Da transcrição à legendagem em busca da perda mínima de conteúdo

Como projeto final do Mestrado em Tradução e Interpretação Especializadas foi proposta a legendagem de um excerto de uma apresentação oral, em ambiente de debate, de um discurso do ator Stephen Fry. Inseriu-se o trabalho no âmbito do mestrado e no seguimento da licenciatura na mesma área, possibilitando o exercício de três das principais áreas do curso: transcrição, tradução e legendagem, por esta ordem. Procurou-se inovar no sentido de aproximar a transcrição à legendagem, com a menor supressão possível de texto e consequentemente da mensagem, enquanto se cumpriram na íntegra as normas e sugestões dos autores-chave da área. Como elementos técnicos do trabalho estão inseridos no corpo do texto a transcrição, a tradução e a legendagem, pois estes são os objetos práticos do trabalho e o grande desafio proposto foi o seguinte: manter a fidelidade entre estes três modos de transferência – obedecer a todo o procedimento distinto a que estes modos obrigam, mas mantendo entre eles uma similaridade que os torne praticamente iguais, no sentido de transmissão da mensagem. Apresentaram-se também uma breve história da tradução audiovisual, os diferentes tipos da mesma, uma abordagem à realidade da área em Portugal, uma contextualização do excerto e do seu conteúdo e a vertente técnica na sua globalidade.

A perspectiva dos professores sobre o alargamento da escolaridade obrigatória e a inclusão de alunos com necessidades educativas especiais no ensino seundário

O tema da dissertação prende-se com as consequências do alargamento da escolaridade obrigatória nas Escolas Secundárias, concretamente naquilo que se relaciona com o previsível aumento de casos de alunos com Necessidades Educativas Especiais decorrente desse alargamento. Este trabalho pretende conhecer o que os professores pensam sobre este tema no que se refere à sua concepção sobre inclusão e Necessidades Educativas Especiais, às suas experiências anteriores com este tipo de alunos, como encaram os professores o alargamento da escolaridade obrigatória no secundário, qual o nível de preparação que pensam ter para trabalhar com estes alunos, como encaram as adequações curriculares que serão necessárias e finalmente que tipo de necessidades pensam que podem surgir nas escolas para dar uma resposta adequada à nova situação. Para que todas as afirmações dos professores estivessem fundamentadas, fez-se uma abordagem teórica referente à evolução do ensino em Portugal e da Educação Especial numa perspectiva nacional e internacional, fazendo também um contraponto com a actualidade. Em termos metodológicos, optou-se por um estudo qualitativo, com características exploratórias e descritivas. Para a recolha de dados foi selecionada uma escola do centro de Lisboa, que se situa numa zona habitacional e de serviços. Realizaram-se seis entrevistas semi-dirigidas, construídas a partir de um guião, constituído por um conjunto de questões formuladas segundo objectivos e organizadas por temas. Para analisar os dados, foi utilizada a técnica de análise de conteúdo. A análise feita permitiu concluir que esta temática não é uma preocupação actual dos professores do ensino secundário. Apesar da aceitação genérica do conceito de inclusão, os professores sentem dificuldade na adequação de conteúdos e na adaptação do sistema de avaliação, embora todos os entrevistados tivessem experiências anteriores com alunos com Necessidades Educativas Especiais. Quanto às necessidades que podem surgir, os professores consideram que elas se vão relacionar sobretudo com equipamento informático, acessibilidades e formação de professores. - Abstract The subject approached in this paper relates to the consequences of the extent of mandatory school years in secondary schools, specifically with the increase in the number of students with special educational needs. Therefore it will be evaluated teacher’s opinions and ideas about the subject, how they define inclusion and special educational needs, their prior experiences with this kind of students and how they intend to face the extend of mandatory school years, their background to deal with this students, and the changes that, in school, they think would be necessary to give adequate answers to this new situation. In order to support teacher’s opinions, a theoretical approach was made, regarding the evolution of teaching and of Special Education in Portugal, in a national and international perspective, comparing it to our current reality. To achieve these goals, a qualitative research was designed, in order to obtain exploratory and descriptive data. To collect the data, a semi-structured interview was created from some preestablished guidelines, according to the objectives and organized by topics, these interviews took place in a school located in the center of Lisbon. To analyze the answers, a content analysis technique was used. The results observed allowed to conclude that this subject is not a current concern for the interviewed teachers. Despite the global acceptance of inclusion, as a concept, teachers still have some difficulties adapting contents and adapting the evaluation system, although all the teachers interviewed had prior experience with students with special educational needs. About the necessities that may emerge, teachers think they will be computer related, regarding accessibility and regarding teacher formation.

Methods for automatic and assisted image annotation

Personal memories composed of digital pictures are very popular at the moment. To retrieve these media items annotation is required. During the last years, several approaches have been proposed in order to overcome the image annotation problem. This paper presents our proposals to address this problem. Automatic and semi-automatic learning methods for semantic concepts are presented. The automatic method is based on semantic concepts estimated using visual content, context metadata and audio information. The semi-automatic method is based on results provided by a computer game. The paper describes our proposals and presents their evaluations.

A hybrid intelligent system for distributed dynamic scheduling

This chapter addresses the resolution of dynamic scheduling by means of meta-heuristic and multi-agent systems. Scheduling is an important aspect of automation in manufacturing systems. Several contributions have been proposed, but the problem is far from being solved satisfactorily, especially if scheduling concerns real world applications. The proposed multi-agent scheduling system assumes the existence of several resource agents (which are decision-making entities based on meta-heuristics) distributed inside the manufacturing system that interact with other agents in order to obtain optimal or near-optimal global performances.

Energy and reserve provision dispatch considering distributed generation and demand response

In competitive electricity markets with deep concerns at the efficiency level, demand response programs gain considerable significance. In the same way, distributed generation has gained increasing importance in the operation and planning of power systems. Grid operators and utilities are taking new initiatives, recognizing the value of demand response and of distributed generation for grid reliability and for the enhancement of organized spot market´s efficiency. Grid operators and utilities become able to act in both energy and reserve components of electricity markets. This paper proposes a methodology for a joint dispatch of demand response and distributed generation to provide energy and reserve by a virtual power player that operates a distribution network. The proposed method has been computationally implemented and its application is illustrated in this paper using a 32 bus distribution network with 32 medium voltage consumers.

Intelligent electric vehicle heuristic for energy resource management using simulated annealing

The smart grid concept appears as a suitable solution to guarantee the power system operation in the new electricity paradigm with electricity markets and integration of large amounts of Distributed Energy Resources (DERs). Virtual Power Player (VPP) will have a significant importance in the management of a smart grid. In the context of this new paradigm, Electric Vehicles (EVs) rise as a good available resource to be used as a DER by a VPP. This paper presents the application of the Simulated Annealing (SA) technique to solve the Energy Resource Management (ERM) of a VPP. It is also presented a new heuristic approach to intelligently handle the charge and discharge of the EVs. This heuristic process is incorporated in the SA technique, in order to improve the results of the ERM. The case study shows the results of the ERM for a 33-bus distribution network with three different EVs penetration levels, i. e., with 1000, 2000 and 3000 EVs. The results of the proposed adaptation of the SA technique are compared with a previous SA version and a deterministic technique.

Distributed energy resource short-term scheduling using signaled particle swarm optimization

Distributed Energy Resources (DER) scheduling in smart grids presents a new challenge to system operators. The increase of new resources, such as storage systems and demand response programs, results in additional computational efforts for optimization problems. On the other hand, since natural resources, such as wind and sun, can only be precisely forecasted with small anticipation, short-term scheduling is especially relevant requiring a very good performance on large dimension problems. Traditional techniques such as Mixed-Integer Non-Linear Programming (MINLP) do not cope well with large scale problems. This type of problems can be appropriately addressed by metaheuristics approaches. This paper proposes a new methodology called Signaled Particle Swarm Optimization (SiPSO) to address the energy resources management problem in the scope of smart grids, with intensive use of DER. The proposed methodology’s performance is illustrated by a case study with 99 distributed generators, 208 loads, and 27 storage units. The results are compared with those obtained in other methodologies, namely MINLP, Genetic Algorithm, original Particle Swarm Optimization (PSO), Evolutionary PSO, and New PSO. SiPSO performance is superior to the other tested PSO variants, demonstrating its adequacy to solve large dimension problems which require a decision in a short period of time.

An integrated approach for distributed energy resource short term scheduling in smart grids considering realistic power system simulation

The large increase of distributed energy resources, including distributed generation, storage systems and demand response, especially in distribution networks, makes the management of the available resources a more complex and crucial process. With wind based generation gaining relevance, in terms of the generation mix, the fact that wind forecasting accuracy rapidly drops with the increase of the forecast anticipation time requires to undertake short-term and very short-term re-scheduling so the final implemented solution enables the lowest possible operation costs. This paper proposes a methodology for energy resource scheduling in smart grids, considering day ahead, hour ahead and five minutes ahead scheduling. The short-term scheduling, undertaken five minutes ahead, takes advantage of the high accuracy of the very-short term wind forecasting providing the user with more efficient scheduling solutions. The proposed method uses a Genetic Algorithm based approach for optimization that is able to cope with the hard execution time constraint of short-term scheduling. Realistic power system simulation, based on PSCAD , is used to validate the obtained solutions. The paper includes a case study with a 33 bus distribution network with high penetration of distributed energy resources implemented in PSCAD .

Distributed generation producers' reserve management

Sustainable development concerns are being addressed with increasing attention, in general, and in the scope of power industry, in particular. The use of distributed generation (DG), mainly based on renewable sources, has been seen as an interesting approach to this problem. However, the increasing of DG in power systems raises some complex technical and economic issues. This paper presents ViProd, a simulation tool that allows modeling and simulating DG operation and participation in electricity markets. This paper mainly focuses on the operation of Virtual Power Producers (VPP) which are producers’ aggregations, being these producers mainly of DG type. The paper presents several reserve management strategies implemented in the scope of ViProd and the results of a case study, based on real data.

ANN based support for distributed energy resources scheduling in smart grids

The future scenarios for operation of smart grids are likely to include a large diversity of players, of different types and sizes. With control and decision making being decentralized over the network, intelligence should also be decentralized so that every player is able to play in the market environment. In the new context, aggregator players, enabling medium, small, and even micro size players to act in a competitive environment, will be very relevant. Virtual Power Players (VPP) and single players must optimize their energy resource management in order to accomplish their goals. This is relatively easy to larger players, with financial means to have access to adequate decision support tools, to support decision making concerning their optimal resource schedule. However, the smaller players have difficulties in accessing this kind of tools. So, it is required that these smaller players can be offered alternative methods to support their decisions. This paper presents a methodology, based on Artificial Neural Networks (ANN), intended to support smaller players’ resource scheduling. The used methodology uses a training set that is built using the energy resource scheduling solutions obtained with a reference optimization methodology, a mixed-integer non-linear programming (MINLP) in this case. The trained network is able to achieve good schedule results requiring modest computational means.

Multilevel negotiation in smart grids for VPP management of distributed resources

A multilevel negotiation mechanism for operating smart grids and negotiating in electricity markets considers the advantages of virtual power player management.

Virtual power producers simulation - negotiating renewable distributed generation in competitive electricity markets

Sustainable development concerns made renewable energy sources to be increasingly used for electricity distributed generation. However, this is mainly due to incentives or mandatory targets determined by energy policies as in European Union. Assuring a sustainable future requires distributed generation to be able to participate in competitive electricity markets. To get more negotiation power in the market and to get advantages of scale economy, distributed generators can be aggregated giving place to a new concept: the Virtual Power Producer (VPP). VPPs are multi-technology and multisite heterogeneous entities that should adopt organization and management methodologies so that they can make distributed generation a really profitable activity, able to participate in the market. This paper presents ViProd, a simulation tool that allows simulating VPPs operation, in the context of MASCEM, a multi-agent based eletricity market simulator.

Towards a future SCADA

Currently, Power Systems (PS) already accommodate a substantial penetration of DG and operate in competitive environments. In the future PS will have to deal with largescale integration of DG and other distributed energy resources (DER), such as storage means, and provide to market agents the means to ensure a flexible and secure operation. This cannot be done with the traditional PS operation. SCADA (Supervisory Control and Data Acquisition) is a vital infrastructure for PS. Current SCADA adaptation to accommodate the new needs of future PS does not allow to address all the requirements. In this paper we present a new conceptual design of an intelligent SCADA, with a more decentralized, flexible, and intelligent approach, adaptive to the context (context awareness). Once a situation is characterized, data and control options available to each entity are re-defined according to this context, taking into account operation normative and a priori established contracts. The paper includes a case-study of using future SCADA features to use DER to deal with incident situations, preventing blackouts.

Scheduling distributed energy resources in an isolated grid - an artificial neural network approach

Power Systems (PS), have been affected by substantial penetration of Distributed Generation (DG) and the operation in competitive environments. The future PS will have to deal with large-scale integration of DG and other distributed energy resources (DER), such as storage means, and provide to market agents the means to ensure a flexible and secure operation. Virtual power players (VPP) can aggregate a diversity of players, namely generators and consumers, and a diversity of energy resources, including electricity generation based on several technologies, storage and demand response. This paper proposes an artificial neural network (ANN) based methodology to support VPP resource schedule. The trained network is able to achieve good schedule results requiring modest computational means. A real data test case is presented.

Intelligent multi-player smart grid management considering distributed energy resources and demand response

The smart grid concept is rapidly evolving in the direction of practical implementations able to bring smart grid advantages into practice. Evolution in legacy equipment and infrastructures is not sufficient to accomplish the smart grid goals as it does not consider the needs of the players operating in a complex environment which is dynamic and competitive in nature. Artificial intelligence based applications can provide solutions to these problems, supporting decentralized intelligence and decision-making. A case study illustrates the importance of Virtual Power Players (VPP) and multi-player negotiation in the context of smart grids. This case study is based on real data and aims at optimizing energy resource management, considering generation, storage and demand response.