978 resultados para RANGE ORDER
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Relatório de estágio de mestrado em Educação Pré-Escolar
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Hand gestures are a powerful way for human communication, with lots of potential applications in the area of human computer interaction. Vision-based hand gesture recognition techniques have many proven advantages compared with traditional devices, giving users a simpler and more natural way to communicate with electronic devices. This work proposes a generic system architecture based in computer vision and machine learning, able to be used with any interface for humancomputer interaction. The proposed solution is mainly composed of three modules: a pre-processing and hand segmentation module, a static gesture interface module and a dynamic gesture interface module. The experiments showed that the core of vision-based interaction systems can be the same for all applications and thus facilitate the implementation. In order to test the proposed solutions, three prototypes were implemented. For hand posture recognition, a SVM model was trained and used, able to achieve a final accuracy of 99.4%. For dynamic gestures, an HMM model was trained for each gesture that the system could recognize with a final average accuracy of 93.7%. The proposed solution as the advantage of being generic enough with the trained models able to work in real-time, allowing its application in a wide range of human-machine applications.
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Tese de Doutoramento Tecnologias e Sistemas de Informação
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Dissertação de mestrado integrado em Engenharia e Gestão Industrial
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A new very high-order finite volume method to solve problems with harmonic and biharmonic operators for one- dimensional geometries is proposed. The main ingredient is polynomial reconstruction based on local interpolations of mean values providing accurate approximations of the solution up to the sixth-order accuracy. First developed with the harmonic operator, an extension for the biharmonic operator is obtained, which allows designing a very high-order finite volume scheme where the solution is obtained by solving a matrix-free problem. An application in elasticity coupling the two operators is presented. We consider a beam subject to a combination of tensile and bending loads, where the main goal is the stress critical point determination for an intramedullary nail.
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Various differential cross-sections are measured in top-quark pair (tt¯) events produced in proton--proton collisions at a centre-of-mass energy of s√=7 TeV at the LHC with the ATLAS detector. These differential cross-sections are presented in a data set corresponding to an integrated luminosity of 4.6 fb−1. The differential cross-sections are presented in terms of kinematic variables of a top-quark proxy referred to as the pseudo-top-quark whose dependence on theoretical models is minimal. The pseudo-top-quark can be defined in terms of either reconstructed detector objects or stable particles in an analogous way. The measurements are performed on tt¯ events in the lepton+jets channel, requiring exactly one charged lepton and at least four jets with at least two of them tagged as originating from a b-quark. The hadronic and leptonic pseudo-top-quarks are defined via the leptonic or hadronic decay mode of the W boson produced by the top-quark decay in events with a single charged lepton.The cross-section is measured as a function of the transverse momentum and rapidity of both the hadronic and leptonic pseudo-top-quark as well as the transverse momentum, rapidity and invariant mass of the pseudo-top-quark pair system. The measurements are corrected for detector effects and are presented within a kinematic range that closely matches the detector acceptance. Differential cross-section measurements of the pseudo-top-quark variables are compared with several Monte Carlo models that implement next-to-leading order or leading-order multi-leg matrix-element calculations.
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Poly(vinylidene fluoride-co-chlorotrifluoroethylene) – P(VDF-CTFE) membranes are increasingly interesting for a wide range of applications, including battery separators, filtration membranes and biomedical applications. This work reports on the morphology, hydrophobicity, thermal and mechanical properties variation of P(VDF-CTFE) membranes processed by nonsolvent induced phase separation technique (NIPS) as a function of the main processing parameters. All membranes show a porous structure composed of large spherulites, (interconnected) micropores and/or microvoids depending on the processing conditions used that in turn affect their hydrophobicity and mechanical properties. The degree of crystallinity of the membranes remains approximately constant with a value of about 15 %, except for the membranes immediately immersed in ethanol, which is of about 23 %. In turn, the crystalline phases present in the copolymer is mainly affected by the temperature and nonsolvent characteristics of the coagulation bath, the β-phase content ranging from 33 to 100 %, depending on those processing parameters. It was show that the temperature of water-based coagulation bath plays an important role in order to produce structurally uniform and homogeneous porous membranes, which is particularly important from the point of view of technological applications.
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The effect of varying separator membrane physical parameters such as degree of porosity, tortuosity and thickness, on battery delivered capacity was studied in order to optimize performance of lithium-ion batteries. This was achieved by a theoretical mathematical model relating the Bruggeman coefficient with the degree of porosity and tortuosity. The inclusion of the separator membrane in the simulation model of the battery system does not affect the delivered capacity of the battery. The ionic conductivity of the separator and consequently the delivered capacity values obtained at different discharge rates depends on the value of the Bruggeman coefficient, which is related with the degree of porosity and tortuosity of the membrane. Independently of scan rate, the optimal value of the degree of porosity is above 50% and the separator thickness should range between 1 μm at 32 μm for improved battery performance.
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Tese de Doutoramento em Ciências da Administração
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Companies and researchers involved in developing miniaturized electronic devices face the basic problem of the needed batteries size, finite life of time and environmental pollution caused by their final deposition. The current trends to overcome this situation point towards Energy Harvesting technology. These harvesters (or scavengers) store the energy from sources present in the ambient (as wind, solar, electromagnetic, etc) and are costless for us. Piezoelectric devices are the ones that show a higher power density, and materials as ceramic PZT or polymeric PVDF have already demonstrated their ability to act as such energy harvester elements. Combinations between piezoelectric and electromagnetic mechanism have been also extensively investigated. Nevertheless, the power generated by these combinations is limited under the application of small magnetic fields, reducing the performance of the energy harvester [1]. In the last years the appearance of magnetoelectric (ME) devices, in which the piezoelectric deformation is driven by the magnetostrictive element, enables to extract the energy of very small electromagnetic signals through the generated magnetoelectric voltage at the piezoelectric element. However, very little work has been done testing PVDF polymer as piezoelectric constituent of the ME energy harvester device, and only to be proposed as a possibility of application [2]. Among the advantages of using piezopolymers for vibrational energy harvesting we can remember that they are ductile, resilient to shock, deformable and lightweight. In this work we demonstrate the feasibility of using magnetostrictive Fe-rich magnetic amorphous alloys/piezoelectric PVDF sandwich-type laminated ME devices as energy harvesters. A very simple experimental set-up will show how these laminates can extract energy, in amounts of μW, from an external AC field.
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Kidney renal failure means that one’s kidney have unexpectedly stopped functioning, i.e., once chronic disease is exposed, the presence or degree of kidney dysfunction and its progression must be assessed, and the underlying syndrome has to be diagnosed. Although the patient’s history and physical examination may denote good practice, some key information has to be obtained from valuation of the glomerular filtration rate, and the analysis of serum biomarkers. Indeed, chronic kidney sickness depicts anomalous kidney function and/or its makeup, i.e., there is evidence that treatment may avoid or delay its progression, either by reducing and prevent the development of some associated complications, namely hypertension, obesity, diabetes mellitus, and cardiovascular complications. Acute kidney injury appears abruptly, with a rapid deterioration of the renal function, but is often reversible if it is recognized early and treated promptly. In both situations, i.e., acute kidney injury and chronic kidney disease, an early intervention can significantly improve the prognosis.The assessment of these pathologies is therefore mandatory, although it is hard to do it with traditional methodologies and existing tools for problem solving. Hence, in this work, we will focus on the development of a hybrid decision support system, in terms of its knowledge representation and reasoning procedures based on Logic Programming, that will allow one to consider incomplete, unknown, and even contradictory information, complemented with an approach to computing centered on Artificial Neural Networks, in order to weigh the Degree-of-Confidence that one has on such a happening. The present study involved 558 patients with an age average of 51.7 years and the chronic kidney disease was observed in 175 cases. The dataset comprise twenty four variables, grouped into five main categories. The proposed model showed a good performance in the diagnosis of chronic kidney disease, since the sensitivity and the specificity exhibited values range between 93.1 and 94.9 and 91.9–94.2 %, respectively.
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Tese de Doutoramento Ciência e Engenharia de Polímeros e Compósitos.
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Tese de Doutoramento em Ciências Jurídicas (área de especialização em Ciências Jurídicas Públicas).
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Kidney renal failure means that one’s kidney have unexpectedlystoppedfunctioning,i.e.,oncechronicdiseaseis exposed, the presence or degree of kidney dysfunction and its progression must be assessed, and the underlying syndrome has to be diagnosed. Although the patient’s history and physical examination may denote good practice, some key information has to be obtained from valuation of the glomerular filtration rate, and the analysis of serum biomarkers. Indeed, chronic kidney sickness depicts anomalous kidney function and/or its makeup, i.e., there is evidence that treatment may avoid or delay its progression, either by reducing and prevent the development of some associated complications, namely hypertension, obesity, diabetes mellitus, and cardiovascular complications. Acute kidney injury appears abruptly, with a rapiddeteriorationoftherenalfunction,butisoftenreversible if it is recognized early and treated promptly. In both situations, i.e., acute kidney injury and chronic kidney disease, an early intervention can significantly improve the prognosis. The assessment of these pathologies is therefore mandatory, although it is hard to do it with traditional methodologies and existing tools for problem solving. Hence, in this work, we will focus on the development of a hybrid decision support system, in terms of its knowledge representation and reasoning procedures based on Logic Programming, that will allow onetoconsiderincomplete,unknown,and evencontradictory information, complemented with an approach to computing centered on Artificial Neural Networks, in order to weigh the Degree-of-Confidence that one has on such a happening. The present study involved 558 patients with an age average of 51.7 years and the chronic kidney disease was observed in 175 cases. The dataset comprise twenty four variables, grouped into five main categories. The proposed model showed a good performance in the diagnosis of chronic kidney disease, since the sensitivity and the specificity exhibited values range between 93.1 and 94.9 and 91.9–94.2 %, respectively.
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During last years, photophysical properties of complexes of semiconductor quantum dots (QDs) with organic dyes have attracted increasing interest. The development of different assemblies based on QDs and organic dyes allows to increase the range of QDs applications, which include imaging, biological sensing and electronic devices.1 Some studies demonstrate energy transfer between QDs and organic dye in assemblies.2 However, for electronic devices purposes, a polymeric matrix is required to enhance QDs photostability. Thus, in order to attach the QDs to the polymer surface it is necessary to chemically modify the polymer to induce electronic charges and stabilize the QDs in the polymer. The present work aims to investigate the design of assemblies based on polymer-coated QDs and an integrated acceptor organic dye. Polymethylmethacrylate (PMMA) and polycarbonate (PC) were used as polymeric matrices, and nile red as acceptor. Additionally, a PMMA matrix modified with 2-mercaptoethylamine is used to improve the attachment between both the donor (QDs) and the acceptor (nile red), as well as to induce a covalent bond between the modified PMMA and the QDs. An enhancement of the energy transfer efficiency by using the modified PMMA is expected and the resulting assembly can be applied for energy harvesting.