978 resultados para Channel Estimation
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Dissertação para obtenção do Grau de Mestre em Engenharia Civil – Perfil de Estruturas
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Dissertação para obtenção do Grau de Doutora em Estatística e Gestão de Risco, Especialidade em Estatística
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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Economics from the NOVA – School of Business and Economics
Energy-efficient diversity combining for different access schemes in a multi-path dispersive channel
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Dissertação para obtenção do Grau de Doutor em Engenharia Electrotécnica e Computadores
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Acute infections by the protozoan Toxoplasma gondii during pregnancy (gestational toxoplasmosis) are known to cause serious health problems to the fetus (congenital toxoplasmosis). In Brasília, there have been few studies on the incidence of toxoplasmosis. This report summarizes a retrospective study performed on 2,636 selected pregnant women attended by the public health system of Guará, a satellite-city of Brasília. In this survey, 17 cases of gestational toxoplasmosis were detected; 15 of which were primary maternal infection and the remaining 2 were consistent with secondary maternal infection. These results suggest an annual seroconversion rate of 0.64 percent (90 percent confidence interval: 0.38, 0.90).
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Water is a limited resource for which demand is growing. Contaminated water from inadequate wastewater treatment provides one of the greatest health challenges as it restricts development and increases poverty in emerging and developing countries. Therefore, the connection between wastewater and human health is linked to access to sanitation and to human waste disposal. Adequate sanitation is expected to create a barrier between disposed human excreta and sources of drinking water. Different approaches to wastewater management are required for different geographical regions and different stages of economic governance depending on the capacity to manage wastewater. Effective wastewater management can contribute to overcome the challenges of water scarcity. Separate collection of human urine at its source is one promising approach that strongly reduces the economic and load demands on wastewater treatment plants (WWTP). Treatment of source-separated urine appears as a sanitation system that is affordable, produces a valuable fertiliser, reduces pollution of water resources and promotes health. However, the technical realisation of urine separation still faces challenges. Biological hydrolysis of urea causes a strong increase of ammonia and pH. Under these conditions ammonia volatilises which can cause odour problems and significant nitrogen losses. The above problems can be avoided by urine stabilisation. Biological nitrification is a suitable process for stabilisation of urine. Urine is a highly concentrated nutrient solution which can lead to strong inhibition effects during bacterial nitrification. This can further lead to process instabilities. The major cause of instability is accumulation of the inhibitory intermediate compound nitrite, which could lead to process breakdown. Enhanced on-line nitrite monitoring can be applied in biological source-separated urine nitrification reactors as a sustainable and efficient way to improve the reactor performance, avoiding reactor failures and eventual loss of biological activity. Spectrophotometry appears as a promising candidate for the development and application of on-line nitrite monitoring. Spectroscopic methods together with chemometrics are presented in this work as a powerful tool for estimation of nitrite concentrations. Principal component regression (PCR) is applied for the estimation of nitrite concentrations using an immersible UV sensor and off-line spectra acquisition. The effect of particles and the effect of saturation, respectively, on the UV absorbance spectra are investigated. The analysis allows to conclude that (i) saturation has a substantial effect on nitrite estimation; (ii) particles appear to have less impact on nitrite estimation. In addition, improper mixing together with instabilities in the urine nitrification process appears to significantly reduce the performance of the estimation model.
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Field Lab in Entrepreneurial Innovative Ventures
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Fundação para a Ciência e a Tecnologia (FCT) - SFRH/BD/64337/2009 ; projects PTDC/ECM/70652/2006, PTDC/ECM/117660/2010 and RECI/ECM-HID/0371/2012
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The aim of this work project is to analyze the current algorithm used by EDP to estimate their clients’ electrical energy consumptions, create a new algorithm and compare the advantages and disadvantages of both. This new algorithm is different from the current one as it incorporates some effects from temperature variations. The results of the comparison show that this new algorithm with temperature variables performed better than the same algorithm without temperature variables, although there is still potential for further improvements of the current algorithm, if the prediction model is estimated using a sample of daily data, which is the case of the current EDP algorithm.
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Structural connectivity models based on Diffusion Tensor Imaging (DTI) are strongly affected by the technique’s inability to resolve crossing fibres, either intra- or inter-hemispherical connections. Several models have been proposed to address this issue, including an algorithm aiming to resolve crossing fibres which is based on Diffusion Kurtosis Imaging (DKI). This technique is clinically feasible, even when multi-band acquisitions are not available, and compatible with multi-shell acquisition schemes. DKI is an extension of DTI enabling the estimation of diffusion tensor and diffusion kurtosis metrics. In this study we compare the performance of DKI and DTI in performing structural brain connectivity. Six healthy subjects were recruited, aged between 25 and 35 (three females). The MRI experiments were performed using a 3T Siemens Trio with a 32-channel head coil. The scans included a T1-weighted sequence (1mm3), and a DWI with b-values 0, 1000 and 2000 s:mm
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Branding Lab
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Field lab: Consulting lab
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It’s impossible to neglect the changes that internet and e-commerce caused in the retail sector, by increasing customers’ expectations and forcing retailers to adapt the business to the new digital era. Internet is characterized by the increase in accessibility to everyone, which can be good or not so. For instance, luxury products rely on the sense of exclusivity, instead of being accessible to everyone. Hence, internet represents a challenge for luxury brands once, although they are able to provide a fullness service to their customers, they need to maintain the exclusiveness in which luxury is sustained. Consequently, the appearance of omni-channel was more than a challenge for the luxury sector, in particular, given the need to provide a full integrated experience through different channels. The aim of this dissertation is to find out how important is omni-channel, even in the luxury industry, and how it’s actually implemented based on the case of one of the most successful companies on luxury fashion e-commerce industry – Farfetch. Even though the company started in London, its founder is a Portuguese entrepreneur, and it’s in Portugal where most of its employees work, divided in two offices – Guimarães e Porto. Therefore, a literature review was written on relevant concepts and ideas about luxury, e-commerce and the different channels’ approaches. There were formulated five propositions that were after discussed according to the information gathered about the company and its strategies. In the end, it was possible to identify which propositions are in accordance with theory and which are not, as well as understand which are the most important strategies and trends about omni-channel in the luxury fashion e-commerce sector.
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Ship tracking systems allow Maritime Organizations that are concerned with the Safety at Sea to obtain information on the current location and route of merchant vessels. Thanks to Space technology in recent years the geographical coverage of the ship tracking platforms has increased significantly, from radar based near-shore traffic monitoring towards a worldwide picture of the maritime traffic situation. The long-range tracking systems currently in operations allow the storage of ship position data over many years: a valuable source of knowledge about the shipping routes between different ocean regions. The outcome of this Master project is a software prototype for the estimation of the most operated shipping route between any two geographical locations. The analysis is based on the historical ship positions acquired with long-range tracking systems. The proposed approach makes use of a Genetic Algorithm applied on a training set of relevant ship positions extracted from the long-term storage tracking database of the European Maritime Safety Agency (EMSA). The analysis of some representative shipping routes is presented and the quality of the results and their operational applications are assessed by a Maritime Safety expert.