Collision-free prioritized medium access control in wireless networks with hidden nodes

We propose a collision-free medium access control (MAC) protocol, which implements static-priority scheduling and works in the presence of hidden nodes. The MAC protocol allows multiple masters and is fully distributed; it is an adaptation to a wireless channel of the dominance protocol used in the CAN bus. But unlike that protocol, our protocol does not require a node having the ability to sense the channel while transmitting to the channel. Our protocol is collision-free even in the presence of hidden nodes and it achieves this without synchronized clocks or out-of-band busy tones. In addition, the protocol is designed to ensure that many non-interfering nodes can transmit in parallel and it functions for both broadcast and unicast transmissions.

Effect of the exposure to maternal smoking during pregnancy and childhood on the body mass index until adolescence

OBJECTIVE Investigate the effect of exposure to smoking during pregnancy and early childhood on changes in the body mass index (BMI) from birth to adolescence.METHODS A population-based cohort of children (0-5 years old) from Cuiabá, Midwest Brazil, was assessed in 1999-2000 (n = 2,405). Between 2009 and 2011, the cohort was re-evaluated. Information about birth weight was obtained from medical records, and exposure to smoking during pregnancy and childhood was assessed at the first interview. Linear mixed effects models were used to estimate the association between exposure to maternal smoking during pregnancy and preschool age, and the body mass index of children at birth, childhood and adolescence.RESULTS Only 11.3% of the mothers reported smoking during pregnancy, but most of them (78.2%) also smoked during early childhood. Among mothers who smoked only during pregnancy (n = 59), 97.7% had smoked only in the first trimester. The changes in body mass index at birth and in childhood were similar for children exposed and those not exposed to maternal smoking. However, from childhood to adolescence the rate of change in the body mass index was higher among those exposed only during pregnancy than among those who were not exposed.CONCLUSIONS Exposure to smoking only during pregnancy, especially in the first trimester, seems to affect changes in the body mass index until adolescence, supporting guidelines that recommend women of childbearing age to stop smoking.

Type System for the ComponentJ Programming Language

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para a obtenção do grau de Mestre em Engenharia Informática.

A smart layer for remote laboratories

Commonly, when a weblab is developed to support remote experiments in sciences and engineering courses, a particular hardware/software architecture is implemented. However, the existence of several technological solutions to implement those architectures difficults the emergence of a standard, both at hardware and software levels. While particular solutions are adopted assuming that only qualified people may implement a weblab, the control of the physical space and the power consumption are often forgotten. Since controlling these two previous aspects may increase the quality of the weblab hosting the remote experiments, this paper proposes the useof a new layer implemented by a domotic system bus with several devices (e.g. lights, power sockets, temperature sensors, and others) able to be controlled through the Internet. We also provide a brief proof-of-concept in the form of a weblab equipped with a simple domotic system usually implemented in smart houses. The added value to the remote experiment hosted at the weblab is also identified in terms of power savings and environment conditions.

Byzantium: Contribuições para o desenvolvimento de um sistema de replicação de bases de dados tolerante a falhas bizantinas

Trabalho apresentado no âmbito do Mestrado em Engenharia Informática, como requisito parcial para obtenção do grau de Mestre em Engenharia Informática

Maximização da valorização energética em aterros sanitários recorrendo a equipamentos baseados no Ciclo Orgânico de Rankine (ORC)

Atualmente, os aterros sanitários representam uma solução para a gestão e tratamento dos resíduos sólidos urbanos. Da deposição, ocorrem duas formas de emissões ao longo do tempo, a produção de biogás e de lixiviados, que resultam sobretudo da decomposição da matéria orgânica. Um dos principais constituintes do biogás é o metano, o qual tem elevado poder calorífico. O presente trabalho aborda, a maximização da valorização energética em aterros sanitários, recorrendo a equipamentos baseados no Ciclo Orgânico de Rankine (ORC) para a produção de eletricidade. É apresentado como caso de estudo a central de valorização energética da Suldouro, em Sermonde, que produz eletricidade a partir do biogás resultante da decomposição da matéria orgânica depositada em aterro. O biogás é utilizado como combustível para os motogeradores utilizados para o seu aproveitamento energético, sendo que apenas cerca de 40% do potencial energético contido no biogás é transformado em eletricidade, registando-se perdas sobretudo nas emissões dos gases de exaustão e na água de arrefecimento dos motores. Para avaliação do potencial da recuperação energética dos gases de escape é avaliado o desempenho termodinâmico do ciclo ORC. Para tal foi desenvolvida uma ferramenta em MATLAB utilizando como modelo a configuração do ORC com recuperador de calor. O cálculo das propriedades termodinâmicas dos fluidos foi obtido através da criação de uma sub-rotina que chama o programa CoolProp. Este programa restitui propriedades como a entalpia, entropia, pressões e temperaturas em cada ponto do ciclo, permitindo assim ao utilizador otimizar o tempo na obtenção de resultados. A avaliação económica é fundamental na tomada de decisões por parte do investidor e dos financiadores do projeto. É então apresentada a análise económica e efetuada uma análise de sensibilidade, onde foram efetuadas variações nos vetores mais importantes de forma a poder avaliar-se o impacto em termos da sua rentabilidade. A ferramenta desenvolvida permite obter de forma prática, os três indicadores económicos extremamente influentes no que se refere à tomada de decisão. A utilização dos sistemas ORC e os seus benefícios não se esgotam na maximização dos aproveitamentos da valorização energética em aterros sanitários. Também a recuperação de calor para a produção de energia elétrica pode ter um impacto importante em muitos setores intensivos de energia, contribuindo significativamente para a redução do consumo e aumentando a eficiência de todo o processo de produção.

Rede de mobilidade sustentável de Beja: viabilidade de implementação de um sistema de bicicletas elétricas

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Civil

"Lazarillo de Tormes": melhoria da mobilidade em Salamanca

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Civil na Área de Especialização de Vias de Comunicação e Transportes

The impact of driving styles on fuel consumption: a data-warehouse-and-data-mining-based discovery process

This paper discusses the results of applied research on the eco-driving domain based on a huge data set produced from a fleet of Lisbon's public transportation buses for a three-year period. This data set is based on events automatically extracted from the control area network bus and enriched with GPS coordinates, weather conditions, and road information. We apply online analytical processing (OLAP) and knowledge discovery (KD) techniques to deal with the high volume of this data set and to determine the major factors that influence the average fuel consumption, and then classify the drivers involved according to their driving efficiency. Consequently, we identify the most appropriate driving practices and styles. Our findings show that introducing simple practices, such as optimal clutch, engine rotation, and engine running in idle, can reduce fuel consumption on average from 3 to 5l/100 km, meaning a saving of 30 l per bus on one day. These findings have been strongly considered in the drivers' training sessions.

Day-ahead Resource Scheduling Including Demand Response for Electric Vehicles

The energy resource scheduling is becoming increasingly important, as the use of distributed resources is intensified and massive gridable vehicle (V2G) use is envisaged. This paper presents a methodology for day-ahead energy resource scheduling for smart grids considering the intensive use of distributed generation and V2G. The main focus is the comparison of different EV management approaches in the day-ahead energy resources management, namely uncontrolled charging, smart charging, V2G and Demand Response (DR) programs i n the V2G approach. Three different DR programs are designed and tested (trip reduce, shifting reduce and reduce+shifting). Othe r important contribution of the paper is the comparison between deterministic and computational intelligence techniques to reduce the execution time. The proposed scheduling is solved with a modified particle swarm optimization. Mixed integer non-linear programming is also used for comparison purposes. Full ac power flow calculation is included to allow taking into account the network constraints. A case study with a 33-bus distribution network and 2000 V2G resources is used to illustrate the performance of the proposed method.

Modified Particle Swarm Optimization Applied to Integrated Demand Response and DG Resources Scheduling

The elastic behavior of the demand consumption jointly used with other available resources such as distributed generation (DG) can play a crucial role for the success of smart grids. The intensive use of Distributed Energy Resources (DER) and the technical and contractual constraints result in large-scale non linear optimization problems that require computational intelligence methods to be solved. This paper proposes a Particle Swarm Optimization (PSO) based methodology to support the minimization of the operation costs of a virtual power player that manages the resources in a distribution network and the network itself. Resources include the DER available in the considered time period and the energy that can be bought from external energy suppliers. Network constraints are considered. The proposed approach uses Gaussian mutation of the strategic parameters and contextual self-parameterization of the maximum and minimum particle velocities. The case study considers a real 937 bus distribution network, with 20310 consumers and 548 distributed generators. The obtained solutions are compared with a deterministic approach and with PSO without mutation and Evolutionary PSO, both using self-parameterization.

Distributed Generation and Demand Response Dispatch for a Virtual Power Player Energy and Reserve Provision

Recent changes in the operation and planning of power systems have been motivated by the introduction of Distributed Generation (DG) and Demand Response (DR) in the competitive electricity markets' environment, with deep concerns at the efficiency level. In this context, grid operators, market operators, utilities and consumers must adopt strategies and methods to take full advantage of demand response and distributed generation. This requires that all the involved players consider all the market opportunities, as the case of energy and reserve components of electricity markets. The present paper proposes a methodology which considers the joint dispatch of demand response and distributed generation in the context of a distribution network operated by a virtual power player. The resources' participation can be performed in both energy and reserve contexts. This methodology contemplates the probability of actually using the reserve and the distribution network constraints. Its application is illustrated in this paper using a 32-bus distribution network with 66 DG units and 218 consumers classified into 6 types of consumers.

Evaluation of the Electric Vehicle Impact in the Power Demand Curve in a Smart Grid Environment

Smart grids with an intensive penetration of distributed energy resources will play an important role in future power system scenarios. The intermittent nature of renewable energy sources brings new challenges, requiring an efficient management of those sources. Additional storage resources can be beneficially used to address this problem; the massive use of electric vehicles, particularly of vehicle-to-grid (usually referred as gridable vehicles or V2G), becomes a very relevant issue. This paper addresses the impact of Electric Vehicles (EVs) in system operation costs and in power demand curve for a distribution network with large penetration of Distributed Generation (DG) units. An efficient management methodology for EVs charging and discharging is proposed, considering a multi-objective optimization problem. The main goals of the proposed methodology are: to minimize the system operation costs and to minimize the difference between the minimum and maximum system demand (leveling the power demand curve). The proposed methodology perform the day-ahead scheduling of distributed energy resources in a distribution network with high penetration of DG and a large number of electric vehicles. It is used a 32-bus distribution network in the case study section considering different scenarios of EVs penetration to analyze their impact in the network and in the other energy resources management.

Retificador monofásico com fator de potência quase unitário

Dissertação para a obtenção do grau de Mestre em Engenharia Eletrotécnica Ramo de Automação e Eletrónica Industrial

Inferência de percursos dos utentes de um transporte coletivo

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia de Redes de Comunicações e Multimédia