大家帮个忙，看看我这两篇论文被EI检索了吗

　　大家帮个忙，看看我这两篇论文被EI检索了吗。大家帮帮忙。。看看
1、Design of the rapid Real-time Detection for Sesame oil flavoring Based on Electronic Nose
2、Rapid Detection of Sesame Oil Flavoring Based on the Gas Sensor Array（会议）
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Accession number:20132116359934

Title:Design of a rapid real-time detection method for sesame oil flavoring based on electronic nose
Authors:Ma, Li-Hui1; Gao, Yong-Yang1; Zhang, Ting1; Dong, Meng1; Xin, Wen-Ping1
Author affiliation:1 College of Quality and Technical Supervision, Hebei University, Baoding 071002, China
Corresponding author:Ma, L.-H.
Source title:Modern Food Science and Technology
Abbreviated source title:Mod. Food Sci. Technol.
Volume:29
Issue:3
Issue date:March 2013
Publication year:2013
Pages:644-646+562
Language:Chinese
ISSN:16739078
Document type:Journal article (JA)
Publisher:South China University of Technology, Guangzhou, 510640, China
Abstract:For the rapid detection of sesame oil flavoring, a real-time and accurate detection of sesame oil flavoring system was developed. The system mainly consists of the data acquisition part and data processing components. The data acquisition part included gas sensor and the host computer; data processing part include a three-layer BP neural network which was trained in Matlab. During the experiment, 8 samples of sesame oil flavoring with different proportions and the standard samples were prepared for the neural network training. The test samples were verified. The system provided a basis method for the rapid detection of sesame oil flavoring.
Number of references:9
Main heading:Vegetable oils
Controlled terms:Data acquisition-Neural networks
Uncontrolled terms:BP neural networks-Different proportions-Electronic NOSE-Neural network training-Rapid detection-Real-time detection-Sesame oil-Standard samples
Classification code:723.2 Data Processing and Image Processing -723.4 Artificial Intelligence -804.1 Organic Compounds
Database:Compendex
Compilation and indexing terms, © 2013 Elsevier Inc.



Accession number:20131816286312

Title:Rapid detection of sesame oil flavoring based on the gas sensor array
Authors:Ma, Lihui1, 2 ; Gao, Yongyang1; Sun, Hui1; Qi, Mingjun1; Zhang, Ting1; Hou, Xiaohua1
Author affiliation:1 College of Quality and Technical Supervision, Hebei University, Baoding 071002, China
2 College of Precision Instrument and Opto-electronics Engineering, Tianjin University, Tianjin 300072, China
Corresponding author:Ma, L. (
Source title:Proceedings - 2013 5th Conference on Measuring Technology and Mechatronics Automation, ICMTMA 2013
Abbreviated source title:Proc. - Conf. Meas. Technol. Mechatronics Autom., ICMTMA
Monograph title:Proceedings - 2013 5th Conference on Measuring Technology and Mechatronics Automation, ICMTMA 2013
Issue date:2013
Publication year:2013
Pages:841-844
Article number:6493862
Language:English
ISBN-13:9780769549323
Document type:Conference article (CA)
Conference name:2013 5th Conference on Measuring Technology and Mechatronics Automation, ICMTMA 2013
Conference date:January 16, 2013 - January 17, 2013
Conference location:Hong Kong, China
Conference code:96678
Sponsor:Central South University; Harbin Engineering University
Publisher:IEEE Computer Society, 2001 L Street N.W., Suite 700, Washington, DC 20036-4928, United States
Abstract:For the rapid detection of sesame oil flavoring, a real-time and accurate detection of sesame oil flavoring system is developed. The system mainly consists of the data acquisition part and data processing components. The data acquisition parts include gas sensor and the host computer. Data processing part include a three-layer BP neural network which is trained in MATLAB. During the experiment, the preparations of sesame oil flavoring samples have eight different proportions, and the standard samples are for the neural network training and test samples are verified. The system provides a basis method for the rapid detection of sesame oil flavoring. © 2013 IEEE.
Number of references:7
Main heading:Vegetable oils
Controlled terms:Chemical sensors-Data acquisition-Neural networks
Uncontrolled terms:BP neural networks-Different proportions-Electronic NOSE-Host computers-Neural network training-Rapid detection-Sesame oil-Standard samples
Classification code:723.2 Data Processing and Image Processing -723.4 Artificial Intelligence -801 Chemistry -804.1 Organic Compounds
DOI:10.1109/ICMTMA.2013.211
Database:Compendex
Compilation and indexing terms, © 2013 Elsevier Inc.