Monovarietal extra-virgin olive oil classification: a fusion of human sensory attributes and an electronic tongue

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.

Texture analysis and classification using deterministic tourist walk

In this paper, we present a study on a deterministic partially self-avoiding walk (tourist walk), which provides a novel method for texture feature extraction. The method is able to explore an image on all scales simultaneously. Experiments were conducted using different dynamics concerning the tourist walk. A new strategy, based on histograms. to extract information from its joint probability distribution is presented. The promising results are discussed and compared to the best-known methods for texture description reported in the literature. (C) 2009 Elsevier Ltd. All rights reserved.

Texture analysis using graphs generated by deterministic partially self-avoiding walks

Texture is one of the most important visual attributes for image analysis. It has been widely used in image analysis and pattern recognition. A partially self-avoiding deterministic walk has recently been proposed as an approach for texture analysis with promising results. This approach uses walkers (called tourists) to exploit the gray scale image contexts in several levels. Here, we present an approach to generate graphs out of the trajectories produced by the tourist walks. The generated graphs embody important characteristics related to tourist transitivity in the image. Computed from these graphs, the statistical position (degree mean) and dispersion (entropy of two vertices with the same degree) measures are used as texture descriptors. A comparison with traditional texture analysis methods is performed to illustrate the high performance of this novel approach. (C) 2011 Elsevier Ltd. All rights reserved.

Sistema eletro-eletrônico para medição direta de torque em dispositivos girantes utilizando extensômetros de resistência elétrica

Neste trabalho propõe-se um sistema para medição de torque em dispositivos girantes, que utiliza extensômetros de resistência elétrica colados nos próprios elementos constituintes do arranjo mecânico sob análise. Um conjunto de circuitos eletrônicos foi especialmente desenvolvido para o sensoreamento das pequenas deformações que ocorrem nos disposotivos girantes. O sistema opera sem contato eletro-mecânico entre a parte estacionária e a parte girante. Para tanto desenvolveu-se também uma metodologia de projeto e construção de transformadores rotativos que são utilizados para transferência da energia que alimenta os circuitos eletrônicos solidários ao elemento mecânico instrumentado. Também foi necessário utilizar um transmissor em freqüência modulada do sinal elétrico proporcional ao torque medido. Uma análise comparativa, dos resultados obtidos entre os sistemas existentes e aqueles alcançados com a técnica proposta neste trabalho, demonstra sua aplicabilidade em diversas situações práticas.

HOPF BIFURCATION FROM LINES of EQUILIBRIA WITHOUT PARAMETERS IN MEMRISTOR OSCILLATORS

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Preparação de resinas de poliuretana à base de óleo de mamona e dietanolamina

The aim of this work was the preparation of polyols from reactions between castor oil and dietanolamine to increase the hydroxyl content and the network degree in the products to application in electronic devices. The polyols and the mixtures obtained were characterized by nuclear magnetic ressonance. Castor oil (CO) is a natural triglyceride - based polyol possessing hydroxyl groups, which allow several reactions that produce many different products. Among them are the polyurethanes (PU), which have been considered an ideal product for the covering of electricelectronic circuits, due to their excellent electrical, shock-absorbing, solvents resistance and hydrolytic stability properties. About 90% of the fatty acids present in the castor oil are ricinoleic acid (12-hydroxyoleic acid), while the remaining 10% correspond to non-hydroxylated fatty acids, mainly linoleic and oleic acids. The chemical analysis of castor oil indicates a hydroxyl number of 2.7. In this work, a polyol was obtained by the reaction of the CO with diethanolamine (DEA), in order to elevate the hydroxyl value from 160 to 230 or to 280 mgKOH/g, and characterized by nuclear magnetic resonance (NMR) 1H and 13C (Mercury 200). The polyadition of the resulting polyol with isophorone diisocianate (IPDI) was carried out at 60°C, and the reaction kinetics was followed by rheological measurements in a Haake RS150 rheometer. The electrical properties were determined in a HP LCR Meter 4262A, at 1.0 Hz and 10.0 KHz. The chemical analysis showed that the polyols obtained presented hydroxyl number from 230 to 280 mgKOH/g. The polyadition reaction with IPDI produced polyurethane resins with the following properties: hardness in the range from 45 shore A to 65 shore D (ASTM D2240); a dielectric constant of 3.0, at 25°C (ASTM D150). Those results indicate that the obtained resins present compatible properties to the similar products of fossil origin, which are used nowadays for covering electric-electronic circuits. Therefore, the PUs from castor oil can be considered as alternative materials of renewable source, free from the highly harmful petroleum - derived solvents

The CMS experiment at the CERN LHC

The Compact Muon Solenoid (CMS) detector is described. The detector operates at the Large Hadron Collider (LHC) at CERN. It was conceived to study proton-proton (and lead-lead) collisions at a centre-of-mass energy of 14 TeV (5.5 TeV nucleon-nucleon) and at luminosities up to 10(34)cm(-2)s(-1) (10(27)cm(-2)s(-1)). At the core of the CMS detector sits a high-magnetic-field and large-bore superconducting solenoid surrounding an all-silicon pixel and strip tracker, a lead-tungstate scintillating-crystals electromagnetic calorimeter, and a brass-scintillator sampling hadron calorimeter. The iron yoke of the flux-return is instrumented with four stations of muon detectors covering most of the 4 pi solid angle. Forward sampling calorimeters extend the pseudo-rapidity coverage to high values (vertical bar eta vertical bar <= 5) assuring very good hermeticity. The overall dimensions of the CMS detector are a length of 21.6 m, a diameter of 14.6 m and a total weight of 12500 t.

A unity power factor multiple isolated outputs switching mode power supply using a single switch

The authors present an offline switching power supply with multiple isolated outputs and unity power factor with the use of only one power processing stage, based on the DC-DC SEPIC (single ended primary inductance converter) modulated by variable hysteresis current control. The principle of operation, the theoretical analysis, the design procedure, an example, and simulation results are presented. A laboratory prototype, rated at 160 W, operating at a maximum switching frequency of 100 kHz, with isolated outputs rated at +5 V/15 A -5 V/1 A, +12 V/6 A and -12 V/1 A, has been built given an input power factor near unity.

Development and application of an electronic tongue for detection and monitoring of nitrate, nitrite and ammonium levels in waters

This work presents the first study and development of an electronic tongue analysis system for the monitoring of nitrogen stable species: nitrate, nitrite and ammonium in water. The electronic tongue was composed of an array of 15 potentiometric poly(vinyl chloride) membrane sensors sensitive to cations and anions plus an artificial neural network (ANN) response model. The building of the ANN model was performed in a medium containing sodium, potassium, and chloride as interfering ions, thus simulating real environmental samples. The correlation coefficient in the cross-validation of nitrate, nitrite and ammonium was satisfactory in the three cases with values higher than 0.92. Finally, the utility of the proposed system is shown in the monitoring of the photoelectrocatalytic treatment of nitrate. © 2013 Elsevier B.V.

Ambiente computacional para projetos de sistemas com tecnologia mista

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Reciclagem de isolantes térmicos presentes em defletores de calor automotivo

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Metodologia de simulação numérica do comportamento térmico em equipamentos eletroeletrônicos

Pós-graduação em Engenharia Elétrica - FEIS

Contribuições para o estudo de atribuição de responsabilidades em circuitos elétricos de baixa tensão

Pós-graduação em Engenharia Elétrica - FEB

Suitability of artificial neural networks for designing LoC circuits

he simulation of complex LoC (Lab-on-a-Chip) devices is a process that requires solving computationally expensive partial differential equations. An interesting alternative uses artificial neural networks for creating computationally feasible models based on MOR techniques. This paper proposes an approach that uses artificial neural networks for designing LoC components considering the artificial neural network topology as an isomorphism of the LoC device topology. The parameters of the trained neural networks are based on equations for modeling microfluidic circuits, analogous to electronic circuits. The neural networks have been trained to behave like AND, OR, Inverter gates. The parameters of the trained neural networks represent the features of LoC devices that behave as the aforementioned gates. This would mean that LoC devices universally compute.

Electron-tube circuits /

Includes bibliographies.