Abstract

Abstract
Nowadays, hydraulic sources are responsible for most of the Brazil's energy production. Hydroelectric power plants (HPP) operators in Brazil usually distribute equally the total power required among the generator units available in the plant. However, studies show that this configuration does not guarantee that each generator unit operate close to its optimal operation point. The energy dispatch optimization problem consists in determining which generation units need to be on or off and what is their respective power-set, so that both the overall HPP costs is minimized and the power required by the plant is met. This paper presents a GPU-based parallel implementation of NSGA-II, to solve the energy dispatch problem of a HPP complaying with the real time restrictions posed by the operation of a real HPP from the reception of the power demand to the energy dispatch. Our implementation obtains better solutions than the sequential implementation currently available.

Abstract
In the past years, data has become increasingly fast and volatile, making the ability to track its evolution an highly significant part of the value extraction process. In this work we present a framework to monitor evolution of clusters and present its use on real world data. We develop a framework over a previous one by Oliveira and Gama from 2013. Its biggest contribution is the addition of the concept of control area. This area will create a region around the cluster where it is still possible to establish associations with clusters from other time points. It aims to expand the search scope for cluster associations while diminishing the number of false positives. Changes to the transition definitions and detection algorithm are also introduced to accommodate the existence of this area. We demonstrate this framework at work in a real world scenario testing it with a telecom industry dataset and make a detailed analysis of the obtained results.

Abstract
If it were possible to automatically detect proficiency in languages using data from eye movements, new levels of customizing computer applications could possibly be achieved. An example in case is web searches where suggestions and results could be adjusted to the user's knowledge of the language. The objective of this study is to compare the reading habits of users with high and low English language proficiency, having in mind the possible automatic detection of the English proficiency level through reading. For this purpose, a study was conducted with two types of user, those with a high level of proficiency (Proficient Users), and those with low proficiency (Basic Users) in the English language. An eye-tracker was used to collect users' eye movements while reading a text in English. Results show that users with high proficiency engage in more careful reading. In contrast, low English proficiency users take more time to read, revisit sentences and paragraphs more often, have more and longer fixations and also a higher number of saccades. As expected, these users have more difficulties in understanding the text.

Abstract
Proper management of supply chains is fundamental in the overall system performance of forest based activities. Usually, efficient, management techniques a decision support, software, which needs to be able to generate fast and effective outputs from the set of possibilities. In order to do this, it is necessary to provide accurate models representative of the dynamic interactions of systems. Due to forest-based supply chains' nature, event-based models are more suited to describe their behaviours. This work proposes the modelling and simulation of a forest based supply chain, in particular the biomass supply chain, through the SimPy framework. This Python based tool allows the modelling of discrete-event, systems using operations such as events, processes Mid resources. The developed model was used to access the impact of changes in the daily working plan in three situations. First, as a control case, the deterministic behaviour was simulated. As a second approach, a machine delay was introduced and its implications in the plan accomplishment were analysed. Finally, to better address real operating conditions, stochastic; behaviours of processing and driving times were simulated. The obtained results validate the SirriPy simulation environment as a framework for modelling supply chains in general and for the biomass problem in particular.

Abstract