Relatório de estágio

Relatório de Estágio apresentado ao Instituto Superior de Contabilidade para a obtenção do Grau de Mestre em Auditoria Orientada por Dr. Rodrigo Mário de Oliveira Carvalho e Dr. Álvaro Manuel de Sousa Carvalho

Lingüística de corpus e estudos da tradução

O objectivo principal deste ensaio é discutir o interesse crescente que os Estudos da Tradução tem expressado acerca da Lingüística de Corpus e seu importante papel para a investigação do fenómeno tradutório. O ensaio apresenta os primeiros trabalhos na interface entre corpora e tradução e como a disciplina dos Estudos da Tradução de base em corpus evoluiu na última década. Uma atenção mais pontual é dada à noção de estudos em corpus de pequena dimensão e sua influência no campo das pesquisas em tradução no Brasil. Além disso, o ensaio explora como o conceito de representatividade tem recebido definições diferentes nos estudos dos fenómenos tradutórios de base em corpus.

Abordagens discursivas dos estudos da tradução

The main aim of this essay is to present the discursive approaches to Translation Studies (TS) as a well-established field of inquiry about translation phenomena. The term ‘discourse’ itself, however, has been considered a contentious one given its multitude of uses without a clear conceptualization as to whether its use and application privilege a more linguistic orientation or a more sociologically and culturally trend to the study of language. The essay, therefore, briefly discusses what counts as ‘discursive’ in TS by introducing the reader to the principal theories that advocate an essentially ‘discursive turn’ in orientation. After that, the essay explores in depth Systemic-Functional Linguistics as a foundational approach to the study of translation. Finally, the essay brings in the advantages of such an approach and, in the end, invites TS theoreticians to give special attention to the uses of the term ‘discourse’ within their investigations.

Multilayer Perceptron Neural Networks Training Through Charged System Search and its Application for Non-Technical Losses Detection

The non-technical loss is not a problem with trivial solution or regional character and its minimization represents the guarantee of investments in product quality and maintenance of power systems, introduced by a competitive environment after the period of privatization in the national scene. In this paper, we show how to improve the training phase of a neural network-based classifier using a recently proposed meta-heuristic technique called Charged System Search, which is based on the interactions between electrically charged particles. The experiments were carried out in the context of non-technical loss in power distribution systems in a dataset obtained from a Brazilian electrical power company, and have demonstrated the robustness of the proposed technique against with several others natureinspired optimization techniques for training neural networks. Thus, it is possible to improve some applications on Smart Grids.