Systematic Review Data
The systematic review data for the paper On the Relevancy of Data Science for Flight Delay Research can be found at survey-analysis.xls.
The possibility for the reader to be able to reproduce all the results presented in papers is significant for the scientific method. Initiatives that publishes methods and experimental evaluation using active documents (such as Jupyter notebook) are relevant for support reproducibility. We have provided an example (analytics-example.ipynb) of a reproducible code that enables the comprehension of some data analytics methods presented in the paper.
Student: Heraldo Pimenta Borges Filho (email@example.com) Advisor: Eduardo Ogasawara (firstname.lastname@example.org) Description: The package STMotif allows performing research of motif in spatial-time series. A motif is a previously unknown subsequence of a (spatial) time series with a relevant number of occurrences. The main purpose is to find a way to handle the issue of large amounts […] Continue reading →
This page contains information about Data Rio Dataset for Urban mobility research. Continue reading →
The Brazilian flight dataset is available at http://eic.cefet-rj.br/~eogasawara/data/flight. The file “airports-br.xlsx” contains all Brazilian airports descriptions. The file “vra.RData” contains all flight data from jan/2009 to dec/2017. The file airports_hist.xlsx contains the histogram of airports activities. It can be observed that the major 62 airports that interact with Brazilian flight mesh correspond to 94% of all flights […] Continue reading →
Students: Diego Vaz Caetano, Josué Dias Cardoso and Luana Guimarães Piani Ferreira Collaborators: Raphael Abreu, João Quadros, Joel Santos Advisors: Leonardo Lignani, Eduardo Ogasawara Abstract The use of simulators as educational tools aims to increase students’ engagement in classes and seems to help them to understand difficult concepts. They can be used in natural science […] Continue reading →
Student: Rebecca Pontes Salles (email@example.com) Advisor: Eduardo Ogasawara (firstname.lastname@example.org) Description: Functions for time series prediction and accuracy assessment using automatic linear modeling. The generated linear models and its yielded prediction errors can be used for benchmarking other time series prediction methods and for creating a demand for the refinement of such methods. For this purpose, […] Continue reading →
Authors: Paula Chaves, Luan Paschoal, Tauan Velasco, Tiago Bento Sampaio, Julliany Brandão, Carlos Otávio Schocair, João Quadros, Talita Oliveira, Eduardo Ogasawara Abstract The new orthographic agreement introduces some changes in the vocabulary of the Portuguese language. Although these changes have modified a small percentage of the vocabulary words, people are struggling to adapt to some […] Continue reading →
Students: Anderson Silva, Fábio Rosa Advisor: Eduardo Ogasawara Abstract: Over the past years, online social networks have increasingly become part of everyday life in many countries. Due to that, enterprises are increasing their presence in online social networks. To make them more attractive, they study ways to innovate and combine digital marketing with new technologies. […] Continue reading →
Students: Leonardo Souto Gimenes Pimentel Collaborators: Kele Belloze, Jorge Soares, Eduardo Ogasawara, Renato Mauro According to the Brazilian Constitution, the only way to become a public employee is passing a public exam. The job-knowledge exam is one of the most important components of a public exam. Studying for such exam is a challenging task that […] Continue reading →
Students: Ana Beatriz Cruz, Sabrina Seriques, and Leonardo Preuss Advisor: Eduardo Ogasawara Abstract: Computer Science students are usually enthusiastic about learning Artificial Intelligence (AI) due to the possibility of developing computer games that incorporate AI behaviors. Under this scenario, Search Algorithms (SA) are a fundamental subject of AI for a broad variety of games. Implementing […] Continue reading →