885 resultados para fuzzy based evaluation method


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The active ingredients used in the formulation of toxic baits for leaf-cutting ants (Hymenoptera: Formicidae) should possess a delayed action defined as an insecticidal activity whereby worker mortality is ≤15% at 24 hours and ≥90% at 21 days. Serious shortcomings have occurred in the search for new active ingredients, such as the initial selection of fenoxycarb, copper oxychloride and diflubenzuron, compounds considered very promising but whose inefficiency was verified only later, indicating methodological problems. In view of this situation, we developed a classification method for insecticidal activity over time using workers of the leaf-cutting ant Atta sexdens rubropilosa Forel. The insecticides used were fipronil, sulfluramid GX071HB and sulfluramid GX439, vehicled in an attractive pasty formulation prepared based on citrus pulp. The results obtained were consistent from a toxicological viewpoint and agreed with the literature in terms of the control of colonies. Sulfluramids were found to possess a delayed action at a broad range of concentrations, in agreement with the fact that these substances are highly effective in the control of all leaf-cutting ant species. The smaller range of concentrations of fipronil with delayed action is probably related to its lower efficacy for species more difficult to control such as Atta capiguara (Forti et al. 2003). We discuss the importance of relating behavioral particularities to the specific feeding habits of leaf-cutting ants, with methodological adequacy of the assessment of insecticides aimed at toxic baits.

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Bioceramic systems based on hydroxylapatite (HAP) are an important class of bioactive materials that may promote bone regeneration. The aim of this research was to evaluate how the stoichiometry of HAP influences its microstructural properties when diagnosed using the combined Rietveld method and Maximum entropy method (MEM). The Rietveld Method (RM) is recognizably a powerful tool used to obtain structural and microstructural information of polycrystalline samples analyzed by x-ray diffraction. Latterly have combined the RM with the maximum entropy method (MEM), with the goal of improve structural refinement results. The MEM provides high resolution maps of electron density and their analysis leave the accurate localization of atoms inside of unit cell. Like that, cycles Rietveld-MEM allow an excellent structural refinement In this work, a hydroxylapatite sample obtained by emulsion method had its structure refined using one cycle Rietveld-MEM with x-ray diffraction data. The indices obtained in initial refinement was Rwp = 7.50%, Re = 6.56%, S - 1.14% e RB = 1.03%. After MEM refinement and electron densities maps analysis to correction of atomics positions, the news indicators of Rietveld refinement quality was Rwp = 7.35%, Re = 6.56%, S = 1.12% and RB = 0.75%. The excellent result obtained to RB shows the efficiency of MEM as auxiliary in the refinement of structure of hydroxylapatite by RM.

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A comparative study, with theoretical analysis and digital simulations, of two conditions based on LMI for the quadratic stability of nonlinear continuous-time dynamic systems, described by Takagi-Sugeno fuzzy models, are presented. This paper shows that the methods proposed by Teixeira et. al. in 2003 provide better or at least the same results of a recent method presented in the literature. © 2005 IEEE.

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This work develops two approaches based on the fuzzy set theory to solve a class of fuzzy mathematical optimization problems with uncertainties in the objective function and in the set of constraints. The first approach is an adaptation of an iterative method that obtains cut levels and later maximizes the membership function of fuzzy decision making using the bound search method. The second one is a metaheuristic approach that adapts a standard genetic algorithm to use fuzzy numbers. Both approaches use a decision criterion called satisfaction level that reaches the best solution in the uncertain environment. Selected examples from the literature are presented to compare and to validate the efficiency of the methods addressed, emphasizing the fuzzy optimization problem in some import-export companies in the south of Spain. © 2012 Brazilian Operations Research Society.

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Pós-graduação em Agronomia (Energia na Agricultura) - FCA

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Introduction: Alkalinization potential is a fundamental property of endodontic epoxy-based cements containing calcium hydroxide. Studies have shown discrepant pH results for same materials at different evaluation periods. A possible reason accounting for these differences may be the assessment procedures. Objective: To evaluate the pH value of an epoxy-based cement (Sealer 26) in different periods of analysis, using two assessment methods. Material and methods: Sealer 26 was manipulated and immediately placed into polyethylene tubes (n=10, each group) and immersed in distilled water. In G1, the tubes were kept in the same water during all experiment; and in G2, the tubes were removed and placed into another flask with an equal amount of water after the pH evaluation. The pH of these solutions was measured at 24 hours, 7, 14 and 28 days. Analysis were made within the same group according to the experimental periods and between groups in each experimental period. Data were submitted to ANOVA (α = 5%) and t test, respectively. Results: For G1 and G2, all periods showed different pH values (p < 0.05), except between 14 and 28 days (p > 0.05) and between 7 and 14 days (p > 0.05), respectively. In each period, no significant differences were observed between the groups. Conclusion: The method to obtain the pH values in different experimental periods no interfered in the final results. However, difference was observed when the results were analyzed at same group.

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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This paper presents an optimum user-steered boundary tracking approach for image segmentation, which simulates the behavior of water flowing through a riverbed. The riverbed approach was devised using the image foresting transform with a never-exploited connectivity function. We analyze its properties in the derived image graphs and discuss its theoretical relation with other popular methods such as live wire and graph cuts. Several experiments show that riverbed can significantly reduce the number of user interactions (anchor points), as compared to live wire for objects with complex shapes. This paper also includes a discussion about how to combine different methods in order to take advantage of their complementary strengths.

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Lipid peroxidation (LPO) has been associated with periodontal disease, and the evaluation of malondialdehyde (MDA) in the gingival crevicular fluid (GCF), an inflammatory exudate from the surrounding tissue of the periodontium, may be useful to clarify the role of LPO in the pathogenesis of periodontal disease. We describe the validation of a method to measure MDA in the GCF using high-performance liquid chromatography. MDA calibration curves were prepared with phosphate-buffered solution spiked with increasing known concentrations of MDA. Healthy and diseased GCF samples were collected from the same patient to avoid interindividual variability. MDA response was linear in the range measured, and excellent agreement was observed between added and detected concentrations of MDA. Samples' intra- and interday coefficients of variation were below 6.3% and 12.4%, respectively. The limit of quantitation (signal/noise = 5) was 0.03 mu M. When the validated method was applied to the GCF, excellent agreement was observed in the MDA quantitation from healthy and diseased sites, and diseased sites presented more MDA than healthy sites (P < 0.05). In this study, a validated method for MDA quantitation in GCF was established with satisfactory sensitivity, precision, and accuracy. (C) 2012 Elsevier Inc. All rights reserved.

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Abstract Background Spotted cDNA microarrays generally employ co-hybridization of fluorescently-labeled RNA targets to produce gene expression ratios for subsequent analysis. Direct comparison of two RNA samples in the same microarray provides the highest level of accuracy; however, due to the number of combinatorial pair-wise comparisons, the direct method is impractical for studies including large number of individual samples (e.g., tumor classification studies). For such studies, indirect comparisons using a common reference standard have been the preferred method. Here we evaluated the precision and accuracy of reconstructed ratios from three indirect methods relative to ratios obtained from direct hybridizations, herein considered as the gold-standard. Results We performed hybridizations using a fixed amount of Cy3-labeled reference oligonucleotide (RefOligo) against distinct Cy5-labeled targets from prostate, breast and kidney tumor samples. Reconstructed ratios between all tissue pairs were derived from ratios between each tissue sample and RefOligo. Reconstructed ratios were compared to (i) ratios obtained in parallel from direct pair-wise hybridizations of tissue samples, and to (ii) reconstructed ratios derived from hybridization of each tissue against a reference RNA pool (RefPool). To evaluate the effect of the external references, reconstructed ratios were also calculated directly from intensity values of single-channel (One-Color) measurements derived from tissue sample data collected in the RefOligo experiments. We show that the average coefficient of variation of ratios between intra- and inter-slide replicates derived from RefOligo, RefPool and One-Color were similar and 2 to 4-fold higher than ratios obtained in direct hybridizations. Correlation coefficients calculated for all three tissue comparisons were also similar. In addition, the performance of all indirect methods in terms of their robustness to identify genes deemed as differentially expressed based on direct hybridizations, as well as false-positive and false-negative rates, were found to be comparable. Conclusion RefOligo produces ratios as precise and accurate as ratios reconstructed from a RNA pool, thus representing a reliable alternative in reference-based hybridization experiments. In addition, One-Color measurements alone can reconstruct expression ratios without loss in precision or accuracy. We conclude that both methods are adequate options in large-scale projects where the amount of a common reference RNA pool is usually restrictive.

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Background Genotyping of hepatitis C virus (HCV) has become an essential tool for prognosis and prediction of treatment duration. The aim of this study was to compare two HCV genotyping methods: reverse hybridization line probe assay (LiPA v.1) and partial sequencing of the NS5B region. Methods Plasma of 171 patients with chronic hepatitis C were screened using both a commercial method (LiPA HCV Versant, Siemens, Tarrytown, NY, USA) and different primers targeting the NS5B region for PCR amplification and sequencing analysis. Results Comparison of the HCV genotyping methods showed no difference in the classification at the genotype level. However, a total of 82/171 samples (47.9%) including misclassification, non-subtypable, discrepant and inconclusive results were not classified by LiPA at the subtype level but could be discriminated by NS5B sequencing. Of these samples, 34 samples of genotype 1a and 6 samples of genotype 1b were classified at the subtype level using sequencing of NS5B. Conclusions Sequence analysis of NS5B for genotyping HCV provides precise genotype and subtype identification and an accurate epidemiological representation of circulating viral strains.

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The diagnosis, grading and classification of tumours has benefited considerably from the development of DCE-MRI which is now essential to the adequate clinical management of many tumour types due to its capability in detecting active angiogenesis. Several strategies have been proposed for DCE-MRI evaluation. Visual inspection of contrast agent concentration curves vs time is a very simple yet operator dependent procedure, therefore more objective approaches have been developed in order to facilitate comparison between studies. In so called model free approaches, descriptive or heuristic information extracted from time series raw data have been used for tissue classification. The main issue concerning these schemes is that they have not a direct interpretation in terms of physiological properties of the tissues. On the other hand, model based investigations typically involve compartmental tracer kinetic modelling and pixel-by-pixel estimation of kinetic parameters via non-linear regression applied on region of interests opportunely selected by the physician. This approach has the advantage to provide parameters directly related to the pathophysiological properties of the tissue such as vessel permeability, local regional blood flow, extraction fraction, concentration gradient between plasma and extravascular-extracellular space. Anyway, nonlinear modelling is computational demanding and the accuracy of the estimates can be affected by the signal-to-noise ratio and by the initial solutions. The principal aim of this thesis is investigate the use of semi-quantitative and quantitative parameters for segmentation and classification of breast lesion. The objectives can be subdivided as follow: describe the principal techniques to evaluate time intensity curve in DCE-MRI with focus on kinetic model proposed in literature; to evaluate the influence in parametrization choice for a classic bi-compartmental kinetic models; to evaluate the performance of a method for simultaneous tracer kinetic modelling and pixel classification; to evaluate performance of machine learning techniques training for segmentation and classification of breast lesion.

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Dysfunction of Autonomic Nervous System (ANS) is a typical feature of chronic heart failure and other cardiovascular disease. As a simple non-invasive technology, heart rate variability (HRV) analysis provides reliable information on autonomic modulation of heart rate. The aim of this thesis was to research and develop automatic methods based on ANS assessment for evaluation of risk in cardiac patients. Several features selection and machine learning algorithms have been combined to achieve the goals. Automatic assessment of disease severity in Congestive Heart Failure (CHF) patients: a completely automatic method, based on long-term HRV was proposed in order to automatically assess the severity of CHF, achieving a sensitivity rate of 93% and a specificity rate of 64% in discriminating severe versus mild patients. Automatic identification of hypertensive patients at high risk of vascular events: a completely automatic system was proposed in order to identify hypertensive patients at higher risk to develop vascular events in the 12 months following the electrocardiographic recordings, achieving a sensitivity rate of 71% and a specificity rate of 86% in identifying high-risk subjects among hypertensive patients. Automatic identification of hypertensive patients with history of fall: it was explored whether an automatic identification of fallers among hypertensive patients based on HRV was feasible. The results obtained in this thesis could have implications both in clinical practice and in clinical research. The system has been designed and developed in order to be clinically feasible. Moreover, since 5-minute ECG recording is inexpensive, easy to assess, and non-invasive, future research will focus on the clinical applicability of the system as a screening tool in non-specialized ambulatories, in order to identify high-risk patients to be shortlisted for more complex investigations.