Design de cenários de aprendizagem

A cada instante surgem novas soluções de aprendizagem, resultado da evolução tecnológica constante com que nos deparamos. Estas inovações potenciam uma transmissão do conhecimento entre o educador e o educando cada vez mais simplificada, rápida e eficiente. Alguns destes avanços têm em vista a centralização no aluno, através da delegação de tarefas e da disponibilização de conteúdos, investindo na autonomia e na auto-aprendizagem, de modo a que cada aluno crie o seu próprio método de estudo, e evolua gradualmente, com o acompanhamento de um professor ou sistema autónomo de aprendizagem. Com esta investigação, é pretendido fazer um estudo dos métodos de aprendizagem ao longo do tempo até à actualidade, enumerando algumas das ferramentas utilizadas no processo de aprendizagem, indicando os vários benefícios, bem como contrapartidas do uso das mesmas. Será também analisado um caso de estudo baseado numa destas ferramentas, descrevendo o seu funcionamento e modo de interacção entre as várias entidades participantes, apresentando os resultados obtidos. O caso de estudo consistirá na criação de um cenário específico de aprendizagem, na área da saúde, analisando-o em diferentes contextos, e evidenciando as características e benefícios de cada ambiente analisado, no processo aprendizagem. Será então demonstrado como é possível optimizar os processos de aprendizagem, utilizando ferramentas de informatização e automatização desses mesmos processos, de forma tornar o processo de ensino mais célere e eficaz, num ambiente controlável, e com as funcionalidades que a tecnologia actual permite.

E-Learning as a shared service in shared services centers

Book Subtitle International Conference, CENTERIS 2010, Viana do Castelo, Portugal, October 20-22, 2010, Proceedings, Part II

Cloud computing sobre a plataforma Windows Azure

A utilização massiva da internet e dos serviços que oferece por parte do utilizador final potencia a evolução dos mesmos, motivando as empresas a apostarem no desenvolvimento deste tipo de soluções. Requisitos como o poder de computação, flexibilidade e escalabilidade tornam-se cada vez mais indissociáveis do desenvolvimento aplicacional, o que leva ao surgimento de paradigmas como o de Cloud Computing. É neste âmbito que surge o presente trabalho. Com o objetivo de estudar o paradigma de Cloud Computing inicia-se um estudo sobre esta temática, onde é detalhado o seu conceito, a sua evolução histórica e comparados os diferentes tipos de implementações que suporta. O estudo detalha posteriormente a plataforma Azure, sendo analisada a sua topologia e arquitetura, detalhando-se os seus componentes e a forma como esta mitiga alguns dos problemas mencionados. Com o conhecimento teórico é desenvolvido um protótipo prático sobre esta plataforma, em que se exploram algumas das particularidades da topologia e se interage com as principais redes sociais. O estudo culmina com uma análise sobre os benefícios e desvantagens do Azure e através de um levantamento das necessidades da empresa, determinam-se as oportunidades que a utilização da plataforma poderá proporcionar.

Macrophages as biomarkers in BCG treatment response in bladder cancer

Bladder cancer is a common urologic cancer and the majority has origin in the urothelium. Patients with intermediate and high risk of recurrence/progression bladder cancer are treated with intravesical instillation with Bacillus Calmette-Guérin, however, approximately 30% of patients do not respond to treatment. At the moment, there are no accepted biomarkers do predict treatment outcome and an early identification of patients better served by alternative therapeutics. The treatment initiates a cascade of cytokines responsible by recruiting macrophages to the tumor site that have been shown to influence treatment outcome. Effective BCG therapy needs precise activation of the Th1 immune pathway associated with M1 polarized macrophages. However, tumor-associated macrophages (TAMs) often assume an immunoregulatory M2 phenotype, either immunosuppressive or angiogenic, that interfere in different ways with the BCG induced antitumor immune response. The M2 macrophage is influenced by different microenvironments in the stroma and the tumor. In particular, the degree of hypoxia in the tumors is responsible by the recruitment and differentiation of macrophages into the M2 angiogenic phenotype, suggested to be associated with the response to treatment. Nevertheless, neither the macrophage phenotypes present nor the influence of localization and hypoxia have been addressed in previous studies. Therefore, this work devoted to study the influence of TAMs, in particular of the M2 phenotype taking into account their localization (stroma or tumor) and the degree of hypoxia in the tumor (low or high) in BCG treatment outcome. The study included 99 bladder cancer patients treated with BCG. Tumors resected prior to treatment were evaluated using immunohistochemistry for CD68 and CD163 antigens, which identify a lineage macrophage marker and a M2-polarized specific cell surface receptor, respectively. Tumor hypoxia was evaluated based on HIF-1α expression. As a main finding it was observed that a high predominance of CD163+ macrophage counts in the stroma of tumors under low hypoxia was associated with BCG immunotherapy failure, possibly due to its immunosuppressive phenotype. This study further reinforces the importance the tumor microenvironment in the modulation of BCG responses.

Literacia de informação na Polícia de Segurança Pública

Orientadora: Doutora Anabela Mesquita Teixeira Sarmento

Strategic bidding in electricity markets: an agent-based simulator with game theory for scenario analysis

Electricity markets are complex environments, involving a large number of different entities, with specific characteristics and objectives, making their decisions and interacting in a dynamic scene. Game-theory has been widely used to support decisions in competitive environments; therefore its application in electricity markets can prove to be a high potential tool. This paper proposes a new scenario analysis algorithm, which includes the application of game-theory, to evaluate and preview different scenarios and provide players with the ability to strategically react in order to exhibit the behavior that better fits their objectives. This model includes forecasts of competitor players’ actions, to build models of their behavior, in order to define the most probable expected scenarios. Once the scenarios are defined, game theory is applied to support the choice of the action to be performed. Our use of game theory is intended for supporting one specific agent and not for achieving the equilibrium in the market. 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. The scenario analysis algorithm has been tested within MASCEM and our experimental findings with a case study based on real data from the Iberian Electricity Market are presented and discussed.

Caracterização molecular da resistência a antimicrobianos em Escherichia coli produtoras de β-lactamases de espectro alargado isoladas em cães e estudo da partilha de clones bacterianos entre animais de companhia e coabitantes humanos

A pressão seletiva originada pelo uso excessivo de antimicrobianos na medicina humana e veterinária tem contribuído para a emergência de estirpes bacterianas multirresistentes, sendo os estudos mais escassos relativamente à sua presença nos animais de companhia. Porque os animais e os seus proprietários partilham o mesmo espaço habitacional, apresentando comportamentos de contacto próximo, existe uma hipótese elevada de transferência microbiana inter-espécie. Ante esta possibilidade é importante escrutinar o papel dos animais de companhia enquanto reservatórios de estirpes e de genes de resistência, bem como a sua envolvência na disseminação de estirpes bacterianas multirresistentes. Importa também, investigar o papel das superfícies e objetos domésticos partilhados por ambos, como potenciadores deste fenómeno. O objetivo deste trabalho foi, identificar o filogrupo e fazer a caracterização molecular dos genes que conferem resistência aos β-lactâmicos e às quinolonas, em quarenta isolados de Escherichia coli produtoras de β-lactamases de espectro alargado (ESBL), obtidas em zaragatoas fecais de cães consultados no Hospital Veterinário do ICBAS-UP. Complementarmente pretendeu-se inferir sobre a partilha de clones de Escherichia coli e Enterococcus spp. com elevadas resistências, em cinco agregados familiares (humanos e seus animais de companhia) assim como avaliar a potencial disseminação de estirpes multirresistentes no ambiente doméstico. Previamente foram recolhidas zaragatoas de fezes, pelo e mucosa oral dos animais e em alguns casos, dos seus proprietários, e ainda do ambiente doméstico. As zaragatoas foram processadas e as estirpes isoladas com base em meios seletivos. Foram realizados testes de suscetibilidade antimicrobiana de modo a estabelecer o fenótipo de resistência de cada isolado. O DNA foi extraído por varias metodologias e técnicas de PCR foram utilizadas para caracterização de filogrupos (Escherichia coli) e identificação da espécie (Enterococcus spp.). A avaliação da proximidade filogenética entre isolados foi efetuada por ERIC PCR e PFGE. No conjunto de quarenta isolados produtores de ESBL e/ou resistentes a quinolonas verificou-se que 47,5% pertenciam ao filogrupo A, havendo uma menor prevalência do filogrupo D (25,0%), B1 (17,5%), e B2 (10,0%).A frequência de resistência nestes isolados é factualmente elevada, sendo reveladora de uma elevada pressão seletiva. Com exceção de dois isolados, os fenótipos foram justificados pela presença de β-lactamases. A frequência da presença de genes foi: 47% blaTEM, 34% blaSHV, 24% blaOXA , 18% blaCTX-M-15, 8% blaCTX-M-2, 3% blaCTX-M-9. Nos isolados resistentes às quinolonas verificou-se maioritariamente a presença de mutações nos genes cromossomais gyrA e parC, e em alguns casos a presença de um determinante de resistência mediado por plasmídeo – qnrS. Nos cinco “agregados familiares” (humanos e animais) estudados foi observada uma partilha frequente de clones de E. coli e Enterococcus faecalis com múltiplas resistências, isolados em fezes e mucosa oral de cães e gatos e fezes e mãos dos respetivos proprietários, evidenciando-se assim uma possível transferência direta entre coabitantes (agregados A, C, D, E). Ficou também comprovado com percentagens de similaridade genotípica superiores a 94% que essa disseminação também ocorre para o ambiente doméstico, envolvendo objetos dos animais e de uso comum (agregados A, E). Os resultados obtidos reforçam a necessidade de um uso prudente dos antimicrobianos, pois elevados padrões de resistências terão um impacto não só na qualidade de vida dos animais mas também na saúde humana. Adicionalmente importa sensibilizar os proprietários para a necessidade de uma maior vigilância relativamente às formas de interação com os animais, bem como para a adoção de medidas higiénicas cautelares após essa mesma interação.

Towards network-on-chip agreement protocols

Demands for functionality enhancements, cost reductions and power savings clearly suggest the introduction of multiand many-core platforms in real-time embedded systems. However, when compared to uni-core platforms, the manycores experience additional problems, namely the lack of scalable coherence mechanisms and the necessity to perform migrations. These problems have to be addressed before such systems can be considered for integration into the realtime embedded domain. We have devised several agreement protocols which solve some of the aforementioned issues. The protocols allow the applications to plan and organise their future executions both temporally and spatially (i.e. when and where the next job will be executed). Decisions can be driven by several factors, e.g. load balancing, energy savings and thermal issues. All presented protocols are analytically described, with the particular emphasis on their respective real-time behaviours and worst-case performance. The underlying assumptions are based on the multi-kernel model and the message-passing paradigm, which constitutes the communication between the interacting instances.

Complex evolution of a multi-particle system

This paper studies a discrete dynamical system of interacting particles that evolve by interacting among them. The computational model is an abstraction of the natural world, and real systems can range from the huge cosmological scale down to the scale of biological cell, or even molecules. Different conditions for the system evolution are tested. The emerging patterns are analysed by means of fractal dimension and entropy measures. It is observed that the population of particles evolves towards geometrical objects with a fractal nature. Moreover, the time signature of the entropy can be interpreted at the light of complex dynamical systems.

Fractional dynamics in financial indexes

The goal of this study is the analysis of the dynamical properties of financial data series from 32 worldwide stock market indices during the period 2000–2009 at a daily time horizon. Stock market indices are examples of complex interacting systems for which a huge amount of data exists. The methods and algorithms that have been explored for the description of physical phenomena become an effective background in the analysis of economical data. In this perspective are applied the classical concepts of signal analysis, Fourier transform and methods of fractional calculus. The results reveal classification patterns typical of fractional dynamical systems.

Analysis of financial data series using fractional Fourier transform and multidimensional scaling

The goal of this study is the analysis of the dynamical properties of financial data series from worldwide stock market indexes during the period 2000–2009. We analyze, under a regional criterium, ten main indexes at a daily time horizon. The methods and algorithms that have been explored for the description of dynamical phenomena become an effective background in the analysis of economical data. We start by applying the classical concepts of signal analysis, fractional Fourier transform, and methods of fractional calculus. In a second phase we adopt the multidimensional scaling approach. Stock market indexes are examples of complex interacting systems for which a huge amount of data exists. Therefore, these indexes, viewed from a different perspectives, lead to new classification patterns.

A sensor classification strategy for robotic manipulators

In practice the robotic manipulators present some degree of unwanted vibrations. The advent of lightweight arm manipulators, mainly in the aerospace industry, where weight is an important issue, leads to the problem of intense vibrations. On the other hand, robots interacting with the environment often generate impacts that propagate through the mechanical structure and produce also vibrations. In order to analyze these phenomena a robot signal acquisition system was developed. The manipulator motion produces vibrations, either from the structural modes or from endeffector impacts. The instrumentation system acquires signals from several sensors that capture the joint positions, mass accelerations, forces and moments, and electrical currents in the motors. Afterwards, an analysis package, running off-line, reads the data recorded by the acquisition system and extracts the signal characteristics. Due to the multiplicity of sensors, the data obtained can be redundant because the same type of information may be seen by two or more sensors. Because of the price of the sensors, this aspect can be considered in order to reduce the cost of the system. On the other hand, the placement of the sensors is an important issue in order to obtain the suitable signals of the vibration phenomenon. Moreover, the study of these issues can help in the design optimization of the acquisition system. In this line of thought a sensor classification scheme is presented. Several authors have addressed the subject of the sensor classification scheme. White (White, 1987) presents a flexible and comprehensive categorizing scheme that is useful for describing and comparing sensors. The author organizes the sensors according to several aspects: measurands, technological aspects, detection means, conversion phenomena, sensor materials and fields of application. Michahelles and Schiele (Michahelles & Schiele, 2003) systematize the use of sensor technology. They identified several dimensions of sensing that represent the sensing goals for physical interaction. A conceptual framework is introduced that allows categorizing existing sensors and evaluates their utility in various applications. This framework not only guides application designers for choosing meaningful sensor subsets, but also can inspire new systems and leads to the evaluation of existing applications. Today’s technology offers a wide variety of sensors. In order to use all the data from the diversity of sensors a framework of integration is needed. Sensor fusion, fuzzy logic, and neural networks are often mentioned when dealing with problem of combing information from several sensors to get a more general picture of a given situation. The study of data fusion has been receiving considerable attention (Esteban et al., 2005; Luo & Kay, 1990). A survey of the state of the art in sensor fusion for robotics can be found in (Hackett & Shah, 1990). Henderson and Shilcrat (Henderson & Shilcrat, 1984) introduced the concept of logic sensor that defines an abstract specification of the sensors to integrate in a multisensor system. The recent developments of micro electro mechanical sensors (MEMS) with unwired communication capabilities allow a sensor network with interesting capacity. This technology was applied in several applications (Arampatzis & Manesis, 2005), including robotics. Cheekiralla and Engels (Cheekiralla & Engels, 2005) propose a classification of the unwired sensor networks according to its functionalities and properties. This paper presents a development of a sensor classification scheme based on the frequency spectrum of the signals and on a statistical metrics. Bearing these ideas in mind, this paper is organized as follows. Section 2 describes briefly the robotic system enhanced with the instrumentation setup. Section 3 presents the experimental results. Finally, section 4 draws the main conclusions and points out future work.

Particle swarm design of digital circuits

Swarm Intelligence (SI) is the property of a system whereby the collective behaviors of (unsophisticated) agents interacting locally with their environment cause coherent functional global patterns to emerge. Particle swarm optimization (PSO) is a form of SI, and a population-based search algorithm that is initialized with a population of random solutions, called particles. These particles are flying through hyperspace and have two essential reasoning capabilities: their memory of their own best position and knowledge of the swarm's best position. In a PSO scheme each particle flies through the search space with a velocity that is adjusted dynamically according with its historical behavior. Therefore, the particles have a tendency to fly towards the best search area along the search process. This work proposes a PSO based algorithm for logic circuit synthesis. The results show the statistical characteristics of this algorithm with respect to number of generations required to achieve the solutions. It is also presented a comparison with other two Evolutionary Algorithms, namely Genetic and Memetic Algorithms.

Interoperability on e-learning 2.0: the PEACE case study

The confluence of education with the evolution of technology boosted the paradigm shift of the face-to-face learning to distance learning. In this scenario e-Learning plays an essential role as a facilitator of the teaching/learning process. However new demands associated with the new Web paradigm require that existent e-Learning environments characterized mostly by monolithic systems begin interacting with new specialized services. In this decentralized scenario the definition of a strategy of interoperability is the cornerstone to ensure the standardization communication among systems. This paper presents a definition of an interoperability strategy for an e-Learning environment at our School (ESEIG) called PEACE – Project for ESEIG Academic Content Environment. This new interoperability model relies on the application of several coordination and integration standards on several services, controlled by teachers and students, and included in the PEACE environment such as social networks, repositories, libraries, e-portfolios, intelligent tutors, recommendation systems and virtual classrooms.

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.