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Dr. Maryam Siadat
Lorraine University

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0 gas sensors
0 Instrument Calibration
0 e-Nose Sensors
0 Air Ambient Quality

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Journal article
Published: 21 May 2021 in Sensors
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This paper investigates the long term drift phenomenon affecting electrochemical sensors used in real environmental conditions to monitor the nitrogen dioxide concentration [NO2]. Electrochemical sensors are low-cost gas sensors able to detect pollutant gas at part per billion level and may be employed to enhance the air quality monitoring networks. However, they suffer from many forms of drift caused by climatic parameter variations, interfering gases and aging. Therefore, they require frequent, expensive and time-consuming calibrations, which constitute the main obstacle to the exploitation of these kinds of sensors. This paper proposes an empirical, linear and unsupervised drift correction model, allowing to extend the time between two successive full calibrations. First, a calibration model is established based on multiple linear regression. The influence of the air temperature and humidity is considered. Then, a correction model is proposed to solve the drift related to age issue. The slope and the intercept of the correction model compensate the change over time of the sensors’ sensitivity and baseline, respectively. The parameters of the correction model are identified using particle swarm optimization (PSO). Data considered in this work are continuously collected onsite close to a highway crossing Metz City (France) during a period of 6 months (July to December 2018) covering almost all the climatic conditions in this region. Experimental results show that the suggested correction model allows maintaining an adequate [NO2] estimation accuracy for at least 3 consecutive months without needing any labeled data for the recalibration.

ACS Style

Rachid Laref; Etienne Losson; Alexandre Sava; Maryam Siadat. Empiric Unsupervised Drifts Correction Method of Electrochemical Sensors for in Field Nitrogen Dioxide Monitoring. Sensors 2021, 21, 3581 .

AMA Style

Rachid Laref, Etienne Losson, Alexandre Sava, Maryam Siadat. Empiric Unsupervised Drifts Correction Method of Electrochemical Sensors for in Field Nitrogen Dioxide Monitoring. Sensors. 2021; 21 (11):3581.

Chicago/Turabian Style

Rachid Laref; Etienne Losson; Alexandre Sava; Maryam Siadat. 2021. "Empiric Unsupervised Drifts Correction Method of Electrochemical Sensors for in Field Nitrogen Dioxide Monitoring." Sensors 21, no. 11: 3581.

Abstract
Published: 01 January 2019 in Proceedings
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Semiconductor functional materials play an increasingly important role in science and technology because of their unique optical, electrical, magnetic, catalytic and chemical properties. They are widely used in fields such as solar cell, photo-catalysts, optical coating, capacitors for large scale integrated devices, electrochromic systems and gas sensors. One important application for semiconductor gas sensors is the detection of pollutant gases for the control of the combustion process.

ACS Style

Zineb Essalhi; Soufiane Krik; Bouchaib Hartiti; Andrea Gaiardo; Abderrazak Lfakir; Matteo Valt; Salah Fadili; Barbara Fabbri; Maryam Siadat; Vincenzo Guidi. Elaboration and Characterization of SnO2 Doped TiO2 Gas Sensors Deposited through Dip and Spin Coating Methods. Proceedings 2019, 14, 23 .

AMA Style

Zineb Essalhi, Soufiane Krik, Bouchaib Hartiti, Andrea Gaiardo, Abderrazak Lfakir, Matteo Valt, Salah Fadili, Barbara Fabbri, Maryam Siadat, Vincenzo Guidi. Elaboration and Characterization of SnO2 Doped TiO2 Gas Sensors Deposited through Dip and Spin Coating Methods. Proceedings. 2019; 14 (1):23.

Chicago/Turabian Style

Zineb Essalhi; Soufiane Krik; Bouchaib Hartiti; Andrea Gaiardo; Abderrazak Lfakir; Matteo Valt; Salah Fadili; Barbara Fabbri; Maryam Siadat; Vincenzo Guidi. 2019. "Elaboration and Characterization of SnO2 Doped TiO2 Gas Sensors Deposited through Dip and Spin Coating Methods." Proceedings 14, no. 1: 23.

Proceedings
Published: 01 January 2019 in Proceedings
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Metal oxide semiconductor gas sensors are used in a various applications in environmental, industrial and medical field, for instance. They are relatively inexpensive compared to other sensing technologies, robust, lightweight, long lasting and benefit from high material sensitivity and quick response times. Copper oxide (CuO) thin film has been promisingly proposed for chemical sensing applications. Particularly, it has been recommended as a sensitive layer for monitoring harmful and combustible gases. It is an attractive material because of nontoxic, inexpensive, abundance advantages, and its fabrication is easy. In this work, we have synthesized CuO thin films by Spray pyrolysis method. The effect of the temperature deposition is investigated:to say 350 °C, 400 °C, and 450 °C while the deposition duration was kipped to 15 min. The samples were analyzed by X-ray diffraction, Raman spectroscopy, XPS analysis, UV-visible transmission and four points probe method.

ACS Style

Maha Hinna; Bouchaib Hartiti; Abdelkrim Batan; François Reniers; Claudine Buess-Herman; Tiriana Segato; Naoual Belouaggadia; Salah Fadili; Maryam Siadat; Philippe Thévenin. Elaboration and Characterization of CuO Thin Films by Spray Pyrolysis Method for Gas Sensors Applications. Proceedings 2019, 14, 55 .

AMA Style

Maha Hinna, Bouchaib Hartiti, Abdelkrim Batan, François Reniers, Claudine Buess-Herman, Tiriana Segato, Naoual Belouaggadia, Salah Fadili, Maryam Siadat, Philippe Thévenin. Elaboration and Characterization of CuO Thin Films by Spray Pyrolysis Method for Gas Sensors Applications. Proceedings. 2019; 14 (1):55.

Chicago/Turabian Style

Maha Hinna; Bouchaib Hartiti; Abdelkrim Batan; François Reniers; Claudine Buess-Herman; Tiriana Segato; Naoual Belouaggadia; Salah Fadili; Maryam Siadat; Philippe Thévenin. 2019. "Elaboration and Characterization of CuO Thin Films by Spray Pyrolysis Method for Gas Sensors Applications." Proceedings 14, no. 1: 55.

Extended abstract
Published: 01 January 2019 in Proceedings
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The tin sulfide (SnS) has p-type conductivity, high absorption coefficient (≥104 cm−1), […]

ACS Style

Youssef Nouri; Bouchaib Hartiti; Abdelkrim Batan; François Reniers; Claudine Buess-Herman; Tiriana Segato; Salah Fadili; Maryam Siadat; Philippe Thévenin. Elaboration and Characterization of SnS Thin Film for Gas Sensors Application. Proceedings 2019, 14, 4 .

AMA Style

Youssef Nouri, Bouchaib Hartiti, Abdelkrim Batan, François Reniers, Claudine Buess-Herman, Tiriana Segato, Salah Fadili, Maryam Siadat, Philippe Thévenin. Elaboration and Characterization of SnS Thin Film for Gas Sensors Application. Proceedings. 2019; 14 (1):4.

Chicago/Turabian Style

Youssef Nouri; Bouchaib Hartiti; Abdelkrim Batan; François Reniers; Claudine Buess-Herman; Tiriana Segato; Salah Fadili; Maryam Siadat; Philippe Thévenin. 2019. "Elaboration and Characterization of SnS Thin Film for Gas Sensors Application." Proceedings 14, no. 1: 4.

Extended abstract
Published: 01 January 2019 in Proceedings
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Chemical gas sensors were studied long ago and nowadays, for the advantageous role they provide to the environment, health condition monitoring and protection. The recent studies focus on the semiconductors sensing abilities, especially of non toxic and low cost compounds. The present work describes the steps to elaborate and perform a chemical sensor using intrinsic and doped semiconductor zinc oxide. First, we synthesized pure oxide using zinc powder, then, two other samples were established where we introduced the same doping percentage of Al and Sn respectively. Using low cost spray pyrolysis, and respecting the same conditions of preparation. The obtained samples were then characterized by X Ray Diffraction (XRD) that revealed the hexagonal wurzite structure and higher crystallite density towards the direction (002), besides the appearance of the vibration modes related to zinc oxide, confirmed by Raman spectroscopy. SEM spectroscopy showed that the surface morphology is ideal for oxidizing/reduction reactions, due to the porous structure and the low grain sizes, especially observed for the sample Sn doped ZnO. The gas testing confirms these predictions showing that the highest response is related to Sn doped ZnO compared to ZnO and followed by Al doped ZnO. The films exhibited responses towards: CO, acetone, methanol, H2, ammonia and NO2. The concentrations were varied from 10 to 500 ppm and the working temperatures from 250 to 500°C, the optimal working temperatures were 350 and 400 °C. Sn doped ZnO showed a high response towards H2 gas target, with a sensitivity reaching 200 at 500 ppm, for 400 °C.

ACS Style

Zahira. El Khalidi; Maryam Siadat; Elisabetta. Comini; Salah. Fadili; Philippe. Thevenin. Sensing Performance of Al and Sn Doped ZnO for Hydrogen Detection. Proceedings 2019, 14, 39 .

AMA Style

Zahira. El Khalidi, Maryam Siadat, Elisabetta. Comini, Salah. Fadili, Philippe. Thevenin. Sensing Performance of Al and Sn Doped ZnO for Hydrogen Detection. Proceedings. 2019; 14 (1):39.

Chicago/Turabian Style

Zahira. El Khalidi; Maryam Siadat; Elisabetta. Comini; Salah. Fadili; Philippe. Thevenin. 2019. "Sensing Performance of Al and Sn Doped ZnO for Hydrogen Detection." Proceedings 14, no. 1: 39.

Journal article
Published: 01 November 2018 in Sensors
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Recently, the emergence of low-cost sensors have allowed electronic noses to be considered for densifying the actual air pollution monitoring networks in urban areas. Electronic noses are affected by changes in environmental conditions and sensor drifts over time. Therefore, they need to be calibrated periodically and also individually because the characteristics of identical sensors are slightly different. For these reasons, the calibration process has become very expensive and time consuming. To cope with these drawbacks, calibration transfer between systems constitutes a satisfactory alternative. Among them, direct standardization shows good efficiency for calibration transfer. In this paper, we propose to improve this method by using kernel SPXY (sample set partitioning based on joint x-y distances) for data selection and support vector machine regression to match between electronic noses. The calibration transfer approach introduced in this paper was tested using two identical electronic noses dedicated to monitoring nitrogen dioxide. Experimental results show that our method gave the highest efficiency compared to classical direct standardization.

ACS Style

Rachid Laref; Etienne Losson; Alexandre Sava; Maryam Siadat. Support Vector Machine Regression for Calibration Transfer between Electronic Noses Dedicated to Air Pollution Monitoring. Sensors 2018, 18, 3716 .

AMA Style

Rachid Laref, Etienne Losson, Alexandre Sava, Maryam Siadat. Support Vector Machine Regression for Calibration Transfer between Electronic Noses Dedicated to Air Pollution Monitoring. Sensors. 2018; 18 (11):3716.

Chicago/Turabian Style

Rachid Laref; Etienne Losson; Alexandre Sava; Maryam Siadat. 2018. "Support Vector Machine Regression for Calibration Transfer between Electronic Noses Dedicated to Air Pollution Monitoring." Sensors 18, no. 11: 3716.

Research article
Published: 01 August 2017 in Journal of Sensors
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Metal oxide sensors are the most often used in electronic nose devices because of their high sensitivity, long lifetime, and low cost. However, these sensors suffer from a lack of response stability making the electronic nose systems useless in industrial applications. The sensor instabilities are particularly caused by incomplete recovery process producing gradual drifts in the sensor responses. This paper focuses on a signal processing method combining baseline manipulation and orthogonal signal correction technique in order to reduce effectively the drift impact from the sensor outputs. The proposed signal processing is explored using experimental data obtained from a gas sensor array responding to various concentrations of pine essential oil vapors. Partial Least Square method is then applied on the corrected dataset to establish a regression model for the estimation of gas concentration. In this work, we show essentially how our drift correction approach can help to improve significantly the stability of the regression model, while ensuring good accuracy.

ACS Style

Rachid Laref; Diaa Ahmadou; Etienne Losson; Maryam Siadat. Orthogonal Signal Correction to Improve Stability Regression Model in Gas Sensor Systems. Journal of Sensors 2017, 2017, 1 -8.

AMA Style

Rachid Laref, Diaa Ahmadou, Etienne Losson, Maryam Siadat. Orthogonal Signal Correction to Improve Stability Regression Model in Gas Sensor Systems. Journal of Sensors. 2017; 2017 ():1-8.

Chicago/Turabian Style

Rachid Laref; Diaa Ahmadou; Etienne Losson; Maryam Siadat. 2017. "Orthogonal Signal Correction to Improve Stability Regression Model in Gas Sensor Systems." Journal of Sensors 2017, no. : 1-8.

Journal article
Published: 09 December 2016 in Clinical Hemorheology and Microcirculation
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ACS Style

B. Pignon; S. Muller; D. Jolly; M. Siadat; E. Petitfrere; B. Vessel; M. Donner; G. Potron; J.F. Stoltz. Validation of a method for erythrocyte aggregation measurement using light back-scattering. Clinical Hemorheology and Microcirculation 2016, 9, 739 -749.

AMA Style

B. Pignon, S. Muller, D. Jolly, M. Siadat, E. Petitfrere, B. Vessel, M. Donner, G. Potron, J.F. Stoltz. Validation of a method for erythrocyte aggregation measurement using light back-scattering. Clinical Hemorheology and Microcirculation. 2016; 9 (5):739-749.

Chicago/Turabian Style

B. Pignon; S. Muller; D. Jolly; M. Siadat; E. Petitfrere; B. Vessel; M. Donner; G. Potron; J.F. Stoltz. 2016. "Validation of a method for erythrocyte aggregation measurement using light back-scattering." Clinical Hemorheology and Microcirculation 9, no. 5: 739-749.

Journal article
Published: 01 January 2015 in Engineering in Agriculture, Environment and Food
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ACS Style

Mahdi Ghasemi-Varnamkhasti; Seyed Saeid Mohtasebi; Maryam Siadat; Hojat Ahmadi; Seyed Hadi Razavi. From simple classification methods to machine learning for the binary discrimination of beers using electronic nose data. Engineering in Agriculture, Environment and Food 2015, 8, 44 -51.

AMA Style

Mahdi Ghasemi-Varnamkhasti, Seyed Saeid Mohtasebi, Maryam Siadat, Hojat Ahmadi, Seyed Hadi Razavi. From simple classification methods to machine learning for the binary discrimination of beers using electronic nose data. Engineering in Agriculture, Environment and Food. 2015; 8 (1):44-51.

Chicago/Turabian Style

Mahdi Ghasemi-Varnamkhasti; Seyed Saeid Mohtasebi; Maryam Siadat; Hojat Ahmadi; Seyed Hadi Razavi. 2015. "From simple classification methods to machine learning for the binary discrimination of beers using electronic nose data." Engineering in Agriculture, Environment and Food 8, no. 1: 44-51.

Journal article
Published: 23 July 2014 in Sensors
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Proteinases are involved in a multitude of important physiological processes, such as protein metabolism. For this reason, a conductometric enzyme biosensor based on proteinase K was developed using two types of nanoparticles (gold and magnetic). The enzyme was directly adsorbed on negatively charged nanoparticles and then deposited and cross-linked on a planar interdigitated electrode (IDE). The biosensor was characterized with bovine serum albumin (BSA) as a standard protein. Higher sensitivity was obtained using gold nanoparticles. The linear range for BSA determination was then from 0.5 to 10 mg/L with a maximum response of 154 µs. These results are greater than that found without any nanoparticles (maximum response of 10 µs). The limit of detection (LOD) was 0.3 mg/L. An inter-sensor reproducibility of 3.5% was obtained.

ACS Style

Wided Nouira; Abderrazak Maaref; Hamid Elaissari; Francis Vocanson; Maryam Siadat; Nicole Jaffrezic-Renault; Abdelhamid Elaissari. Enhanced Response of a Proteinase K-Based Conductometric Biosensor Using Nanoparticles. Sensors 2014, 14, 13298 -13307.

AMA Style

Wided Nouira, Abderrazak Maaref, Hamid Elaissari, Francis Vocanson, Maryam Siadat, Nicole Jaffrezic-Renault, Abdelhamid Elaissari. Enhanced Response of a Proteinase K-Based Conductometric Biosensor Using Nanoparticles. Sensors. 2014; 14 (7):13298-13307.

Chicago/Turabian Style

Wided Nouira; Abderrazak Maaref; Hamid Elaissari; Francis Vocanson; Maryam Siadat; Nicole Jaffrezic-Renault; Abdelhamid Elaissari. 2014. "Enhanced Response of a Proteinase K-Based Conductometric Biosensor Using Nanoparticles." Sensors 14, no. 7: 13298-13307.

Conference paper
Published: 01 January 2014 in International Conference on Sensor Networks
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ACS Style

D. Ahmadou; Etienne Losson; M. Siadat; M. Lumbreras. Sensors and Features Selection for Robust Gas Concentration Evaluation. International Conference on Sensor Networks 2014, 237 -243.

AMA Style

D. Ahmadou, Etienne Losson, M. Siadat, M. Lumbreras. Sensors and Features Selection for Robust Gas Concentration Evaluation. International Conference on Sensor Networks. 2014; ():237-243.

Chicago/Turabian Style

D. Ahmadou; Etienne Losson; M. Siadat; M. Lumbreras. 2014. "Sensors and Features Selection for Robust Gas Concentration Evaluation." International Conference on Sensor Networks , no. : 237-243.

Conference paper
Published: 14 March 2013 in Journal of Physics: Conference Series
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ACS Style

W Nouira; H Barhoumi; A Maaref; N Jaffrézic Renault; Maryam Siadat. Tailoring of analytical performances of urea biosensors using nanomaterials. Journal of Physics: Conference Series 2013, 416, 1 .

AMA Style

W Nouira, H Barhoumi, A Maaref, N Jaffrézic Renault, Maryam Siadat. Tailoring of analytical performances of urea biosensors using nanomaterials. Journal of Physics: Conference Series. 2013; 416 ():1.

Chicago/Turabian Style

W Nouira; H Barhoumi; A Maaref; N Jaffrézic Renault; Maryam Siadat. 2013. "Tailoring of analytical performances of urea biosensors using nanomaterials." Journal of Physics: Conference Series 416, no. : 1.

Comparative study
Published: 10 September 2012 in Materials Science and Engineering: C
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The aim of this study was to show the feasibility and the performances of nanoparticle biosensing. A glucose conductometric biosensor was developed using two types of nanoparticles (gold and magnetic), glucose oxidase (GOD) being adsorbed on PAH (poly(allylamine hydrochloride)) modified nanoparticles, deposited on a planar interdigitated electrode (IDEs). The best sensitivities for glucose detection were obtained with magnetic nanoparticles (70 μM/mM and 3 μM of detection limit) compared to 45 μM/mM and 9 μM with gold nanoparticles and 30 μM/mM and 50 μM with GOD directly cross-linked on IDEs. When stored in phosphate buffer (20 mM, pH 7.3) at 4 °C, the biosensor showed good stability for more than 12 days.

ACS Style

Wided Nouira; Abderrazak Maaref; Hamid Elaissari; Francis Vocanson; Maryam Siadat; Nicole Jaffrezic-Renault. Comparative study of conductometric glucose biosensor based on gold and on magnetic nanoparticles. Materials Science and Engineering: C 2012, 33, 298 -303.

AMA Style

Wided Nouira, Abderrazak Maaref, Hamid Elaissari, Francis Vocanson, Maryam Siadat, Nicole Jaffrezic-Renault. Comparative study of conductometric glucose biosensor based on gold and on magnetic nanoparticles. Materials Science and Engineering: C. 2012; 33 (1):298-303.

Chicago/Turabian Style

Wided Nouira; Abderrazak Maaref; Hamid Elaissari; Francis Vocanson; Maryam Siadat; Nicole Jaffrezic-Renault. 2012. "Comparative study of conductometric glucose biosensor based on gold and on magnetic nanoparticles." Materials Science and Engineering: C 33, no. 1: 298-303.

Journal article
Published: 27 April 2012 in Czech Journal of Food Sciences
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Many chemical changes in beer aroma occur during storage (aging), and monitoring these changes could give guidelines to the brewers how to manage and control the brewing process to obtain the final product with a high stability in flavour after packaging. In this regard, our laboratory aimed at a research into the application of an electronic nose in order to get the fingerprint of the change of non alcoholic beer aroma during aging. Th discriminatory power of the sensor array of this system was evaluated. Principal Component Analysis (PCA) and Soft Independent Modelling of Class Analogy (SIMCA) techniques were used for this purpose. The results obtained can direct us to performing other parts of our project. Considering the discriminatory power of the sensor array used, we can develop the application of a specific electronic nose system by picking up the most effective sensors or ignoring the redundant sensors.

ACS Style

M. Ghasemi-Varnamkhasti; S.S. Mohtasebi; M. Siadat; S.H. Razavi; H. Ahmadi; A. Dicko. Discriminatory power assessment of the sensor array of an electronic nose system for the detection of non alcoholic beer aging. Czech Journal of Food Sciences 2012, 30, 236 -240.

AMA Style

M. Ghasemi-Varnamkhasti, S.S. Mohtasebi, M. Siadat, S.H. Razavi, H. Ahmadi, A. Dicko. Discriminatory power assessment of the sensor array of an electronic nose system for the detection of non alcoholic beer aging. Czech Journal of Food Sciences. 2012; 30 (No. 3):236-240.

Chicago/Turabian Style

M. Ghasemi-Varnamkhasti; S.S. Mohtasebi; M. Siadat; S.H. Razavi; H. Ahmadi; A. Dicko. 2012. "Discriminatory power assessment of the sensor array of an electronic nose system for the detection of non alcoholic beer aging." Czech Journal of Food Sciences 30, no. No. 3: 236-240.

Journal article
Published: 23 February 2012 in Electroanalysis
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A new conductometric biosensor based on interdigitated electrodes (IDEs) has been developed for the detection of enzymatic substrates using gold nanoparticles (GNPs), synthesized bellowing the citrate process, with an average diameter of 23 nm and functionalized with urease using layer‐by‐layer technique. A detection limit of 100 µM of urea is obtained when cross‐linked urease is directly immobilized on top of the IDEs (interdigitated distance: 20 µm) whereas a detection limit of 2 µM is obtained when urease functionalized gold nanoparticles are deposited on the top of the IDEs. The use of gold nanoparticles allows the increase of the sensitivity of detection (from 10 µS/mM to 107 µS/mM) due to the decrease of the thickness of probed zone.

ACS Style

W. Nouira; A. Maaref; Francis Vocanson; Maryam Siadat; Joelle Saulnier; F. Lagarde; Nicole Jaffrezicrenault. Enhancement of Enzymatic IDE Biosensor Response Using Gold Nanoparticles. Example of the Detection of Urea. Electroanalysis 2012, 24, 1088 -1094.

AMA Style

W. Nouira, A. Maaref, Francis Vocanson, Maryam Siadat, Joelle Saulnier, F. Lagarde, Nicole Jaffrezicrenault. Enhancement of Enzymatic IDE Biosensor Response Using Gold Nanoparticles. Example of the Detection of Urea. Electroanalysis. 2012; 24 (5):1088-1094.

Chicago/Turabian Style

W. Nouira; A. Maaref; Francis Vocanson; Maryam Siadat; Joelle Saulnier; F. Lagarde; Nicole Jaffrezicrenault. 2012. "Enhancement of Enzymatic IDE Biosensor Response Using Gold Nanoparticles. Example of the Detection of Urea." Electroanalysis 24, no. 5: 1088-1094.

Journal article
Published: 01 January 2012 in Procedia Engineering
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ACS Style

M. Siadat; H. Sambemana; M. Lumbreras. New Transient Feature for Metal Oxide Gas Sensor Response Processing. Procedia Engineering 2012, 47, 52 -55.

AMA Style

M. Siadat, H. Sambemana, M. Lumbreras. New Transient Feature for Metal Oxide Gas Sensor Response Processing. Procedia Engineering. 2012; 47 ():52-55.

Chicago/Turabian Style

M. Siadat; H. Sambemana; M. Lumbreras. 2012. "New Transient Feature for Metal Oxide Gas Sensor Response Processing." Procedia Engineering 47, no. : 52-55.

Journal article
Published: 01 December 2011 in Sensor Letters
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International audienceAn interdigitated conductometric biosensor for the detection of urea was obtained by functionalization of magnetic nanoparticles with polyelectrolyte:Poly(allylamine hydrochloride) (PAH), for urease immobilization, using the method of layer-by-layer deposition (LbL). The maximum of response obtained with nanoparticles is 39 μS compared to 20 μS for urease directly cross-linked on the sensor. The dynamic range is very much enlarged: from 0.1 mM to 10 mM with urease-PAH coated nanoparticles and 1 mM to 5 mM for directly cross-linked urease on the sensor. The biosensor was stable over a period of 30 days

ACS Style

W. Nouira; A. Maaref; M. Siadat; A. Errachid; N. Jaffrezic-Renault. Conductometric Biosensors Based on Layer-by-Layer Coated Paramagnetic Nanoparticles for Urea Detection. Sensor Letters 2011, 9, 2272 -2274.

AMA Style

W. Nouira, A. Maaref, M. Siadat, A. Errachid, N. Jaffrezic-Renault. Conductometric Biosensors Based on Layer-by-Layer Coated Paramagnetic Nanoparticles for Urea Detection. Sensor Letters. 2011; 9 (6):2272-2274.

Chicago/Turabian Style

W. Nouira; A. Maaref; M. Siadat; A. Errachid; N. Jaffrezic-Renault. 2011. "Conductometric Biosensors Based on Layer-by-Layer Coated Paramagnetic Nanoparticles for Urea Detection." Sensor Letters 9, no. 6: 2272-2274.

Journal article
Published: 28 November 2011 in Sensors and Actuators B: Chemical
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In this work, attempts were made in order to characterize the change of aroma of alcoholic and non alcoholic beers during the aging process by use of a metal oxide semiconductor based electronic nose. The aged beer samples were statistically characterized in several classes. Linear techniques as principal component analysis (PCA) and Linear Discriminant Analaysis (LDA) were performed over the data that revealed non alcoholic beer classes are separated except a partial overlapping between zones corresponding to two specified classes of the aged beers. A clear discrimination was not found among the alcoholic beer classes showing the more stability of such type of beer compared with non alcoholic beer. In this research, to classify the classes, two types of artificial neural networks were used: Probabilistic Neural Networks (PNN) with Radial Basis Functions (RBF) and FeedForward Networks with Backpropagation (BP) learning method. The classification success was found to be 90% and 100% for alcoholic and non alcoholic beers, respectively. Application of PNN showed the classification accuracy of 83% and 100%, respectively for the aged alcoholic and non alcoholic beer classes as well. Finally, this study showed the capability of the electronic nose system for the evaluation of the aroma fingerprint changes in beer during the aging process.

ACS Style

Mahdi Ghasemi-Varnamkhasti; Seyed Saeid Mohtasebi; Maryam Siadat; Jesús Lozano; Hojat Ahmadi; Seyed Hadi Razavi; Amadou Dicko. Aging fingerprint characterization of beer using electronic nose. Sensors and Actuators B: Chemical 2011, 159, 51 -59.

AMA Style

Mahdi Ghasemi-Varnamkhasti, Seyed Saeid Mohtasebi, Maryam Siadat, Jesús Lozano, Hojat Ahmadi, Seyed Hadi Razavi, Amadou Dicko. Aging fingerprint characterization of beer using electronic nose. Sensors and Actuators B: Chemical. 2011; 159 (1):51-59.

Chicago/Turabian Style

Mahdi Ghasemi-Varnamkhasti; Seyed Saeid Mohtasebi; Maryam Siadat; Jesús Lozano; Hojat Ahmadi; Seyed Hadi Razavi; Amadou Dicko. 2011. "Aging fingerprint characterization of beer using electronic nose." Sensors and Actuators B: Chemical 159, no. 1: 51-59.

Discussion
Published: 31 May 2011 in Trends in Food Science & Technology
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Authentication of the flavor of non alcoholic beer and control of its quality according to the present standards is an actual challenge in brewery. Electronic and bioelectronic tongues, which could be known as the taste sensors, are the advanced and emerging analytical technologies simulating the taste detection modality of the human tongue by means of electrochemical sensors or biosensors array. Although, application of electronic tongue has been reported for alcoholic beers but no work on the flavor sensory evaluation of non alcoholic beer by use of bioelectronic tongue has been published. Employment of electronic and bioelectronic tongues can reduce some problems in quality control of non alcoholic beers. Recently published works show a promising perspective for the fulfillment of this goal. This paper discusses and concludes that these analytical tools have a high potential application in brewery to monitor the flavor of non alcoholic beer in the immediate future.

ACS Style

Mahdi Ghasemi-Varnamkhasti; Seyed Saeid Mohtasebi; Maria Luz Rodriguez-Mendez; M. Siadat; H. Ahmadi; S.H. Razavi. Electronic and bioelectronic tongues, two promising analytical tools for the quality evaluation of non alcoholic beer. Trends in Food Science & Technology 2011, 22, 245 -248.

AMA Style

Mahdi Ghasemi-Varnamkhasti, Seyed Saeid Mohtasebi, Maria Luz Rodriguez-Mendez, M. Siadat, H. Ahmadi, S.H. Razavi. Electronic and bioelectronic tongues, two promising analytical tools for the quality evaluation of non alcoholic beer. Trends in Food Science & Technology. 2011; 22 (5):245-248.

Chicago/Turabian Style

Mahdi Ghasemi-Varnamkhasti; Seyed Saeid Mohtasebi; Maria Luz Rodriguez-Mendez; M. Siadat; H. Ahmadi; S.H. Razavi. 2011. "Electronic and bioelectronic tongues, two promising analytical tools for the quality evaluation of non alcoholic beer." Trends in Food Science & Technology 22, no. 5: 245-248.

Journal article
Published: 01 January 2011 in Journal of Water Resource and Protection
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A sensor array comprising 9 potentiometric chemical sensors and some pattern recognition tools for the data processing has been applied in order to characterize the groundwater in the plain of Kairouan Region (Tunisia). A total of 17 groundwater samples were collected from three different villages and analyzed for their chemical components. Nine chemical parameters were determined: Potassium, Sodium, Calcium, Ammonium, Cadmium, Chlorides, Nitrates, Fluoride and pH. Multi-sensor responses measured in each water sample were diagnosed by Principal Component Analysis (PCA) and Cluster Analysis (CA). PCA is a procedure for reducing data redundancy. CA is used to detect spatial similarity among sampling sites. This methodology is simple, rapid and the obtained results demonstrate that the electronic tongue technique based on the sensor array combined with pattern recognition method could be a useful tool for the characterization and the classification of wells water samples.

ACS Style

Khawla Sghaier; Houcine Barhoumi; Abderrazak Maaref; Maryam Siadat; Nicole Jaffrezic-Renault. Characterization and Classification of Groundwater from Wells Using an Electronic Tongue (Kairouan, Tunisia). Journal of Water Resource and Protection 2011, 03, 531 -539.

AMA Style

Khawla Sghaier, Houcine Barhoumi, Abderrazak Maaref, Maryam Siadat, Nicole Jaffrezic-Renault. Characterization and Classification of Groundwater from Wells Using an Electronic Tongue (Kairouan, Tunisia). Journal of Water Resource and Protection. 2011; 03 (07):531-539.

Chicago/Turabian Style

Khawla Sghaier; Houcine Barhoumi; Abderrazak Maaref; Maryam Siadat; Nicole Jaffrezic-Renault. 2011. "Characterization and Classification of Groundwater from Wells Using an Electronic Tongue (Kairouan, Tunisia)." Journal of Water Resource and Protection 03, no. 07: 531-539.