Gustavo Henrique Matos Bezerra Motta

An instance selection method for large datasets based on Markov Geometric Diffusion

Given the growing amount of data produced from within different areas of knowledge, data mining methods currently have to face challenging datasets with greater numbers of instances and attributes. However, the processing capacity of data mining algorithms is struggling under this growth. One alternative for tackling the problem is to perform instance selection on the data in order to reduce its size, as a preprocessing step for data mining algorithms.This study presents e-MGD, a method for instance selection as an extension of the Markov Geometric Diffusion method, which is a linear complexity method used in computergraphics for the simplification of triangular meshes. The original method was extended so that it was capable of reducing datasets commonly found in the field of data mining. For this purpose, two essential points of adjustment were required. Firstly, it was necessary to build a geometric structure from the data and secondly, to adjust the method so that it could deal with types of attributes encountered within these datasets. These adjustments however, did not influence the complexity of the final e-MGD, since it remained linear, which enabled it to be applied to datasets with a greater number of instances and features. One distinct characteristic of the proposed extension is that it focuses on preserving dataset information rather than improving classification accuracy, as in the case of most instance selection methods.In order to assess the performance of the method, we compared it with a number of classical and contemporary instance selection methods using medium to large datasets, plus a further set of very large datasets. The results demonstrated a good performance in terms of classification accuracy when compared to results from other methods, indicating that the e-MGD is a good alternative for instance selection.

A Multi-stream Tool to Support Transmission in Surgery Applied to Telemedicine

The increasing network bandwidth capacity and the diminishing costs of related services have led to a rising number of applications in the field of Information and Communication Technology. A special case is applications based on video streaming. Telemedicine can be highlighted in some scenarios for applying this technology, such as clinical sessions, second medical opinion, interactive lessons or virtual conferences. These scenarios often imply a dedicated transmission environment. A restriction in such solutions is the inability to handle multiple video streams. Thus, this paper presents a low-cost infrastructure for video collaboration in healthcare and based on open technologies. The proposed infrastructure enables remote management of simultaneous multiple streams. We also discuss results of experiments held in the Lauro Wanderley Academic Hospital, Brazil. One of the results is the contribution for teaching experiences, particularly by allowing students to remotely regard surgical procedures and providing real-time interaction. Finally, we present new prospects for using the developed technology on other applications in Telemedicine and Telepresence.

Experiences with Arthron for Live Surgery Transmission in Brazilian Telemedicine University Network

The increasing network bandwidth capacity and the diminishing costs of related services have led to a rising number of applications in the field of Information and Communication Technology. A special case is applications based on video streaming. Telemedicine can be highlighted in some scenarios for applying this technology, such as clinical sessions, second medical opinion, interactive lessons or virtual conferences. These scenarios often imply a dedicated transmission environment. A restriction in such solutions is the inability to handle multiple video streams. Thus, this paper presents a low-cost infrastructure for video collaboration in healthcare and based on open technologies. The proposed infrastructure enables remote management of simultaneous multiple streams. We also discuss results of experiments held in the Lauro Wanderley Academic Hospital, Brazil. One of the results is the contribution for teaching experiences, particularly by allowing students to remotely regard surgical procedures and providing real-time interaction. Finally, we present new prospects for using the developed technology on other applications in Telemedicine and Telepresence.

A Strategy of Multimedia Reflectors to Encryption and Codification in Real Time

The constant need of sharing data in information systems leads to the development of more complex and creative solutions to the physical or cost limitations of the nowadays technology. The main problems of a distributed system include: the huge information volume by time interval carried over the network infrastructure, and the confidentiality of the ongoing data. Going into the media transmission sub area, there are even more restrictions to be considered. Error or delay, for example, can drastically impact the user experience in real-time transmission. In this context, this paper proposes a tool for performing efficient and secure distribution and encryption of video streams. This tool was implemented and applied in several contexts. In order to validate the tool in a set of possible situations, tests of the video reflector were made using several sets of parameters evolving variations of video codecs and presence or absence of cryptography.