A Data-mining-based Methodology to support MV Electricity Customers' Characterization

This paper presents an electricity medium voltage (MV) customer characterization framework supportedby knowledge discovery in database (KDD). The main idea is to identify typical load profiles (TLP) of MVconsumers and to develop a rule set for the automatic classification of new consumers. To achieve ourgoal a methodology is proposed consisting of several steps: data pre-processing; application of severalclustering algorithms to segment the daily load profiles; selection of the best partition, corresponding tothe best consumers’ segmentation, based on the assessments of several clustering validity indices; andfinally, a classification model is built based on the resulting clusters. To validate the proposed framework,a case study which includes a real database of MV consumers is performed.

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.

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

FETO-PLACENTARY PATHOLOGY IN HUMAN PARVOVIRUS B19 INFECTION

In view of the scarce references concerning the histological data in congenital parvovirus human B19 infection, we intend to provide a description of the pathological features observed in six autopsies.The virus was detected by DNA hybridization (ISH-DBH),PCR and electronmicroscopy (EM) in paraffin-embedded feto-placentary tissues.These cases constitute a subset from 86 Non Immunologic Hydrops Fetalis (NIHF) cases, in which a systemic complex of inflammatory/degenerative lesions of unknown etiology was visualized by optical microscopy. In one case a syphilitic process was detected, typefying a double infection. All fetuses showed a similar pathology - hydrops, hepato-splenomegaly, lung hypoplasia and erythroblastemia, the specific histological feature being the presence of intranuclear inclusions in the erythroid progenitors, in the erythropoietic visceral tissue and in blood marrow. Complex cardiopathy allied to abnormal lung lobulation and polisplenia were observed once; in 2 cases endocardial fibroelastosis was diagnosed. The pulmonary lesions were represented by dysmaturity allied to interstitial mononuclear infiltration. The hepatic consisted of cholestasis, portal fibrosis, canalicular proliferation, hemossiderosis, focal necroses and giant cell transformation. The central nervous system lesions were predominantly anoxic although the autolysis impaired a correct diagnosis.

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.

Paracoccidioides brasilienses isolates obtained from patients with acute and chronic disease exhibit morphological differences after animal passage

The basis for virulence in Paracoccidioides brasiliensis is not completely understood. There is a consensus that the sequencial in vitro subcultivation of P. brasiliensis leads to loss of its pathogenicity, which can be reverted by reisolation from animal passage. Attention to morphological and biochemical properties that are regained or demonstrated after animal passage may provide new insights into factors related to the pathogenicity and virulence of P. brasiliensis. We evaluated morphological characters: the percentage of budding cells, number of buds by cell and the diameter of 100 mother cells of yeast-like cells of 30 P. brasiliensis isolates, before and after animal passage. The isolates were obtained from patients with different clinical forms of paracoccidioidomycosis (PCM): acute form (group A, n=15) and chronic form (group C, n=15). The measurement of the yeast cell sizes was carried out with the aid of an Olympus CBB microscope coupled with a micrometer disc. We measured the major transverse and longitudinal axes of 100 viable cells of each preparation. The percentage of budding cells as also the number of buds by cell was not influenced by animal passage, regardless of the source of the strain (acute or chronic groups). The size values of P. brasiliensis isolates from groups A and C, measured before the animal passage exhibited the same behavior. After animal passage, there was a statistically significant difference between the cell sizes of P. brasiliensis isolates recovered from testicles inoculated with strains from groups A and C. The maximum diameter of mother cells from group A isolates exhibited a size of 42.1mm in contrast with 32.9mm exhibited by mother cells from group C (p<0.05). The diameter of 1500 mother cells from group A isolates exhibited a medium size of 16.0mm (SD ± 4.0), a value significantly higher than the 14.1mm (SD = ± 3.3) exhibited by 1500 mother cells from group C isolates (p<0.05). Our results reinforce the polymorphism exhibited by P. brasiliensis in biological material and the need for further investigations to elucidate the role of morphological parameters of the fungus in the natural history of the disease.

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

Deteção e extinção de incêndio em Data Center

O presente trabalho enquadra-se na temática de segurança contra incêndio em edifícios e consiste num estudo de caso de projeto de deteção e extinção de incêndio num Data Center. Os objetivos deste trabalho resumem-se à realização de um estudo sobre o estado da arte da extinção e deteção automática de incêndio, ao desenvolvimento de uma ferramenta de software de apoio a projetos de extinção por agentes gasosos, como também à realização de um estudo e uma análise da proteção contra incêndios em Data Centers. Por último foi efetuado um estudo de caso. São abordados os conceitos de fogo e de incêndio, em que um estudo teórico à temática foi desenvolvido, descrevendo de que forma pode o fogo ser originado e respetivas consequências. Os regulamentos nacionais relativos à Segurança Contra Incêndios em Edifícios (SCIE) são igualmente abordados, com especial foco nos Sistemas Automáticos de Deteção de Incêndio (SADI) e nos Sistemas Automáticos de Extinção de Incêndio (SAEI), as normas nacionais e internacionais relativas a esta temática também são mencionadas. Pelo facto de serem muito relevantes para o desenvolvimento deste trabalho, os sistemas de deteção de incêndio são exaustivamente abordados, mencionando características de equipamentos de deteção, técnicas mais utilizadas como também quais os aspetos a ter em consideração no dimensionamento de um SADI. Quanto aos meios de extinção de incêndio foram mencionados quais os mais utilizados atualmente, as suas vantagens e a que tipo de fogo se aplicam, com especial destaque para os SAEI com utilização de gases inertes, em que foi descrito como deve ser dimensionado um sistema deste tipo. Foi também efetuada a caracterização dos Data Centers para que seja possível entender quais as suas funcionalidades, a importância da sua existência e os aspetos gerais de uma proteção contra incêndio nestas instalações. Por último, um estudo de caso foi desenvolvido, um SADI foi projetado juntamente com um SAEI que utiliza azoto como gás de extinção. As escolhas e os sistemas escolhidos foram devidamente justificados, tendo em conta os regulamentos e normas em vigor.