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The increased amount of fake news has created a demand for different fake news detection methods. One way to detect fake news is with machine learning models. While there is a lot of research on different fake news detection models, there is not that much research done on the effects of sentiment information on the classification accuracy of the models. Sentiment information means the overall tone of each of the news articles in the dataset, whether it is positive, neutral, or negative. The goal of this thesis is to find out how sentiment information affects the performance of two of the most popular fake news detection machine learning models. These models are the Naïve Bayes and Support Vector Machine. The sentiment analysis was done with TextBlob and Vader, which are already tested and trained sentiment analysis tools available in Python. The results showed that sentiment information did not have any significant effect on the classification accuracy of the fake news detection models. In most of the cases the addition of sentiment information slightly decreased the accuracy of the models. Valeuutisten kasvanut määrä on aiheuttanut tarvetta löytää erilaisia menetelmiä valeuutisten havaitsemiseen. Yksi tapa havaita valeuutisia on koneoppimismenetelmien avulla. Vaikka erilaisia valeuutisten havaitsemiseen käytettyjä koneoppimismalleja on tutkittu paljon, ei ole vielä paljon tutkimusta siitä, miten tunnetieto vaikuttaa koneoppimismallien luokittelutarkkuuteen. Tunnetiedolla tarkoitetaan tietoaineiston kunkin uutisartikkelin yleistä sävyä, eli onko artikkeli positiivinen, neutraali vai negatiivinen. Tämän työn tavoitteena on selvittää, millainen vaikutus tunnetiedolla on kahteen suosituimpaan valeuutisten havaitsemiseen käytetyn koneoppimismallin suorituskykyyn. Nämä mallit ovat Naïve Bayes ja Support Vector Machine. Tunneanalyysi tehtiin käyttäen TextBlobia ja Vaderia, jotka ovat Pythonista löytyviä valmiiksi valmennettuja ja testattuja tunneanalyysityökaluja. Tulokset näyttivät, että tunnetiedolla ei ollut merkittävä vaikutus valeuutisia havaitsevien koneoppimismallien luokittelutarkkuuteen. Suurimmassa osassa tuloksista tunnetietojen lisääminen hiukan laski mallien tarkkuutta.

Kandidaatintyössä esitellään sulasuolareaktorien historian lisäksi lyhyesti reaktorityypin toimintaperiaate ja sulasuolareaktoritutkimuksen nykytilanne. Kandidaatintyöstä käy ilmi, että Oak Ridgen kansallinen laboratorio ORNL oli merkittävä tekijä sulasuolareaktoritutkimuksessa 1940-luvun lopulta aina 1980-luvun alkuun. Ainoat rakennetut sulasuolatekniikkaa käyttävät reaktorit olivat ORNL:n kehittämiä. Oak Ridgen kansallisen laboratorion lopetettua sulasuolatekniikan tutkimusohjelmansa, laantui sulasuolareaktoritutkimus pitkäksi aikaa. 2000-luvun alussa kiinnostus tekniikkaa kohtaan virkosi ja kirjoitushetkellä sulasuolareaktoreita kehitetään useissa tutkimusohjelmissa.

Drying, a crucial step in process engineering aimed at producing optimal product moisture content, has evolved over time from batch processing methods to continuous processing alternatives. Continuous drying methods offer uniform moisture content of the product at lower operational cost. In this study, a continuous veneer drying model was developed based on mass and energy balances. The simulated veneer dryer is a semiautomatic machine designed to maximise the drying process efficiency via control mechanisms such as the veneer transport rate, fan speed, opening angle of the inlet and outlet dampers, and radiator temperature. In the dryer, veneer plates are conveyed horizontally through the number of connected chambers where hot air is blown transversely. The optimal drying process is dynamically maintained via the Proportional–integral–derivative controllers, manipulating the rate of the damper lids opening, that are connected to the sensors monitoring the air properties in the chambers of the drying unit. The model-based sensitivity analysis ANOVA was carried out for energy optimisation purposes. The analysis outcomes indicated that radiator temperature, initial moisture content of veneer sheets and conveyor speed are the most influential parameters affecting the drying rate. Automatic control of damper lids provides optimal temperature and moisture content of drying environment at lower energy costs. Post-print / Final draft

Android-ekosysteemi on erilaisille älylaitteille kehitetty avoimeen lähdekoodiin pohjautuva ekosysteemi, joka on rakennettu Linux -järjestelmäytimen ympärille. Se julkaistiin vuonna 2007, jonka jälkeen sitä on päivitetty säännöllisesti, ja se on laajentunut älypuhelimista muun muassa älykelloihin ja Internet of Things -laitteisiin. Vuonna 2017 se oli myydyin käyttöliittymä sekä älypuhelimien että taulutietokoneiden käyttöjärjestelmänä. Tässä työssä sille luotiin neljä erilaista tulevaisuudenskenaariota käyttäen yhdistettyä skenaariomenetelmää. Ensimmäisessä skenaariossa Android jatkaa nykyisellään markkinajohtajana. Toisessa skenaariossa Google korvaa Android-ekosysteemin toisella ekosysteemillä. Kolmannessa skenaariossa Google lopettaa Android-ekosysteemin tukemisen. Neljännessä skenaariossa Android-ekosysteemi kasvaa yleiskäyttöjärjestelmäksi. The Android ecosystem is an open-source ecosystem developed for various smart devices built around the Linux-kernel. It was released in 2007, after which it has been updated regularly, and has expanded from smartphones to smartwatches and Internet of Things devices, for example. In 2017, it was best-selling operating system, both smartphones and tablet PCs. In this work, four different future scenarios were created using the combined scenario method. In the first scenario, Android continues to be the market leader. In the second scenario, Google replaces the Android ecosystem with another ecosystem. In the third scenario, Google stops supporting the Android ecosystem. In the fourth scenario, the Android ecosystem is growing into a universal operating system.

This doctoral study was conducted as an inquiry of the international entrepreneur in order to balance off the domination of firm-level studies and limited discussion of the individual as the initial driver in the international entrepreneurship phenomenon (IE). Two research questions guide the study: ‘How do individuals make sense of themselves as becoming and being international entrepreneurs?’ and ‘How to theorise of individuals becoming and being international entrepreneurs through a narrative approach?’. With a processual view of the phenomenon, this study embraces IE as a journey and approaches histories and sense-making of individuals through narrative inquiry, paying attention to the different efforts by which entrepreneurs (and researchers) contextualize—and constitute—the personal-level IE journeys. The qualitative dataset consists of interviews and historical data. Data analysis builds on ‘hermeneutic reasoning’, suggesting that meanings and implications of journeys individuals have undertaken can be better grasped after they have unfolded in time. The findings in the four publications construct the contribution of this article-based dissertation. Publications I, II and III embrace narrative sense-making as meaning structure to past actions and lived events and illuminate how the international entrepreneurial ‘self’ as an actor and agent in retrospect manifests individuals as the ‘autobiographical authors’ in regard to developmental, transitional and generational experiences and their meanings in becoming and being an international entrepreneur. They provide evidence of how the founders’ sense-making and identity work feed into the behavioural orientations and ‘bounded and boundaryless’ career journeys of becoming and being international. Publications I, III and IV are novel attempts to address empirically the social historic process in which IE is embedded and its significance for the individual. When analysed against the (inter)generational backdrop of individuals’ actions and life-events, we may trace how international entrepreneurs are the protagonists of their own generations and leaving a legacy to the next.

Dokumenttien, valokuvien, videon ja äänen digitoinnin rinnalle on syntynyt tarve digitoida kohteita kolmiulotteisesti. Kolmiulotteinen digitointi asettaa digitoinnille uusia haasteita, sillä kohteista on kerättävissä hyvin paljon dataa. Digitointia varten tarvitaan siis prosessi jossa määritellään mitä kohteesta tulee digitoida ja miten tämä tehdään, jotta työ pystytään tekemään järkevässä ajassa järkevin kustannuksin. Työssä tutkittiin kirjallisuustutkimuksen ja kolmen digitointikohteen kautta miten prosessi tulisi muodostaa. Lopputuloksena muotoutui prosessimalli, jossa vaiheittain toteutetaan erilaisten työryhmien kanssa digitointisuunnitelma, laitevalinnat sekä digitointityö. Prosessin avulla digitointihankkeen suunnittelu helpottuu ja kustannusten sekä projektin etenemisen esittely asiakkaalle on yksinkertaista. Documents, photographs, sound and video have been digitized for nearly two decades now, and the need to digitize varying objects in three dimensions has been developed. Three-dimensional digitization presents new challenges to the digitization processes. Targets contain a very large amount of data. Because of this a process to determine what and how to digitize is needed. The process needs to determine how the task in each project can be accomplished in a reasonable amount of time and effort. In this thesis, the problem was approached with literature study and case studies of three different digitization cases. As a result a process model for digitization planning was created, where digitization plan, equipment and digitization project will be defined in stages. With the model it will be simpler to evaluate the costs of the digitization project and easier to present the project to the customer.

In this thesis we study the field of opinion mining by giving a comprehensive review of the available research that has been done in this topic. Also using this available knowledge we present a case study of a multilevel opinion mining system for a student organization's sales management system. We describe the field of opinion mining by discussing its historical roots, its motivations and applications as well as the different scientific approaches that have been used to solve this challenging problem of mining opinions. To deal with this huge subfield of natural language processing, we first give an abstraction of the problem of opinion mining and describe the theoretical frameworks that are available for dealing with appraisal language. Then we discuss the relation between opinion mining and computational linguistics which is a crucial pre-processing step for the accuracy of the subsequent steps of opinion mining. The second part of our thesis deals with the semantics of opinions where we describe the different ways used to collect lists of opinion words as well as the methods and techniques available for extracting knowledge from opinions present in unstructured textual data. In the part about collecting lists of opinion words we describe manual, semi manual and automatic ways to do so and give a review of the available lists that are used as gold standards in opinion mining research. For the methods and techniques of opinion mining we divide the task into three levels that are the document, sentence and feature level. The techniques that are presented in the document and sentence level are divided into supervised and unsupervised approaches that are used to determine the subjectivity and polarity of texts and sentences at these levels of analysis. At the feature level we give a description of the techniques available for finding the opinion targets, the polarity of the opinions about these opinion targets and the opinion holders. Also at the feature level we discuss the various ways to summarize and visualize the results of this level of analysis. In the third part of our thesis we present a case study of a sales management system that uses free form text and that can benefit from an opinion mining system. Using the knowledge gathered in the review of this field we provide a theoretical multi level opinion mining system (MLOM) that can perform most of the tasks needed from an opinion mining system. Based on the previous research we give some hints that many of the laborious market research tasks that are done by the sales force, which uses this sales management system, can improve their insight about their partners and by that increase the quality of their sales services and their overall results.

Gadget-laitteet ovat nousseet merkittäväksi osaksi koko yhteiskuntaamme. Niistä on kuitenkin kirjoitettu vain vähän kattavia tutkimuksia laajemmassa mittakaavassa. Tämän työn tavoitteena on tutkia gadget-laitteiden historiaa, nykytilannetta, tulevaisuutta, sekä itse gadget-termin alkuperää ja merkitystä. Työn aluksi selvitetään termin merkitys, ja tämän pohjalta kuvataan laitteiden historiaa 1950-luvulta alkaen, aina nykypäivään ja lähitulevaisuuteen saakka. Gadgets have become an important element of our whole society. Still, there haven’t been many comprehensive studies done on them in a large scale. The goal of this thesis, is to study the history, present day and future of gadgets, and the origin and definition of the gadget term. The definition of the term is made at the start of the thesis and based on this, the history of gadgets is presented from the 1950s all the way to the modern day and the near future.

Recovery boilers are built all over the world. The roots of recovery technology are longer than the roots of recovery boilers. But it wasn’t until the invention of recovery boilers before the Second World War that the pulping technology was revolutionalized. This led to long development of essentially the same type of equipment, culminating into units that are largest biofuel boilers in the world. Early recovery technology concentrated on chemical recovery as chemicals cost money and if one could recycle these chemicals then the profitability of pulp manufacture would improve. For pulp mills the significance of electricity generation from the recovery boiler was for long secondary. The most important design criterion for the recovery boiler was a high availability. The electricity generation in recovery boiler process can be increased by elevated main steam pressure and temperature or by higher black liquor dry solids as well as improving its steam cycle. This has been done in the modern Scandinavian units. Post-print / final draft

The changes in the labor market accompanied by digitalization have influenced the approaches used for recruitment purposes. The development of machine learning and, specifically, natural language processing allowed new services for automated resume screening to appear. These services aim to reduce the time that HR specialists dedicate to sorting out unsuitable candidates, thus saving the costs per hire. This master thesis provides an analysis of the possible approach for matching CVs to JDs based on the taxonomy of competencies. In the literature review, there are the description and comparison of the different ontologies and taxonomies, and the analysis of the previous research performed in vacancy–CV matching provided. In the methodology part, there are the concepts of natural language processing and information extraction described, and the Sentence Transformer model and named entity recognition explained. Besides, evaluation approaches for taxonomy enrichment and vacancy–CV matching are suggested. In the solution development part, the described concepts and models are applied to the JDs and CVs data to perform taxonomy enrichment and matching tasks. The assessment of the matching algorithm performance based on the expert’s evaluation is presented. Based on the results obtained, the potential usage of the research and possible limitations are discussed.