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Big data is now being utilized widely and developed rapidly. The researches on big data area is meaningful as it provides all kind of information. Answering aggregation queries are also very important in both research and commercial fields. In this paper we aim to introduce a sampling method to answer aggregation queries on realistic massive data with controlled relative error bound. We used JSON as the experiment material data which makes it different from the related and existed researches. Wikipeida records are stored as big JSON data provides the realistic data environment which makes the results meaningful and trustworthy. We utilize the Wikipedia big JSON file, process data, modify and adapt the sampling algorithm with given relative error bound. Specifically, preliminary process of big JSON file and implement retrieving interested attributes and store the filtered attributes for sampling use. Then modify the dividing buckets algorithm to divide data into buckets by their similarity and the weight of data group. Then answer the aggregation queries on the sampled data. We analyze the experiment results with the error bound, confidence and running time and the relations of error bound and sample sizes. We expect the results of error bound is under what have given so the results are reliable and the sampling method to dramatically reduce the running time and space for answering aggregation queries.

Sand and dust storms are one of the major regional environmental problems that affect human health. Many environmental studies have focused on airborne dust concentrations observed at different regions and have tried to connect the observations to specific dust source regions. This thesis aims to provide a new dust classifications scheme for the Eastern Mediterranean region, specifically observed in Amman, Jordan. I utilized a combination of a long-term data-base consisting of aerosol particle number concentration in coarse mode (1–10 µm) during November 2013 – July 2018 and air mass back trajectories analysis to visually identify the Sand and Dust Storm (SDS) episodes. The classification included three main source regions of for the submicron dust, namely Sahara, Arabia, and Levant. I also classified the data according to the, episode intensity according to their corresponding number concentrations as no-dust, mild, intermediate, and strong intensities and further classified the range of back trajectories as short, intermediate, long, and very long, which indicates the distance between the observation site and the source region.. The results showed that majority of the dust events and an elevated number of dust days are influenced by a source in Levant and Sahara source region. These events which dominated during 70 days in 2016. The Levant source governed during 60 days during the same period. Other dust sources contributed less to the dusty days, and the lowest dusty days number was due to emissions from Levant & Arabia (19 days). The episode intensity varied censurably and underlined variability from the different source areas. The maximum intensity in the dust episode concentration was linked to Levant & Sahara with a max number concentration of 95 /cm3. The classification method was successful and it was able to establish a dust source database in the Eastern Mediterranean region based on the long-term observations performed in Amman with variable dust concentration and dust periods in different seasons and different meteorological circumstances.

Perinteisten levyperustaisten relaatiotietokantojen taulujen sisältämä tieto talletetaan riveittäin peräkkäistiedostoihin ja rivi koostuu yleensä useista eri sarakkeista. Tällöin tietokantaan kohdistettava yleensä SQL-kielinen kysely saa haettua yhden rivin tiedot nopeasti, varsinkin jos kyseinen rivi sattuu olemaan jo valmiiksi muistissa. Jos kyselyllä haetaankin tietoja useilta sadoilta, ellei jopa tuhansilta riveiltä ja kyselyyn sisältyy hakuehto, jossa voi olla mukana useita sarakkeita, niin kyselystä tulee yleensä aina hidas, elleivät rivit sitten sattumalta ole järjestetty hakutekijän mukaan. Lisäksi jos haettavat rivit eivät ole valmiina muistissa, niin järjestelmä joutuu tekemään hitaan tiedon haun levyltä ja tämä hidastaa entisestään halutun tulosjoukon muodostamista. Sarakeorientoituneessa tietokannassa kunkin taulun sarakkeen tieto voidaan tallettaa omaan tiedostoonsa, tai sitten kunkin sarakkeen tiedot sijaitsevat peräkkäin samassa tiedostossa. Kunkin sarakkeen tiedot voidaan myös tiivistää ja säästää näin tilaa. Sarakeorientoituneesta taulusta tietyn rajatun osajoukon hakeminen on usein nopeampaa, koska kysely voidaan kohdistaa vain haluttuihin sarakkeisiin ja koska sarakkeet arvot ovat peräkkäin, ovat tiedot näin nopeasti saatavilla. Jos tiedot eivät ole jo valmiiksi muistissa, niin myös tiedon hakeminen ulkoiselta tiedostolta nopeutuu, koska halutut tiedot ovat peräkkäin levyllä. Kun sarakeorientoitunut tietokanta sijoitetaan keskusmuistiin, niin myös mahdollinen levyltä lukemiseen kuluva viive poistuu, ja tulosten saanti nopeutuu entisestään. Tutkielmassa tarkastellaan sarakeorientoituneen keskusmuistitietokannan toimintaa ja sen liittämistä osaksi muuta tietokantajärjestelmää. ACM Computing Classification System (CCS): Information systems → Main memory engines Information systems → Data compression Information systems → Database query processing

Port cities have through times been in the forefront of cultural, social and technological changes. The cityspace of Helsinki is in this sense also a target of consistant change. One of the biggest challenges has been the relocation of the harbour to Vuosaari, which has opened the Western Harbour for redevelopment. Western Harbour and particularly Jätkäsaari, which is now under redevelopment, is in the focus of this thesis. Especially the development and evolution from a harbour area to an urban part of inner-city is being investigated. How does the general historical development of harbours appear like? Harbours have elsewhere in the world became underused areas in central city locations, since they were for a long time physically, socially and economically isolated from the rest of the city structure. What is the restructuring of Western Harbour like - the phases of the process and the reasons for the change of use? The redevelopment of central harbour areas and industrial waterfronts forms a unique opportunity, but their legacy often consists of a polluted environment that is in a comprehensive need of renovation. This port-city interface is a zone of contested and overlapping challenges, where modern city planning meets the area of port operations. What are the prerequisites of good urban fabric and design in the redevelopment of an old harbour area? This thesis forms a qualitative and comparative case study. Brian Hoyle's Port-city evolution and interface theories are used to illustrate the temporal developments and changes in port cities. Yehuda Hayuth's model about Trends and developments on the port-city interface complements Hoyles model. The redevelopment of Western Harbour and Jätkäsaari is also compared to HafenCity Hamburg. With the help of Rinio Bruttomesso and Michael Clark we form an image about the conditions of good urban fabric in the former harbour areas and of what that is required from them to ensure a more effective and successful entity. The global and historical development of port cities complies well with Hoyles Port-city theory. Port cities were a single unit at the beginning of the evolution, but became separated over the years, as ports moved to more suitable locations (due to increasing vessel sizes, need of space). Hence, the regeneration and reintegration (besides physically, also culturally and spiritually) of former harbour areas has becomed the challenge. The developments that are demonstrated through Hoyles theory are caused by technological, social and economic changes. The introduction of steamships and containers form the two most important singular contributing causes, that have controlled the development of harbours. The Port-city theory describes well the development of Western Harbour, the final stages take place here relatively late, but in a faster pace than elsewhere. The RAMA-survey, the citys growth and development needs, as well as the location of the port constituted problems that worked as an initiation for the transformation process of Western Harbour. The redevelopment constitutes a challenge, where the ability to solve intersecting goals and purposes, environmental problems and the aim of creating a good city structure is at the core. Good urban design in the former port areas is based on determining the nature, range of functions and features as well as their diversity and the blending of them in the area. Also the utilization of old port structures - houses and elements together with the purity of the surrounding waters constitute contributing themes. A number of solutions related to the organizing of the cityspace, like opening up the waterfront and the ritualization of it, along with the chance to create a pedestrian- and public transit-city and build innovative and bold architecture are all central themes that have a chance of being realized on the waterfront. The construction of Western Harbour gives Helsinki a new maritime image and renews the city in its original core. It is an inner-city expansion, which has a large impact on the image of southern Helsinki - its city structure and city life. The objective is to build a city for the unknown future, which is both a challenge and an opportunity.

Tässä tutkielmassa tutkittiin säteilypakote-käsitteen oppimista Ilmasto.nyt-kurssilla ja kurssin taustamuuttujien vaikutusta kurssin suorittamiseen. Kurssi on monitieteinen ja se toteutettiin monimuoto-opetuksena. Ilmasto.nyt-kurssille osallistui monella tapaa heterogeeninen opiskelijajoukko. Kurssin suoritti vuosina 2016 ja 2017, 172 opiskelijaa, joista 38 otettiin mukaan tähän tutkimukseen. Kurssille osallistuneita tutkittiin sukupuolen, opiskeluvuoden, tiedekunnan, vastausten pituuden ja suorituskielen mukaan. Tutkimuksessa havaittiin että 5.-6. vuoden opiskelijat ja äidinkielellä vastanneet saivat muita parempia arvosanoja. Pidemmät vastaukset paransivat arvosanoja keskimäärin. Opiskelijat valitsivat kysymyspatterista vastattavaksi erilaisia kysymyksiä riippuen opiskelijan tiedekunnasta. Kurssia arvioitiin haastavaksi, mutta hyödylliseksi ja kattavaksi. Tutkimuksessa käytettiin tilastollisia menetelmiä, eri taustamuuttujien ja arvosanojen välisten riippuvuuksien selvittämiseksi.

IASI on vuodesta 2007 käytössä ollut satelliitti-instrumentti Metop-polaarisatelliitissa. IASI-mittauksista johdettuja lopputuotteita ovat mm. lämpötilan ja kosteuden pystyprofiilit, pilven ylärajan lämpötila ja paine sekä eri hivenkaasujen pitoisuudet. Tämä työ on alkua IASI:n käyttöönotolle Ilmatieteen laitoksella. Työssä selvitetään IASI:n lämpötilaprofiileiden ja pilven ylärajan paineen soveltuvuutta sääpalvelulle vertailemalla niitä jo käytössä oleviin sääpalvelun työkaluihin. IASI-mittauksista johdettuja lämpötilaprofiileita verrataan Ilmatieteen laitoksen operatiivisiin pintaluotauksiin. Lisäksi tarkastellaan IASI:n lämpötilaprofiileiden vaikutusta paikallisen analyysi- ja ennustustyökalu LAPS:in lämpötila-analyysiin. IASI:n pilven ylärajan lämpötiloja verrataan AVHRR-radiometrista johdettuihin pilven ylärajan lämpötiloihin. IASI:sta ja AVHRR:stä johdetut keskimääräiset lämpötilat olivat lähes samat alapilville. Yläpilville ja osittain läpinäkyville cirrus-pilville lämpötilaero oli noin 5 Celsius-astetta. IASI:n lämpötilaluotaukset osoittautuivat käyttökelpoisiksi etenkin keski- ja ylätroposfäärissä (350 - 600 hPa), jossa IASI:n antama lämpötila erosi pintaluotauksen lämpötilasta vain noin ±1 Celsius-astetta. IASI:n lämpötilaluotausten suurin ongelma on mittausten katkeaminen pilven ylärajaan. IASI-luotauksilla oli suuri vaikutus LAPS-lämpötila-analyysiin mallin koko alueella, mutta vertailuaineiston puutteessa ei voida varmasti sanoa onko vaikutus positiivinen vai negatiivinen. Tulokset ovat lupaavia. IASI:n lämpötilaluotaukset ja pilven ylärajan lämpötila vaikuttavat käyttökelpoisilta sääpalvelun tarpeisiin.

Taloudellisten, institutionaalisten ja teknologisten ympäristöjen kiihtyvä muutostahti on luonut tarpeen tehdä oikeita valintoja menestymisen ja kehityksen takeeksi. Parhaimman valinnan tekee henkilö, jolla on eniten tietoa ja varmuutta tiedon paikkansapitävyydestä. Vaihtoehtoisesti päätöksenteon epävarmuustekijöitä voidaan hallita eliminointimenetelmillä, joiden hyödyntäminen voi myös johtaa parempiin päätöksiin. Epävarmuuden minimoimisen edellytyksenä on niin ikään pohjatietojen parantaminen. Tästä tarpeesta ovat nousseet tiedonlouhintamenetelmät. Tiedonlouhintamenetelmiä on kehittynyt valtava määrä vastaamaan kysynnän luomia tarpeita. Päätöksentekopuu on eräs tällainen analysointimenetelmä ja päätöksentekopuun pohjalta on luotu koneoppimismenetelmä satunnaismetsä. Satunnaismetsä on tutkimusten mukaan tällä hetkellä paras saatavilla oleva luokittelumenetelmä ja valikoitunut tämän tutkielman aiheeksi. Luvussa 2 luomme pohjaa satunnaismetsä-menetelmän ymmärtämiseksi. Lähdemme liikkeelle koneoppimisesta ja datalouhintamenetelmistä, joilla alustamme päätöksentekopuutyökalun. Käy ilmi, että on olemassa luokittelu-, regressio- ja luokitteluregressiopuita, ja että tässä tutkielmassa keskitymme luokittelupuihin. Tämän jälkeen esittelemme päätöksentekopuun metodologiaa. Luvussa 3 esittelemme tutkielman kannalta päätöksentekopuiden tärkeimmät validointimenetelmät, sillä datalouhinnassa analysointimenetelmien validoiminen on yhtä tärkeää kuin itse analysoiminen. Esittelemme mallien validointiin liittyviä käsitteitä, kuten tarkkuus, yleistysvirhe ja ylisovittuminen. Käymme läpi yleisimpiä tapoja validoida malleja, sekä näytämme esimerkkien kautta työkalut, joita käytämme tutkielmassa. Näitä ovat tarkkuus, väärinluokittelumatriisi, ROC-, kumulatiivinen saanti- ja nostokäyrä. Luvussa 4 esittelemme satunnaismetsä-koneoppimismenetelmän. Käymme ensiksi läpi joukko-oppimisen metodologiaa, jonka jälkeen käsittelemme satunnaismetsän algoritmin. Osoitamme teoreettisesti, miksi satunnaismetsä on parempi luokittelija kuin esimerkiksi päätöksentekopuu näyttämällä, että satunnaismetsän puumäärän kasvaessa satunnaismetsän yleistysvirhe suppenee kohti nollaa. Analysoimme teoreettisesti satunnaismetsän hyötyjä ja haittoja. Satunnaismetsän hyötyjä ovat sen tarkkuus, nopeus, ymmärrettävyys, toimivuus valtavilla datamäärillä, sekä kykeneväisyys analysoida tietojoukon merkittävimpiä muuttujia. Haittoja ovat, että satunnaismetsä ei suoriudu yhtä hyvin regressio-ongelmissa kuin esimerkiksi logistinen regressiomalli, sekä huono sovellettavuus pieniin tietojoukkoihin. Luvussa 5 sovellamme opittuja taitoja suppeaan tietojoukkoon. Tarkoituksenamme on arvioida RStudion ja SAS Enterprise Minerin satunnaismetsä-pakettien toimivuutta tunnetulla syötejoukolla. Analysoimme satunnaismetsäin suoriutumista luokittelutehtävässä ja vertailemme tuloksia päätöksentekopuuhun ja regressiomalliin. Hyödynnämme luvussa 3 opittuja validointimenetelmiä. Käy ilmi, että RStudion ja SAS Enterprise Minerin satunnaismetsä-paketit toimivat hyvin, ja että satunnaismetsä suoriutuu pienenkin tietojoukon luokittelussa malleista parhaiten. Luvussa 6 sovellamme satunnaismetsää yrityksen tarjoamaan haasteeseen, jossa tarkoitus on selittää ja ennustaa uusien asiakkaiden tietyn asiakassegmentin asiakasvaihtuvuutta. Käytämme yhtiön tarjoamia tietokantoja ja SAS Enterprise Miner-työkalua. Suoritamme vertailun satunnaismetsä- ja päätöksentekopuu-mallien välillä käyttämällä luvussa 3 esiteltyjä validointimenetelmiä ja analysoimme tulokset. Käy ilmi, että ROC-käyrien ja tarkkuuden perusteella satunnaismetsä suoriutuu sekä luokittelussa että ennustamisessa paremmin kuin päätöksentekopuu. Luvussa 7 pohdimme, millaisissa puitteissa satunnaismetsä soveltuu yrityksen liiketoimintaprosessiin. Käymme läpi vaatimuksia, joita satunnaismetsän soveltaminen asettaa, sekä mitä lisäarvoa satunnaismetsä menetelmänä tuo yritykselle. Tulos on, että satunnaismetsä soveltuu hyvin yrityksille, jotka hyödyntävät SAS-työkaluja ja tuo lisäarvoa analysointitehtäviin olemalla ymmärrettävä malli, mutta kuitenkin monipuolinen, nopea ja tarkka.

The number of IoT and sensor devices is expected to reach 25 billion by 2030. Many IoT appli- cations, such as connected vehicle and smart factory that require high availability, scalability, low latency, and security have appeared in the world. There have been many attempts to use cloud computing for IoT applications, but the mentioned requirements cannot be ensured in cloud environments. To solve this problem, edge computing has appeared in the world. In edge environments, containerization technology is useful to deploy apps with limited resources. In this thesis, two types of high available Kubernetes architecture (2 nodes with an external DB and 3 nodes with embedded DB) were surveyed and implemented using K3s distribution that is suitable for edges. By having a few experiments with the implemented K3s clusters, this thesis shows that the K3s clusters can provide high availability and scalability. We discuss the limitations of the implementations and provide possible solutions too. In addition, we provide the resource usages of each cluster in terms of CPU, RAM, and disk. Both clusters need only less than 10% CPU and about 500MB RAM on average. However, we could see that the 3 nodes cluster with embedded DB uses more resources than the 2 nodes + external DB cluster when changing the status of clusters. Finally, we show that the implemented K3s clusters are suitable for many IoT applications such as connected vehicle and smart factory. If an application that needs high availability and scalability has to be deployed in edge environments, the K3s clusters can provide good solutions to achieve the goals of the applications. The 2 nodes + external DB cluster is suitable for the applications where the amount of data fluctuate often, or where there is a stable connection with the external DB. On the other hand, the 3 nodes cluster will be suitable for the applications that need high availability of the database even in poor internet connection. ACM Computing Classification System (CCS) Computer systems organization → Embedded and cyber-physical systems Human-centered computing → Ubiquitous and mobile computing

Traditional natural language processing has been shown to have excessive reliance on human-annotated corpora. However, the recent successes of machine translation and speech recognition, ascribed to the effective use of the increasingly availability of web-scale data in the wild, has given momentum to a re-surging interest in attempting to model natural language with simple statistical models, such as the n-gram model, that are easily scaled. Indeed, words and word combinations provide all the representational machinery one needs for solving many natural language tasks. The degree of semantic similarity between two words is a function of the similarity of the linguistic contexts in which they appear. Word representations are mathematical objects, often vectors, that capture syntactic and semantic properties of a word. This results in words that are semantic cognates having similar word representations, an important property that we will widely use. We claim that word representations provide a superb framework for unsupervised learning on unlabelled data by compactly representing the distributional properties of words. The current state-of-the-art word representation adopts the skip-gram model to train shallow neural networks and presents negative sampling, an idea borrowed from Noise Contrastive Estimation, as an efficient method of inducing embeddings. An alternative approach contends that the inherent multi-contextual nature of words entails a more Canonical Correlation Analysis-like approach for best results. In this thesis we develop the first fully Bayesian model to induce word embeddings. The prominent contributions of this thesis are: 1. A crystallisation of the best practices from previous literature on word embeddings and matrix factorisation into a single hierarchical Bayesian model. 2. A scalable matrix factorisation technique for structured sparse data. 3. Representation of the latent dimensions as continuous Gaussian densities instead of as point estimates. We analyse a corpus of 170 million tokens and learn for each word form a vectorial representation based on the 8 surrounding context words with a negative sampling rate of 2 per token. We would like to stress that while we certainly hope to beat the state-of-the-art, our primary goal is to develop a stochastic and scalable Bayesian model. We evaluate the quality of the word embeddings against the word analogy tasks as well as other such tasks as word similarity and chunking. We demonstrate competitive performance on standard benchmarks.

This Master’s thesis studies the mechanisms connected to negative changes in educational outcomes in upper comprehensive schools in Helsinki. What are the factors associated with negative changes in educational outcomes of individual students during the transition from 7th to 9th grade? There is an increased socioeconomic and ethnic segregation in Helsinki Metropolitan Area, and the differences between schools’ levels of success have also been growing throughout the 21st century. There is little research on combining schools and city development in Finland. The aim is to examine is there an association between decreasing individual educational outcomes and socio-spatial or school segregation, and to look at what is the role of individual factors and social context in decreased educational outcomes. Studying pupils and schools is a good way to capture local processes of differentiation and neighbourhood effect, because children and youth are especially prone to neighbourhood and school effects due to their ongoing process of socialization, localized lives in their neighbourhood and shared institutions, such as school. This study is conducted quantitatively, and the main method in this study is hierarchical linear regression. The data is from Metropolitan Longitudinal Finland research, which studies the success and wellbeing of pupils in upper comprehensive schools in the Helsinki Metropolitan area. The study was conducted during the Fall of 2011 and the Spring of 2014 tracking the same cohort when the pupils were in their 7th and 9th grades. The results suggest that there are no differences found between schools, but some of the qualities describing neighborhoods indicate that some neighbourhood effect might be found. There are indications that pupils with decreased educational outcomes are more likely to study in schools that are located in low income areas than higher income areas. Also, for pupils with decreased educational outcomes, attending a school that is located in Northern or Southeastern Great districts is more likely than attending a school in Eastern Great district. Based on the results, pupils with negative change in educational outcomes are more likely to spend time with friends of own area than with school friends. Boys have a bigger risk for a negative change in educational outcomes than girls, and the change of school is connected to decreased educational outcomes. Mother’s education and immigration background was not found to have connection with decreased educational outcomes. Decreased educational outcomes have a connection with a low parents’ pedagogical ethos, but no connection with peers’ pedagogical ethos was found. The results are significant from the perspective of urban and educational politics and planning. The indications that the educational outcomes in upper comprehensive schools in Helsinki are differentiated in neighborhood level for example between Great districts, and in individual level between genders, challenge the goals of equal educational opportunities. Also, urban planning should be targeted to prevent socio-spatial differentiation of neighborhoods, in order to combat differentiation in schools’ composition of pupils. In future research, the starting level of educational success could be studied more closely- does decrease in educational outcomes implicate different educational paths for pupils that start with high starting level than pupils that have lower starting level in the beginning? This study provided information that there are no differences between schools found currently, but the processes of differentiation are not stable, so the processes should be observed continuously.