Fatores influenciadores da gestão da qualidade e independência do auditor: um estudo de caso

Dissertação apresentada ao Instituto Superior de Contabilidade para obtenção do Grau de Mestre em Auditoria Orientada por: Doutora Alcina Dias

Adaptive learning in multiagent systems: a forecasting methodology based on error analysis

Electricity markets are complex environments, involving a large number of different entities, playing in a dynamic scene to obtain the best advantages and profits. MASCEM is a multi-agent electricity market simu-lator to model market players and simulate their operation in the market. Market players are entities with specific characteristics and objectives, making their decisions and interacting with other players. MASCEM pro-vides several dynamic strategies for agents’ behaviour. This paper presents a method that aims to provide market players strategic bidding capabilities, allowing them to obtain the higher possible gains out of the market. This method uses an auxiliary forecasting tool, e.g. an Artificial Neural Net-work, to predict the electricity market prices, and analyses its forecasting error patterns. Through the recognition of such patterns occurrence, the method predicts the expected error for the next forecast, and uses it to adapt the actual forecast. The goal is to approximate the forecast to the real value, reducing the forecasting error.

Os padrões de vinculação estabelecidos e indicadores de resilência (autonomia e capacidades de interação social) em crianças de idade pré-escolar em função da frequência em rede pública ou privada

A dissertação procura compreender de que maneira a frequência da criança numa escola pública ou numa escola privada, poderá afetar o desenvolvimento dos indicadores de resiliência definidos (autonomia e capacidades de interação social) e a sua vinculação aos pais. O presente estudo realizou-se em três escolas do primeiro ciclo com jardim de infância, duas das quais pertenciam ao ensino público e uma ao ensino privado. A revisão da literatura, exposta nos vários capítulos, apresenta a visão de diversos investigadores sobre a problemática da relação entre o desenvolvimento dos indicadores de resiliência definidos, a maneira como as crianças criam as suas relações de vinculação, focando as diferenças relativamente à frequência em rede pública ou rede privada. Por se tratar de um estudo comparativo, foi escolhida uma metodologia quantitativa. Procedeu-se, em seguida, a uma análise qualitativa dos resultados obtidos em algumas variáveis. O estudo conclui que não se verificam diferenças significativas no que diz respeito aos resultados obtidos pelas crianças relativamente às variáveis em estudo, com exceção do indicador de resiliência “capacidades de interação social”. Este estudo também nos mostra que existem várias variáveis a ter em conta para compreender a resiliência e a relação entre as variáveis, nomeadamente, as qualificações dos prestadores de cuidados. Sugere-se a continuação do trabalho iniciado, avaliando a vinculação e os indicadores de resiliência estudados (autonomia e capacidades de interação social) destas mesmas crianças, no futuro. Sugere-se ainda a realização de outros estudos, dentro da mesma área, que possam aprofundar a influência das diversas variáveis que dizem respeito ao contexto socioeconómico e sociodemográfico onde as crianças estão inseridas e ver de que maneira estes afetam as variáveis estudadas neste trabalho. - Abstract The dissertation sought to understand how child‟s frequency in a public or a private school, can affect the development of resilience indicators defined (autonomy and capabilities social interaction capabilities) and their connection to parents. This study was conducted in three primary schools with kindergarten, two of which belonged to public education and one to private education. The literature review, exposed in several chapters, presents the view of many researchers on the issue of the relationship between the development of resilience indicators defined, the way children create their linking relations, focusing on the differences in the frequency on public or private school. Since this is a comparative study, a quantitative methodology was chosen. Then we‟ve proceeded to a qualitative analysis of the results obtained on some variables. The study concludes that there are no significant differences with regard to the results obtained by children, for the variables under study except for the indicator of resilience “capabilities of social interaction”. This study also shows that there are several variables to take into account to understand the resilience and the relation between variables, namely, the qualifications of care providers. It is suggested to continue the work begun by evaluating the binding and resilience indicators studied (autonomy and social interaction skills) of these same children in the future. It is also suggested in other studies within the same area, which may deepen the influence of several variables that relate to socio-demographic and socio-economic context where children are located and see how they affect the variables studied in this work

Genetic algorithm methodology applied to intelligent house control

In recent years the use of several new resources in power systems, such as distributed generation, demand response and more recently electric vehicles, has significantly increased. Power systems aim at lowering operational costs, requiring an adequate energy resources management. In this context, load consumption management plays an important role, being necessary to use optimization strategies to adjust the consumption to the supply profile. These optimization strategies can be integrated in demand response programs. The control of the energy consumption of an intelligent house has the objective of optimizing the load consumption. This paper presents a genetic algorithm approach to manage the consumption of a residential house making use of a SCADA system developed by the authors. Consumption management is done reducing or curtailing loads to keep the power consumption in, or below, a specified energy consumption limit. This limit is determined according to the consumer strategy and taking into account the renewable based micro generation, energy price, supplier solicitations, and consumers’ preferences. The proposed approach is compared with a mixed integer non-linear approach.

Perspetivas das educadoras de infância de uma instituição particular de solidariedade social sobre o contributo da colaboração para o seu desenvolvimento profissional

Dissertação apresentada à Escola Superior de Educação de Lisboa para obtenção de grau de mestre em Ciências da Educação, especialidade em Supervisão em Educação

Construção e desenvolvimento da identidade profissional do educador de infância - percursos no masculino : um estudo de três casos

Dissertação de Mestrado em Supervisão em Educação, enquadrada na linha de investigação sobre Desenvolvimento Profissional dos Professores, apresentada à Escola Superior de Educação de Lisboa

Perspetivas dos professores do 1º ciclo sobre a supervisão no processo de avaliação de desempenho e os seus efeitos no desenvolvimento profissional

Dissertação apresentada à Escola Superior de Educação de Lisboa para obtenção de grau de mestre em Ciências da Educação, especialização Supervisão em Educação

O fim de um ciclo? A coconstrução da articulação curricular entre o 1.º e o 2.º Ciclos do Ensino Básico

Dissertação Apresentada à Escola Superior de Educação de Lisboa para obtenção de grau de mestre em Ciências da Educação - Especialidade Supervisão em Educação

Práticas de inclusão de alunos com perturbação do espectro do autismo no 1º Ciclo

Dissertação apresentada à Escola Superior de Educação de Lisboa para obtenção de grau de mestre em Ciências da Educação, especialidade Educação Especial – Problemas Cognitivos e Multideficiência

A data-mining based methodology for wind forecasting

In many countries the use of renewable energy is increasing due to the introduction of new energy and environmental policies. Thus, the focus on the efficient integration of renewable energy into electric power systems is becoming extremely important. Several European countries have already achieved high penetration of wind based electricity generation and are gradually evolving towards intensive use of this generation technology. The introduction of wind based generation in power systems poses new challenges for the power system operators. This is mainly due to the variability and uncertainty in weather conditions and, consequently, in the wind based generation. In order to deal with this uncertainty and to improve the power system efficiency, adequate wind forecasting tools must be used. This paper proposes a data-mining-based methodology for very short-term wind forecasting, which is suitable to deal with large real databases. The paper includes a case study based on a real database regarding the last three years of wind speed, and results for wind speed forecasting at 5 minutes intervals.

A data-mining-based methodology for transmission expansion planning

In recent decades, all over the world, competition in the electric power sector has deeply changed the way this sector’s agents play their roles. In most countries, electric process deregulation was conducted in stages, beginning with the clients of higher voltage levels and with larger electricity consumption, and later extended to all electrical consumers. The sector liberalization and the operation of competitive electricity markets were expected to lower prices and improve quality of service, leading to greater consumer satisfaction. Transmission and distribution remain noncompetitive business areas, due to the large infrastructure investments required. However, the industry has yet to clearly establish the best business model for transmission in a competitive environment. After generation, the electricity needs to be delivered to the electrical system nodes where demand requires it, taking into consideration transmission constraints and electrical losses. If the amount of power flowing through a certain line is close to or surpasses the safety limits, then cheap but distant generation might have to be replaced by more expensive closer generation to reduce the exceeded power flows. In a congested area, the optimal price of electricity rises to the marginal cost of the local generation or to the level needed to ration demand to the amount of available electricity. Even without congestion, some power will be lost in the transmission system through heat dissipation, so prices reflect that it is more expensive to supply electricity at the far end of a heavily loaded line than close to an electric power generation. Locational marginal pricing (LMP), resulting from bidding competition, represents electrical and economical values at nodes or in areas that may provide economical indicator signals to the market agents. This article proposes a data-mining-based methodology that helps characterize zonal prices in real power transmission networks. To test our methodology, we used an LMP database from the California Independent System Operator for 2009 to identify economical zones. (CAISO is a nonprofit public benefit corporation charged with operating the majority of California’s high-voltage wholesale power grid.) To group the buses into typical classes that represent a set of buses with the approximate LMP value, we used two-step and k-means clustering algorithms. By analyzing the various LMP components, our goal was to extract knowledge to support the ISO in investment and network-expansion planning.

Strategic bidding methodology for electricity markets using adaptive learning

The very particular characteristics of electricity markets, require deep studies of the interactions between the involved players. MASCEM is a market simulator developed to allow studying electricity market negotiations. This paper presents a new proposal for the definition of MASCEM players’ strategies to negotiate in the market. The proposed methodology is implemented as a multiagent system, using reinforcement learning algorithms to provide players with the capabilities to perceive the changes in the environment, while adapting their bids formulation according to their needs, using a set of different techniques that are at their disposal. This paper also presents a methodology to define players’ models based on the historic of their past actions, interpreting how their choices are affected by past experience, and competition.

Dinâmicas e relações intra-organizacionais nos cuidados às crianças / adolescentes com diabetes mellitus tipo 1

Mestrado em Intervenção Sócio-Organizacional na Saúde. Área de especialização: Políticas de Administração e Gestão dos Serviços de Saúde.

Zonal prices analysis supported by a data mining based methodology

A methodology based on data mining techniques to support the analysis of zonal prices in real transmission networks is proposed in this paper. The mentioned methodology uses clustering algorithms to group the buses in typical classes that include a set of buses with similar LMP values. Two different clustering algorithms have been used to determine the LMP clusters: the two-step and K-means algorithms. In order to evaluate the quality of the partition as well as the best performance algorithm adequacy measurements indices are used. The paper includes a case study using a Locational Marginal Prices (LMP) data base from the California ISO (CAISO) in order to identify zonal prices.

Optimal methodology for renewable energy dispatching in islanded operation

The management of energy resources for islanded operation is of crucial importance for the successful use of renewable energy sources. A Virtual Power Producer (VPP) can optimally operate the resources taking into account the maintenance, operation and load control considering all the involved cost. This paper presents the methodology approach to formulate and solve the problem of determining the optimal resource allocation applied to a real case study in Budapest Tech’s. The problem is formulated as a mixed-integer linear programming model (MILP) and solved by a deterministic optimization technique CPLEX-based implemented in General Algebraic Modeling Systems (GAMS). The problem has also been solved by Evolutionary Particle Swarm Optimization (EPSO). The obtained results are presented and compared.