Passive image interferometry （PII） is becoming a powerful tool for detecting the temporal variations in the Earth＇s structure, which applies coda wave interferometry to the waveforrns from the cross-correlation of ...Passive image interferometry （PII） is becoming a powerful tool for detecting the temporal variations in the Earth＇s structure, which applies coda wave interferometry to the waveforrns from the cross-correlation of seismic ambient noise. There are four techniques for estimating temporal change of seismic velocity with PII： moving-window cross-correlation technique （MWCCT）, moving-window cross-spectrum technique （MWCST）, stretching technique （ST） and moving-window stretching technique （MWST）. In this paper, we use the continuous seismic records from a typical station pair near the Wenchuan Ms8.0 earthquake fault zone and generate three sets of waveforms by stacking cross-correlation function of ambient noise with different numbers of days, and then apply four techniques to processing the three sets of waveforms and compare their results. Our results indicate that the techniques based on moving-window （MWCCT, MWCST and MWST） are superior in detecting the change of seismic velocity, and the MWCST can give a better estimate of velocity change than the other moving-window techniques due to measurement error. We also investigate the clock errors and their influences on measuring velocity change. We find that when the clock errors are not very large, they have limited impact on the estimate of the velocity change with the moving-window techniques.展开更多
Partial least squares discriminant analysis (PLS-DA) with integrated moving-window (MW) waveband screening was applied to the discriminant analysis of liquor brands with near-infrared (NIR) spectroscopy. Luzhou Laojia...Partial least squares discriminant analysis (PLS-DA) with integrated moving-window (MW) waveband screening was applied to the discriminant analysis of liquor brands with near-infrared (NIR) spectroscopy. Luzhou Laojiao, a popular liquor with strong fragrant flavor, was used as the identified liquor brand (160 samples, negative, 52 vol alcoholicity). Liquors of 10 other brands with strong fragrant flavor were used as the interferential brands (200 samples, positive, 52 vol alcoholicity). The Kennard-Stone algorithm was used for the division of modeling samples to achieve uniformity and representativeness. Based on the MW-PLS-DA, a simplified optimal model set with 157 wavebands was further proposed. This set contained five types of wavebands corresponding to the NIR absorption bands of water, ethanol, and other micronutrients (i.e., acids, aldehydes, phenols, and aromatic compounds) in liquor for practical choice. Using five selected simple models with 4775 - 4239, 7804 - 6569, 6264 - 5844, 9435 - 7896, and 12066 - 10373 cm-1, the validation recognition rates were obtained as 99.3% or higher. Results show good prediction performance and low model complexity, and also provided a valuable reference for designing small dedicated instruments. The proposed method is a promising tool for large-scale inspection of liquor food safety.展开更多
The moving window bis corelation coefficients(MW BiCC)was proposed and employed for the discriminant analysis of transgenic sugarcane leaves and B-thalassemia with visible and near-infrared(Vis NIR)spectroscopy.The we...The moving window bis corelation coefficients(MW BiCC)was proposed and employed for the discriminant analysis of transgenic sugarcane leaves and B-thalassemia with visible and near-infrared(Vis NIR)spectroscopy.The well-performed moving window principal component analysis linear discriminant analysis(MWPCA-LDA)was also conducted for comparison.A total of 306 transgenic(positive)and 150 nont ransgenic(negative)leave samples of sugarcane were collected and divided to calibration,prediction,and validation.The diffuse reflection spectra were corected using Savitzky-Golay(SG)smoothing with first-order derivative(d=1),third-degree polynomial(p=3)and 25 smpothing points(m=25).The selected waveband was 736-1054nm with MW-BiCC,and the positive and negative validation recognition rates(V_REC^(+),VREC^(-))were 100%,98.0%,which achieved the same effect as MWPCA-LDA.Another example,the 93 B-thalassemia(positive)and 148 nonthalassemia(negative)of human hemolytic samples were colloctod.The transmission spectra were corrected using SG smoothing withd=1,p=3 and m=53.Using M W-BiCC,many best wavebands were selected(e.g.,1116-1146,17941848 and 22842342nm).The V_REC^(+)and V_REC^(-)were both 100%,which achieved the same effect as MW-PCA-LDA.Importantly,the BICC only required ca lculating correlation cofficients between the spectrum of prediction sample and the average spectra of two types of calibration samples.Thus,BiCC was very simple in algorithm,and expected to obtain more applications.The results first confirmed the feasibility of distinguishing B-thalassemia and normal control samples by NIR spectroscopy,and provided a promising simple tool for large population thalassemia screening.展开更多
基金supported by National Natural Science Foundation of China (No. 41074061)Basic Research Plan of the Institute of Earthquake Science, China Earthquake Administration (No. 2007-13)
文摘Passive image interferometry （PII） is becoming a powerful tool for detecting the temporal variations in the Earth＇s structure, which applies coda wave interferometry to the waveforrns from the cross-correlation of seismic ambient noise. There are four techniques for estimating temporal change of seismic velocity with PII： moving-window cross-correlation technique （MWCCT）, moving-window cross-spectrum technique （MWCST）, stretching technique （ST） and moving-window stretching technique （MWST）. In this paper, we use the continuous seismic records from a typical station pair near the Wenchuan Ms8.0 earthquake fault zone and generate three sets of waveforms by stacking cross-correlation function of ambient noise with different numbers of days, and then apply four techniques to processing the three sets of waveforms and compare their results. Our results indicate that the techniques based on moving-window （MWCCT, MWCST and MWST） are superior in detecting the change of seismic velocity, and the MWCST can give a better estimate of velocity change than the other moving-window techniques due to measurement error. We also investigate the clock errors and their influences on measuring velocity change. We find that when the clock errors are not very large, they have limited impact on the estimate of the velocity change with the moving-window techniques.
文摘Partial least squares discriminant analysis (PLS-DA) with integrated moving-window (MW) waveband screening was applied to the discriminant analysis of liquor brands with near-infrared (NIR) spectroscopy. Luzhou Laojiao, a popular liquor with strong fragrant flavor, was used as the identified liquor brand (160 samples, negative, 52 vol alcoholicity). Liquors of 10 other brands with strong fragrant flavor were used as the interferential brands (200 samples, positive, 52 vol alcoholicity). The Kennard-Stone algorithm was used for the division of modeling samples to achieve uniformity and representativeness. Based on the MW-PLS-DA, a simplified optimal model set with 157 wavebands was further proposed. This set contained five types of wavebands corresponding to the NIR absorption bands of water, ethanol, and other micronutrients (i.e., acids, aldehydes, phenols, and aromatic compounds) in liquor for practical choice. Using five selected simple models with 4775 - 4239, 7804 - 6569, 6264 - 5844, 9435 - 7896, and 12066 - 10373 cm-1, the validation recognition rates were obtained as 99.3% or higher. Results show good prediction performance and low model complexity, and also provided a valuable reference for designing small dedicated instruments. The proposed method is a promising tool for large-scale inspection of liquor food safety.
基金supported by the Science and Technology Project of Guangdong Province of China(Nos.2014A020213016 and 2014A020212445).
文摘The moving window bis corelation coefficients(MW BiCC)was proposed and employed for the discriminant analysis of transgenic sugarcane leaves and B-thalassemia with visible and near-infrared(Vis NIR)spectroscopy.The well-performed moving window principal component analysis linear discriminant analysis(MWPCA-LDA)was also conducted for comparison.A total of 306 transgenic(positive)and 150 nont ransgenic(negative)leave samples of sugarcane were collected and divided to calibration,prediction,and validation.The diffuse reflection spectra were corected using Savitzky-Golay(SG)smoothing with first-order derivative(d=1),third-degree polynomial(p=3)and 25 smpothing points(m=25).The selected waveband was 736-1054nm with MW-BiCC,and the positive and negative validation recognition rates(V_REC^(+),VREC^(-))were 100%,98.0%,which achieved the same effect as MWPCA-LDA.Another example,the 93 B-thalassemia(positive)and 148 nonthalassemia(negative)of human hemolytic samples were colloctod.The transmission spectra were corrected using SG smoothing withd=1,p=3 and m=53.Using M W-BiCC,many best wavebands were selected(e.g.,1116-1146,17941848 and 22842342nm).The V_REC^(+)and V_REC^(-)were both 100%,which achieved the same effect as MW-PCA-LDA.Importantly,the BICC only required ca lculating correlation cofficients between the spectrum of prediction sample and the average spectra of two types of calibration samples.Thus,BiCC was very simple in algorithm,and expected to obtain more applications.The results first confirmed the feasibility of distinguishing B-thalassemia and normal control samples by NIR spectroscopy,and provided a promising simple tool for large population thalassemia screening.
