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Atomic force microscopy (AFM) is a widely utilized characterization method capable of capturing atomic level detail in individual organic molecules. However, an AFM image contains relatively little information about the deeper atoms in a molecule and thus interpretation of AFM images of non-planar molecules offers significant challenges for human experts. An end-to-end solution starting from an AFM imaging system ending in an automated image interpreter would be a valuable asset for all research utilizing AFM. Machine learning has become a ubiquitous tool in all areas of science. Artificial neural networks (ANNs), a specific machine learning tool, have also arisen as a popular method many fields including medical imaging, self-driving cars and facial recognition systems. In recent years, progress towards interpreting AFM images from more complicated samples has been made utilizing ANNs. In this thesis, we aim to predict sample structures from AFM images by modeling the molecule as a graph and using a generative model to build the molecular structure atom-by-atom and bond-by-bond. The generative model uses two types of ANNs, a convolutional attention mechanism to process the AFM images and a graph neural network to process the generated molecule. The model is trained and tested using simulated AFM images. The results of the thesis show that the model has the capability to learn even slight details from complicated AFM images, especially when the model only adds a single atom to the molecule. However, there are challenges to overcome in the generative model for it to become a part of a fully capable end-to-end AFM process.

Around the world, cities are using branding as a discursive and strategic practice to adjust to intensified, ongoing competition of tourists, investments, events and skilled labour. Simultaneously, in the era of the societal turning point, sustainability issues have become a global topic, and cities have begun to brand themselves as ‘pioneer’ in sustainability. Gradually, place branding’s potential as a strategic instrument of urban development and change has been understood, and therefore, it is increasingly applied in urban governance. This thesis focuses on this change in place branding and explores the relationship between place branding and sustainable development in the context of Helsinki’s branding. More specifically, I study how place branding can be harnessed as a transformative and strategic tool to further sustainable urban development. The theoretical foundation is built on place branding literature that takes into consideration the diverse and transformative role of place branding. I reinforce the place branding theory with the concept of imaginary, which are visions of the future utilised to steer decision-making and further policies. The imaginaries can act as technologies of governance, through which cities delegate responsibility for the citizens to guide them towards a specific aim, for instance, ‘Sustainable Helsinki’. My research data consists of strategies and a website produced by the City of Helsinki. The material addresses sustainable development and the City’s branding cuts through all content. I analyse the content through frame analysis to find how Helsinki frames itself in terms of sustainable development and if any imaginaries attempt to steer the citizens to take responsibility for their sustainability actions. My research findings confirm the increasingly common perception in place brand research according to which place branding can be used as a comprehensive strategic tool in urban development. In Helsinki, place branding has moved over from mere city marketing towards a governance strategy whose objective is to both manage perceptions about places and shape the place according to the city strategies or policies. Also, what stood out was the emphasis on economic sustainability, which was visible even in sections that addressed the other two dimensions – environmental or social. This finding highlights how Helsinki’s branding is heavily influenced by the common narratives of economic success and international competition. Central findings in my research were that Helsinki uses competitive and cooperative ways of portraying itself in sustainable development and succeeding in global competition. In both of these frames, Helsinki uses imaginaries of ‘Sustainable Helsinki’, but in different ways. In the competitive tone of voice, the delegation of responsibility is more implying and indirect since the focus is on the objective, not the process. In cooperative framing, the imaginaries are more straightforwardly asserting responsibility to people and businesses. My research shows that there are several ways to guide people through place branding, but in Helsinki’s case, the city is appealing to the freedom and independence of its locals.

This master’s thesis is a case study about the perspectives that the mobile youth in the Nairobi region have in their roles in the changing world. The study begins with an assumption that the hegemonic narrative of the modern nation-state is being challenged in the globalizing world. It focuses on the worldviews and identities of the youth who have previously been awarded with a scholarship in the United States via Kennedy-Lugar Youth Exchange and Study (YES) program and currently influence in the Nairobi region. Place and citizenship are used as central theoretical concepts in the study. A multimethod design of qualitative approaches was used to conduct the empirical part of the research. The primary data was collected from the Nairobi region YES alumni by semi-structured interviews, observation and a focus group session. In addition, an expert interview was conducted and public reports regarding the subject of the research were used as secondary data. The data was analyzed with Atlas.ti software, combining coding and qualitative content analysis. The main findings of the study state that the YES alumni are globally oriented mobile and flexible citizens who identify with multiple groups and places. They sense belonging to Kenya but also identify as global citizens. Values that emerge during the research are especially related to learning and experiencing, benevolence and being successful. The youth aim to develop skills that respond to the challenges presented by globalization. In addition, the participants describe the exchange experience in the United States as an important factor that has changed the course of their lives in one way or another. As a conclusion it can be summed that the Nairobi region YES alumni are in a position where adjusting to to the changing world is possible especially due to tertiary education and possessing skills that maybe be applied in transnational expert careers. In the end of the research it is suggested that the groups who do not adjust to the changes as flexibly or whose worldviews and identities do not match in the narratives of globalization and mobility should be acknowledged next.

Public consultation has become a legally mandated part of planning practices in many countries, including Finland. At the same time as planners have to adapt their practices to include the public, cities have become more diverse than ever before. How to incorporate urban residents’ different perspectives and social realities in the planning process in a way that leads to socially just outcomes is one of the key questions in twenty-first century urban planning. This thesis examines this topic through a case study of a participatory planning project in Jyväskylä, Finland. One of the City’s aims with the project was to increase the participation rates of residents from immigrant backgrounds. The actions of the municipality are analysed by applying Othengrafen and Reimer’s cultural planning model, in which planning practices are examined as artifacts reflective of their wider cultural context. The thesis finds that the case reflects cultural narratives of immigrant integration as a unidirectional process rather than as an exchange between cultures. The focus is on teaching the immigrant how to become a participant in the Finnish society through the adoption of new practices and behaviours. This can also be regarded as part of gaining cultural citizenship, referring to the performative way in which borders between the national community and others are constructed in twenty-first century Europe.

Land use change refers to the modification of the Earth's surface by humans. Land use/land cover change (in short, land change), especially the clearing of tree cover, is a major source of increased carbon dioxide (CO2) emissions contributing to anthropogenic climate change. In this study, carbon densities and changes in aboveground tree carbon (agc) across different land cover types were mapped in the Taita Hills, Kenya, using field measurements, airborne laser scanning (ALS) data and classified satellite imagery. An existing biomass map was used for retrieving carbon densities for a part of the study area. For the lowland area, another biomass map was created with a regression model based on field measurements of 415 trees on 61 plots and metrics calculated from discrete return ALS data. Explanatory variables in the linear regression model were the standard deviation and 60 % height percentiles of return elevations. Carbon fraction was calculated as 47 % of aboveground biomass. 11 land cover classes were classified from a satellite image with an object-based approach. Overall classification accuracy was 71.1 % with most confusion between the cropland and shrubland classes and shrubland and thicket. Based on the biomass maps, carbon densities were calculated for different land cover classes. Mean carbon densities were 89.0 Mg C ha-1 for indigenous broadleaved forests, 29.0 Mg C ha-1 for plantation forests, 15.6 Mg C ha-1 for woodland, 5.5 Mg C ha-1 for thicket, 3.2 Mg C ha-1 for shrubland, 8.1 Mg C ha-1 for croplands above 1220 meters above sea level (m a.s.l.) and 2.3 Mg C ha-1 for croplands below 1220 m a.s.l.. Land cover maps from 1987, 1992, 2003 and 2011 were used for studying the impact of land change on aboveground carbon stocks. A reduction in carbon storage was observed between years 1987, 1992 and 2003. An increase in total carbon stocks from 2003 to 2011 was observed as a results of increased proportion of woodland, plantation forest and broadleaved forest. These changes should be further verified in a spatially explicit way. More detailed data should be used in order to understand the full complexity of the dynamics between land change and carbon stocks in the heterogeneous landscape of the Taita Hills.

We investigated the impact of various parameters on new particle formation rates predicted for the sulfuric acid - ammonia system using cluster distribution dynamics simulations, in our case ACDC (Atmospheric Cluster Dynamics Code). The predicted particle formation rates increase significantly if rotational symmetry number of monomers (sulfuric acid and ammonia molecules, and bisulfate and ammonium ions) are considered in the simulation. On the other hand, inclusion of the rotational symmetry number of the clusters only changes the results slightly, and only in conditions where charged clusters dominate the particle formation rate because most of the clusters stable enough to participate in new particle formation display no symmetry, therefore have a rotational symmetry number of one, and the few exceptions to this rule are positively charged. Further, we tested the influence of the application of a quasi-harmonic correction for low-frequency vibrational modes. Generally, this decreases predicted new particle formation rates, and significantly alters the shape of the formation rate curve plotted against the sulfuric acid concentration. We found that the impact of the maximum size of the clusters explicitly included in the simulations depends on the simulated conditions and the errors due to the limited set of clusters simulated generally increase with temperature, and decrease with vapor concentrations. The boundary conditions for clusters that are counted as formed particles (outgrowing clusters) have only a small influence on the results, provided that the definition is chemically reasonable and the set of simulated clusters is sufficiently large. We compared predicted particle formation rates with experimental data measured at the CLOUD (Cosmics Leaving OUtdoor Droplets) chamber. A cluster distribution dynamics model shows improved agreement with experiments when using our new input data and the proposed combination of symmetry and quasi-harmonic corrections., compared to an earlier study based on older quantum chemical data.

In this thesis, we discuss the Relative Lempel-Ziv (RLZ) lossless compression algorithm, our implementation of it, and the performance of RLZ in comparison to more traditional lossless compression programs such as gzip. Like the LZ77 compression algorithm, the RLZ algorithm compresses its input by parsing it into a series of phrases, which are then encoded as a position+length number pair describing the location of the phrase within the text. Unlike ordinary LZ77, where these pairs refer to earlier points in the same text and thus decompression must happen sequentially, in RLZ the pairs point to an external text called the dictionary. The benefit of this approach is faster random access to the original input given its compressed form: with RLZ, we can rapidly (in linear time with respect to the compressed length of the text) begin decompression from anywhere. With non-repetitive data, such as the text of a single book, website, or one version of a program's source code, RLZ tends to perform poorer than traditional compression methods, both in terms of compression ratio and in terms of runtime. However, with very similar or highly repetitive data, such as the entire version history of a Wikipedia article or many versions of a genome sequence assembly, RLZ can compress data better than gzip and approximately as well as xz. Dictionary selection requires care, though, as compression performance relies entirely on it.

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.

There are two primary types of quantum computers: quantum annealers and circuit model computers. Quantum annealers are specifically designed to tackle particular problems, as opposed to circuit model computers, which can be viewed as universal quantum computers. Substantial efforts are underway to develop quantum-based algorithms for various classical computational problems. The objective of this thesis is to implement algorithms for solving graph problems using quantum annealer computers and analyse these implementations. The aim is to contribute to the ongoing development of algorithms tailored for this type of machine. Three distinct types of graph problems were selected: all pairs shortest path, graph isomorphism, and community detection. These problems were chosen to represent varying levels of computational complexity. The algorithms were tested using the D-Wave quantum annealer Advantage system 4.1, equipped with 5760 qubits. D-Wave provides a cloud platform called Leap and a Python library, Ocean tools, through which quantum algorithms can be designed and run using local simulators or real quantum computers in the cloud. Formulating graph problems to be solved on quantum annealers was relatively straightforward, as significant literature already contains implementations of these problems. However, running these algorithms on existing quantum annealer machines proved to be challenging. Even though quantum annealers currently boast thousands of qubits, algorithms performed satisfactorily only on small graphs. The bottleneck was not the number of qubits but rather the limitations imposed by topology and noise. D-Wave also provides hybrid solvers that utilise both the Quantum Processing Unit (QPU) and CPU to solve algorithms, which proved to be much more reliable than using a pure quantum solver.

Rise in popularity of Cloud computing has introduced new challenges for IT-governance. The multitude of different services and possible configurations Cloud providers offer can make it hard to get a comprehensive overview of the environment. To successfully govern an organisations Cloud environment it is important to be able to easily make accurate and reliable observations of the environments state, security, and changes to the configurations. This thesis takes a look into the research literature to find out what kinds of risks have been identified in governing the Cloud environment and ways to mitigate them. One of the latest advancements in improving the Cloud governance is the introduction of automated formal reasoning tools for configuration analysis. One customer case where multiple vendors are building services on multiple cloud accounts is used as an example. Architecture for application, security, and audit log collection, indexing, and monitoring is described. Special attention is given to the identity and access management requirements. The thesis concludes with the assessment of the selected approach and tools and services used to implement it. Some alternative solutions, possible improvements, and further development to the implementation are considered.