Entrincheirados no tempo: a FEB e os ex-combatentes no cinema documentário

Pós-graduação em História - FCHS

O impacto da crise do socialismo no partido comunista do Brasil, 1988-1992

O artigo analisa o impacto das transformações no Leste Europeu sobre o Partido Comunista do Brasil (PC do B), entre o 7a Congresso Partidario (maio de 1988) e o 8° Congresso (fevereiro de 1992). Esse impacto levou a mudanças no partido, as quais podem ser assim resumidas: crítica moderada a Stalin, mais importante por ser a primeira na história do PC do B (manteve-se, entretanto, a concepção de partido marxista-leninista de vanguarda); abandono da teoria das duas etapas da revolução brasileira; realinhamento político no plano internacional, em apoio a partidos comunistas dentro e fora do poder; pêndulo à esquerda na política interna brasileira.

As primeiras interpretações marxistas da realidade brasileira

Pós-graduação em Ciências Sociais - FFC

Comparing support vector machines and artificial neural networks in the recognition of steering angle for driving of mobile robots through paths in plantations

The use of mobile robots turns out to be interesting in activities where the action of human specialist is difficult or dangerous. Mobile robots are often used for the exploration in areas of difficult access, such as rescue operations and space missions, to avoid human experts exposition to risky situations. Mobile robots are also used in agriculture for planting tasks as well as for keeping the application of pesticides within minimal amounts to mitigate environmental pollution. In this paper we present the development of a system to control the navigation of an autonomous mobile robot through tracks in plantations. Track images are used to control robot direction by pre-processing them to extract image features. Such features are then submitted to a support vector machine and an artificial neural network in order to find out the most appropriate route. A comparison of the two approaches was performed to ascertain the one presenting the best outcome. The overall goal of the project to which this work is connected is to develop a real time robot control system to be embedded into a hardware platform. In this paper we report the software implementation of a support vector machine and of an artificial neural network, which so far presented respectively around 93% and 90% accuracy in predicting the appropriate route. (C) 2013 The Authors. Published by Elsevier B.V. Selection and peer review under responsibility of the organizers of the 2013 International Conference on Computational Science

The Changing Nature of Multilateralism and Brazilian Foreign Policy

An important characteristic of the current international setting is the crisis of the structure in existence, rather than the emergence of a new order. The rise of new interests and demands, as well as the speed of the transformation make the current understanding of global governance more complex. Brazil, like other medium powers, has an interest in institutionalised multilateralism as a means of increasing its bargaining capacity and hindering the unilateralism of major powers, without being antagonistic to them. It is attempting to increase its weight in traditional international bodies, which provide the grounding for international legitimacy, as well as in new informal arrangements. While this strategy could lead to the establishment of a new hierarchy that brings in countries of growing relative importance, it has put the weight of regional integration into another perspective in Brazilian foreign policy.

The application of neural networks to the analysis of dissolved gases in insulating oil used in transformers

The state of insulating oils used in transformers is determined through the accomplishment of physical-chemical tests, which determine the state of the oil, as well as the chromatography test, which determines possible faults in the equipment. This article concentrate on determining, from a new methodology, a relationship among the variation of the indices obtained from the physical-chemical tests with those indices supplied by the chromatography tests.The determination of the relationship among the tests is accomplished through the application of neural networks. From the data obtained by physical-chemical tests, the network is capable to determine the relationship among the concentration of the main gases present in a certain sample, which were detected by the chromatography tests.More specifically, the proposed approach uses neural networks of perceptron type constituted of multiple layers. After the process of network training, it is possible to determine the existent relationship between the physical-chemical tests and the amount of gases present in the insulating oil.