider and direct detection experiments, leaving the parameter space of the model rather constrained. Depending on the values of the other free parameters, a viable mass range of around 100-200 GeV is found for the vector dark matter. The possibility of probing the properties of dark matter through experiments and observations exists. The existence and properties of the dark scalar field could be examined in the Large Hadron Collider. Possible phenomena in the scalar sector of the model, such as phase transitions, could be studied with upcoming gravitational wave detectors, namely the Laser Interferometer Space Antenna. Direct detection experiments provide a way of seeking the dark matter particle itself. With all these possibilities, the future seems interesting.
  • Hotari, Juho (2024)
    Quantum computing has an enormous potential in machine learning, where problems can quickly scale to be intractable for classical computation. Quantum machine learning is research area that combines the interplay of ideas from quantum computing and machine learning. Powerful and useful machine learning is dependent on having large-scale datasets used to train the models to be able to solve real-life problems. Currently, quantum machine learning lacks a plethora of large-scale quantum datasets required to further develop the models and test the quantum machine learning algorithms. Lack of large datasets is currently limiting the quantum advantage in the field of quantum machine learning. In this thesis, the concept of quantum data and different types of applied quantum datasets used to develop quantum machine learning models is studied. The research methodology is based on a systematic and comparative literature review of the state of the art articles in quantum computing and quantum machine learning in the recent years. We classify datasets into inherent and non-inherent quantum data based on the nature of the data. The preliminary literature review addresses patterns in the applied quantum machine learning. Testing and benchmarking QML models primarily uses non-inherent quantum data, or classical data encoded into the quantum system, while separate research is focused on generating inherent quantum datasets.
  • Vartiainen, Pyörni (2024)
    Sums of log-normally distributed random variables arise in numerous settings in the fields of finance and insurance mathematics, typically to model the value of a portfolio of assets over time. In particular, the use of the log-normal distribution in the popular Black-Scholes model allows future asset prices to exhibit heavy tails whilst still possessing finite moments, making the log-normal distribution an attractive assumption. Despite this, the distribution function of the sum of log-normal random variables cannot be expressed analytically, and has therefore been studied extensively through Monte Carlo methods and asymptotic techniques. The asymptotic behavior of log-normal sums is of especial interest to risk managers who wish to assess how a particular asset or portfolio behaves under market stress. This motivates the study of the asymptotic behavior of the left tail of a log-normal sum, particularly when the components are dependent. In this thesis, we characterize the asymptotic behavior of the left and right tail of a sum of dependent log-normal random variables under the assumption of a Gaussian copula. In the left tail, we derive exact asymptotic expressions for both the distribution function and the density of a log-normal sum. The asymptotic behavior turns out to be closely related to Markowitz mean-variance portfolio theory, which is used to derive the subset of components that contribute to the tail asymptotics of the sum. The asymptotic formulas are then used to derive expressions for expectations conditioned on log-normal sums. These formulas have direct applications in insurance and finance, particularly for the purposes of stress testing. However, we call into question the practical validity of the assumptions required for our asymptotic results, which limits their real-world applicability.
  • Pirilä, Pauliina (2024)
    This thesis discusses short-term parking pricing in the context of Finnish shopping centre parking halls. The focus is on one shopping centre located in Helsinki where parking fees are high and there is a constant need for raising the prices. Therefore, it is important to have a strategy that maximises parking hall income without compromising the customers' interest. If the prices are too high, customers will choose to park elsewhere or reduce their parking in private parking halls. There is a lot of competition with off-street parking competing against on-street parking and access parking, not to mention other parking halls. The main goal of this thesis is to raise problems with parking pricing and discuss how to find the most beneficial pricing method. To achieve this, this thesis project conducted an analysis on one Finnish shopping centre parking hall data. This data was analysed to discover the average behaviour of the parkers and how the raised parking fees affect both the parker numbers and the income of the parking hall. In addition, several pricing strategies from literature and real-life examples were discussed and evaluated, and later combined with the analysis results. The results showed that there are some similarities with results from literature but there were some surprising outcomes too. It seems that higher average hourly prices are correlated with longer stays, but still the parkers who tend to park longer have more inelastic parking habits than those who park for shorter durations. The calculated price elasticity of demand values show that compared to other parking halls, parking is on average more elastic in the analysed parking hall. This further emphasises the importance of milder price raises at least for the shorter parking durations. Moreover, there are noticeable but explainable characteristics in parker behaviour. Most of the parkers prefer to park for under one hour to take advantage of the first parking hour being free. This leads to profit losses in both the shopping centre and parking hall income. Therefore, a dynamic pricing strategy is suggested as one pricing option, since it adjusts the prices automatically based on occupancy rates. Although there are some challenges with this particular method, in the long run it could turn out to be the most beneficial for both the parking hall owners and the parkers. To conclude, choosing a suitable pricing strategy and model for a parking hall is crucial and the decisions should be based on findings from data.
  • Rintaniemi, Ari-Heikki (2024)
    In this thesis a Retrieval-Augmented Generation (RAG) based Question Answering (QA) system is implemented. The RAG framework is composed of three components: a data storage, a retriever and a generator. To evaluate the performance of the system, a QA dataset is created from Prime minister Orpo's Government Programme. The QA pairs are created by human and also generated by using transformer-based language models. Experiments are conducted by using the created QA dataset to evaluate the performance of the different options to implement the retriever (both traditional algorithmic and transformer-based language models) and generator (transformer-based language models) components. The language model options used in the generator component are the same which were used for generating QA pairs to the QA dataset. Mean reciprocal rank (MRR) and semantic answer similarity (SAS) are used to measure the performance of the retriever and generator component, respectively. The used SAS metric turns out to be useful for providing an aggregated level view on the performance of the QA system, but it is not an optimal evaluation metric for every scenario identified in the results of the experiments. Inference costs of the system are also analysed, as commercial language models are included in the evaluation. Analysis of the created QA dataset shows that the language models generate questions that tend to reveal information from the underlying paragraphs, or the questions do not provide enough context, making the questions difficult to answer for the QA system. The human created questions are diverse and thus more difficult to answer compared to the language model generated questions. The QA pair source affects the results: the language models used in the generator component receive on average high score answers to QA pairs which they had themselves generated. In order to create a high quality QA dataset for QA system evaluation, human effort is needed for creating the QA pairs, but also prompt engineering could provide a way to generate more usable QA pairs. Evaluation approaches for the generator component need further research in order to find alternatives that would provide an unbiased view to the performance of the QA system.
  • Ojasalo, Amanda (2024)
    Climate change and urbanization are among the largest environmental challenges facing the world today. The role of vegetation in urban environments is substantial from the perspectives of climate, ecology, and human-wellbeing. Plant phenology plays a key role in the functionality and feedbacks related to these ecosystem services and the characteristics of urban phenology can considerably differ from rural areas due to Urban Heat Island (UHI), vegetation composition, hydrological changes, light pollution, and air pollutants. Several previous studies using coarse resolution remote sensing data have reported longer Growing Season Length (GSL) in urban areas compared to their rural counterpart and the UHI effect is generally considered as the main driver for these differences. However, urban phenology studies have not been implemented on a regional European scale and high-resolution remote sensing data is needed to understand the characteristics of heterogenous and sparse urban vegetation. Therefore, the objectives of this study were (1) to analyse GSL along the urban-rural gradients in 38 European capital cities using Copernicus HR-VPP phenology dataset on a 10-meter spatial resolution, (2) to analyse GSL along the urban-rural gradient between the 38 European capital cities, and (3) to find out how Land Surface Temperature (LST), land cover and dominant leaf type influence on the GSL variation. The GSL pattern along the urban-rural gradients were classified into six categories based on linear and quadratic fits. The results showed that the GSL along the gradient in European capital cities is highly variate. It shortens along the gradient in 8 cities and the urban GSL is longer in 26 cities when compared to the overall surrounding zone, contradictory to the general outcome of previous studies. The influence of LST, land cover and dominant leaf type was examined with a Geographically Weighted Regression (GWR) model which considers the spatial nonstationary of variables. The final GWR model variables included LST, the proportion of urban land cover above 30 % of sealed surface and the proportion of broadleaved trees which all had spatially varying and nonlinear influences on GSL. These results and the variate gradient patterns suggest that despite the significance of LST, GSL variation along the urban-rural gradient is more driven by changes in land cover and vegetation characteristics. Spatial modelling techniques are needed to understand these locally varying relationships. There are several potential methodological and site-related explanations for the divergent findings of this and previous studies. The key methodological difference is the better spatial resolution which improves the accuracy of GSL detection, agricultural land cover masking and urban area definition. Site-related explanations include the different background climate and vegetation types, urban vegetation composition and species, and urbanization intensity. In addition, several heatwaves took place during the study period potentially contributing to the early senescence of urban vegetation. This study highlights the need for a high-resolution remote sensing data when analysing urban vegetation phenology and provides new information about the complex dynamics of urban phenology in general level and in European capital cities. These results can be beneficial for developing sustainable cities where urban vegetation plays a key role in adapting and mitigating climatic, ecological, and societal challenges.
  • Leppiniemi, Salla-Sofia (2024)
    Kaupungistuminen on nopea ilmiö maailmanlaajuisesti. Kaupungistuminen johtaa myös muutoksiin maankäytössä, mikä usein näkyy kaupunkien tiivistymisenä viherrakenteen kustannuksella. Viherrakenteen ilmalaatuun liittyvistä vaikutuksista on tehty paljon tutkimusta, mutta tutkimuksien tulokset aiheesta ovat ristiriitaisia. Maisterintutkielma käsittelee viherrakenteen vaikutuksia ilmanlaatuun kaupungeissa. Työ pyrkii kartoittamaan mitkä taustalla olevat tekijät vaikuttavat viherrakenteen ilmanlaadullisiin seurauksiin. Lisäksi työ tarkastelee voiko tuloksia soveltaa suomalaiseen kaupunkisuunnitteluun ja jos voi niin millä tavoin. Tutkielma suoritetaan käyttäen systemaattista kirjallisuuskatsausta, joka tiivistää ja arvioi jo valmiina olevaa tutkimusaineistoa sekä kartoittaa epävarmuusalueita. Kokoavan tutkimuksen avulla voidaan selvittää ovatko tutkimusten tulokset esimerkiksi yhteneviä sen osalta, että viherrakennetta kannattaa integroida kaupunkeihin ilmaa puhdistavan vaikutuksen takia Tutkielman aineistona toimii hakulausein sekä sisäänotto- ja poissulkukriteerein huolellisesti ja kriittisesti valitut tieteelliset tutkimukset. Tutkielmaan valikoitui 51 alkuperäistutkimusta. Aineiston analyysissä käytettiin sisällönanalyysiä, joka tarjoaa mahdollisuuden tarkastella asioiden välisiä yhteyksiä, yhtäläisyyksiä ja eroavaisuuksia. Valikoidut tutkimukset koottiin tiivistetysti taulukkoon tutkimuksen läpinäkyvyyden lisäämiseksi. Aineiston sisällönanalyysin perusteella käy ilmi, että viherrakenteen vaikutus kaupunkien ilmanlaatuun on pääosin positiivinen. Neljännes tutkimuksista viittaa siihen, että sillä voi olla myös ilmanlaatua heikentäviä vaikutuksia. Erityisesti viherseinillä ja -katoilla havaitaan eniten ilmanlaatua parantavia ominaisuuksia. Toiseksi tulevat puut, pensaat ja nurmi, ja kolmanneksi suuremmat viheralueet kuten metsät ja puistot. Viherseinät ja -katot aiheuttavat vähiten haitallisia vaikutuksia, kun taas suurimmat haitat liittyvät puihin, pensaisiin ja nurmikkoon. Tulosten vaihtelevuus johtuu erilaisista tutkimusmenetelmistä, tutkimusajankohdista, ilmastollisista olosuhteista, vuodenaikojen vaihtelusta, ilmansaastepitoisuuksista alueella, vuorokaudenajoista, kasvuston sijainnista, viherrakennetyypistä sekä kasvilajeista. Tulosten soveltaminen suomalaiseen viherrakentamiseen on haastavaa, sillä tutkimusten ilmasto-olosuhteet eroavat merkittävästi Suomen oloista. Samankaltaisiin suomalaisiin olosuhteisiin valikoitujen tutkimusten mukaan viherkattojen ja puistojen suosiminen kaupunkirakenteessa, metsien säilyttäminen vilkkaampien teiden varrella ja viherseinien hyödyntäminen katujen varsilla voivat osittain parantaa ilmanlaatua.
  • Ahtinen, Sini-Maaria (2024)
    Asukkaiden tyytyväisyyttä omaan asuinalueeseensa pidetään yhtenä yleisimmistä asuinalueiden laatua tarkastelevista mittareista. Asumistyytyväisyys on myös liitetty oleelliseksi osaksi ihmisen yleistä elämänlaatua ja asuinympäristöä voidaan pitää ihmisen arkielämän tärkeimpänä elinympäristön osa-alueena. Tässä tutkielmassa tutkimuskohteena olivat lähiöissä asuvien henkilöiden asumistyytyväisyys. Lähiöt ovat oleellinen osa suomalaista kaupunkikuvaa ja Suomessa lähiöiden, ja niissä asuvien ihmisten määrä on merkittävä. Kun puhutaan tyytyväisyydestä, niin puhutaan ihmisten subjektiivisesta kokemuksesta. Tutkittaessa aihetta, joka on ihmisten subjektiivisista kokemuksista riippuvainen, luo se tutkimukselle omat haasteensa. On tiedossa, että ihmisillä on suuria eroja siinä, kuinka he pystyvät ilmaisemaan epämukavuutta sekä tyytyväisyyttä. Kun siis tehdään tutkimusta, jossa tyytyväisyyden mittarina käytetään henkilön subjektiivista arviota, tulokset perustuvat siihen olettamukseen, että ihmisten omat arviot elämästään ja tyytyväisyyden tasostaan ovat luotettavia mittareita. Tämän tutkielman tavoitteena on selvittää, millä tekijöillä on yhteys suomalaisissa lähiöissä asuvien henkilöiden asumistyytyväisyyteen. Tutkimuksen aineistona toimii Helsingin yliopiston ja Suomen Akatemian rahoittaman PREFARE-hankkeen (2012–2015) aikana hankittu aineisto. Aineistoon on kyselydatan lisäksi yhdistetty vastaajien sijainnin perusteella kontekstuaalista rekisteritietoa, jotka saatiin ruututietokannasta. Aineisto on siis kaksitasoinen, yksilötaso, jossa vastaajia oli 7728 ja lähiötaso, jossa alueita oli 71. Aineiston analyysimenetelmänä toimi monitasoinen lineaarinen regressiomalli, jonka avulla pystyttiin analysoimaan monitasoista aineistoa. Analyysissä aineistosta luotiin asumistyytyväisyyttä kuvaava tyytyväisyysmuuttuja ja tutkielmassa tarkasteltiin aluetasonmuuttujien, yksilötason taustamuuttujien ja asuinympäristön kokemiseen liittyvien muuttujien yhteyksiä tähän tyytyväisyysmuuttujaan. Tutkielman oleellisin tulos oli maineen merkitys asumistyytyväisyyteen. Aluetason muuttujien yhteydet tyytyväisyysmuuttujaan kulkivat hyvin vahvasti mainemuuttujan kautta ja maineella oli myös tarkasteltavista muuttujista vahvin yhteys tyytyväisyyteen. Maineen lisäksi kaksi muuta kokemusmuuttujaa, turvallisuus ja naapurisuhteet olivat hyvin vahvassa yhteydessä asumistyytyväisyyden kanssa. Yksilötason taustamuuttujista vahvimmat yhteydet tyytyväisyysmuuttujaan olivat tulotasolla, iällä ja asunnon hallintamuodolla.
  • Skog, Robert (2024)
    The Venusian atmosphere has everything to be an exciting natural sulfur laboratory. In addition to relatively high concentrations of sulfur dioxide, suitable conditions in the atmosphere make both thermo- and photochemical reactions possible, allowing for complex chemical reactions and the formation of new sulfur containing compounds. These compounds could explain or contribute to the enigmatic 320-400 nm absorption feature in the atmosphere. One of the proposed absorbers is polysulfur compounds. While some experimentally obtained UV-VIS spectra have been published, studying the different polysulfur species individually is extremely difficult due to the reactive nature of sulfur. In this thesis UV-VIS spectra for polysulfur species S2 to S8 were simulated using the nuclear ensemble approach to determine if they fit the absorption profile. In total, 38 polysulfur species were considered. All were optimized at the wB97X-D/aug-cc-pV(T+d)Z level of theory, with the S2, S3, and S4 structures also being optimized at the CCSD(T)/aug-cc-pV(T+d)Z level of theory. For 13 structures UV-VIS spectra were simulated using a nuclear ensemble of 2000 geometries, with vertical excitations calculated at the EOM-CCSD/def2-TZVPD or the wB97X-D/def2-TZVPD levels of theory. The simulated UV-VIS spectra for the smaller species were in quite good agreement with experimental ones. Two different molecules were identified with substantial absorption cross sections in the range of the unknown absorber: The open chain isomer of S3 (3.78×10^-17 cm^2 at 370 nm), and the trigonal isomer of S4 (4.76×10^-17 cm^2 at 360 nm). However, the mixing ratios of these species in the Venusian atmosphere are also needed to make a more conclusive statement. Other polysulfur compounds have insignificant absorption cross sections in the 320-400 nm range and can therefore be excluded. The calculated absorption cross sections can be used to calculate photolysis rates, which can be straight away added to atmospheric models of Venus. In addition, this work will help future space missions to Venus, for example by focusing their search for the unknown absorber.
  • Mukkula, Olli (2024)
    Quantum computers utilize qubits to store and process quantum information. In superconducting quantum computers, qubits are implemented as quantum superconducting resonant circuits. The circuits are operated only at the two energy states, which form the computational basis for the qubit. To suppress leakage to uncomputational states, superconducting qubits are designed to be anharmonic oscillators, which is achieved using one or more Josephson junctions, a nonlinear superconducting element. One of the main challenges in developing quantum computers is minimizing the decoherence caused by environmental noise. Decoherence is characterized by two coherence times, T1 for depolarization processes and T2 for dephasing. This thesis reviews and investigates the decoherence properties of superconducting qubits. The main goal of the thesis is to analyze the tradeoff between anharmonicity and dephasing in a qubit unimon. Recently developed unimon incorporates a single Josephson junction shunted by a linear inductor and a capacitor. Unimon is tunable by external magnetic flux, and at the half flux quantum bias, the Josephson energy is partially canceled by the inductive energy, allowing unimon to have relatively high anharmonicity while remaining fully protected against low-frequency charge noise. In addition, at the sweet spot with respect to the magnetic flux, unimon becomes immune to first-order perturbations in the flux. The sweet spot, however, is relatively narrow, making unimon susceptible to dephasing through the quadratic coupling to the flux noise. In the first chapter of this thesis, we present a comprehensive look into the basic theory of superconducting qubits, starting with two-state quantum systems, followed by superconductivity and superconducting circuit elements, and finally combining these two by introducing circuit quantum electrodynamics (cQED), a framework for building superconducting qubits. We follow with a theoretical discussion of decoherence in two-state quantum systems, described by the Bloch-Redfield formalism. We continue the discussion by estimating decoherence using perturbation theory, with special care put into the dephasing due to the low-frequency 1/f noise. Finally, we review the theoretical model of unimon, which is used in the numerical analysis. As a main result of this thesis, we suggest a design parameter regime for unimon, which gives the best ratio between anharmonicity and T2.
  • Männistö, Theo (2024)
    The traditional method for identifying sulfate soils has been the incubation method, which typically takes 9-19 weeks. However, in collaboration, the Finnish Environment Institute (SYKE), Geological Survey of Finland (GTK), and Åbo Akademi developed a faster hydrogen peroxide oxidation method for identifying sulfate soils and assessing acidity potential. This method allows for sulfate soil identification and acidity potential estimation in just a few hours. The hydrogen peroxide oxidation method was used to identify sulfate soils in the Helsinki region and to evaluate the method. The study areas included the Sunnuntaipalsta-field area in Malmi, the area associated with the relocation of Gasgrid’s gas pipeline in Pihlajamäki, and the Hermanninranta- Kyläsaari area. Sulfate concentrations determined by the oxidation method were compared with concentrations obtained through water extraction at the Helsinki geophysical, environmental and mineralogical laboratories (Hellabs) of the University of Helsinki's Department of Geology and Geophysics, and acid extraction at ALS Finland Ltd. In Malmi, the method worked well and reliably, indicating naturally acidified soil with relatively low sulfur concentrations. Deeper layers revealed potential acidic sulfate soil materials. In Pihlajamäki, the method was effective, identifying clear potential acidic sulfate soils even with samples consisting of clay fillings. Challenges arose in the Hermanninranta-Kyläsaari area due to contaminated fill soils with high pH values and various hydrocarbons. The lower layers of the samples were rich in organic matter (LOI > 10%), causing the hydrogen peroxide oxidation method to overestimate sulfate concentrations, resulting in deviations with both acid and water extraction results. Based on the results, the hydrogen peroxide oxidation method performs most reliably when loss on ignition (LOI) is < 10% and the pH change (ΔpH) after oxidation is less than 5 units. The method could be a valuable addition to soil investigations conducted by the City of Helsinki's construction services public enterprise, Stara, in their Street and ground laboratory. The method is effective and enables the rapid identification of potential acidic sulfate soils.
  • Joensuu, Matilda (2024)
    In this master’s thesis, linear zwitterionic poly(ethylene imine) methyl-carboxylates (l-PEI-MCs) were synthesized through a four-step synthesis. The synthesis started with the polymerization of 2-ethyl-2-oxazoline (EtOx) monomers into poly(2-ethyl-2-oxazoline) (PEtOx) homopolymers with polymerization degree of 50 and 100. Living cationic ring-opening polymerization (LCROP) enabled a good control over the molecular weights. Subsequently, the side chains of PEtOxs were cleaved off by acidic hydrolysis. This resulted in linear poly(ethylene imine)s (l-PEIs) bearing a secondary amine group in repeating units of the polymer chain. These amine units were then functionalized with methyl-carboxylate moieties by first introducing tert-butyl ester functionalities to l-PEI chains, and subsequently cleaving off the tert-butyl groups. The final polymer is a polyzwitterion, featuring both an anionic carboxylate and a cationic tertiary amine group within a single repeating unit. Polymers produced in each step were characterized via 1H-NMR and FT-IR spectroscopy and their thermal properties were analyzed by differential scanning calorimetry (DSC). The molecular weights and dispersities (Ð) of PEtOx polymers were additionally estimated by gel permeation chromatography (GPC). Via 1H-NMR, the degree of polymerization for PEtOxs and the hydrolysis degree for l-PEIs were determined. FT-IR gave a further insight into the structures of polymers, successfully confirming the ester functionality of modified l-PEI. The disappearance of the tert-butyl proton signal in 1H-NMR spectrum after deprotection verified the successful removal of tert-butyl groups, resulting in the final product with methyl-carboxylate functionalities. By DSC, different thermal transitions, i.e., glass transition (Tg), melting (Tm) and crystallization (Tc), were observed, and the effects of molar mass and polymer modifications on these transitions were being investigated. The state of the art explores the literature regarding synthesis and properties of poly(2-oxazoline)s (POx), poly(ethylene imine)s (PEIs), and polyzwitterions. The theory behind living cationic ring-opening polymerization of 2-oxazolines and acidic hydrolysis of POxs is described. Different post-polymerization modification strategies to functionalize PEIs are being discussed. In addition, possible applications for each of these polymer classes are shortly outlined.
  • Nygren, Henrik (2024)
    The MOOC Center of University of Helsinki maintains a learning management system, primarily used in the online courses offered by the Department of Computer Science. The learning management system is being used in more courses, leading to a need for additional exercise types. In order to satisfy this need, we plan to use additional teams of developers to create these exercise types. However, we would like to minimize any negative effects that the new exercise types may have on the overall system, specifically regarding stability and security. In this work, we propose a plugin system for creating new exercise types, and implement it to production system used by real students. The system's plugins are deployed as separate services and use sandboxed IFrames for their user interfaces. Communication with the plugins occurs through the use of HTTP requests and message passing. The designed plugin system fulfilled its aims and worked in its production deployment. Notably, it was concluded that it is challenging for plugins to disrupt the host system. This plugin system serves as an example that it is possible to create a plugin system where the plugins are isolated from the host system.
  • Oksa, Ella (2024)
    Sobolev functions generalize the concept of differentiability for functions beyond classical settings. The spaces of Sobolev functions are fundamental in mathematics and physics, particularly in the study of partial differential equations and functional analysis. This thesis provides an overview of construction of an extension operator on the space of Sobolev functions on a locally uniform domain. The primary reference is Luke Rogers' work "A Degree-Independent Sobolev Extension Operator". Locally uniform domains satisfy certain geometric properties, for example there are not too thin cusps. However locally uniform domains can possess highly non-rectifiable boundaries. For instance, the interior of the Koch snowflake represents a locally uniform domain with a non-rectifiable boundary. First we will divide the interior points of the complement of our locally uniform domain into dyadic cubes and use a collection of the cubes having certain geometric properties. The collection is called Whitney decomposition of the locally uniform domain. To extend a Sobolev function to a small cube in the Whitney decomposition one approach is to use polynomial approximations to the function on an nearby piece of the domain. We will use a polynomial reproducing kernel in order to obtain a degree independent extension operator. This involves defining the polynomial reproducing kernel in sets of the domain that we call here twisting cones. These sets are not exactly cones, but have some similarity to cones. Although a significant part of Rogers' work deals extensively with proving the existence of the kernel with the desired properties, our focus will remain in the construction of the extension operator so we will discuss the polynomial reproducing kernel only briefly. The extension operator for small Whitney cubes will be defined as convolution of the function with the kernel. For large Whitney cubes it is enough to set the extension to be 0. Finally the extension operator will be the smooth sum of the operators defined for each cube. Ultimately, since the domain is locally uniform the boundary is of measure zero and no special definition for the extension is required there. However it is necessary to verify that the extension "matches" the function correctly at the boundary, essentially that their k-1-th derivatives are Lipschitz there. This concludes the construction of a degree independent extension operator for Sobolev functions on a locally uniform domain.