5 resultados para Sensory fusion

em Universidade do Minho


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Olive oil quality grading is traditionally assessed by human sensory evaluation of positive and negative attributes (olfactory, gustatory, and final olfactorygustatory sensations). However, it is not guaranteed that trained panelist can correctly classify monovarietal extra-virgin olive oils according to olive cultivar. In this work, the potential application of human (sensory panelists) and artificial (electronic tongue) sensory evaluation of olive oils was studied aiming to discriminate eight single-cultivar extra-virgin olive oils. Linear discriminant, partial least square discriminant, and sparse partial least square discriminant analyses were evaluated. The best predictive classification was obtained using linear discriminant analysis with simulated annealing selection algorithm. A low-level data fusion approach (18 electronic tongue signals and nine sensory attributes) enabled 100 % leave-one-out cross-validation correct classification, improving the discrimination capability of the individual use of sensor profiles or sensory attributes (70 and 57 % leave-one-out correct classifications, respectively). So, human sensory evaluation and electronic tongue analysis may be used as complementary tools allowing successful monovarietal olive oil discrimination.

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This paper presents a methodology based on the Bayesian data fusion techniques applied to non-destructive and destructive tests for the structural assessment of historical constructions. The aim of the methodology is to reduce the uncertainties of the parameter estimation. The Young's modulus of granite stones was chosen as an example for the present paper. The methodology considers several levels of uncertainty since the parameters of interest are considered random variables with random moments. A new concept of Trust Factor was introduced to affect the uncertainty related to each test results, translated by their standard deviation, depending on the higher or lower reliability of each test to predict a certain parameter.

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A search for a charged Higgs boson, H±, decaying to a W± boson and a Z boson is presented. The search is based on 20.3 fb−1 of proton-proton collision data at a center-of-mass energy of 8 TeV recorded with the ATLAS detector at the LHC. The H± boson is assumed to be produced via vector-boson fusion and the decays W±→qq′¯ and Z→e+e−/μ+μ− are considered. The search is performed in a range of charged Higgs boson masses from 200 to 1000 GeV. No evidence for the production of an H± boson is observed. Upper limits of 31--1020 fb at 95% CL are placed on the cross section for vector-boson fusion production of an H± boson times its branching fraction to W±Z. The limits are compared with predictions from the Georgi-Machacek Higgs Triplet Model.

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Olive oils may be commercialized as intense, medium or light, according to the intensity perception of fruitiness, bitterness and pungency attributes, assessed by a sensory panel. In this work, the capability of an electronic tongue to correctly classify olive oils according to the sensory intensity perception levels was evaluated. Cross-sensitivity and non-specific lipid polymeric membranes were used as sensors. The sensor device was firstly tested using quinine monohydrochloride standard solutions. Mean sensitivities of 14±2 to 25±6 mV/decade, depending on the type of plasticizer used in the lipid membranes, were obtained showing the device capability for evaluating bitterness. Then, linear discriminant models based on sub-sets of sensors, selected by a meta-heuristic simulated annealing algorithm, were established enabling to correctly classify 91% of olive oils according to their intensity sensory grade (leave-one-out cross-validation procedure). This capability was further evaluated using a repeated K-fold cross-validation procedure, showing that the electronic tongue allowed an average correct classification of 80% of the olive oils used for internal-validation. So, the electronic tongue can be seen as a taste sensor, allowing differentiating olive oils with different sensory intensities, and could be used as a preliminary, complementary and practical tool for panelists during olive oil sensory analysis.

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Up to 20% of patients with pilocytic astrocytoma (PA) experience a poor outcome. BRAF alterations and Fibroblast growth factor receptor 1 (FGFR1) point mutations are key molecular alterations in Pas, but their clinical implications are not established. We aimed to determine the frequency and prognostic role of these alterations in a cohort of 69 patients with PAs. We assessed KIAA1549:BRAF fusion by fluorescence in situ hybridization and BRAF (exon 15) mutations by capillary sequencing. In addition, FGFR1 expression was analyzed using immunohistochemistry, and this was compared with gene amplification and hotspot mutations (exons 12 and 14) assessed by fluorescence in situ hybridization and capillary sequencing. KIAA1549:BRAF fusion was identified in almost 60% of cases. Two tumors harbored mutated BRAF. Despite high FGFR1 expression overall, no cases had FGFR1 amplifications. Three cases harbored a FGFR1 p.K656E point mutation. No correlation was observed between BRAF and FGFR1 alterations. The cases were predominantly pediatric (87%), and no statistical differences were observed in molecular alterations-related patient ages. In summary, we confirmed the high frequency of KIAA1549:BRAF fusion in PAs and its association with a better outcome. Oncogenic mutations of FGFR1, although rare, occurred in a subset of patients with worse outcome. These molecular alterations may constitute alternative targets for novel clinical approaches, when radical surgical resection is unachievable.