Search results for "hinta"

Computationally intelligent methods for qualitative data analysis

2002

This study focuses on computationally intelligent methods, which are applied to the analysis of survey data in educational research. The methods can be used with complex data sets, which contain several data types. Each data type is analyzed in a separate subanalysis, and the results from these subanalyses can be combined. The methodology makes it possible to locate groups of similar answers from the subanalyses, and to identify these groups using background information. It also allows one to compare groups that are selected from different subanalyses, from different populations, and to locate and identify similar textual answers. In connection to this study, a software application has been…

Automatic knowledge discovery from sparse and large-scale educational data : case Finland

2017

The Finnish educational system has received a lot of attention during the 21st century. Especially, the outstanding results in the first three cycles of the Programme for International Student Assessment (PISA) have made Finland’s education system internationally famous, and its unique characteristics have been under active research by various, predominantly educational, scholars since then. However, despite the availability of real but often sparse big data sets that would allow more evidence-based decision making, existing research to date has mostly concentrated on using classical qualitative and (univariate) quantitative methods. This thesis discusses, in general terms, knowledge discove…

Semantics of Voids within Data: Ignorance-Aware Machine Learning

2021

Operating with ignorance is an important concern of geographical information science when the objective is to discover knowledge from the imperfect spatial data. Data mining (driven by knowledge discovery tools) is about processing available (observed, known, and understood) samples of data aiming to build a model (e.g., a classifier) to handle data samples that are not yet observed, known, or understood. These tools traditionally take semantically labeled samples of the available data (known facts) as an input for learning. We want to challenge the indispensability of this approach, and we suggest considering the things the other way around. What if the task would be as follows: how to buil…

Multitask deep learning for native language identification

2020

Identifying the native language of a person by their text written in English (L1 identification) plays an important role in such tasks as authorship profiling and identification. With the current proliferation of misinformation in social media, these methods are especially topical. Most studies in this field have focused on the development of supervised classification algorithms, that are trained on a single L1 dataset. Although multiple labeled datasets are available for L1 identification, they contain texts authored by speakers of different languages and do not completely overlap. Current approaches achieve high accuracy on available datasets, but this is attained by training an individua…

Finnish attitudes toward mining : citizen survey - 2016 results

2017

Assessing the Commodity Market Price and Terms of Trade Exposures of Macroeconomy in Emerging and Developing Countries

2021

This paper provides novel evidence on commodity market exposure, i.e., the impacts of commodity price and terms of trade fluctuations on macro performance amongst 46 emerging and developing countries (EMDCs) in Africa, Asia and the Latin American and Caribbean (LAC) region. We estimate the exposure of six macroeconomic variables to the commodity prices and terms of trade. Our results indicate that in overall terms, there is a strong and statistically significant long-run relationship between the vector of analyzed world trade prices and macro variables in all EMDCs. However, based on the short-term reactions, only about 10% of the macroeconomic variation amongst the EMDCs is due to commodit…

A Bayesian spatio‐temporal analysis of markets during the Finnish 1860s famine

2022

We develop a Bayesian spatio-temporal model to study pre-industrial grain market integration during the Finnish famine of the 1860s. Our model takes into account several problematic features often present when analysing multiple spatially interdependent time series. For example, compared with the error correction methodology commonly applied in econometrics, our approach allows simultaneous modelling of multiple interdependent time series avoiding cumbersome statistical testing needed to predetermine the market leader as a point of reference. Furthermore, introducing a flexible spatio-temporal structure enables analysing detailed regional and temporal dynamics of the market mechanisms. Appl…

Bridewealth : an ethnographic study on the narratives and descriptions of the practice of bridewealth establishing its purposes, effects and conseque…

2015

Tämä tutkimus analysoi morsiushinnan tapaa seuraavissa Kenian etnisissä ryhmissä: Kalenjin, Kisii, Kikuju, Luhya, Meru, Maasai ja Kamba. Tämä analyysi perustuu pääasiassa minun etnograafiseen työhön, joka toteutettiin helmi-kesäkuussa 2012. Sen aikana keräsin tietoja käyttämällä avoimia haastatteluja ja myös osallistumalla informanttien rutiineihin, eli heidän jokapäiväiseen elämään. Morsiushinta aihe ilmentyi vasta syväanalyysin aikana kenttätyössä kerätyistä haastattelujen litteroinnista. Haastattelut olivat vuorovaikutuskeskusteluja, joissa minun haastateltavat myös esittivät minulle kysymyksiä . Osallistujien kokonaismäärä oli 29 ja meidän vuoropuhelut olivat heidän erilaisista tavoista…

Detector-based visual analysis of time-series data

2015

Information Extraction from Binary Skill Assessment Data with Machine Learning

2021

Strength training exercises are essential for rehabilitation, improving our health as well as in sports. For optimal and safe training, educators and trainers in the industry should comprehend exercise form or technique. Currently, there is a lack of tools measuring in-depth skills of strength training experts. In this study, we investigate how data mining methods can be used to identify novel and useful skill patterns from a binary multiple choice questionnaire test designed to measure the knowledge level of strength training experts. A skill test assessing exercise technique expertise and comprehension was answered by 507 fitness professionals with varying backgrounds. A triangulated appr…