Search for dissertations about: "machine learning relation"
Showing result 21 - 25 of 32 swedish dissertations containing the words machine learning relation.
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21. Bioinformatics Methods for Topology Prediction of Membrane Proteins
Abstract : Membrane proteins are key elements of the cell since they are associated with a variety of very important biological functions crucial to its survival. They are implicated in cellular recognition and adhesion, act as molecular receptors, transport substrates through membranes and exhibit specific enzymatic activity. READ MORE
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22. An analytical framework for studying transcriptional regulation
Abstract : The state and behavior of any living cell is controlled by a complex interplay of different regulatory processes, with the regulation of transcription playing a major role. When a cell adapts to a new environment it often does that by modulating gene transcript levels, mainly through changes in transcription factor binding events. READ MORE
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23. Our Humanity Exposed : Predictive Modelling in a Legal Context
Abstract : This thesis examines predictive modelling from the legal perspective. Predictive modelling is a technology based on applied statistics, mathematics, machine learning and artificial intelligence that uses algorithms to analyse big data collections, and identify patterns that are invisible to human beings. READ MORE
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24. Essays on Firm Turnover, Growth, and Investment Behavior in Ethiopian Manufacturing
Abstract : This thesis analyses the dynamics and investment behavior of Ethiopian manufacturing firms in post-reform period using establishment level industrial census panel data from 1996 to 2003. Three related topics such as firm turnover and productivity differentials, determinants of firm growth, and the effect of adjustment cost and irreversibility on firm investment decisions are investigated empirically. READ MORE
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25. Conceptualizing and Measuring Well-Being Using Statistical Semantics and Numerical Rating Scales
Abstract : How to define and measure individuals’ well-being is important, as this has an impact on both research and society at large. This thesis concerns how to define and measure the self-reported well-being of individuals, which involves both theorizing as well as developing and applying empirical and statistical methods in order to gain a better understanding of well-being. READ MORE