Abstract
This paper describes a two-month summer collective internship conceived to provide a unique hands-on experience in robotics. The objective of the Robotics Craftsmanship International Academy, or RobotCraft for short, is to introduce higher education students in the full design cycle of a mobile robotic platform, providing training in computer-aided design (CAD), mechatronics, low-level programming of embedded systems, high-level development using the Robot Operating System (ROS), and artificial intelligence. This non-academic teaching, which successfully completed its second edition, already encompassed around 150 students and 100 universities, being evaluated by participants as challenging, engaging, and beneficial not only to their overall understanding of robotics, but also guiding them through their future academic and professional endeavors. © 2019, Springer Nature Switzerland AG.

Abstract
This paper describes a two-month summer intensive course designed to introduce participants with a hands-on technical craft on robotics and to acquire experience in the low-level details of embedded systems. Attendants started this course with a brief introduction to robotics; learned to draw, design and create a personalized 3D structure for their mobile robotic platform and developed skills in embedded systems. They were familiarize with the practices used in robotics, learning to connect all sensors and actuator, developing a typical application on differential kinematic using Arduino, exploring ROS features under Raspberry Pi environment and Arduino - Raspberry Pi communication. Different paradigms and some real applications and programming were addressed on the topic of Artificial Intelligence. This paper describes not just the concept, layout and methodology used on RobotCraft 2017 but also presents the participants knowledge background and their overall opinions, leading to focus on lessons learned and suggestions for future editions.

Abstract
Information Extraction (IE) and fusion are complex fields and have been useful in several domains to deal with heterogeneous data sources. Criminal police are challenged in forensics activities with the extraction, processing and interpretation of numerous documents from different types and with distinct formats (templates), such as narrative criminal reports, police databases and the result of OSINT activities, just to mention a few. Such challenges suggest, among others, to cope with and manually connect some hard to interpret meanings, such as license plates, addresses, names, slang and figures of speech. This paper aims to deal with forensic IE and fusion, thus a system was proposed to automatically extract, transform, clean, load and connect police reports that arrived from different sources. The same system aims to help police investigators to identify and correlate interesting extracted entities. © 2020, Springer Nature Switzerland AG.

Abstract
RobotCraft is an international internship with a summer course in robotics designed especially for BSc to PhD students. The students attending this 2-months program have the opportunity to work in robotics, focusing on several state-of-theart approaches, technologies and learned how to design, build and program their robots throughout multiple activities, carefully prepared to provide a wide range of skills and knowledge in the topic. This paper describes the methodology used to introduce participants to a hands-on technical craft on robotics and to acquire experience in the low-level details of embedded systems.

Abstract
In this paper we describe a comparative classification of Pneumonia using Convolution Neural Network. The database used was the dataset Labeled Optical Coherence Tomography (OCT) and Chest X-Ray Images for Classification made available by (Kermany, 2018) with a total of 5863 images, with 2 classes: normal and pneumonia. To evaluate the generalization capacity of the models, cross-validation of k-fold was used. The classification models proved to be efficient compared to the work of (Kermany et al., 2018) which obtained 92.8 % and the present work had an average accuracy of 95.30 %.

Abstract
The lack of physical activity and poor nutrition triggers various diseases, among them is diabetes. In this context, several researches seek ways that can mitigate these diseases to provide a better quality of life for people. Therefore, the present work aims to analyze the possible inhibitors of the enzyme Dipeptidil Peptidase 4 that hypotheses will be stipulated for the creation of new drugs through molecular docking techniques, that is, a computational simulation of combinations of drugs of the family of gliptins with other antidiabetics (metformin, glyburide and cucurbitacin). Among the results, it was observed that the antidiabetic cucurbitacin combined with the gliptines obtained greater energy during the process.