36 resultados para DGGE microbial identification
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Dissertação para a obtenção do grau de doutor em Biologia pelo Instituto de Tecnologia Química e Biológica. Universidade Nova de Lisboa.
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Dissertação para obtenção do Grau de Mestre em Engenharia Química e Bioquímica
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Dissertation presented to obtain the Ph.D degree in Biology
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Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores
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Dissertation presented to obtain the Ph.D degree in Biochemistry
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Dissertation presented to obtain the Ph.D degree in Biology
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Doctoral dissertation for Ph.D. degree in Sustainable Chemistry
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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Finance from the NOVA – School of Business and Economics
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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics
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Dissertation to obtain the degree of Master in Chemical and Biochemical Engineering
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Dissertação para obtenção do Grau de Doutor em Engenharia Química e Bioquímica
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Dissertação para obtenção do Grau de Doutor em Engenharia Química e Bioquímica
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Mesoamerican cultures had a strong tradition of written and pictorial manuscripts, called the codices. In studies already performed it was found the use of Maya Blue, made from a mixture of indigo and a clay called palygorskite, forming an incredibly stable material where the dye is trapped inside the nanotubes of the clay, after heating. However, a bigger challenge lies in the study of the yellows used, for these civilizations might have used this clay-dye mixture to produce their yellow colorants. As a first step, it was possible to provide identification, by non-invasive methods, of two colorants (a flavonoid and a carotenoid). While the flavonoid absorbed between 368-379 nm, the carotenoid would absorb around 455 nm. A temperature study also conducted allowed to set 140ºC as the desirable temperature to heat the samples without degrading them. FT-IR, conventional Raman and SERS allowed us to understand the existence of a reaction between the dyes and the clays (palygorskite and kaolinite), however it is difficult to understand it in a molecular point of view. As a second step, five species of Mexican dyes were selected on the basis of historical sources. The Maya yellow samples were produced adapting the recipe proposed by Reyes-Valerio, supporting the yellow dyes extracted from the dried plants on the clays, with addition of water, and then heated at 140ºC. It was found that the addition of water in palygorskite would increase the pH, hence deprotonating the molecules having a clear negative effect in the color. A second recipe was developed, without the addition of water; however, it was found that the use of water based binders would still alter the color of the samples with palygorskite. In this case, kaolinite without heating yield better results as a Maya yellow hybrid. It was found that the Maya chemistry might not have been the same for all the colors. The Mesoamericans might have found that different dyes could work better to their desires if matched with different clays. It was noticeable that for a clear distinction between flavonoids and carotenoids the reflectance and emission studies suffice, but when clay is added, Raman techniques will perform better. For this reason, conventional Raman and SERS were employed in order to create a database for the Mesoamerican dyestuffs for a future identification.
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Nowadays, reducing energy consumption is one of the highest priorities and biggest challenges faced worldwide and in particular in the industrial sector. Given the increasing trend of consumption and the current economical crisis, identifying cost reductions on the most energy-intensive sectors has become one of the main concerns among companies and researchers. Particularly in industrial environments, energy consumption is affected by several factors, namely production factors(e.g. equipments), human (e.g. operators experience), environmental (e.g. temperature), among others, which influence the way of how energy is used across the plant. Therefore, several approaches for identifying consumption causes have been suggested and discussed. However, the existing methods only provide guidelines for energy consumption and have shown difficulties in explaining certain energy consumption patterns due to the lack of structure to incorporate context influence, hence are not able to track down the causes of consumption to a process level, where optimization measures can actually take place. This dissertation proposes a new approach to tackle this issue, by on-line estimation of context-based energy consumption models, which are able to map operating context to consumption patterns. Context identification is performed by regression tree algorithms. Energy consumption estimation is achieved by means of a multi-model architecture using multiple RLS algorithms, locally estimated for each operating context. Lastly, the proposed approach is applied to a real cement plant grinding circuit. Experimental results prove the viability of the overall system, regarding both automatic context identification and energy consumption estimation.
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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.