Real-time communications over wired/wireless PROFIBUS networks supporting inter-cell mobility

PROFIBUS is an international standard (IEC 61158, EN 50170) for factory-floor communications, with several thousands of installations worldwide. Taking into account the increasing need for mobile devices in industrial environments, one obvious solution is to extend traditional wired PROFIBUS networks with wireless capabilities. In this paper, we outline the major aspects of a hybrid wired/wireless PROFIBUS-based architecture, where most of the design options were made in order to guarantee the real-time behaviour of the overall network. We also introduce the timing unpredictability problems resulting from the co-existence of heterogeneous physical media in the same network. However, the major focus of this paper is on how to guarantee real-time communications in such a hybrid network, where nodes (and whole segments) can move between different radio cells (inter-cell mobility). Assuming a simple mobility management mechanism based on mobile nodes performing periodic radio channel assessment and switching, we propose a methodology to compute values for specific parameters that enable an optimal (minimum) and bounded duration of the handoff procedure.

Futures of work and skills: some foresight exercises in Europe and USA

The Knowledge-based society brought a new way of living and working. The increasing decline of work in primary sector and traditional industries, related with the significant increase of employment in the service sector and in the knowledge work, changed the way companies and individuals establish their relations, the way work and life is organised. These changes are usual and fast and so the feeling of insecurity and unpredictability become more and more sharp. In this context, foresight exercises are necessary tools helping in the identification of the key variables and main trends of evolution. This report will present some foresight studies about work and skills in Europe and USA, in order to contribute to think about possible evolutions and trends.

The daily and hourly energy consumption and load forecasting using artifitial neural network method: a case study using a set of 93 households in Portugal

It is important to understand and forecast a typical or a particularly household daily consumption in order to design and size suitable renewable energy systems and energy storage. In this research for Short Term Load Forecasting (STLF) it has been used Artificial Neural Networks (ANN) and, despite the consumption unpredictability, it has been shown the possibility to forecast the electricity consumption of a household with certainty. The ANNs are recognized to be a potential methodology for modeling hourly and daily energy consumption and load forecasting. Input variables such as apartment area, numbers of occupants, electrical appliance consumption and Boolean inputs as hourly meter system were considered. Furthermore, the investigation carried out aims to define an ANN architecture and a training algorithm in order to achieve a robust model to be used in forecasting energy consumption in a typical household. It was observed that a feed-forward ANN and the Levenberg-Marquardt algorithm provided a good performance. For this research it was used a database with consumption records, logged in 93 real households, in Lisbon, Portugal, between February 2000 and July 2001, including both weekdays and weekend. The results show that the ANN approach provides a reliable model for forecasting household electric energy consumption and load profile. © 2014 The Author.

Análise e gestão de risco de actividades em outsourcing : estudo de caso

Mestrado em Auditoria

Run-time defragmentation for dynamically reconfigurable hardware

Reconfigurable computing experienced a considerable expansion in the last few years, due in part to the fast run-time partial reconfiguration features offered by recent SRAM-based Field Programmable Gate Arrays (FPGAs), which allowed the implementation in real-time of dynamic resource allocation strategies, with multiple independent functions from different applications sharing the same logic resources in the space and temporal domains. However, when the sequence of reconfigurations to be performed is not predictable, the efficient management of the logic space available becomes the greatest challenge posed to these systems. Resource allocation decisions have to be made concurrently with system operation, taking into account function priorities and optimizing the space currently available. As a consequence of the unpredictability of this allocation procedure, the logic space becomes fragmented, with many small areas of free resources failing to satisfy most requests and so remaining unused. A rearrangement of the currently running functions is therefore necessary, so as to obtain enough contiguous space to implement incoming functions, avoiding the spreading of their components and the resulting degradation of system performance. A novel active relocation procedure for Configurable Logic Blocks (CLBs) is herein presented, able to carry out online rearrangements, defragmenting the available FPGA resources without disturbing functions currently running.

Desenvolvimento de apoio à decisão operacional – previsão de curto prazo de geração distribuída de tecnologia eólica ligada à RND

No contexto da penetração de energias renováveis no sistema elétrico, Portugal ocupa uma posição de destaque a nível mundial, muito devido à produção de eólica. Com um sistema elétrico com forte presença de fontes de energia renováveis, novos desafios surgem, nomeadamente no caso da energia eólica pela sua imprevisibilidade e volatilidade. O recurso eólico embora seja ilimitado não é armazenável, surgindo assim a necessidade da procura de modelos de previsão de produção de energia elétrica dos parques eólicos de modo a permitir uma boa gestão do sistema. Nesta dissertação apresentam-se as contribuições resultantes de um trabalho de pesquisa e investigação sobre modelos de previsão da potência elétrica com base em valores de previsões meteorológicas, nomeadamente, valores previstos da intensidade e direção do vento. Consideraram-se dois tipos de modelos: paramétricos e não paramétricos. Os primeiros são funções polinomiais de vários graus e a função sigmoide, os segundos são redes neuronais artificiais. Para a estimação dos modelos e respetiva validação, são usados dados recolhidos ao longo de dois anos e três meses no parque eólico do Pico Alto de potência instalada de 6 MW. De forma a otimizar os resultados da previsão, consideram-se diferentes classes de perfis de produção, definidas com base em quatro e oito direções do vento, e ajustam-se os modelos propostos em cada uma das classes. São apresentados e discutidos resultados de uma análise comparativa do desempenho dos diferentes modelos propostos para a previsão da potência.

Demonstration of the Multi-Agent Simulator of Competitive Electricity Markets

Electricity markets are complex environments with very particular characteristics. A critical issue concerns the constant changes they are subject to. This is a result of the electricity markets’ restructuring, performed so that the competitiveness could be increased, but with exponential implications in the increase of the complexity and unpredictability in those markets’ scope. The constant growth in markets unpredictability resulted in an amplified need for market intervenient entities in foreseeing market behavior. The need for understanding the market mechanisms and how the involved players’ interaction affects the outcomes of the markets, contributed to the growth of usage of simulation tools. Multi-agent based software is particularly well fitted to analyze dynamic and adaptive systems with complex interactions among its constituents, such as electricity markets. This paper presents the Multi-Agent System for Competitive Electricity Markets (MASCEM) – a simulator based on multi-agent technology that provides a realistic platform to simulate electricity markets, the numerous negotiation opportunities and the participating entities.

Real-Time Application Mapping for Many-Cores Using a Limited Migrative Model

Many-core platforms are an emerging technology in the real-time embedded domain. These devices offer various options for power savings, cost reductions and contribute to the overall system flexibility, however, issues such as unpredictability, scalability and analysis pessimism are serious challenges to their integration into the aforementioned area. The focus of this work is on many-core platforms using a limited migrative model (LMM). LMM is an approach based on the fundamental concepts of the multi-kernel paradigm, which is a promising step towards scalable and predictable many-cores. In this work, we formulate the problem of real-time application mapping on a many-core platform using LMM, and propose a three-stage method to solve it. An extended version of the existing analysis is used to assure that derived mappings (i) guarantee the fulfilment of timing constraints posed on worst-case communication delays of individual applications, and (ii) provide an environment to perform load balancing for e.g. energy/thermal management, fault tolerance and/or performance reasons.

Towards the Certification of Multicore Platforms in the Avionics Domain

Poster presented in Work in Progress Session, The 28th GI/ITG International Conference on Architecture of Computing Systems (ARCS 2015). 24 to 27, Mar, 2015. Porto, Portugal.

Towards the Certification of Multicore Platforms in the Avionics Domain

Presented at Work in Progress Session, The 28th GI/ITG International Conference on Architecture of Computing Systems (ARCS 2015). 24 to 27, Mar, 2015. Porto, Portugal.

Type-based protocol conformance and aliasing control in concurrent java programs

Dissertação para obtenção do Grau de Mestre em Engenharia Informática

Ontologies for the interoperability of multiagent electricity markets simulation platforms

Electricity markets worldwide are complex and dynamic environments with very particular characteristics. These are the result of electricity markets’ restructuring and evolution into regional and continental scales, along with the constant changes brought by the increasing necessity for an adequate integration of renewable energy sources. The rising complexity and unpredictability in electricity markets has increased the need for the intervenient entities in foreseeing market behaviour. Market players and regulators are very interested in predicting the market’s behaviour. Market players need to understand the market behaviour and operation in order to maximize their profits, while market regulators need to test new rules and detect market inefficiencies before they are implemented. The growth of usage of simulation tools was driven by the need for understanding those mechanisms and how the involved players' interactions affect the markets' outcomes. Multi-agent based software is particularly well fitted to analyse dynamic and adaptive systems with complex interactions among its constituents, such as electricity markets. Several modelling tools directed to the study of restructured wholesale electricity markets have emerged. Still, they have a common limitation: the lack of interoperability between the various systems to allow the exchange of information and knowledge, to test different market models and to allow market players from different systems to interact in common market environments. This dissertation proposes the development and implementation of ontologies for semantic interoperability between multi-agent simulation platforms in the scope of electricity markets. The added value provided to these platforms is given by enabling them sharing their knowledge and market models with other agent societies, which provides the means for an actual improvement in current electricity markets studies and development. The proposed ontologies are implemented in MASCEM (Multi-Agent Simulator of Competitive Electricity Markets) and tested through the interaction between MASCEM agents and agents from other multi-agent based simulators. The implementation of the proposed ontologies has also required a complete restructuring of MASCEM’s architecture and multi-agent model, which is also presented in this dissertation. The results achieved in the case studies allow identifying the advantages of the novel architecture of MASCEM, and most importantly, the added value of using the proposed ontologies. They facilitate the integration of independent multi-agent simulators, by providing a way for communications to be understood by heterogeneous agents from the various systems.

Risk of employing an evolvable production system

Nowadays manufacturing companies are facing a more challenging environment due to the unpredictability of the markets in order to survive. Enterprises need to keep innovating and deliver products with new internal or external characteristics. There are strategies and solutions, to different organisational level from strategic to operational, when technology is growing faster in operational level, more specifically in manufacturing system. This means that companies have to deal with the changes of the emergent manufacturing systems while it can be expensive and not easy to be implement. An agile manufacturing system can help to cope with the markets changeability. Evolvable Production Systems (EPS) is an emergent paradigm which aims to bring new solutions to deal with changeability. The proposed paradigm is characterised by modularity and intends to introduce high flexibility and dynamism at shop floor level through the use of the evolution of new computational devices and technology. This new approach brings to enterprises the ability to plug and unplug new devices and allowing fast reformulation of the production line without reprogramming. There is no doubt about the advantages and benefits of this emerging technology but the feasibility and applicability is still under questioned. Most researches in this area are focused on technical side, explaining the advantages of those systems while there are no sufficient works discussing the implementation risks from different perspective, including business owner. The main objective of this work is to propose a methodology and model to identify, classify and measure potential risk associated with an implementation of this emergent paradigm. To quantify the proposed comprehensive risk model, an Intelligent Decision system is developed employing Fuzzy Inference System to deal with the knowledge of experts, as there are no historical data and sufficient research on this area. The result can be the vulnerability assessment of implementing EPS technology in manufacturing companies when the focus is more on SMEs. The present dissertation used the experts’ knowledge and experiences, who were involved in FP7 project IDEAS, which is one of the leading projects in this area.

Os sentidos da educação religiosa na construção do eu contemporâneo: espiritualidades juvenis

Dissertação de mestrado em Ciências da Educação (área de especialização em Sociologia da Educação e Políticas Educativas)

Moody choice

If choices depend on the decision maker's mood, is the attempt to derive any consistency in choice doomed? In this paper we argue that, even with full unpredictability of mood, the way choices from a menu relate to choices from another menu exhibits some structure. We present two alternative models of 'moody choice' and show that, in either of them, not all choice patterns are possible. Indeed, we characterise both models in terms of consistency requirements of the observed choice data.