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

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.

Prevalence of Trypanosoma cruzi and Leishmania chagasi infection and risk factors in a Colombian indigenous population

This study was carried out in order to obtain base-line data concerning the epidemiology of American Visceral Leishmaniasis and Chagas’ Disease in an indigenous population with whom the government is starting a dwelling improvement programme. Information was collected from 242 dwellings (1,440 people), by means of house to house interviews about socio-economic and environmental factors associated with Leishmania chagasi and Trypanosoma cruzi transmission risk. A leishmanin skin test was applied to 385 people and 454 blood samples were collected on filter paper in order to detect L. chagasi antibodies by ELISA and IFAT and T. cruzi antibodies by ELISA. T. cruzi seroprevalence was 8.7% by ELISA, L. chagasi was 4.6% and 5.1% by IFAT and ELISA, respectively. ELISA sensitivity and specificity for L. chagasi antibodies were 57% and 97.5% respectively, as compared to the IFAT. Leishmanin skin test positivity was 19%. L. chagasi infection prevalence, being defined as a positive result in the three-immunodiagnostic tests, was 17.1%. Additionally, 2.7% of the population studied was positive to both L. chagasi and T. cruzi, showing a possible cross-reaction. L. chagasi and T. cruzi seropositivity increased with age, while no association with gender was observed. Age (p<0.007), number of inhabitants (p<0.05), floor material (p<0.03) and recognition of vector (p<0.01) were associated with T. cruzi infection, whilst age ( p<0.007) and dwelling improvement (p<0.02) were associated with L. chagasi infection. It is necessary to evaluate the long-term impact of the dwelling improvement programme on these parasitic infections in this community.

Expatriates’ influence on knowledge sharing: an empirical study with International portuguese companies

Despite the abundant literature in knowledge management, few empirical studies have explored knowledge management in connection with international assignees. This phenomenon has a special relevance in the Portuguese context, since (a) there are no empirical studies concerning this issue that involves international Portuguese companies; (b) the national business reality is incipient as far as internationalisation is concerned, and; (c) the organisational and national culture presents characteristics that are distinctive from the most highly studied contexts (e.g., Asia, USA, Scandinavian countries, Spain, France, The Netherlands, Germany, England and Russia). We examine the role of expatriates in transfer and knowledge sharing within the Portuguese companies with operations abroad. We focus specifically on expatriates’ role on knowledge sharing connected to international Portuguese companies and our findings take into account organizational representatives’ and expatriates’ perspectives. Using a comparative case study approach, we examine how three main dimensions influence the role of expatriates in knowledge sharing among headquarters and their subsidiaries (types of international assignment, reasons for using expatriation and international assignment characteristics). Data were collected using semi‐structured interviews to 30 Portuguese repatriates and 14 organizational representatives from seven Portuguese companies. The findings suggest that the reasons that lead Portuguese companies to expatriating employees are connected to: (1) business expansion needs; (2) control of international operations and; (3) transfer and knowledge sharing. Our study also shows that Portuguese companies use international assignments in order to positively respond to the increasingly decaying domestic market in the economic areas in which they operate. Evidence also reveals that expatriation is seen as a strategy to fulfill main organizational objectives through their expatriates (e.g., business internationalization, improvement of the coordination and control level of the units/subsidiaries abroad, replication of aspects of the home base, development and incorporation of new organizational techniques and processes). We also conclude that Portuguese companies have developed an International Human Resources Management strategy, based on an ethnocentric approach, typically associated with companies in early stages of internationalization, i.e., the authority and decision making are centered in the home base. Expatriates have a central role in transmitting culture and technical knowledge from company’s headquarters to the company’s branches. Based on the findings, the article will discuss in detail the main theoretical and managerial implications. Suggestions for further research will also be presented.

Satisfaction towards human resources practices and repatriates’ retention: an empirical examination in the portuguese companies context

This paper examines the relationship between the level of satisfaction towards Human Resources Management practices among repatriates and the decision to remain on the home company after expatriation. Data was collected through semi-structured interviews of 28 Portuguese repatriates who remain and 16 organisational representatives from eight companies located in Portugal. The results show that (1) compensation system during the international assignment; (2) permanent support during the international assignment and; (3) recognition upon the return of the work and effort of expatriates during the international assignment are the most important HRM practices for promoting satisfaction among repatriates. Moreover, it is at repatriation phase that repatriates show higher dissatisfaction with HRM support. These findings will be discussed in detail and implications and suggestions for future research will be proposed as well.

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

Exploring why portuguese companies expatriate, and portuguese expatriates accept international assignments

This study explores (1) the reasons that lead Portuguese companies to use expatriates and (2) the motivations that led the repatriates to accepting an international assignment. Semistructured interviews were carried out on 44 individuals (14 responsible for organizational management of the expatriates and 30 repatriates), in seven international companies based in Portugal, and analysis of the thematic content was conducted for data processing. Results suggest that the reasons that lead Portuguese companies to expatriating employees are connected to business needs and the control of international operations, while individual motivations are linked to personal and professional ambition, the will to serve the company and organizational pressure. We concluded that Portuguese companies, like most European companies, seem to develop a strategy of International Human Resources Management (IHRM) according to an ethnocentric approach, characteristic to companies in early stages of internationalization. Similarly, the main motivations of Portuguese repatriates are identical to those of other expatriates, though the will to serve the company seems to be more valued by Portuguese repatriates than by expatriates from other countries.

Financiamento e Desempenho Organizacional: estudos de caso em ONGD Portuguesas

Dissertação de Mestrado em Gestão e Internacionalização de Empresas