907 resultados para decoupling and matching network


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Emerging infectious diseases, such as severe acute respiratory syndrome (SARS), are of huge economic importance. They are difficult to predict. The World Health Organization has a Global Outbreak Alert and Response Network, which was involved at an early stage in the SARS outbreak in 2003. Three major lessons were learned as a result of the SARS epidemic in 2003, involving communication, evidence-based action and global partnerships. It is proposed that a series of broadband global response networks should be developed. At a technical level the networks are essentially in place, such as the Internet2 global network. Suitable peripheral devices also exist. What has not yet been created is the appropriate software to allow the use of these networks, although a number of commercial products are in the process of development.

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In general, modern networks are analysed by taking several Key Performance Indicators (KPIs) into account, their proper balance being required in order to guarantee a desired Quality of Service (QoS), particularly, cellular wireless heterogeneous networks. A model to integrate a set of KPIs into a single one is presented, by using a Cost Function that includes these KPIs, providing for each network node a single evaluation parameter as output, and reflecting network conditions and common radio resource management strategies performance. The proposed model enables the implementation of different network management policies, by manipulating KPIs according to users' or operators' perspectives, allowing for a better QoS. Results show that different policies can in fact be established, with a different impact on the network, e.g., with median values ranging by a factor higher than two.

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In a “perfect” drinking water system, the water quality for the consumers should be the same as the quality of the water leaving the treatment plant. However, some variability along the system can lead to a decrease in water quality (such as discolouration) which is usually reflected in the number of the customer complaints. This change may be related to the amount of sediment in the distribution network, leading to an increase in turbidity at the water supply. Since there is no such thing as a perfect drinking water system, the behaviour of particles in a drinking water network needs a suitable approach in order to understand how it works. Moreover, the combination of measurements, such as turbidity patterns and the Resuspension Potential Method (RPM) aid in the prevention of discoloured water complaints and intervention in the treatment upgrade or the network cleaning. Besides sediments there is also bacterial regrowth in the network, which is related to the water quality and distribution network characteristics. In a theoretical drinking water system higher velocities, temperature and shorter residences times lead to wider bacterial growth. In this study we observe velocity and residence steady-states and bacterial does not seem to be related to either. It can be concluded that adequate measurements of RPM, customer complaints and bacterial concentrations allow a wider knowledge on particle behaviour in drinking water systems.

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OBJECTIVE Develop an index to evaluate the maternal and neonatal hospital care of the Brazilian Unified Health System.METHODS This descriptive cross-sectional study of national scope was based on the structure-process-outcome framework proposed by Donabedian and on comprehensive health care. Data from the Hospital Information System and the National Registry of Health Establishments were used. The maternal and neonatal network of Brazilian Unified Health System consisted of 3,400 hospitals that performed at least 12 deliveries in 2009 or whose number of deliveries represented 10.0% or more of the total admissions in 2009. Relevance and reliability were defined as criteria for the selection of variables. Simple and composite indicators and the index of completeness were constructed and evaluated, and the distribution of maternal and neonatal hospital care was assessed in different regions of the country.RESULTS A total of 40 variables were selected, from which 27 single indicators, five composite indicators, and the index of completeness of care were built. Composite indicators were constructed by grouping simple indicators and included the following variables: hospital size, level of complexity, delivery care practice, recommended hospital practice, and epidemiological practice. The index of completeness of care grouped the five variables and classified them in ascending order, thereby yielding five levels of completeness of maternal and neonatal hospital care: very low, low, intermediate, high, and very high. The hospital network was predominantly of small size and low complexity, with inadequate child delivery care and poor development of recommended and epidemiological practices. The index showed that more than 80.0% hospitals had a low index of completeness of care and that most qualified heath care services were concentrated in the more developed regions of the country.CONCLUSIONS The index of completeness proved to be of great value for monitoring the maternal and neonatal hospital care of Brazilian Unified Health System and indicated that the quality of health care was unsatisfactory. However, its application does not replace specific evaluations.

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This paper provides a two-stage stochastic programming approach for the development of optimal offering strategies for wind power producers. Uncertainty is related to electricity market prices and wind power production. A hybrid intelligent approach, combining wavelet transform, particle swarm optimization and adaptive-network-based fuzzy inference system, is used in this paper to generate plausible scenarios. Also, risk aversion is explicitly modeled using the conditional value-at-risk methodology. Results from a realistic case study, based on a wind farm in Portugal, are provided and analyzed. Finally, conclusions are duly drawn.

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The elastic behavior of the demand consumption jointly used with other available resources such as distributed generation (DG) can play a crucial role for the success of smart grids. The intensive use of Distributed Energy Resources (DER) and the technical and contractual constraints result in large-scale non linear optimization problems that require computational intelligence methods to be solved. This paper proposes a Particle Swarm Optimization (PSO) based methodology to support the minimization of the operation costs of a virtual power player that manages the resources in a distribution network and the network itself. Resources include the DER available in the considered time period and the energy that can be bought from external energy suppliers. Network constraints are considered. The proposed approach uses Gaussian mutation of the strategic parameters and contextual self-parameterization of the maximum and minimum particle velocities. The case study considers a real 937 bus distribution network, with 20310 consumers and 548 distributed generators. The obtained solutions are compared with a deterministic approach and with PSO without mutation and Evolutionary PSO, both using self-parameterization.

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Trabalho apresentado no âmbito do Mestrado em Engenharia Informática, como requisito parcial para obtenção do grau de Mestre em Engenharia Informática

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The Internet of Things (IoT) has emerged as a paradigm over the last few years as a result of the tight integration of the computing and the physical world. The requirement of remote sensing makes low-power wireless sensor networks one of the key enabling technologies of IoT. These networks encompass several challenges, especially in communication and networking, due to their inherent constraints of low-power features, deployment in harsh and lossy environments, and limited computing and storage resources. The IPv6 Routing Protocol for Low Power and Lossy Networks (RPL) [1] was proposed by the IETF ROLL (Routing Over Low-power Lossy links) working group and is currently adopted as an IETF standard in the RFC 6550 since March 2012. Although RPL greatly satisfied the requirements of low-power and lossy sensor networks, several issues remain open for improvement and specification, in particular with respect to Quality of Service (QoS) guarantees and support for mobility. In this paper, we focus mainly on the RPL routing protocol. We propose some enhancements to the standard specification in order to provide QoS guarantees for static as well as mobile LLNs. For this purpose, we propose OF-FL (Objective Function based on Fuzzy Logic), a new objective function that overcomes the limitations of the standardized objective functions that were designed for RPL by considering important link and node metrics, namely end-to-end delay, number of hops, ETX (Expected transmission count) and LQL (Link Quality Level). In addition, we present the design of Co-RPL, an extension to RPL based on the corona mechanism that supports mobility in order to overcome the problem of slow reactivity to frequent topology changes and thus providing a better quality of service mainly in dynamic networks application. Performance evaluation results show that both OF-FL and Co-RPL allow a great improvement when compared to the standard specification, mainly in terms of packet loss ratio and average network latency. 2015 Elsevier B.V. Al

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Dissertation to obtain PhD in Industrial Engineering

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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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Tissue engineering arises from the need to regenerate organs and tissues, requiring the development of scaffolds, which can provide an optimum environment for tissue growth. In this work, chitosan with different molecular weights was used to develop biodegradable 3D inverted colloidal crystals (ICC) structures for bone regeneration, exhibiting uniform pore size and interconnected network. Moreover, in vitro tests were conducted by studying the influence of the molecular weight in the degradation kinetics and mechanical properties. The production of ICC included four major stages: fabrication of microspheres; assembly into a cohesive structure, polymeric solution infiltration and microsphere removal. Chitosan’s degree of deacetylation was determined by infrared spectroscopy and molecular weight was obtained via capillary viscometry. In order to understand the effect of the molecular weight in ICC structures, the mass loss and mechanical properties were analyzed after degradation with lysozyme. Structure morphology observation before and after degradation was performed by scanning electron microscopy. Cellular adhesion and proliferation tests were carried out to evaluate ICC in vitro response. Overall, medium molecular weight ICC revealed the best balance in terms of mechanical properties, degradation rate, morphology and biological behaviour.

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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.

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Tese de Doutoramento em Psicologia na área de especialização de Psicologia das Organizações apresentada ao ISPA - Instituto Universitário

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This dissertation consists of three essays on the labour market impact of firing and training costs. The modelling framework resorts to the search and matching literature. The first chapter introduces firing costs, both liner and non-linear, in a new Keynesian model, analysing business cycle effects for different wage rigidity degrees. The second chapter adds training costs in a model of a segmented labour market, accessing the interaction between these two features and the skill composition of the labour force. Finally, the third chapter analyses empirically some of the issues raised in the second chapter.

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Tese de Doutoramento em Ciências da Saúde.