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Predicting the direction, maximum, minimum and closing price of daily/Intra-daily bitcoin exchange rate using batch and online machine learning techniques
(Universidade Federal de São Carlos, 2018-09-19) Arguelles, Dennys Christian Mallqui; Fernandes, Ricardo Augusto Souza; https://lattes.cnpq.br/0880243208789454; https://lattes.cnpq.br/6617444730810557
Bitcoin is the most accepted cryptocurrency in the world, which makes it attractive for investors and traders. However, the great challenge in predicting the Bitcoin exchange rate is its high volatility. Therefore, the prediction of its behavior is of great importance for financial markets. In this way, in recent years, Few studies were proposed based on the use of machine learning techniques to predict the direction of their exchange rate, albeit with low precision. Therefore, as a first contribution of this paper, it can be highlighted the analysis and identification of internal and external variables/attributes considered as relevant for predicting the Bitcoin exchange rate in daily and intra-daily time frequencies. The increased use of machine learning techniques to predict time series and the acceptance of cryptocurrencies as financial instruments motivated the present study to seek more accurate predictions for the Bitcoin exchange rate. For this purpose, it was used different techniques of attribute selection to candidate variables. In relation of internal variables is proposed to use Blockchain information and generate technical indicators commonly used by traders. About external variables is proposed to use international economic indices and social trends extracted from Google and Wikipedia. As a second contribution, a methodology is proposed to predict the direction of the Bitcoin exchange rate against the dollar. In addition, it was explored the possibility of directly predict the maximum, minimum and closing prices, including these information to predict the trend. For this, Artificial Neural Networks, Recurrent Neural Networks, Support Vector Machines and Ensemble models (combining regression and clusterization) were used. As a third contribution for intra-daily time frequency, the data-stream learning methods are explored under the hypothesis that Bitcoin price presents a non-stationary behavior. Thus, it is observed that in long term, Bitcoin behaves more like a traditional instrument and, therefore, is increasingly affected by the international context and economic fundamentals. Likewise, the results showed that the selected attributes and the best machine learning model achieved an improvement of more than 10% in accuracy, for the price direction predictions with respect to the state-of-the-art papers, using the same period of information. In relation to the maximum, minimum and closing Bitcoin prices regressions, it was possible to obtain Mean Absolute Percentage Errors between 1% and 2%. Finally, in the prediction of intra-daily price movement, through the use of data-stream learning techniques, is obtained a result that improves more than 6% in accuracy to other previous studies.
Estudo de microscopia eletrônica de transmissão in situ de nanoestrutura de óxidos mistos em altas temperaturas
(Universidade Federal de São Carlos, 2018-09-19) Maya Johnson, Santiago; Leite, Edson Roberto; https://lattes.cnpq.br/1025598529469393; https://lattes.cnpq.br/1898909730588076
This work addresses the characterization of the high temperature reactions between different nanoparticles oxides, CeO2-ZrO2 and CeO2-SnO2, by the direct observation of the phenomenon by in situ Transmission Electron Microscopy (TEM). The nanoparticles were synthesized via three different synthesis methods, hydrothermal, solvothermal, and solvent-control. The changes in the size and morphology of the nanoparticles, the interactions that lead to processes of sintering / densification, and the phase transformations that occur during the experiments were documented. Also, a detailed study of the influence of the electron beam current density on the sample, and its synergism with the temperature during the in situ experiments was performed. The interactions between the oxide metal nanoparticles and the films of the TEM grids showed a great influence during the in situ tests at high temperature. For the experimental setups tested in this work, the main mechanism of interaction between the nanoparticles was oriented attachment.
A motivação de alunos na preparação e demonstração de experimentos para a divulgação de química: um olhar a partir da teoria da autodeterminação
(Universidade Federal de São Carlos, 2018-09-19) Faitanini, Beatriz Derisso; Bretones, Paulo Sérgio; https://lattes.cnpq.br/0016646045895716; https://lattes.cnpq.br/4716307148937666
This research had as its main objective the study of the motivational profile of students from the first year of High School in a private school of São Carlos during the completion of a choice process, preparation and demonstration of experimental practices of Chemistry. For understanding of the motivation in the school context it was used as a theoretical reference the Self-Determination Theory, outlining six motivational levels which an individual may present, proposing a self-determination continuum of self-determination. To collect data two questionnaires were used, an open-ended and the other using the Likert scale, applied before and after the completion of a process, and the meetings filming. The open-ended questionnaire aimed to evaluate the satisfaction of the basic psychological needs of the students during the research; the questionnaire using the Likert scale aimed to obtain the students' motivational profile. The data analysis showed that before the implementation of this project the students had higher MR values for the Integrated Regulation and lower for the less self-determined motivational forms. After the project was carried out, the MR values for Integrated Regulation and Intrinsic Motivation increased even more, while the values for less self-determined forms, such as amotivation, decreased, showing that there were – in reference of learning motives - a significant variation in the students' motivational profile. The individual analysis of the students showed that there was a significant change in the motivational orientation of three students, while the others remained with the same motivational orientation, mainly because they were students who declared themselves motivated to study Chemistry even before the implementation of the project. We also observed that the data provided elements that confirm that the occurrence of situations that favor the satisfaction of the basic psychological needs brings the enthusiasm of the students in situations considered favorable to the promotion of intrinsic motivation. Thus, the data collection instruments showed themselves as adequate for the objectives of this work, but it is still important to continue research on the motivation of students in chemistry classes, mainly to understand how the satisfaction of basic needs can influence this change of motivational profile and what factors influence the satisfaction of these needs.