Automatic evaluation of wavelength spectra from quartz by means of machine learning

I have for this thesis worked on automating the steps in evaluating wavelength spectra from quartz. To do this I have applied different machine learning algorithms suitable to the automation requirement at each step, and they were implemented using Python. A neural network is used to fit a curve to cathodoluminescence spectra from quartz. From this curve are feature values extracted, which are then to be used by a machine learning classification algorithm to predict which of three defined groups a quartz sample belong to. Two machine learning classification algorithms have been evaluated: The kNN algorithm and the Random Forest algorithm. These algorithms were trained on multiple feature subsets derived from two different datasets. The difference between the two datasets is that one, the reduced dataset, has had cathodoluminescence spectra influenced, primarily by feldspar, removed. The classification algorithm whose model achieved the highest accuracy was the kNN algorithm with 84%. It achieved this when trained on a feature subset derived from the reduced dataset where only features representing intensity were included. The best performing model by the Random Forest algorithm achieved an accuracy of 81%

Prospect for Norwegian Salmon in Brazil: A Market Integration Analysis

Master's thesis in Industrial EconomicsNorwegian seafood production-expansion mean looking for additional markets to sell products. In this regard, Brazil has been pointed out as one potential new market for Norwegian salmon. There are two main reasons for this: Norway already have a long history of major trade with Brazil, and two, Brazil have already been importing salmon for some years from Chile. If salmon in that time have become an integrated part of the Brazilian fish market it could mean a smoother and less risky entry for Norwegian salmon exporters. In this thesis I apply three different, but in many regards similar, statistical techniques to look for long-term bivariate relationship between the price of salmon and 9 other local groups of fish sold locally in the Brazilian fish market. The total of 10 data series, of which these prices make up, span a period of roughly 4.5 years from February 2014 to July 2018. The results from all three tests point toward the same conclusion, that salmon is an integrated part of the Brazilian fish market. In addition, there is statistical evidence to suggest that the price of salmon could be influencing the price of local species in the long-run