The Experts below are selected from a list of 17214 Experts worldwide ranked by ideXlab platform
Guohua Hui - One of the best experts on this subject based on the ideXlab platform.
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design of a portable electronic Nose System and application in k value prediction for large yellow croaker pseudosciaena crocea
Food Analytical Methods, 2016Co-Authors: Hailin Feng, Wei Liu, Yuanyuan Gao, Guohua HuiAbstract:In this paper, a portable electronic Nose (E-Nose) System was designed, and its application in K value prediction for large yellow croaker (Pseudosciaena crocea) was also explored. E-Nose responses to croaker samples were measured for 8 days. Microbiological and chemical indexes including total viable count (TVC), K value, and GC-MS were synchronously examined. Principal component analysis (PCA) and stochastic resonance (SR) were utilized for E-Nose measurement data analysis. Results suggested that croaker’s K value increased rapidly due to microbial propagation. GC-MS results presented the information of volatile gas emitted by croaker samples, and provided reliable references for E-Nose responses. PCA method could not discriminate all croaker samples, while SR signal-to-noise ratio (SNR) maximum (Max SNR ) values quantitatively discriminated all samples. Large yellow croaker K value predictive model was developed by linear fitting regression between K values and Max SNR values with a regression coefficient (R 2 ) of 0.96. Validating experiment results demonstrated that the forecasting accuracy of this model is 83 % the regression coefficient of the developed model was 0.83. E-Nose is a useful tool for food quality examination. But, there are no such standard references for E-Nose examination, which limits the applications of this technique. The method proposed here will promote the applications of E-Nose in aquatic product quality rapid analysis.
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an electronic Nose System based on an array of carbon nanotubes gas sensors with pattern recognition techniques
International Conference on Bioinformatics and Biomedical Engineering, 2010Co-Authors: Zikai Zhao, Guohua HuiAbstract:Abstract-This paper presents design of an electronic Nose based on an array of aligned multi-walled carbon nanotubes (MWNT) ionization gas sensors and pattern recognition techniques for gas detection. The raw data, including discharge voltages and currents, is acquired by measurement of sensor array response and transformed to the computer by peripheral circuit, and processed by Principal Components Analysis (PCA). Back-propagation neural networks (BPNN) are applied to determine gas varieties. Results demonstrate the developed electronic Nose System is capable to identify target gases successfully and is promising for field applications.
Benachir Bouchikhi - One of the best experts on this subject based on the ideXlab platform.
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a portable electronic Nose System for the identification of cannabis based drugs
Sensors and Actuators B-chemical, 2011Co-Authors: Z Haddi, E Llobet, El N Bari, A Amari, H Alami, Benachir BouchikhiAbstract:Abstract We report on a research aimed at evaluating the capacity of a simple, low-cost, portable electronic Nose System based on commercially available metal oxide gas sensors to classify different types of drugs. Five drugs, namely cannabis buds, cannabis plants, hashish, snuff tobacco and tobacco leaves were employed. A dedicated real-time data acquisition System based on dynamic headspace sampling, a microcontroller and a laptop computer have been designed and constructed for this application. To demonstrate its discrimination capability, unsupervised and supervised classification models have been built and validated. Principal Component Analysis (PCA) of volatile profiles revealed five distinct groups corresponding to the five different drugs analyzed. This was further confirmed by a multivariate analysis of variance (MANOVA) test. Support Vectors Machines (SVMs) were applied to build a classifier and reached a 98.5% success rate in the recognition of the different drugs analyzed. This work demonstrates for the first time that the electronic Nose technology could be successfully applied to the identification of illegal drugs.
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an electronic Nose System based on a micro machined gas sensor array to assess the freshness of sardines
Sensors and Actuators B-chemical, 2009Co-Authors: El N Barbri, Benachir Bouchikhi, Xavier Correig, J Mirhisse, Radu Ionescu, El N Bari, E LlobetAbstract:Abstract An electronic Nose System based on a four-element, integrated, micro-machined, metal oxide gas sensor array is used to assess, in an objective manner, the evolutionary stages of freshness in sardine samples stored up to 1-week at 4 °C. The sensors developed were based on tin oxide doped with Pt or Pd or Bi, and on tungsten oxide doped with Au. The selection of the gas sensitive materials was based on a previous identification and quantification of characteristic compounds found in the headspace of sardines determined by solid phase micro-extraction gas chromatography coupled to mass spectrometry. Principal component analysis performed on the responses of the sensor array revealed that sardine samples could be classified in three freshness states. This was in good agreement with the results of a microbiological analysis. A support vector machine-based classifier reached a 100% success rate in the identification of sardine freshness. The stability of the electronic Nose classification ability was assessed by correctly classifying measurement databases gathered 1-month apart. By building and validating quantitative partial least squares models, which employed as input data the gas sensor responses, it was possible to predict with good accuracy the total viable counts (TVC) of aerobic bacteria present in sardine samples. For the validation dataset, the correlation coefficient between actual and predicted TVC was 0.91, which indicates that the electronic Nose System developed is a simple and rapid technique for evaluating sardine freshness.
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application of a portable electronic Nose System to assess the freshness of moroccan sardines
Materials Science and Engineering: C, 2008Co-Authors: El N Barbri, Xavier Correig, E Llobet, El N Bari, Benachir BouchikhiAbstract:In this paper, we propose the investigation and the realisation of an electronic Nose System able to evaluate fish freshness in real-time, under the constraints of being suitable for miniaturization and portability. Six tin oxide based Taguchi gas sensors are used to analyse sardine samples stored at 4 °C. A dedicated real-time data acquisition System based on a microcontroller and portable computer have been designed and constructed for this application. Principal component analysis (PCA) and support vector machines (SVMs) results show that the System is able to assess the freshness of sardines stored at 4 °C.
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Electronic Nose based on metal oxide semiconductor sensors as an alternative technique for the spoilage classification of red meat
Sensors, 2008Co-Authors: Noureddine El Barbri, Nezha El Bari, Eduard Llobet, Xavier Correig, Benachir BouchikhiAbstract:The aim of the present study was to develop an electronic Nose for the quality control of red meat. Electronic Nose and bacteriological measurements are performed to analyse samples of beef and sheep meat stored at 4C for up to 15 days. Principal component analysis (PCA) and support vector machine (SVM) based classification techniques are used to investigate the performance of the electronic Nose System in the spoilage classification of red meats. The bacteriological method was selected as the reference method to consistently train the electronic Nose System. The SVM models built classified meat samples based on the total microbial population into unspoiled (microbial counts < 6 log10 cfu/g) and spoiled (microbial counts = 6 log10 cfu/g). The preliminary results obtained by the bacteria total viable counts (TVC) show that the shelf-life of beef and sheep meats stored at 4 C are 7 and 5 days, respectively. The electronic Nose System coupled to SVM could discriminate between unspoiled/ spoiled beef or sheep meats with a success rate of 98.81 or 96.43 respectively. To investigate whether the results of the electronic Nose correlated well with the results of the bacteriological analysis, partial least squares (PLS) calibration models were built and validated. Good correlation coefficients between the electronic Nose signals and bacteriological data were obtained, a clear indication that the electronic Nose System can become a simple and rapid technique for the quality control of red meats.
Hailin Feng - One of the best experts on this subject based on the ideXlab platform.
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design of a portable electronic Nose System and application in k value prediction for large yellow croaker pseudosciaena crocea
Food Analytical Methods, 2016Co-Authors: Hailin Feng, Wei Liu, Yuanyuan Gao, Guohua HuiAbstract:In this paper, a portable electronic Nose (E-Nose) System was designed, and its application in K value prediction for large yellow croaker (Pseudosciaena crocea) was also explored. E-Nose responses to croaker samples were measured for 8 days. Microbiological and chemical indexes including total viable count (TVC), K value, and GC-MS were synchronously examined. Principal component analysis (PCA) and stochastic resonance (SR) were utilized for E-Nose measurement data analysis. Results suggested that croaker’s K value increased rapidly due to microbial propagation. GC-MS results presented the information of volatile gas emitted by croaker samples, and provided reliable references for E-Nose responses. PCA method could not discriminate all croaker samples, while SR signal-to-noise ratio (SNR) maximum (Max SNR ) values quantitatively discriminated all samples. Large yellow croaker K value predictive model was developed by linear fitting regression between K values and Max SNR values with a regression coefficient (R 2 ) of 0.96. Validating experiment results demonstrated that the forecasting accuracy of this model is 83 % the regression coefficient of the developed model was 0.83. E-Nose is a useful tool for food quality examination. But, there are no such standard references for E-Nose examination, which limits the applications of this technique. The method proposed here will promote the applications of E-Nose in aquatic product quality rapid analysis.
Keationg Tang - One of the best experts on this subject based on the ideXlab platform.
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development of a dual mos electronic Nose camera System for improving fruit ripeness classification
Sensors, 2018Co-Authors: Li-ying Chen, Shihwen Chiu, Ting-i Chou, Keationg TangAbstract:Electronic Nose (E-Nose) Systems have become popular in food and fruit quality evaluation because of their rapid and repeatable availability and robustness. In this paper, we propose an E-Nose System that has potential as a non-destructive System for monitoring variation in the volatile organic compounds produced by fruit during the maturing process. In addition to the E-Nose System, we also propose a camera System to monitor the peel color of fruit as another feature for identification. By incorporating E-Nose and camera Systems together, we propose a non-destructive solution for fruit maturity monitoring. The dual E-Nose/camera System presents the best Fisher class separability measure and shows a perfect classification of the four maturity stages of a banana: Unripe, half-ripe, fully ripe, and overripe.
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Development of an electronic-Nose System for fruit maturity and quality monitoring
2018 IEEE International Conference on Applied System Invention (ICASI), 2018Co-Authors: Li-ying Chen, Shihwen Chiu, De-ming Wong, Chen-yu Fang, Chen-i Chiu, Ting-i Chou, Cheng-chun Wu, Keationg TangAbstract:Potential application of a metal oxide semiconductor based electronic Nose (E-Nose) as a non-destructive System for monitoring the change in volatile organic production of fruit during the maturing process. Using PCA analysis, it was possible to distinguish and to classify the different stages. The result showed that this method yielded highest average accuracies greater than 90% in classifying fruit maturity.
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development of a breath detection method based e Nose System for lung cancer identification
2018 IEEE International Conference on Applied System Invention (ICASI), 2018Co-Authors: De-ming Wong, Shihwen Chiu, Li-ying Chen, Chen-yu Fang, Chen-i Chiu, Ting-i Chou, Cheng-chun Wu, Keationg TangAbstract:In this paper, we focused on the method of lung cancer identification by breath. Lung cancer had occupied the first place in the top ten leading causes of death. When lung cancer patients were diagNosed, most of the patients had lost the opportunity of cure. However, physicians determined the lung cancer cases in complicated steps. Therefore, the purpose of this breath detection System was to help physicians to quickly screen for rapid screening lung cancer. We used KNN and SVM with leave-one-out cross validation to analyze. Finally, we got good accuracy that was 84.4%.
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a bio inspired two layer multiple walled carbon nanotube polymer composite sensor array and a bio inspired fast adaptive readout circuit for a portable electronic Nose
Biosensors and Bioelectronics, 2011Co-Authors: Lichun Wang, Keationg Tang, Shihwen Chiu, Sungyi Yang, Chengtzu KuoAbstract:We report a fully integrated, portable, battery-operated electronic Nose System comprising a bio-inspired two-layer multiple-walled carbon nanotube (MWNT)-polymer composite sensor array, a bio-inspired fast-adaptive readout circuit, and a microprocessor embedded with a pattern recognition algorithm. The two-layer MWNT-polymer composite sensor is simple to operate, and the membrane quality can be easily controlled. These two-layer membranes have improved sensitivity and stability. The fast-adaptive readout circuit responds to the sensor response, while tuning out the long-term constant background humidity, temperature, and odors. This portable electronic Nose System successfully classified four complex alcohol samples 40 times for each sample; these samples were sake, sorghum liquor, medical liquor, and whisky.
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development of a portable electronic Nose System for the detection and classification of fruity odors
Sensors, 2010Co-Authors: Keationg Tang, Shihwen Chiu, Chihheng Pan, Hungyi Hsieh, Yaosheng Liang, Ssuchieh LiuAbstract:In this study, we have developed a prototype of a portable electronic Nose (E-Nose) comprising a sensor array of eight commercially available sensors, a data acquisition interface PCB, and a microprocessor. Verification software was developed to verify System functions. Experimental results indicate that the proposed System prototype is able to identify the fragrance of three fruits, namely lemon, banana, and litchi.
E Llobet - One of the best experts on this subject based on the ideXlab platform.
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a portable electronic Nose System for the identification of cannabis based drugs
Sensors and Actuators B-chemical, 2011Co-Authors: Z Haddi, E Llobet, El N Bari, A Amari, H Alami, Benachir BouchikhiAbstract:Abstract We report on a research aimed at evaluating the capacity of a simple, low-cost, portable electronic Nose System based on commercially available metal oxide gas sensors to classify different types of drugs. Five drugs, namely cannabis buds, cannabis plants, hashish, snuff tobacco and tobacco leaves were employed. A dedicated real-time data acquisition System based on dynamic headspace sampling, a microcontroller and a laptop computer have been designed and constructed for this application. To demonstrate its discrimination capability, unsupervised and supervised classification models have been built and validated. Principal Component Analysis (PCA) of volatile profiles revealed five distinct groups corresponding to the five different drugs analyzed. This was further confirmed by a multivariate analysis of variance (MANOVA) test. Support Vectors Machines (SVMs) were applied to build a classifier and reached a 98.5% success rate in the recognition of the different drugs analyzed. This work demonstrates for the first time that the electronic Nose technology could be successfully applied to the identification of illegal drugs.
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an electronic Nose System based on a micro machined gas sensor array to assess the freshness of sardines
Sensors and Actuators B-chemical, 2009Co-Authors: El N Barbri, Benachir Bouchikhi, Xavier Correig, J Mirhisse, Radu Ionescu, El N Bari, E LlobetAbstract:Abstract An electronic Nose System based on a four-element, integrated, micro-machined, metal oxide gas sensor array is used to assess, in an objective manner, the evolutionary stages of freshness in sardine samples stored up to 1-week at 4 °C. The sensors developed were based on tin oxide doped with Pt or Pd or Bi, and on tungsten oxide doped with Au. The selection of the gas sensitive materials was based on a previous identification and quantification of characteristic compounds found in the headspace of sardines determined by solid phase micro-extraction gas chromatography coupled to mass spectrometry. Principal component analysis performed on the responses of the sensor array revealed that sardine samples could be classified in three freshness states. This was in good agreement with the results of a microbiological analysis. A support vector machine-based classifier reached a 100% success rate in the identification of sardine freshness. The stability of the electronic Nose classification ability was assessed by correctly classifying measurement databases gathered 1-month apart. By building and validating quantitative partial least squares models, which employed as input data the gas sensor responses, it was possible to predict with good accuracy the total viable counts (TVC) of aerobic bacteria present in sardine samples. For the validation dataset, the correlation coefficient between actual and predicted TVC was 0.91, which indicates that the electronic Nose System developed is a simple and rapid technique for evaluating sardine freshness.
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application of a portable electronic Nose System to assess the freshness of moroccan sardines
Materials Science and Engineering: C, 2008Co-Authors: El N Barbri, Xavier Correig, E Llobet, El N Bari, Benachir BouchikhiAbstract:In this paper, we propose the investigation and the realisation of an electronic Nose System able to evaluate fish freshness in real-time, under the constraints of being suitable for miniaturization and portability. Six tin oxide based Taguchi gas sensors are used to analyse sardine samples stored at 4 °C. A dedicated real-time data acquisition System based on a microcontroller and portable computer have been designed and constructed for this application. Principal component analysis (PCA) and support vector machines (SVMs) results show that the System is able to assess the freshness of sardines stored at 4 °C.
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Classification of the strain and growth phase of cyanobacteria in potable water using an electronic Nose System
IEE Proceedings - Science Measurement and Technology, 2000Co-Authors: Hyun Woo Shin, E Llobet, J W Gardner, Evor L HinesAbstract:An electronic Nose comprising an array of six commercial odour sensors has been used to monitor not only different strains, but also the growth phase, of cyanobacteria which is normally called blue green algal. A series of experiments were carried out to analyse the nature of two closely related strains of cyanobacteria, Microcystis aeruginosa PCC 7806 that produces a toxin and PCC 7941 that does not. The authors have constructed a measurement System for the testing of the cyanobacteria in water over a period of up to 40 days. After some pre-processing to remove the variation associated with running the electronic Nose in ambient air, the two different strains, and their growth phase, were classified with principal components analysis, multilayer perceptron (MLP), learning vector quantisation (LVQ), and fuzzy ARTMAP. The optimal MLP network was found to classify correctly 97.1%, of unknown non-toxic and 100% of unknown toxic cyanobacteria. The optimal LVQ and fuzzy ARTMAP algorithms were able to classify 100% of both strains of cyanobacteria. The accuracy of MLP, LVQ and fuzzy ARTMAP algorithms with the four different growth phases of toxic cyanobacteria was 92.3%, 95.1% and 92.3%, respectively.
