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Tämä pro gradu -tutkielma pyrkii tuomaan uusia ajatuksia matematiikan opetuksen ja opiskelun tueksi. Matemaattinen sisältö on suunniteltu lukion oppimäärää silmällä pitäen. Tutkielma käsittelee integraalikurssin opetusta ja lähestymistavaksi on valittu tehtävien kautta oppiminen. Tutkielmassa pyritään avaamaan lukiossa käsiteltävän integraalilaskennan teoriaa tehtävien keinoin. Tavoitteena on se, että opiskelijat oppisivat matematiikkaa ja sen teoriaa itsenäisesti laskemalla. Tutkielmassa on mukana avoimia ja suljettuja tehtäviä, jotka pyrkivät lisäämään käsitteellistä osaamista ja kokoamaan aihekokonaisuuksia yhteen. Tutkielmassa esitellään ensin avoimet ongelma-tehtävät ja paneudutaan niiden merkitykseen opetuksen näkökulmasta, jonka jälkeen siirrytään lukion integraalikurssin matemaattiseen sisältöön ja tehtävien pariin. Avoin tehtävä on matemaattinen tehtävätyyppi, jossa joko alku tai loppu on avoin tai molemmat ovat avoimia (Pehkonen, 2005). Ongelmatehtävä puolestaan on tehtävä, joka on sopivan haastava ratkaisijalleen. Matemaattisen ajattelun ja luovuuden kehittämisen menetelmänä tarjotaan usein ongelmaratkaisua (mm. Mason, Burton & Stacey 1982; Schoenfeld 1985; Stanic & Kilpatrick 1988). Avoimet tehtävät soveltuvat mainiosti haastamaan oppilaan ajattelua. Ne ajavat oppilaan tekemään itsenäisiä ja opetuksen näkökulmasta parhaimmillaan matemaattisia johtopäätöksiä koskien opiskeltavaa aihetta tai siihen liittyvää teoriaa. Opetuksen painopisteen muuttaminen opettajakeskeisestä luennoimisesta oppilaskeskeiseksi tuo mukanaan haasteita. Esimerkiksi voidaan epäröidä, opitaanko laskemalla myös matematiikan teoriaa itsenäisesti tai ryhmissä opiskelemalla. Tutkielma pyrkii vastaamaan teorian oppimisen haasteeseen tehtävien keinoin, jotka tutkielmassa on varta vasten luotu teorian oppimista varten. Tehtävät on pyritty rakentamaan niin, että ne olisivat sopivan haastavia ja sisältäisivät syvyyttä. Aihealueittain on pyritty luomaan hieman helpompia ja haastavampia tehtäviä. Tehtävät johdattelevat teorian äärelle tai syventävät jo olemassa olevien käsitteiden ymmärrystä. Oppilaita haastetaan piirtämään kuvia, esittämään ideoitaan, perustelemaan sanallisesti havaintojaan ja laskemaan. Avoimen tehtävän arvioiminen numeerisesti on haastavaa. Perinteinen suljettu tehtävä arvioidaan prosessin kautta. Tästä lähdettiin ja tänne päädyttiin; yksi lähtö ja yksi maali. Avoin tehtävä on monihaarainen ja sen arvioimisessa pitää mennä jossain mielessä kokonaisuuksien arvioimiseen.

Tämän työn tarkoitus on helpottaa opettajia ja koulutusalan asiantuntijoita lähestymään Wilberin Integraaliteoriaa ja integraaliopetusta. Integraaliteoriaa viitekehyksenä käyttävä integraaliopetus on yksi varteenotettavimmista vaihtoehdoista tulevaisuuden integraaliseksi ja mahdollisimman kokonaisvaltaiseksi opetusmenetelmäksi. Teoria-osiossa käydään läpi Integraaliteorian teorian tausta ja kehitysvaiheet. Sitten esitellään Integraaliteorian tärkeimmät osapuolet: AQAL matriisi, Wilber-Combs hila ja Integraalinen Metodologinen Pluralismi. Seuraavaksi keskustellaan integraaliopetuksesta, sen tarpeesta ja tunnuspiirteistä, ja siitä miten integraaliopetuksessa tulisi huomioida Integraaliteorian tärkeimmät osapuolet. Lopuksi pohditaan opettajan roolia ja integraaliopetuksen haasteita. Työn empiirinen osa koostuu toukokuussa 2018 Meksikossa Tecnologico de Monterrey -yliopiston Tampicon kampuksella tehdystä kyselytutkimuksesta. Kysetutkimuksen tarkoituksena oli selvittää opiskelijoiden subjektiivisia asenteita, mielipiteitä ja kokemuksia integraaliopetuksesta. Vastauksille suoritettiin tilastollinen analyysi SPSS ohjelmistolla. Opiskelijat arvioiva integraaliopetuksen hyödyn korkeaksi oppimiselle ja opiskelulle. Heidän arvioiden perusteella myös integraalinen lähestymistapa elämää kohtaan ylipäätään arvioitiin hyödylliseksi. Integraaliopetuksen transformatiivinen potentiaali arvioitiin korkeaksi. Lisäksi opiskelijat pitivät integraaliopetuksen piirteitä ja tavoitteita tärkeinä opetukselle. Vertailuryhmien (sukupuoli, ikä, opintolukukaudet yliopistossa, lukion keskiarvo ja yliopiston keskiarvo) sisäisien ryhmien vastauksien tilastollista poikkeavuutta ei löytynyt. Täten, opiskelijat arviot integraaliopetuksesta olivat positiivisia riippumatta taustatekijöistä.

Cyberthreat intelligence is currently a hot topic in the information security community. Today's business models are forcing organizations to move into the cyberspace, and because of this they phase new threats. Organizations need to address these new threats in order to protect their systems from adversaries. One method for doing so is to develop a threat intelligence program, in which the organization actively gathers intelligence about current and emerging cyberthreats. Indicators of compromise can be used in organization's security infrastructure to look for and to prevent threats in near real-time. Indicators can be obtained from public intelligence feeds, and they can be shared in threat information sharing communities formed by organizations facing similar threats. Regardless of the source of threat intelligence, the intelligence should be evaluated by skilled security analysts to verify that the indicators of compromise suit the target environment. By sharing threat information organizations can benefit from security incidents seen by other organizations, and the participants can leverage the actionable intelligence to adjust their defenses before similar threats realize within their own network. Organizations can utilize purpose-built software to manage their threat intelligence. This supports the organization in developing its threat intelligence program. Threat information management platforms aid organizations in managing the quality and richness of threat intelligence and these platforms often come with information sharing capabilities built into the software, enabling organizations to share threat intelligence with each other. Organizations are able to distribute actionable intelligence into their security infrastructure more easily if they use a threat information management platform as the centralized point for managing the organization's threat intelligence. An example of an integration point is the organization's security information and event management (SIEM) system, which is often utilized by a security operations center (SOC) to perform analytics on the organization's log data. When the logs collected by a SIEM system are enriched with actionable intelligence security analysts are likely to see more informed alerts and less false positives. This thesis defines an integration between a threat information management platform and a SIEM.We measure and evaluate how much the integration reduces SOC's burden of manually importing threat intelligence into their monitoring infrastructure. Two questionnaires with SOC analysts were carried out for this purpose. We also evaluate how much integration fastens the deployment of actionable intelligence for detecting emerging threats. The evaluation is based on security incident ticket data obtained from a production SOC environment.

Until recently, database management systems focused on the relational model, in which data are organized into tables with columns and rows. Relational databases are known for the widely standardized Structured Query Language (SQL), transaction processing, and strict data schema. However, with the introduction of Big Data, relational databases became too heavy for some use cases. In response, NoSQL databases were developed. The four best-known categories of NoSQL databases are key-value, document, column family, and graph databases. NoSQL databases impose fewer data consistency control measures to make processing more efficient. NoSQL databases haven’t replaced SQL databases in the industry. Many legacy applications still use SQL databases, and newer applications also often require the more strict and secure data processing of SQL databases. This is where the idea of SQL and NoSQL integration comes in. There are two mainstream approaches to combine the benefits of SQL and NoSQL databases:multi-model databases and polyglot persistence. Multi-model databases are database management systems that store and process data in multiple different data models under the same engine. Polyglot persistence refers to the principle of building a system architecture that uses different kinds of database engines to store data. Systems implementing the polyglot persistence principle are called polystores. This thesis introduces SQL and NoSQL databases and their two main integration strategies: multi-model databases and polyglot persistence. Some representative multi-model databases and polystores are introduced. In conclusion, some challenges and future research directions for multi-model databases and polyglot persistence are introduced and discussed.

Heating, ventilation, and air conditioning (HVAC) systems consume massive amounts of energy. Fortunately, by carefully controlling these systems, a significant amount of energy savings can be achieved. This requires detecting a presence or amount of people inside the building. Countless different sensors can be used for this purpose, most common being air quality sensors, passive infrared sensors, wireless devices, and cameras. A comprehensive review and comparison are done for these sensors in this thesis. Low-resolution infrared cameras in counting people are further researched in this thesis. The research is about how different infrared camera features influence counting accuracy. These features are resolution, frame rate and viewing angle. Two systems were designed: a versatile counting algorithm, and a testing system which modifies these camera features and tests the performance of the counting algorithm. The results prove that infrared cameras with resolution as low as 4x2 are as accurate as higher resolution cameras, and that frame rate above 5 frames per second does not bring any significant advantages in accuracy. Resolution of 2x2 is also sufficient in counting but requires higher frame rates. Viewing angles need to be carefully adjusted for best accuracy. In conclusion, this study proves that even the most primitive infrared cameras can be used for accurate counting. This puts infrared cameras in a new light since primitive cameras can be cheaper to manufacture. Therefore, infrared cameras used in occupancy counting become significantly more feasible and have potential for widespread adoption.

Actinides are heavy elements with no known physiological function in man, animals or plants. The actinides are radioactive without exception. In addition, the actinides exhibit metallotoxic properties. Due to these properties the actinides represent a health hazard to living organisms. This hazard can materialize should actinides be accidentally released into the environment. Decontamination regimes are used to treat humans contaminated with actinides. The knowledge of actinide bioinorganic chemistry inside the tissues and bodily fluids of humans is required for the development of internal decontamination therapies. Unfortunately, fairly little is known of the behaviour of actinides inside the human body at a molecular level. Human serum albumin (HSA) is a blood plasma protein. With a concentration of circa 600 micromolar, it is the most ubiquitous of the blood-borne proteins. HSA has a multitude of physiological functions, one among them being the role of metal carrier. It is tempting to speculate that HSA might be an actor responsible for actinide distribution inside the human body. In this study, the interaction between HSA and trivalent curium was investigated using time-resolved laser fluorescence spectroscopy (TRLFS) in a bid to obtain information useful in decontamination therapy development. TRLFS is a highly sensitive technique that allows the determination of speciation data even at trace level concentrations. Cm(III) has excellent optical properties, making it amenable for study using TRLFS and a convenient representative of trivalent actinides in general. In addition to Cm(III) the trivalent actinide analogue Eu(III), which is also a good fluorescent probe, was also utilized. Nuclear magnetic resonance (NMR) spectroscopy was used in an experiment aimed at resolving the site of interaction. The experiments revealed the existence of a CmHSA complex. It was discovered that 90 % of available Cm(III) was in the CmHSA complex at physiological pH and temperature (7,4 and 310 K, respectively). A pH 8,0 conditional stability constant log K of 6,8 +/- 0,5 and a Cm(III):HSA reaction stoichiometry of 1:1 were determined for the complex. In addition, the thermodynamic parameters deltaH and deltaS were determined. The number of non-water ligands in the first coordination sphere of Cm(III) was determined to be five or six. Furthermore, a combined TRLFS and NMR approach revealed the HSA binding locus of Cm(III) and Eu(III). Based on the results, a model could be presented, in which trivalent actinides bind HSA at the amino-terminus of the protein and that the site shares at least some of its ligands with the canonical Cu(II) binding site of HSA.

The formation of snowfall is a consequence of interactions between physical processes and the size distribution of snow particles. In this study, 1-dimensional steady-state model in combination with weather radar observations was used to retrieve the vertical evolution of a snow particle size distribution. The snow growth model uses the zeroth, the first and the second mass moments of a particle size distribution for calculating the evolution of distribution parameters. The model includes physical snow growth processes, such as ice nucleation, water vapor deposition and aggregation. Other processes, such riming, breakup and ice multiplication were not considered in this study. Given the model setup, snowfall cases where either supercooled liquid water is absent or supercooled liquid drops are small enough that they don't collide with ice particles can be physically represented by the model developed in this study. To analyze the model performance and its ability to retrieve snow microphysical properties, two distinct snowfall cases, that took place on 26th and 30th December 2010, were selected. The December 30th case is a typical snowfall event and the model was able to reproduce particle size distributions and radar variables in December 30th case that agreed well with observations. Particular radar signatures that have recently attracted a lot of attention in the scientific literature took place during the December 26th case. It is believed that they are associated with enhanced vapor deposition and aggregation growth of ice particles. The case of 26th December could not be accurately modeled probably because of invalid steady state assumption or missing microphysical processes. The number concentration of small particles at the ground level is underestimated in model results. The model also cannot produce approximately exponential size distribution as was observed by ground instruments. The underestimated number of small particles refers that breakup of particles or ice multiplication could have a significant role in the evolution of size distribution. However, based on the model runs with different types of snow particles, the model produced high intensity snowfall when high number concentration of plate crystals existed, which could cause the above-mentioned signatures. So our study does corroborate results presented in literature, but may indicate that there is a missing snow growth process that is currently not considered. As a part of this study the currently available 2-moment model was extended to a 3-moment scheme. These two schemes were extensively tested and analyzed. Changes in size distribution shape due to aggregation and deposition is captured by the 3-moment scheme. In the 2-moment scheme shape of a particle distribution is constant. It was found that ice water content (IWC) and snowfall rate grow faster in the 3-moment model than in the 2-moment model. Fast increase in IWC due to ice particle growth by water vapor deposition leads to narrowing of a size distribution. In upper parts of clouds, the 3-moment scheme produces questionably narrow size distributions, which needs to be studied in the future.

Finding information such as images that match the users need is a demanding task. The user has to be aware of the right keywords to search with and the underlying collection might not contain the intended images for all users. We propose a methodology to overcome these limitations by generating images matching the users needs instead of retrieving them from a collection. The methodology combines generative adversarial networks (GANs) capable of generating photorealistic images with relevance feedback from users. The methodology was evaluated with 29 user experiments where users were given a set of image retrieval tasks to find images not present in the collection of images. The images generated using the system were compared to the baseline images the users picked from a set of images representing image search results. The results from the study show that image quality was improved significantly across all image domains (cats, cars, beds, faces) and relative improvement was greater the less the starting image had in common with the target. The results suggest that generating images can be more useful than retrieving them from an existing collection.

Tutkielman aiheena on ollut tutkia onko mahdollista tuottaa sellainen interaktiivinen verkkosivu lukion pitkän matematiikan 7. kurssille (Derivaatta), missä teorian lisäksi opiskelija pystyy tekemään kurssiin liittyviä tehtäviä ja saada niistä automaattista palautetta. Sivustolta vaadittavia ominaisuuksia ovat matemaattisen tekstin editori tehtävien tekemiseen sekä piirto-ja animaatio-ohjelma matematiikan havainnollistamiseen. Sivustoa varten käytiin läpi useita jo olemassa olevia ohjelmia, joiden perusteella matemaattisen tekstin editori päätettiin tehdä itse ja piirto-ohjelmaksi valittiin Geogebra-ohjelma. Geogebra on suunniteltu matemaattiseksi havainnollistamisvälineeksi, jolla on helppo luoda matematiikan ongelmia visualisoivia kuvia ja animaatioita. Lisäksi se on helppo upottaa internet-sivustolle. Matemaattista tekstiä tuottavaa editoria varten päädyttiin luomaan oma MathML-kieleen perustuva tekstieditori, jolla voi kirjoittaa matemaattista tekstiä internetsivuilla. Sivusto pitää sisällään teoriaosuudet raja-arvosta, jatkuvuudesta sekä derivaatasta ja pitää sisällään 30 näihin liittyvää tehtävää. Jokaisesta tehtävästä on kolme eri versiota, joista käyttäjälle arvotaan satunnaisesti yksi. Käyttäjä tekee tehtävän matemattiikkaeditoriin, jonka vastauksen ohjelma tarkistaa. Kun tehtävä saadaan suoritettua hyväksytysti, saa käyttäjä pisteen. Editori on selainkohtainen, joten selain muistaa jälkikäteenkin mitkä tehtävät käyttäjä on tehnyt. Käyttäjä voi myös tallentaa tekemänsä ratkaisut selaimen omaan muistiin myöhempää tarkastelua varten. Tutkimuksen tuloksena saatiin, että Derivaatta-kurssia varten on mahdollista tuottaa kokonainen sivusto, jonka avulla koko kurssin suorittaminen verkossa on mahdollista. Tutkielman sivusto ei käsitä koko kurssia, mutta kun siihen lisätään koko kurssin teoria ja tehtävät sekä niiden tarkistukseen tarvittava ohjelmisto (esim. STACK), kokeet, keskustelualueen sekä oppilaiden hallintaan liittyvät sivut on verkkokurssin läpikäyntiin tarvittava kokonaisuus olemassa. Tämän lisäksi sivustoa varten laadittu matematiikkaeditori ja tehtävät mahdollistavat opiskelijoiden harjoittelun tietokoneella tapahtuvaan matematiikan kirjoittamiseen, jota vuonna 2019 suoritettava sähköinen matematiikan ylioppilaskirjoitus vaatii.

The rapidly increasing global energy demand has led to the necessity of finding sustainable alternatives for energy production. Fusion power is seen as a promising candidate for efficient and environmentally friendly energy production. One of the main challenges in the development of fusion power plants is finding suitable materials for the plasma-facing components in the fusion reactor. The plasma-facing components must endure extreme environments with high heat fluxes and exposure to highly energetic ions and neutral particles. So far the most promising materials for the plasma-facing components are tungsten (W) and tungsten-based alloys. A promising class of materials for the plasma-facing components is high-entropy alloys. Many high-entropy alloys have been shown to exhibit high resistance to radiation and other wanted properties for many industrial and high-energy applications. In materials research, both experimental and computational methods can be used to study the materials’ properties and characteristics. Computational methods can be either quantum mechanical calculations, that produce accurate results while being computationally extremely heavy, or more efficient atomistic simulations such as classical molecular dynamics simulations. In molecular dynamics simulations, interatomic potentials are used to describe the interactions between particles and are often analytical functions that can be fitted to the properties of the material. Instead of fixed functional forms, interatomic potentials based on machine learning methods have also been developed. One such framework is the Gaussian approximation potential, which uses Gaussian process regression to estimate the energies of the simulation system. In this thesis, the current state of fusion reactor development and the research of high-entropy alloys is presented and an overview of the interatomic potentials is given. Gaussian approximation potentials for WMoTa concentrated alloys are developed using different number of sparse training points. A detailed description of the training database is given and the potentials are validated. The developed potentials are shown to give physically reasonable results in terms of certain bulk and surface properties and could be used in atomistic simulations.