Wine classification by taste sensors made from ultra-thin films and using neural networks

Riul, Antonio; Sousa, Humberto Costa de; Malmegrim, Roger R.; Santos, David S. dos; Carvalho, André C. P. L. F. de; Fonseca, Fernando Josepetti; Oliveira, Osvaldo N.; Mattoso, Luiz H. C.

doi:10.1016/j.snb.2003.09.025

Cited by 164 publications

(84 citation statements)

References 45 publications

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“…Fs-laser processing can also be used to fabricate interdigitated electrodes (IDEs) in metals for analytical chemical sensors, such as electronic tongues (e-tongue) [121][122][123][124] with high definition and accuracy. An interesting study on laser-induced heating, melting and ablation of metals, specifically aluminum, with a fundamental approach, has been recently published in Ref.…”

Section: Gold Ablation For Designing Microelectrodesmentioning

confidence: 99%

Ultrafast Laser Pulses for Structuring Materials at Micro/Nano Scale: From Waveguides to Superhydrophobic Surfaces

Corrêa

Almeida

et al. 2017

Photonics

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Abstract:The current demand for fabricating optical and photonic devices displaying high performance, using low-cost and time-saving methods, prompts femtosecond (fs)-laser processing as a promising methodology. High and low repetition femtosecond lasers enable surface and/or bulk modification of distinct materials, which can be used for applications ranging from optical waveguides to superhydrophobic surfaces. Herein, some fundamental aspects of fs-laser processing of materials, as well as the basics of their most common experimental apparatuses, are introduced. A survey of results on polymer fs-laser processing, resulting in 3D waveguides, electroluminescent structures and active hybrid-microstructures for luminescence or biological microenvironments is presented. Similarly, results of fs-laser processing on glasses, gold and silicon to produce waveguides containing metallic nanoparticles, analytical chemical sensors and surface with modified features, respectively, are also described. The complexity of fs-laser micromachining involves precise control of material properties, pushing ultrafast laser processing as an advanced technique for micro/nano devices.

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Section: Gold Ablation For Designing Microelectrodesmentioning

confidence: 99%

Ultrafast Laser Pulses for Structuring Materials at Micro/Nano Scale: From Waveguides to Superhydrophobic Surfaces

Corrêa

Almeida

et al. 2017

Photonics

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“…A number of efforts have been made to classify different tea using sensor array and electrochemical techniques such as Cyclic Voltammetry, Potentiometry and Conductivity. However, in comparison to potentiometry, especially with voltammetry, the impedance measurements are advantageous because of the potential experimental simplicity and the reduction of the response times [7].…”

Section: Preliminary Of Svmmentioning

confidence: 99%

Survey on Tea Discriminator

Gupta¹,

Shukla²

2015

IJCA

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A number of beverages viz. hard drink, soft drink, packet juice, tea are being used around the globe having different chemical compositions. Organoleptic Systems are being used for a variety of detection tasks from checking quality of food products to medicinal diagnosis by detecting chemical compositions. The entire organoleptic system, from sample delivery stage to classification stage, is usually optimized to a particular problem domain in order to provide suitable sensing performance. The optimization of sample preparation, signal processing, feature extraction, classifier are as important as choice of sensors within the array in enhancing the performance of the organoleptic system because presence of irrelevant features increases the dimensionality of the search space, which can do reverse effect on the accuracy of the Pattern Recognition (PARC) techniques.Tea in present world is the most popular beverage having enormous global marketing. Various researchers have made a number of efforts to correlate tea quality with its chemical composition which led to many humanoid errors and may vary from person to person. This problem can be solved by using an instrument called "Electronic Tongue (i-tongue)". It is developed to reduce human sensory test panels, get accurate measurement of taste, prepare optimized development time and cost. This system analyses liquid including an array of non-specific chemical sensors with partial specificity for different component in liquid samples and appropriate pattern recognition capable of recognizing the qualitative and quantitative composition of sample and complex solutions. A number of attempts have been performed using sensor array and electrochemical techniques such as Cyclic Voltammetry, Potentiometry and Conductivity to classify different types of tea.

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“…The classification performance of eSNN was experimentally explored [70,69] based on water and wine samples collected from [8] and [58]. The topology of the model consists of two layers.…”

Section: Taste Recognitionmentioning

confidence: 99%

Evolving spiking neural network—a survey

2013

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This paper provides a comprehensive literature survey on the evolving Spiking Neural Network (eSNN) architecture since its introduction in 2006 as a further extension of the ECoS paradigm introduced by Kasabov in 1998. We summarize the functioning of the method, discuss several of its extensions and present a number of applications in which the eSNN method was employed. We focus especially on some proposed extensions that allow the processing of spatio-temporal data and for feature and parameter optimisation of eSNN models to achieve better accuracy on classification/prediction problems and to facilitate new knowledge discovery. Finally, some open problems are discussed and future directions highlighted.

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Wine classification by taste sensors made from ultra-thin films and using neural networks

Cited by 164 publications

References 45 publications

Ultrafast Laser Pulses for Structuring Materials at Micro/Nano Scale: From Waveguides to Superhydrophobic Surfaces

Ultrafast Laser Pulses for Structuring Materials at Micro/Nano Scale: From Waveguides to Superhydrophobic Surfaces

Survey on Tea Discriminator

Evolving spiking neural network—a survey

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