870 resultados para Classifier Generalization Ability


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The present investigation observed the sealing ability of low shrinkage composite resins in large and deep cavities, placed and photocured in one increment. Large, deep cavities (5.0 mm diameter and 2.5 mm deep) surrounded by enamel were prepared in bovine teeth, which were then divided into five groups. Groups 1, 2, 3 and 4: acid conditioning + Adper Single Bond (3M/ESPE, St Paul, MN, USA) and restoration with Aelite LS Posterior (BISCO Inc. Schaumburg, IL, USA) (G1); Filtek Z-350 (3M/ESPE,St Paul, MN, USA) (G2); Filtek Z-350 Flow (3M/ESPE, St Paul, MN, USA) (G3); Premisa (KERR Corporation, Orange, CA, USA) (G4). Group 5: Silorane Adhesive system (3M/ESPE, St Paul, MN, USA) + restoration with Filtek Low Shrinkage Posterior P90 (3M/ESPE, St Paul, MN, USA). After polymerization, the teeth were immersed in 0.5% basic fuchsine solution and immediately washed. Using the Imagetool Software, the extent of dye along the margins was calculated as a percentage of total perimeter. The restorations were then transversally sectioned and the depth of dye penetration was calculated in mm, using the same software. Kruskal-Wallis analysis for all groups showed no statistical differences for extent (p = 0.54) or depth (p = 0.8364) of dye penetration. According to this methodology, the so-called low shrinkage composite resins had the same sealing ability compared to regular and flowable nanocomposite materials.

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A predição do preço da energia elétrica é uma questão importante para todos os participantes do mercado, para que decidam as estratégias mais adequadas e estabeleçam os contratos bilaterais que maximizem seus lucros e minimizem os seus riscos. O preço da energia tipicamente exibe sazonalidade, alta volatilidade e picos. Além disso, o preço da energia é influenciado por muitos fatores, tais como: demanda de energia, clima e preço de combustíveis. Este trabalho propõe uma nova abordagem híbrida para a predição de preços de energia no mercado de curto prazo. Tal abordagem combina os filtros autorregressivos integrados de médias móveis (ARIMA) e modelos de Redes Neurais (RNA) numa estrutura em cascata e utiliza variáveis explanatórias. Um processo em dois passos é aplicado. Na primeira etapa, as variáveis explanatórias são preditas. Na segunda etapa, os preços de energia são preditos usando os valores futuros das variáveis exploratórias. O modelo proposto considera uma predição de 12 passos (semanas) a frente e é aplicada ao mercado brasileiro, que possui características únicas de comportamento e adota o despacho centralizado baseado em custo. Os resultados mostram uma boa capacidade de predição de picos de preço e uma exatidão satisfatória de acordo com as medidas de erro e testes de perda de cauda quando comparado com técnicas tradicionais. Em caráter complementar, é proposto um modelo classificador composto de árvores de decisão e RNA, com objetivo de explicitar as regras de formação de preços e, em conjunto com o modelo preditor, atuar como uma ferramenta atrativa para mitigar os riscos da comercialização de energia.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Three culture media (Brucella agar, Farrell medium, and CITA) were compared for their effectiveness in inhibiting contamination and for isolating Brucella spp. One hundred lymph nodes from pigs (n = 50) and wild boars (n = 50) with lymphadenitis were collected in slaughterhouses in the State of Sao Paulo and were assessed on these three selective media for Brucella spp. All of the samples were negative for Brucella spp. on the three culture media. On the agar medium, fungal (70 plates) and Gram-positive bacterial (59 plates) contaminants were observed; in the CITA medium, the absence of fungal and Gram-positive bacteria on 15 plates was observed; no bacterial or fungal growth was observed on the Farrell media. The results demonstrated that the CITA and Farrell media inhibited the growth of contaminants better than the Brucella agar.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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In general, pattern recognition techniques require a high computational burden for learning the discriminating functions that are responsible to separate samples from distinct classes. As such, there are several studies that make effort to employ machine learning algorithms in the context of big data classification problems. The research on this area ranges from Graphics Processing Units-based implementations to mathematical optimizations, being the main drawback of the former approaches to be dependent on the graphic video card. Here, we propose an architecture-independent optimization approach for the optimum-path forest (OPF) classifier, that is designed using a theoretical formulation that relates the minimum spanning tree with the minimum spanning forest generated by the OPF over the training dataset. The experiments have shown that the approach proposed can be faster than the traditional one in five public datasets, being also as accurate as the original OPF. (C) 2014 Elsevier B. V. All rights reserved.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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In this letter, a speech recognition algorithm based on the least-squares method is presented. Particularly, the intention is to exemplify how such a traditional numerical technique can be applied to solve a signal processing problem that is usually treated by using more elaborated formulations.

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This article presents some results of a study investigating the use of the simulator VLAB, developed by Carnegie Mellon University, to increase the capacity of graduate students in Chemistry in the preparation of experimental procedures. The activity was conducted in two stages, first the students were asked a manuscript describing in detail the procedure and equipment used in the technique of dissolution and delivering it to the teacher. Later in the computer lab, each student performed the same procedure using the simulator. The activity has been proposed to determine if there could be accuracy gains of the description of the process when performed by the simulator. One of the main positive aspects obtained using the simulator students was the recognition of error, important in that the great majority recognized omitted or confused any process step. This reflection showed the students that in addition to testing a procedure using the simulator facilitates the organization of thought and helps arrange it logically. With the use of simulators, students are encouraged to take risks, to explore, to experience a new way, and a real lab usually offers much less room for risk, exploitation and failure.

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Nickel-titanium rotatory systems should remove dentin during the root canal preparation to promote the enlargement and tapered shape with continuously narrowing towards the apex. Objective: The aim of this study was to analyze the cutting ability of three NiTi rotatory systems (n = 12): ProTaper (group 1), Mtwo (group 2), and K3 (group 3). Material and methods: Thirty six maxillary molar teeth were weighted on an analytical balance before and after the rotatory preparation of the mesio-buccal root canal. Data was statistically analyzed by ANOVA and Tukey s test with a significance level of 5%. Results: The results revealed the following mass differences (g) before and after the root canal preparation: ProTaper (group 1 – 0.0159 ± 0.004), Mtwo (group 2 – 0.0125 ± 0.002), and K3 (group 3 – 0.007 ± 0.003). Conclusion: ProTaper showed the highest cutting ability among the three tested nickel-titanium rotatory systems followed by Mtwo and K3.

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The Mineral Trioxide Aggregate (MTA) has excellent biological property. However, its consistency makes it difficult to be inserted into retrograde cavities. Objective:To evaluate the ability of different methods to fill retrograde cavities with MTA. Material and methods: Root canals of thirty single-rooted resin teeth were prepared and filled. After the cut of 3 mm short of apical third, retrograde cavities with 3 mm deep were prepared using an ultrasound device and retrotips (CVD, São José dos Campos, SP, Brazil). The retrograde preparation was evaluate by using an operative microscope (D.F. Vasconcellos, São Paulo, SP, Brazil). The teeth were randomly divided into three groups (n = 10), according to the method: 1) condenser (Trinity, São Paulo, SP, Brazil); 2) MTA applicator (Angelus, Londrina, Brazil) + condenser; 3) condenser associated with ultrasound (CVD, São José dos Campos, SP, Brazil). After the filling of retrograde cavities with white MTA (Angelus, Londrina, Brazil), teeth were radiographed using a digital system (Kodak RVG 6000, Rochester, NY, USA). The images were analyzed by UTHSCSA Image Tool 3.0 software. The percentage of filling was calculated by the proportion between the total area of retrograde cavity and the filled area. The radiographic density mean of each third of retrograde cavity filled with MTA was measured by using the histogram tool of the software. The results were submitted to ANOVA and Tukey tests, with 5% of significance. Results: There was no difference in percentage of filling among the groups (p > 0.05) (approximately 85%). By comparing the thirds, the condenser and MTA applicator groups showed higher density for apical and middle third than cervical third (p < 0.05). The ultrasound group presented similar density among the thirds. Conclusion: The filling ability was similar for the studied methods. Ultrasound promoted better distribution of MTA in retrograde cavity, but did not increase the density of material.

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)