Adaptive learning in agents behaviour: A framework for electricity markets simulation

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 (Multi-Agent System for Competitive Electricity Markets) is a multi-agent electricity market simulator that models market players and simulates their operation in the market. Market players are entities with specific characteristics and objectives, making their decisions and interacting with other players. This paper presents a methodology to provide decision support to electricity market negotiating players. This model allows integrating different strategic approaches for electricity market negotiations, and choosing the most appropriate one at each time, for each different negotiation context. This methodology is integrated in ALBidS (Adaptive Learning strategic Bidding System) – a multiagent system that provides decision support to MASCEM's negotiating agents so that they can properly achieve their goals. ALBidS uses artificial intelligence methodologies and data analysis algorithms to provide effective adaptive learning capabilities to such negotiating entities. The main contribution is provided by a methodology that combines several distinct strategies to build actions proposals, so that the best can be chosen at each time, depending on the context and simulation circumstances. The choosing process includes reinforcement learning algorithms, a mechanism for negotiating contexts analysis, a mechanism for the management of the efficiency/effectiveness balance of the system, and a mechanism for competitor players' profiles definition.

Participação de crianças com multidificiência e deficiência visual em actividades na escola : orientações para a intervenção

O crescente reconhecimento das limitações das crianças com multideficiência e deficiência visual, quer nas interacções com os parceiros quer de uma forma geral nos ambientes em que se inserem, motivou este estudo, que pretendeu analisar o nível de participação destas crianças em actividades na escola. Considerando a importância de contribuir com informação para orientações na intervenção educativa de crianças com MDVI, realizou-se um estudo que analisa o seu comportamento e envolvimento em actividades da escola. Para a realização deste estudo, observaram-se os comportamentos de três crianças com MDVI, com idades compreendidas entre os 9 e os 10 anos, em três ambientes da escola, nomeadamente a sala de aula, o refeitório e o recreio, e em três actividades (pintura, jogos, almoço, saltar à corda, andar de baloiço e subir escadas) de forma a analisar o seu envolvimento e limitações nas actividades. Na análise dos dados das observações foram identificadas quatro categorias de participação: Inicia, Perde Oportunidade, Inicia com Apoio e Comportamento Potencialmente Comunicativo, registando-se valores que permitiram encontrar características dos comportamentos das crianças observadas, assim como o seu nível de participação em actividades na escola. Os resultados do estudo permitiram verificar que a participação das crianças em actividades está condicionada pelos ambientes em que estão envolvidas, e não pelas problemáticas que cada criança apresenta.----------------------------------------ABSTRACT: The motivation of this study is the increasing knowledge and awareness of children who have multiple disabilities and a visual impairment (MDVI) and the limitation with their peer interactions and in general. The purpose of this study was to analyze the participation level of children with MDVI in school activities. Considering the importance of contributing with guidelines for educational intervention with children with MDVI, we did a study that analyzes the behavior and the level of participation of MDVI children in school activities. In this research study we observed the behavior of three children with MDVI, of 9/10 years old, in three different environments at school; the classroom, the canteen and the playground, and in different activities (painting, playing games, having lunch, skipping rope, etc), in order to analyze their participation and their activity limitations in the activities referred. Data analysis identified four categories of participation: Initiation; Missed Opportunities; Initiation with support and Potentially communicative behavior. Results of data analysis allowed us to find out characteristics of children´s behavior, as well as their level of participation in activities. The main findings of this research allowed us to verify that the child’s engagement in activities depends on the environments where they are located and not on their disability.

Enhancing the selection of a model-based clustering with external categorical variables

In cluster analysis, it can be useful to interpret the partition built from the data in the light of external categorical variables which are not directly involved to cluster the data. An approach is proposed in the model-based clustering context to select a number of clusters which both fits the data well and takes advantage of the potential illustrative ability of the external variables. This approach makes use of the integrated joint likelihood of the data and the partitions at hand, namely the model-based partition and the partitions associated to the external variables. It is noteworthy that each mixture model is fitted by the maximum likelihood methodology to the data, excluding the external variables which are used to select a relevant mixture model only. Numerical experiments illustrate the promising behaviour of the derived criterion.

Monitoring the ex-vivo expansion of human mesenchymal stem/stromal cells in xeno-free microcarrier-based reactor systems by MIR spectroscopy

Human mesenchymal stem/stromal cells (MSCs) have received considerable attention in the field of cell-based therapies due to their high differentiation potential and ability to modulate immune responses. However, since these cells can only be isolated in very low quantities, successful realization of these therapies requires MSCs ex-vivo expansion to achieve relevant cell doses. The metabolic activity is one of the parameters often monitored during MSCs cultivation by using expensive multi-analytical methods, some of them time-consuming. The present work evaluates the use of mid-infrared (MIR) spectroscopy, through rapid and economic high-throughput analyses associated to multivariate data analysis, to monitor three different MSCs cultivation runs conducted in spinner flasks, under xeno-free culture conditions, which differ in the type of microcarriers used and the culture feeding strategy applied. After evaluating diverse spectral preprocessing techniques, the optimized partial least square (PLS) regression models based on the MIR spectra to estimate the glucose, lactate and ammonia concentrations yielded high coefficients of determination (R2 ≥ 0.98, ≥0.98, and ≥0.94, respectively) and low prediction errors (RMSECV ≤ 4.7%, ≤4.4% and ≤5.7%, respectively). Besides PLS models valid for specific expansion protocols, a robust model simultaneously valid for the three processes was also built for predicting glucose, lactate and ammonia, yielding a R2 of 0.95, 0.97 and 0.86, and a RMSECV of 0.33, 0.57, and 0.09 mM, respectively. Therefore, MIR spectroscopy combined with multivariate data analysis represents a promising tool for both optimization and control of MSCs expansion processes.

GPU implementation of the simplex identification via split augmented Lagrangian

Hyperspectral imaging can be used for object detection and for discriminating between different objects based on their spectral characteristics. One of the main problems of hyperspectral data analysis is the presence of mixed pixels, due to the low spatial resolution of such images. This means that several spectrally pure signatures (endmembers) are combined into the same mixed pixel. Linear spectral unmixing follows an unsupervised approach which aims at inferring pure spectral signatures and their material fractions at each pixel of the scene. The huge data volumes acquired by such sensors put stringent requirements on processing and unmixing methods. This paper proposes an efficient implementation of a unsupervised linear unmixing method on GPUs using CUDA. The method finds the smallest simplex by solving a sequence of nonsmooth convex subproblems using variable splitting to obtain a constraint formulation, and then applying an augmented Lagrangian technique. The parallel implementation of SISAL presented in this work exploits the GPU architecture at low level, using shared memory and coalesced accesses to memory. The results herein presented indicate that the GPU implementation can significantly accelerate the method's execution over big datasets while maintaining the methods accuracy.

Práticas de contabilidade e controlo de gestão no setor automóvel

Dissertação apresentada para obtenção do Grau de Mestre em Contabilidade e Finanças, sob orientação de: Amélia Ferreira da Silva José António Fernandes Lopes Oliveira Vale

Parallel hyperspectral unmixing method via split augmented lagrangian on GPU

One of the main problems of hyperspectral data analysis is the presence of mixed pixels due to the low spatial resolution of such images. Linear spectral unmixing aims at inferring pure spectral signatures and their fractions at each pixel of the scene. The huge data volumes acquired by hyperspectral sensors put stringent requirements on processing and unmixing methods. This letter proposes an efficient implementation of the method called simplex identification via split augmented Lagrangian (SISAL) which exploits the graphics processing unit (GPU) architecture at low level using Compute Unified Device Architecture. SISAL aims to identify the endmembers of a scene, i.e., is able to unmix hyperspectral data sets in which the pure pixel assumption is violated. The proposed implementation is performed in a pixel-by-pixel fashion using coalesced accesses to memory and exploiting shared memory to store temporary data. Furthermore, the kernels have been optimized to minimize the threads divergence, therefore achieving high GPU occupancy. The experimental results obtained for the simulated and real hyperspectral data sets reveal speedups up to 49 times, which demonstrates that the GPU implementation can significantly accelerate the method's execution over big data sets while maintaining the methods accuracy.

Modelação de equações estruturais para avaliar e monitorizar o estado de condição de um sistema mecânico.

Dissertação apresentada como requisito parcial para obtenção do grau de Mestre em Estatística e Gestão de Informação.

Topics regarding access to european information institutions: European Union so close and yet so far

From the 1990s, the Parliament, the Council and the European Commission adopted a new approach to disclosure of their working papers. Legal instruments to regulate and allow a fairly broad access to internal working documents of these institutions were created. European institutions also exploited the potential of Information and Communication Technologies, developing new instruments to register the documents produced and make them accessible to the public. The commitment to transparency sought to shows a more credible European government, and reduces the democratic deficit. However, the data analysis regarding access to EU institutions documents shows that general public is still far from direct contact with European bodies.

Tudo o que vem à rede é peixe? A credibilidade da informação na web

O objetivo deste estudo é conhecer uma vertente específica do perfil informacional dos alunos que cresceram na era digital, ditos nativos digitais, na utilização que fazem da Internet. Assim, pretende-se aferir os critérios que aplicam na avaliação das fontes de informação disponíveis na web na vertente da credibilidade. A análise dos dados obtidos, resultantes da aplicação de 195 questionários a alunos do 8º ao 12º, é enquadrada e sustentada por revisão da literatura acerca do conceito de credibilidade da informação.

Adaptive Learning in Games: Defining Profiles of Competitor Players

Artificial Intelligence has been applied to dynamic games for many years. The ultimate goal is creating responses in virtual entities that display human-like reasoning in the definition of their behaviors. However, virtual entities that can be mistaken for real persons are yet very far from being fully achieved. This paper presents an adaptive learning based methodology for the definition of players’ profiles, with the purpose of supporting decisions of virtual entities. The proposed methodology is based on reinforcement learning algorithms, which are responsible for choosing, along the time, with the gathering of experience, the most appropriate from a set of different learning approaches. These learning approaches have very distinct natures, from mathematical to artificial intelligence and data analysis methodologies, so that the methodology is prepared for very distinct situations. This way it is equipped with a variety of tools that individually can be useful for each encountered situation. The proposed methodology is tested firstly on two simpler computer versus human player games: the rock-paper-scissors game, and a penalty-shootout simulation. Finally, the methodology is applied to the definition of action profiles of electricity market players; players that compete in a dynamic game-wise environment, in which the main goal is the achievement of the highest possible profits in the market.

A credibilidade da informação na web: estudo de práticas informacionais em contexto escolar

Apresentam-se os resultados parcelares de um estudo destinado a promover um melhor conhecimento das estratégias que os jovens em idade escolar (12-18 anos) consideram relevantes para avaliar as fontes de informação disponíveis na Internet. Para o efeito, foi aplicado um inquérito distribuído a uma amostra de 195 alunos de uma escola do 3o ciclo e outra do ensino secundário de um concelho do distrito do Porto. São apresentados e discutidos os resultados acerca da perceção destes alunos quanto aos critérios a aplicar na avaliação das fontes de informação disponíveis na Internet, na vertente da credibilidade. Serão apresenta- das as práticas que os jovens declaram ter relativamente ao uso de critérios de autoria, originalidade, estrutura, atualidade e de comparação para avaliar a credibilidade das fontes de informação. Em complemento, estes resultados serão comparados e discutidos com as perceções que os mesmos inquiridos demonstram possuir relativamente aos elementos que compõem cada um destes critérios. A análise dos dados obtidos é enquadrada e sustentada numa revisão da literatura acerca do conceito de credibilidade, aplicado às fontes de informação disponíveis na Internet. São ainda abordados alguns tópicos relaciona- dos com a inclusão de estratégias de avaliação da credibilidade da informação digital no modelo Big6, um dos modelos de desenvolvimento de competências de literacia da informação mais conhecidos e utilizados nas bibliotecas escolares portuguesas.

Screening pentachlorophenol degradation ability by environmental fungal strains belonging to the phyla Ascomycota and Zygomycota

Pentachlorophenol (PCP) bioremediation by the fungal strains amongst the cork- colonising community has not yet been analysed. In this paper, the co- and direct metabolism of PCP by each of the 17 fungal species selected from this community were studied. Using hierarchical data analysis, the isolates were ranked by their PCP bioremediation potential. Fifteen isolates were able to degrade PCP under co-metabolic conditions, and surprisingly Chrysonilia sitophila, Trichoderma longibrachiatum, Mucor plumbeus, Penicillium janczewskii and P. glandicola were able to directly metabolise PCP, leading to its complete depletion from media. PCP degradation intermediates are preliminarily discussed. Data emphasise the signiWcance of these fungi to have an interesting potential to be used in PCP bioremediation processes.

Plataforma de Dados de Saúde - Portal Institucional

O presente documento de dissertação retrata o desenvolvimento do projeto PDS-Portal Institucional cujo cerne é um sistema para recolha, armazenamento e análise de dados (plataforma de Business Intelligence). Este portal está enquadrado na área da saúde e é uma peça fundamental no sistema da Plataforma de dados da Saúde, que é constituído por quatro portais distintos. Esta plataforma tem como base um sistema totalmente centrado no utente, que agrega dados de saúde dos utentes e distribui pelos diversos intervenientes: utente, profissionais de saúde nacionais e internacionais e organizações de saúde. O objetivo principal deste projeto é o desenvolvimento do PDS-Portal Institucional, recorrendo a uma plataforma de Business Intelligence, com o intuito de potenciar os utilizadores de uma ferramenta analítica para análise de dados. Estando a informação armazenada em dois dos portais da Plataforma de dados da Saúde (PDS-Portal Utente e PDS-Portal Profissional), é necessário modular um armazém de dados que agregue a informação de ambos e, através do PDS-PI, distribua um conjunto de análises ao utilizador final. Para tal este sistema comtempla um mecanismo totalmente automatizado para extração, tratamento e carregamento de dados para o armazém central, assim como uma plataforma de BI que disponibiliza os dados armazenados sobre a forma de análises específicas. Esta plataforma permite uma evolução constante e é extremamente flexível, pois fornece um mecanismo de gestão de utilizadores e perfis, assim como capacita o utilizador de um ambiente Web para análise de dados, permitindo a partilha e acesso a partir de dispositivos móveis. Após a implementação deste sistema foi possível explorar os dados e tirar diversas conclusões que são de extrema importância tanto para a evolução da PDS como para os métodos de praticar os cuidados de saúde em Portugal. Por fim são identificados alguns pontos de melhoria do sistema atual e delineada uma perspetiva de evolução futura. É certo que a partir do momento que este projeto seja lançado para produção, novas oportunidades surgirão e o contributo dos utilizadores será útil para evoluir o sistema progressivamente.

An initial examination of the epidemiology of malaria in the State of Roraima, in the Brazilian Amazon Basin

This study firstly describes the epidemiology of malaria in Roraima, Amazon Basin in Brazil, in the years from 1991 to 1993: the predominance of plasmodium species, distribution of the blood slides examined, the malaria risk and seasonality; and secondly investigates whether population growth from 1962 to 1993 was associated with increasing risk of malaria. Frequency of malaria varied significantly by municipality. Marginally more malaria cases were reported during the dry season (from October to April), even after controlling for by year and municipality. Vivax was the predominant type in all municipalities but the ratio of plasmodium types varied between municipalities. No direct association between population growth and increasing risk of malaria from 1962 to 1993 was detected. Malaria in Roraima is of the "frontier" epidemiological type with high epidemic potential.