28 resultados para Efficient dominating set
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Dissertação de mestrado integrado em Engenharia e Gestão Industrial
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Dissertação de mestrado integrado em Engenharia de Telecomunicações e Informática
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We demonstrate the first example of silicon nanowire array photocathodes coupled with hollow spheres of the emerging earth-abundant cobalt phosphide catalysts. Compared to bare silicon nanowire arrays, the hybrid electrodes exhibit significantly improved photoelectrochemical performance toward the solar-driven H2 evolution reaction.
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Dissertação de mestrado integrado em Engenharia Civil
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The Symbolic Aggregate Approximation (iSAX) is widely used in time series data mining. Its popularity arises from the fact that it largely reduces time series size, it is symbolic, allows lower bounding and is space efficient. However, it requires setting two parameters: the symbolic length and alphabet size, which limits the applicability of the technique. The optimal parameter values are highly application dependent. Typically, they are either set to a fixed value or experimentally probed for the best configuration. In this work we propose an approach to automatically estimate iSAX’s parameters. The approach – AutoiSAX – not only discovers the best parameter setting for each time series in the database, but also finds the alphabet size for each iSAX symbol within the same word. It is based on simple and intuitive ideas from time series complexity and statistics. The technique can be smoothly embedded in existing data mining tasks as an efficient sub-routine. We analyze its impact in visualization interpretability, classification accuracy and motif mining. Our contribution aims to make iSAX a more general approach as it evolves towards a parameter-free method.
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Dissertação de mestrado integrado em Engenharia Civil
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Dissertação de mestrado integrado em Engenharia Civil
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[Excerpt] Lignocellulosic plant biomass is being envisioned by biorefinery industry as an alternative to current petroleum platform because of the large scale availability, low cost and environmentally benign production. The industrial bioprocessing designed to transform lignocellulosic biomass into biofuels are harsh and the enzymatic reactions may be severely compromised reducing the production of fermentable sugars from lignocellulosic biomass. Thermophilic bacteria consortium are a potential source of cellulases and hemicellulases adapted to extreme environmental conditions, which can be exploited as a new source for the development of more robust enzymatic cocktails. (...)
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Recently, there has been a growing interest in the field of metabolomics, materialized by a remarkable growth in experimental techniques, available data and related biological applications. Indeed, techniques as Nuclear Magnetic Resonance, Gas or Liquid Chromatography, Mass Spectrometry, Infrared and UV-visible spectroscopies have provided extensive datasets that can help in tasks as biological and biomedical discovery, biotechnology and drug development. However, as it happens with other omics data, the analysis of metabolomics datasets provides multiple challenges, both in terms of methodologies and in the development of appropriate computational tools. Indeed, from the available software tools, none addresses the multiplicity of existing techniques and data analysis tasks. In this work, we make available a novel R package, named specmine, which provides a set of methods for metabolomics data analysis, including data loading in different formats, pre-processing, metabolite identification, univariate and multivariate data analysis, machine learning, and feature selection. Importantly, the implemented methods provide adequate support for the analysis of data from diverse experimental techniques, integrating a large set of functions from several R packages in a powerful, yet simple to use environment. The package, already available in CRAN, is accompanied by a web site where users can deposit datasets, scripts and analysis reports to be shared with the community, promoting the efficient sharing of metabolomics data analysis pipelines.
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Dissertação de mestrado em Educação Especial (área de especialização em Intervenção Precoce)
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PhD in Chemical and Biological Engineering
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Tese de Doutoramento em Engenharia Mecânica.
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The concepts involved in sustainable textile fashion, demanding good knowledge about raw materials, processes, end use properties and circuits amongst others, are able to determine the way the textile product is designed and the behavior of the consumer, regarding life style and buying decisions. The textile product`s life integrates raw materials, their processing, distribution, use by the consumer and destination of the product after useful lifetime, this is, his complete life cycle. It is very important to recognize the power of the consumer to influence parameters related to sustainability, namely when he decides how, when and why he buys and afterwards by the attitudes taken during and after use. The conscious act of consumption involves ethical, ecological and technical knowledge in which the concern is overall lifecycle of the fashion product and not exclusively aesthetic and symbolic values strongly related with its ephemeral nature. The present work proposes the classification of textile products by means of an innovative label aiming to establish a rating related to the Life of Fashion Products, by using parameters considered with especial impact in lifecycle, as textile fibers, processing conditions, generated wastes, commercialization circuits, durability and cleaning procedures. This label for sustainable fashion products aims to assist the stakeholders with informed attitudes and correct decisions in order to promote the objectives of sustainable fashion near designers, consumers and industrial experts.