Två dikter af K. Aug. Tavaststjerna

Soitinnus: lauluääni, piano.

Analysis of patterns in mining time series using Qlucore

Raw measurement data does not always immediately convey useful information, but applying mathematical statistical analysis tools into measurement data can improve the situation. Data analysis can offer benefits like acquiring meaningful insight from the dataset, basing critical decisions on the findings, and ruling out human bias through proper statistical treatment. In this thesis we analyze data from an industrial mineral processing plant with the aim of studying the possibility of forecasting the quality of the final product, given by one variable, with a model based on the other variables. For the study mathematical tools like Qlucore Omics Explorer (QOE) and Sparse Bayesian regression (SB) are used. Later on, linear regression is used to build a model based on a subset of variables that seem to have most significant weights in the SB model. The results obtained from QOE show that the variable representing the desired final product does not correlate with other variables. For SB and linear regression, the results show that both SB and linear regression models built on 1-day averaged data seriously underestimate the variance of true data, whereas the two models built on 1-month averaged data are reliable and able to explain a larger proportion of variability in the available data, making them suitable for prediction purposes. However, it is concluded that no single model can fit well the whole available dataset and therefore, it is proposed for future work to make piecewise non linear regression models if the same available dataset is used, or the plant to provide another dataset that should be collected in a more systematic fashion than the present data for further analysis.

MCMC Analysis Of Classical Time Series Algorithms

Identification of order of an Autoregressive Moving Average Model (ARMA) by the usual graphical method is subjective. Hence, there is a need of developing a technique to identify the order without employing the graphical investigation of series autocorrelations. To avoid subjectivity, this thesis focuses on determining the order of the Autoregressive Moving Average Model using Reversible Jump Markov Chain Monte Carlo (RJMCMC). The RJMCMC selects the model from a set of the models suggested by better fitting, standard deviation errors and the frequency of accepted data. Together with deep analysis of the classical Box-Jenkins modeling methodology the integration with MCMC algorithms has been focused through parameter estimation and model fitting of ARMA models. This helps to verify how well the MCMC algorithms can treat the ARMA models, by comparing the results with graphical method. It has been seen that the MCMC produced better results than the classical time series approach.

Regime Switching Models for Electricity Time Series that Capture Fat Tailed Distributions

In the power market, electricity prices play an important role at the economic level. The behavior of a price trend usually known as a structural break may change over time in terms of its mean value, its volatility, or it may change for a period of time before reverting back to its original behavior or switching to another style of behavior, and the latter is typically termed a regime shift or regime switch. Our task in this thesis is to develop an electricity price time series model that captures fat tailed distributions which can explain this behavior and analyze it for better understanding. For NordPool data used, the obtained Markov Regime-Switching model operates on two regimes: regular and non-regular. Three criteria have been considered price difference criterion, capacity/flow difference criterion and spikes in Finland criterion. The suitability of GARCH modeling to simulate multi-regime modeling is also studied.

Analysis of Patterns in Electricity Spot Market Time Series

Due to its non-storability, electricity must be produced at the same time that it is consumed, as a result prices are determined on an hourly basis and thus analysis becomes more challenging. Moreover, the seasonal fluctuations in demand and supply lead to a seasonal behavior of electricity spot prices. The purpose of this thesis is to seek and remove all causal effects from electricity spot prices and remain with pure prices for modeling purposes. To achieve this we use Qlucore Omics Explorer (QOE) for the visualization and the exploration of the data set and Time Series Decomposition method to estimate and extract the deterministic components from the series. To obtain the target series we use regression based on the background variables (water reservoir and temperature). The result obtained is three price series (for Sweden, Norway and System prices) with no apparent pattern.

Informationsbeteende och inlärningsmiljöer : en kvalitativ studie av medicine studerandes informationsbeteende i två olika utbildningsprogram

Avhandlingens övergripande syfte är att granska relationerna mellan olika undervisningsmetoder och studenters informationsbeteende, vilket i denna undersökning inbegriper även deras informationskompetens. Vikten av att undersöka dessa förhållanden kan motiveras med att både kunskap om de faktorer som påverkar utvecklandet av informationskompetens och forskning som tar fram olika mönster i studenternas informationsbeteende behövs för att sådana inlärningsmiljöer, informationssystem och -tjänster som stöder studenternas inlärning skall kunna utvecklas. I avhandlingen söks svar på följande frågor: 1. Vilka faktorer i inlärningsmiljöerna, dvs. problembaserad inlärningsmiljö (pbl) och traditionell inlärningsmiljö, påverkar informationsbeteendet och hur påverkar dessa faktorer? 2. Hurdan information behövs i inlärningsprocessen? Hur anskaffas informationen? Vilka informationskanaler och -källor används och hur används de? 3. Hur används information i samband med inlärningen? I undersökningen används en kvalitativ forskningsansats och det huvudsakliga undersökningsmaterialet består av intervjuer med 16 medicine studerande som studerar enligt en problembaserad inlärningsmetod och 15 studerande som studerar i ett traditionellt ämnesbaserat utbildningsprogram. Den empiriska delen av undersökningen utfördes i slutet av 1990-talet. Resultaten indikerar att en problembaserad inlärningsmiljö utvecklar förståelsen av kunskap, aktiverar informationsanskaffningen och informationsanvändningen, samt främjar utvecklingen av studenternas informationskompetens såsom den definierades i denna undersökning. Högre nivå av informationskompetens och aktiv informationsanvändning förekom emellertid i båda utbildningsprogrammen även bland studenter som hade påbörjat de fördjupade studiernas slutarbete, vilket framhäver motivationens och de verkliga informationsbehovens roll i informationsbeteendet och i utvecklandet av informationskompetensen.

Konsertto kahdelle käyrätorvelle Es : Konsert för två valthorn Ess

Soitinnus: käyrätorvet (2), orkesteri.

Viva la mamma : eli Oopperan ihanuus ja kurjuus : kaksinäytöksinen ooppera = eller Operans härlighet och elände : opera i två akter

Sibelius-Akatemian konserttisarja 12.2.1981.