Modelos e interfaces gráficos para objectos de aprendizagem na área da saúde

A educação é uma área bastante importante no desenvolvimento humano e tem vindo a adaptar-se às novas tecnologias. Tentam-se encontrar novas maneiras de ensinar de modo a obter um rendimento cada vez maior na aprendizagem das pessoas. Com o aparecimento de novas tecnologias como os computadores e a Internet, a concepção de aplicações digitais educativas cresceu e a necessidade de instruir cada vez melhor os alunos leva a que estas aplicações precisem de um interface que consiga leccionar de uma maneira rápida e eficiente. A combinação entre o ensino com o auxílio dessas novas tecnologias e a educação à distância deu origem ao e-Learning (ensino à distância). Através do ensino à distância, as possibilidades de aumento de conhecimento dos alunos aumentaram e a informação necessária tornou-se disponível a qualquer hora em qualquer lugar com acesso à Internet. Mas os cursos criados online tinham custos altos e levavam muito tempo a preparar o que gerou um problema para quem os criava. Para recuperar o investimento realizado decidiu-se dividir os conteúdos em módulos capazes de serem reaproveitados em diferentes contextos e diferentes tipos de utilizadores. Estes conteúdos modulares foram denominados Objectos de Aprendizagem. Nesta tese, é abordado o estudo dos Objectos de Aprendizagem e a sua evolução ao longo dos tempos em termos de interface com o utilizador. A concepção de um interface que seja natural e simples de utilizar nem sempre é fácil e independentemente do contexto em que se insere, requer algum conhecimento de regras que façam com que o utilizador que use determinada aplicação consiga trabalhar com um mínimo de desempenho. Na concepção de Objectos de Aprendizagem, áreas de complexidade elevada como a Medicina levam a que professores ou doutores sintam alguma dificuldade em criar um interface com conteúdos educativos capaz de ensinar com eficiência os alunos, devido ao facto de grande parte deles desconhecerem as técnicas e regras que levam ao desenvolvimento de um interface de uma aplicação. Através do estudo dessas regras e estilos de interacção torna-se mais fácil a criação de um bom interface e ao longo desta tese será estudado e proposto uma ferramenta que ajude tanto na criação de Objectos de Aprendizagem como na concepção do respectivo interface.

Construção de interfaces em Flex para sistemas de experimentação remota

Os laboratórios de experimentação remota estão normalmente associados a tecnologias ou soluções proprietárias, as quais restringem a sua utilização a determinadas plataformas e obrigam ao uso de software específico no lado do cliente. O ISEP possui um laboratório de experimentação remota, baseado em instrumentação virtual, usado no apoio ao ensino da electrónica e construído sobre uma plataforma NIELVIS da National Instruments. O software de controlo da plataforma recorre à linguagem gráfica de programação LabVIEW. Esta é uma ferramenta desenvolvida pela National Instruments que facilita o desenvolvimento de aplicações de sistemas de experimentação remota, mas que possui várias limitações, nomeadamente a necessidade de instalação do lado do cliente de um plug-in, cuja disponibilidade se encontra limitada a determinadas versões de sistemas operativos e de Web Browsers. A experiência anterior demonstrou que estas questões limitam o número de clientes com possibilidade de acesso ao laboratório remoto, para além de, em alguns casos, se ter verificado não ser transparente a sua instalação e utilização. Neste contexto, o trabalho de investigação consistiu no desenvolvimento de uma solução que permite a geração de interfaces que possibilitam o controlo remoto do sistema implementado, e que, ao mesmo tempo, são independentes da plataforma usada pelo cliente.

Real-time fault injection using enhanced on-chip debug infrastructures

The rapid increase in the use of microprocessor-based systems in critical areas, where failures imply risks to human lives, to the environment or to expensive equipment, significantly increased the need for dependable systems, able to detect, tolerate and eventually correct faults. The verification and validation of such systems is frequently performed via fault injection, using various forms and techniques. However, as electronic devices get smaller and more complex, controllability and observability issues, and sometimes real time constraints, make it harder to apply most conventional fault injection techniques. This paper proposes a fault injection environment and a scalable methodology to assist the execution of real-time fault injection campaigns, providing enhanced performance and capabilities. Our proposed solutions are based on the use of common and customized on-chip debug (OCD) mechanisms, present in many modern electronic devices, with the main objective of enabling the insertion of faults in microprocessor memory elements with minimum delay and intrusiveness. Different configurations were implemented starting from basic Components Off-The-Shelf (COTS) microprocessors, equipped with real-time OCD infrastructures, to improved solutions based on modified interfaces, and dedicated OCD circuitry that enhance fault injection capabilities and performance. All methodologies and configurations were evaluated and compared concerning performance gain and silicon overhead.

Smart meters as a tool for energy efficiency

Gradually smart grids and smart meters are closer to the home consumers. Several countries has developed studies focused in the impacts arising from the introduction of these technologies and one of the main advantages are related to energy efficiency, observed through the awareness of the population on behalf of a more efficient consumption. These benefits are felt directly by consumers through the savings on electricity bills and also by the concessionaires through the minimization of losses in transmission and distribution, system stability, smaller loading during peak hours, among others. In this article two projects that demonstrate the potential energy savings through smart meters and smart grids are presented. The first performed in Korea, focusing on the installation of smart meters and the impact of use of user interfaces. The second performed in Portugal, focusing on the control of loads in a residence with distributed generation.

Multiple-choice tests: a tool in assessing knowledge

The purpose of this paper is to analyse if Multiple-Choice Tests may be considered an interesting alternative for assessing knowledge, particularly in the Mathematics area, as opposed to the traditional methods, such as open questions exams. In this sense we illustrate some opinions of the researchers in this area. Often the perception of the people about the construction of this kind of exams is that they are easy to create. But it is not true! Construct well written tests it’s a hard work and needs writing ability from the teachers. Our proposal is analyse the construction difficulties of multiple - choice tests as well some advantages and limitations of this type of tests. We also show the frequent critics and worries, since the beginning of this objective format usage. Finally in this context some examples of Multiple-Choice Items in the Mathematics area are given, and we illustrate as how we can take advantage and improve this kind of tests.

A simulation tool for demand response programs implementation

The design and development of simulation models and tools for Demand Response (DR) programs are becoming more and more important for adequately taking the maximum advantages of DR programs use. Moreover, a more active consumers’ participation in DR programs can help improving the system reliability and decrease or defer the required investments. DemSi, a DR simulator, designed and implemented by the authors of this paper, allows studying DR actions and schemes in distribution networks. It undertakes the technical validation of the solution using realistic network simulation based on PSCAD. DemSi considers the players involved in DR actions, and the results can be analyzed from each specific player point of view.

Adaptive tool for automatic data collection of real electricity markets

The study of electricity markets operation has been gaining an increasing importance in last years, as result of the new challenges that the electricity markets restructuring produced. This restructuring increased the competitiveness of the market, but with it its complexity. The growing complexity and unpredictability of the market’s evolution consequently increases the decision making difficulty. Therefore, the intervenient entities are forced to rethink their behaviour and market strategies. Currently, lots of information concerning electricity markets is available. These data, concerning innumerous regards of electricity markets operation, is accessible free of charge, and it is essential for understanding and suitably modelling electricity markets. This paper proposes a tool which is able to handle, store and dynamically update data. The development of the proposed tool is expected to be of great importance to improve the comprehension of electricity markets and the interactions among the involved entities.

Electric vehicle scenario simulator tool for smart grid operators

This paper presents a simulator for electric vehicles in the context of smart grids and distribution networks. It aims to support network operator´s planning and operations but can be used by other entities for related studies. The paper describes the parameters supported by the current version of the Electric Vehicle Scenario Simulator (EVeSSi) tool and its current algorithm. EVeSSi enables the definition of electric vehicles scenarios on distribution networks using a built-in movement engine. The scenarios created with EVeSSi can be used by external tools (e.g., power flow) for specific analysis, for instance grid impacts. Two scenarios are briefly presented for illustration of the simulator capabilities.

A short-term risk management tool applied to OMEL electricity market using particle swarm optimization

Short-term risk management is highly dependent on long-term contractual decisions previously established; risk aversion factor of the agent and short-term price forecast accuracy. Trying to give answers to that problem, this paper provides a different approach for short-term risk management on electricity markets. Based on long-term contractual decisions and making use of a price range forecast method developed by the authors, the short-term risk management tool presented here has as main concern to find the optimal spot market strategies that a producer should have for a specific day in function of his risk aversion factor, with the objective to maximize the profits and simultaneously to practice the hedge against price market volatility. Due to the complexity of the optimization problem, the authors make use of Particle Swarm Optimization (PSO) to find the optimal solution. Results from realistic data, namely from OMEL electricity market, are presented and discussed in detail.

A long-term swarm intelligence hedging tool applied to electricity markets

This paper proposes a swarm intelligence long-term hedging tool to support electricity producers in competitive electricity markets. This tool investigates the long-term hedging opportunities available to electric power producers through the use of contracts with physical (spot and forward) and financial (options) settlement. To find the optimal portfolio the producer risk preference is stated by a utility function (U) expressing the trade-off between the expectation and the variance of the return. Variance estimation and the expected return are based on a forecasted scenario interval determined by a long-term price range forecast model, developed by the authors, whose explanation is outside the scope of this paper. The proposed tool makes use of Particle Swarm Optimization (PSO) and its performance has been evaluated by comparing it with a Genetic Algorithm (GA) based approach. To validate the risk management tool a case study, using real price historical data for mainland Spanish market, is presented to demonstrate the effectiveness of the proposed methodology.

A long-term risk management tool for electricity markets using swarm intelligence

This paper addresses the optimal involvement in derivatives electricity markets of a power producer to hedge against the pool price volatility. To achieve this aim, a swarm intelligence meta-heuristic optimization technique for long-term risk management tool is proposed. This tool investigates the long-term opportunities for risk hedging available for electric power producers through the use of contracts with physical (spot and forward contracts) and financial (options contracts) settlement. The producer risk preference is formulated as a utility function (U) expressing the trade-off between the expectation and the variance of the return. Variance of return and the expectation are based on a forecasted scenario interval determined by a long-term price range forecasting model. This model also makes use of particle swarm optimization (PSO) to find the best parameters allow to achieve better forecasting results. On the other hand, the price estimation depends on load forecasting. This work also presents a regressive long-term load forecast model that make use of PSO to find the best parameters as well as in price estimation. The PSO technique performance has been evaluated by comparison with a Genetic Algorithm (GA) based approach. A case study is presented and the results are discussed taking into account the real price and load historical data from mainland Spanish electricity market demonstrating the effectiveness of the methodology handling this type of problems. Finally, conclusions are dully drawn.

PCMAT Metadata Authoring Tool

This paper introduces the PCMAT platform project and, in particular, one of its components, the PCMAT Metadata Authoring Tool. This is an educational web application that allows the project metadata creators to write the metadata associated to each learning object without any concern for the metadata schema semantics. Furthermore it permits the project managers to add or delete elements to the schema, without having to rewrite or compile any code.

SmartClean: an incremental data cleaning tool

This paper presents the SmartClean tool. The purpose of this tool is to detect and correct the data quality problems (DQPs). Compared with existing tools, SmartClean has the following main advantage: the user does not need to specify the execution sequence of the data cleaning operations. For that, an execution sequence was developed. The problems are manipulated (i.e., detected and corrected) following that sequence. The sequence also supports the incremental execution of the operations. In this paper, the underlying architecture of the tool is presented and its components are described in detail. The tool's validity and, consequently, of the architecture is demonstrated through the presentation of a case study. Although SmartClean has cleaning capabilities in all other levels, in this paper are only described those related with the attribute value level.

IGTAI - an Idea Generation Tool for Ambient Inteligence

Today, business group decision making is an extremely important activity. A considerable number of applications and research have been made in the past years in order to increase the effectiveness of decision making process. In order to support the idea generation process, IGTAI (Idea Generation Tool for Ambient Intelligence) prototype was created. IGTAI is a Group Decision Support System designed to support any kind of meetings namely distributed, asynchronous or face to face. It aims at helping geographically distributed (or not) people and organizations in the idea generation task, by making use of pervasive hardware in a meeting room, expanding the meeting beyond the room walls by allowing a ubiquitous access through different kinds of equipment. This paper focus on the research made to build IGTAI prototype, its architecture and its main functionalities, namely the support given in the different phases of the idea generation meeting.

Interfaces inovadores para a aprendizagem musical

Mestrado em Engenharia Informática