Least Square Regression Method for Estimating Gas Concentration in an Electronic Nose System

Khalaf, Walaa; Pace, Calogero; Gaudioso, Manlio

doi:10.3390/s90301678

Cited by 42 publications

(21 citation statements)

References 18 publications

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“…To overcome this problem, alcohol gas sensors were used to measure the ethanol concentration in the gas phase instantaneously. Alcohol gas sensors, or more generally volatile organic compound gas sensors, are used in many applications including vehicle and semiconductor industries, organic vapor detectors/alarms, air/food quality control, security, and as electronic noses to identify gases and their concentrations . Also, alcohol gas sensors offer many useful features, such as high sensitivity, long life, miniature size, low cost, easy construction for the drive circuit, and good repeatability.…”

Section: Methodsmentioning

confidence: 99%

Separation of azeotropic mixtures using air microbubbles generated by fluidic oscillation

et al. 2015

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The feasibility of separating the azeotropic mixture of ethanol-water using microbubble-mediated batch distillation is presented. The effects of the depth of the liquid mixture in the bubble tank and of the inlet air microbubble temperature on the process efficiency were investigated. The enrichment of ethanol in the vapor phase was higher than that achieved at equilibrium conditions for all liquid ethanol mole fractions considered, including the azeotrope. On decreasing the depth of the liquid mixture and increasing the temperature of the air microbubbles, the separation efficiency of ethanol was improved. Ethanol with purity of about 98.2 vol % was obtained using the lowest liquid level (3 mm) in conjunction with the highest air microbubble temperature (908C). Separation was achieved with a small rise in the temperature of the liquid mixture (48C) at a depth of 3 mm and evaporation time of 90 min making this system suitable for treating thermally sensitive mixtures.

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Section: Methodsmentioning

confidence: 99%

Separation of azeotropic mixtures using air microbubbles generated by fluidic oscillation

et al. 2015

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“…Applications of such sensors were obtained in sectors shown in Tab.1, in particular of environmental and industrial monitoring and for the control of Indoor comfort parameters [27,30].…”

Section: Discussionmentioning

confidence: 99%

“…It combines the new instrumentation and the engineering knowledge with chemistry and medicine, and it is the attainment of a diagnostic monitoring for human diseases [12][13][14][15][16][17][18][19][20][21][22][23][24][25][26].…”

Section: Introductionmentioning

confidence: 99%

The Applications of the New Technologies “E-Sensing” in Hospitals

Cannistraro¹,

Lorenzini²

2016

IJHT

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The technologies or techniques "e-sensing", in the past decade have had significant developments from the technical and commercial point of view. The term "e-sensing", refers to the ability to reproduce human senses by means of sensors and recognition systems. The proposed work has been developed within the doctoral thesis and is part of a larger research project about sensors underway at the Faculty of Engineering of Messina. The research, combining the knowledge of engineering methods and tools with medical and chemical competence, is oriented to the development of a system able of monitoring the exhaled air for diagnostic purposes, for the realization of electronic systems at a low cost, for the diagnostics in medicine. It was built an artificial olfactory system, known as "electronic nose", which allows monitoring the exhaled air components of patients undergoing a dialysis treatment. This diagnostic non-invasive method is able to provide at low cost, through the specific control of the markers of the exhaled air, some useful information to assess health of dialyzed patients. The realized device, was tested for biomedical applications and mainly for the specific monitoring of volatile biomarkers in the exhaled air, associated with certain medical conditions (eg. NH3 for nephrological diseases). It will allow to obtain an effective early diagnosis of the disease reducing care times and, at the same time, reducing the invasiveness of diagnostic treatments.

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“…In terms of its real-world application, the calorimetric-sensor-based system, it is therefore limited to the specific applications; however, with the development of electrochemical sensors and IT (both hardware and software), electronic systems became more intelligent and portable [10,11]. Due to these technological developments, an increasingly diverse array of e-nose applications continues to gradually emerge and includes medical check-ups [12], pollution and gas leak searches [13], environmental protection [14], and cosmetics industry [4,15,16].…”

Section: Introductionmentioning

confidence: 99%

Gas Classification Using Combined Features Based on a Discriminant Analysis for an Electronic Nose

2016

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This paper proposes a gas classification method for an electronic nose (e-nose) system, for which combined features that have been configured through discriminant analysis are used. First, each global feature is extracted from the entire measurement section of the data samples, while the same process is applied to the local features of the section that corresponds to the stabilization, exposure, and purge stages. The discriminative information amounts in the individual features are then measured based on the discriminant analysis, and the combined features are subsequently composed by selecting the features that have a large amount of discriminative information. Regarding a variety of volatile organic compound data, the results of the experiment show that, in a noisy environment, the proposed method exhibits classification performance that is relatively excellent compared to the other feature types.

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Least Square Regression Method for Estimating Gas Concentration in an Electronic Nose System

Cited by 42 publications

References 18 publications

Separation of azeotropic mixtures using air microbubbles generated by fluidic oscillation

Separation of azeotropic mixtures using air microbubbles generated by fluidic oscillation

The Applications of the New Technologies “E-Sensing” in Hospitals

Gas Classification Using Combined Features Based on a Discriminant Analysis for an Electronic Nose

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