Automatic inspection of petroleum well drilling has became paramount in the last years, mainly because of the crucial importance of saving time and operations during the drilling process in order to avoid some problems, such as the collapse of the well borehole walls. In this paper, we extended another work by proposing a fast petroleum well drilling monitoring through a modified version of the...

It was introduced in this paper the Optimum-Path Forest for land use classification aiming a better environmental management, using images obtained from CBERS 2B CCD satellite covering the area of the Rio das Pedras watershed, Itatinga City, São Paulo State, Brazil. We also compared the Optimum-Path Forest algorithm with the well known supervised classifiers: Artificial Neural Networks using Mu...

We show that, given a wheel with nonnegative edge lengths and pairs of terminals located on the wheel's outer cycle such that no two terminal pairs cross, then a path packing, i. e., a collection of edge disjoint paths connecting the given terminal pairs, of minimum length can be found in strongly polynomial time. Moreover, we exhibit for this case a system of linear inequalities that provides ...

the most important objectives of monetary policy are to provide price stability, economic growth and favorable employment levels. since achieving these goals is not directly accessible for policy makers, so introducing and studying the appropriate tools and intermediate targets seem necessary. for this reason, this paper tries to answer this question: whether can we introduce an appropriate rul...

In the last decade, machine learning-based approaches became capable of performing a wide range complex tasks sometimes better than humans, demanding fraction time. Such an advance is partially due to exponential growth in amount data available, which makes it possible extract trustworthy real-world information from them. However, such generally imbalanced since some phenomena are more likely o...

We present a graph-based framework for pattern recognition, called Optimum-Path Forest (OPF), and describe one of its classifiers developed for the supervised learning case. This classifier does not require parameters and can handle some overlapping among multiple classes with arbitrary shapes. The method reduces the pattern recognition problem into the computation of an optimum-path forest in ...

OPFython is an open-sourced Python package that implements Optimum-Path Forest algorithms using object-oriented programming and a straightforward structure. It provides alternative implementation to the standard LibOPF package, which heavily depends on C language occasionally hinders fast prototyping. Additionally, documented code, unitary tests, examples assist users in learning how work with ...