999 resultados para semantic processing


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

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

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

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The main objective of this review is to provide a descriptive analysis of the biological and physiological markers of tactile sensorial processing in healthy, full-term newborns. Research articles were selected according to the following study design criteria: (a) tactile stimulation for touch sense as an independent variable; (b) having at least one biological or physiological variable as a dependent variable; and (c) the group of participants were characterized as full-term and healthy newborns; a mixed group of full-term newborns and preterm newborns; or premature newborns with appropriate-weight-for-gestational age and without clinical differences or considered to have a normal, healthy somatosensory system. Studies were then grouped according to the dependent variable type, and only those that met the aforementioned three major criteria were described. Cortisol level, growth measures, and urinary catecholamine, serotonin, and melatonin levels were reported as biological-marker candidates for tactile sensorial processing. Heart rate, body temperature, skin-conductance activity, and vagal reactivity were described as neurovegetative-marker candidates. Somatosensory evoked potentials, somatosensory evoked magnetic fields, and functional neuroimaging data also were included.

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Dissertação para obtenção do Grau de Mestre em Engenharia Mecânica

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Dissertação para obtenção do Grau de Doutor em Química Sustentável

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

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Dissertação para obtenção do Grau de Doutora 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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The EM3E Master is an Education Programme supported by the European Commission, the European Membrane Society (EMS), the European Membrane House (EMH), and a large international network of industrial companies, research centers and universities

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The present work is devoted to study the pre-treatment of lignocellulosic biomass, especially wheat straw, by the application of the acidic ionic liquid (IL) such as 1-butyl-3-methylimidazolium hydrogen sulphate. The ability of this IL to hydrolysis and conversion of biomass was scrutinised. The pre-treatment with hydrogen sulphate-based IL allowed to obtain a liquor rich in hemicellulosic sugars, furans and organic acids, and a solid fraction mainly constituted by cellulose and lignin. Quantitative and qualitative analyses of the produced liquors were made by capillary electrophoresis and high-performance liquid chromatography. Pre-treatment conditions were set to produce xylose or furfural. Specific range of temperatures from 70 to 175 °C and residence times from 20.0 to 163.3 min were studied by fixing parameters such as biomass/IL ratio (10 % (w/w)) and water content (1.25 % (w/w)) in the pre-treatment process. Statistical modelling was applied to maximise the xylose and furfural concentrations. For the purpose of reaction condition comparison the severity factor for studied ionic liquid was proposed and applied in this work. Optimum conditions for xylose production were identified to be at 125 °C and 82.1 min, at which 16.7 % (w/w) xylose yield was attained. Furfural was preferably formed at higher pre-treatment temperatures and longer reaction time (161 °C and 104.5 min) reaching 30.7 % (w/w) maximum yield. The influence of water content on the optimum xylose formation was also studied. Pre-treatments with 5 and 10 % (w/w) water content were performed and an increase of 100 % and 140 % of xylose yield was observed, respectively, while the conversion into furfural maintained unchanged.

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The increasing use of information and communication technologies (ICT) in diverse professional and personal contexts calls for new knowledge, and a set of abilities, competences and attitudes, for an active and participative citizenship. In this context it is acknowledged that universities have an important role innovating in the educational use of digital media to promote an inclusive digital literacy. The educational potential of digital technologies and resources has been recognized by both researchers and practitioners. Multiple pedagogical models and research approaches have already contributed to put in evidence the importance of adapting instructional and learning practices and processes to concrete contexts and educational goals. Still, academic and scientific communities believe further investments in ICT research is needed in higher education. This study focuses on educational models that may contribute to support digital technology uses, where these can have cognitive and educational relevance when compared to analogical technologies. A teaching and learning model, centered in the active role of the students in the exploration, production, presentation and discussion of interactive multimedia materials, was developed and applied using the internet and exploring emergent semantic hypermedia formats. The research approach focused on the definition of design principles for developing class activities that were applied in three different iterations in undergraduate courses from two institutions, namely the University of Texas at Austin, USA and the University of Lisbon, Portugal. The analysis of this study made possible to evaluate the potential and efficacy of the model proposed and the authoring tool chosen in the support of metacognitive skills and attitudes related to information structuring and management, storytelling and communication, using computers and the internet.

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This thesis introduces a novel conceptual framework to support the creation of knowledge representations based on enriched Semantic Vectors, using the classical vector space model approach extended with ontological support. One of the primary research challenges addressed here relates to the process of formalization and representation of document contents, where most existing approaches are limited and only take into account the explicit, word-based information in the document. This research explores how traditional knowledge representations can be enriched through incorporation of implicit information derived from the complex relationships (semantic associations) modelled by domain ontologies with the addition of information presented in documents. The relevant achievements pursued by this thesis are the following: (i) conceptualization of a model that enables the semantic enrichment of knowledge sources supported by domain experts; (ii) development of a method for extending the traditional vector space, using domain ontologies; (iii) development of a method to support ontology learning, based on the discovery of new ontological relations expressed in non-structured information sources; (iv) development of a process to evaluate the semantic enrichment; (v) implementation of a proof-of-concept, named SENSE (Semantic Enrichment kNowledge SourcEs), which enables to validate the ideas established under the scope of this thesis; (vi) publication of several scientific articles and the support to 4 master dissertations carried out by the department of Electrical and Computer Engineering from FCT/UNL. It is worth mentioning that the work developed under the semantic referential covered by this thesis has reused relevant achievements within the scope of research European projects, in order to address approaches which are considered scientifically sound and coherent and avoid “reinventing the wheel”.

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Ontologies formalized by means of Description Logics (DLs) and rules in the form of Logic Programs (LPs) are two prominent formalisms in the field of Knowledge Representation and Reasoning. While DLs adhere to the OpenWorld Assumption and are suited for taxonomic reasoning, LPs implement reasoning under the Closed World Assumption, so that default knowledge can be expressed. However, for many applications it is useful to have a means that allows reasoning over an open domain and expressing rules with exceptions at the same time. Hybrid MKNF knowledge bases make such a means available by formalizing DLs and LPs in a common logic, the Logic of Minimal Knowledge and Negation as Failure (MKNF). Since rules and ontologies are used in open environments such as the Semantic Web, inconsistencies cannot always be avoided. This poses a problem due to the Principle of Explosion, which holds in classical logics. Paraconsistent Logics offer a solution to this issue by assigning meaningful models even to contradictory sets of formulas. Consequently, paraconsistent semantics for DLs and LPs have been investigated intensively. Our goal is to apply the paraconsistent approach to the combination of DLs and LPs in hybrid MKNF knowledge bases. In this thesis, a new six-valued semantics for hybrid MKNF knowledge bases is introduced, extending the three-valued approach by Knorr et al., which is based on the wellfounded semantics for logic programs. Additionally, a procedural way of computing paraconsistent well-founded models for hybrid MKNF knowledge bases by means of an alternating fixpoint construction is presented and it is proven that the algorithm is sound and complete w.r.t. the model-theoretic characterization of the semantics. Moreover, it is shown that the new semantics is faithful w.r.t. well-studied paraconsistent semantics for DLs and LPs, respectively, and maintains the efficiency of the approach it extends.

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With the recent advances in technology and miniaturization of devices such as GPS or IMU, Unmanned Aerial Vehicles became a feasible platform for a Remote Sensing applications. The use of UAVs compared to the conventional aerial platforms provides a set of advantages such as higher spatial resolution of the derived products. UAV - based imagery obtained by a user grade cameras introduces a set of problems which have to be solved, e. g. rotational or angular differences or unknown or insufficiently precise IO and EO camera parameters. In this work, UAV - based imagery of RGB and CIR type was processed using two different workflows based on PhotoScan and VisualSfM software solutions resulting in the DSM and orthophoto products. Feature detection and matching parameters influence on the result quality as well as a processing time was examined and the optimal parameter setup was presented. Products of the both workflows were compared in terms of a quality and a spatial accuracy. Both workflows were compared by presenting the processing times and quality of the results. Finally, the obtained products were used in order to demonstrate vegetation classification. Contribution of the IHS transformations was examined with respect to the classification accuracy.