Prediction of reservoir fracture is the key to explore fracture-type reservoir. When a shear-wave propagates in anisotropic media containing fracture,it splits into two polarized shear waves: fast shear wave and slow ...Prediction of reservoir fracture is the key to explore fracture-type reservoir. When a shear-wave propagates in anisotropic media containing fracture,it splits into two polarized shear waves: fast shear wave and slow shear wave. The polarization and time delay of the fast and slow shear wave can be used to predict the azimuth and density of fracture. The current identification method of fracture azimuth and fracture density is cross-correlation method. It is assumed that fast and slow shear waves were symmetrical wavelets after completely separating,and use the most similar characteristics of wavelets to identify fracture azimuth and density,but in the experiment the identification is poor in accuracy. Pearson correlation coefficient method is one of the methods for separating the fast wave and slow wave. This method is faster in calculating speed and better in noise immunity and resolution compared with the traditional cross-correlation method. Pearson correlation coefficient method is a non-linear problem,particle swarm optimization( PSO) is a good nonlinear global optimization method which converges fast and is easy to implement. In this study,PSO is combined with the Pearson correlation coefficient method to achieve identifying fracture property and improve the computational efficiency.展开更多
Temporal-spatial cross-correlation analysis of non-stationary wind speed time series plays a crucial role in wind field reconstruction as well as in wind pattern recognition.Firstly,the near-surface wind speed time se...Temporal-spatial cross-correlation analysis of non-stationary wind speed time series plays a crucial role in wind field reconstruction as well as in wind pattern recognition.Firstly,the near-surface wind speed time series recorded at different locations are studied using the detrended fluctuation analysis(DFA),and the corresponding scaling exponents are larger than 1.This indicates that all these wind speed time series have non-stationary characteristics.Secondly,concerning this special feature( i.e.,non-stationarity)of wind signals,a cross-correlation analysis method,namely detrended cross-correlation analysis(DCCA) coefficient,is employed to evaluate the temporal-spatial cross-correlations between non-stationary time series of different anemometer pairs.Finally,experiments on ten wind speed data synchronously collected by the ten anemometers with equidistant arrangement illustrate that the method of DCCA cross-correlation coefficient can accurately analyze full-scale temporal-spatial cross-correlation between non-stationary time series and also can easily identify the seasonal component,while three traditional cross-correlation techniques(i.e.,Pearson coefficient,cross-correlation function,and DCCA method) cannot give us these information directly.展开更多
We present a unified approach to describing and linking several methods for representing categorical data in a contingency table. These methods include: correspondence analysis, Hellinger distance analysis, the log-ra...We present a unified approach to describing and linking several methods for representing categorical data in a contingency table. These methods include: correspondence analysis, Hellinger distance analysis, the log-ratio alternative, which is appropriate for compositional data, and the non-symmetrical correspondence analysis. We also present two solutions working with cummulative frequencies.展开更多
Current research on metaphor analysis is generally knowledge-based and corpus-based,which calls for methods of automatic feature extraction and weight calculation.Combining natural language processing(NLP),latent sema...Current research on metaphor analysis is generally knowledge-based and corpus-based,which calls for methods of automatic feature extraction and weight calculation.Combining natural language processing(NLP),latent semantic analysis(LSA),and Pearson correlation coefficient,this paper proposes a metaphor analysis method for extracting the content words from both literal and metaphorical corpus,calculating correlation degree,and analyzing their relationships.The value of the proposed method was demonstrated through a case study by using a corpus with keyword“飞翔(fly)”.When compared with the method of Pearson correlation coefficient,the experiment shows that the LSA can produce better results with greater significance in correlation degree.It is also found that the number of common words that appeared in both literal and metaphorical word bags decreased with the correlation degree.The case study also revealed that there are more nouns appear in literal corpus,and more adjectives and adverbs appear in metaphorical corpus.The method proposed will benefit NLP researchers to develop the required step-by-step calculation tools for accurate quantitative analysis.展开更多
Objective:To observe the levels of serum cystatin C (Cys C), brain natriuretic peptide (BNP) in traumatic patients and correlation analysis with traumatic severity.Methods:120 emergency traumatic patients in emergency...Objective:To observe the levels of serum cystatin C (Cys C), brain natriuretic peptide (BNP) in traumatic patients and correlation analysis with traumatic severity.Methods:120 emergency traumatic patients in emergency department of our hospital were rolled from December 2015 to December 2016, who were divided into minor trauma group (n=41), severe trauma group (n=43) and critical trauma group (n=36) according to the injury severity score (ISS). The levels of serum Cys C, BNP of the patients in the 3 groups were detected on 0 h, 24 h, 3 d and 7 d after admission respectively. Pearson correlation analysis of the levels of serum Cys C, BNP and ISS.Results: There were no significant differences in the levels of serum Cys C, BNP on 0 hours between the three groups;There were no significant differences in the levels of serum Cys C, BNP on 0 h, 24 h, 3 d and 7 d in minor trauma group;The levels of serum Cys C, BNP on 24 h, 3 d and 7 d were all higher than those of 0 h in severe trauma group, and the levels of serum Cys C on 3 d and 7 d were both higher than those of 24 h;The levels of serum Cys C, BNP on 24 h, 3 d and 7 d were all higher than those of 0 h in critical trauma group, the levels of serum Cys C, BNP on 3 d and 7 d were both higher than those of 24 h, and the levels of serum Cys C on 7 d were higher than those of 3 d;The levels of serum Cys C, BNP in severe trauma and critical trauma groups were significantly higher compared with minor trauma group on 24 h, 3 d and 7 d. Pearson correlation analysis, the level of serum Cys C were positively correlated with ISS, the level of serum BNP were positively correlated with ISS.Conclusion:Different levels of traumatic patients had different levels of serum Cys C, BNP increased at different times. Pearson correlation analysis showed that the levels of serum Cys C, BNP were both positively correlated with traumatic severity, which suggested that the levels of serum Cys C, BNP may be important indicators of traumatic severity and could provide important reference value for clinical evaluation of traumatic severity.展开更多
文摘Prediction of reservoir fracture is the key to explore fracture-type reservoir. When a shear-wave propagates in anisotropic media containing fracture,it splits into two polarized shear waves: fast shear wave and slow shear wave. The polarization and time delay of the fast and slow shear wave can be used to predict the azimuth and density of fracture. The current identification method of fracture azimuth and fracture density is cross-correlation method. It is assumed that fast and slow shear waves were symmetrical wavelets after completely separating,and use the most similar characteristics of wavelets to identify fracture azimuth and density,but in the experiment the identification is poor in accuracy. Pearson correlation coefficient method is one of the methods for separating the fast wave and slow wave. This method is faster in calculating speed and better in noise immunity and resolution compared with the traditional cross-correlation method. Pearson correlation coefficient method is a non-linear problem,particle swarm optimization( PSO) is a good nonlinear global optimization method which converges fast and is easy to implement. In this study,PSO is combined with the Pearson correlation coefficient method to achieve identifying fracture property and improve the computational efficiency.
基金Projects(61271321,61573253,61401303)supported by the National Natural Science Foundation of ChinaProject(14ZCZDSF00025)supported by Tianjin Key Technology Research and Development Program,China+1 种基金Project(13JCYBJC17500)supported by Tianjin Natural Science Foundation,ChinaProject(20120032110068)supported by Doctoral Fund of Ministry of Education of China
文摘Temporal-spatial cross-correlation analysis of non-stationary wind speed time series plays a crucial role in wind field reconstruction as well as in wind pattern recognition.Firstly,the near-surface wind speed time series recorded at different locations are studied using the detrended fluctuation analysis(DFA),and the corresponding scaling exponents are larger than 1.This indicates that all these wind speed time series have non-stationary characteristics.Secondly,concerning this special feature( i.e.,non-stationarity)of wind signals,a cross-correlation analysis method,namely detrended cross-correlation analysis(DCCA) coefficient,is employed to evaluate the temporal-spatial cross-correlations between non-stationary time series of different anemometer pairs.Finally,experiments on ten wind speed data synchronously collected by the ten anemometers with equidistant arrangement illustrate that the method of DCCA cross-correlation coefficient can accurately analyze full-scale temporal-spatial cross-correlation between non-stationary time series and also can easily identify the seasonal component,while three traditional cross-correlation techniques(i.e.,Pearson coefficient,cross-correlation function,and DCCA method) cannot give us these information directly.
文摘We present a unified approach to describing and linking several methods for representing categorical data in a contingency table. These methods include: correspondence analysis, Hellinger distance analysis, the log-ratio alternative, which is appropriate for compositional data, and the non-symmetrical correspondence analysis. We also present two solutions working with cummulative frequencies.
基金Fundamental Research Funds for the Central Universities of Ministry of Education of China(No.19D111201)。
文摘Current research on metaphor analysis is generally knowledge-based and corpus-based,which calls for methods of automatic feature extraction and weight calculation.Combining natural language processing(NLP),latent semantic analysis(LSA),and Pearson correlation coefficient,this paper proposes a metaphor analysis method for extracting the content words from both literal and metaphorical corpus,calculating correlation degree,and analyzing their relationships.The value of the proposed method was demonstrated through a case study by using a corpus with keyword“飞翔(fly)”.When compared with the method of Pearson correlation coefficient,the experiment shows that the LSA can produce better results with greater significance in correlation degree.It is also found that the number of common words that appeared in both literal and metaphorical word bags decreased with the correlation degree.The case study also revealed that there are more nouns appear in literal corpus,and more adjectives and adverbs appear in metaphorical corpus.The method proposed will benefit NLP researchers to develop the required step-by-step calculation tools for accurate quantitative analysis.
文摘Objective:To observe the levels of serum cystatin C (Cys C), brain natriuretic peptide (BNP) in traumatic patients and correlation analysis with traumatic severity.Methods:120 emergency traumatic patients in emergency department of our hospital were rolled from December 2015 to December 2016, who were divided into minor trauma group (n=41), severe trauma group (n=43) and critical trauma group (n=36) according to the injury severity score (ISS). The levels of serum Cys C, BNP of the patients in the 3 groups were detected on 0 h, 24 h, 3 d and 7 d after admission respectively. Pearson correlation analysis of the levels of serum Cys C, BNP and ISS.Results: There were no significant differences in the levels of serum Cys C, BNP on 0 hours between the three groups;There were no significant differences in the levels of serum Cys C, BNP on 0 h, 24 h, 3 d and 7 d in minor trauma group;The levels of serum Cys C, BNP on 24 h, 3 d and 7 d were all higher than those of 0 h in severe trauma group, and the levels of serum Cys C on 3 d and 7 d were both higher than those of 24 h;The levels of serum Cys C, BNP on 24 h, 3 d and 7 d were all higher than those of 0 h in critical trauma group, the levels of serum Cys C, BNP on 3 d and 7 d were both higher than those of 24 h, and the levels of serum Cys C on 7 d were higher than those of 3 d;The levels of serum Cys C, BNP in severe trauma and critical trauma groups were significantly higher compared with minor trauma group on 24 h, 3 d and 7 d. Pearson correlation analysis, the level of serum Cys C were positively correlated with ISS, the level of serum BNP were positively correlated with ISS.Conclusion:Different levels of traumatic patients had different levels of serum Cys C, BNP increased at different times. Pearson correlation analysis showed that the levels of serum Cys C, BNP were both positively correlated with traumatic severity, which suggested that the levels of serum Cys C, BNP may be important indicators of traumatic severity and could provide important reference value for clinical evaluation of traumatic severity.
