Biomarkers in Solea Senegalensis Kaup, 1858 exposed to contaminated estuarine sediments: a multi-level approach

Thesis submitted to the Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia for the degree of Doctor of Philosophy in Environmental Sciences

Multi-scale vegetation classification using earth observation data of the Sundarban mangrove forest, Bangladesh.

Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies.

Multi-agent Simulation of Bilateral Contracting in Competitive Electricity Markets

Traditional vertically integrated power utilities around the world have evolved from monopoly structures to open markets that promote competition among suppliers and provide consumers with a choice of services. Market forces drive the price of electricity and reduce the net cost through increased competition. Electricity can be traded in both organized markets or using forward bilateral contracts. This article focuses on bilateral contracts and describes some important features of an agent-based system for bilateral trading in competitive markets. Special attention is devoted to the negotiation process, demand response in bilateral contracting, and risk management. The article also presents a case study on forward bilateral contracting: a retailer agent and a customer agent negotiate a 24h-rate tariff.

Realistic Multi-Agent Simulation of Competitive Electricity Markets

The dynamism and ongoing changes that the electricity markets sector is constantly suffering, enhanced by the huge increase in competitiveness, create the need of using simulation platforms to support operators, regulators, and the involved players in understanding and dealing with this complex environment. This paper presents an enhanced electricity market simulator, based on multi-agent technology, which provides an advanced simulation framework for the study of real electricity markets operation, and the interactions between the involved players. MASCEM (Multi-Agent Simulator of Competitive Electricity Markets) uses real data for the creation of realistic simulation scenarios, which allow the study of the impacts and implications that electricity markets transformations bring to different countries. Also, the development of an upper-ontology to support the communication between participating agents, provides the means for the integration of this simulator with other frameworks, such as MAN-REM (Multi-Agent Negotiation and Risk Management in Electricity Markets). A case study using the enhanced simulation platform that results from the integration of several systems and different tools is presented, with a scenario based on real data, simulating the MIBEL electricity market environment, and comparing the simulation performance with the real electricity market results.

Data Mining Approach to support the Generation of Realistic Scenarios for Multi-Agent simulation of Electricity Markets

This paper presents the Realistic Scenarios Generator (RealScen), a tool that processes data from real electricity markets to generate realistic scenarios that enable the modeling of electricity market players’ characteristics and strategic behavior. The proposed tool provides significant advantages to the decision making process in an electricity market environment, especially when coupled with a multi-agent electricity markets simulator. The generation of realistic scenarios is performed using mechanisms for intelligent data analysis, which are based on artificial intelligence and data mining algorithms. These techniques allow the study of realistic scenarios, adapted to the existing markets, and improve the representation of market entities as software agents, enabling a detailed modeling of their profiles and strategies. This work contributes significantly to the understanding of the interactions between the entities acting in electricity markets by increasing the capability and realism of market simulations.

Distributed Intelligent Management of Microgrids using a Multi-Agent Simulation Platform

Multi-agent approaches have been widely used to model complex systems of distributed nature with a large amount of interactions between the involved entities. Power systems are a reference case, mainly due to the increasing use of distributed energy sources, largely based on renewable sources, which have potentiated huge changes in the power systems’ sector. Dealing with such a large scale integration of intermittent generation sources led to the emergence of several new players, as well as the development of new paradigms, such as the microgrid concept, and the evolution of demand response programs, which potentiate the active participation of consumers. This paper presents a multi-agent based simulation platform which models a microgrid environment, considering several different types of simulated players. These players interact with real physical installations, creating a realistic simulation environment with results that can be observed directly in the reality. A case study is presented considering players’ responses to a demand response event, resulting in an intelligent increase of consumption in order to face the wind generation surplus.

Genetic diversity of arginine catabolic mobile element in Staphylococcus epidermidis

PLos One, 4(11): ARTe7722

Sistema para a monitorização ativa com recurso ao cloud computing

O desenvolvimento de aplicações para dispositivos móveis já não é uma área recente, contudo continua a crescer a um ritmo veloz. É notório o avanço tecnológico dos últimos anos e a crescente popularidade destes dispositivos. Este avanço deve-se não só à grande evolução no que diz respeito às características destes dispositivos, mas também à possibilidade de criar aplicações inovadoras, práticas e passíveis de solucionar os problemas dos utilizadores em geral. Nesse sentido, as necessidades do quotidiano obrigam à implementação de soluções que satisfaçam os utilizadores, e nos dias de hoje, essa satisfação muitas vezes passa pelos dispositivos móveis, que já tem um papel fundamental na vida das pessoas. Atendendo ao aumento do número de raptos de crianças e à insegurança que se verifica nos dias de hoje, as quais dificultam a tarefa de todos os pais/cuidadores que procuraram manter as suas crianças a salvo, é relevante criar uma nova ferramenta capaz de os auxiliar nesta árdua tarefa. A partir desta realidade, e com vista a cumprir os aspetos acima mencionados, surge assim esta dissertação de mestrado. Esta aborda o estudo e implementação efetuados no sentido de desenvolver um sistema de monitorização de crianças. Assim, o objetivo deste projeto passa por desenvolver uma aplicação nativa para Android e um back-end, utilizando um servidor de base de dados NoSQL para o armazenamento da informação, aplicando os conceitos estudados e as tecnologias existentes. A solução tem como principais premissas: ser o mais user-friendly possível, a otimização, a escalabilidade para outras situações (outros tipos de monitorizações) e a aplicação das mais recentes tecnologias. Assim sendo, um dos estudos mais aprofundados nesta dissertação de mestrado está relacionado com as bases de dados NoSQL, dada a sua importância no projeto.

Sistema de apoio à racionalização da utilização de energia eléctrica

Esta dissertação descreve o sistema de apoio à racionalização da utilização de energia eléctrica desenvolvido no âmbito da unidade curricular de Tese/Dissertação. O domínio de aplicação enquadra-se no contexto da Directiva da União Europeia 2006/32/EC que declara ser necessário colocar à disposição dos consumidores a informação e os meios que promovam a redução do consumo e o aumento da eficiência energética individual. O objectivo é o desenvolvimento de uma solução que permita a representação gráfica do consumo/produção, a definição de tectos de consumo, a geração automática de alertas e alarmes, a comparação anónima com clientes com perfil idêntico por região e a previsão de consumo/produção no caso de clientes industriais. Trata-se de um sistema distribuído composto por front-end e back-end. O front-end é composto pelas aplicações de interface com o utilizador desenvolvidas para dispositivos móveis Android e navegadores Web. O back-end efectua o armazenamento e processamento de informação e encontra-se alojado numa plataforma de cloud computing – o Google App Engine – que disponibiliza uma interface padrão do tipo serviço Web. Esta opção assegura interoperabilidade, escalabilidade e robustez ao sistema. Descreve-se em detalhe a concepção, desenvolvimento e teste do protótipo realizado, incluindo: (i) as funcionalidades de gestão e análise de consumo e produção de energia implementadas; (ii) as estruturas de dados; (iii) a base de dados e o serviço Web; e (iv) os testes e a depuração efectuados. (iv) Por fim, apresenta-se o balanço deste projecto e efectuam-se sugestões de melhoria.

CANDi: context-aware node discovery for short-range cooperation

Multi-standard mobile devices are allowing users to enjoy higher data rates with ubiquitous connectivity. However, the benefits gained from multiple interfaces come at an expense—that being higher energy consumption in an era where mobile devices need to be energy compliant. One promising solution is the usage of short-range cooperative communication as an overlay for infrastructure-based networks taking advantage of its context information. However, the node discovery mechanism, which is pivotal to the bearer establishment process, still represents a major burden in terms of the total energy budget. In this paper, we propose a technology agnostic approach towards enhancing the MAC energy ratings by presenting a context-aware node discovery (CANDi) algorithm, which provides a priori knowledge towards the node discovery mechanism by allowing it to search nodes in the near vicinity at the ‘right time and at the right place’. We describe the different beacons required for establishing the cooperation, as well as the context information required, including battery level, modes, location and so on. CANDi uses the long-range network (WiMAX and WiFi) to distribute the context information about cooperative clusters (Ultra-wideband-based) in the vicinity. The searching nodes can use this context in locating the cooperative clusters/nodes, which facilitates the establishing of short-range connections. Analytical and simulation results are obtained, and the energy saving gains are further demonstrated in the laboratory using a customised testbed. CANDi saves up to 50% energy during the node discovery process, while the demonstrative testbed shows up to 75% savings in the total energy budget, thus validating the algorithm, as well as providing viable evidence to support the usage of short-range cooperative communications for energy savings.

A framework for memory contention analysis in multi-core platforms

The last decade has witnessed a major shift towards the deployment of embedded applications on multi-core platforms. However, real-time applications have not been able to fully benefit from this transition, as the computational gains offered by multi-cores are often offset by performance degradation due to shared resources, such as main memory. To efficiently use multi-core platforms for real-time systems, it is hence essential to tightly bound the interference when accessing shared resources. Although there has been much recent work in this area, a remaining key problem is to address the diversity of memory arbiters in the analysis to make it applicable to a wide range of systems. This work handles diverse arbiters by proposing a general framework to compute the maximum interference caused by the shared memory bus and its impact on the execution time of the tasks running on the cores, considering different bus arbiters. Our novel approach clearly demarcates the arbiter-dependent and independent stages in the analysis of these upper bounds. The arbiter-dependent phase takes the arbiter and the task memory-traffic pattern as inputs and produces a model of the availability of the bus to a given task. Then, based on the availability of the bus, the arbiter-independent phase determines the worst-case request-release scenario that maximizes the interference experienced by the tasks due to the contention for the bus. We show that the framework addresses the diversity problem by applying it to a memory bus shared by a fixed-priority arbiter, a time-division multiplexing (TDM) arbiter, and an unspecified work-conserving arbiter using applications from the MediaBench test suite. We also experimentally evaluate the quality of the analysis by comparison with a state-of-the-art TDM analysis approach and consistently showing a considerable reduction in maximum interference.