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This thesis is an ethnographic exploration into co-production evaluation. The aim of this thesis is to evaluate outcomes of a knowledge co-production workshop in the context of Finnish urban planning using a co-production evaluation framework. For the context of the research, the status of allotment gardens in urban planning was studied. Central concepts also include participation and the status of knowledge in the urban planning context. I collected my research data by participating in the workshop process as a co-facilitator and co-producer in a garden workshop held in Pähkinärinne allotment plots in June 2022. I carried out the research using qualitative research methods, participatory observation. Field notes and the material and data the garden workshop produced are the main body of data. The results show that the workshop did produce a tangible outcome, a usable concept for the Pähkinärinne allotment gardens. When situated in the Finnish urban planning context, analysis shows that implementation may be difficult due to institutional and governance barriers. Intangible impacts were produced in the form of social learning. This entailed the identification of existing social networks in and outside of the allotment plots and their development through social capital. These effects fare better in the Finnish context through self-governance and self-organization. As a conclusion, it can be said that the knowledge co-production process was a successful process but in the Finnish urban planning context bottom-up initiatives can be difficult to implement due to institutional barriers and city-led planning and participation.

Kawah Ijen is the picturesque crater of the Ijen volcano located in Eastern Java, Indonesia. However, it is not just any volcano crater, as it happens to be the locus of labour-intensive sulphur mining operation. Each day up to 15 tons of sulphur is extracted from the Ijen crater by the 350 men working as manual miners. These men carry even 100 kilogram loads of sulphur out from the crater with bare brawn and the work is with no doubt burdensome. Kawah Ijen's natural beauty has also caught the interest of tourists', and the crater has become commodified as a tourism destination, visited by hundreds of international tourists each day. Thus the storyline of this master's thesis is two-fold. The first research objective scrutinizes the Kawah Ijen sulphur mine from a commodity chain perspective, emphasizing the tough work the sulphur miners have to bear in order to satisfy the needs of the consumers at the end of the chain. The second, and the essential objective of this research in turn interrogates how the presence of the sulphur miners has become also an inevitable part of the Kawah Ijen tourism experience. In this the aspiration is to elucidate how the sulphur miners have become aestheticized as a Global South tourism attraction. In other words, this research aims to interrogate the peculiarity of this reality, by exploring how both trade and culture, and human and commodity mobilities are entangled and enshrouded within the crater of the Ijen volcano. In human geography, a research framework of 'Follow the thing' has been adopted by scholars in order to study the geographically far-flung production chains of consumer goods. As a framework it aims to make critical political-economic connections between the consumers and distant, and often also underprivileged, producers. In this Marxist-influenced undertaking emphasis is placed particularly on commodity fetishism. This notion has been mobilized to illuminate how consumers have become alienated from the means of production, in their symbolically-laden everyday consumption. As sulphur is a raw material needed in the production processes of many goods such as white sugar, fertilizers, medicines, and rubber, this research shows how these commodities were 'followed' into their origins to this particular sulphur mine. During a period of field work, a method of participant observation was utilized to get contextual understanding of this production site. The initial research objective is therefore to make connections and create awareness of the inequalities within commodity production networks. In the final research objective of this master's thesis, a postcolonial approach is mobilized to critically interrogate this initial setting, in which the miners are seen as poor and stagnant producers. Thus the Kawah Ijen tourists are taken under lens in order to gain understanding of this touristic encounter nuanced with cross-cultural and socio-economic differences between the tourists and the miners. Therefore the setting of Kawah Ijen will not only be observed as a place of production, but also as a site - and object - of consumption. By analysing blogged travel stories written by the tourists themselves, this research aims to illuminate what the tourism experience of the Kawah Ijen is about in the realm of consumption. Special attention is given to how the encounter with sulphur miners has become a constitutive part of the adventurous and authentic tourism experience of Kawah Ijen. The blog post analysis on the Kawah Ijen tourism narrative shows how the imaginaries of the sulphur miner as the 'Other' are adhered to, as the tourists construct their travel identities, make meaning of their experiences and finally represent their experience to the outside world. Finally this research aims to make ruptures to Global South fetishism by elucidating how the Kawah Ijen sulphur mine has become both commoditized and fetishized in its own right. In this fetishzation process the sulphur miners are depicted as poor and primitive, which as categories act as symbols for authentic tourism consumption in the social frameworks of the tourists. However, the aim is not to demonize the tourists, but to give recognition to the nuanced personal and social realities they are embedded in their consumption. Hence, the tourism experience of Kawah Ijen is constructed through a point of view more sensitive to the subjective negotiation of authenticity. It is argued that the Kawah Ijen tourism experience is a process in which the meaning of the experience is negotiated in a wider framework, which is vicariously embedded in postcolonial discourse. Finally, it is concluded that although there is some unequal power relations at presence in the tourism consumption of Kawah Ijen, the tourism can be the means to make more sustainable living for the miners. The leapfrog from the mining to tourism has to be only carried out in a deliberate way with respect to all of the stakeholders.

BitTorrent is one of the most used file sharing protocols on the Internet today. Its efficiency is based on the fact that when users download a part of a file, they simultaneously upload other parts of the file to other users. This allows users to efficiently distribute large files to each other, without the need of a centralized server. The most popular torrent site is the Pirate Bay with more than 5,700,000 registered users. The motivation for this research is to find information about the use of BitTorrent, especially on the Pirate Bay website. This will be helpful for system administrators and researchers. We collected data on all of the torrents uploaded to the Pirate Bay from 25th of December, 2010 to 28th of October, 2011. Using this data we found out that a small percentage of users are responsible for a large portion of the uploaded torrents. There are over 81,000 distinct users, but the top nine publishers have published more than 16% of the torrents. We examined the publishing behaviour of the top publishers. The top usernames were publishing so much content that it became obvious that there are groups of people behind the usernames. Most of the content published is video files with a 52% share. We found out that torrents are uploaded to the Pirate Bay website at a fast rate. About 92% of the consecutive uploads have happened within 100 seconds or less from each other. However, the publishing activity varies a lot. These deviations in the publishing activity may be caused by down time of the Pirate Bay website, fluctuations in the publishing activity of the top publishers, national holidays or weekdays. One would think that the publishing activity with so many independent users would be quite level, but surprisingly this is not the case. About 85% of the files of the torrents are less than 1.5 GB in size. We also discovered that torrents of popular feature films were uploaded to the Pirate Bay very fast after their release and the top publishers appear to be competing on who releases the torrents first. It seems like the impact of the top publishers is quite significant in the publishing of torrents.

In this thesis we present and evaluate a novel approach for energy-efficient and continuous transportation behavior monitoring for smartphones. Our work builds on a novel adaptive hierarchical sensor management scheme (HASMET), which decomposes the classification task into smaller subtasks. In comparison to previous work, our approach improves the task of transportation behavior monitoring on three aspects. First, by employing only the minimal set of necessary sensors for each subtask, we are able to significantly reduce power consumption of the detection task. Second, using the hierarchical decomposition, we are able to tailor features and classifiers for each subtask, improving the accuracy and robustness of the detection task. Third, we are able to extend the detectable motorised modalities to cover most common public transportation vehicles. All of these attributes are highly desirable for real-time transportation behavior monitoring and serve as important steps toward implementing the first truly practical transportation behavior monitoring on mobile phones. In the course of the research, we have developed an Android application for sensor data collection and utilized it to collect over 200 hours of transportation data, along with 2.5 hours of energy consumption data of the sensors. We apply our method on the data to demonstrate that compared to current state-of-art, our method offers higher detection accuracy, provides more robust transportation behavior monitoring and achieves significant reduction in power consumption. For evaluating results with respect to the continuous nature of the transportation behavior monitoring, we use event and frame-based metrics presented by Ward et al.

Tässä työssä kehitettiin SQUID-pohjainen laitteisto helium-3:lla tehtäviä NMR-mittauksia varten ja suoritettiin mittauksia sekä nk. jatkuvan aallon (continous wave) NMR:llä että pulssitetun aallon (pulsed wave) menetelmällä. Helium-3:n korkean hinnan (n. 5000 euroa/litra) takia työssä käytettiin testitarkoituksiin NMR-materiaaleina myös fluoria sisältävää teflonia ja vetyä sisältävää jäätä. Laitteisto suunniteltiin ja rakennettiin Aalto-yliopiston O.V. Lounasmaa -laboratoriossa, nykyiseltä nimeltään Low Temperature Laboratory. NMR eli ydinmagneettinen resonanssi on ilmiö jossa ydinspinilliset atomiytimet sijoitetaan staattiseen magneettikenttään ja viritetään niitä ulkoisella sähkömagneettisella säteilyllä, jonka jälkeen niiden viritystila purkautuu vapauttaen NMR-signaalin. Tällä tavalla pystytään tutkimaan monia aineen eri ominaisuuksia. SQUID eli Superconducting Quantum Interference Detector taas on nimensä mukaisesti kvantti-interferenssiin perustuva laite, joka kykenee havaitsemaan erittäin pieniä magneettikenttiä. NMR:n yhteydessä se on tehokas esivahvistin, jonka avulla voidaan havaita hyvin pieniäkin signaaleja. Tässä työssä sillä on tarkoitus parantaa signaali-kohinasuhdetta verrattuna perinteisiin puolijohde-esivahvistimiin ja saada aikaan ilmaisin jolla voidaan mitata myös matalammilla taajuuksilla kuin tutkimusryhmällä on nykyisin käytössä. Suoritettujen mittausten perusteella laitteisto kykeni havaitsemaan NMR-signaalin jatkuvan aallon menetelmällä jokaisesta tutkitusta aineesta. Pulssitettuja mittauksia ei vielä toistaiseksi onnistuttu tekemään onnistuneesti johtuen heliumin pitkähköstä, n. 30 sekunnin, relaksaatioajasta joka teki pidemmistä mittaussarjoista vaikeita toteuttaa. Vastaavasti kahdella kiinteällä aineella, teflonilla ja jäällä, resonanssin leveys oli niin suuri että energian absorbointi pulsseilla näytteeseen olisi hankalaa ja tuottaisi signaaleja joiden pienuus tekisi niistä hankalasta havaittavia, joten näitä aineita tutkittiin tässä työssä vain jatkuvan aallon menetelmällä.

The thesis presents and evaluates a model for detecting changes in discourses in diachronic text corpora. Detecting and analyzing discourses that typically evolve over a period of time and differ in their manifestations in individual documents is a challenging task, and existing approaches like topic modeling are often not able to reach satisfactory results. One key problem is the difficulty of properly evaluating the results of discourse detection methods, due in large part to the lack of annotated text corpora. The thesis proposes a solution where synthetic datasets containing non-stable discourse patterns are generated from a corpus of news articles. Using the news categories as a proxy for discourses allows both to control the complexity of the data and to evaluate the model results based on the known discourse patterns. The complex task of extracting topics from texts is commonly performed using generative models, which are based on simplifying assumptions regarding the process of data generation. The model presented in the thesis explores instead the potential of deep neural networks, combined with contrastive learning, to be used for discourse detection. The neural network model is first trained using supervised contrastive loss function, which teaches the model to differentiate the input data based on the type of discourse pattern it belongs to. This pretrained model is then employed for both supervised and unsupervised downstream classification tasks, where the goal is to detect changes in the discourse patterns at the timepoint level. The main aim of the thesis is to find out whether contrastive pretraining can be used as a part of a deep learning approach to discourse change detection, and whether the information encoded into the model during contrastive training can generalise to other, closely related domains. The results of the experiments show that contrastive pretraining can be used to encode information that directly relates to its learning goal into the end products of the model, although the learning process is still incomplete. However, the ability of the model to generalise this information in a way that could be useful in the timepoint level classification tasks remains limited. More work is needed to improve the model performance, especially if it is to be used with complex real world datasets.

The Meridional overturning circulation (MOC) is one crucial component in Earth's climate system, redistributing heat round the globe. The abyssal limb of the MOC is fed by the deep water formation near the poles. A basic requirement for any successful climate model simulation is the ability to reproduce this circulation correctly. The deep water formation itself, convection, occurs on smaller scales than the climate model grid size. Therefore the convection process needs to be parameterized. It is, however, somewhat unclear how well the parameterizations which are developed for turbulence can reproduce the deep convection and associated water mass transformations. The convection in the Greenland Sea was studied with 1-D turbulence model GOTM and with data from three Argo floats. The model was run over the winter 2010-2011 with ERA-Interim and NCEP/NCAR atmospheric forcings and with three different mixing parameterizations, k-e, k-kL (Mellor-Yamada) and KPP. Furthermore, the effects of mesoscale spatial variations in the atmospheric forcing data were tested by running the model with forcings taken along the floats' paths (Lagrangian approach) and from the floats' median locations (Eulerian approach). The convection was found to happen by gradual mixed layer deepening. It caused salinity decrease in the Recirculating Atlantic Water (RAW) layer just below the surface while in the deeper layers salinity and density increase was clearly visible. A slight temperature decrease was observed in whole water column above the convection depth. Atmospheric forcing had the strongest effect on the model results. ERA-interim forcing produced model output closer to the observations, but the convection begun too early with both forcings and both generated too low temperatures in the end. The salinity increase at mid-depths was controlled mainly by the RAW layer, but also atmospheric freshwater flux was found to affect the end result. Furthermore, NCEP/NCAR freshwater flux was found to be large enough (negative) to become a clear secondary driving factor for the convection. The results show that mixing parameterization mainly alters the timing of convection. KPP parameterization produced clearly too fast convection while k-e parameterization produced output which was closest to the observations. The results using Lagrangian and Eulerian approaches were ambiguous in the sense that neither of them was systematically closer to the observations. This could be explained by the errors in the reanalyzes arising from their grid size. More conclusive results could be produced with the aid of finer scale atmospheric data. The results, however, clearly indicate that atmospheric variability in scales of 100 km produces quantifiable differences in the results.

High-quality thin films deposited by Atomic layer deposition (ALD) are key components in numerous modern technological applications. The technique is extensively used in the semiconductor and photovoltaic industry, for example. ALD is an excellent technique for thin film deposition due to its characteristic self-limiting surface reactions that allow a reproducible, conformal, and precisely controlled coating on a substrate. Numerous new ALD materials are developed each year to advance technological innovations to new levels. However, occasionally a desired material cannot be produced directly by ALD. To still obtain the impressive features of ALD, an ALD thin film can be transformed chemically or physically in a manner that preserves the film-like structure of the original layer. This thesis explores these types of ALD film transformations, or conversions, by attempting the conversions of atomic layer deposited Al2O3 from a two-dimensional film to a tree-dimensional film structure, Ru to RuO2, Re to ReO3, ZnO to ZIF-8, and ZrOx to UiO-66 films. Current preparation methods, common applications, and general properties of these five materials are explored in the literature review. This provides an insight on some of the key features of the fabrication of these materials and what value the thin film structure brings them. It also highlights the challenges that are encountered regarding these processes. If the material has been obtained through conversion of an ALD thin film, the process is reviewed with detail. Additionally, the literature review explains the basics of conversion reactions as well as fundamentals of ALD. The experimental section focuses on studying and optimizing the distinct challenges as well as explores new methods for fabricating the materials through the conversion of ALD thin films. Conversion of zirconium oxide thin films to UiO-66 under terephthalic acid vapor was attempted with modest results. Ru thin films were converted into crystalline RuO2 under ambient and O2 atmospheres successfully and the processes seem promising for further research. Re and ReNx films were partially converted to ReO3 under O2, O3 and humid environments. The continuity of these films proved to be problematic. Factors affecting the formation of ZIF-8 and Al2O3 “grass" in the conversions of ZnO under 2-methylimidazole vapor and Al2O3 under heated water, respectively, were assessed, and the optimization of these processes was studied.

Copuloista on tullut yleinen työkalu finanssimaailman käyttötarkoituksiin. Tämän työn tavoitteena on esitellä copuloiden teoriaa ja sen soveltamista rahoitusriskien mallintamiseen. Copulat määritellään ja niihin liittyvää keskeistä teoriaa käydään läpi. Tärkeimpiä korrelaatiokonsepteja esitellään, muun muassa tunnusluvut Kendallin tau ja Spearmanin rho. Lisäksi copulaperheet, joihin eniten käytetyt copulat kuuluvat, määritellään. Copuloiden parametreja voi estimoida eri metodien avulla. Kolme tärkeintä loguskottavuusfunktioon perustuvaa metodia käydään läpi, samoin kuin Monte Carlo -menetelmä, jolla voidaan simuloida muuttujia copuloista. Esitellään häntäriippuvuus, joka on hyödyllinen käsite äärimmäisiä ilmiöitä mallinnettaessa. Value at Risk eli VaR on yksi tärkeimmistä sijoitusriskien riskimitoista. Uudelleenjärjestelyalgoritmiin perustuvan menetelmän avulla voidaan laskea huonoimmat ja parhaat VaR:n arvot. Menetelmän toimintaa havainnollistetaan järjestelemällä eräs matriisi algoritmin avulla niin, että nähdään huonoimman VaR:n yläraja. Menetelmää sovelletaan vielä kolmen eri osakkeen, Nokian, Samsungin ja Danske Bankin, useamman vuoden päivittäisistä tappioista koostetun matriisin uudelleenjärjestelyyn. Näin saatu huonoimman VaR:n yläraja on suurempi kuin historiallisen VaR:n arvo, joka laskettiin toisella menetelmällä. Tutkielman teorian käytännön soveltamista jatketaan vielä laskemalla osakkeiden tappioiden välisiä korrelaatioita. Nokian ja Deutsche Bankin tappioiden välisen korrelaatiokertoimen huomataan olevan arvoltaan suurin, ja todettaan, että niiden välistä riippuvuusrakennetta voidaan kuvata parhaiten t-copulalla.

Due to next generation of sequencing technologies the amount of public sequence data is exponentially growing, however the rate of sequence annotation is lagging behind. There is need for development of robust computational tools for correct assignment of annotation to protein sequences. Sequence homology based inference of molecular function assignment and subsequent transfer of the annotation is the traditional way of annotating genome sequences. TF-IDF based methodology of mining informative description of high quality annotated sequences can be used to cluster functionally similar and dissimilar protein sequences. The aim of this thesis work is to perform the correlation analysis of TF-IDF methodology with standard methods of Gene Ontology (GO) semantic similarity measures. We have developed and implemented a high-throughput tool named GOParGenPy for effective and faster analysis related to Gene Ontology. It incorporates any Gene Ontology linked annotation file and generates corresponding data matrices, which provides a useful interface for any downstream analysis associated with Gene Ontology across various mathematical platforms. Finally, the correlation evaluation between TF-IDF and standard Gene Ontology semantic similarity methods validates the effectiveness of TF-IDF methodology in order to cluster functionally similar protein sequences.