989 resultados para Algorithm Comparison
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A descriptive study was developed to compare air and surfaces fungal contamination in ten hospitals’ food units and two food units from companies. Fifty air samples of 250 litres through impaction method were collected from hospitals’ food units and 41 swab samples from surfaces were also collected, using a 10 by 10 cm square stencil. Regarding the two companies, ten air samples and eight surface samples were collected. Air and surface samples were collected in food storage facilities, kitchen, food plating and canteen. Outdoor air was also collected since this is the place regarded as a reference. Simultaneously, temperature, relative humidity and meal numbers were registered. Concerning air from hospitals’ food units, 32 fungal species were identified, being the two most commonly isolated genera Penicillium sp.
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Este trabalho utiliza uma estrutura pin empilhada, baseada numa liga de siliceto de carbono amorfo hidrogenado (a-Si:H e/ou a-SiC:H), que funciona como filtro óptico na zona visível do espectro electromagnético. Pretende-se utilizar este dispositivo para realizar a demultiplexagem de sinais ópticos e desenvolver um algoritmo que permita fazer o reconhecimento autónomo do sinal transmitido em cada canal. O objectivo desta tese visa implementar um algoritmo que permita o reconhecimento autónomo da informação transmitida por cada canal através da leitura da fotocorrente fornecida pelo dispositivo. O tema deste trabalho resulta das conclusões de trabalhos anteriores, em que este dispositivo e outros de configuração idêntica foram analisados, de forma a explorar a sua utilização na implementação da tecnologia WDM. Neste trabalho foram utilizados três canais de transmissão (Azul – 470 nm, Verde – 525 nm e Vermelho – 626 nm) e vários tipos de radiação de fundo. Foram realizadas medidas da resposta espectral e da resposta temporal da fotocorrente do dispositivo, em diferentes condições experimentais. Variou-se o comprimento de onda do canal e o comprimento de onda do fundo aplicado, mantendo-se constante a intensidade do canal e a frequência de transmissão. Os resultados obtidos permitiram aferir sobre a influência da presença da radiação de fundo e da tensão aplicada ao dispositivo, usando diferentes sequências de dados transmitidos nos vários canais. Verificou-se, que sob polarização inversa, a radiação de fundo vermelho amplifica os valores de fotocorrente do canal azul e a radiação de fundo azul amplifica o canal vermelho e verde. Para polarização directa, apenas a radiação de fundo azul amplifica os valores de fotocorrente do canal vermelho. Enquanto para ambas as polarizações, a radiação de fundo verde, não tem uma grande influência nos restantes canais. Foram implementados dois algoritmos para proceder ao reconhecimento da informação de cada canal. Na primeira abordagem usou-se a informação contida nas medidas de fotocorrente geradas pelo dispositivo sob polarização inversa e directa. Pela comparação das duas medidas desenvolveu-se e testou-se um algoritmo que permite o reconhecimento dos canais individuais. Numa segunda abordagem procedeu-se ao reconhecimento da informação de cada canal mas com aplicação de radiação de fundo, tendo-se usado a informação contida nas medidas de fotocorrente geradas pelo dispositivo sob polarização inversa sem aplicação de radiação de fundo com a informação contida nas medidas de fotocorrente geradas pelo dispositivo sob polarização inversa com aplicação de radiação de fundo. Pela comparação destas duas medidas desenvolveu-se e testou-se o segundo algoritmo que permite o reconhecimento dos canais individuais com base na aplicação de radiação de fundo.
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This paper is on the problem of short-term hydro scheduling, particularly concerning head-dependent reservoirs under competitive environment. We propose a new nonlinear optimization method to consider hydroelectric power generation as a function of water discharge and also of the head. Head-dependency is considered on short-term hydro scheduling in order to obtain more realistic and feasible results. The proposed method has been applied successfully to solve a case study based on one of the main Portuguese cascaded hydro systems, providing a higher profit at a negligible additional computation time in comparison with a linear optimization method that ignores head-dependency.
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Mestrado de Radiações aplicadas às Tecnologias da Saúde. Área de especialização: Imagem Digital com Radiação X.
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5th. European Congress on Computational Methods in Applied Sciences and Engineering (ECCOMAS 2008) 8th. World Congress on Computational Mechanics (WCCM8)
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A descriptive study was developed in order to compare indoor and outdoor air contamination caused by fungi and particles in seven poultry units. Twenty eight air samples of 25 litters were collected through the impaction method on malt extract agar. Air sampling and particles concentration measurement were done in the interior and also outside premises of the poultries’ pavilions. Regarding the fungal load in the air, indoor concentration of mold was higher than outside air in six poultry units. Twenty eight species / genera of fungi were identified indoor, being Scopulariopsis brevicaulis (40.5%) the most commonly isolated species and Rhizopus sp. (30.0%) the most commonly isolated genus. Concerning outdoor, eighteen species/genera of fungi were isolated, being Scopulariopsis brevicaulis (62.6%) also the most isolated. All the poultry farms analyzed presented indoor fungi different from the ones identified outdoors. Regarding particles’ contamination, PM2.5, PM5.0 and PM10 had a statistically significant difference (Mann-Whitney U test) between the inside and outside of the pavilions, with the inside more contaminated (p=.006; p=.005; p=.005, respectively). The analyzed poultry units are potential reservoirs of substantial amounts of fungi and particles and could therefore free them in the atmospheric air. The developed study showed that indoor air was more contaminated than outdoors, and this can result in emission of potentially pathogenic fungi and particles via aerosols from poultry units to the environment, which may post a considerable risk to public health and contribute to environmental pollution.
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This article describes work performed on the assessment of the levels of airborne ultrafine particles emitted in two welding processes metal-active gas (MAG) of carbon steel and friction-stir welding (FSW) of aluminium in terms of deposited area in alveolar tract of the lung using a nanoparticle surface area monitor analyser. The obtained results showed the dependence from process parameters on emitted ultrafine particles and clearly demonstrated the presence of ultrafine particles, when compared with background levels. The obtained results showed that the process that results on the lower levels of alveolar-deposited surface area is FSW, unlike MAG. Nevertheless, all the tested processes resulted in important doses of ultrafine particles that are to be deposited in the human lung of exposed workers.
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The purpose of this study is a cross-qualitative and quantitative gait analysis in 3 traumatic unilateral amputees using prosthesis with pin suspension compared to the use of prosthesis with a high vacuum suspension, the Harmony® system. In Portugal, there aren’t many studies made in the field of orthotic and prosthetic and knowledge about the number of amputees in the country. The only know is that the major cause of lower limb amputation is diabetes mellitus, being the most affected population the older age groups. The combination of technological developments with daily needs of the amputees is becoming more and more important for they better quality of life. This work was done during the curricular unit “Investigation in Prosthetics and Orthotics” class, in the 4th year of Health Technology School of Lisbon, in Portugal. This study analyzes if the change of suspension in transtibial prosthesis will influence some physiological response in amputees.
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Fluorescence confocal microscopy (FCM) is now one of the most important tools in biomedicine research. In fact, it makes it possible to accurately study the dynamic processes occurring inside the cell and its nucleus by following the motion of fluorescent molecules over time. Due to the small amount of acquired radiation and the huge optical and electronics amplification, the FCM images are usually corrupted by a severe type of Poisson noise. This noise may be even more damaging when very low intensity incident radiation is used to avoid phototoxicity. In this paper, a Bayesian algorithm is proposed to remove the Poisson intensity dependent noise corrupting the FCM image sequences. The observations are organized in a 3-D tensor where each plane is one of the images acquired along the time of a cell nucleus using the fluorescence loss in photobleaching (FLIP) technique. The method removes simultaneously the noise by considering different spatial and temporal correlations. This is accomplished by using an anisotropic 3-D filter that may be separately tuned in space and in time dimensions. Tests using synthetic and real data are described and presented to illustrate the application of the algorithm. A comparison with several state-of-the-art algorithms is also presented.
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A novel hybrid approach, combining wavelet transform, particle swarm optimization, and adaptive-network-based fuzzy inference system, is proposed in this paper for short-term electricity prices forecasting in a competitive market. Results from a case study based on the electricity market of mainland Spain are presented. A thorough comparison is carried out, taking into account the results of previous publications. Finally, conclusions are duly drawn.
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This paper presents an algorithm to efficiently generate the state-space of systems specified using the IOPT Petri-net modeling formalism. IOPT nets are a non-autonomous Petri-net class, based on Place-Transition nets with an extended set of features designed to allow the rapid prototyping and synthesis of system controllers through an existing hardware-software co-design framework. To obtain coherent and deterministic operation, IOPT nets use a maximal-step execution semantics where, in a single execution step, all enabled transitions will fire simultaneously. This fact increases the resulting state-space complexity and can cause an arc "explosion" effect. Real-world applications, with several million states, will reach a higher order of magnitude number of arcs, leading to the need for high performance state-space generator algorithms. The proposed algorithm applies a compilation approach to read a PNML file containing one IOPT model and automatically generate an optimized C program to calculate the corresponding state-space.
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In this paper, a hybrid intelligent approach is proposed for short-term electricity prices forecasting in a competitive market. The proposed approach is based on the wavelet transform and a hybrid of neural networks and fuzzy logic. Results from a case study based on the electricity market of mainland Spain are presented. A thorough comparison is carried out, taking into account the results of previous publications. Conclusions are duly drawn. (C) 2010 Elsevier Ltd. All rights reserved.
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The present research paper presents five different clustering methods to identify typical load profiles of medium voltage (MV) electricity consumers. These methods are intended to be used in a smart grid environment to extract useful knowledge about customer’s behaviour. The obtained knowledge can be used to support a decision tool, not only for utilities but also for consumers. Load profiles can be used by the utilities to identify the aspects that cause system load peaks and enable the development of specific contracts with their customers. The framework presented throughout the paper consists in several steps, namely the pre-processing data phase, clustering algorithms application and the evaluation of the quality of the partition, which is supported by cluster validity indices. The process ends with the analysis of the discovered knowledge. To validate the proposed framework, a case study with a real database of 208 MV consumers is used.
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This paper proposes artificial neural networks in combination with wavelet transform for short-term wind power forecasting in Portugal. The increased integration of wind power into the electric grid, as nowadays occurs in Portugal, poses new challenges due to its intermittency and volatility. Hence, good forecasting tools play a key role in tackling these challenges. Results from a real-world case study are presented. A comparison is carried out, taking into account the results obtained with other approaches. Finally, conclusions are duly drawn. (C) 2010 Elsevier Ltd. All rights reserved.
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In recent years the use of several new resources in power systems, such as distributed generation, demand response and more recently electric vehicles, has significantly increased. Power systems aim at lowering operational costs, requiring an adequate energy resources management. In this context, load consumption management plays an important role, being necessary to use optimization strategies to adjust the consumption to the supply profile. These optimization strategies can be integrated in demand response programs. The control of the energy consumption of an intelligent house has the objective of optimizing the load consumption. This paper presents a genetic algorithm approach to manage the consumption of a residential house making use of a SCADA system developed by the authors. Consumption management is done reducing or curtailing loads to keep the power consumption in, or below, a specified energy consumption limit. This limit is determined according to the consumer strategy and taking into account the renewable based micro generation, energy price, supplier solicitations, and consumers’ preferences. The proposed approach is compared with a mixed integer non-linear approach.