Contributos para a eficácia do clustering usando o tagging social

Nos últimos anos temos vindo a assistir a uma mudança na forma como a informação é disponibilizada online. O surgimento da web para todos possibilitou a fácil edição, disponibilização e partilha da informação gerando um considerável aumento da mesma. Rapidamente surgiram sistemas que permitem a coleção e partilha dessa informação, que para além de possibilitarem a coleção dos recursos também permitem que os utilizadores a descrevam utilizando tags ou comentários. A organização automática dessa informação é um dos maiores desafios no contexto da web atual. Apesar de existirem vários algoritmos de clustering, o compromisso entre a eficácia (formação de grupos que fazem sentido) e a eficiência (execução em tempo aceitável) é difícil de encontrar. Neste sentido, esta investigação tem por problemática aferir se um sistema de agrupamento automático de documentos, melhora a sua eficácia quando se integra um sistema de classificação social. Analisámos e discutimos dois métodos baseados no algoritmo k-means para o clustering de documentos e que possibilitam a integração do tagging social nesse processo. O primeiro permite a integração das tags diretamente no Vector Space Model e o segundo propõe a integração das tags para a seleção das sementes iniciais. O primeiro método permite que as tags sejam pesadas em função da sua ocorrência no documento através do parâmetro Social Slider. Este método foi criado tendo por base um modelo de predição que sugere que, quando se utiliza a similaridade dos cossenos, documentos que partilham tags ficam mais próximos enquanto que, no caso de não partilharem, ficam mais distantes. O segundo método deu origem a um algoritmo que denominamos k-C. Este para além de permitir a seleção inicial das sementes através de uma rede de tags também altera a forma como os novos centróides em cada iteração são calculados. A alteração ao cálculo dos centróides teve em consideração uma reflexão sobre a utilização da distância euclidiana e similaridade dos cossenos no algoritmo de clustering k-means. No contexto da avaliação dos algoritmos foram propostos dois algoritmos, o algoritmo da “Ground truth automática” e o algoritmo MCI. O primeiro permite a deteção da estrutura dos dados, caso seja desconhecida, e o segundo é uma medida de avaliação interna baseada na similaridade dos cossenos entre o documento mais próximo de cada documento. A análise de resultados preliminares sugere que a utilização do primeiro método de integração das tags no VSM tem mais impacto no algoritmo k-means do que no algoritmo k-C. Além disso, os resultados obtidos evidenciam que não existe correlação entre a escolha do parâmetro SS e a qualidade dos clusters. Neste sentido, os restantes testes foram conduzidos utilizando apenas o algoritmo k-C (sem integração de tags no VSM), sendo que os resultados obtidos indicam que a utilização deste algoritmo tende a gerar clusters mais eficazes.

Psycho-physio dynamics in violin-piano duo: a pianist's perspective

The case study looked at psychological and physiological responses to stress in musicians, comparing a newly formed and a consolidated violin-piano duo. The common element between these duos was the pianist. Using the psychological tests (STAI Y1 and Y2, K-MPAI, MMPI-2, ICAC), the immunoassay saliva test to measure cortisol (stress hormone) and non- invasive device VitalJacket® developed at the University of Aveiro, Portugal, participants were monitored under various performance conditions. Others quantitative and qualitative dataset were collected including a pianist’s personal diary (analyzed by psychiatrist), semi-structured interviews with members of long-terms chamber music duo and perceptual evaluations (listening test) of the performances by expert listeners. The variables included two performance venues (European university and secondary school), as well as well-known repertoire, recently known repertoire and newly known repertoire. The latter was given approximately one week before each recital. The psychological and physiological dataset were collected for a total of eight recitals – two series of four recitals each. The unexpected results show that state anxiety levels and stress of the pianist, who does not present an anxious profile, either in social or in musical terms, are always higher when playing with a well-known partner. Possible explanations may be due to the highest expectations for quality of performance and implications of mirror neurons (since the reactions are very different according to the partner). In other words, the “known” (i.e., the consolidated duo) can become “trapped” within a predetermined space, especially at the psychological level, while the “unknown” (the occasional duo) seems to be less involved and therefore more reassuring and exciting in positive terms. In addition, the preference of the expert audience is for the consolidated duo.

Management and Control of Water Supply Systems

The fast increase in the energy’s price has brought a growing concern about the highly expensive task of transporting water. By creating an hydraulic model of the Water Supply System’s (WSS) network and predicting its behaviour, it is possible to take advantage of the energy’s tariffs, reducing the total cost on pumping activities. This thesis was developed, in association with a technology transfer project called the E-Pumping. It focuses on finding a flexible supervision and control strategy, adaptable to any existent Water Supply System (WSS), as well as forecasting the water demand on a time period chosen by the end user, so that the pumping actions could be planned to an optimum schedule, that minimizes the total operational cost. The OPC protocol, associated to a MySQL database were used to develop a flexible tool of supervision and control, due to their adaptability to function with equipments from various manufacturers, being another integrated modular part of the E-Pumping project. Furthermore, in this thesis, through the study and performance tests of several statistical models based on time series, specifically applied to this problem, a forecasting tool adaptable to any station, and whose model parameters are automatically refreshed at runtime, was developed and added to the project as another module. Both the aforementioned modules were later integrated with an Graphical User Interface (GUI) and installed in a pilot application at the ADDP’s network. The implementation of this software on WSSs across the country will reduce the water supply companies’ running costs, improving their market competition and, ultimately, lowering the water price to the end costumer.

Describing vocal performance of Portuguese cantadeiras of Alto Minho

Portugal has strong musical traditions, which have been perpetrated by decades through folkloristic activities. In folk groups from Alto Minho (north of Portugal), folk singing is mostly performed by cantadeiras, amateur female solo singers who learn this style orally. Their vocal characteristics are distinctive when compared with other regions of the country; however, deep understanding of these vocal practices is still missing. The present work aims at studying Alto Minho cantadeira’s vocal performance in a multidimensional perspective, envisioning social, cultural and physiological understanding of this musical style. Thus, qualitative and quantitative data analyses were carried out, to: (i) describe current performance practices, (ii) explore existent perceptions about most relevant voice features in this region, (iii) investigate physiological and acoustic properties of this style, and (iv) compare this style of singing with other non-classical singing styles of other countries. Dataset gathered involved: 78 groups whose members were telephone interviewed, 13 directors who were asked to fill in a questionnaire on performance practices, 1 cantadeira in a pilot study, 16 cantadeiras in preliminary voice recordings, 77 folk group members in listening tests, and 10 cantadeiras in multichannel recordings, including audio, ELG, air flow and intra-oral pressure signals. Data were analysed through thematic content analysis, descriptive and inferential statistics, hierarchical principal components, and multivariate linear regression models. Most representative voices have a high pitched and loud voice, with a bright timbre, predominance of chest register without excessive effort, and good text intelligibility with regional accent. High representativeness levels were obtained by few cantadeiras; these sing with high levels of subglottal pressure and vocal fold contact quotient, predominance of high spectrum energy and vocal loudness, corroborating indications of prevalence of pressed phonation. These vocal characteristics resemble belting in musical theatre and share similarities with country (USA) and ojikanje (Croatia) singing. Strategies that may contribute to the preservation of this type of singing and the vocal health of current cantadeiras are discussed, pointing at the direction of continuous education among folk groups, following practices that are already adopted elsewhere in Europe.

Decentralizing IP mobility management in future networks

The massive adoption of sophisticated mobile devices and applications led to the increase of mobile data in the last decade, which it is expected to continue. This increase of mobile data negatively impacts the network planning and dimension, since core networks are heavy centralized. Mobile operators are investigating atten network architectures that distribute the responsibility of providing connectivity and mobility, in order to improve the network scalability and performance. Moreover, service providers are moving the content servers closer to the user, in order to ensure high availability and performance of content delivery. Besides the e orts to overcome the explosion of mobile data, current mobility management models are heavy centralized to ensure reachability and session continuity to the users connected to the network. Nowadays, deployed architectures have a small number of centralized mobility anchors managing the mobile data and the mobility context of millions of users, which introduces issues related to performance and scalability that require costly network mechanisms. The mobility management needs to be rethought out-of-the box to cope with atten network architectures and distributed content servers closer to the user, which is the purpose of the work developed in this Thesis. The Thesis starts with a characterization of mobility management into well-de ned functional blocks, their interaction and potential grouping. The decentralized mobility management is studied through analytical models and simulations, in which di erent mobility approaches distinctly distribute the mobility management functionalities through the network. The outcome of this study showed that decentralized mobility management brings advantages. Hence, it was proposed a novel distributed and dynamic mobility management approach, which is exhaustively evaluated through analytical models, simulations and testbed experiments. The proposed approach is also integrated with seamless horizontal handover mechanisms, as well as evaluated in vehicular environments. The mobility mechanisms are also speci ed for multihomed scenarios, in order to provide data o oading with IP mobility from cellular to other access networks. In the pursuing of the optimized mobile routing path, a novel network-based strategy for localized mobility is addressed, in which a replication binding system is deployed in the mobility anchors distributed through the access routers and gateways. Finally, we go further in the mobility anchoring subject, presenting a context-aware adaptive IP mobility anchoring model that dynamically assigns the mobility anchors that provide the optimized routing path to a session, based on the user and network context. The integration of dynamic and distributed concepts in the mobility management, such as context-aware adaptive mobility anchoring and dynamic mobility support, allow the optimization of network resources and the improvement of user experience. The overall outcome demonstrates that decentralized mobility management is a promising direction, hence, its ideas should be taken into account by mobile operators in the deployment of future networks.

Development of infrared spectroscopy for assessing bacterial quality in foods

Rapid and specific detection of foodborne bacteria that can cause food spoilage or illness associated to its consumption is an increasingly important task in food industry. Bacterial detection, identification, and classification are generally performed using traditional methods based on biochemical or serological tests and the molecular methods based on DNA or RNA fingerprints. However, these methodologies are expensive, time consuming and laborious. Infrared spectroscopy is a reliable, rapid, and economic technique which could be explored as a tool for bacterial analysis in the food industry. In this thesis it was evaluated the potential of IR spectroscopy to study the bacterial quality of foods. In Chapter 2, it was developed a calibration model that successfully allowed to predict the bacterial concentration of naturally contaminated cooked ham samples kept at refrigeration temperature during 8 days. In this part, it was developed the methodology that allowed the best reproducibility of spectra from bacteria colonies with minimal sample preparation, which was used in the subsequent work. Several attempts trying different resolutions and number of scans in the IR were made. A spectral resolution of 4 cm-1, with 32 scans were the settings that allowed the best results. Subsequently, in Chapter 3, it was made an attempt to identify 22 different foodborne bacterial genera/species using IR spectroscopy coupled with multivariate analysis. The principal component analysis, used as an exploratory technique, allowed to form distinct groups, each one corresponding to a different genus, in most of the cases. Then, a hierarchical cluster analysis was performed to further analyse the group formation and the possibility of distinction between species of the same bacterial genus. It was observed that IR spectroscopy not only is suitable to the distinction of the different genera, but also to differentiate species of the same genus, with the simultaneous use of principal component analysis and cluster analysis techniques. The utilization of IR spectroscopy and multivariate statistical analysis were also investigated in Chapter 4, in order to confirm the presence of Listeria monocytogenes and Salmonella spp. isolated from contaminated foods, after growth in selective medium. This would allow to substitute the traditional biochemical and serological methods that are used to confirm these pathogens and that delay the obtainment of the results up to 2 days. The obtained results allowed the distinction of 3 different Listeria species and the distinction of Salmonella spp. from other bacteria that can be mistaken with them. Finally, in chapter 5, high pressure processing, an emerging methodology that permits to produce microbiologically safe foods and extend their shelf-life, was applied to 12 foodborne bacteria to determine their resistance and the effects of pressure in cells. A treatment of 300 MPa, during 15 minutes at room temperature was applied. Gram-negative bacteria were inactivated to undetectable levels and Gram-positive showed different resistances. Bacillus cereus and Staphylococcus aureus decreased only 2 logs and Listeria innocua decreased about 5 logs. IR spectroscopy was performed in bacterial colonies before and after HPP in order to investigate the alterations of the cellular compounds. It was found that high pressure alters bands assigned to some cellular components as proteins, lipids, oligopolysaccharides, phosphate groups from the cell wall and nucleic acids, suggesting disruption of the cell envelopes. In this work, bacterial quantification and classification, as well as assessment of cellular compounds modification with high pressure processing were successfully performed. Taking this into account, it was showed that IR spectroscopy is a very promising technique to analyse bacteria in a simple and inexpensive manner.

Infection mechanism of Diplodia corticola

Diplodia corticola is regarded as the most virulent fungus involved in cork oak decline, being able to infect not only Quercus species (mainly Q. suber and Q. ilex), but also grapevines (Vitis vinifera) and eucalypts (Eucalyptus sp.). This endophytic fungus is also a pathogen whose virulence usually manifests with the onset of plant stress. Considering that the infection normally culminates in host death, there is a growing ecologic and socio-economic concern about D. corticola propagation. The molecular mechanisms of infection are hitherto largely unknown. Accordingly, the aim of this study was to unveil potential virulence effectors implicated in D. corticola infection. This knowledge is fundamental to outline the molecular framework that permits the fungal invasion and proliferation in plant hosts, causing disease. Since the effectors deployed are mostly proteins, we adopted a proteomic approach. We performed in planta pathogenicity tests to select two D. corticola strains with distinct virulence degrees for our studies. Like other filamentous fungi D. corticola secretes protein at low concentrations in vitro in the presence of high levels of polysaccharides, two characteristics that hamper the fungal secretome analysis. Therefore, we first compared several methods of extracellular protein extraction to assess their performance and compatibility with 1D and 2D electrophoretic separation. TCA-Acetone and TCA-phenol protein precipitation were the most efficient methods and the former was adopted for further studies. The proteins were extracted and separated by 2D-PAGE, proteins were digested with trypsin and the resulting peptides were further analysed by MS/MS. Their identification was performed by de novo sequencing and/or MASCOT search. We were able to identify 80 extracellular and 162 intracellular proteins, a milestone for the Botryosphaeriaceae family that contains only one member with the proteome characterized. We also performed an extensive comparative 2D gel analysis to highlight the differentially expressed proteins during the host mimicry. Moreover, we compared the protein profiles of the two strains with different degrees of virulence. In short, we characterized for the first time the secretome and proteome of D. corticola. The obtained results contribute to the elucidation of some aspects of the biology of the fungus. The avirulent strain contains an assortment of proteins that facilitate the adaptation to diverse substrates and the identified proteins suggest that the fungus degrades the host tissues through Fenton reactions. On the other hand, the virulent strain seems to have adapted its secretome to the host characteristics. Furthermore, the results indicate that this strain metabolizes aminobutyric acid, a molecule that might be the triggering factor of the transition from a latent to a pathogenic state. Lastly, the secretome includes potential pathogenicity effectors, such as deuterolysin (peptidase M35) and cerato-platanin, proteins that might play an active role in the phytopathogenic lifestyle of the fungus. Overall, our results suggest that D. corticola has a hemibiotrophic lifestyle, switching from a biotrophic to a necrotrophic interaction after plant physiologic disturbances.This understanding is essential for further development of effective plant protection measures.