976 resultados para least weighted squares


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Dissertação de mest., Qualidade em Análises, Faculdade de Ciências e Tecnologia, Univ. do Algarve, 2013

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Forty years after the Carnation Revolution, the relatively young Portuguese democracy is experiencing dramatically low levels of public specific support for democracy. This article tests the leverage of demand-side and supply-side accounts to explain differentials in public satisfaction with democracy. Through ordinary least squares regression analyses that draw on the unique data of the ‘Barometer 40 Years of Democracy in Portugal (2014)’, this articles shows that age cohort, identification with extreme parties, evaluation of the country’s political past, and economic performance are strong correlates of citizens’ specific support for democracy

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Freshness and safety of muscle foods are generally considered as the most important parameters for the food industry. To address the rapid determination of meat spoilage, Fourier transform infrared (FTIR) spectroscopy technique, with the help of advanced learning-based methods, was attempted in this work. FTIR spectra were obtained from the surface of beef samples during aerobic storage at various temperatures, while a microbiological analysis had identified the population of Total viable counts. A fuzzy principal component algorithm has been also developed to reduce the dimensionality of the spectral data. The results confirmed the superiority of the adopted scheme compared to the partial least squares technique, currently used in food microbiology.

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With the electricity market liberalization, the distribution and retail companies are looking for better market strategies based on adequate information upon the consumption patterns of its electricity consumers. A fair insight on the consumers’ behavior will permit the definition of specific contract aspects based on the different consumption patterns. In order to form the different consumers’ classes, and find a set of representative consumption patterns we use electricity consumption data from a utility client’s database and two approaches: Two-step clustering algorithm and the WEACS approach based on evidence accumulation (EAC) for combining partitions in a clustering ensemble. While EAC uses a voting mechanism to produce a co-association matrix based on the pairwise associations obtained from N partitions and where each partition has equal weight in the combination process, the WEACS approach uses subsampling and weights differently the partitions. As a complementary step to the WEACS approach, we combine the partitions obtained in the WEACS approach with the ALL clustering ensemble construction method and we use the Ward Link algorithm to obtain the final data partition. The characterization of the obtained consumers’ clusters was performed using the C5.0 classification algorithm. Experiment results showed that the WEACS approach leads to better results than many other clustering approaches.

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The paper introduces an approach to solve the problem of generating a sequence of jobs that minimizes the total weighted tardiness for a set of jobs to be processed in a single machine. An Ant Colony System based algorithm is validated with benchmark problems available in the OR library. The obtained results were compared with the best available results and were found to be nearer to the optimal. The obtained computational results allowed concluding on their efficiency and effectiveness.

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In this paper, we present two Partial Least Squares Regression (PLSR) models for compressive and flexural strength responses of a concrete composite material reinforced with pultrusion wastes. The main objective is to characterize this cost-effective waste management solution for glass fiber reinforced polymer (GFRP) pultrusion wastes and end-of-life products that will lead, thereby, to a more sustainable composite materials industry. The experiments took into account formulations with the incorporation of three different weight contents of GFRP waste materials into polyester based mortars, as sand aggregate and filler replacements, two waste particle size grades and the incorporation of silane adhesion promoter into the polyester resin matrix in order to improve binder aggregates interfaces. The regression models were achieved for these data and two latent variables were identified as suitable, with a 95% confidence level. This technological option, for improving the quality of GFRP filled polymer mortars, is viable thus opening a door to selective recycling of GFRP waste and its use in the production of concrete-polymer based products. However, further and complementary studies will be necessary to confirm the technical and economic viability of the process.

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Submitted in partial fulfillment for the Requirements for the Degree of PhD in Mathematics, in the Speciality of Statistics in the Faculdade de Ciências e Tecnologia

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Durante as últimas décadas observou-se o crescimento da importância das avaliações fornecidas pelas agências de rating, sendo este um fator decisivo na tomada de decisão dos investidores. Também os emitentes de dívida são largamente afetados pelas alterações das classificações atribuídas por estas agências. Esta investigação pretende, por um lado, compreender se estas agências têm poder para conseguirem influenciar a evolução da dívida pública e qual o seu papel no mercado financeiro. Por outro, pretende compreender quais os fatores determinantes da dívida pública portuguesa, bem como a realização de uma análise por percentis com o objetivo de lhe atribuir um rating. Para a análise dos fatores que poderão influenciar a dívida pública, a metodologia utilizada é uma regressão linear múltipla estimada através do Método dos Mínimos Quadrados (Ordinary Least Squares – OLS), em que num cenário inicial era composta por onze variáveis independentes, sendo a dívida pública a variável dependente, para um período compreendido entre 1996 e 2013. Foram realizados vários testes ao modelo inicial, com o objetivo de encontrar um modelo que fosse o mais explicativo possível. Conseguimos ainda identificar uma relação inversa entre o rating atribuído por estas agências e a evolução da dívida pública, no sentido em que para períodos em que o rating desce, o crescimento da dívida é mais acentuado. Não nos foi, no entanto, possível atribuir um rating à dívida pública através de uma análise de percentis.

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Paper presented at Geo-Spatial Crossroad GI_Forum, Salzburg, Austria.

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de imagem em RM, caracterizada pela sua alta resolução espacial e grande sensibilidade a diferenças de susceptibilidade magnética dos tecidos, acentuando as propriedades paramagnéticas de produtos como a desoxihemoglobina, hemossiderina, ferro e cálcio e sendo particularmente útil na avaliação das estruturas venosas. Objectivos: O objectivo deste trabalho é fazer uma breve revisão das aplicações clínicas da sequência SWI em neuropediatria e demonstrar a sua grande utilidade, nomeadamente em comparação as a sequência T2*. Material e Métodos: Os exames foram realizados a crianças com idades compreendidas entre o período neonatal e os 16 anos, internadas ou seguidas em consulta no Hospital Pediátrico D. Estefânia; as imagens SWI foram efectuadas em equipamento Siemens 1.5 T, Avanto, com os seguintes parâmetros: TR 49, TE 40, flip angle 15, espessura 1,6mm. Resultados: Apresentamos vários casos ilustrativos de patologias em que o SWI demonstra a sua utilidade e mais-valia, nomeadamente na detecção de lesões hemorrágicas recentes ou antigas em diferentes contextos particulares em neuropediatria (patologia hipoxico-isquémica, vascular, trauma não acidental), detecção de cavernomas e anomalias venosas de desenvolvimento, avaliação de tumores e doenças neurodegenerativas. Conclusão: A sequência SWI é bastante útil na avaliação imagiológica de várias patologias e variantes venosas em neuropediatria, fornecendo uma informação adicional com implicações diagnósticas e prognósticas comparativamente com o T2*, obviando também a administração de contraste para avaliação de estruturas venosas.

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Multiparametric Magnetic Resonance Imaging has been increasingly used for detection, localization and staging of prostate cancer over the last years. It combines high-resolution T2 Weighted-Imaging and at least two functional techniques, which include Dynamic Contrast–Enhanced Magnetic Resonance Imaging, Diffusion-Weighted Imaging, and Magnetic Resonance Imaging Spectroscopy. Although the combined use of a pelvic phased-array and an Endorectal Coil is considered the state-of-the-art for Magnetic Resonance Imaging evaluation of prostate cancer, Endorectal Coil is only absolute mandatory for Magnetic Resonance Imaging Spectroscopy at 1.5 T. Sensitivity and specificity levels in cancer detection and localization have been improving with functional technique implementation, compared to T2 Weighted-Imaging alone. It has been particularly useful to evaluate patients with abnormal PSA and negative biopsy. Moreover, the information added by the functional techniques may correlate to cancer aggressiveness and therefore be useful to select patients for focal radiotherapy, prostate sparing surgery, focal ablative therapy and active surveillance. However, more studies are needed to compare the functional techniques and understand the advantages and disadvantages of each one. This article reviews the basic principles of prostatic mp-Magnetic Resonance Imaging, emphasizing its role on detection, staging and active surveillance of prostate cancer.

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Geographic information systems give us the possibility to analyze, produce, and edit geographic information. Furthermore, these systems fall short on the analysis and support of complex spatial problems. Therefore, when a spatial problem, like land use management, requires a multi-criteria perspective, multi-criteria decision analysis is placed into spatial decision support systems. The analytic hierarchy process is one of many multi-criteria decision analysis methods that can be used to support these complex problems. Using its capabilities we try to develop a spatial decision support system, to help land use management. Land use management can undertake a broad spectrum of spatial decision problems. The developed decision support system had to accept as input, various formats and types of data, raster or vector format, and the vector could be polygon line or point type. The support system was designed to perform its analysis for the Zambezi river Valley in Mozambique, the study area. The possible solutions for the emerging problems had to cover the entire region. This required the system to process large sets of data, and constantly adjust to new problems’ needs. The developed decision support system, is able to process thousands of alternatives using the analytical hierarchy process, and produce an output suitability map for the problems faced.

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Different oil-containing substrates, namely, used cooking oil (UCO), fatty acids-byproduct from biodiesel production (FAB) and olive oil deodorizer distillate (OODD) were tested as inexpensive carbon sources for the production of polyhydroxyalkanoates (PHA) using twelve bacterial strains, in batch experiments. The OODD and FAB were exploited for the first time as alternative substrates for PHA production. Among the tested bacterial strains, Cupriavidus necator and Pseudomonas resinovorans exhibited the most promising results, producing poly-3-hydroxybutyrate, P(3HB), form UCO and OODD and mcl-PHA mainly composed of 3-hydroxyoctanoate (3HO) and 3-hydroxydecanoate (3HD) monomers from OODD, respectively. Afterwards, these bacterial strains were cultivated in bioreactor. C. necator were cultivated in bioreactor using UCO as carbon source. Different feeding strategies were tested for the bioreactor cultivation of C. necator, namely, batch, exponential feeding and DO-stat mode. The highest overall PHA productivity (12.6±0.78 g L-1 day-1) was obtained using DO-stat mode. Apparently, the different feeding regimes had no impact on polymer thermal properties. However, differences in polymer‟s molecular mass distribution were observed. C. necator was also tested in batch and fed-batch modes using a different type of oil-containing substrate, extracted from spent coffee grounds (SCG) by super critical carbon dioxide (sc-CO2). Under fed-batch mode (DO-stat), the overall PHA productivity were 4.7 g L-1 day-1 with a storage yield of 0.77 g g-1. Results showed that SCG can be a bioresource for production of PHA with interesting properties. Furthermore, P. resinovorans was cultivated using OODD as substrate in bioreactor under fed-batch mode (pulse feeding regime). The polymer was highly amorphous, as shown by its low crystallinity of 6±0.2%, with low melting and glass transition temperatures of 36±1.2 and -16±0.8 ºC, respectively. Due to its sticky behavior at room temperature, adhesiveness and mechanical properties were also studied. Its shear bond strength for wood (67±9.4 kPa) and glass (65±7.3 kPa) suggests it may be used for the development of biobased glues. Bioreactor operation and monitoring with oil-containing substrates is very challenging, since this substrate is water immiscible. Thus, near-infrared spectroscopy (NIR) was implemented for online monitoring of the C. necator cultivation with UCO, using a transflectance probe. Partial least squares (PLS) regression was applied to relate NIR spectra with biomass, UCO and PHA concentrations in the broth. The NIR predictions were compared with values obtained by offline reference methods. Prediction errors to these parameters were 1.18 g L-1, 2.37 g L-1 and 1.58 g L-1 for biomass, UCO and PHA, respectively, which indicates the suitability of the NIR spectroscopy method for online monitoring and as a method to assist bioreactor control. UCO and OODD are low cost substrates with potential to be used in PHA batch and fed-batch production. The use of NIR in this bioprocess also opened an opportunity for optimization and control of PHA production process.

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Os estudos da satisfação e lealdade do cliente em ambiente Business-to-Business têm emergido devido ao interesse práctico e académico. Recorreu-se a um caso práctico de uma empresa de software internacional, ESRI, a operar em Portugal com modelo de negócio B2B e comportamento de compra extensivo. Desenvolveu-se um modelo estrutural com 11 variáveis latentes: lealdade; satisfação; imagem; atmosfera; cooperação; adaptação; processos; tecnologia; orientação ao cliente; competências; colaboradores e comunicação. Foram analisadas 304 respostas ao questionário de satisfação e de seguida aplicou-se o modelo a seis grupos de clientes segmentados de acordo com a contribuição do cliente para as receitas e o comportamento no processo de decisão de compra. Recorreu-se a modelos SEM (Structural Equation Modelling) com estimação dos parâmetros através da metodologia PLS (partial Least Squares). Os resultados mostram nos seis segmentos, que os valores da empresa, a cooperação através da competência dos colaboradores e da orientação ao cliente e a tecnologia são factores mais importantes para a satisfação e lealdade dos clientes.

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Mestrado em Contabilidade, Fiscalidade e Finanças Empresariais