The Computational Thinking (CT) is recognized as a set of reasoning and critical skills, classified as “mental tools” to be used by the individual in solving various problems. Developing the competence of this “computational ...

The evolution of the Internet and the Web has given rise to a vast amount of text messages containing opinions. Although the importance of sentiment analysis has grown proportionately, the use of the traditional bag of ...

Electricity in Brazil is mostly generated by hydroelectric plants that depend on the volume of water in their reservoirs. Due to the fact that rainfall is decreasing, other methods with higher costs to generate energy are ...

Privacy is the cause of an important concern in the context of mobile applications, once these applications manipulate a countless number of the users’ confidential and personal information through their mobile devices. ...

Virtualization is one of the foundations of cloud computing as it allows better utilization of computing resources in a data center. There are different virtualization approaches that offer similar functionality, but with ...

The Smart City (SC) concept aims to promote dynamic and flexible systems to the cities, that interact with each others and help to maintain the stability and scalability of it’s resources and services, usually through ...

Due to the widespread adoption of distributed systems when building applications, demand for reliability and availability has increased. These properties can be achieved through replication techniques using algorithms that ...

The methodologies currently used by startups for market discovery and software development focus on a more agile and fast development, aiming to obtain learning about the potential market. Often, these methodologies set ...

This work describes a new classification technique called P2C - Partitioning to Classify. The main goal is to achieve reasonable classification performances using linear prediction methods, even on datasets with non-linear ...

Unsupervised data clustering is not a trivial process, as no previous knowledge is available and real data is often complex and multi-faceted. To make matters worse, traditionally, clustering aims to describe the data ...