An automatic tool to Extract, Transform and Load data from real electricity markets

The study of Electricity Markets operation has been gaining an increasing importance in the last years, as result of the new challenges that the restructuring produced. Currently, lots of information concerning Electricity Markets is available, as market operators provide, after a period of confidentiality, data regarding market proposals and transactions. These data can be used as source of knowledge, to define realistic scenarios, essential for understanding and forecast Electricity Markets behaviour. The development of tools able to extract, transform, store and dynamically update data, is of great importance to go a step further into the comprehension of Electricity Markets and the behaviour of the involved entities. In this paper we present an adaptable tool capable of downloading, parsing and storing data from market operators’ websites, assuring actualization and reliability of stored data.

Analysis of Consumption Data to Detect Commercial Losses Using Performance Evaluation Methods in a Smart Grid

Electric power networks, namely distribution networks, have been suffering several changes during the last years due to changes in the power systems operation, towards the implementation of smart grids. Several approaches to the operation of the resources have been introduced, as the case of demand response, making use of the new capabilities of the smart grids. In the initial levels of the smart grids implementation reduced amounts of data are generated, namely consumption data. The methodology proposed in the present paper makes use of demand response consumers’ performance evaluation methods to determine the expected consumption for a given consumer. Then, potential commercial losses are identified using monthly historic consumption data. Real consumption data is used in the case study to demonstrate the application of the proposed method.

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.

A study on parallel versus sequential relational fuzzy clustering methods

Dissertação para obtenção do Grau de Mestre em Engenharia Informática

Towards a unified European electricity market: The contribution of data-mining to support realistic simulation studies

Worldwide electricity markets have been evolving into regional and even continental scales. The aim at an efficient use of renewable based generation in places where it exceeds the local needs is one of the main reasons. A reference case of this evolution is the European Electricity Market, where countries are connected, and several regional markets were created, each one grouping several countries, and supporting transactions of huge amounts of electrical energy. The continuous transformations electricity markets have been experiencing over the years create the need to use simulation platforms to support operators, regulators, and involved players for understanding and dealing with this complex environment. This paper focuses on demonstrating the advantage that real electricity markets data has for the creation of realistic simulation scenarios, which allow the study of the impacts and implications that electricity markets transformations will bring to the participant countries. A case study using MASCEM (Multi-Agent System for Competitive Electricity Markets) is presented, with a scenario based on real data, simulating the European Electricity Market environment, and comparing its performance when using several different market mechanisms.

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.

Improving discovery in the life sciences using semantic Web technologies and linked data: design principles for life sciences knowledge organization systems

Dissertation presented to obtain the Ph.D degree in Bioinformatics

Declarative approach to data extraction of web pages

Thesis submitted to Faculdade de Ciências e Tecnologia of the Universidade Nova de Lisboa, in partial fulfilment of the requirements for the degree of Master in Computer Science

Exploring distributed computing tools through data mining tasks

Harnessing idle PCs CPU cycles, storage space and other resources of networked computers to collaborative are mainly fixated on for all major grid computing research projects. Most of the university computers labs are occupied with the high puissant desktop PC nowadays. It is plausible to notice that most of the time machines are lying idle or wasting their computing power without utilizing in felicitous ways. However, for intricate quandaries and for analyzing astronomically immense amounts of data, sizably voluminous computational resources are required. For such quandaries, one may run the analysis algorithms in very puissant and expensive computers, which reduces the number of users that can afford such data analysis tasks. Instead of utilizing single expensive machines, distributed computing systems, offers the possibility of utilizing a set of much less expensive machines to do the same task. BOINC and Condor projects have been prosperously utilized for solving authentic scientific research works around the world at a low cost. In this work the main goal is to explore both distributed computing to implement, Condor and BOINC, and utilize their potency to harness the ideal PCs resources for the academic researchers to utilize in their research work. In this thesis, Data mining tasks have been performed in implementation of several machine learning algorithms on the distributed computing environment.

Vibroacoustic disease II: The biological and acoustical basis of low frequency noise induced pathology

Proceedings Institute of Acoustics (UK); vol. 25, nº2, p. 72-78.

Implementação de um processo industrial de coloração de granito

O presente estágio foi desenvolvido na Britafiel. Um dos projectos em que a Empresa se encontra envolvida é o STOCO, pretendendo implementar à escala industrial um processo de coloração de pedra granítica natural para fins decorativos. Foi neste projecto que se enquadrou o estágio. O tema do estágio centra-se no processo de coloração de granito tendo como principal foco a implementação de um processo industrial de produção de granito colorido. O projecto STOCO nasce da necessidade de complementar a actividade da empresa com produtos de maior valor acrescentado para valorização da matéria-prima de base, o granito. STOCO, resultante de Stone Color, é o nome dado ao projecto e ao novo produto que é granito colorido, sob a forma de brita. Pretende-se obter um produto amigo do ambiente e com boas características: manter a textura natural da pedra granítica e assegurar uma boa resistência a factores agressivos. Estudos prévios de qualidade e de toxicidade mostraram que o produto STOCO desenvolvido até então apresenta um bom comportamento face a agressões climatéricas e que não compromete a vida das espécies usadas nos testes (peixes). Em relação aos lixiviados e resíduos da pedra colorida STOCO, estes não apresentaram qualquer problema ambiental, sendo considerado um produto amigo do ambiente. À data de início do presente trabalho estava em funcionamento um equipamento protótipo de produção de granito colorido (100 kg/partida), sendo a instalação e o arranque da unidade industrial (3 ton/h) concretizados no início de 2014, já no decorrer deste trabalho. Os objectivos cumpridos no âmbito deste trabalho foram então a implementação de uma linha industrial de produção de brita colorida, avaliação técnica do processo e do custo industrial de produção associado às matérias-primas. Neste relatório é descrito o processo inicial adoptado e apresentam-se as alterações efectuadas para melhoria do processo produtivo. Resolveram-se problemas como: definição e instalação de equipamentos complementares para a entrada e a saída da brita no equipamento industrial; pó excessivo na brita; cheiro intenso a gás e elevado ruído; adequação do sistema de pintura; e secagem incompleta da brita. Alguns destes problemas não foram totalmente resolvidos, mas sim minimizados. O equipamento industrial necessita ainda de alterações em diversas áreas, que foram identificadas e para as quais são feitas sugestões de melhoria. Conseguiu-se ainda fazer alguns testes para uma possível substituição de alguns constituintes da tinta. Os componentes que entram na composição base da tinta aquosa, são de modo simplificado: ligante, pigmento, solvente e aditivos. Os constituintes que mais encarecem a tinta, e consequentemente o processo em causa, são o ligante e o pigmento. Os estudos efectuados precisam de ser aprofundados, na tentativa de melhorar o processo minimizando os custos de produção. Formalizaram-se os procedimentos escritos de produção STOCO tanto para o protótipo como para o processo industrial e elaborou-se uma ficha técnica de produto para a brita colorida STOCO.

Caracterização da Exposição ao Ruído dos Trabalhadores da Indústria Portuguesa

Dissertação de Mestrado em Gestão Integrada da Qualidade, Ambiente e Segurança

Investigating habitat association of breeding birds using public domain satellite imagery and land cover data.

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

Is There Sufficient Training of Health Care Staff on Noise Reduction in Neonatal Intensive Care Units? a Pilot Study From NeoNoise Project

Evidence indicates that exposure to high levels of noise adversely affects human health, and these effects are dependent upon various factors. In hospitals, there are many sources of noise, and high levels exert an impact on patients and staff, increasing both recovery time and stress, respectively. The goal of this pilot study was to develop, implement and evaluate the effectiveness of a training program (TP) on noise reduction in a Neonatal Intensive Care Units (NICU) by comparing the noise levels before and after the implementation of the program. A total of 79 health professionals participated in the study. The measurements of sound pressure levels took into account the layout of the unit and location of the main sources of noise. General results indicated that LAeq levels before implementation of the training program were often excessive, ranging from 48.7 ± 2.94 dBA to 71.7 ± 4.74 dBA, exceeding international guidelines. Similarly following implementation of the training program noise levels remained unchanged (54.5 ± 0.49 dBA to 63.9 ± 4.37 dBA), despite a decrease in some locations. There was no significant difference before and after the implementation of TP. However a significant difference was found for Lp, Cpeak, before and after training staff, suggesting greater care by healthcare professionals performing their tasks. Even recognizing that a TP is quite important to change behaviors, this needs to be considered in a broader context to effectively control noise in the NICU.