Algorithm for the Parkinson’s disease behavioural models characterization using a biosensor

Dissertação para obtenção do Grau de Mestre em Engenharia Biomédica

Botnet cluster identification

Botnets are a group of computers infected with a specific sub-set of a malware family and controlled by one individual, called botmaster. This kind of networks are used not only, but also for virtual extorsion, spam campaigns and identity theft. They implement different types of evasion techniques that make it harder for one to group and detect botnet traffic. This thesis introduces one methodology, called CONDENSER, that outputs clusters through a self-organizing map and that identify domain names generated by an unknown pseudo-random seed that is known by the botnet herder(s). Aditionally DNS Crawler is proposed, this system saves historic DNS data for fast-flux and double fastflux detection, and is used to identify live C&Cs IPs used by real botnets. A program, called CHEWER, was developed to automate the calculation of the SVM parameters and features that better perform against the available domain names associated with DGAs. CONDENSER and DNS Crawler were developed with scalability in mind so the detection of fast-flux and double fast-flux networks become faster. We used a SVM for the DGA classififer, selecting a total of 11 attributes and achieving a Precision of 77,9% and a F-Measure of 83,2%. The feature selection method identified the 3 most significant attributes of the total set of attributes. For clustering, a Self-Organizing Map was used on a total of 81 attributes. The conclusions of this thesis were accepted in Botconf through a submited article. Botconf is known conferênce for research, mitigation and discovery of botnets tailled for the industry, where is presented current work and research. This conference is known for having security and anti-virus companies, law enforcement agencies and researchers.

Análise comparada da classificação “pixel a pixel” e orientada por objecto de uma imagem WorldView 2 de Maputo, Moçambique

O desenvolvimento das tecnologias associadas à Detecção Remota e aos Sistemas de Informação Geográfica encontram-se cada vez mais na ordem do dia. E, graças a este desenvolvimento de métodos para acelerar a produção de informação geográfica, assiste-se a um crescente aumento da resolução geométrica, espectral e radiométrica das imagens, e simultaneamente, ao aparecimento de novas aplicações com o intuito de facilitar o processamento e a análise de imagens através da melhoria de algoritmos para extracção de informação. Resultado disso são as imagens de alta resolução, provenientes do satélite WorldView 2 e o mais recente software Envi 5.0, utilizados neste estudo. O presente trabalho tem como principal objectivo desenvolver um projecto de cartografia de uso do solo para a cidade de Maputo, com recurso ao tratamento e à exploração de uma imagem de alta resolução, comparando as potencialidades e limitações dos resultados extraídos através da classificação “pixel a pixel”, através do algoritmo Máxima Verossimilhança, face às potencialidades e eventuais limitações da classificação orientada por objecto, através dos algoritmos K Nearest Neighbor (KNN) e Support Vector Machine (SVM), na extracção do mesmo número e tipo de classes de ocupação/uso do solo. Na classificação “pixel a pixel”, com a aplicação do algoritmo classificação Máxima Verosimilhança, foram ensaiados dois tipos de amostra: uma primeira constituída por 20 classes de ocupação/uso do solo, e uma segunda por 18 classes. Após a fase de experimentação, os resultados obtidos com a primeira amostra ficaram aquém das espectativas, pois observavam-se muitos erros de classificação. A segunda amostra formulada com base nestes erros de classificação e com o objectivo de os minimizar, permitiu obter um resultado próximo das espectativas idealizadas inicialmente, onde as classes de interesse coincidem com a realidade geográfica da cidade de Maputo. Na classificação orientada por objecto foram 4 as etapas metodológicas utilizadas: a atribuição do valor 5 para a segmentação e 90 para a fusão de segmentos; a selecção de 15 exemplos sobre os segmentos gerados para cada classe de interesse; bandas diferentemente distribuídas para o cálculo dos atributos espectrais e de textura; os atributos de forma Elongation e Form Factor e a aplicação dos algoritmos KNN e SVM. Confrontando as imagens resultantes das duas abordagens aplicadas, verificou-se que a qualidade do mapa produzido pela classificação “pixel a pixel” apresenta um nível de detalhe superior aos mapas resultantes da classificação orientada por objecto. Esta diferença de nível de detalhe é justificada pela unidade mínima do processamento de cada classificador: enquanto que na primeira abordagem a unidade mínima é o pixel, traduzinho uma maior detalhe, a segunda abordagem utiliza um conjunto de pixels, objecto, como unidade mínima despoletando situações de generalização. De um modo geral, a extracção da forma dos elementos e a distribuição das classes de interesse correspondem à realidade geográfica em si e, os resultados são bons face ao que é frequente em processamento semiautomático.

Métodos de aprendizagem automática: um estudo baseado na avaliação e previsão de clientes bancários

Data Mining surge, hoje em dia, como uma ferramenta importante e crucial para o sucesso de um negócio. O considerável volume de dados que atualmente se encontra disponível, por si só, não traz valor acrescentado. No entanto, as ferramentas de Data Mining, capazes de transformar dados e mais dados em conhecimento, vêm colmatar esta lacuna, constituindo, assim, um trunfo que ninguém quer perder. O presente trabalho foca-se na utilização das técnicas de Data Mining no âmbito da atividade bancária, mais concretamente na sua atividade de telemarketing. Neste trabalho são aplicados catorze algoritmos a uma base de dados proveniente do call center de um banco português, resultante de uma campanha para a angariação de clientes para depósitos a prazo com taxas de juro favoráveis. Os catorze algoritmos aplicados no caso prático deste projeto podem ser agrupados em sete grupos: Árvores de Decisão, Redes Neuronais, Support Vector Machine, Voted Perceptron, métodos Ensemble, aprendizagem Bayesiana e Regressões. De forma a beneficiar, ainda mais, do que a área de Data Mining tem para oferecer, este trabalho incide ainda sobre o redimensionamento da base de dados em questão, através da aplicação de duas estratégias de seleção de atributos: Best First e Genetic Search. Um dos objetivos deste trabalho prende-se com a comparação dos resultados obtidos com os resultados presentes no estudo dos autores Sérgio Moro, Raul Laureano e Paulo Cortez (Sérgio Moro, Laureano, & Cortez, 2011). Adicionalmente, pretende-se identificar as variáveis mais relevantes aquando da identificação do potencial cliente deste produto financeiro. Como principais conclusões, depreende-se que os resultados obtidos são comparáveis com os resultados publicados pelos autores mencionados, sendo os mesmos de qualidade e consistentes. O algoritmo Bagging é o que apresenta melhores resultados e a variável referente à duração da chamada telefónica é a que mais influencia o sucesso de campanhas similares.

MicroECG: an integrated platform for the cardiac arrythmia detection and characterization

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Engenharia Electrotécnica e Computadores

The use of analytical hierarchy process in spatial decision support system for land use management

Geographic information systems give us the possibility to analyze, produce, and edit geographic information. Furthermore, these systems fall short on the analysis and support of complex spatial problems. Therefore, when a spatial problem, like land use management, requires a multi-criteria perspective, multi-criteria decision analysis is placed into spatial decision support systems. The analytic hierarchy process is one of many multi-criteria decision analysis methods that can be used to support these complex problems. Using its capabilities we try to develop a spatial decision support system, to help land use management. Land use management can undertake a broad spectrum of spatial decision problems. The developed decision support system had to accept as input, various formats and types of data, raster or vector format, and the vector could be polygon line or point type. The support system was designed to perform its analysis for the Zambezi river Valley in Mozambique, the study area. The possible solutions for the emerging problems had to cover the entire region. This required the system to process large sets of data, and constantly adjust to new problems’ needs. The developed decision support system, is able to process thousands of alternatives using the analytical hierarchy process, and produce an output suitability map for the problems faced.

Land cover mapping analysis and urban growth modeling using remote sensing techniques

The rapid growth of big cities has been noticed since 1950s when the majority of world population turned to live in urban areas rather than villages, seeking better job opportunities and higher quality of services and lifestyle circumstances. This demographic transition from rural to urban is expected to have a continuous increase. Governments, especially in less developed countries, are going to face more challenges in different sectors, raising the essence of understanding the spatial pattern of the growth for an effective urban planning. The study aimed to detect, analyse and model the urban growth in Greater Cairo Region (GCR) as one of the fast growing mega cities in the world using remote sensing data. Knowing the current and estimated urbanization situation in GCR will help decision makers in Egypt to adjust their plans and develop new ones. These plans should focus on resources reallocation to overcome the problems arising in the future and to achieve a sustainable development of urban areas, especially after the high percentage of illegal settlements which took place in the last decades. The study focused on a period of 30 years; from 1984 to 2014, and the major transitions to urban were modelled to predict the future scenarios in 2025. Three satellite images of different time stamps (1984, 2003 and 2014) were classified using Support Vector Machines (SVM) classifier, then the land cover changes were detected by applying a high level mapping technique. Later the results were analyzed for higher accurate estimations of the urban growth in the future in 2025 using Land Change Modeler (LCM) embedded in IDRISI software. Moreover, the spatial and temporal urban growth patterns were analyzed using statistical metrics developed in FRAGSTATS software. The study resulted in an overall classification accuracy of 96%, 97.3% and 96.3% for 1984, 2003 and 2014’s map, respectively. Between 1984 and 2003, 19 179 hectares of vegetation and 21 417 hectares of desert changed to urban, while from 2003 to 2014, the transitions to urban from both land cover classes were found to be 16 486 and 31 045 hectares, respectively. The model results indicated that 14% of the vegetation and 4% of the desert in 2014 will turn into urban in 2025, representing 16 512 and 24 687 hectares, respectively.

Urban land use change analysis and modelling: a case study of Setubal-Sesimbra, Portugal

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

An overview of the higher level classification of Pucciniomycotina based on combined analyses of nuclear large and small subunit rDNA sequences

Mycologia, Vol. 98, nº6

ECG wave detector and delineation with wavelets

Proceedings of the International Conference on Computational Intelligence in Medicine Healthcare, CIMED 2005, Costa da Caparica, June 29 - July 1, 2005

Developing and validating a measure of the strength of the HRM system: Operationalizing the construct and relationships among its dimensions

The four studies in this article introduce a questionnaire to measure Strength of the HRM System (HRMSQ), a multidimensional construct, theoretically developed by Bowen and Ostroff (2004). Strength of the HRM System is a set of process characteristics that lead to effectiveness in conveying signals to employees that allow them to create a shared meaning of desired and appropriate work behaviours. Nine characteristics are suggested, grouped in three features: Distinctiveness, Consistency and Consensus. Study 1 developed and tested a questionnaire in a sample of workers from five different sectors. Study 2 cross-validated the measure in a sample of civil servants in a municipality. These two studies used performance appraisal as the reference HRM practice and led to a short version of the HRMSQ. Study 3 and Study 4 extend the HRMSQ to several common HRM practices. The HRMSQ is tested in two samples, of call center and several private and public organizations‟ workers (study 3). In study 4 the questionnaire is refined and tested with a sample from a hotel chain and finally cross-validated with two other samples, in the insurance and batteries sectors, leading to a longer version of the HRMSQ. Content analysis of several interviews with human resource managers and the Rasch model (1960, 1961, 1980), were used to define and select the indicators of the questionnaire. Convergent, discriminant and predictive validity of the measure are tested. The results of the four studies highlight the complexity of the relationships between the proposed characteristics and support the validity of a parsimonious measure of Strength of the HRM System.

Classificação de tumores de cancro na mama através de radar de banda ultra-larga de microondas

Dissertação para obtenção do Grau de Mestre em Engenharia Biomédica

Clearing the cloudy crystal balls: Hybrid modelling for energy and climate change mitigation scenarios – A case study for Portugal

Dissertação para obtenção do Grau de Doutor em Ambiente

Developing clinical trials in the portuguese family medicine : challenges and opportunities in the European context

RESUMO: Introdução: A hipótese colocada nesta tese é a de que poderia haver um número bastante mais elevado de ensaios clínicos na medicina familiar portuguesa se os obstáculos fossem removidos e as oportunidades exploradas de modo adequado. Contexto: Em Portugal existe uma nova geração de Médicos de Família que está a assumir postos de trabalho um pouco por todo o país e que é aceite como sendo a mais bem preparada geração de sempre. Métodos: Busca na MEDLINE. Leitura de artigos na única publicação científica dedicada à Medicina Geral e Familiar – RPMGF. Consulta em livros portugueses de política da saúde e acerca do Plano Nacional de Saúde. O INFARMED foi contactado e relatórios seus sobre ensaios clínicos foram analisados. Os Médicos de Família portugueses foram contactados e convidados a responder a questionários. Além disso, quinze personalidades da Medicina Portuguesa foram chamadas a sugerir soluções. Resultados: De acordo com dados do INFARMED, de 2006 a 2011 houve apenas quatro centros de saúde envolvidos em ensaios clínicos. Em Portugal: Existe um número pouco significativo de ensaios académicos; Praticamente não há infraestruturas de suporte ou treino; Os registos clínicos eletrónicos são usados de forma ineficiente; a investigação é fracamente ligada às carreiras médicas; há isolamento interno e externo; a já complexa regulamentação da União Europeia é complicada ainda mais; há um subfinanciamento da Investigação Clínica. Os Médicos de Família portugueses estão disponíveis para participar ativamente numa mudança. Discussão: Com os presentes resultados o diagnóstico para a presente situação é claramente negativo. Felizmente existem muito boas oportunidades para melhorar. Conclusão/Recomendações: Tempo, dinheiro e apoio têm de ser fornecidos aos Médicos de Família portugueses. É nesse sentido que são fornecidas vinte recomendações para obter uma verdadeira mudança no panorama dos Ensaios Clínicos na Medicina Familiar portuguesa.-------------ABSTRACT: Introduction: The hypothesis of this thesis is that there could be a much greater number of Clinical Trials in Portuguese Family Medicine if obstacles were removed and opportunities explored properly. Background: In Portugal there is a new generation of Family Doctors that is assuming permanent positions all over the country and is accepted to be the most well prepared generation ever. Methods: Search on MEDLINE. Relevant articles were also identified in the only jornal dedicated to Portuguese Family Medicine, RPMGF. A search was made on Portuguese health policy textbooks and national health plan policy. INFARMED was also contacted and their reports about Clinical Trials were analysed. Portuguese Family Doctors themselves were contacted and invited to answer questionnaires. Besides that, fifteen key opinion leaders related to Portuguese Medicine were approached for solutions. Results: According to INFARMED data, from 2006 to 2011 there were only four health centres involved in clinical trials. In Portugal there is: A negligible number of academic trials; almost no support infrastructures or training; inefficiently used electronic health records; a research weakly linked to medical careers; an uninformed isolation internally and externally; an already complex European Union regulation that is compounded even more; Scarce funding for clinical research. Portuguese Family Doctors are keen to actively participate in a change. Discussion: With the present results the diagnosis for the current situation is clearly negative. Fortunately there are very good opportunities to improve. Conclusion/Recommendations: Time, money and support must be given to Portuguese Family Doctors. In this context, twenty recommendations are provided intending to promote a true change in Portuguese Family Medicine Clinical Trials panorama.

Analysis and visualization of energy use for university campus

The reduction of greenhouse gas emissions is one of the big global challenges for the next decades due to its severe impact on the atmosphere that leads to a change in the climate and other environmental factors. One of the main sources of greenhouse gas is energy consumption, therefore a number of initiatives and calls for awareness and sustainability in energy use are issued among different types of institutional and organizations. The European Council adopted in 2007 energy and climate change objectives for 20% improvement until 2020. All European countries are required to use energy with more efficiency. Several steps could be conducted for energy reduction: understanding the buildings behavior through time, revealing the factors that influence the consumption, applying the right measurement for reduction and sustainability, visualizing the hidden connection between our daily habits impacts on the natural world and promoting to more sustainable life. Researchers have suggested that feedback visualization can effectively encourage conservation with energy reduction rate of 18%. Furthermore, researchers have contributed to the identification process of a set of factors which are very likely to influence consumption. Such as occupancy level, occupants behavior, environmental conditions, building thermal envelope, climate zones, etc. Nowadays, the amount of energy consumption at the university campuses are huge and it needs great effort to meet the reduction requested by European Council as well as the cost reduction. Thus, the present study was performed on the university buildings as a use case to: a. Investigate the most dynamic influence factors on energy consumption in campus; b. Implement prediction model for electricity consumption using different techniques, such as the traditional regression way and the alternative machine learning techniques; and c. Assist energy management by providing a real time energy feedback and visualization in campus for more awareness and better decision making. This methodology is implemented to the use case of University Jaume I (UJI), located in Castellon, Spain.