Biblioteca de navegação autónoma baseada em campos de potencial

Trabalho de Final de Mestrado para obtenção do grau de Mestre em Engenharia Informática e de Computadores

A articulação da linguagem na educação pré-escolar

Relatório da Prática Profissional Supervisionada Mestrado em Educação Pré-Escolar

Multi-agent management system for electric vehicle charging

This paper proposes an implementation, based on a multi-agent system, of a management system for automated negotiation of electricity allocation for charging electric vehicles (EVs) and simulates its performance. The widespread existence of charging infrastructures capable of autonomous operation is recognised as a major driver towards the mass adoption of EVs by mobility consumers. Eventually, conflicting requirements from both power grid and EV owners require automated middleman aggregator agents to intermediate all operations, for example, bidding and negotiation, between these parts. Multi-agent systems are designed to provide distributed, modular, coordinated and collaborative management systems; therefore, they seem suitable to address the management of such complex charging infrastructures. Our solution consists in the implementation of virtual agents to be integrated into the management software of a charging infrastructure. We start by modelling the multi-agent architecture using a federated, hierarchical layers setup and as well as the agents' behaviours and interactions. Each of these layers comprises several components, for example, data bases, decision-making and auction mechanisms. The implementation of multi-agent platform and auctions rules, and of models for battery dynamics, is also addressed. Four scenarios were predefined to assess the management system performance under real usage conditions, considering different types of profiles for EVs owners', different infrastructure configurations and usage and different loads on the utility grid (where real data from the concession holder of the Portuguese electricity transmission grid is used). Simulations carried with the four scenarios validate the performance of the modelled system while complying with all the requirements. Although all of these have been performed for one charging station alone, a multi-agent design may in the future be used for the higher level problem of distributing energy among charging stations. Copyright (c) 2014 John Wiley & Sons, Ltd.

A inspecção da educação na República Democrática de São Tomé e Príncipe: concepções, dinâmicas e estruturas organizacionais

Dissertação apresentada à Escola Superior de Educação de Lisboa para Obtenção de Grau de Mestre em Ciências da Educação - Especialização em Supervisão da Educação

On the Problem of Balancing the DC Capacitor Voltage Divider in Back-to-Back Multilevel Converters

This paper presents a new generalized solution for DC bus capacitors voltage balancing in back-to-back m level diode-clamped multilevel converters connecting AC networks. The solution is based on the DC bus average power flow and exploits the switching configuration redundancies. The proposed balancing solution is particularized for the back-to-back multilevel structure with m=5 levels. This back-to-back converter is studied working with bidirectional power flow, connecting an induction machine to the power grid.

Agent Inferencing Meets the Semantic Web

We provide all agent; the capability to infer the relations (assertions) entailed by the rules that, describe the formal semantics of art RDFS knowledge-base. The proposed inferencing process formulates each semantic restriction as a rule implemented within a, SPARQL query statement. The process expands the original RDF graph into a fuller graph that. explicitly captures the rule's described semantics. The approach is currently being explored in order to support descriptions that follow the generic Semantic Web Rule Language. An experiment, using the Fire-Brigade domain, a small-scale knowledge-base, is adopted to illustrate the agent modeling method and the inferencing process.

Formaldehyde in indoor air: a public health problem?

Formaldehyde was the first air pollutant, which already in the 1970s emerged as a specifically non-industrial indoor air quality problem. Yet formaldehyde remained an indoor air quality issue and the formaldehyde level in residential indoor air is among the highest of any indoor air contaminant. Formaldehyde concentrations in 4 different indoor settings (schools, office buildings, new dwellings and occupied dwellings) in Portugal were measured using Photo Ionization Detection (PID) equipment (11,7 eV lamps). All the settings presented results higher than the reference value proposed by Portuguese legislation. Furthermore, occupied dwellings showed 3 units with results above the reference. We could conclude that formaldehyde presence is a reality in monitored indoor settings. Concentration levels are higher than the Portuguese reference value for indoor settings and these can indicate health problems for occupants.

Dynamic equilibrium through reinforcement learning

Reinforcement Learning is an area of Machine Learning that deals with how an agent should take actions in an environment such as to maximize the notion of accumulated reward. This type of learning is inspired by the way humans learn and has led to the creation of various algorithms for reinforcement learning. These algorithms focus on the way in which an agent’s behaviour can be improved, assuming independence as to their surroundings. The current work studies the application of reinforcement learning methods to solve the inverted pendulum problem. The importance of the variability of the environment (factors that are external to the agent) on the execution of reinforcement learning agents is studied by using a model that seeks to obtain equilibrium (stability) through dynamism – a Cart-Pole system or inverted pendulum. We sought to improve the behaviour of the autonomous agents by changing the information passed to them, while maintaining the agent’s internal parameters constant (learning rate, discount factors, decay rate, etc.), instead of the classical approach of tuning the agent’s internal parameters. The influence of changes on the state set and the action set on an agent’s capability to solve the Cart-pole problem was studied. We have studied typical behaviour of reinforcement learning agents applied to the classic BOXES model and a new form of characterizing the environment was proposed using the notion of convergence towards a reference value. We demonstrate the gain in performance of this new method applied to a Q-Learning agent.

O cálculo mental na resolução de problemas : um estudo no 1.º ano de escolaridade

Este estudo tem como principal objectivo compreender de que modo os alunos de 1.º ano de escolaridade desenvolvem estratégias de cálculo mental, num contexto de resolução de problemas de adição e subtracção. Para tal, procurou responder-se a três questões: a) Que estratégias de cálculo mental são utilizadas pelos alunos na resolução de problemas de adição e subtracção?; b) De que modo evoluem essas estratégias?; e c) Será que o significado da operação de adição ou subtracção, presente no problema, influencia a estratégia de cálculo mental utilizada na sua resolução? Tendo em conta a problemática do estudo, seguiu-se uma metodologia de natureza qualitativa, tendo sido realizados três estudos de caso. O trabalho de campo deste estudo foi realizado numa turma do 1.º ano do 1.º ciclo do ensino básico, da qual sou professora, tendo sido concluído no início do ano lectivo seguinte, quando os alunos frequentavam o 2.º ano de escolaridade. Os alunos em estudo resolveram três cadeias de problemas, contemplando os diferentes significados das operações de adição e subtracção: as primeiras duas cadeias foram resolvidas a pares, na sala de aula, e a última foi resolvida individualmente, apenas pelos alunos que constituíram os casos e fora da sala de aula. Os registos realizados pelos alunos aquando da resolução dos problemas, juntamente com as gravações áudio, vídeo e as notas de campo, constituíram-se como as principais fontes de recolha de dados. Os dados permitem afirmar que as estratégias de cálculo usadas pelos alunos evoluíram de estratégias elementares baseadas em contagem e na utilização de factos numéricos, para estratégias de cálculo mental complexas, aditivas ou subtractivas das categorias 1010 e N10. Foi possível identificar uma preferência por estratégias aditivas do tipo 1010 na resolução dos problemas de adição e, na resolução dos problemas de subtracção, as estratégias utilizadas pelos alunos variaram com o significado presente em cada problema: foram usadas estratégias subtractivas do tipo 1010 em problemas com o significado de retirar e, na resolução dos problemas com os significados de comparar e completar, de um modo geral, os alunos utilizaram estratégias aditivas do tipo A10, pertencente à categoria N10. Os dados apontam também para uma possível influência do ambiente de aprendizagem na utilização de estratégias de cálculo mental mais eficientes, particularmente a nível da estratégia aditiva do tipo 1010. Os dados permitem ainda concluir que alunos do 1.º ano são capazes de desenvolver e utilizar estratégias de cálculo mental, referidas na literatura a que tive acesso (por exemplo, Beishuizen, 1993; 2001; Buys, 2001; Cooper, Heirdsfield & Irons, 1995; Thompson & Smith, 1999), associadas a alunos mais velhos. Deste modo, os resultados deste estudo salientam a necessidade de, em ambientes de aprendizagem enriquecedores, o professor promover o desenvolvimento de estratégias complexas de cálculo mental, evoluindo para além das estratégias de cálculo elementares, habitualmente associadas aos alunos mais novos.

Estratégias para negociação de contratos bilaterais em mercados multi-agente de energia eléctrica

A energia eléctrica é um bem essencial para a maioria das sociedades. O seu fornecimento tem sido encarado como um serviço público, da responsabilidade dos governos, através de empresas monopolistas, públicas e privadas. O Mercado Ibérico de Electricidade (MIBEL) surge com o objectivo da integração e cooperação do sector eléctrico Português e Espanhol, no qual é possível negociar preços e volumes de energia. Actualmente, as entidades podem negociar através de um mercado bolsista ou num mercado de contratos bilaterais. Uma análise dos mercados de electricidade existentes mostra que estes estão longe de estarem liberalizados. As tarifas não reflectem o efeito da competitividade. Além disso, o recurso a contratos bilaterais limita frequentemente os clientes a um único fornecedor de energia eléctrica. Nos últimos anos, têm surgido uma série de ferramentas computacionais que permitem simular, parte ou a totalidade, dos mercados de electricidade. Contudo, apesar das suas potencialidades, muitos simuladores carecem de flexibilidade e generalidade. Nesta perspectiva, esta dissertação tem como principal objectivo o desenvolvimento de um simulador de mercados de energia eléctrica que possibilite lidar com as dificuldades inerentes a este novo modelo de mercado, recorrendo a agentes computacionais autónomos. A dissertação descreve o desenho e a implementação de um simulador simplificado para negociação de contratos bilaterais em mercados de energia, com particular incidência para o desenho das estratégias a utilizar pelas partes negociais. Além disso, efectua-se a descrição de um caso prático, com dados do MIBEL. Descrevem-se também várias simulações computacionais, envolvendo retalhistas e consumidores de energia eléctrica, que utilizam diferentes estratégias negociais. Efectua-se a análise detalhada dos resultados obtidos. De forma sucinta, os resultados permitem concluir que as melhores estratégias para cada entidade, no caso prático estudado, são: a estratégia de concessões fixas, para o retalhista, e a estratégia de concessões baseada no volume de energia, para o consumidor.

A hybrid approach to multi-agent decision-making

In the aftermath of a large-scale disaster, agents' decisions derive from self-interested (e.g. survival), common-good (e.g. victims' rescue) and teamwork (e.g. fire extinction) motivations. However, current decision-theoretic models are either purely individual or purely collective and find it difficult to deal with motivational attitudes; on the other hand, mental-state based models find it difficult to deal with uncertainty. We propose a hybrid, CvI-JI, approach that combines: i) collective 'versus' individual (CvI) decisions, founded on the Markov decision process (MDP) quantitative evaluation of joint-actions, and ii)joint-intentions (JI) formulation of teamwork, founded on the belief-desire-intention (BDI) architecture of general mental-state based reasoning. The CvI-JI evaluation explores the performance's improvement

RFID together with multi-agent systems to control global value chains

Nowadays, the cooperative intelligent transport systems are part of a largest system. Transportations are modal operations integrated in logistics and, logistics is the main process of the supply chain management. The supply chain strategic management as a simultaneous local and global value chain is a collaborative/cooperative organization of stakeholders, many times in co-opetition, to perform a service to the customers respecting the time, place, price and quality levels. The transportation, like other logistics operations must add value, which is achieved in this case through compression lead times and order fulfillments. The complex supplier's network and the distribution channels must be efficient and the integral visibility (monitoring and tracing) of supply chain is a significant source of competitive advantage. Nowadays, the competition is not discussed between companies but among supply chains. This paper aims to evidence the current and emerging manufacturing and logistics system challenges as a new field of opportunities for the automation and control systems research community. Furthermore, the paper forecasts the use of radio frequency identification (RFID) technologies integrated into an information and communication technologies (ICT) framework based on distributed artificial intelligence (DAI) supported by a multi-agent system (MAS), as the most value advantage of supply chain management (SCM) in a cooperative intelligent logistics systems. Logistical platforms (production or distribution) as nodes of added value of supplying and distribution networks are proposed as critical points of the visibility of the inventory, where these technological needs are more evident.

The problem of estimating the volatility of zero coupon bond interest rate

Financial literature and financial industry use often zero coupon yield curves as input for testing hypotheses, pricing assets or managing risk. They assume this provided data as accurate. We analyse implications of the methodology and of the sample selection criteria used to estimate the zero coupon bond yield term structure on the resulting volatility of spot rates with different maturities. We obtain the volatility term structure using historical volatilities and Egarch volatilities. As input for these volatilities we consider our own spot rates estimation from GovPX bond data and three popular interest rates data sets: from the Federal Reserve Board, from the US Department of the Treasury (H15), and from Bloomberg. We find strong evidence that the resulting zero coupon bond yield volatility estimates as well as the correlation coefficients among spot and forward rates depend significantly on the data set. We observe relevant differences in economic terms when volatilities are used to price derivatives.

Epidemiology of malaria, schistosomiasis, geohelminths, anemia and malnutrition in the context of a demographic surveillance system in Northern Angola

Background: Malaria, schistosomiasis and geohelminth infection are linked to maternal and child morbidity and mortality in sub-Saharan Africa. Knowing the prevalence levels of these infections is vital to guide governments towards the implementation of successful and cost-effective disease control initiatives. Methodology/Principal Findings: A cross-sectional study of 1,237 preschool children (0–5 year olds), 1,142 school-aged children (6–15 year olds) and 960 women (.15 year olds) was conducted to understand the distribution of malnutrition, anemia, malaria, schistosomiasis (intestinal and urinary) and geohelminths in a north-western province of Angola. We used a recent demographic surveillance system (DSS) database to select and recruit suitable households. Malnutrition was common among children (23.3% under-weight, 9.9% wasting and 32.2% stunting), and anemia was found to be a severe public health problem (i.e., .40%). Malaria prevalence was highest among preschool children reaching 20.2%. Microhematuria prevalence levels reached 10.0% of preschool children, 16.6% of school-aged children and 21.7% of mothers. Geohelminth infections were common, affecting 22.3% of preschool children, 31.6% of school-aged children and 28.0% of mothers. Conclusions: Here we report prevalence levels of malaria, schistosomiasis and geohelminths; all endemic in this poorly described area where a DSS has been recently established. Furthermore we found evidence that the studied infections are associated with the observed levels of anemia and malnutrition, which can justify the implementation of integrated interventions for the control of these diseases and morbidities.

Fungal contamination of poultries litter: a public health problem

Exposure to certain fungi can cause human illness. Fungi cause adverse human health effects through three specific mechanisms: generation of a harmful immune response (e.g., allergy or hypersensitivity pneumonitis); direct infection by the fungal organism; by toxic-irritant effects from mold byproducts, such as mycotoxins. In Portugal there is an increasingly industry of large facilities that produce whole chickens for domestic consumption and only few investigations have reported on fungal contamination of the poultry litter. The material used for poultry litter is varied but normally can be constitute by: pine shavings; sawdust of eucalyptus; other types of wood; peanut; coffee; sugar cane; straw; hay; grass; paper processed. Litter is one of the most contributive factors to fungal contamination in poultries. Spreading litter is one of the tasks that normally involve higher exposure of the poultry workers to dust, fungi and their metabolites, such as VOC’s and mycotoxins. After being used and removed from poultries, litter is ploughed into agricultural soils, being this practice potentially dangerous for the soil environment, as well for both humans and animals. The goal of this study was to characterize litter’s fungal contamination and also to report the incidence of keratinophilic and toxigenic fungi.