14 resultados para Clustering and objective measures

em Repositório Científico do Instituto Politécnico de Lisboa - Portugal


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In data clustering, the problem of selecting the subset of most relevant features from the data has been an active research topic. Feature selection for clustering is a challenging task due to the absence of class labels for guiding the search for relevant features. Most methods proposed for this goal are focused on numerical data. In this work, we propose an approach for clustering and selecting categorical features simultaneously. We assume that the data originate from a finite mixture of multinomial distributions and implement an integrated expectation-maximization (EM) algorithm that estimates all the parameters of the model and selects the subset of relevant features simultaneously. The results obtained on synthetic data illustrate the performance of the proposed approach. An application to real data, referred to official statistics, shows its usefulness.

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Background: Computed tomography (CT) is one of the most used modalities for diagnostics in paediatric populations, which is a concern as it also delivers a high patient dose. Research has focused on developing computer algorithms that provide better image quality at lower dose. The iterative reconstruction algorithm Sinogram-Affirmed Iterative Reconstruction (SAFIRE) was introduced as a new technique that reduces noise to increase image quality. Purpose: The aim of this study is to compare SAFIRE with the current gold standard, Filtered Back Projection (FBP), and assess whether SAFIRE alone permits a reduction in dose while maintaining image quality in paediatric head CT. Methods: Images were collected using a paediatric head phantom using a SIEMENS SOMATOM PERSPECTIVE 128 modulated acquisition. 54 images were reconstructed using FBP and 5 different strengths of SAFIRE. Objective measures of image quality were determined by measuring SNR and CNR. Visual measures of image quality were determined by 17 observers with different radiographic experiences. Images were randomized and displayed using 2AFC; observers scored the images answering 5 questions using a Likert scale. Results: At different dose levels, SAFIRE significantly increased SNR (up to 54%) in the acquired images compared to FBP at 80kVp (5.2-8.4), 110kVp (8.2-12.3), 130kVp (8.8-13.1). Visual image quality was higher with increasing SAFIRE strength. The highest image quality was scored with SAFIRE level 3 and higher. Conclusion: The SAFIRE algorithm is suitable for image noise reduction in paediatric head CT. Our data demonstrates that SAFIRE enhances SNR while reducing noise with a possible reduction of dose of 68%.

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Background - For dose reduction actions, the principle of “image quality as good as possible” to “image quality as good as needed” requires to know whether the physical measures and visual image quality relate. Visual evaluation and objective physical measures of image quality can appear to be different. If there is no noticeable effect on the visual image quality with a low dose but there is a objective physical measure impact, then the overall dose may be reduced without compromising the diagnostic image quality. Low dose imaging can be used for certain types of observations, e.g. thoracic scoliosis, control after metal implantation for osteosynthesis, reviewing pneumonia and tuberculosis. Aim of the study - To determine whether physical measures of noise predict visual (clinical) image quality at low dose levels.

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O objectivo pretendido alcançar é o de obter uma redução nos consumos de energia eléctrica do Município de Vila Franca de Xira, recorrendo à URE. Esta URE consiste num conjunto de acções e/ou medidas e/ou procedimentos e/ou equipamentos cuja aplicação tem como fim, o de potenciar uma utilização e uma gestão mais racional e rentável da energia - daí se podendo dizer, cada vez mais, que a mesma é um factor essencial de economia energética, logo, de redução de custos. A aplicação destas acções e/ou medidas e/ou procedimentos e/ou equipamentos deverá, por isso, ser extensível aos Municípios, com o fim de fazer reduzir uma factura energética de grande peso e significado, a qual, em tempos que são de profunda crise económica, pode tornar problemático ou até mesmo hipotecar, o respectivo futuro. Assim e se por um lado existe no Município um conjunto alargado de situações estabelecidas sem critérios de racionabilidade energética e ás quais, todavia, é já possível fazer aplicar essas acções e/ou medidas e/ou procedimentos e/ou equipamentos de URE, por outro lado, é daí garantido que se poderá alcançar a pretendida redução dos consumos energéticos do Município, sempre assegurando e mantendo o conforto e a produtividade das actividades dependentes dessa energia. Com esse objectivo e partindo da análise de um conjunto de instalações e/ou equipamentos já existentes ou com possibilidades de virem a ser estabelecidas/os pelo Município, é pretendido definir, estudar e classificar, um conjunto de dados que tendam a desenvolver, potenciar e justificar a decisão da sua aplicação. Um conjunto alargado de exemplos práticos ou Casos de Estudo serão desenvolvidos, tentando chegar a conclusões sobre a viabilidade económica das soluções apresentadas e, daí, da decisão da oportunidade da execução do conjunto de trabalhos inerentes à aplicação desse tipo de situação.

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Aspergillus is among a growing list of allergens that aggravate asthmatic responses. Significant pulmonary pathology is associated with Aspergillus-induced allergic and asthmatic lung disease. Environments with high levels of exposure to fungi are found in animal production facilities such as for swine and poultry, and farmers working with these are at increased risk for occupational respiratory diseases. Seven Portuguese poultry and seven swine farms were analyzed in order to estimate the prevalence, amount, and distribution of Aspergillus species, as well as to determine the presence of clinical symptoms associated with asthma and other allergy diseases in these highly contaminated settings. From the collected fungal isolates (699), an average incidence of 22% Aspergillus was detected in poultry farms, while the prevalence at swine farms was 14%. The most frequently isolated Aspergillus species were A. versicolor, A. flavus, and A. fumigatus. In poultry farms, A. flavus presented the highest level of airborne spores (>2000 CFU/m3), whereas in swine farms the highest was A. versicolor, with an incidence fourfold greater higher than the other mentioned species. Eighty workers in these settings were analyzed, ranging in age from 17 to 93 yr. The potentially hazardous exposure of poultry workers to mold allergens using sensitization markers was evaluated. Although no significant positive association was found between fungal contamination and sensitization to fungal antigens, a high incidence of respiratory symptoms in professionals without asthma was observed, namely, wheezing associated with dyspnea (23.8%) and dyspnea after strenuous activities (12.3%), suggesting underdiagnosed respiratory disturbances. Further, 32.5% of all exposed workers noted an improvement of respiratory ability during resting and holidays. From all the analyzed workers, seven were previously diagnosed with asthma and four reported the first attack after the age of 40 yr, which may be associated with their occupational exposure. Some of the fungi, namely, the Aspergillus species detected in this study, are known to induce hypersensitivity reactions in humans. This study confirmed the presence and distribution of Aspergillus in Portuguese poultry and swine farms, suggesting a possible occupational health problem and raising the need for preventive and protective measures to apply to avoid exposure in both occupational settings.

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Organic waste is a rich substrate for microbial growth, and because of that, workers from waste industry are at higher risk of exposure to bioaerosols. This study aimed to assess fungal contamination in two plants handling solid waste management. Air samples from the two plants were collected through an impaction method. Surface samples were also collected by swabbing surfaces of the same indoor sites. All collected samples were incubated at 27◦C for 5 to 7 d. After lab processing and incubation of collected samples, quantitative and qualitative results were obtained with identification of the isolated fungal species. Air samples were also subjected to molecular methods by real-time polymerase chain reaction (RT PCR) using an impinger method to measure DNA of Aspergillus flavus complex and Stachybotrys chartarum. Assessment of particulate matter (PM) was also conducted with portable direct-reading equipment. Particles concentration measurement was performed at five different sizes (PM0.5; PM1; PM2.5; PM5; PM10). With respect to the waste sorting plant, three species more frequently isolated in air and surfaces were A. niger (73.9%; 66.1%), A. fumigatus (16%; 13.8%), and A. flavus (8.7%; 14.2%). In the incineration plant, the most prevalent species detected in air samples were Penicillium sp. (62.9%), A. fumigatus (18%), and A. flavus (6%), while the most frequently isolated in surface samples were Penicillium sp. (57.5%), A. fumigatus (22.3%) and A. niger (12.8%). Stachybotrys chartarum and other toxinogenic strains from A. flavus complex were not detected. The most common PM sizes obtained were the PM10 and PM5 (inhalable fraction). Since waste is the main internal fungal source in the analyzed settings, preventive and protective measures need to be maintained to avoid worker exposure to fungi and their metabolites.

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Clinical and environmental samples from Portugal were screened for the presence of Aspergillus and the distributions of the species complexes were determined in order to understand how their distributions differ based on their source. Fifty-seven Aspergillus isolates from clinical samples were collected from 10 health institutions. Six species complexes were detected by internal transcribed spacer sequencing; Fumigati, Flavi, and Nigri were found most frequently (50.9%, 21.0%, and 15.8%, respectively). β-tubulin and calmodulin sequencing resulted in seven cryptic species (A. awamorii, A. brasiliensis, A. fructus, A. lentulus, A. sydowii, A. tubingensis, Emericella echinulata) being identified among the 57 isolates. Thirty-nine isolates of Aspergillus were recovered from beach sand and poultry farms, 31 from swine farms, and 80 from hospital environments, for a total 189 isolates. Eleven species complexes were found in these 189 isolates, and those belonging to the Versicolores species complex were found most frequently (23.8%). There was a significant association between the different environmental sources and distribution of the species complexes; the hospital environment had greater variability of species complexes than other environmental locations. A high prevalence of cryptic species within the Circumdati complex was detected in several environments; from the isolates analyzed, at least four cryptic species were identified, most of them growing at 37ºC. Because Aspergillus species complexes have different susceptibilities to antifungals, knowing the species-complex epidemiology for each setting, as well as the identification of cryptic species among the collected clinical isolates, is important. This may allow preventive and corrective measures to be taken, which may result in decreased exposure to those organisms and a better prognosis.

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Research on cluster analysis for categorical data continues to develop, new clustering algorithms being proposed. However, in this context, the determination of the number of clusters is rarely addressed. We propose a new approach in which clustering and the estimation of the number of clusters is done simultaneously for categorical data. We assume that the data originate from a finite mixture of multinomial distributions and use a minimum message length criterion (MML) to select the number of clusters (Wallace and Bolton, 1986). For this purpose, we implement an EM-type algorithm (Silvestre et al., 2008) based on the (Figueiredo and Jain, 2002) approach. The novelty of the approach rests on the integration of the model estimation and selection of the number of clusters in a single algorithm, rather than selecting this number based on a set of pre-estimated candidate models. The performance of our approach is compared with the use of Bayesian Information Criterion (BIC) (Schwarz, 1978) and Integrated Completed Likelihood (ICL) (Biernacki et al., 2000) using synthetic data. The obtained results illustrate the capacity of the proposed algorithm to attain the true number of cluster while outperforming BIC and ICL since it is faster, which is especially relevant when dealing with large data sets.

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Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Química e Biológica

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Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Civil na Área de Especialização de Edificações

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Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Civil na Área de Especialização de Hidráulica

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Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Mecânica

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This paper describes the use of a Control Banding Tool to assess and further control of exposure of nanoparticles emitted during welding operations. The tool was applied to Metal Active Gas (MAG) arc welding of mild and stainless steel, providing semi-quantitative data on the process, so that protection measures could be derived, e.g. exhaust gas ventilation by hoods, local ventilation devices and containment measures. This tool is quite useful to compare and evaluate the characteristics of arc welding procedures so that more eco-friendly processes could be preferred over the more potentially noxious ones.

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The main result of this work is a new criterion for the formation of good clusters in a graph. This criterion uses a new dynamical invariant, the performance of a clustering, that characterizes the quality of the formation of clusters. We prove that the growth of the dynamical invariant, the network topological entropy, has the effect of worsening the quality of a clustering, in a process of cluster formation by the successive removal of edges. Several examples of clustering on the same network are presented to compare the behavior of other parameters such as network topological entropy, conductance, coefficient of clustering and performance of a clustering with the number of edges in a process of clustering by successive removal.