Regularized Generalized Canonical Correlation Analysis
Tenenhaus, Arthur; Tenenhaus, Michel
2011-01-01
Regularized generalized canonical correlation analysis (RGCCA) is a generalization of regularized canonical correlation analysis to three or more sets of variables. It constitutes a general framework for many multi-block data analysis methods. It combines the power of multi-block data analysis methods (maximization of well identified criteria) and…
Functional Multiple-Set Canonical Correlation Analysis
Hwang, Heungsun; Jung, Kwanghee; Takane, Yoshio; Woodward, Todd S.
2012-01-01
We propose functional multiple-set canonical correlation analysis for exploring associations among multiple sets of functions. The proposed method includes functional canonical correlation analysis as a special case when only two sets of functions are considered. As in classical multiple-set canonical correlation analysis, computationally, the…
Regularized canonical correlation analysis with unlabeled data
Xi-chuan ZHOU; Hai-bin SHEN
2009-01-01
In standard canonical correlation analysis (CCA), the data from definite datasets are used to estimate their canonical correlation. In real applications, for example in bilingual text retrieval, it may have a great portion of data that we do not know which set it belongs to. This part of data is called unlabeled data, while the rest from definite datasets is called labeled data. We propose a novel method called regularized canonical correlation analysis (RCCA), which makes use of both labeled and unlabeled samples. Specifically, we learn to approximate canonical correlation as if all data were labeled. Then. we describe a generalization of RCCA for the multi-set situation. Experiments on four real world datasets, Yeast, Cloud, Iris, and Haberman, demonstrate that,by incorporating the unlabeled data points, the accuracy of correlation coefficients can be improved by over 30%.
Face hallucination using orthogonal canonical correlation analysis
Zhou, Huiling; Lam, Kin-Man
2016-05-01
A two-step face-hallucination framework is proposed to reconstruct a high-resolution (HR) version of a face from an input low-resolution (LR) face, based on learning from LR-HR example face pairs using orthogonal canonical correlation analysis (orthogonal CCA) and linear mapping. In the proposed algorithm, face images are first represented using principal component analysis (PCA). Canonical correlation analysis (CCA) with the orthogonality property is then employed, to maximize the correlation between the PCA coefficients of the LR and the HR face pairs to improve the hallucination performance. The original CCA does not own the orthogonality property, which is crucial for information reconstruction. We propose using orthogonal CCA, which is proven by experiments to achieve a better performance in terms of global face reconstruction. In addition, in the residual-compensation process, a linear-mapping method is proposed to include both the inter- and intrainformation about manifolds of different resolutions. Compared with other state-of-the-art approaches, the proposed framework can achieve a comparable, or even better, performance in terms of global face reconstruction and the visual quality of face hallucination. Experiments on images with various parameter settings and blurring distortions show that the proposed approach is robust and has great potential for real-world applications.
Nimon, Kim; Henson, Robin K.; Gates, Michael S.
2010-01-01
In the face of multicollinearity, researchers face challenges interpreting canonical correlation analysis (CCA) results. Although standardized function and structure coefficients provide insight into the canonical variates produced, they fall short when researchers want to fully report canonical effects. This article revisits the interpretation of…
Regression, Discriminant Analysis, and Canonical Correlation Analysis with Homals
Jan de Leeuw
2009-01-01
It is shown that the homals package in R can be used for multiple regression, multi-group discriminant analysis, and canonical correlation analysis. The homals solutions are only different from the more conventional ones in the way the dimensions are scaled by the eigenvalues.It is shown that the homals package in R can be used for multiple regression, multi-group discriminant analysis, and canonical correlation analysis. The homals solutions are only different from the more conventional ones...
Canonical correlation analysis of course and teacher evaluation
Sliusarenko, Tamara; Ersbøll, Bjarne Kjær
2010-01-01
information obtained from the course evaluation form overlaps with information obtained from the teacher evaluation form. Employing canonical correlation analysis it was found that course and teacher evaluations are correlated. However, the structure of the canonical correlation is subject to change with...... changes in teaching methods from one year to another....
Fusing Face and Periocular biometrics using Canonical correlation analysis
Lakshmiprabha, N. S.
2016-01-01
This paper presents a novel face and periocular biometric fusion at feature level using canonical correlation analysis. Face recognition itself has limitations such as illumination, pose, expression, occlusion etc. Also, periocular biometrics has spectacles, head angle, hair and expression as its limitations. Unimodal biometrics cannot surmount all these limitations. The recognition accuracy can be increased by fusing dual information (face and periocular) from a single source (face image) us...
Sparse canonical correlation analysis: new formulation and algorithm.
Chu, Delin; Liao, Li-Zhi; Ng, Michael K; Zhang, Xiaowei
2013-12-01
In this paper, we study canonical correlation analysis (CCA), which is a powerful tool in multivariate data analysis for finding the correlation between two sets of multidimensional variables. The main contributions of the paper are: 1) to reveal the equivalent relationship between a recursive formula and a trace formula for the multiple CCA problem, 2) to obtain the explicit characterization for all solutions of the multiple CCA problem even when the corresponding covariance matrices are singular, 3) to develop a new sparse CCA algorithm, and 4) to establish the equivalent relationship between the uncorrelated linear discriminant analysis and the CCA problem. We test several simulated and real-world datasets in gene classification and cross-language document retrieval to demonstrate the effectiveness of the proposed algorithm. The performance of the proposed method is competitive with the state-of-the-art sparse CCA algorithms. PMID:24136440
Asymptotic distributions in the projection pursuit based canonical correlation analysis
无
2010-01-01
In this paper, associations between two sets of random variables based on the projection pursuit (PP) method are studied. The asymptotic normal distributions of estimators of the PP based canonical correlations and weighting vectors are derived.
Interpreting canonical correlation analysis through biplots of stucture correlations and weights
Braak, ter C.J.F.
1990-01-01
This paper extends the biplot technique to canonical correlation analysis and redundancy analysis. The plot of structure correlations is shown to the optimal for displaying the pairwise correlations between the variables of the one set and those of the second. The link between multivariate regressio
Constrained Canonical Correlation.
DeSarbo, Wayne S.; And Others
1982-01-01
A variety of problems associated with the interpretation of traditional canonical correlation are discussed. A response surface approach is developed which allows for investigation of changes in the coefficients while maintaining an optimum canonical correlation value. Also, a discrete or constrained canonical correlation method is presented. (JKS)
A NOVEL ALGORITHM FOR VOICE CONVERSION USING CANONICAL CORRELATION ANALYSIS
Jian Zhihua; Yang Zhen
2008-01-01
A novel algorithm for voice conversion is proposed in this paper. The mapping function of spectral vectors of the source and target speakers is calculated by the Canonical Correlation Analysis(CCA) estimation based on Gaussian mixture models. Since the spectral envelope feature remains a majority of second order statistical information contained in speech after Linear Prediction Coding(LPC) analysis, the CCA method is more suitable for spectral conversion than Minimum Mean Square Error (MMSE) because CCA explicitly considers the variance of each component of the spectral vectors during conversion procedure. Both objective evaluations and subjective listening tests are conducted. The experimental results demonstrate that the proposed scheme can achieve better performance than the previous method which uses MMSE estimation criterion.
Climate Prediction Center(CPC)Ensemble Canonical Correlation Analysis Forecast of Temperature
National Oceanic and Atmospheric Administration, Department of Commerce — The Ensemble Canonical Correlation Analysis (ECCA) temperature forecast is a 90-day (seasonal) outlook of US surface temperature anomalies. The ECCA uses Canonical...
Rainforth, Tom; Wood, Frank
2015-01-01
We introduce canonical correlation forests (CCFs), a new decision tree ensemble method for classification. Individual canonical correlation trees are binary decision trees with hyperplane splits based on canonical correlation components. Unlike axis-aligned alternatives, the decision surfaces of CCFs are not restricted to the coordinate system of the input features and therefore more naturally represent data with correlation between the features. Additionally we introduce a novel alternative ...
Analysis of multivariate genotype - environment data using Nonlinear Canonical Correlation Analysis
Pinnschmidt, H.O.
2004-01-01
Nonlinear Canonical Correlation Analysis (NCCA) is a method well suited for visualising the main features in multivariate data of various scales. NCCA is useful for obtaining an overall orientation of genotype properties and environment characteristics.
A canonical correlation analysis of intelligence and executive functioning.
Davis, Andrew S; Pierson, Eric E; Finch, W Holmes
2011-01-01
Executive functioning is one of the most researched and debated topics in neuropsychology. Although neuropsychologists routinely consider executive functioning and intelligence in their assessment process, more information is needed regarding the relationship between these constructs. This study reports the results of a canonical correlation study between the most widely used measure of adult intelligence, the Wechsler Adult Intelligence Scale, 3rd edition (WAIS-III; Wechsler, 1997), and the Delis-Kaplan Executive Function System (D-KEFS; Delis, Kaplan, & Kramer, 2001). The results suggest that, despite considerable shared variability, the measures of executive functioning maintain unique variance that is not encapsulated in the construct of global intelligence. PMID:21390902
Creativity and Brain-Functioning in Product Development Engineers: A Canonical Correlation Analysis
Travis, Frederick; Lagrosen, Yvonne
2014-01-01
This study used canonical correlation analysis to explore the relation among scores on the Torrance test of figural and verbal creativity and demographic, psychological and physiological measures in Swedish product-development engineers. The first canonical variate included figural and verbal flexibility and originality as dependent measures and…
National Oceanic and Atmospheric Administration, Department of Commerce — The Ensemble Canonical Correlation Analysis (ECCA) precipitation forecast is a 90-day (seasonal) outlook of US surface precipitation anomalies. The ECCA uses...
Interpreting Canonical Correlation Analysis through Biplots of Structure Correlations and Weights.
ter Braak, Cajo J. F.
1990-01-01
Canonical weights and structure correlations are used to construct low dimensional views of the relationships between two sets of variables. These views, in the form of biplots, display familiar statistics: correlations between pairs of variables, and regression coefficients. (SLD)
Linear and Nonlinear Multiset Canonical Correlation Analysis (invited talk)
Hilger, Klaus Baggesen; Nielsen, Allan Aasbjerg; Larsen, Rasmus;
2002-01-01
the sum of the pair-wise correlations over all sets. The new algorithm is termed multi-set ACE (MACE) and can find multiple orthogonal eigensolutions. MACE is a generalization of the linear multiset correlations analysis (MCCA). It handles multivariate multisets of arbitrary mixtures of both...... continuous and categorical variables by applying only bivariate scatterplot smoothers for which the data analyst may specify appropriate restrictions when performing an exploratory analysis of the data....
Charlene C. Lew; De Bruin, Gideon P.
2006-01-01
This study investigated the relationships between the scales of the Adult Career Concerns Inventory (ACCI) and those of the Career Attitudes and Strategies Inventory (CASI). The scores of 202 South African adults for the two inventories were subjected to a canonical correlation analysis. Two canonical variates made statistically significant contributions to the explanation of the relationships between the two sets of variables. Inspection of the correlations of the original variables with the...
Erayman, Mustafa; Abeyo, Bekele Geleta; Baenziger, P. Stephen; Budak, Hikmet; Eskridge, Kent M
2006-01-01
To examine the seedling characteristics of nine different bread wheat (Triticum aestivum L.) varieties, several variables regarding seedling size and germination characteristics were analyzed using canonical correlation analysis. Significantly correlated first canonical variate pairs indicated that the variables within each set such as coleoptile length, shoot length and fresh weight within size set, and emergence rate index and germination percentage can be regarded as main factors for vigor...
Charlene C Lew
2006-03-01
Full Text Available This study investigated the relationships between the scales of the Adult Career Concerns Inventory (ACCI and those of the Career Attitudes and Strategies Inventory (CASI. The scores of 202 South African adults for the two inventories were subjected to a canonical correlation analysis. Two canonical variates made statistically significant contributions to the explanation of the relationships between the two sets of variables. Inspection of the correlations of the original variables with the first canonical variate suggested that a high level of career concerns in general, as measured by the ACCI, is associated with high levels of career worries, more geographical barriers, a low risk-taking style and a non-dominant interpersonal style, as measured by the CASI. The second canonical variate suggested that concerns with career exploration and advancement of one’s career is associated with low job satisfaction, low family commitment, high work involvement, and a dominant style at work.
Canonical Information Analysis
Vestergaard, Jacob Schack; Nielsen, Allan Aasbjerg
2015-01-01
Canonical correlation analysis is an established multivariate statistical method in which correlation between linear combinations of multivariate sets of variables is maximized. In canonical information analysis introduced here, linear correlation as a measure of association between variables is...... replaced by the information theoretical, entropy based measure mutual information, which is a much more general measure of association. We make canonical information analysis feasible for large sample problems, including for example multispectral images, due to the use of a fast kernel density estimator...... for entropy estimation. Canonical information analysis is applied successfully to (1) simple simulated data to illustrate the basic idea and evaluate performance, (2) fusion of weather radar and optical geostationary satellite data in a situation with heavy precipitation, and (3) change detection in...
Resistant multiple sparse canonical correlation.
Coleman, Jacob; Replogle, Joseph; Chandler, Gabriel; Hardin, Johanna
2016-04-01
Canonical correlation analysis (CCA) is a multivariate technique that takes two datasets and forms the most highly correlated possible pairs of linear combinations between them. Each subsequent pair of linear combinations is orthogonal to the preceding pair, meaning that new information is gleaned from each pair. By looking at the magnitude of coefficient values, we can find out which variables can be grouped together, thus better understanding multiple interactions that are otherwise difficult to compute or grasp intuitively. CCA appears to have quite powerful applications to high-throughput data, as we can use it to discover, for example, relationships between gene expression and gene copy number variation. One of the biggest problems of CCA is that the number of variables (often upwards of 10,000) makes biological interpretation of linear combinations nearly impossible. To limit variable output, we have employed a method known as sparse canonical correlation analysis (SCCA), while adding estimation which is resistant to extreme observations or other types of deviant data. In this paper, we have demonstrated the success of resistant estimation in variable selection using SCCA. Additionally, we have used SCCA to find multiple canonical pairs for extended knowledge about the datasets at hand. Again, using resistant estimators provided more accurate estimates than standard estimators in the multiple canonical correlation setting. R code is available and documented at https://github.com/hardin47/rmscca. PMID:26963062
Resistant Multiple Sparse Canonical Correlation
Coleman, Jacob; Replogle, Joseph; Chandler, Gabriel; Hardin, Johanna
2014-01-01
Canonical Correlation Analysis (CCA) is a multivariate technique that takes two datasets and forms the most highly correlated possible pairs of linear combinations between them. Each subsequent pair of linear combinations is orthogonal to the preceding pair, meaning that new information is gleaned from each pair. By looking at the magnitude of coefficient values, we can find out which variables can be grouped together, thus better understanding multiple interactions that are otherwise difficu...
Costa, Valter Magalhaes; Pereira, Iraci Martinez, E-mail: valter.costa@usp.b [Instituto de Pesquisas Energeticas e Nucleares (IPEN/CNEN-SP), Sao Paulo, SP (Brazil)
2011-07-01
The monitoring of variables and diagnosis of sensor fault in nuclear power plants or processes industries is very important because a previous diagnosis allows the correction of the fault and, like this, to prevent the production stopped, improving operator's security and it's not provoking economics losses. The objective of this work is to build a set, using bivariate correlation and canonical correlation, which will be the set of input variables of an artificial neural network to monitor the greater number of variables. This methodology was applied to the IEA-R1 Research Reactor at IPEN. Initially, for the input set of neural network we selected the variables: nuclear power, primary circuit flow rate, control/safety rod position and difference in pressure in the core of the reactor, because almost whole of monitoring variables have relation with the variables early described or its effect can be result of the interaction of two or more. The nuclear power is related to the increasing and decreasing of temperatures as well as the amount radiation due fission of the uranium; the rods are controls of power and influence in the amount of radiation and increasing and decreasing of temperatures; the primary circuit flow rate has the function of energy transport by removing the nucleus heat. An artificial neural network was trained and the results were satisfactory since the IEA-R1 Data Acquisition System reactor monitors 64 variables and, with a set of 9 input variables resulting from the correlation analysis, it was possible to monitor 51 variables. (author)
The monitoring of variables and diagnosis of sensor fault in nuclear power plants or processes industries is very important because a previous diagnosis allows the correction of the fault and, like this, to prevent the production stopped, improving operator's security and it's not provoking economics losses. The objective of this work is to build a set, using bivariate correlation and canonical correlation, which will be the set of input variables of an artificial neural network to monitor the greater number of variables. This methodology was applied to the IEA-R1 Research Reactor at IPEN. Initially, for the input set of neural network we selected the variables: nuclear power, primary circuit flow rate, control/safety rod position and difference in pressure in the core of the reactor, because almost whole of monitoring variables have relation with the variables early described or its effect can be result of the interaction of two or more. The nuclear power is related to the increasing and decreasing of temperatures as well as the amount radiation due fission of the uranium; the rods are controls of power and influence in the amount of radiation and increasing and decreasing of temperatures; the primary circuit flow rate has the function of energy transport by removing the nucleus heat. An artificial neural network was trained and the results were satisfactory since the IEA-R1 Data Acquisition System reactor monitors 64 variables and, with a set of 9 input variables resulting from the correlation analysis, it was possible to monitor 51 variables. (author)
Multiset Canonical Correlations Analysis and Multispectral, Truly Multitemporal Remote Sensing Data
Nielsen, Allan Aasbjerg
2002-01-01
This paper describes two- and multiset canonical correlations analysis (CCA) for data fusion, multi-source, multiset or multi-temporal exploratory data analysis. These techniques transform multivariate multiset data into new orthogonal variables called canonical variates (CVs) which when applied in...... remote sensing exhibit ever decreasing similarity (as expressed by correlation measures) over sets consisting of 1) spectral variables at fixed points in time (R-mode analysis), or 2) temporal variables with fixed wavelengths (T-mode analysis). The CVs are invariant to linear and affine transformations...... different. This difference is ascribed to the noise structure in the data. The CCA methods are related to partial least squares (PLS) methods. The paper very briefly describes multiset CCA based multiset PLS. Also, the CCA methods can be applied as multivariate extensions to empirical orthogonal functions...
Bilenko, Natalia Y.; Gallant, Jack L.
2015-01-01
Canonical correlation analysis (CCA) is a valuable method for interpreting cross-covariance across related datasets of different dimensionality. There are many potential applications of CCA to neuroimaging data analysis. For instance, CCA can be used for finding functional similarities across fMRI datasets collected from multiple subjects without resampling individual datasets to a template anatomy. In this paper, we introduce Pyrcca, an open-source Python module for executing CCA between two...
The monitoring of variables and diagnosis of sensor fault in nuclear power plants or processes industries is very important because an early diagnosis allows the correction of the fault and, like this, do not cause the production interruption, improving operator's security and it's not provoking economics losses. The objective of this work is, in the whole of all variables monitor of a nuclear power plant, to build a set, not necessary minimum, which will be the set of input variables of an artificial neural network and, like way, to monitor the biggest number of variables. This methodology was applied to the IEA-R1 Research Reactor at IPEN. For this, the variables Power, Rate of flow of primary circuit, Rod of control/security and Difference in pressure in the core of the reactor ( Δ P) was grouped, because, for hypothesis, almost whole of monitoring variables have relation with the variables early described or its effect can be result of the interaction of two or more. The Power is related to the increasing and decreasing of temperatures as well as the amount radiation due fission of the uranium; the Rods are controls of power and influence in the amount of radiation and increasing and decreasing of temperatures and the Rate of flow of primary circuit has function of the transport of energy by removing of heat of the nucleus Like this, labeling B= {Power, Rate of flow of Primary Circuit, Rod of Control/Security and Δ P} was computed the correlation between B and all another variables monitoring (coefficient of multiple correlation), that is, by the computer of the multiple correlation, that is tool of Theory of Canonical Correlations, was possible to computer how much the set B can predict each variable. Due the impossibility of a satisfactory approximation by B in the prediction of some variables, it was included one or more variables that have high correlation with this variable to improve the quality of prediction. In this work an artificial neural network
Wu, Guo Rong; Chen, Fuyong; Kang, Dezhi; Zhang, Xiangyang; Marinazzo, Daniele; Chen, Huafu
2011-11-01
Multivariate Granger causality is a well-established approach for inferring information flow in complex systems, and it is being increasingly applied to map brain connectivity. Traditional Granger causality is based on vector autoregressive (AR) or mixed autoregressive moving average (ARMA) model, which are potentially affected by errors in parameter estimation and may be contaminated by zero-lag correlation, notably when modeling neuroimaging data. To overcome this issue, we present here an extended canonical correlation approach to measure multivariate Granger causal interactions among time series. The procedure includes a reduced rank step for calculating canonical correlation analysis (CCA), and extends the definition of causality including instantaneous effects, thus avoiding the potential estimation problems of AR (or ARMA) models. We tested this approach on simulated data and confirmed its practical utility by exploring local network connectivity at different scales in the epileptic brain analyzing scalp and depth-EEG data during an interictal period. PMID:21788178
Getting full control of canonical correlation analysis with the AutoBiplot.CCA function
Alves, M. Rui
2016-06-01
Function AutoBiplot.CCA was built in R language. Given two multivariate data sets, this function carries out a conventional canonical correlation analysis, followed by the automatic production of predictive biplots based on the accuracy of readings as assessed by a mean standard predictive error and a user defined tolerance value. As the user's intervention is mainly restricted to the choice of the magnitude of the t.axis value, common misinterpretations, overestimations and adjustments between outputs and personal beliefs are avoided.
A canonical correlation analysis based method for contamination event detection in water sources.
Li, Ruonan; Liu, Shuming; Smith, Kate; Che, Han
2016-06-15
In this study, a general framework integrating a data-driven estimation model is employed for contamination event detection in water sources. Sequential canonical correlation coefficients are updated in the model using multivariate water quality time series. The proposed method utilizes canonical correlation analysis for studying the interplay between two sets of water quality parameters. The model is assessed by precision, recall and F-measure. The proposed method is tested using data from a laboratory contaminant injection experiment. The proposed method could detect a contamination event 1 minute after the introduction of 1.600 mg l(-1) acrylamide solution. With optimized parameter values, the proposed method can correctly detect 97.50% of all contamination events with no false alarms. The robustness of the proposed method can be explained using the Bauer-Fike theorem. PMID:27264637
Sliusarenko, Tamara; Clemmensen, Line Katrine Harder
At the Technical University of Denmark (DTU) course evaluations are performed by the students on a questionnaire. On one form the students are asked specific questions regarding the course. On a second form they are asked specific questions about the teacher. We propose to apply canonical...... correlation analysis (CCA) to investigate the association between how students evaluate the course and how students evaluate the teacher and to reveal the structure of this association. Student’s evaluation data is characterized by high correlation between the variables (questions) and insufficient sample...
Krafty, Robert T; Hall, Martica
2013-03-01
Although many studies collect biomedical time series signals from multiple subjects, there is a dearth of models and methods for assessing the association between frequency domain properties of time series and other study outcomes. This article introduces the random Cramér representation as a joint model for collections of time series and static outcomes where power spectra are random functions that are correlated with the outcomes. A canonical correlation analysis between cepstral coefficients and static outcomes is developed to provide a flexible yet interpretable measure of association. Estimates of the canonical correlations and weight functions are obtained from a canonical correlation analysis between the static outcomes and maximum Whittle likelihood estimates of truncated cepstral coefficients. The proposed methodology is used to analyze the association between the spectrum of heart rate variability and measures of sleep duration and fragmentation in a study of older adults who serve as the primary caregiver for their ill spouse. PMID:24851143
Detection for gene-gene co-association via kernel canonical correlation analysis
Yuan Zhongshang
2012-10-01
Full Text Available Abstract Background Currently, most methods for detecting gene-gene interaction (GGI in genomewide association studies (GWASs are limited in their use of single nucleotide polymorphism (SNP as the unit of association. One way to address this drawback is to consider higher level units such as genes or regions in the analysis. Earlier we proposed a statistic based on canonical correlations (CCU as a gene-based method for detecting gene-gene co-association. However, it can only capture linear relationship and not nonlinear correlation between genes. We therefore proposed a counterpart (KCCU based on kernel canonical correlation analysis (KCCA. Results Through simulation the KCCU statistic was shown to be a valid test and more powerful than CCU statistic with respect to sample size and interaction odds ratio. Analysis of data from regions involving three genes on rheumatoid arthritis (RA from Genetic Analysis Workshop 16 (GAW16 indicated that only KCCU statistic was able to identify interactions reported earlier. Conclusions KCCU statistic is a valid and powerful gene-based method for detecting gene-gene co-association.
Canonical correlation analysis of the characteristics of charcoal from Qualea parviflora Mart.
Thiago de Paula Protásio
2014-03-01
Full Text Available This study aimed to examine the relationships between the characteristics of charcoal from Qualea parviflora Mart. using canonical correlation analysis. Five trees were analyzed in such way that 5-cm thick discs were removed from each tree at the base, DBH (1.30 m, middle and top sections. The wood was carbonized in a muffle furnace at a heating rate of 1.67 °C min-1. A canonical correlation analysis was conducted to investigate the relationships between the group formed by fixed carbon, volatile matter, ash, elemental carbon, hydrogen, nitrogen, sulfur and oxygen levels and a second group formed by the gravimetric yield, higher heating value and relative bulk density of the charcoal. A tendency was noted for high levels of fixed carbon and elemental carbon to be associated to low levels of volatile matter, ash and oxygen and to low gravimetric yield. Fixed carbon and elemental carbon levels had a positive relation to higher heating value and to relative bulk density, whereas volatile matter, ash and oxygen levels had a negative relation to such characteristics. The higher the gravimetric yield from carbonization, the higher the volatile matter, ash and oxygen levels will be in the resulting charcoal.
Analysis of Input and Output of China’s Agriculture Based on Canonical Correlation
2011-01-01
I select effective irrigated area, consumption of agricultural chemical fertilizer, electricity consumed in rural areas, and total power of agricultural machinery as input variables of China’s agriculture; I select grain, bean, tobacco, oil-bearing crop and fruit as output variables of China’s agriculture. By using the data of China Statistical Yearbook in 2010, based on the analysis method of canonical correlation, I conduct research on the input and output of China’s agriculture. The results show that consumption of chemical fertilizer has the biggest impact on the agricultural output of China, followed by the input of total power of agricultural machinery; the canonical variable of agricultural output of China is mainly impacted by grain, oil-bearing crop and fruit; in terms of the selected variables, the output increase of grain, oil-bearing crop and fruit in China arises from the input increase of agricultural chemical fertilizer and machinery, and there is high-degree correlation between the two. According to the conclusions, the policy suggestions are put forward as follows: gradually decrease consumption of chemical fertilizer; increase the use of modern agricultural machinery; increase agricultural irrigation input.
The integrated model of sport confidence: a canonical correlation and mediational analysis.
Koehn, Stefan; Pearce, Alan J; Morris, Tony
2013-12-01
The main purpose of the study was to examine crucial parts of Vealey's (2001) integrated framework hypothesizing that sport confidence is a mediating variable between sources of sport confidence (including achievement, self-regulation, and social climate) and athletes' affect in competition. The sample consisted of 386 athletes, who completed the Sources of Sport Confidence Questionnaire, Trait Sport Confidence Inventory, and Dispositional Flow Scale-2. Canonical correlation analysis revealed a confidence-achievement dimension underlying flow. Bias-corrected bootstrap confidence intervals in AMOS 20.0 were used in examining mediation effects between source domains and dispositional flow. Results showed that sport confidence partially mediated the relationship between achievement and self-regulation domains and flow, whereas no significant mediation was found for social climate. On a subscale level, full mediation models emerged for achievement and flow dimensions of challenge-skills balance, clear goals, and concentration on the task at hand. PMID:24334324
Ignacio Santamaría
2008-04-01
Full Text Available This paper treats the identification of nonlinear systems that consist of a cascade of a linear channel and a nonlinearity, such as the well-known Wiener and Hammerstein systems. In particular, we follow a supervised identification approach that simultaneously identifies both parts of the nonlinear system. Given the correct restrictions on the identification problem, we show how kernel canonical correlation analysis (KCCA emerges as the logical solution to this problem. We then extend the proposed identification algorithm to an adaptive version allowing to deal with time-varying systems. In order to avoid overfitting problems, we discuss and compare three possible regularization techniques for both the batch and the adaptive versions of the proposed algorithm. Simulations are included to demonstrate the effectiveness of the presented algorithm.
Study on soil water characteristics of tobacco fields based on canonical correlation analysis
Xiao-hou SHAO; Yu WANG; Li-dong BI; You-bo YUAN; Xian-kun SU; Jian-guo MO
2009-01-01
In order to identify the principal factors influencing soil water characteristics (SWC) and evaluate SWC effectively, the multivariate-statistical canonical correlation analysis (CCA) method was used to study and analyze the correlation between SWC and soil physical and chemical properties. Twenty-two soil samples were taken from 11 main tobacco-growing areas in Guizhou Province in China and the soil water characteristic curves (SWCC) and basic physical and chemical properties of the soil samples were determined. The results show that: (1) The soil bulk density, soil total porosity and soil capillary porosity have significant effects on SWC of tobacco fiels. Bulk density and total porosity are positively correlated with soil water retention characteristics (SWRC), and soil capillary porosity is positively correlated with soil water supply characteristics (SWSC). (2) Soil samples from different soil layers at the same soil sampling point show similarity or consistency in SWC. Inadequate soil water supply capability and imbalance between SWRC and SWSC are problems of tobacco soil. (3) The SWC of loamy clay are generally superior to those of silty clay loam.
Personalized Subject Learning Based on Topic Detection and Canonical Correlation Analysis
Zhangzu SHI
2015-10-01
Full Text Available To keep pace with the time, learning from printed medium alone is no longer a comprehensive approach. Fresh digital contents can definitely be the complement of printed education medium. Although timely access to fresh contents is becoming increasingly important for education and gaining such access is no longer a problem, the capacity for human teachers to assimilate such huge amounts of contents is limited. Topic Detection (TD is then a promising research area that addresses speedy access of desired contents based on topic or subject. On the other hand, personalized education is getting more attention because it facilitates the improvement of creativity and subject learning of the students. This paper reveals a patented Personalized Subject Learning (PSL system that caters for the need of personalized education and efficiently provides subject based contents. An efficient topic detection algorithm for providing subject content is presented. Moreover, since education contents are multimedia based ones with multimodal, PSL introduces Canonical Correlation Analysis (CCA method to detect multimodal correlations across different types of media. Due to its novelty, PSL has been used as the key engine in a real world application of personalized education system as the smart education module sponsored by a Smart City project.
Hesse Morten
2005-05-01
Full Text Available Abstract Background Personality disorders are common in substance abusers. Self-report questionnaires that can aid in the assessment of personality disorders are commonly used in assessment, but are rarely validated. Methods The Danish DIP-Q as a measure of co-morbid personality disorders in substance abusers was validated through principal components factor analysis and canonical correlation analysis. A 4 components structure was constructed based on 238 protocols, representing antagonism, neuroticism, introversion and conscientiousness. The structure was compared with (a a 4-factor solution from the DIP-Q in a sample of Swedish drug and alcohol abusers (N = 133, and (b a consensus 4-components solution based on a meta-analysis of published correlation matrices of dimensional personality disorder scales. Results It was found that the 4-factor model of personality was congruent across the Danish and Swedish samples, and showed good congruence with the consensus model. A canonical correlation analysis was conducted on a subset of the Danish sample with staff ratings of pathology. Three factors that correlated highly between the two variable sets were found. These variables were highly similar to the three first factors from the principal components analysis, antagonism, neuroticism and introversion. Conclusion The findings support the validity of the DIP-Q as a measure of DSM-IV personality disorders in substance abusers.
Extending Local Canonical Correlation Analysis to Handle General Linear Contrasts for fMRI Data
Mingwu Jin
2012-01-01
Full Text Available Local canonical correlation analysis (CCA is a multivariate method that has been proposed to more accurately determine activation patterns in fMRI data. In its conventional formulation, CCA has several drawbacks that limit its usefulness in fMRI. A major drawback is that, unlike the general linear model (GLM, a test of general linear contrasts of the temporal regressors has not been incorporated into the CCA formalism. To overcome this drawback, a novel directional test statistic was derived using the equivalence of multivariate multiple regression (MVMR and CCA. This extension will allow CCA to be used for inference of general linear contrasts in more complicated fMRI designs without reparameterization of the design matrix and without reestimating the CCA solutions for each particular contrast of interest. With the proper constraints on the spatial coefficients of CCA, this test statistic can yield a more powerful test on the inference of evoked brain regional activations from noisy fMRI data than the conventional t-test in the GLM. The quantitative results from simulated and pseudoreal data and activation maps from fMRI data were used to demonstrate the advantage of this novel test statistic.
Lei, Baiying; Chen, Siping; Ni, Dong; Wang, Tianfu
2016-01-01
To address the challenging task of diagnosing neurodegenerative brain disease, such as Alzheimer's disease (AD) and mild cognitive impairment (MCI), we propose a novel method using discriminative feature learning and canonical correlation analysis (CCA) in this paper. Specifically, multimodal features and their CCA projections are concatenated together to represent each subject, and hence both individual and shared information of AD disease are captured. A discriminative learning with multilayer feature hierarchy is designed to further improve performance. Also, hybrid representation is proposed to maximally explore data from multiple modalities. A novel normalization method is devised to tackle the intra- and inter-subject variations from the multimodal data. Based on our extensive experiments, our method achieves an accuracy of 96.93% [AD vs. normal control (NC)], 86.57 % (MCI vs. NC), and 82.75% [MCI converter (MCI-C) vs. MCI non-converter (MCI-NC)], respectively, which outperforms the state-of-the-art methods in the literature. PMID:27242506
Satomura, Hironori; Adachi, Kohei
2013-07-01
To facilitate the interpretation of canonical correlation analysis (CCA) solutions, procedures have been proposed in which CCA solutions are orthogonally rotated to a simple structure. In this paper, we consider oblique rotation for CCA to provide solutions that are much easier to interpret, though only orthogonal rotation is allowed in the existing formulations of CCA. Our task is thus to reformulate CCA so that its solutions have the freedom of oblique rotation. Such a task can be achieved using Yanai's (Jpn. J. Behaviormetrics 1:46-54, 1974; J. Jpn. Stat. Soc. 11:43-53, 1981) generalized coefficient of determination for the objective function to be maximized in CCA. The resulting solutions are proved to include the existing orthogonal ones as special cases and to be rotated obliquely without affecting the objective function value, where ten Berge's (Psychometrika 48:519-523, 1983) theorems on suborthonormal matrices are used. A real data example demonstrates that the proposed oblique rotation can provide simple, easily interpreted CCA solutions. PMID:25106398
DNA pattern recognition using canonical correlation algorithm
B K Sarkar; Chiranjib Chakraborty
2015-10-01
We performed canonical correlation analysis as an unsupervised statistical tool to describe related views of the same semantic object for identifying patterns. A pattern recognition technique based on canonical correlation analysis (CCA) was proposed for finding required genetic code in the DNA sequence. Two related but different objects were considered: one was a particular pattern, and other was test DNA sequence. CCA found correlations between two observations of the same semantic pattern and test sequence. It is concluded that the relationship possesses maximum value in the position where the pattern exists. As a case study, the potential of CCA was demonstrated on the sequence found from HIV-1 preferred integration sites. The subsequences on the left and right flanking from the integration site were considered as the two views, and statistically significant relationships were established between these two views to elucidate the viral preference as an important factor for the correlation.
Johann M Schepers
2006-02-01
Full Text Available The principal objective of the study was to determine the utility of canonical correlation analysis, coupled with target rotation, in coping with the effects of differential skewness of variables representing two batteries of tests. Generally speaking joint factor analyses of two or more batteries of tests result in factors of skewness rather than factors of content. To examine the problem, the General Scholastic Aptitude Test (GSAT and Senior Ability Tests (SAT were jointly applied to a sample of 1598 first-year university students, and subjected to both a principal factor analysis (PFA and a canonical correlation analysis (CCA, coupled with target rotation. Three factors were obtained in both inst ances. The PFA yielded factors of skewness and the CCA factors of content. The target rotation gave a good fit with the theoretically specified values. The implications of the findings are discussed.
Lee, Hye-Seung; Paik, Myunghee Cho; Lee, Joseph H.
2008-01-01
Analysis of multiple traits can provide additional information beyond analysis of a single trait, allowing better understanding of the underlying genetic mechanism of a common disease. To accommodate multiple traits in familial correlation analysis adjusting for confounders, we develop a regression model for canonical correlation parameters and propose joint modeling along with mean and scale parameters. The proposed method is more powerful than the regression method modeling pairwise correla...
Caicedo Dorado, Alexander; Papademetriou, M. D.; Elwell, C. E.; Hoskote, A; Elliot, M J; Van Huffel, Sabine; Tachtsidis, I
2013-01-01
Neonates supported on extracorporeal membrane oxygenation (ECMO) are at high risk of brain injury due to haemodynamic instability. In order to monitor cerebral and peripheral (muscle) haemodynamic and oxygenation changes in this population we used a dual-channel near-infrared spectroscopy (NIRS) system. In addition, to assess interrelations between NIRS and systemic variables, collected simultaneously, canonical correlation analysis (CCA) was employed. CCA can quantify the relationship betwee...
Jing LIU; Drane, Wanzer; Liu, Xuefeng; Wu, Tiejian
2008-01-01
This study was to explore the relationships between personal exposure to ten volatile organic compounds (VOCs) and biochemical liver tests with the application of canonical correlation analysis. Data from a subsample of the 1999–2000 National Health and Nutrition Examination Survey were used. Serum albumin, total bilirubin (TB), alanine aminotransferase (ALT), aspartate aminotransferase (AST), lactate dehydrogenase (LDH), alkaline phosphatase (ALP), and γ-glutamyl transferase (GGT) served as ...
Life skills and subjective well-being of people with disabilities: a canonical correlation analysis.
da Silva Cardoso, Elizabeth; Blalock, Kacie; Allen, Chase A; Chan, Fong; Rubin, Stanford E
2004-12-01
This study examined the canonical relationships between a set of life skill variables and a set of subjective well-being variables among a national sample of vocational rehabilitation clients in the USA. Self-direction, work tolerance, general employability, and self-care were related to physical, family and social, and financial well-being. This analysis also found that communication skill is related to family and social well-being, while psychological well-being is not related to any life skills in the set. The results showed that vocational rehabilitation services aimed to improve life functioning will lead to an improvement in subjective quality of life. PMID:15573000
Singanamalli, Asha; Wang, Haibo; Lee, George; Shih, Natalie; Rosen, Mark; Master, Stephen; Tomaszewski, John; Feldman, Michael; Madabhushi, Anant
2014-03-01
While the plethora of information from multiple imaging and non-imaging data streams presents an opportunity for discovery of fused multimodal, multiscale biomarkers, they also introduce multiple independent sources of noise that hinder their collective utility. The goal of this work is to create fused predictors of disease diagnosis and prognosis by combining multiple data streams, which we hypothesize will provide improved performance as compared to predictors from individual data streams. To achieve this goal, we introduce supervised multiview canonical correlation analysis (sMVCCA), a novel data fusion method that attempts to find a common representation for multiscale, multimodal data where class separation is maximized while noise is minimized. In doing so, sMVCCA assumes that the different sources of information are complementary and thereby act synergistically when combined. Although this method can be applied to any number of modalities and to any disease domain, we demonstrate its utility using three datasets. We fuse (i) 1.5 Tesla (T) magnetic resonance imaging (MRI) features with cerbrospinal fluid (CSF) proteomic measurements for early diagnosis of Alzheimer's disease (n = 30), (ii) 3T Dynamic Contrast Enhanced (DCE) MRI and T2w MRI for in vivo prediction of prostate cancer grade on a per slice basis (n = 33) and (iii) quantitative histomorphometric features of glands and proteomic measurements from mass spectrometry for prediction of 5 year biochemical recurrence postradical prostatectomy (n = 40). Random Forest classifier applied to the sMVCCA fused subspace, as compared to that of MVCCA, PCA and LDA, yielded the highest classification AUC of 0.82 +/- 0.05, 0.76 +/- 0.01, 0.70 +/- 0.07, respectively for the aforementioned datasets. In addition, sMVCCA fused subspace provided 13.6%, 7.6% and 15.3% increase in AUC as compared with that of the best performing individual view in each of the three datasets, respectively. For the biochemical recurrence
Canonical correlations between chemical and energetic characteristics of lignocellulosic wastes
Thiago de Paula Protásio
2012-09-01
Full Text Available Canonical correlation analysis is a statistical multivariate procedure that allows analyzing linear correlation that may exist between two groups or sets of variables (X and Y. This paper aimed to provide canonical correlation analysis between a group comprised of lignin and total extractives contents and higher heating value (HHV with a group of elemental components (carbon, hydrogen, nitrogen and sulfur for lignocellulosic wastes. The following wastes were used: eucalyptus shavings; pine shavings; red cedar shavings; sugar cane bagasse; residual bamboo cellulose pulp; coffee husk and parchment; maize harvesting wastes; and rice husk. Only the first canonical function was significant, but it presented a low canonical R². High carbon, hydrogen and sulfur contents and low nitrogen contents seem to be related to high total extractives contents of the lignocellulosic wastes. The preliminary results found in this paper indicate that the canonical correlations were not efficient to explain the correlations between the chemical elemental components and lignin contents and higher heating values.
Alamgir Kabir
Full Text Available This analysis was conducted to explore the association between 5 birth size measurements (weight, length and head, chest and mid-upper arm [MUAC] circumferences as dependent variables and 10 maternal factors as independent variables using canonical correlation analysis (CCA. CCA considers simultaneously sets of dependent and independent variables and, thus, generates a substantially reduced type 1 error. Data were from women delivering a singleton live birth (n = 14,506 while participating in a double-masked, cluster-randomized, placebo-controlled maternal vitamin A or β-carotene supplementation trial in rural Bangladesh. The first canonical correlation was 0.42 (P<0.001, demonstrating a moderate positive correlation mainly between the 5 birth size measurements and 5 maternal factors (preterm delivery, early pregnancy MUAC, infant sex, age and parity. A significant interaction between infant sex and preterm delivery on birth size was also revealed from the score plot. Thirteen percent of birth size variability was explained by the composite score of the maternal factors (Redundancy, RY/X = 0.131. Given an ability to accommodate numerous relationships and reduce complexities of multiple comparisons, CCA identified the 5 maternal variables able to predict birth size in this rural Bangladesh setting. CCA may offer an efficient, practical and inclusive approach to assessing the association between two sets of variables, addressing the innate complexity of interactions.
Canonical correlations between chemical and energetic characteristics of lignocellulosic wastes
Thiago de Paula Protásio; Gustavo Henrique Denzin Tonoli; Mário Guimarães Júnior; Lina Bufalino; Allan Motta Couto; Paulo Fernando Trugilho
2012-01-01
Canonical correlation analysis is a statistical multivariate procedure that allows analyzing linear correlation that may exist between two groups or sets of variables (X and Y). This paper aimed to provide canonical correlation analysis between a group comprised of lignin and total extractives contents and higher heating value (HHV) with a group of elemental components (carbon, hydrogen, nitrogen and sulfur) for lignocellulosic wastes. The following wastes were used: eucalyptus shavings; pine...
Reynolds, Richard J.; Childers, Douglas K.; Pajewski, Nicholas M.
2009-01-01
Canonical analysis measures nonlinear selection on latent axes from a rotation of the gamma matrix (γ) of quadratic and correlation selection gradients. Here we document that the conventional method of testing eigenvalues (double regression) under the null hypothesis of no nonlinear selection is incorrect. Through simulation we demonstrate that under the null the expectation of some eigenvalues from canonical analysis will be nonzero, which leads to unacceptably high type 1 error rates. Using...
Prera, Alejandro J.; Grimsrud, Kristine M.; Thacher, Jennifer A.; McCollum, Dan W.; Berrens, Robert P.
2014-10-01
As public land management agencies pursue region-specific resource management plans, with meaningful consideration of public attitudes and values, there is a need to characterize the complex mix of environmental attitudes in a diverse population. The contribution of this investigation is to make use of a unique household, mail/internet survey data set collected in 2007 in the Southwestern United States (Region 3 of the U.S. Forest Service). With over 5,800 survey responses to a set of 25 Public Land Value statements, canonical correlation analysis is able to identify 7 statistically distinct environmental attitudinal groups. We also examine the effect of expected changes in regional demographics on overall environmental attitudes, which may help guide in the development of socially acceptable long-term forest management policies. Results show significant support for conservationist management policies and passive environmental values, as well as a greater role for stakeholder groups in generating consensus for current and future forest management policies.
Chen, Xiaogang; Wang, Yijun; Gao, Shangkai; Jung, Tzyy-Ping; Gao, Xiaorong
2015-08-01
Objective. Recently, canonical correlation analysis (CCA) has been widely used in steady-state visual evoked potential (SSVEP)-based brain-computer interfaces (BCIs) due to its high efficiency, robustness, and simple implementation. However, a method with which to make use of harmonic SSVEP components to enhance the CCA-based frequency detection has not been well established. Approach. This study proposed a filter bank canonical correlation analysis (FBCCA) method to incorporate fundamental and harmonic frequency components to improve the detection of SSVEPs. A 40-target BCI speller based on frequency coding (frequency range: 8-15.8 Hz, frequency interval: 0.2 Hz) was used for performance evaluation. To optimize the filter bank design, three methods (M1: sub-bands with equally spaced bandwidths; M2: sub-bands corresponding to individual harmonic frequency bands; M3: sub-bands covering multiple harmonic frequency bands) were proposed for comparison. Classification accuracy and information transfer rate (ITR) of the three FBCCA methods and the standard CCA method were estimated using an offline dataset from 12 subjects. Furthermore, an online BCI speller adopting the optimal FBCCA method was tested with a group of 10 subjects. Main results. The FBCCA methods significantly outperformed the standard CCA method. The method M3 achieved the highest classification performance. At a spelling rate of ˜33.3 characters/min, the online BCI speller obtained an average ITR of 151.18 ± 20.34 bits min-1. Significance. By incorporating the fundamental and harmonic SSVEP components in target identification, the proposed FBCCA method significantly improves the performance of the SSVEP-based BCI, and thereby facilitates its practical applications such as high-speed spelling.
Golugula Abhishek
2011-12-01
Full Text Available Abstract Background Multimodal data, especially imaging and non-imaging data, is being routinely acquired in the context of disease diagnostics; however, computational challenges have limited the ability to quantitatively integrate imaging and non-imaging data channels with different dimensionalities and scales. To the best of our knowledge relatively few attempts have been made to quantitatively fuse such data to construct classifiers and none have attempted to quantitatively combine histology (imaging and proteomic (non-imaging measurements for making diagnostic and prognostic predictions. The objective of this work is to create a common subspace to simultaneously accommodate both the imaging and non-imaging data (and hence data corresponding to different scales and dimensionalities, called a metaspace. This metaspace can be used to build a meta-classifier that produces better classification results than a classifier that is based on a single modality alone. Canonical Correlation Analysis (CCA and Regularized CCA (RCCA are statistical techniques that extract correlations between two modes of data to construct a homogeneous, uniform representation of heterogeneous data channels. In this paper, we present a novel modification to CCA and RCCA, Supervised Regularized Canonical Correlation Analysis (SRCCA, that (1 enables the quantitative integration of data from multiple modalities using a feature selection scheme, (2 is regularized, and (3 is computationally cheap. We leverage this SRCCA framework towards the fusion of proteomic and histologic image signatures for identifying prostate cancer patients at the risk of 5 year biochemical recurrence following radical prostatectomy. Results A cohort of 19 grade, stage matched prostate cancer patients, all of whom had radical prostatectomy, including 10 of whom had biochemical recurrence within 5 years of surgery and 9 of whom did not, were considered in this study. The aim was to construct a lower
Conventional analysis of clinical resting electroencephalography (EEG) recordings typically involves assessment of spectral power in pre-defined frequency bands at specific electrodes. EEG is a potentially useful technique in drug development for measuring the pharmacodynamic (PD) effects of a centrally acting compound and hence to assess the likelihood of success of a novel drug based on pharmacokinetic–pharmacodynamic (PK–PD) principles. However, the need to define the electrodes and spectral bands to be analysed a priori is limiting where the nature of the drug-induced EEG effects is initially not known. We describe the extension to human EEG data of a generalised semi-linear canonical correlation analysis (GSLCCA), developed for small animal data. GSLCCA uses data from the whole spectrum, the entire recording duration and multiple electrodes. It provides interpretable information on the mechanism of drug action and a PD measure suitable for use in PK–PD modelling. Data from a study with low (analgesic) doses of the μ-opioid agonist, remifentanil, in 12 healthy subjects were analysed using conventional spectral edge analysis and GSLCCA. At this low dose, the conventional analysis was unsuccessful but plausible results consistent with previous observations were obtained using GSLCCA, confirming that GSLCCA can be successfully applied to clinical EEG data. (paper)
Winderbaum, Lyron; Koch, Inge; Mittal, Parul; Hoffmann, Peter
2016-06-01
Applying MALDI-MS imaging to tissue microarrays (TMAs) provides access to proteomics data from large cohorts of patients in a cost- and time-efficient way, and opens the potential for applying this technology in clinical diagnosis. The complexity of these TMA data-high-dimensional low sample size-provides challenges for the statistical analysis, as classical methods typically require a nonsingular covariance matrix that cannot be satisfied if the dimension is greater than the sample size. We use TMAs to collect data from endometrial primary carcinomas from 43 patients. Each patient has a lymph node metastasis (LNM) status of positive or negative, which we predict on the basis of the MALDI-MS imaging TMA data. We propose a variable selection approach based on canonical correlation analysis that explicitly uses the LNM information. We apply LDA to the selected variables only. Our method misclassifies 2.3-20.9% of patients by leave-one-out cross-validation and strongly outperforms LDA after reduction of the original data with principle component analysis. PMID:27028088
Cetin, Bayram; Ilhan, Mustafa; Yilmaz, Ferat
2014-01-01
The aim of this study is to examine the relationship between the fear of receiving negative criticism and taking academic risk through canonical correlation analysis-in which a relational model was used. The participants of the study consisted of 215 university students enrolled in various programs at Dicle University's Ziya Gökalp Faculty of…
Razavi, Amir Reza; Gill, Hans; Ahlfeldt, Hans; Shahsavar, Nosrat
2005-01-01
Data mining methods can be used for extracting specific medical knowledge such as important predictors for recurrence of breast cancer in pertinent data material. However, when there is a huge quantity of variables in the data material it is first necessary to identify and select important variables. In this study we present a preprocessing method for selecting important variables in a dataset prior to building a predictive model.In the dataset, data from 5787 female patients were analysed. To cover more predictors and obtain a better assessment of the outcomes, data were retrieved from three different registers: the regional breast cancer, tumour markers, and cause of death registers. After retrieving information about selected predictors and outcomes from the different registers, the raw data were cleaned by running different logical rules. Thereafter, domain experts selected predictors assumed to be important regarding recurrence of breast cancer. After that, Canonical Correlation Analysis (CCA) was applied as a dimension reduction technique to preserve the character of the original data.Artificial Neural Network (ANN) was applied to the resulting dataset for two different analyses with the same settings. Performance of the predictive models was confirmed by ten-fold cross validation. The results showed an increase in the accuracy of the prediction and reduction of the mean absolute error. PMID:16160255
Purevdorj, Oyunaa
2016-01-01
Teacher mathematical knowledge for teaching (MKT) (Ball et al, 2008) is a key to student achievement in school mathematics. In this paper, Mongolian secondary school teachers’ mathematical knowledge for teaching is analyzed using canonical correlation analysis (Hotelling, 1935) focusing on mathematical theory of concept image and concept definition (Tall & Vinner, 1981) of planes shapes in secondary geometry. The term “analysis” is conceptualized as identifying interrelations among sub-domain...
Canonical analysis based on mutual information
Nielsen, Allan Aasbjerg; Vestergaard, Jacob Schack
2015-01-01
Canonical correlation analysis (CCA) is an established multi-variate statistical method for finding similarities between linear combinations of (normally two) sets of multivariate observations. In this contribution we replace (linear) correlation as the measure of association between the linear...... combinations with the information theoretical measure mutual information (MI). We term this type of analysis canonical information analysis (CIA). MI allows for the actual joint distribution of the variables involved and not just second order statistics. While CCA is ideal for Gaussian data, CIA facilitates...... analysis of variables with different genesis and therefore different statistical distributions and different modalities. As a proof of concept we give a toy example. We also give an example with one (weather radar based) variable in the one set and eight spectral bands of optical satellite data in the...
Vahedi, Shahrum; Farrokhi, Farahman; Gahramani, Farahnaz; Issazadegan, Ali
2012-01-01
Objective: Approximately 66-80%of graduate students experience statistics anxiety and some researchers propose that many students identify statistics courses as the most anxiety-inducing courses in their academic curriculums. As such, it is likely that statistics anxiety is, in part, responsible for many students delaying enrollment in these courses for as long as possible. This paper proposes a canonical model by treating academic procrastination (AP), learning strategies (LS) as predictor v...
Li, Chuan-Yun; Cun WEI; Kai-wen PAN; Ma, Hai-Ying
2011-01-01
Objective The present study investigates the influence of professional stress and social support on professional burnout among low-rank army officers.Methods The professional stress,social support,and professional burnout scales among low-rank army officers were used as test tools.Moreover,the officers of established units(battalion,company,and platoon) were chosen as test subjects.Out of the 260 scales sent,226 effective scales were received.The descriptive statistic and canonical correlatio...
Canonical Correlation Analysis Used in Optimal Selection of Vernicia fordii%典型相关分析在油桐选优中的应用
徐永杰; 周席华; 罗治建; 章承林; 吴代坤; 肖小华; 郑孝严
2011-01-01
试验对油桐[Vernicia fordii(Hemsl.)Airy-Shaw]选优数据进行了连续三年的典型相关分析,结果显示,与油桐优树综合产油因子关系较密切的生长因子首先是绝干子含仁率、鲜子出干子率、树龄、枝下高、丛生果个数,其次是干仁含水率、单果重、鲜果出鲜子率、树高、层间距.利用典型相关方程对40株决选优树进行了聚类分析,结果显示,Ⅰ类中选含油率高的单株与在Ⅱ类中选产量高的单株,可作为下一步的无性系选育目标.%The canonical correlation analysis of the three-years Vernicia fordii (Hemal.) Airy-Shaw optimal selection showed that,first growth factors integrated with the oil producing factors of Ⅴ. fordii were absolutely dry seed rate with Jen, outlet dry seeds rate of fresh seeds, age of the tree, first branch height and the number of clustered fruits ;and the minor factors were moisture content of the dry nut, fruit weight, fresh seeds rate of fresh fruit, height of the tree and the spacing of layers. The cluster analysis of 40 plants of Ⅴ. fordii using canonical correlation equation showed that, high oil yield trees in type Ⅰ and high fruit yield trees in type Ⅱ could be selected as the next selection goals of ramets.
改进典型相关分析的虹膜鉴别算法%Iris recognition algorithm based on improved canonical correlation analysis
冯莹莹; 余世干; 刘辉
2014-01-01
Canonical Correlation Analysis(CCA)can not better portray the local changes in the iris image, a novel iris recognition method is proposed based on improved CCA algorithm in this paper. Firstly, the correlation between global features and local features are integrated to form the recognition features, the redundant information between the features is eliminated and the global information and local information is integrated effectively at the same time, the performance of ICCA is tested by CASIA datasets. The result show that ICCA’s recognition accuracy is significantly better than the reference model.%针对典型相关分析（CCA）无法准确刻画虹膜图像的局部遮挡变化缺陷，提出一种改进典型相关分析相融合（ICCA）的虹膜识别方法。以全局和局部特征间的相关性特征作为有效的判别信息，通过划分子模，并以简单投票进行结果矫正，提高方法的稳定性，以CASIA数据集验证ICCA的有效性。结果表明，ICCA的识别率明显优于参比方法。
Functional linear regression via canonical analysis
He, Guozhong; Wang, Jane-Ling; Yang, Wenjing; 10.3150/09-BEJ228
2011-01-01
We study regression models for the situation where both dependent and independent variables are square-integrable stochastic processes. Questions concerning the definition and existence of the corresponding functional linear regression models and some basic properties are explored for this situation. We derive a representation of the regression parameter function in terms of the canonical components of the processes involved. This representation establishes a connection between functional regression and functional canonical analysis and suggests alternative approaches for the implementation of functional linear regression analysis. A specific procedure for the estimation of the regression parameter function using canonical expansions is proposed and compared with an established functional principal component regression approach. As an example of an application, we present an analysis of mortality data for cohorts of medflies, obtained in experimental studies of aging and longevity.
Alexander, Erika D.
Canonical correlation analysis is a parsimonious way of breaking down the association between two sets of variables through the use of linear combinations. As a result of the analysis, many types of coefficients can be generated and interpreted. These coefficients are only considered stable and reliable if the number of subjects per variable is…
The Application of Canonical Correlation to Two-Dimensional Contingency Tables
Alberto F. Restori; Gary S. Katz; Howard B. Lee
2010-01-01
This paper re-introduces and demonstrates the use of Mickeys (1970) canonical correlation method in analyzing large two-dimensional contingency tables. This method of analysis supplements the traditional analysis using the Pearson chi-square. Examples and a MATLAB source listing are provided.
The Application of Canonical Correlation to Two-Dimensional Contingency Tables
Alberto F. Restori
2010-03-01
Full Text Available This paper re-introduces and demonstrates the use of Mickeys (1970 canonical correlation method in analyzing large two-dimensional contingency tables. This method of analysis supplements the traditional analysis using the Pearson chi-square. Examples and a MATLAB source listing are provided.
王大伟; 陈浩; 王延杰
2009-01-01
A new fusing facial feature recognition algorithm based on kernel Canonical Correlation Analysis ( Kernel CCA) was proposed,for mapping image data into feature space and improving classifying accuracy. In our approach, we first map the image data through kernel function,then extract feature from the directions of rows and columns. Our algorithm simplifies the computation without decomposing the mapped matrix and gains the more discriminated features. The experiment results on OTCBVS V/IR face database of Ohio state university show that our algorithm gets better performance than other facial recognition method based on CCA with recognition accuracytate more than 90%. In addition,it also can get the excellent results with the illumination and expression variance.%为了更有效地映射图像数据样本到可分类特征空间,提高分类正确率,提出了一种新的基于核函数的典型相关分析的融合人脸识别算法.该方法首先把图像矩阵通过核函数影射到核空间,然后从核空间的行和列两个方向进行特征抽取,同时避免分解映射后的数据矩阵,简化了数据运算,获得了更具鉴别力的分类特征.在Ohio州立大学的OTCBVS可见/红外人脸数据库中进行了分类识别实验,实验结果表明:该方法可以获得90%以上的识别正确率,优于其他的典型相关分析的人脸识别方法的分类正确率.此外,对不均匀光照变化,表情变化等人脸识别的常见问题具有很好的抵抗能力.
Costa, Valter Magalhaes
2011-07-01
The monitoring of variables and diagnosis of sensor fault in nuclear power plants or processes industries is very important because an early diagnosis allows the correction of the fault and, like this, do not cause the production interruption, improving operator's security and it's not provoking economics losses. The objective of this work is, in the whole of all variables monitor of a nuclear power plant, to build a set, not necessary minimum, which will be the set of input variables of an artificial neural network and, like way, to monitor the biggest number of variables. This methodology was applied to the IEA-R1 Research Reactor at IPEN. For this, the variables Power, Rate of flow of primary circuit, Rod of control/security and Difference in pressure in the core of the reactor ( {Delta} P) was grouped, because, for hypothesis, almost whole of monitoring variables have relation with the variables early described or its effect can be result of the interaction of two or more. The Power is related to the increasing and decreasing of temperatures as well as the amount radiation due fission of the uranium; the Rods are controls of power and influence in the amount of radiation and increasing and decreasing of temperatures and the Rate of flow of primary circuit has function of the transport of energy by removing of heat of the nucleus Like this, labeling B= {l_brace}Power, Rate of flow of Primary Circuit, Rod of Control/Security and {Delta} P{r_brace} was computed the correlation between B and all another variables monitoring (coefficient of multiple correlation), that is, by the computer of the multiple correlation, that is tool of Theory of Canonical Correlations, was possible to computer how much the set B can predict each variable. Due the impossibility of a satisfactory approximation by B in the prediction of some variables, it was included one or more variables that have high correlation with this variable to improve the quality of prediction. In this
Theory of extreme correlations using canonical Fermions and path integrals
The t–J model is studied using a novel and rigorous mapping of the Gutzwiller projected electrons, in terms of canonical electrons. The mapping has considerable similarity to the Dyson–Maleev transformation relating spin operators to canonical Bosons. This representation gives rise to a non Hermitian quantum theory, characterized by minimal redundancies. A path integral representation of the canonical theory is given. Using it, the salient results of the extremely correlated Fermi liquid (ECFL) theory, including the previously found Schwinger equations of motion, are easily rederived. Further, a transparent physical interpretation of the previously introduced auxiliary Greens function and the ‘caparison factor’, is obtained. The low energy electron spectral function in this theory, with a strong intrinsic asymmetry, is summarized in terms of a few expansion coefficients. These include an important emergent energy scale Δ0 that shrinks to zero on approaching the insulating state, thereby making it difficult to access the underlying very low energy Fermi liquid behavior. The scaled low frequency ECFL spectral function, related simply to the Fano line shape, has a peculiar energy dependence unlike that of a Lorentzian. The resulting energy dispersion obtained by maximization is a hybrid of a massive and a massless Dirac spectrum EQ∗∼γQ−√(Γ02+Q2), where the vanishing of Q, a momentum type variable, locates the kink minimum. Therefore the quasiparticle velocity interpolates between (γ∓1) over a width Γ0 on the two sides of Q=0, implying a kink there that strongly resembles a prominent low energy feature seen in angle resolved photoemission spectra (ARPES) of cuprate materials. We also propose novel ways of analyzing the ARPES data to isolate the predicted asymmetry between particle and hole excitations. -- Highlights: •Spectral function of the Extremely Correlated Fermi Liquid theory at low energy. •Electronic origin of low energy kinks in
Recovery of spectral data using weighted canonical correlation regression
Eslahi, Niloofar; Amirshahi, Seyed Hossein; Agahian, Farnaz
2009-05-01
The weighted canonical correlation regression technique is employed for reconstruction of reflectance spectra of surface colors from the related XYZ tristimulus values of samples. Flexible input data based on applying certain weights to reflectance and colorimetric values of Munsell color chips has been implemented for each particular sample which belongs to Munsell or GretagMacbeth Colorchecker DC color samples. In fact, the colorimetric and spectrophotometric data of Munsell chips are selected as fundamental bases and the color difference values between the target and samples in Munsell dataset are chosen as a criterion for determination of weighting factors. The performance of the suggested method is evaluated in spectral reflectance reconstruction. The results show considerable improvements in terms of root mean square error (RMS) and goodness-of-fit coefficient (GFC) between the actual and reconstructed reflectance curves as well as CIELAB color difference values under illuminants A and TL84 for CIE1964 standard observer.
杨静; 李文平; 张健沛
2012-01-01
现存的多维数据流典型相关分析(Canonical Correlation Analysis,简称CCA)算法主要是基于近似技术的求解方法,本质上并不是持续更新的精确算法.为了能在时变的环境中持续、快速而精确地跟踪数据流之间的相关性,本文提出一种多维数据流典型相关跟踪算法TCCA.该算法基于秩2更新理论,通过并行方式持续更新样本协方差矩阵的特征子空间,进而实现多维数据流典型相关的快速跟踪.理论分析及仿真实验结果表明,TCCA具有较好的稳定性、较高的计算效率和精度,可以作为基本工具应用于数据流相关性检测、特征融合、数据降维等数据流挖掘领域.%Existing algorithms for canonical correlation analysis(CCA) of multidimensional data streams are mostly based on approximate techniques,but are not the precise algorithms for updates in essence. In this study,a novel canonical correlation analysis algorithm, called TCCA( Tracking CCA) ,is proposed for tracking the correlations rapidly and accurately between two multidimensional data streams in the time-varying environments. By introducing the technique of rank two modifications to update the eigen-subspace of the sample covariance matrix in parallel,TCCA can rapidly track the correlations of data streams. Theoretical analysis and experimental results indicate that the TCCA algorithm has better stability, high computational efficiency and accuracy. It could be presented as a basic tool for correlation detection on data streams, feature fusion, dimension reduction and other areas of data streams mining.
Canonical Correlation between the Leaf Quality Indicators of "Moderate Aroma" Flue-cured Tobacco
Lin; MENG; Yuangang; DAI; Chengdong; WANG; Shusheng; WANG; Wenjing; SONG; Yuanhua; WU; Yimin; XU
2015-01-01
In order to find out the correlation between tobacco quality evaluation indicators in China’s traditional " moderate aroma" tobaccoproducing areas and simplify the tobacco quality evaluation indicators,we evaluate the appearance quality and smoking quality of 143 flue-cured tobacco leaf samples in China’s " moderate aroma" tobacco-producing areas,test the physical traits and chemical component,and analyze the canonical correlation between four quality evaluation indicators. The results show that there is significant or extremely significant canonical correlation between four evaluation indicators( tobacco smoking quality,chemical component,appearance quality and physical trait quality); the cumulative variance contribution rate of evaluation indicators is in the order of chemical component( 69. 17%) > appearance quality( 68. 76%) > physical traits( 64. 13%); appearance quality is most closely related to physical traits( 93. 84%). The individual indicators for tobacco quality evaluation make different contribution to the correlation between quality evaluation indicators. The chemical component evaluation indicators mainly include total sugar and ratio of total sugar to betaine; sensory taste indicators mainly include aroma volume,smoke concentration,irritation and softness degree; physical trait evaluation indicators mainly include leaf weight,leaf length and leaf density; appearance quality indicators mainly include leaf organizational structure,color,maturity and identity. Studies have shown that in the large-scale ecoregion,using canonical correlation analysis to simplify tobacco quality evaluation indicators is feasible.
Jian Li
2012-04-01
Full Text Available Dissolved gas analysis (DGA has been widely applied to diagnose internal faults in transformer insulation systems. However, the accuracy of DGA technique is limited because of the lack of positive correlation of the fault-identifying gases with faults found in power transformers. This paper presents a laboratory study on the correlation between oil dissolved gas formation and partial discharge (PD statistical parameters. Canonical correlation analysis (CCA is employed to explore the underlying correlation and to extract principal feature parameters and gases in the development of different PD defects. This study is aimed to provide more information in assisting the separation, classification and identification of PD defects, which might improve the existing transformer dissolved gas analysis (DGA schemes. An application of a novel ratio method for discharge diagnosis is proposed. The evaluation of DGA data both in laboratory and actual transformers proves the effectiveness of the method and the correlation investigation.
Wilson, Celia M.
2010-01-01
Research pertaining to the distortion of the squared canonical correlation coefficient has traditionally been limited to the effects of sampling error and associated correction formulas. The purpose of this study was to compare the degree of attenuation of the squared canonical correlation coefficient under varying conditions of score reliability.…
Enginyurt, Ozgur; Cankaya, Soner; Aksay, Kadir; Tunc, Taner; Koc, Bozkurt; Bas, Orhan; Ozer, Erdal
2016-04-01
Objective Burnout syndrome can significantly reduce the performance of health workers. Although many factors have been identified as antecedents of burnout, few studies have investigated the role of organisational commitment in its development. The purpose of the present study was to examine the relationships between subdimensions of burnout syndrome (emotional exhaustion, depersonalisation and personal accomplishment) and subdimensions of organisational commitment (affective commitment, continuance commitment and normative commitment). Methods The present study was a cross-sectional survey of physicians and other healthcare employees working in the Ministry of Health Ordu University Education and Research Hospital. The sample consisted of 486 healthcare workers. Data were collected using the Maslach Burnout Inventory and the Organisation Commitment Scale, and were analysed using the canonical correlation approach. Results The first of three canonical correlation coefficients between pairs of canonical variables (Ui , burnout syndrome and Vi, organisational commitment) was found to be statistically significant. Emotional exhaustion was found to contribute most towards the explanatory capacity of canonical variables estimated from the subdimensions of burnout syndrome, whereas affective commitment provided the largest contribution towards the explanatory capacity of canonical variables estimated from the subdimensions of organisational commitment. Conclusions The results of the present study indicate that affective commitment is the primary determinant of burnout syndrome in healthcare professionals. What is known about the topic? Organisational commitment and burnout syndrome are the most important criteria in predicting health workforce performance. An increasing number of studies in recent years have clearly indicated the field's continued relevance and importance. Conversely, canonical correlation analysis (CCA) is a technique for describing the relationship
Pb pollution from automobile exhausts around highways is a persistent problem in India. Pb intoxication in mammalian body is a complex phenomenon which is influence by agonistic and antagonistic interactions of several other heavy metals and micronutrients. An attempt has been made to study the association between Pb and Zn accumulation in different physiological systems of cattles (n = 200) by application of both canonical correlation and canonical correspondence analyses. Pb was estimated from plasma, liver, bone, muscle, kidney, blood and milk where as Zn was measured from all these systems except bone, blood and milk. Both statistical techniques demonstrated that there was a strong association among blood-Pb, liver-Zn, kidney-Zn and muscle-Zn. From observations, it can be assumed that Zn accumulation in cattles' muscle, liver and kidney directs Pb mobilization from those organs which in turn increases Pb pool in blood. It indicates antagonistic activity of Zn to the accumulation of Pb. Although there were some contradictions between the observations obtained from the two different statistical methods, the overall pattern of Pb accumulation in various organs as influenced by Zn were same. It is mainly due to the fact that canonical correlation is actually a special type of canonical correspondence analyses where linear relationship is followed between two groups of variables instead of Gaussian relationship.
Karmakar, Partha; Das, Pradip Kumar; Mondal, Seema Sarkar; Karmakar, Sougata; Mazumdar, Debasis
2010-10-01
Pb pollution from automobile exhausts around highways is a persistent problem in India. Pb intoxication in mammalian body is a complex phenomenon which is influence by agonistic and antagonistic interactions of several other heavy metals and micronutrients. An attempt has been made to study the association between Pb and Zn accumulation in different physiological systems of cattles (n = 200) by application of both canonical correlation and canonical correspondence analyses. Pb was estimated from plasma, liver, bone, muscle, kidney, blood and milk where as Zn was measured from all these systems except bone, blood and milk. Both statistical techniques demonstrated that there was a strong association among blood-Pb, liver-Zn, kidney-Zn and muscle-Zn. From observations, it can be assumed that Zn accumulation in cattles' muscle, liver and kidney directs Pb mobilization from those organs which in turn increases Pb pool in blood. It indicates antagonistic activity of Zn to the accumulation of Pb. Although there were some contradictions between the observations obtained from the two different statistical methods, the overall pattern of Pb accumulation in various organs as influenced by Zn were same. It is mainly due to the fact that canonical correlation is actually a special type of canonical correspondence analyses where linear relationship is followed between two groups of variables instead of Gaussian relationship.
Paulo Fernando Trugilho
2003-01-01
Full Text Available The analysis of canonical correlation measures the existence and the intensity of the association between two groups of variables. The research objectified to evaluate thecanonical correlation between chemical and physical characteristics and fiber dimensional ofwood of Eucalyptus grandis and Eucalyptus saligna clones, verifying the interdependenceamong the groups of studied variables. The analysis indicated that the canonical correlationswere high and that in two cases the first and second pair were significant at the level of 1% ofprobability. The analysis of canonical correlation showed that the groups are notindependent. The intergroup associations indicated that the wood of high insoluble lignin contentand low ash content is associated with the high radial and tangential contraction and highbasic density wood.
A Canonical Analysis of the Massless Superparticle
McKeon, D G C
2012-01-01
The canonical structure of the action for a massless superparticle is considered in d = 2 + 1 and d = 3 + 1 dimensions. This is done by examining the contribution to the action of each of the components of the spinor {\\theta} present; no attempt is made to maintain manifest covariance. Upon using the Dirac Bracket to eliminate the second class constraints arising from the canonical momenta associated with half of these components, we find that the remaining components have canonical momenta that are all first class constraints. From these first class constraints, it is possible to derive the generator of half of the local Fermionic {\\kappa}-symmetry of Siegel; which half is contingent upon the choice of which half of the momenta associated with the components of {\\theta} are taken to be second class constraints. The algebra of the generator of this Fermionic symmetry transformation is examined.
李一辰; 潘迎
2011-01-01
[Objective] To study the relationship between body shape and physical quality indicators of preschool children. [Methods] 6 405 preschool children were tested on body shape including height, sit high, weight, chest circumference, skinfold thickness, and physical quality indicators which include stan ding long jump, throw for distance, seat proneness, the time of shuttle run, walk balance beam and feet consecutive jump. Data were analyzed by canonical correlation analysis. [ Results] First pair canonical variables was selected by canonical correlation analysis and its coefficient was 0. 760. The canonical variables representing the body shape indicators were height, chest circumference, abdominal skinfold thickness and weight. Among these indicators, height played the most important role. The canonical variables representing the physical quality indicators were standing long jump, throw for distance and the time of shuttle run, standing long jump played the most important role. Height and chest circumference were positive to physical quality, while abdominal skinfold thickness and weight were negative to physical quality. [Conclusions] Correlationship is found between the body shape and the physical quality in preschool children. Height and standing long jump play the most important roles.%[目的]探讨学龄前儿童身体形态指标与身体素质之间的关系.[方法]对6405名学龄前儿童进行身体形态指标(身高、坐高、体重、胸围及皮褶厚度)测量与身体素质(立定跳远、网球掷远、坐位体前屈、10m往返跑、走平衡木及双脚连续跳)的测试,采用典型相关分析法进行统计分析.[结果]选取第一对典型变量进行分析,典型相关系数为0.760(P<0.001).代表身体形态指标的典型变量为身高、胸围、腹部皮摺厚度及体重,其中身高的作用最大.代表身体素质指标的典型变量为立定跳远、网球掷远及10m往返跑时间,其中立定跳远的作用最大.身高
周晓彦; 郑文明; 辛明海
2013-01-01
In facial expression recognition, the existences of image noises and the irrelevant image information to the expression changes usually influence the recognition accuracy. The traditional facial expression recognition method using kernel canonical correlation analysis (KCCA) is difficulty to solve this problem. To overcome this drawback, a kernel canonical correlation analysis with sparse representation (SKCCA) is proposed and applied to the facial expression recognition. The basic idea of the SKCCA method is to utilize the sparse representation approach to choose the spectral components of the facial feature matrix before modeling the correlation between facial feature matrix and the expression semantic feature matrix. Then, the expression recognition is carried out based on the correlation model. To demonstrate the superiority of the proposed method over the traditional KCCA method, extensive experiments are conducted on the JAFFE database and the experimental results confirm the effectiveness of the proposed method.% 在面部表情识别中，由于图像特征中存在与情感语义无关的信息及噪声干扰等因素，在一定程度上影响表情识别的准确性。传统的基于核典型相关分析的识别方法难以有效克服这些因素的影响。为尽可能排除这些影响表情识别的因素，提出一种基于稀疏表示的核典型相关分析方法，并将其应用于表情识别中。该方法的基本思想是应用稀疏学习方法来自动选择表情特征矩阵中的关键特征谱成分进行表情特征与情感语义特征之间的相关性建模，然后通过建立的模型完成对待测表情图像的语义特征估计，并用于表情的分类识别。为验证所提方法较传统的基于核典型相关分析方法的优越性，选取国际标准表情数据库JAFFE进行实验，实验结果证实了所提方法的有效性。
Mustafa İlhan
2013-01-01
Full Text Available The aim of this research was to investigate the relationships between positive and negative perfectionism and study skills. Relational screening model was used in this study with this aim. Workgroup of the investigation consists of 207 students receiving study in three high schools in Battalgazi District of Malatya City, in the spring semester of 2011-2012 school year. 105 (50.72% of the students in the workgroup are female and 102 (50.28% of whom are male. In the research, “The Positive and Negative Perfectionism Scale” developed by Kırdök (2004 has been used to determine the perfectionism characteristics of the students and “The Study Skills Scale” developed by Mr. Bay, Tuğluk and Gençdoğan (2004 has been used to test the study skills of the students. In the research, the relationship between the perfectionism data set composing of positive perfectionism and negative perfectionism variables; and study skills data set composing of motivation, time management, and exam preparation-test anxiety management variables has been investigated by canonical correlation analysis. The results of canonical correlation analysis demonstrated that there were significant relationships between positive and negative perfectionism and study skills. Common variance that the positive and negative perfectionism and study skills data sets share has been calculated as 35.59%.
Discovery of a tight correlation for gamma ray burst afterglows with `canonical' light curves
Dainotti, M G; Capozziello, S; Cardone, V F; Ostrowski, M
2010-01-01
Gamma Ray Bursts (GRB) observed up to redshifts $z>8$ are fascinating objects to study due to their still unexplained relativistic outburst mechanisms and a possible use to test cosmological models. Our analysis of 77 GRB afterglows with known redshifts revealed a physical subsample of long GRBs with canonical {\\it plateau breaking to power-law} light curves with a significant {\\it luminosity $L^*_X$ - break time $T^*_a$} correlation in the GRB rest frame. This subsample forms approximately the {\\it upper envelope} of the studied distribution. We have also found a similar relation for a small sample of GRB afterglows that belong to the intermediate class (IC) between the short and the long ones. It proves that within the full sample of afterglows there exist physical subclasses revealed here by tight correlations of their afterglow properties. The afterglows with regular (`canonical') light curves obey not only a mentioned tight physical scaling, but -- for a given $T^*_a$ -- the more regular progenitor explo...
Waste Rock Discrimination Based on Kernel Canonical Correlation Analysis%一种基于核典型相关分析的煤炭矸石鉴别方法
翟永前; 王浩; 赵力
2013-01-01
提出了一种利用核典型相关分析(KCCA)来抽取煤炭矸石的非线性鉴别特征,并用其进行煤炭矸石自动识别的方法.实验表明,对小样本煤炭矸石图像,提出的方法可以得到较好的识别性能,再结合机械自动化技术即可以达到煤矸自动分选的目的.%This paper presents a method based on the KCCA(Kernal Canonical Correlation Analysis) to extract the nonlinear characteristics of the waste rock,and apply it to recognise the waste rock automatically. The experiments show that this method can get good recognition performance with small sample waste rock images. When combined with mechanical automation technology, this method can achieve the purpose of the waste rock sorting.
气象因素对农田鼠类数量影响的典型相关分析%Canonical correlation analysis of climate factors and farmland rodent density
刘自远
2011-01-01
Objective To study the impact of farmland climate factors on the rodent community. Methods From 1978 to 1993, canonical correlation analysis of the farmland rodent density and climate factors in Kaijiang county, Sichuan province was conducted. Results In the period, the overall farmland rodent density was 5.58%-26.57% ; Apodemus agrarius density 1.91%-18.41%, Rattus norvegicus density 0.68%-10.86%, and Anourosorex squamipes density 0.47%-9.50%. Among the canonical correlation coefficients between 12 climate factors including temperature, humidity, rainfall and sunshine, and four variables (overall rodent density, Ap. Agrarius density, R. Norvegicu density, An. Squamipes density), the first couple (correlation coefficient r-1.0000) was statistically significant (χ2=248.7032, P<0.01). The largest coefficient of the rodent density was noted in the overall rodent density (4.7748), and the largest coefficient of the climate factors was the average sunshine from July to August (-3.1532), followed by average humidity from July to August (-1.6177) and then average rainfall from July to August (-1.4652). All were negatively correlated. Conclusion Farmland rodent quantity was mainly affected by average sunshine, humidity and rainfall from July to August.%目的 探讨气象因素对农田鼠类数量的影响.方法 采用典型相关分析对开江县1978-1993年农田鼠密度与气象因素进行统计分析.结果 1978-1993年开江县农田总鼠密度为5.58％～26.57％,黑线姬鼠、褐家鼠、四川短尾鼩密度分别为1.91％～18.41％、0.68％～10.86％、0.47％～9.50％.气温、湿度、降雨量、日照数等12种气象因素与总鼠密度,黑线姬鼠、褐家鼠、四川短尾鼩密度4个因变量的典型相关系数中,第1对(r=1.0000)有统计学意义(x2=248.7032,P＜0.01),鼠类数量以总鼠密度标准系数最大(4.7748),气象因素标准系数最大的依次为7-8月平均日照数(-3.1532)、7-8月平均湿度(-1.6177)和7-8
Integrative correlation: Properties and relation to canonical correlations✩
Cope, Leslie; Naiman, Daniel Q.; Parmigiani, Giovanni
2013-01-01
The integrative correlation coefficient was developed to facilitate the validation of expression microarray results in public datasets, by identifying genes that are reproducibly measured across studies and even across microarray platforms. In the current study, we develop a number of interesting and important mathematical and statistical properties of the integrative correlation coefficient, including a unique permutation-based null distribution with the unusual property that the variance do...
Rapid ecotoxicological assessment of heavy metal combined polluted soil using canonical analysis
CHEN Su-hua; ZHOU Qi-xing; SUN Tie-heng; LI Pei-jun
2003-01-01
Quick, simple to perform, and cheap biomarkers were combined in a rapid assessment approach to measure the effects of metal pollutants, Cu, Cd, Pb and Zn in meadow burozem on wheat. Analysis of orthogonal design showed that the significant zinc factor indicated both the inhibition rate of shoot mass and that of root elongation were affected by zinc( P ＜ 0.05 and P ＜ 0.01, respectively). The first toxicity canonical variable (TOXI), formed from the toxicity data set, explained 49% of the total variance in the toxicity data set; the first biological canonical variable(BIOL) explained 42% of the total variation in the biological data set. The correlation between the first canonical variables TOXI and BIOL (canonical correlation) was 0.94 ( P ＜ 0.0001). Therefore, it is reliable and feasible to use the achievement to assess toxicity of heavy metal combined polluted soil using canonical analysis. Toxicity of soil combined polluted by heavy metals to plant community was estimated by comparing the IC50 values describing the concentration needed to cause 50% decrease with grow rate compared to no metal addition. Environmental quality standard for soils prescribe that all these tested concentration of heavy metals in soil should not cause hazard and pollution ultimately, whereas it indicated that the soils in second grade cause more or less than 50% inhibition rates of wheat growth. So environmental quality standard for soils can be modified to include other features.
An Alternative Method to Predict Performance: Canonical Redundancy Analysis.
Dawson-Saunders, Beth; Doolen, Deane R.
1981-01-01
The relationships between predictors of performance and subsequent measures of clinical performance in medical school were examined for two classes at Southern Illinois University of Medicine. Canonical redundancy analysis was used to evaluate the association between six academic and three biographical preselection characteristics and four…
Testing the significance of canonical axes in redundancy analysis
Legendre, P.; Oksanen, J.; Braak, ter C.J.F.
2011-01-01
1. Tests of significance of the individual canonical axes in redundancy analysis allow researchers to determine which of the axes represent variation that can be distinguished from random. Variation along the significant axes can be mapped, used to draw biplots or interpreted through subsequent anal
IDENTIFICATION OF IDEOTYPES BY CANONICAL ANALYSIS IN Panicum maximum
Janaina Azevedo Martuscello
2015-04-01
Full Text Available Grouping of genotypes by canonical variable analysis is an important tool in breeding. It allows the grouping of individuals with similar characteristics that are associated with superior agronomic performance and may indicate the ideal profile of a plant for the region. The objective of the present study was to define, by canonical analysis, the agronomic profile of Panicum maximum plants adapted to the Agreste region. The experiment was conducted in a completely randomized design with 28 treatments, 22 genotypes of Panicum maximum, and cultivars Mombasa, Tanzania, Massai, Milenio, BRS Zuri, and BRS Tamani in triplicate in 4-m² plots. Plots were harvested five times and the following traits were evaluated: plant height; total, leaf, and stem; dead dry matter yields; leaf:stem ratio; leaf percentage; and volumetric density of forage. The analysis of canonical variables was performed based on the phenotypic means of the evaluated traits and on the residual variance and covariance matrix. Genotype PM34 showed higher mean leaf dry matter yield under the conditions of the Agreste of Alagoas (on average 53% higher than cultivars Mombasa, Tanzania, Milenio and Massai. It was possible to summarize the variation observed in eight agronomic characteristics in only two canonical variables accounting for 81.44 % of the data variation. The ideotype plant adapted to the conditions of the Agreste should be tall and present high leaf yield, leaf percentage, and leaf:stem ratio, and intermediate values of volumetric density of forage.
Alkharusi, Hussain
2013-01-01
The present study aims at deriving correlational models of students' perceptions of assessment tasks, motivational orientations, and learning strategies using canonical analyses. Data were collected from 198 Omani tenth grade students. Results showed that high degrees of authenticity and transparency in assessment were associated with positive…
Change detection in bi-temporal data by canonical information analysis
Nielsen, Allan Aasbjerg; Vestergaard, Jacob Schack
2015-01-01
Canonical correlation analysis (CCA) is an established multivariate statistical method for finding similarities between linear combinations of (normally two) sets of multivariate observations. In this contribution we replace (linear) correlation as the measure of association between the linear...... combinations with the information theoretical measure mutual information (MI). We term this type of analysis canonical information analysis (CIA). MI allows for the actual joint distribution of the variables involved and not just second order statistics. Where CCA is ideal for Gaussian data, CIA facilitates...... analysis of variables with different genesis and therefore different statistical distributions. As a proof of concept we give a toy example. We also give an example with DLR 3K camera data from two time points covering a motor way....
王云龙; 周立
2011-01-01
The statistic datum of Chinese tourism industry in 1997-2008 were used as input index value and the tourism number and tourism income as output index value. After each variable＇s Pearson correlation analysis, a canonical correlations model of Chinese tourism input and output was built, and a quantitative analysis of the correlations between them was made. Chinese tourism development decisive factors were decided. Also some suggestions to make further analysis of Chinese tourism input and output structure were given and some conclusions were drawn from the facts. Research found the input-output indicators playing a decisive role in the development of Chinese tourism industry that input indicator is passenger turnover growth and output indicator is tourism people number. Research results show firstly that the development of improving transportation in tourism has a more vital significance to improve the total tourist income. Transportation is the pillar industry department of tourism. Secondly, passenger turnover growth and more tourism people account for regional vitality, attraction and openness enhance. The development for tourism need to increase the local activity level in social, economy, and culture.%以1997—2008年中国旅游业支柱产业数据为投入指标值，以旅游人次数和旅游收入为产出指标值，在对各变量进行两两相关（皮尔逊相关）分析的基础上，构建中国旅游业支柱产业投入与产出的典型相关模型，定量判别投入——产出各分变量的关联作用程度及影响，确定了中国旅游业发展投入——产出的决定性因素，并提出相关结论。研究发现，对中国旅游业发展投入产出方面起到决定性作用的指标，投入方面为旅客周转量增长，产出方面是旅游人次数。研究结果首先表明发展（旅游）交通业对提高旅游总收入有着更重要的意义。旅游交通业是当之无愧的旅游支柱产业部门。其次
Clinical Trials With Large Numbers of Variables: Important Advantages of Canonical Analysis.
Cleophas, Ton J
2016-01-01
Canonical analysis assesses the combined effects of a set of predictor variables on a set of outcome variables, but it is little used in clinical trials despite the omnipresence of multiple variables. The aim of this study was to assess the performance of canonical analysis as compared with traditional multivariate methods using multivariate analysis of covariance (MANCOVA). As an example, a simulated data file with 12 gene expression levels and 4 drug efficacy scores was used. The correlation coefficient between the 12 predictor and 4 outcome variables was 0.87 (P = 0.0001) meaning that 76% of the variability in the outcome variables was explained by the 12 covariates. Repeated testing after the removal of 5 unimportant predictor and 1 outcome variable produced virtually the same overall result. The MANCOVA identified identical unimportant variables, but it was unable to provide overall statistics. (1) Canonical analysis is remarkable, because it can handle many more variables than traditional multivariate methods such as MANCOVA can. (2) At the same time, it accounts for the relative importance of the separate variables, their interactions and differences in units. (3) Canonical analysis provides overall statistics of the effects of sets of variables, whereas traditional multivariate methods only provide the statistics of the separate variables. (4) Unlike other methods for combining the effects of multiple variables such as factor analysis/partial least squares, canonical analysis is scientifically entirely rigorous. (5) Limitations include that it is less flexible than factor analysis/partial least squares, because only 2 sets of variables are used and because multiple solutions instead of one is offered. We do hope that this article will stimulate clinical investigators to start using this remarkable method. PMID:23591025
Removal of the ballistocardiographic artifact from EEG-fMRI data: a canonical correlation approach
The simultaneous recording of electroencephalogram (EEG) and functional magnetic resonance imaging (fMRI) can give new insights into how the brain functions. However, the strong electromagnetic field of the MR scanner generates artifacts that obscure the EEG and diminish its readability. Among them, the ballistocardiographic artifact (BCGa) that appears on the EEG is believed to be related to blood flow in scalp arteries leading to electrode movements. Average artifact subtraction (AAS) techniques, used to remove the BCGa, assume a deterministic nature of the artifact. This assumption may be too strong, considering the blood flow related nature of the phenomenon. In this work we propose a new method, based on canonical correlation analysis (CCA) and blind source separation (BSS) techniques, to reduce the BCGa from simultaneously recorded EEG-fMRI. We optimized the method to reduce the user's interaction to a minimum. When tested on six subjects, recorded in 1.5 T or 3 T, the average artifact extracted with BSS-CCA and AAS did not show significant differences, proving the absence of systematic errors. On the other hand, when compared on the basis of intra-subject variability, we found significant differences and better performance of the proposed method with respect to AAS. We demonstrated that our method deals with the intrinsic subject variability specific to the artifact that may cause averaging techniques to fail.
Chang; Zhaofeng; Wang; Qiangqiang; Zhang; Jianhui; Tang; Jinnian; Zhu; Shujuan; Fan; Baoli; Zhang; Dabiao; Liu; Shizeng; Zhang; Guozhong; Li; Aide
2014-01-01
Accumulated sand-belts refer to those formed along the oasis fringe,especially at the upwind location,due to the accumulation of sand blocked by farmland windbreak. In the 60 years since the foundation of new China,a lot of trees have been planted for desertification combating in northwest and north China,thus,accumulated sand-belts were formed at the upwind location. The formation and the ecological effects of the accumulated sand-belts along the oasis fringe is a new scientific concern. To study the formation causes of these belts in Hexi corridor,21 samples were selected,and the height / width of the belts,as well as the vegetation,soil,soil moisture and climatic factors were investigated. This paper analyzed the correlation between the height / width of the belts and the vegetation,soil,soil moisture and climatic factors using the methods of variance analysis,correlation analysis and canonical correlation analysis. The results indicate that: the accumulated sand-belts take a trend of being high and wide in the east whereas low and narrow in the west,and most of the parts tend to be stable; the species on the belts are dominated by Tamarix austromongolica,the vegetation cover and the pure vegetation cover of different dominant species on the leeward slope of the accumulated sand-belts vary significantly. The canonical correlation analysis shows that: the height and width of accumulated sand-belt is the interaction of precipitation,distance to the sand source,leeward vegetation cover and annual average wind speed. Moreover,the height of accumulated sand-belts are negatively correlated to the soil moisture at the depth of 30- 50 cm,air humidity and leeward vegetation cover,and the width of the belts is also negatively correlated with the distance to the sand source. The ecological effects of the accumulated sand-belts are both positive( stopping sands from moving into farmland,protective role as an obstacle)and negative( when the belts decay and activate one day
Multi-set multi-temporal canonical analysis of psoriasis images
Gomez, David Delgado; Maletti, Gabriela Mariel; Nielsen, Allan Aasbjerg; Ersbøll, Bjarne Kjær
Nowadays, the medical tracking of dermatological diseases is imprecise, mainly due to the lack of suitable objective methods to evaluate the lesion. The severity of the disease is currently scored by doctors merely by means of visual examination. In this work, multi-set canonical correlation...... analysis over registered images is proposed to track the evolution of the disease automatically. This method transforms the original images into sets of variables that exhibit decreasing degree of similarity, based on correlation measures. Due to this property, these new variables are more suitable to...... detect where changes occur. An experiment with 5 different time series collected from psoriasis patients during 4 different sessions is conducted. The analysis of the obtained results points out some patterns that can be used both to interpret and summarize the evolution of the lesion and to achieve a...
孙颖
2011-01-01
基于安徽省水泥行业B2B市场顾客的抽样调查数据,运用典型相关分析法实证研究水泥行业顾客生命周期的影响因素.利用SPSS13.0统计分析软件分析实证数据,通过因子分析、典型相关分析等方法研究顾客满意、顾客价值、顾客信任及其子因素与顾客生命周期之间的关系.结果表明,顾客满意、顾客价值和顾客信任是影响顾客生命周期的三大重要因素.%This paper chooses the customers of cement industry in B2B market to be the sampling data of investigation.It analyzes the three factors of customer lifetime cycle based on canonical correlation analysis.By the SPSS 13.0,this paper analyzes the relationships between the customer satisfaction,customer value and customer trust and customer lifetime cycle using the factor analysis and canonical correlation analysis.The results indicate that customer satisfaction,customer value and customer trust are the three major factors of customer lifetime cycle and they all have sub-factors.The cement businesses could make use of the factors to calculate and forecast the customer keeping rate,and take different measures to maintain good customer relationship.
Nandi, Debottam
2016-01-01
In this work, we present a consistent Hamiltonian analysis of cosmological perturbations for generalized non-canonical scalar fields. In order to do so, we introduce a new phase-space variable that is uniquely defined for different non-canonical scalar fields. We also show that this is the simplest and efficient way of expressing the Hamiltonian. We extend the Hamiltonian approach of [arXiv:1512.02539] to non-canonical scalar field and obtain a new definition of speed of sound in phase-space. In order to invert generalized phase-space Hamilton's equations to Euler-Lagrange equations of motion, we prescribe a general inversion formulae and show that our approach for non-canonical scalar field is consistent. We also obtain the third and fourth order interaction Hamiltonian for generalized non-canonical scalar fields and briefly discuss the extension of our method to generalized Galilean scalar fields.
Anna Maria Stellacci
2012-07-01
Full Text Available Hyperspectral (HS data represents an extremely powerful means for rapidly detecting crop stress and then aiding in the rational management of natural resources in agriculture. However, large volume of data poses a challenge for data processing and extracting crucial information. Multivariate statistical techniques can play a key role in the analysis of HS data, as they may allow to both eliminate redundant information and identify synthetic indices which maximize differences among levels of stress. In this paper we propose an integrated approach, based on the combined use of Principal Component Analysis (PCA and Canonical Discriminant Analysis (CDA, to investigate HS plant response and discriminate plant status. The approach was preliminary evaluated on a data set collected on durum wheat plants grown under different nitrogen (N stress levels. Hyperspectral measurements were performed at anthesis through a high resolution field spectroradiometer, ASD FieldSpec HandHeld, covering the 325-1075 nm region. Reflectance data were first restricted to the interval 510-1000 nm and then divided into five bands of the electromagnetic spectrum [green: 510-580 nm; yellow: 581-630 nm; red: 631-690 nm; red-edge: 705-770 nm; near-infrared (NIR: 771-1000 nm]. PCA was applied to each spectral interval. CDA was performed on the extracted components to identify the factors maximizing the differences among plants fertilised with increasing N rates. Within the intervals of green, yellow and red only the first principal component (PC had an eigenvalue greater than 1 and explained more than 95% of total variance; within the ranges of red-edge and NIR, the first two PCs had an eigenvalue higher than 1. Two canonical variables explained cumulatively more than 81% of total variance and the first was able to discriminate wheat plants differently fertilised, as confirmed also by the significant correlation with aboveground biomass and grain yield parameters. The combined
Jacobs, Glenn
2009-01-01
This analysis assesses the factors underlying Charles Horton Cooley's place in the sociological canon as they relate to George Herbert Mead's puzzling diatribe-echoed in secondary accounts-against Cooley's social psychology and view of the self published scarcely a year after his death. The illocutionary act of publishing his critique stands as an effort to project the image of Mead's intellectual self and enhance his standing among sociologists within and outside the orbit of the University of Chicago. It expressed Mead's ambivalence toward his precursor Cooley, whose influence he never fully acknowledged. In addition, it typifies the contending fractal distinctions of the scientifically discursive versus literary styles of Mead and Cooley, who both founded the interpretive sociological tradition. The contrasting styles and attitudes toward writing of the two figures are discussed, and their implications for the problems of scale that have stymied the symbolic interactionist tradition are explored. PMID:19360893
Discrete canonical analysis of three-dimensional gravity with cosmological constant
Berra-Montiel, J.; E. Rosales-Quintero, J.
2015-05-01
We discuss the interplay between standard canonical analysis and canonical discretization in three-dimensional gravity with cosmological constant. By using the Hamiltonian analysis, we find that the continuum local symmetries of the theory are given by the on-shell space-time diffeomorphisms, which at the action level, correspond to the Kalb-Ramond transformations. At the time of discretization, although this symmetry is explicitly broken, we prove that the theory still preserves certain gauge freedom generated by a constant curvature relation in terms of holonomies and the Gauss's law in the lattice approach.
Holland, Denise D.; Piper, Randy T.
2016-01-01
Intellectual goods can follow the same pattern as physical goods with the product life cycle of birth, growth, maturity, and decline. For the intellectual good of technological, pedagogical, and content knowledge (TPACK), its birth began with Shulman (1986, 1987). Canonical correlation analysis (CCA) was used to test the relationships among five…
于明洁; 郭鹏
2012-01-01
Taking the relation between innovation input and output of the regional innovation system as the research object, the paper conducts empirical research based on the canonical correlation analysis method. The result shows that, there are strong correlation among the innovation input and output, the number of whole time research and development personnel has significant effects on the invention patent, the national innovation fund has significant effects on the new products sales income of the enterprises, the fixed asset per capita has inhibitory effects on both the number of the High-Tech Enterprise and the new products sales income of the enterprises, the number of research and development personnel in the industrial ventures above the scale has significant effects on both the High-Tech Enterprise and the new products sales income of the enterprises. Finally, some policy suggestions are offered in accordance with the research result.%国家软科学研究计划项目“陕西航空产业集群发展战略研究”（2010GXS5D264）；西安市软科学研究计划项目“面向国际化大都市的西安市产学研创新系统协调发展研究”（HJll08—3）；西北工业大学研究生创业种子基金项目“区域创新系统协调性与区域创新能力关系研究”（Z2011126）
Group sparse canonical correlation analysis for genomic data integration
Lin, Dongdong; Zhang, Jigang; Li, Jingyao; Calhoun, Vince D.; Deng, Hong-Wen; Wang, Yu-Ping
2013-01-01
Background The emergence of high-throughput genomic datasets from different sources and platforms (e.g., gene expression, single nucleotide polymorphisms (SNP), and copy number variation (CNV)) has greatly enhanced our understandings of the interplay of these genomic factors as well as their influences on the complex diseases. It is challenging to explore the relationship between these different types of genomic data sets. In this paper, we focus on a multivariate statistical method, canonica...
Luo, Chongliang; Liu, Jin; Dey, Dipak K; Chen, Kun
2016-07-01
In many fields, multi-view datasets, measuring multiple distinct but interrelated sets of characteristics on the same set of subjects, together with data on certain outcomes or phenotypes, are routinely collected. The objective in such a problem is often two-fold: both to explore the association structures of multiple sets of measurements and to develop a parsimonious model for predicting the future outcomes. We study a unified canonical variate regression framework to tackle the two problems simultaneously. The proposed criterion integrates multiple canonical correlation analysis with predictive modeling, balancing between the association strength of the canonical variates and their joint predictive power on the outcomes. Moreover, the proposed criterion seeks multiple sets of canonical variates simultaneously to enable the examination of their joint effects on the outcomes, and is able to handle multivariate and non-Gaussian outcomes. An efficient algorithm based on variable splitting and Lagrangian multipliers is proposed. Simulation studies show the superior performance of the proposed approach. We demonstrate the effectiveness of the proposed approach in an [Formula: see text] intercross mice study and an alcohol dependence study. PMID:26861909
Canonical variate analysis in safflower (Carthamus tinctorius L.
D.Shivani*, Ch. Sreelakshmi and C.V. Sameer Kumar
2011-12-01
Full Text Available Seventy five genotypes of safflower representing the broad spectrum of variation were assessed for genetic divergence for eightcharacters using Mahalanobis D2 statistic and principal component analysis. The seed yield contributed maximum towards thetotal genetic divergence followed by test weight and number of seeds per capitulam. On the basis of clustering method, twelveclusters were obtained for D2 statistic. The best clusters with regard to seed yield and oil content were cluster XII and cluster II,respectively. Principal component analysis identified three principal components which explained 83.02% variability. GenotypesGMU 3470, GMU 3484, GMU 3499, A-1, JSF-1 and GMU 3475 (based on PCI axis were divergent.
Comparative analysis of cyanobacterial superoxide dismutases to discriminate canonical forms
Prabaharan Dharmar
2007-11-01
Full Text Available Abstract Background Superoxide dismutases (SOD are ubiquitous metalloenzymes that catalyze the disproportion of superoxide to peroxide and molecular oxygen through alternate oxidation and reduction of their metal ions. In general, SODs are classified into four forms by their catalytic metals namely; FeSOD, MnSOD, Cu/ZnSOD and NiSOD. In addition, a cambialistic form that uses Fe/Mn in its active site also exists. Cyanobacteria, the oxygen evolving photosynthetic prokaryotes, produce reactive oxygen species that can damage cellular components leading to cell death. Thus, the co-evolution of an antioxidant system was necessary for the survival of photosynthetic organisms with SOD as the initial enzyme evolved to alleviate the toxic effect. Cyanobacteria represent the first oxygenic photoautotrophs and their SOD sequences available in the databases lack clear annotation. Hence, the present study focuses on structure and sequence pattern of subsets of cyanobacterial superoxide dismutases. Result The sequence conservation and structural analysis of Fe (Thermosynechococcus elongatus BP1 and MnSOD (Anabaena sp. PCC7120 reveal the sharing of N and C terminal domains. At the C terminal domain, the metal binding motif in cyanoprokaryotes is DVWEHAYY while it is D-X-[WF]-E-H-[STA]-[FY]-[FY] in other pro- and eukaryotes. The cyanobacterial FeSOD differs from MnSOD at least in three ways viz. (i FeSOD has a metal specific signature F184X3A188Q189.......T280......F/Y303 while, in Mn it is R184X3G188G189......G280......W303, (ii aspartate ligand forms a hydrogen bond from the active site with the outer sphere residue of W243 in Fe where as it is Q262 in MnSOD; and (iii two unique lysine residues at positions 201 and 255 with a photosynthetic role, found only in FeSOD. Further, most of the cyanobacterial Mn metalloforms have a specific transmembrane hydrophobic pocket that distinguishes FeSOD from Mn isoform. Cyanobacterial Cu/ZnSOD has a copper domain and two
The equations of motion for multi-time correlation Green's functions are transformed into those for equal-time correlation Green's functions, which include the equations of motion for electron's and photon's density matrices as well as vertex functions. In two-body correlation truncation approximation, we present the explicit expressions for the equations of motion, Gauss law and Ward identities explicitly
Bayram Çetin
2009-01-01
Full Text Available The aim of this research was to examine the relationship between achievement goal orientations and the use of stress-coping strategies among college students. The sample consisted of 532 university students who were enrolled in different programs at Sakarya University, in Turkey. Of the participants, 279 were female and 253 were male. To assess strategies typically used in coping with stressful situations, the Coping Scale (Ozbay & Olivarez, 1999 and to measure achievement goal orientations of the sample the Achievement Goal Orientations Scale (Midgley et al.,1998 were administrated. Canonical correlation and MANOVA were conducted to statistically analyze the data. Consistent with hypotheses, results demonstrated that there were high relationships between students’ achievement goal orientations and their use of coping strategies.
Todeschini, R; Ballabio, D; Consonni, V; Manganaro, A; Mauri, A
2009-08-19
So far, similarity/diversity of objects has been widely studied in different research fields and a number of distance measures to estimate diversity between objects have been proposed. However, not much interest has been addressed to analysis of how diverse are configurations of objects in two different multivariate spaces. Since computerisation and automation nowadays lead to a large availability of information, it is apparent that a system could be described in different ways and, consequently, methods for comparison of the different viewpoints are required. These methods, for instance, may be usefully applied to Quantitative Structure-Activity Relationship (QSAR) studies. In this field, several thousands of molecular descriptors have been proposed in the literature and different selections of descriptors define different chemical spaces that need to be compared. Moreover, variable selection techniques such as Genetic Algorithms, Simulated Annealing, and Tabu Search are widely used to process available information in order to select optimal QSAR models. When more than one optimal model results, the problem arising is how to compare these models to find out whether they are really diverse or based on descriptors explaining almost the same information. In this paper, novel indices are proposed to measure similarity/diversity between pairs of data sets by the aid of the variable cross-correlation matrix. PMID:19616688
The authority of the ecumenical patriarch in the Orthodox Church: A historico-canonical analysis
Vranić Vasilije
2010-01-01
Full Text Available During the 20th century, the exact role and the scope of jurisdictional authority of the Ecumenical Patriarch was an object of attention of both theologians and historians. The problem of defining the Patriarch was reactualized through the intensification of conciliar negotiations of Orthodox Churches. The purpose of this article is to demonstrate that the pretensions of the Ecumenical Patriarch for universal jurisdiction over the entire Orthodox Diaspora, and the pretensions for the right of final arbitration in the ecclesial matters of the entire Orthodox communion, do not have a support in the Orthodox Ecclesiology. This will be argued in a historical analysis of the relevant prescriptions of the Eastern Orthodox Canon Law, which will be placed into the context of the history of the Christian Church, primarily of the Patristic period, since there disciplines play a vital role in the Orthodox understanding of Ecclesiological Tradition.
The increasing use of secondary fiber in papermaking has led to the production of paper containing a wide range of contaminants. Wastepaper mills need to develop quality control methods for evaluating the incoming wastepaper stock as well as testing the specifications of the final product. The goal of this work is to present a fast and successful methodology for identifying different paper types. In this way, undesirable paper types can be refused, thus improving the runnability of the paper machine and the quality of the paper manufactured. In this work we examine various types of paper using information obtained by an appropriate chemometric treatment of infrared spectral data. For this purpose, we studied a large number of paper sheets of three different types (namely coated, offset and cast-coated) supplied by several paper manufacturers. We recorded Fourier transform infrared (FTIR) spectra with the aid of an attenuated total reflectance (ATR) module and near-infrared (NIR) reflectance spectra by means of fiber optics. Both techniques proved expeditious and required no sample pretreatment. The primary objective of this work was to develop a methodology for the accurate identification of samples of different paper types. For this purpose, we used the chemometric discrimination technique extended canonical variate analysis (ECVA) in combination with the k nearest neighbor (kNN) method to classify samples in the prediction set. Use of the NIR and FTIR techniques under these conditions allowed paper types to be identified with 100% success in prediction samples
José Wilson da Silva
2007-07-01
Full Text Available A análise de correlações canônicas mede a existência e a intensidade da associação entre dois grupos de variáveis ou caracteres de importância. Este trabalho teve como objetivo estimar a intensidade de associação entre os grupos de caracteres agronômicos e industriais em cana-de-açúcar. Pela análise de correlações canônicas, ficouevidenciado que clones com maior número de touceiras por parcela e maior número de colmos por touceira tendem a proporcionar um aumento na produção de cana (TCH, e para incrementar o rendimento de TCH, brix e a pol% devem ser selecionados clones baixos, com maior diâmetro, maior número de colmos por touceiras.The analysis of canonical correlations measures the existence and the intensity of the association between two groups of variables or characters of importance. This study aimed to estimate the intensity in the association between the agronomic and industrial characters in sugarcane. The analysis of canonic correlations allowed to conclude that clones with bigger number of stalks per parcel, greater number of stalks per stool tend to provide an increase in the TCH production. Another conclusion was that shorter clones with largerdiameter, greater number of stalks per stool and plants, are determinant in increasing TCH, brix and pol% characteristics.
Intermittency analysis of correlated data
We describe the method of the analysis of the dependence of the factorial moments on the bin size in which the correlations between the moments computed for different bin sizes are taken into account. For large multiplicity nucleus-nucleus data inclusion of the correlations does not change the values of the slope parameter, but gives errors significantly reduced as compared to the case of fits with no correlations. (author)
Interpretation of correlation analysis results
Kılıç, Selim
2012-01-01
Correlation analysis is used to quantify the degree of linear association between two variables. Correlation coefficient is showed as “r” and it may have values between (-) 1 and (+)1. The symbols (-) or (+) in front of “r coefficient” show the direction of correlation. The direction of association does not affect the strength of association. A “ r coefficient” which is equal or greater than 0.70 is accepted as a good association. Correlation coeefficient only remarks the strength of associat...
A Canonical Analysis of the Einstein-Hilbert Action in First Order Form
Kiriushcheva, N.; Kuzmin, S V; McKeon, D. G. C.
2006-01-01
Using the Dirac constraint formalism, we examine the canonical structure of the Einstein-Hilbert action $S_d = \\frac{1}{16\\pi G} \\int d^dx \\sqrt{-g} R$, treating the metric $g_{\\alpha\\beta}$ and the symmetric affine connection $\\Gamma_{\\mu\
Gauge constrained conditions and quantization of SU(N) gauge theories are analysed by means of Dirac's formalism. In the framework of algebraic dynamics, gauge invariance, Gauss law and Ward identities are discussed. With use of the version of conservation law in correlation dynamics, the conserved Gauss law and Ward identities related to residual gauge invariance can be transformed into initial value problems
Maria Helena Rigão
2009-11-01
Full Text Available Uma das estratégias utilizadas pelos melhoristas de batata é a eliminação de um grande número de clones nas primeiras gerações de seleção, para reduzir os custos e o trabalho de manutenção e multiplicação destes. O objetivo deste trabalho foi avaliar o uso da correlação canônica entre caracteres de tubérculos plantados, relacionados com os colhidos, para auxiliar a seleção precoce de clones de batata. Foram conduzidos três ensaios em diferentes épocas, na área experimental do Departamento de Fitotecnia da Universidade Federal de Santa Maria. Foram avaliados os tubérculos-semente e aqueles colhidos de 10 progênies de batata. Os caracteres utilizados para a análise da correlação canônica foram: o comprimento, o maior e o menor diâmetro e a massa fresca. Com o uso da correlação canônica, observou-se que há relação das diferentes características dos tubérculos plantados e daqueles colhidos. O comprimento apresentou a maior associação entre os tubérculos plantados e colhidos. Tubérculos compridos resultam na produção de tubérculos alongados.A potato breeding strategy is applied in early selection to discard the majority of potato clones, to reduce costs and efforts for maintenance and multiplication. The objective of this research was to test the canonical correlation of seeded tuber traits and harvested tubers to assist the early selection of potato clones. Three experiments in different seasons were carried out in the experimental area of the Horticultural Department of the Federal University of Santa Maria. Seeded and harvested tubers of ten potato progeny were evaluated. The tuber traits length, larger and smaller diameter, and fresh weight were submitted to canonical correlation analysis. The canonical correlation showed a trait relationship between potato seeds and their production. The largest association was tuber length. Therefore, long seed tubers produce elongated tubers as well.
The equations of motion for multi-time correlation Green's functions have been transformed into those for equal-time correlation Green's functions, which include the equations of motion for quark's and gluon's density matrices as well as vertex functions. In two-body correlation truncation approximation, we present the formalism for the equations of motion, Gauss law and Ward identities explicitly
Boyd, R. K.; Brumfield, J. O.; Campbell, W. J.
1984-01-01
Three feature extraction methods, canonical analysis (CA), principal component analysis (PCA), and band selection, have been applied to Thematic Mapper Simulator (TMS) data in order to evaluate the relative performance of the methods. The results obtained show that CA is capable of providing a transformation of TMS data which leads to better classification results than provided by all seven bands, by PCA, or by band selection. A second conclusion drawn from the study is that TMS bands 2, 3, 4, and 7 (thermal) are most important for landcover classification.
佳能EOS系列广告策略分析%Analysis of Canon EOS Advertisement Strategies
杜丹阳
2015-01-01
文章主要研究佳能EOS系列相机的广告策略问题，运用文献分析和实证分析的方法，结合其广告效果，从广告市场策略，产品策略，媒介策略，表现策略等方面入手，对相机业巨头佳能旗下EOS系列的广告策略进行分析评价。通过对广告策略的分析，探讨其广告战略的成功之处，为我国企业的广告营销提供借鉴经验。%The article mainly talks about the advertisement strategies of Canon EOS. Using the method of document research and empirical analysis and combining with the advertising effect to analyze the advertisement strategies of Canon EOS from the aspects of advertising market strategy, product strategy, media strategy and performance strategy. According to the analysis to conclude its success and provides experience for corporations' advertising marketing in China.
Analysis of Canon EOS Advertisement Strategies%佳能EOS系列广告策略分析
杜丹阳
2015-01-01
The article mainly talks about the advertisement strategies of Canon EOS. Using the method of document research and empirical analysis and combining with the advertising effect to analyze the advertisement strategies of Canon EOS from the aspects of advertising market strategy, product strategy, media strategy and performance strategy. According to the analysis to conclude its success and provides experience for corporations' advertising marketing in China.%文章主要研究佳能EOS系列相机的广告策略问题，运用文献分析和实证分析的方法，结合其广告效果，从广告市场策略，产品策略，媒介策略，表现策略等方面入手，对相机业巨头佳能旗下EOS系列的广告策略进行分析评价。通过对广告策略的分析，探讨其广告战略的成功之处，为我国企业的广告营销提供借鉴经验。
Fifth-order canonical geometric aberration analysis of electrostatic round lenses
Liu Zhi Xiong
2002-01-01
In this paper the fifth-order canonical geometric aberration patterns are analyzed and a numerical example is given on the basis of the analytical expressions of fifth-order aberration coefficients derived in the present work. The fifth-order spherical aberration, astigmatism and field curvature, and distortion are similar to the third-order ones and the fifth-order coma is slightly different. Besides, there are two more aberrations which do not exist in the third-order aberration: they are peanut aberration and elliptical coma in accordance with their shapes. In the numerical example, by using a cross-check of the calculated coefficients with those computed through the differential algebraic method, it has been verified that all the expressions are correct and the computational results are reliable with high precision.
Image patch analysis of sunspots and active regions. I. Intrinsic dimension and correlation analysis
Moon, Kevin R; Delouille, Veronique; De Visscher, Ruben; Watson, Fraser; Hero, Alfred O
2015-01-01
Complexity of an active region is related to its flare-productivity. Mount Wilson or McIntosh sunspot classifications measure such complexity but in a categorical way, and may therefore not use all the information present in the observations. Moreover, such categorical schemes hinder a systematic study of an active region's evolution for example. We propose fine-scale quantitative descriptors for an active region's complexity and relate them to the Mount Wilson classification. We analyze the local correlation structure within continuum and magnetogram data, as well as the cross-correlation between continuum and magnetogram data. We compute the intrinsic dimension, partial correlation, and canonical correlation analysis (CCA) of image patches of continuum and magnetogram active region images taken from the SOHO-MDI instrument. We use masks of sunspots derived from continuum as well as larger masks of magnetic active regions derived from the magnetogram to analyze separately the core part of an active region fr...
Twist-4 effects in electroproduction: Canonical operators and coefficient functions
The interpretation of observed scaling violations in leptoproduction is complicated by the possible presence of significant higher-twist effects. We refine the machinery of the operator-product expansion sufficiently for a study of twist-4 effects. In particular, we introduce and review the advantages of a special, ''canonical'' basis. We demonstrate that the canonical basis is adequate for the necessary twist-4 perturbative calculations, and calculate the operator's tree-level coefficient functions in electroproduction. Our results establish a framework within which careful analysis of more accurate data can provide information regarding correlations among the constituents of the proton
Moslehi, Roxana; Mills, James L; Signore, Caroline; Kumar, Anil; Ambroggio, Xavier; Dzutsev, Amiran
2013-01-01
We previously suggested links between specific XPD mutations in the fetal genome and the risk of placental maldevelopment and preeclampsia, possibly due to impairment of Transcription Factor (TF)IIH-mediated functions in placenta. To identify the underlying mechanisms, we conducted the current integrative analysis of several relevant transcriptome data sources. Our meta-analysis revealed downregulation of TFIIH subunits in preeclamptic placentas. Our overall integrative analysis suggested tha...
Rosa, M.J.; Mehta, M.A.; Pich, E.M.; Risterucci, C.; Zelaya, F.; Reinders, A.A.T.S.; Williams, S.C.R.; Dazzan, P.; Doyle, O.M.; Marquand, A.F.
2015-01-01
An increasing number of neuroimaging studies are based on either combining more than one data modality (inter-modal) or combining more than one measurement from the same modality (intra-modal). To date, most intra-modal studies using multivariate statistics have focused on differences between datase
Canonical-correlation analysis applied to selection-index methodology in quails
Marubayashi Hidalgo, A.; Silva, da L.P.; Mota, R.R.; Martins, E.N.
2014-01-01
Genetic evaluations in dual-purpose quails (Coturnix coturnix) have demonstrated that overall genetic gains in a breeding program are achieved not only based on a specific trait, but on several. The most common technique to use all this information is the selection index. Another alternative may be
Analysis of Negative Correlation Learning
Liu Yong; Zou Xiu-fen
2003-01-01
This paper describes negative correlation learning for designing neural network ensembles. Negative correlation learning has been firstly analysed in terms of minimising mutual information on a regression task. By ninimising the mutual information between variables extracted by two neural networks, they are forced to convey different information about some features of their input. Based on the decision boundaries and correct response sets, negative correlation learning has been further studied on two pattern classification problems. The purpose of examining the decision boundaries and the correct response sets is not only to illustrate the learning behavior of negative correlation learning, but also to cast light on how to design more effective neural network ensembles. The experimental results showed the decision boundary of the trained neural network ensemble by negative correlation learning is almost as good as the optimum decision boundary.
Correlative feature analysis on FFDM
Identifying the corresponding images of a lesion in different views is an essential step in improving the diagnostic ability of both radiologists and computer-aided diagnosis (CAD) systems. Because of the nonrigidity of the breasts and the 2D projective property of mammograms, this task is not trivial. In this pilot study, we present a computerized framework that differentiates between corresponding images of the same lesion in different views and noncorresponding images, i.e., images of different lesions. A dual-stage segmentation method, which employs an initial radial gradient index (RGI) based segmentation and an active contour model, is applied to extract mass lesions from the surrounding parenchyma. Then various lesion features are automatically extracted from each of the two views of each lesion to quantify the characteristics of density, size, texture and the neighborhood of the lesion, as well as its distance to the nipple. A two-step scheme is employed to estimate the probability that the two lesion images from different mammographic views are of the same physical lesion. In the first step, a correspondence metric for each pairwise feature is estimated by a Bayesian artificial neural network (BANN). Then, these pairwise correspondence metrics are combined using another BANN to yield an overall probability of correspondence. Receiver operating characteristic (ROC) analysis was used to evaluate the performance of the individual features and the selected feature subset in the task of distinguishing corresponding pairs from noncorresponding pairs. Using a FFDM database with 123 corresponding image pairs and 82 noncorresponding pairs, the distance feature yielded an area under the ROC curve (AUC) of 0.81±0.02 with leave-one-out (by physical lesion) evaluation, and the feature metric subset, which included distance, gradient texture, and ROI-based correlation, yielded an AUC of 0.87±0.02. The improvement by using multiple feature metrics was statistically
Correlative feature analysis on FFDM
Yuan Yading; Giger, Maryellen L.; Li Hui; Sennett, Charlene [Department of Radiology, Committee on Medical Physics, University of Chicago, 5841 South Maryland Avenue, MC 2026 Chicago, Illinois 60637 (United States)
2008-12-15
Identifying the corresponding images of a lesion in different views is an essential step in improving the diagnostic ability of both radiologists and computer-aided diagnosis (CAD) systems. Because of the nonrigidity of the breasts and the 2D projective property of mammograms, this task is not trivial. In this pilot study, we present a computerized framework that differentiates between corresponding images of the same lesion in different views and noncorresponding images, i.e., images of different lesions. A dual-stage segmentation method, which employs an initial radial gradient index (RGI) based segmentation and an active contour model, is applied to extract mass lesions from the surrounding parenchyma. Then various lesion features are automatically extracted from each of the two views of each lesion to quantify the characteristics of density, size, texture and the neighborhood of the lesion, as well as its distance to the nipple. A two-step scheme is employed to estimate the probability that the two lesion images from different mammographic views are of the same physical lesion. In the first step, a correspondence metric for each pairwise feature is estimated by a Bayesian artificial neural network (BANN). Then, these pairwise correspondence metrics are combined using another BANN to yield an overall probability of correspondence. Receiver operating characteristic (ROC) analysis was used to evaluate the performance of the individual features and the selected feature subset in the task of distinguishing corresponding pairs from noncorresponding pairs. Using a FFDM database with 123 corresponding image pairs and 82 noncorresponding pairs, the distance feature yielded an area under the ROC curve (AUC) of 0.81{+-}0.02 with leave-one-out (by physical lesion) evaluation, and the feature metric subset, which included distance, gradient texture, and ROI-based correlation, yielded an AUC of 0.87{+-}0.02. The improvement by using multiple feature metrics was statistically
V. S. Olkhovsky
2009-01-01
Full Text Available Recent developments are reviewed and some new results are presented in the study of time in quantum mechanics and quantum electrodynamics as an observable, canonically conjugate to energy. This paper deals with the maximal Hermitian (but nonself-adjoint operator for time which appears in nonrelativistic quantum mechanics and in quantum electrodynamics for systems with continuous energy spectra and also, briefly, with the four-momentum and four-position operators, for relativistic spin-zero particles. Two measures of averaging over time and connection between them are analyzed. The results of the study of time as a quantum observable in the cases of the discrete energy spectra are also presented, and in this case the quasi-self-adjoint time operator appears. Then, the general foundations of time analysis of quantum processes (collisions and decays are developed on the base of time operator with the proper measures of averaging over time. Finally, some applications of time analysis of quantum processes (concretely, tunneling phenomena and nuclear processes are reviewed.
Van der Vyver’s analysis of rights: a case study drawn from thirteenth-century canon law
Charles J. Reid, Jr.
1999-03-01
Full Text Available In an important article published in 1988, Johan Van der Vyver challenged the prevailing reliance on Wesley Hohfeld’s taxonomy of rights. Hohfeld's division of rights into claims, powers, privileges and immunities, Van der Vyver stresses, is excessively concerned with "inter-individual legal relations” at the expense of the right-holder's relationship to the object of the right. Van der Vyver proposes instead that an assertion of right involves three distinct juridic aspects:• legal capacity, which is "the competence to occupy the offices of legal subject;• legal claim, which "comprises claims of a legal subject as against other persons to a legal object";• legal entitlement, which specifies the boundaries of the right-holder's ability to use, enjoy, consume, destroy or alienate the right in question.This article applies Van der Vyver’s taxonomy to the operations of thirteenthcentury canon law, and demonstrates that Van der Vyver’s analysis provides greater depth than Hohfeld's, in that it considers both the relationship of the person claiming a particular right and the object of that right.
Vestergaard, Jacob Schack; Nielsen, Allan Aasbjerg
2013-01-01
Canonical correlation analysis (CCA) maximizes correlation between two sets of multivariate data. We applied CCA to multivariate satellite data and univariate radar data in order to produce a subspace descriptive of heavily precipitating clouds. A misalignment, inherent to the nature of the two d...
AN IMPROVED ALGORITHM FOR DPIV CORRELATION ANALYSIS
WU Long-hua
2007-01-01
In a Digital Particle Image Velocimetry (DPIV) system, the correlation of digital images is normally used to acquire the displacement information of particles and give estimates of the flow field. The accuracy and robustness of the correlation algorithm directly affect the validity of the analysis result. In this article, an improved algorithm for the correlation analysis was proposed which could be used to optimize the selection/determination of the correlation window, analysis area and search path. This algorithm not only reduces largely the amount of calculation, but also improves effectively the accuracy and reliability of the correlation analysis. The algorithm was demonstrated to be accurate and efficient in the measurement of the velocity field in a flocculation pool.
Vibration analysis using digital correlation
Gilbert, John A.; Lehner, David L.; Dudderar, T. Dixon; Matthys, Donald R.
1988-01-01
This paper demonstrates the use of a computer-based optical method for locating the positions of nodes and antinodes in vibrating members. Structured light patterns are projected at an angle onto the vibrating surface using a 35 mm slide projector. The vibrating surface and the projected images are captured in a time averaged photograph which is subsequently digitized. The inherent fringe patterns are filtered to determine amplitudes of vibration, and computer programs are used to compare the time averaged images to images recorded prior to excitation to locate nodes and antinodes. Some of the influences of pattern regularity on digital correlation are demonstrated, and a speckle-based method for determining the mode shapes and the amplitudes of vibration with variable sensitivity is suggested.
Quantum correlations; quantum probability approach
Majewski, W A
2014-01-01
This survey gives a comprehensive account of quantum correlations understood as a phenomenon stemming from the rules of quantization. Centered on quantum probability it describes the physical concepts related to correlations (both classical and quantum), mathematical structures, and their consequences. These include the canonical form of classical correlation functionals, general definitions of separable (entangled) states, definition and analysis of quantumness of correlations, description o...
NEW CORRELATION COEFFICIENT FOR DATA ANALYSIS
Falie, Dragos; Livia DAVID
2012-01-01
The proposed correlation coefficient better characterize the statistical independence of two random variables that are a linear mixture of two independent sources. This correlation coefficient can be calculated with analytical relations or with the known algorithms of independent components analysis (ICA). The value of the correlation coefficient is zero when the random variables are a statistically independent and it is one when these are fully dependent.
Bakony, Mikolt; Hufnágel, Levente; Tőzsér, János; Jurkovich, Viktor
2015-01-01
We investigated the associations between heart rate variability (HRV) parameters and some housing- and individual-related variables using the canonical correspondence analysis (CCOA) method in lactating Holstein-Friesian dairy cows. We collected a total of 5200 5-min interbeat interval (IBI) samples from 260 animals on five commercial dairy farms [smaller-scale farms with 70 (Farm 1, n = 50) and 80 cows per farm (Farm 2, n = 40), and larger-scale farms with 850 (Farm 3, n = 66), 1900 (Farm 4, n = 60) and 1200 (Farm 5, n = 45) cows. Dependent variables included HRV parameters, which reflect the activity of the autonomic nervous system: heart rate (HR), the root mean square of successive differences (RMSSD) in IBIs, the standard deviation 1 (SD1), the high frequency (HF) component of HRV and the ratio between the low frequency (LF) and the HF parameter (LF/HF). Explanatory variables were group size, space allowance, milking frequency, parity, daily milk yield, body condition score, locomotion score, farm, season and physical activity (lying, lying and rumination, standing, standing and rumination and feeding). Physical activity involved in standing, feeding and in rumination was associated with HRV parameters, indicating a decreasing sympathetic and an increasing vagal tone in the following order: feeding, standing, standing and rumination, lying and rumination, lying. Objects representing summer positioned close to HR and LF and far from SD1, RMSSD and HF indicate a higher sympathetic and a lower vagal activity. Objects representing autumn, spring and winter associated with increasing vagal activity, in this order. Time-domain measures of HRV were associated with most of the housing- and individual-related explanatory variables. Higher HR and lower RMSSD and SD1 were associated with higher group size, milking frequency, parity and milk yield, and low space allowance. Higher parity and milk yield were associated with higher sympathetic activity as well (higher LF
Carlos García-Bedoya Maguiña
2011-05-01
Full Text Available Canon es un concepto clave en la historia literaria. En el presente artículo,se revisa la evolución histórica del canon literario peruano. Es solo con la llamada República Aristocrática, en las primeras décadas del siglo XX, que cabe hablar en el caso peruano de la formación de un auténtico canon nacional. El autor denomina a esta primera versión del canon literario peruano como canon oligárquico y destaca la importancia de la obra de Riva Agüero y de Ventura García Calderón en su configuración. Es solo más tarde, desde los años 20 y de modo definitivo desde los años 50, que puede hablarse de la emergencia de un nuevo canon literarioal que el autor propone determinar canon posoligárquico.
Refined Multifractal Cross-Correlation Analysis
Oświȩcimka, Paweł; Forczek, Marcin; Jadach, Stanisław; Kwapień, Jarosław
2013-01-01
We propose a modified algorithm - Multifractal Cross-Correlation Analysis (MFCCA) - that is able to consistently identify and quantify multifractal cross-correlations between two time series. Our motivation for introducing this algorithm is that the already existing methods like MF-DXA have serious limitations for most of the signals describing complex natural processes. The principal component of the related improvement is proper incorporation of the sign of fluctuations. We present a broad analysis of the model fractal stochastic processes as well as of the real-world signals and show that MFCCA is a robust tool and allows a reliable quantification of the cross-correlative structure of analyzed processes. We, in particular, analyze a relation between the generalized Hurst exponent and the MFCCA parameter $\\lambda_q$. This relation provides information about the character of potential multifractality in cross-correlations of the processes under study and thus enables selective insight into their dynamics. Us...
Detrended cross-correlation analysis of electroencephalogram
In the paper we use detrended cross-correlation analysis (DCCA) to study the electroencephalograms of healthy young subjects and healthy old subjects. It is found that the cross-correlation between different leads of a healthy young subject is larger than that of a healthy old subject. It was shown that the cross-correlation relationship decreases with the aging process and the phenomenon can help to diagnose whether the subject's brain function is healthy or not. (interdisciplinary physics and related areas of science and technology)
Bertot, Yves; Gonthier, Georges; Ould Biha, Sidi; Pasca, Ioana
2008-01-01
In this paper, we present an approach to describe uniformly iterated “big” operations and to provide lemmas that encapsulate all the commonly used reasoning steps on these constructs. We show that these iterated operations can be handled generically using the syntactic notation and canonical structure facilities provided by the Coq system. We then show how these canonical big operations played a crucial enabling role in the study of various parts of linear algebra and multi-dimensional real a...
Relations between canonical and non-canonical inflation
Gwyn, Rhiannon [Max-Planck-Institut fuer Gravitationsphysik (Albert-Einstein-Institut), Potsdam (Germany); Rummel, Markus [Hamburg Univ. (Germany). 2. Inst. fuer Theoretische Physik; Westphal, Alexander [Deutsches Elektronen-Synchrotron (DESY), Hamburg (Germany). Theory Group
2012-12-15
We look for potential observational degeneracies between canonical and non-canonical models of inflation of a single field {phi}. Non-canonical inflationary models are characterized by higher than linear powers of the standard kinetic term X in the effective Lagrangian p(X,{phi}) and arise for instance in the context of the Dirac-Born-Infeld (DBI) action in string theory. An on-shell transformation is introduced that transforms non-canonical inflationary theories to theories with a canonical kinetic term. The 2-point function observables of the original non-canonical theory and its canonical transform are found to match in the case of DBI inflation.
Relations between canonical and non-canonical inflation
We look for potential observational degeneracies between canonical and non-canonical models of inflation of a single field φ. Non-canonical inflationary models are characterized by higher than linear powers of the standard kinetic term X in the effective Lagrangian p(X,φ) and arise for instance in the context of the Dirac-Born-Infeld (DBI) action in string theory. An on-shell transformation is introduced that transforms non-canonical inflationary theories to theories with a canonical kinetic term. The 2-point function observables of the original non-canonical theory and its canonical transform are found to match in the case of DBI inflation.
Laumont, Céline M; Daouda, Tariq; Laverdure, Jean-Philippe; Bonneil, Éric; Caron-Lizotte, Olivier; Hardy, Marie-Pierre; Granados, Diana P; Durette, Chantal; Lemieux, Sébastien; Thibault, Pierre; Perreault, Claude
2016-01-01
In view of recent reports documenting pervasive translation outside of canonical protein-coding sequences, we wished to determine the proportion of major histocompatibility complex (MHC) class I-associated peptides (MAPs) derived from non-canonical reading frames. Here we perform proteogenomic analyses of MAPs eluted from human B cells using high-throughput mass spectrometry to probe the six-frame translation of the B-cell transcriptome. We report that ∼ 10% of MAPs originate from allegedly noncoding genomic sequences or exonic out-of-frame translation. The biogenesis and properties of these 'cryptic MAPs' differ from those of conventional MAPs. Cryptic MAPs come from very short proteins with atypical C termini, and are coded by transcripts bearing long 3'UTRs enriched in destabilizing elements. Relative to conventional MAPs, cryptic MAPs display different MHC class I-binding preferences and harbour more genomic polymorphisms, some of which are immunogenic. Cryptic MAPs increase the complexity of the MAP repertoire and enhance the scope of CD8 T-cell immunosurveillance. PMID:26728094
A survey of roadside vegetation and soils along Lahore-Islamabad motorway (M-2) was undertaken and the data were subjected to Canonical Correspondence Analysis to investigate the vegetation structure and its relationships to the selected edaphic variables. In addition, the patterns of plant species distribution in the whole study area and its different regions were also determined. CCA ordination was performed on a matrix containing % age cover value for all species (n = 227 species) on 397 sampled plots. This relationship was determined by ordination analysis. The environmental variables selected for analysis were organic matter, sodium, potassium, calcium, magnesium, total nitrogen and trace elements like lead, zinc, nickel, cadmium, chromium and iron. In CCA analysis of all the quadrats, chromium, zinc, lead, nickel, sodium and potassium were the most important variables influencing the quadrats distribution. The study also provides basic information for the implementation of conservation oriented planning and management to preserve and improve the road verges of M-2. (author)
You, Setthivoine
2015-11-01
A new canonical field theory has been developed to help interpret the interaction between plasma flows and magnetic fields. The theory augments the Lagrangian of general dynamical systems to rigourously demonstrate that canonical helicity transport is valid across single particle, kinetic and fluid regimes, on scales ranging from classical to general relativistic. The Lagrangian is augmented with two extra terms that represent the interaction between the motion of matter and electromagnetic fields. The dynamical equations can then be re-formulated as a canonical form of Maxwell's equations or a canonical form of Ohm's law valid across all non-quantum regimes. The field theory rigourously shows that helicity can be preserved in kinetic regimes and not only fluid regimes, that helicity transfer between species governs the formation of flows or magnetic fields, and that helicity changes little compared to total energy only if density gradients are shallow. The theory suggests a possible interpretation of particle energization partitioning during magnetic reconnection as canonical wave interactions. This work is supported by US DOE Grant DE-SC0010340.
Robust Correlated and Individual Component Analysis.
Panagakis, Yannis; Nicolaou, Mihalis A; Zafeiriou, Stefanos; Pantic, Maja
2016-08-01
Recovering correlated and individual components of two, possibly temporally misaligned, sets of data is a fundamental task in disciplines such as image, vision, and behavior computing, with application to problems such as multi-modal fusion (via correlated components), predictive analysis, and clustering (via the individual ones). Here, we study the extraction of correlated and individual components under real-world conditions, namely i) the presence of gross non-Gaussian noise and ii) temporally misaligned data. In this light, we propose a method for the Robust Correlated and Individual Component Analysis (RCICA) of two sets of data in the presence of gross, sparse errors. We furthermore extend RCICA in order to handle temporal incongruities arising in the data. To this end, two suitable optimization problems are solved. The generality of the proposed methods is demonstrated by applying them onto 4 applications, namely i) heterogeneous face recognition, ii) multi-modal feature fusion for human behavior analysis (i.e., audio-visual prediction of interest and conflict), iii) face clustering, and iv) thetemporal alignment of facial expressions. Experimental results on 2 synthetic and 7 real world datasets indicate the robustness and effectiveness of the proposed methodson these application domains, outperforming other state-of-the-art methods in the field. PMID:26552077
Canonical affordances in context
Alan Costall
2012-12-01
Full Text Available James Gibson’s concept of affordances was an attempt to undermine the traditional dualism of the objective and subjective. Gibson himself insisted on the continuity of “affordances in general” and those attached to human artifacts. However, a crucial distinction needs to be drawn between “affordances in general” and the “canonical affordances” that are connected primarily to artifacts. Canonical affordances are conventional and normative. It is only in such cases that it makes sense to talk of the affordance of the object. Chairs, for example, are for sitting-on, even though we may also use them in many other ways. A good deal of confusion has arisen in the discussion of affordances from (1 the failure to recognize the normative status of canonical affordances and (2 then generalizing from this special case.
Image patch analysis of sunspots and active regions. I. Intrinsic dimension and correlation analysis
Moon, Kevin R.; Li, Jimmy J.; Delouille, Véronique; De Visscher, Ruben; Watson, Fraser; Hero, Alfred O.
2016-01-01
Context. The flare productivity of an active region is observed to be related to its spatial complexity. Mount Wilson or McIntosh sunspot classifications measure such complexity but in a categorical way, and may therefore not use all the information present in the observations. Moreover, such categorical schemes hinder a systematic study of an active region's evolution for example. Aims: We propose fine-scale quantitative descriptors for an active region's complexity and relate them to the Mount Wilson classification. We analyze the local correlation structure within continuum and magnetogram data, as well as the cross-correlation between continuum and magnetogram data. Methods: We compute the intrinsic dimension, partial correlation, and canonical correlation analysis (CCA) of image patches of continuum and magnetogram active region images taken from the SOHO-MDI instrument. We use masks of sunspots derived from continuum as well as larger masks of magnetic active regions derived from magnetogram to analyze separately the core part of an active region from its surrounding part. Results: We find relationships between the complexity of an active region as measured by its Mount Wilson classification and the intrinsic dimension of its image patches. Partial correlation patterns exhibit approximately a third-order Markov structure. CCA reveals different patterns of correlation between continuum and magnetogram within the sunspots and in the region surrounding the sunspots. Conclusions: Intrinsic dimension has the potential to distinguish simple from complex active regions. These results also pave the way for patch-based dictionary learning with a view toward automatic clustering of active regions.
Canonical phylogenetic ordination.
Giannini, Norberto P
2003-10-01
A phylogenetic comparative method is proposed for estimating historical effects on comparative data using the partitions that compose a cladogram, i.e., its monophyletic groups. Two basic matrices, Y and X, are defined in the context of an ordinary linear model. Y contains the comparative data measured over t taxa. X consists of an initial tree matrix that contains all the xj monophyletic groups (each coded separately as a binary indicator variable) of the phylogenetic tree available for those taxa. The method seeks to define the subset of groups, i.e., a reduced tree matrix, that best explains the patterns in Y. This definition is accomplished via regression or canonical ordination (depending on the dimensionality of Y) coupled with Monte Carlo permutations. It is argued here that unrestricted permutations (i.e., under an equiprobable model) are valid for testing this specific kind of groupwise hypothesis. Phylogeny is either partialled out or, more properly, incorporated into the analysis in the form of component variation. Direct extensions allow for testing ecomorphological data controlled by phylogeny in a variation partitioning approach. Currently available statistical techniques make this method applicable under most univariate/multivariate models and metrics; two-way phylogenetic effects can be estimated as well. The simplest case (univariate Y), tested with simulations, yielded acceptable type I error rates. Applications presented include examples from evolutionary ethology, ecology, and ecomorphology. Results showed that the new technique detected previously overlooked variation clearly associated with phylogeny and that many phylogenetic effects on comparative data may occur at particular groups rather than across the entire tree. PMID:14530135
The canonical and grand canonical models for nuclear multifragmentation
G Chaudhuri; S Das Gupta
2010-08-01
Many observables seen in intermediate energy heavy-ion collisions can be explained on the basis of statistical equilibrium. Calculations based on statistical equilibrium can be implemented in microcanonical ensemble, canonical ensemble or grand canonical ensemble. This paper deals with calculations with canonical and grand canonical ensembles. A recursive relation developed recently allows calculations with arbitrary precision for many nuclear problems. Calculations are done to study the nature of phase transition in nuclear matter.
Gait correlation analysis based human identification.
Chen, Jinyan
2014-01-01
Human gait identification aims to identify people by a sequence of walking images. Comparing with fingerprint or iris based identification, the most important advantage of gait identification is that it can be done at a distance. In this paper, silhouette correlation analysis based human identification approach is proposed. By background subtracting algorithm, the moving silhouette figure can be extracted from the walking images sequence. Every pixel in the silhouette has three dimensions: horizontal axis (x), vertical axis (y), and temporal axis (t). By moving every pixel in the silhouette image along these three dimensions, we can get a new silhouette. The correlation result between the original silhouette and the new one can be used as the raw feature of human gait. Discrete Fourier transform is used to extract features from this correlation result. Then, these features are normalized to minimize the affection of noise. Primary component analysis method is used to reduce the features' dimensions. Experiment based on CASIA database shows that this method has an encouraging recognition performance. PMID:24592144
Gait Correlation Analysis Based Human Identification
Jinyan Chen
2014-01-01
Full Text Available Human gait identification aims to identify people by a sequence of walking images. Comparing with fingerprint or iris based identification, the most important advantage of gait identification is that it can be done at a distance. In this paper, silhouette correlation analysis based human identification approach is proposed. By background subtracting algorithm, the moving silhouette figure can be extracted from the walking images sequence. Every pixel in the silhouette has three dimensions: horizontal axis (x, vertical axis (y, and temporal axis (t. By moving every pixel in the silhouette image along these three dimensions, we can get a new silhouette. The correlation result between the original silhouette and the new one can be used as the raw feature of human gait. Discrete Fourier transform is used to extract features from this correlation result. Then, these features are normalized to minimize the affection of noise. Primary component analysis method is used to reduce the features’ dimensions. Experiment based on CASIA database shows that this method has an encouraging recognition performance.
Metrics correlation and analysis service (MCAS)
The complexity of Grid workflow activities and their associated software stacks inevitably involves multiple organizations, ownership, and deployment domains. In this setting, important and common tasks such as the correlation and display of metrics and debugging information (fundamental ingredients of troubleshooting) are challenged by the informational entropy inherent to independently maintained and operated software components. Because such an information 'pond' is disorganized, it a difficult environment for business intelligence analysis i.e. troubleshooting, incident investigation and trend spotting. The mission of the MCAS project is to deliver a software solution to help with adaptation, retrieval, correlation, and display of workflow-driven data and of type-agnostic events, generated by disjoint middleware.
Metrics correlation and analysis service (MCAS)
Baranovski, Andrew; Dykstra, Dave; Garzoglio, Gabriele; Hesselroth, Ted; Mhashilkar, Parag; Levshina, Tanya; /Fermilab
2009-05-01
The complexity of Grid workflow activities and their associated software stacks inevitably involves multiple organizations, ownership, and deployment domains. In this setting, important and common tasks such as the correlation and display of metrics and debugging information (fundamental ingredients of troubleshooting) are challenged by the informational entropy inherent to independently maintained and operated software components. Because such an information 'pond' is disorganized, it a difficult environment for business intelligence analysis i.e. troubleshooting, incident investigation and trend spotting. The mission of the MCAS project is to deliver a software solution to help with adaptation, retrieval, correlation, and display of workflow-driven data and of type-agnostic events, generated by disjoint middleware.
Quaternion Linear Canonical Transform Application
Bahri, Mawardi
2015-01-01
Quaternion linear canonical transform (QLCT) is a generalization of the classical linear canonical transfom (LCT) using quaternion algebra. The focus of this paper is to introduce an application of the QLCT to study of generalized swept-frequency filter
Realizations of the Canonical Representation
M K Vemuri
2008-02-01
A characterisation of the maximal abelian subalgebras of the bounded operators on Hilbert space that are normalised by the canonical representation of the Heisenberg group is given. This is used to classify the perfect realizations of the canonical representation.
Olesen, Merete Halkjær; Shetty, Nisha; Gislum, René;
2011-01-01
Near-infrared (NIR) reflectance spectroscopy is a common non-destructive method for predicting seed quality parameters, such as moisture, oil, carbohydrates and protein content. Furthermore, variations in absorbance between germinating and non-germinating seeds have been shown in single seed...... studies. Spinach (Spinacia oleracea L.) is the major crop in vegetable seed production in Denmark and two seed lots with viability percentages of 90% and 97% were chosen for examination by single seed NIR spectroscopy. Lipids play a major role in both ageing and germination. During accelerated ageing......, lipid peroxidation leads to deterioration of cell membranes and contributes in that way to reducing seed viability of the seed sample. These biochemical changes may be the reason for a clear grouping between aged and non-aged seeds when performing the extended canonical variates analysis (ECVA...
Rhythmic canons and modular tiling
Caure, Hélianthe
2016-01-01
This thesis is a contribution to the study of modulo p tiling. Many mathematical and computational tools were used for the study of rhythmic tiling canons. Recent research has mainly focused in finding tiling without inner periodicity, being called Vuza canons. Those canons are a constructive basis for all rhythmic tiling canons, however, they are really difficult to obtain. Best current method is a brut force exploration that, despite a few recent enhancements, is exponential. Many technics ...
Canonical quantization of macroscopic electromagnetism
Philbin, Thomas Gerard
2010-01-01
Application of the standard canonical quantization rules of quantum field theory to macroscopic electromagnetism has encountered obstacles due to material dispersion and absorption. This has led to a phenomenological approach to macroscopic quantum electrodynamics where no canonical formulation is attempted. In this paper macroscopic electromagnetism is canonically quantized. The results apply to any linear, inhomogeneous, magnetodielectric medium with dielectric functions that obey the Krame...
Revisiting Canonical Quantization
Klauder, John R.
2012-01-01
Conventional canonical quantization procedures directly link various c-number and q-number quantities. Here, we advocate a different association of classical and quantum quantities that renders classical theory a natural subset of quantum theory with \\hbar>0, in conformity with the real world wherein nature has chosen \\hbar>0 rather than \\hbar=0. While keeping the good results of conventional procedures, some examples are presented for which the new procedures offer better results than conven...
Canonical Infinitesimal Deformations
Ran, Ziv
1998-01-01
This paper gives a canonical construction, in terms of additive cohomological functors, of the universal formal deformation of a compact complex manifold without vector fields (more generally of a faithful $g$-module, where $g$ is a sheaf of Lie algebras without sections). The construction is based on a certain (multivariate) Jacobi complex $J(g)$ associatd to $g$: indeed ${\\mathbb C}\\oplus {\\mathbb H}^0(J(g))^*$ is precisely the base ring of the universal deformation.
Analysis on Homocysteine's Risk to Atherosclerosis and Its Correlations with Serum Lipids
李河; 郭兰; 肖敏; 陈铁峰; 吴书林; 余细勇; 石美铃; 董太明; 刘小清; 黄平; 李义和
2004-01-01
Objectives To explore the homocysteine's risk to atherosclerosis and its correlations with serum lipids TG,TG and HDL-C. Methods With a cross sectional study, 490 subjects (aged 41-86 yrs, male 420 and female 70) were surveyed in 1999 in Guangdong Province, China. The main research variables were homocysteine (Hcy) and the serum lipids total cholesterol (TC), triglyceride (TG),high-density lipoprotein cholesterol(HDL-C). Results Hcy was a possible risk factor resulting in atherosclerosis (OR=l.15, 0.05 ＜P ＜0.10, n=108) with Logistic regression analysis. There is no correlation or much lower degree correlation between Hey and the serum lipids group of TC, TG, HDL-C. The canonical correlation coefficient between V1 and W1 was R1,Can =0.12(0.05＜P＜0.10, n=490, V1=Hcy, W1= - 0.9446 * TC + 0.1588 * TG + 0.6009 * HDL-C). Conclusions It is possible that Hcy is a risk factor to atherosclerosis and is independent of serum lipids group or has much lower correlation with it. It is necessary to do more research to explore the risk degree of Hcy inducing atherosclerosis and whether are there are bigger correlations or higher independence between Hcy and other risk factors during the progress of atherosclerosis.
The random-variable canonical distribution
An alternative interpretation to Gibbs' concept of the canonical distribution for an ensemble of systems in statistical equilibrium is proposed. Whereas Gibbs' theory is based upon a consideration of systems subject to dynamical law, the present analysis relies neither on the classical equations of motion nor makes use of any a priori probability of a complexion; rather, it makes avail of the basic algebra of random variables and, specifically, invokes the law of large numbers. Thereby, a canonical distribution is derived which describes a macrosystem in probabilistic, rather than deterministic, terms, and facilitates the understanding of energy fluctuations which occur in macrosystems at an overall constant ensemble temperature. A discussion is given of a modified form of the Gibbs canonical distribution which takes full account of the effects of random energy fluctuations. It is demonstrated that the results from this modified analysis are entirely consonant with those derived from the random-variable approach. (author)
Extension of warm inflation to non-canonical scalar fields
Zhang, Xiao-Min
2014-01-01
We extend the warm inflationary scenario to the case of the non-canonical scalar fields. The equation of motion and the other basic equations of this new scenario are obtained. The Hubble damped term is enhanced in non-canonical inflation. A linear stability analysis is performed to give the proper slow roll conditions in warm non-canonical inflation. We study the density fluctuations in the new picture and obtain an approximate analytic expression of the power spectrum. The energy scale at the horizon crossing is depressed by both non-canonical effect and thermal effect, so does the tensor-to-scalar ratio. Besides the synergy, the non-canonical effect and the thermal effect are competing in the case of the warm non-canonical inflation.
Correlation Analysis of SFI Peculiar Velocities
We present results of a statistical analysis of the SFI catalog of peculiar velocities, a recently completed survey of spiral field galaxies with I-band Tully-Fisher distances. The velocity field statistic utilized is the velocity correlation function, ψ1(r), originally introduced by Gorski et al. The analysis is performed in redshift space so as to circumvent potential ambiguities connected with inhomogeneous Malmquist bias corrections. The results from the SFI sample are compared with linear-theory predictions for a class of cosmological models. We generate a large set of mock samples, extracted from N-body simulations, which are used to assess the reliability of our analysis and to estimate the associated uncertainties. We assume a class of cold dark matter-like power spectrum models, specified by σ8, the rms fluctuation amplitude within a sphere of 8 h-1 Mpc radius, and by the shape parameter, Γ. Defining η8 =σ8 Ω0.60, we find that the measured ψ1(r) implies a degenerate constraint in the (η8, Γ)-plane, with η8 =0.3±0.1(Γ/0.2)0.5 at the 2 σ level for the inverse Tully-Fisher (ITF) calibration presented in this paper. We investigate how much this constraint changes as we account for uncertainties in the analysis method and uncertainties in the distance indicator, and we consider alternative ITF calibrations. We find that both changing the error-weighting scheme and selecting galaxies according to different limiting line widths has a negligible effect. On the contrary, the model constraints are quite sensitive to the ITF calibration. The other ITF calibrations, by Giovanelli et al. and da Costa et al. both yield, for Γ = 0.2, a best-fit value of η8 ≅ 0.6. (c) (c) 2000. The American Astronomical Society
Bonduelle, M
1987-01-01
The Canon Law (Codex Iuris Canonici), promulgated in 1917, was a classification of laws and jurisprudence which ruled the early Church, governed the ecclesiastical condition of Roman Church until its reorganisation in 1983. It forbade to be ordained or to exercise orders already received to "those who are or were epileptics either not quite in their right mind or possessed by the Evil One". All the context and in particular the paragraph which treated of bodily lacks, indicated that between these three conditions, there was juxtaposition and no confusion. The texts specified the foundations of these dispositions, not in a malefic view of epilepsy inherited from Morbus Sacer of Antiquity, but in decency and on account of risk incured by Eucharist in case of fit. Some derogations could attenuate the severity of these dispositions--as jurisprudence had taken progresses of Epileptology and therapeutics into consideration. In the new Code of Canon Law (1983) physical disabilities were removed from the text and also possessed evil and epilepsy, the only impediment being "insanity or other psychic defect" appreciation of which is done by experts. Concerning poorly controlled epilepsies, we believe that experts will be allowed to express their opinion and a new jurisprudence will make up for the silence of the law. PMID:3310183
Sahamet Bulbul; Selay Giray
2012-01-01
Life satisfaction has two essential subdimension that are job satisfaction and special life satisfaction. The subject of the relationship between these two basic subdimensions catch most of social scientists attention since 1950. With expectation of existing interaction between job satisfaction and special life satisfaction, different theoretical approaches developed. The basic objective of this study is to determine whether existing relationship between job satisfaction and special life sati...
A New Methodology of Spatial Cross-Correlation Analysis
Chen, Yanguang
2015-01-01
Spatial correlation modeling comprises both spatial autocorrelation and spatial cross-correlation processes. The spatial autocorrelation theory has been well-developed. It is necessary to advance the method of spatial cross-correlation analysis to supplement the autocorrelation analysis. This paper presents a set of models and analytical procedures for spatial cross-correlation analysis. By analogy with Moran’s index newly expressed in a spatial quadratic form, a theoretical framework is deri...
Correlation of iris biometrics and DNA
Harder, Stine; Clemmensen, Line Katrine Harder; Dahl, Anders Bjorholm; Andersen, Jeppe D.; Johansen, Peter; Christoffersen, Susanne R.; Morling, Niels; Borsting, Claus; Paulsen, Rasmus Reinhold
2013-01-01
images: One for iris color and one for iris texture. Both biometrics were high dimensional and a sparse principle component analysis (SPCA) reduced the dimensions and resulted in a representation of data with good interpretability. The correlations between the sparse principal components (SPCs) and the......The presented work concerns prediction of complex human phenotypes from genotypes. We were interested in correlating iris color and texture with DNA. Our data consist of 212 eye images along with DNA: 32 single-nucleotide polymorphisms (SNPs). We used two types of biometrics to describe the eye...... 32 SNPs were found using a canonical correlation analysis (CCA). The result was a single significant canonical correlation (CC) for both biometrics. Each CC comprised two correlated canonical variables, consisting of a linear combination of SPCs and a linear combination of SNPs, respectively. The...
基于规范变量分析的数据重构方法及应用%Data Reconstruction and Application Based on Canonical Variate Analysis
卢娟; 龚晶; 许凤慧
2012-01-01
针对工业系统的数据采集过程中数据遗失的现象,提出并推导了基于规范变量分析的数据重构公式,并与主元分析方法进行遗失数据重构的效果进行了比较。通过对一实际化工吸附分离过程的遗失数据重构,验证了所提方法的有效性和优越性。%According to industrial system of data acquisition process data loss phenomenon,this paper proposed and derived data reconstruction formula based on canonical variate analysis,and with the PCA method for missing data reconstruction results were compared.The effectiveness and superiority of the proposed missing data reconstruction method is proved by an actual chemical adsorption separation process.
Zhu, Xiaofeng; Suk, Heung-Il; Lee, Seong-Whan; Shen, Dinggang
2016-09-01
Fusing information from different imaging modalities is crucial for more accurate identification of the brain state because imaging data of different modalities can provide complementary perspectives on the complex nature of brain disorders. However, most existing fusion methods often extract features independently from each modality, and then simply concatenate them into a long vector for classification, without appropriate consideration of the correlation among modalities. In this paper, we propose a novel method to transform the original features from different modalities to a common space, where the transformed features become comparable and easy to find their relation, by canonical correlation analysis. We then perform the sparse multi-task learning for discriminative feature selection by using the canonical features as regressors and penalizing a loss function with a canonical regularizer. In our experiments on the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset, we use Magnetic Resonance Imaging (MRI) and Positron Emission Tomography (PET) images to jointly predict clinical scores of Alzheimer's Disease Assessment Scale-Cognitive subscale (ADAS-Cog) and Mini-Mental State Examination (MMSE) and also identify multi-class disease status for Alzheimer's disease diagnosis. The experimental results showed that the proposed canonical feature selection method helped enhance the performance of both clinical score prediction and disease status identification, outperforming the state-of-the-art methods. PMID:26254746
WGCNA: an R package for weighted correlation network analysis
Horvath Steve; Langfelder Peter
2008-01-01
Abstract Background Correlation networks are increasingly being used in bioinformatics applications. For example, weighted gene co-expression network analysis is a systems biology method for describing the correlation patterns among genes across microarray samples. Weighted correlation network analysis (WGCNA) can be used for finding clusters (modules) of highly correlated genes, for summarizing such clusters using the module eigengene or an intramodular hub gene, for relating modules to one ...
Firmino José do Nascimento Filho
2012-06-01
Full Text Available Este trabalho teve como objetivo quantificar o grau de asociação entre variáveis de parte aérea e de raízes em mudas clonadas de guaranazeiro, utilizando-se correlações canônicas, a fim de aperfeiçoar o procedimento de seleção de mudas para garantir o aumento da porcentagem de sobrevivência das mudas após o plantio. Foram avaliados dois grupos de variáveis em mudas aptas ao plantio definitivo de 36 clones de guaranazeiro. O delineamento usado foi o aleatorizado em blocos com cinco repetições e 10 plantas por parcela, sob condições de viveiro. Os caracteres avaliados foram submetidos à análise de correlações canônicas. Utilizou-se a análise de correlações canônicas. O grupo de variáveis da parte aérea não se mostrou independente do grupo de variáveis do sistema radicular. Através de seleção baseada em variáveis da parte aérea pode-se melhorar o sistema radicular, principalmente através do maior comprimento do ramo (CRA. A seleção de clones de guaraná para maior peso de raiz pode ser efetuada de forma indireta, realizando-se mensurações do comprimento dos ramos, o que evita a necessidade de se destruir as mudas.This study aimed to quantify the degree of association between variables of shoots and roots system of seedlings cloned from guarana, using canonical correlations, in order to improve the procedure of selection of seedlings to ensure increased survival percentage of seedlings after planting. Two groups of variables suitable for final planting seedlings in 36 guarana clones. The experimental design was a randomized complete block with five replications and 10 plants per plot, under nursery conditions. We used the canonical correlation analysis. The group of variables of shoot is not independent of variable group of root system. Through selection based on variables from the air, you can improve the root system, mainly through the greater length of the branch (CRA. Can practice the selection of clones
Statistical analysis of angular correlation measurements
Obtaining the multipole mixing ratio, δ, of γ transitions in angular correlation measurements is a statistical problem characterized by the small number of angles in which the observation is made and by the limited statistic of counting, α. The inexistence of a sufficient statistics for the estimator of δ, is shown. Three different estimators for δ were constructed and their properties of consistency, bias and efficiency were tested. Tests were also performed in experimental results obtained in γ-γ directional correlation measurements. (Author)
Canonical versus grand canonical treatment of the conservation laws
The differences between the canonical and the grand canoncial treatment of the conservation laws in the relativistic statistical thermodynamics are discussed. The possible implications on the thermodynamics description of hadronic matter created in particle or ion collisions are considered
Correlation and path coefficient analysis in coconut (Cocos nucifera L.)
S. Geethanjali, D. Rajkumar and N.Shoba
2014-01-01
A total of 43 coconut germplasm accessions were characterized for nut yield and fruit component traits. Correlation analysis showed that most of the fruit traits viz., fruit length, fruit breadth, fruit weight, nut weight, kernel weight and copra weight per nut were positively correlated with each other but showed significant negative correlation with the number of nuts produced per palm per annum. Shell thickness and husk thickness were not correlated with any of the fruit component traits. ...
Asymmetric matrices in an analysis of financial correlations
Kwapien, J; Górski, A Z; Oswiecimka, P
2006-01-01
Financial markets are highly correlated systems that reveal both the inter-market dependencies and the correlations among their different components. Standard analyzing techniques include correlation coefficients for pairs of signals and correlation matrices for rich multivariate data. In the latter case one constructs a real symmetric matrix with real non-negative eigenvalues describing the correlation structure of the data. However, if one performs a correlation-function-like analysis of multivariate data, when a stress is put on investigation of delayed dependencies among different types of signals, one can calculate an asymmetric correlation matrix with complex eigenspectrum. From the Random Matrix Theory point of view this kind of matrices is closely related to Ginibre Orthogonal Ensemble (GinOE). We present an example of practical application of such matrices in correlation analyses of empirical data. By introducing the time lag, we are able to identify temporal structure of the inter-market correlation...
Correlation analysis of gamma-ray data with varying sensitivities
A gamma-ray source is defined as a significant excess of the correlated count or the correlated flux over the underlying background. Therefore, the most important information from cross-correlating the raw data for accepting or rejecting a point source as a gamma-ray source is the correlated strength of the source expressed in the correlated counts or the correlated flux and the parent standard deviation of the underlying background. Exact expressions are derived here for the standard deviation of the correlated flux and the parent standard deviation of the underlying background of a gamma-ray excess in a correlation analysis. The advantage of these expressions over the ones previously used is that they are exact and that their derivations do not need the assumption that the sensitivity values for all the sky bins in the matrix over which cross-correlation is done are the same
OPERATIONAL MODAL ANALYSIS SCHEMES USING CORRELATION TECHNIQUE
Zheng Min; Shen Fan; Chen Huaihai
2005-01-01
For some large-scale engineering structures in operating conditions, modal parameters estimation must base itself on response-only data. This problem has received a considerable amount of attention in the past few years. It is well known that the cross-correlation function between the measured responses is a sum of complex exponential functions of the same form as the impulse response function of the original system. So this paper presents a time-domain operating modal identification global scheme and a frequency-domain scheme from output-only by coupling the cross-correlation function with conventional modal parameter estimation. The outlined techniques are applied to an airplane model to estimate modal parameters from response-only data.
THE INTEGRATION OF CAPITAL MARKETS: CORRELATION ANALYSIS
Ioan TRENCA; Eva DEZSI
2010-01-01
The financial theory predicts that gains can be achieved through international portfolio diversification, if the different markets are not correlated. As we can see the level of interaction or independence between markets has an important impact of the investments, in means of risk and return. International portfolio diversification can lead to efficient asset allocation and reduce risk, assets associated with similar levels of risk are anticipated to have similar levels of return in integrat...
Intersubject information mapping: revealing canonical representations of complex natural stimuli
Nikolaus Kriegeskorte
2015-03-01
Full Text Available Real-world time-continuous stimuli such as video promise greater naturalism for studies of brain function. However, modeling the stimulus variation is challenging and introduces a bias in favor of particular descriptive dimensions. Alternatively, we can look for brain regions whose signal is correlated between subjects, essentially using one subject to model another. Intersubject correlation mapping (ICM allows us to find brain regions driven in a canonical manner across subjects by a complex natural stimulus. However, it requires a direct voxel-to-voxel match between the spatiotemporal activity patterns and is thus only sensitive to common activations sufficiently extended to match up in Talairach space (or in an alternative, e.g. cortical-surface-based, common brain space. Here we introduce the more general approach of intersubject information mapping (IIM. For each brain region, IIM determines how much information is shared between the subjects' local spatiotemporal activity patterns. We estimate the intersubject mutual information using canonical correlation analysis applied to voxels within a spherical searchlight centered on each voxel in turn. The intersubject information estimate is invariant to linear transforms including spatial rearrangement of the voxels within the searchlight. This invariance to local encoding will be crucial in exploring fine-grained brain representations, which cannot be matched up in a common space and, more fundamentally, might be unique to each individual – like fingerprints. IIM yields a continuous brain map, which reflects intersubject information in fine-grained patterns. Performed on data from functional magnetic resonance imaging (fMRI of subjects viewing the same television show, IIM and ICM both highlighted sensory representations, including primary visual and auditory cortices. However, IIM revealed additional regions in higher association cortices, namely temporal pole and orbitofrontal cortex. These
Multifractal Height Cross-Correlation Analysis
Krištoufek, Ladislav
Prague: Proffesional publishing, 2011, s. 1-19. ISBN 978-80-7431-058-4. [Mathematical Methods in Economics 2011. Jánska Dolina (SK), 06.09.2011-09.09.2011] R&D Projects: GA ČR GA402/09/0965; GA ČR GD402/09/H045 Grant ostatní: GAUK(CZ) 118310 Institutional research plan: CEZ:AV0Z10750506 Institutional support: RVO:67985556 Keywords : cross-correlations * multifractality * long-range dependence Subject RIV: AH - Economics http://library.utia.cas.cz/separaty/2012/E/kristoufek-0367954.pdf
Thematic mapper studies band correlation analysis
Ungar, S. G.; Kiang, R.
1976-01-01
Spectral data representative of thematic mapper candidate bands 1 and 3 to 7 were obtained by selecting appropriate combinations of bands from the JSC 24 channel multispectral scanner. Of all the bands assigned, only candidate bands 4 (.74 mu to .80 mu) and 5 (.80 mu to .91 mu) showed consistently high intercorrelation from region to region and time to time. This extremely high correlation persisted when looking at the composite data set in a multitemporal, multilocation domain. The GISS investigations lend positive confirmation to the hypothesis, that TM bands 4 and 5 are redundant.
Uncertainty relations, zero point energy and the linear canonical group
Sudarshan, E. C. G.
1993-01-01
The close relationship between the zero point energy, the uncertainty relations, coherent states, squeezed states, and correlated states for one mode is investigated. This group-theoretic perspective enables the parametrization and identification of their multimode generalization. In particular the generalized Schroedinger-Robertson uncertainty relations are analyzed. An elementary method of determining the canonical structure of the generalized correlated states is presented.
Handwriting: Feature Correlation Analysis for Biometric Hashes
Ralf Steinmetz
2004-04-01
Full Text Available In the application domain of electronic commerce, biometric authentication can provide one possible solution for the key management problem. Besides server-based approaches, methods of deriving digital keys directly from biometric measures appear to be advantageous. In this paper, we analyze one of our recently published specific algorithms of this category based on behavioral biometrics of handwriting, the biometric hash. Our interest is to investigate to which degree each of the underlying feature parameters contributes to the overall intrapersonal stability and interpersonal value space. We will briefly discuss related work in feature evaluation and introduce a new methodology based on three components: the intrapersonal scatter (deviation, the interpersonal entropy, and the correlation between both measures. Evaluation of the technique is presented based on two data sets of different size. The method presented will allow determination of effects of parameterization of the biometric system, estimation of value space boundaries, and comparison with other feature selection approaches.
Multifractal cross-correlation analysis in electricity spot market
Fan, Qingju; Li, Dan
2015-07-01
In this paper, we investigate the multiscale cross-correlations between electricity price and trading volume in Czech market based on a newly developed algorithm, called Multifractal Cross-Correlation Analysis (MFCCA). The new algorithm is a natural multifractal generalization of the Detrended Cross-Correlation Analysis (DCCA), and is sensitive to cross-correlation structure and free from limitations of other algorithms. By considering the original sign of the cross-covariance, it allows us to properly quantify and detect the subtle characteristics of two simultaneous recorded time series. First, the multifractality and the long range anti-persistent auto-correlations of price return and trading volume variation are confirmed using Multifractal Detrended Fluctuation Analysis (MF-DFA). Furthermore, we show that there exist long-range anti-persistent cross-correlations between price return and trading volume variation by MFCCA. And we also identify that the cross-correlations disappear on the level of relative small fluctuations. In order to obtain deeper insight into the dynamics of the electricity market, we analyze the relation between generalized Hurst exponent and the multifractal cross-correlation scaling exponent λq. We find that the difference between the generalized Hurst exponent and the multifractal cross-correlation scaling exponent is significantly different for smaller fluctuation, which indicates that the multifractal character of cross-correlations resembles more each other for electricity price and trading volume on the level of large fluctuations and weakens for the smaller ones.
Sparse canonical methods for biological data integration: application to a cross-platform study
Robert-Granié Christèle
2009-01-01
Full Text Available Abstract Background In the context of systems biology, few sparse approaches have been proposed so far to integrate several data sets. It is however an important and fundamental issue that will be widely encountered in post genomic studies, when simultaneously analyzing transcriptomics, proteomics and metabolomics data using different platforms, so as to understand the mutual interactions between the different data sets. In this high dimensional setting, variable selection is crucial to give interpretable results. We focus on a sparse Partial Least Squares approach (sPLS to handle two-block data sets, where the relationship between the two types of variables is known to be symmetric. Sparse PLS has been developed either for a regression or a canonical correlation framework and includes a built-in procedure to select variables while integrating data. To illustrate the canonical mode approach, we analyzed the NCI60 data sets, where two different platforms (cDNA and Affymetrix chips were used to study the transcriptome of sixty cancer cell lines. Results We compare the results obtained with two other sparse or related canonical correlation approaches: CCA with Elastic Net penalization (CCA-EN and Co-Inertia Analysis (CIA. The latter does not include a built-in procedure for variable selection and requires a two-step analysis. We stress the lack of statistical criteria to evaluate canonical correlation methods, which makes biological interpretation absolutely necessary to compare the different gene selections. We also propose comprehensive graphical representations of both samples and variables to facilitate the interpretation of the results. Conclusion sPLS and CCA-EN selected highly relevant genes and complementary findings from the two data sets, which enabled a detailed understanding of the molecular characteristics of several groups of cell lines. These two approaches were found to bring similar results, although they highlighted the same
AN APOLOGY OF THE LITERARY CANON IN A LINGUISTIC STUDY
Alexey Vladimirovich Sosnin
2015-10-01
Full Text Available The article highlights the principles of selecting practical material for a linguistic study aspiring to objectivity and states that in such a study orientation to the literary text is absolutely essential, as a solid corpus of literary texts is indispensable for describing complicated linguistic phenomena and mental structures standing behind them. The article puts forward the postulate that any serious study into the English language should be constructed on the English literary canon – a global textual corpus on the basis of which the greatest part of the educated speakers’ conceptual sphere is formed. At the same time, the article considers certain problems related to the Anglicist’s orientation towards the canon – its definition, limits, central and peripheral authors, the criteria of a literary work canonic status, arguments of those opposing any canonicity in literature, reconstruction of the canon in other cultures. The article also analyzes the cognitive aspect and tells about the key transformation of the English mentality, which gave rise to thinking in the terms of the time, cause-and-effect, and probability in canonic literature. The author of the article comes up with a principal conclusion: orientation to the literary canon in a linguistic study allows reconciling of linguistics and literature studies and including into the analysis nonlinguistic semiotic systems as well as idiolectal systems of conceptualizing the world in literary works.
sample. Referenced to T 0, the canonical XRT light curves well trace the SPL light curves. The T 0's of the canonical light curves in our analysis are usually much larger than the offsets of the known precursors from the main GRBs. If the prior emission hypothesis is real, the X-ray emission is better interpreted within the external shock models based on the spectral and temporal indices of the X-rays. The lack of detection of a jet-like break in most XRT light curves implies that the opening angle of the prior emission jet would be usually large.
Nondestructive Evaluation Correlated with Finite Element Analysis
Abdul-Azid, Ali; Baaklini, George Y.
1999-01-01
Advanced materials are being developed for use in high-temperature gas turbine applications. For these new materials to be fully utilized, their deformation properties, their nondestructive evaluation (NDE) quality and material durability, and their creep and fatigue fracture characteristics need to be determined by suitable experiments. The experimental findings must be analyzed, characterized, modeled and translated into constitutive equations for stress analysis and life prediction. Only when these ingredients - together with the appropriate computational tools - are available, can durability analysis be performed in the design stage, long before the component is built. One of the many structural components being evaluated by the NDE group at the NASA Lewis Research Center is the flywheel system. It is being considered as an energy storage device for advanced space vehicles. Such devices offer advantages over electrochemical batteries in situations demanding high power delivery and high energy storage per unit weight. In addition, flywheels have potentially higher efficiency and longer lifetimes with proper motor-generator and rotor design. Flywheels made of fiber-reinforced polymer composite material show great promise for energy applications because of the high energy and power densities that they can achieve along with a burst failure mode that is relatively benign in comparison to those of flywheels made of metallic materials Therefore, to help improve durability and reduce structural uncertainties, we are developing a comprehensive analytical approach to predict the reliability and life of these components under these harsh loading conditions. The combination of NDE and two- and three-dimensional finite element analyses (e.g., stress analyses and fracture mechanics) is expected to set a standardized procedure to accurately assess the applicability of using various composite materials to design a suitable rotor/flywheel assembly.
On the correlation analysis of electric field inside jet engine
KRISHNA A.; Khattab, T.; Abdelaziz, A.F.; Guizani, M.
2014-01-01
A Simple channel modeling method based on correlation analysis of the electric field inside jet engine is presented. The analysis of the statistical propagation characteristics of electromagnetic field inside harsh jet engine environment is presented by using `Ansys® HFSS'. In this paper, we propose a method to locate the best position for receiving probes inside jet engine with minimum correlation between the receiver points which have strong average electric field. Moreover, a MIMO system c...
CORRELATION AND PATH COEFFICIENT ANALYSIS IN GROUNDNUT (ARACHIS HYPOGAEA L.)
C. Pavan Kumar; R Rekha; O. Venkateswarulu; R P Vasanthi
2014-01-01
Sixty six genotypes of groundnut were used to study the correlation and path analysis for yield and yield contributing characters. Correlation studies revealed that kernel yield was significantly and positively associated with pod yield per plant, number of mature pods per plant, shelling percentage, harvest index, sound mature kernel percentage, specific leaf weight at 60 DAS, protein content and oil content. Path coefficient analysis indicated that pod yield per plant and shelling percentag...
胡麻农艺性状与品质性状的相关性分析%Correlation Analysis Between Agronomic Traits and Quality Traits in Flax
王利民; 党占海; 张建平; 赵利; 党照; 赵玮
2013-01-01
为了研究胡麻主要农艺性状与品质性状间的相互关系，为胡麻品质育种提供理论依据，以256份胡麻品种资源为材料，应用简单相关和典型相关分析方法，对胡麻主要农艺性状和品质性状间的相关性进行了分析。结果表明：胡麻农艺性状和品质性状间存在显著地相关性，通过典型相关分析可以归纳出6对主要典型变量，占两组性状间总相关信息的99.30%，在二者典型相关中起决定作用的主要性状有千粒重、单株果数、单株产量、单株分茎数及含油率、油酸、亚油酸、亚麻酸含量。其中，前3对典型变量所包含的相关信息分别占两组性状间全部相关信息的45.47%、30.53%和13.51%，所凝聚的生物学信息主要是千粒重与含油率、单株果数与油酸及亚麻酸含量、单株分茎数与含油率的相关性，表明千粒重大、单株果数多而分茎数较少的品种含油率及油酸的含量较高。因此，通过农艺性状可以实现对胡麻品质性状的间接选择。%To analyze the correlation between agronomic traits and quality traits in flax and provide scientific basis for flax quality breeding, the simple correlation and canonical correlation analysis was used to study the correlation between agronomic traits and quality traits in 256 flax cultivars. The results showed that, the correlation between agronomic traits and quality traits of flax was extremely significant. Using canonical correlation analysis, 6 pairs of canonical variables were obtained which contained 99.3%of the total correlation information between agronomic and quality traits. The main traits that played a decisive role in canonical correlation were 1000-seeds weight, fruits per plant, plant yield, stems per plant, oil content, oleic acid, linoleic acid and linolenic acid. Among the 6 pairs of canonical variables, the correlation information involved in front 3 pairs of canonical variables were 45
Multiscale Detrended Cross-Correlation Analysis of STOCK Markets
Yin, Yi; Shang, Pengjian
2014-06-01
In this paper, we employ the detrended cross-correlation analysis (DCCA) to investigate the cross-correlations between different stock markets. We report the results of cross-correlated behaviors in US, Chinese and European stock markets in period 1997-2012 by using DCCA method. The DCCA shows the cross-correlated behaviors of intra-regional and inter-regional stock markets in the short and long term which display the similarities and differences of cross-correlated behaviors simply and roughly and the persistence of cross-correlated behaviors of fluctuations. Then, because of the limitation and inapplicability of DCCA method, we propose multiscale detrended cross-correlation analysis (MSDCCA) method to avoid "a priori" selecting the ranges of scales over which two coefficients of the classical DCCA method are identified, and employ MSDCCA to reanalyze these cross-correlations to exhibit some important details such as the existence and position of minimum, maximum and bimodal distribution which are lost if the scale structure is described by two coefficients only and essential differences and similarities in the scale structures of cross-correlation of intra-regional and inter-regional markets. More statistical characteristics of cross-correlation obtained by MSDCCA method help us to understand how two different stock markets influence each other and to analyze the influence from thus two inter-regional markets on the cross-correlation in detail, thus we get a richer and more detailed knowledge of the complex evolutions of dynamics of the cross-correlations between stock markets. The application of MSDCCA is important to promote our understanding of the internal mechanisms and structures of financial markets and helps to forecast the stock indices based on our current results demonstrated the cross-correlations between stock indices. We also discuss the MSDCCA methods of secant rolling window with different sizes and, lastly, provide some relevant implications and
Model independent analysis of nearly L\\'evy correlations
Novák, T; Eggers, H C; de Kock, M
2016-01-01
A model-independent method for the analysis of the two-particle short-range correlations is presented, that can be utilized to describe e.g. Bose-Einstein (HBT), dynamical (ridge) or other correlation functions, that have a nearly L\\'evy or streched exponential shape. For the special case of L\\'evy exponent alpha = 1, the earlier Laguerre expansions are recovered, for the alpha = 2 special case, a new expansion method is obtained for nearly Gaussian correlation functions. Multi-dimensional L\\'evy expansions are also introduced and their potential application to analyze rigde correlation data is discussed.
Multifractal cross-correlation spectra analysis on Chinese stock markets
Zhao, Xiaojun; Shang, Pengjian; Shi, Wenbin
2014-05-01
In this paper, the long-range cross-correlation of Chinese stock indices is systematically studied. The multifractal detrended cross-correlation analysis (MF-DXA) appears to be one of the most effective methods in detecting long-range cross-correlation of two non-stationary variables. The Legendre spectrum and the large deviations spectrum are extended to the cross-correlation case, so as to present multifractal structure of stock return and volatility series. It is characterized of the multifractality in Chinese stock markets, partly due to clusters of local detrended covariance with large and small magnitudes.
Periodicity, the Canon and Sport
Thomas F. Scanlon
2015-10-01
Full Text Available The topic according to this title is admittedly a broad one, embracing two very general concepts of time and of the cultural valuation of artistic products. Both phenomena are, in the present view, largely constructed by their contemporary cultures, and given authority to a great extent from the prestige of the past. The antiquity of tradition brings with it a certain cachet. Even though there may be peripheral debates in any given society which question the specifics of periodization or canonicity, individuals generally accept the consensus designation of a sequence of historical periods and they accept a list of highly valued artistic works as canonical or authoritative. We will first examine some of the processes of periodization and of canon-formation, after which we will discuss some specific examples of how these processes have worked in the sport of two ancient cultures, namely Greece and Mesoamerica.
Analysis and perturbation of degree correlation in complex networks
Xiang, Ju; Hu, Tao; Zhang, Yan
2015-01-01
Degree correlation is an important topological property common to many real-world networks. In this paper, the statistical measures for characterizing the degree correlation in networks are investigated analytically. We give an exact proof of the consistency for the statistical measures, reveal the general linear relation in the degree correlation, which provide a simple and interesting perspective on the analysis of the degree correlation in complex networks. By using the general linear analysis, we investigate the perturbation of the degree correlation in complex networks caused by the addition of few nodes and the rich club. The results show that the assortativity of homogeneous networks such as the ER graphs is easily to be affected strongly by the simple structural changes, while it has only slight variation for heterogeneous networks with broad degree distribution such as the scale-free networks. Clearly, the homogeneous networks are more sensitive for the perturbation than the heterogeneous networks.
Meta-Analysis of Correlations Among Usability Measures
Hornbæk, Kasper Anders Søren; Effie Lai Chong, Law
2007-01-01
Understanding the relation between usability measures seems crucial to deepen our conception of usability and to select the right measures for usability studies. We present a meta-analysis of correlations among usability measures calculated from the raw data of 73 studies. Correlations...... are generally low: effectiveness measures (e.g., errors) and efficiency measures (e.g., time) has a correlation of .247 ± .059 (Pearson's product-moment correlation with 95% confidence interval), efficiency and satisfaction (e.g., preference) one of .196 ± .064, and effectiveness and satisfaction one of .164...... ± .062. Changes in task complexity do not influence these correlations, but use of more complex measures attenuates them. Standard questionnaires for measuring satisfaction appear more reliable than homegrown ones. Measures of users' perceptions of phenomena are generally not correlated with objective...
Existence of log canonical closures
Hacon, Christopher D
2011-01-01
Let $f:X\\to U$ be a projective morphism of normal varieties and $(X,\\Delta)$ a dlt pair. We prove that if there is an open set $U^0\\subset U$, such that $(X,\\Delta)\\times_U U^0$ has a good minimal model over $U^0$ and the images of all the non-klt centers intersect $U^0$, then $(X,\\Delta)$ has a good minimal model over $U$. As consequences we show the existence of log canonical compactifications for open log canonical pairs, and the fact that the moduli functor of stable schemes satisfies the valuative criterion for properness.
Gauge Theory by canonical Transformations
Koenigstein, Adrian; Stoecker, Horst; Struckmeier, Juergen; Vasak, David; Hanauske, Matthias
2016-01-01
Electromagnetism, the strong and the weak interaction are commonly formulated as gauge theories in a Lagrangian description. In this paper we present an alternative formal derivation of U(1)-gauge theory in a manifestly covariant Hamilton formalism. We make use of canonical transformations as our guiding tool to formalize the gauging procedure. The introduction of the gauge field, its transformation behaviour and a dynamical gauge field Lagrangian/Hamiltonian are unavoidable consequences of this formalism, whereas the form of the free gauge Lagrangian/Hamiltonian depends on the selection of the gauge dependence of the canonically conjugate gauge fields.
Case studies in canonical stewardship.
Cafardi, N P; Hite, J
1985-11-01
In facing the challenges that confront Catholic health care today, it is important to know which civil law forms will assist in preserving the Church's ministry. The proper meshing of civil law and canon law thus provides a vehicle to strengthen the apostolate's work. The case studies presented here suggest several means of applying the principles in the new Code of Canon Law to three potentially problematic situations: the merger of a Catholic and non-Catholic hospital, the leasing of a Catholic hospital to an operating company, and the use of the multicorporate format. PMID:10274590
Canonical density matrix perturbation theory.
Niklasson, Anders M N; Cawkwell, M J; Rubensson, Emanuel H; Rudberg, Elias
2015-12-01
Density matrix perturbation theory [Niklasson and Challacombe, Phys. Rev. Lett. 92, 193001 (2004)] is generalized to canonical (NVT) free-energy ensembles in tight-binding, Hartree-Fock, or Kohn-Sham density-functional theory. The canonical density matrix perturbation theory can be used to calculate temperature-dependent response properties from the coupled perturbed self-consistent field equations as in density-functional perturbation theory. The method is well suited to take advantage of sparse matrix algebra to achieve linear scaling complexity in the computational cost as a function of system size for sufficiently large nonmetallic materials and metals at high temperatures. PMID:26764847
Canonical and grand canonical theory of spinodal instabilities
In the context of the mean field approximation to the Landau-Ginzburg-Wilson functional integral, describing the equilibrium properties of a system with a conserved order parameter, the conditions for critical instabilities in the canonical ensemble are analysed. (A.C.A.S.)
Correlation and Path Analysis in Multicut Fodder Sorghum
K. Iyanar, G. Vijayakumar and A.K. Fazllullah Khan.
2010-07-01
Full Text Available Genotypic correlation coefficient and path coefficient analysis was carried out in 109 genotypes of multicut fodder sorghumbetween fourteen fodder yields and yield related characters for each cut and subjected to pooled analysis. The result showedthat all the characters except hydrocyanic acid, total soluble solids and crude protein had positive significant association withgreen fodder yield per plant. Among these traits dry fodder yield exhibited high correlation (0.953 coefficient with greenfodder yield per plant followed by leaf length, plant height and number of leaves. Plant height exerted the highest directeffect on green fodder yield followed by leaf length and breadth and leaf stem ratio. Hence, selection for any of these traitsmight result in simultaneous improvement in the yield. The results of correlation and path analysis indicated that dueimportance should be given for plant height because of its significant correlation and high direct effect, apart from its highindirect effect through dry fodder yield
WGCNA: an R package for weighted correlation network analysis
Horvath Steve
2008-12-01
Full Text Available Abstract Background Correlation networks are increasingly being used in bioinformatics applications. For example, weighted gene co-expression network analysis is a systems biology method for describing the correlation patterns among genes across microarray samples. Weighted correlation network analysis (WGCNA can be used for finding clusters (modules of highly correlated genes, for summarizing such clusters using the module eigengene or an intramodular hub gene, for relating modules to one another and to external sample traits (using eigengene network methodology, and for calculating module membership measures. Correlation networks facilitate network based gene screening methods that can be used to identify candidate biomarkers or therapeutic targets. These methods have been successfully applied in various biological contexts, e.g. cancer, mouse genetics, yeast genetics, and analysis of brain imaging data. While parts of the correlation network methodology have been described in separate publications, there is a need to provide a user-friendly, comprehensive, and consistent software implementation and an accompanying tutorial. Results The WGCNA R software package is a comprehensive collection of R functions for performing various aspects of weighted correlation network analysis. The package includes functions for network construction, module detection, gene selection, calculations of topological properties, data simulation, visualization, and interfacing with external software. Along with the R package we also present R software tutorials. While the methods development was motivated by gene expression data, the underlying data mining approach can be applied to a variety of different settings. Conclusion The WGCNA package provides R functions for weighted correlation network analysis, e.g. co-expression network analysis of gene expression data. The R package along with its source code and additional material are freely available at http://www.genetics.ucla.edu/labs/horvath/CoexpressionNetwork/Rpackages/WGCNA.
Zhu, Xiaofeng; Suk, Heung-Il
2016-01-01
Fusing information from different imaging modalities is crucial for more accurate identification of the brain state because imaging data of different modalities can provide complementary perspectives on the complex nature of brain disorders. However, most existing fusion methods often extract features independently from each modality, and then simply concatenate them into a long vector for classification, without appropriate consideration of the correlation among modalities. In this paper, we propose a novel method to transform the original features from different modalities to a common space, where the transformed features become comparable and easy to find their relation, by canonical correlation analysis. We then perform the sparse multi-task learning for discriminative feature selection by using the canonical features as regressors and penalizing a loss function with a canonical regularizer. In our experiments on the Alzheimer’s Disease Neuroimaging Initiative (ADNI) dataset, we use Magnetic Resonance Imaging (MRI) and Positron Emission Tomography (PET) images to jointly predict clinical scores of Alzheimer’s Disease Assessment Scale-Cognitive subscale (ADAS-Cog) and Mini-Mental State Examination (MMSE) and also identify multi-class disease status for Alzheimer’s disease diagnosis. The experimental results showed that the proposed canonical feature selection method helped enhance the performance of both clinical score prediction and disease status identification, outperforming the state-of-the-art methods. PMID:26254746
ANALYSIS OF COVARIANCE WITH SPATIALLY CORRELATED SECONDARY VARIABLES
Data sets which contain measurements on a spatially referenced response and covariate are analyzed using either co-kriging or spatial analysis of covariance. While co-kriging accounts for the correlation structure of the covariate, it is purely a predictive tool. Alternatively, spatial analysis of c...
Romanticism, Sexuality, and the Canon.
Rowe, Kathleen K.
1990-01-01
Traces the Romanticism in the work and persona of film director Jean-Luc Godard. Examines the contradictions posed by Godard's politics and representations of sexuality. Asserts, that by bringing an ironic distance to the works of such canonized directors, viewers can take pleasure in those works despite their contradictions. (MM)
Interval arithmetic operations for uncertainty analysis with correlated interval variables
Jiang, Chao; Fu, Chun-Ming; Ni, Bing-Yu; Han, Xu
2016-08-01
A new interval arithmetic method is proposed to solve interval functions with correlated intervals through which the overestimation problem existing in interval analysis could be significantly alleviated. The correlation between interval parameters is defined by the multidimensional parallelepiped model which is convenient to describe the correlative and independent interval variables in a unified framework. The original interval variables with correlation are transformed into the standard space without correlation, and then the relationship between the original variables and the standard interval variables is obtained. The expressions of four basic interval arithmetic operations, namely addition, subtraction, multiplication, and division, are given in the standard space. Finally, several numerical examples and a two-step bar are used to demonstrate the effectiveness of the proposed method.
Analysis of genotype-phenotype correlations in human holoprosencephaly.
Solomon, Benjamin D; Mercier, Sandra; Vélez, Jorge I; Pineda-Alvarez, Daniel E; Wyllie, Adrian; Zhou, Nan; Dubourg, Christèle; David, Veronique; Odent, Sylvie; Roessler, Erich; Muenke, Maximilian
2010-02-15
Since the discovery of the first gene causing holoprosencephaly (HPE), over 500 patients with mutations in genes associated with non-chromosomal, non-syndromic HPE have been described, with detailed descriptions available in over 300. Comprehensive clinical analysis of these individuals allows examination for the presence of genotype-phenotype correlations. These correlations allow a degree of differentiation between patients with mutations in different HPE-associated genes and for the application of functional studies to determine intragenic correlations. These early correlations are an important advance in the understanding of the clinical aspects of this disease, and in general argue for continued analysis of the genetic and clinical findings of large cohorts of patients with rare diseases in order to better inform both basic biological insight and care and counseling for affected patients and families. PMID:20104608
Correlation and path coefficient analysis in coconut (Cocos nucifera L.
S. Geethanjali, D. Rajkumar and N.Shoba
2014-12-01
Full Text Available A total of 43 coconut germplasm accessions were characterized for nut yield and fruit component traits. Correlation analysis showed that most of the fruit traits viz., fruit length, fruit breadth, fruit weight, nut weight, kernel weight and copra weight per nut were positively correlated with each other but showed significant negative correlation with the number of nuts produced per palm per annum. Shell thickness and husk thickness were not correlated with any of the fruit component traits. Path analysis revealed that nut yield and copra content per nut had positive direct effect on the total copra yield per palm. The results of this study showed that equal consideration should be given for both nut yield and copra content per nut while selecting elite genotypes for dual purpose viz., tender nut or culinary use and copra for oil extraction.
Correlation and path coefficient analysis in Jatropha curcas L.
Maurya Ramanuj; Kumar Umesh; Katiyar Ratna; Kumar Yadav Hemant
2015-01-01
Correlation and path analysis on 80 diverse accessions of J. curcas showed that seed weight/plant was significantly and positively associated with female flower/plant, male flower/plant, number of flower/plant, number of seed/plant, fruit weight/plant, seed width and negatively associated with oil content. Oil content was negatively and significantly correlated with all the traits studied with strong negative association with female flower/plant followed by...
Analysis of Genotype-Phenotype Correlations in Human Holoprosencephaly
Solomon, Benjamin D.; Mercier, Sandra; Vélez, Jorge I.; Pineda-Alvarez, Daniel E.; Wyllie, Adrian; Zhou, Nan; Dubourg, Christèle; David, Veronique; Odent, Sylvie; Roessler, Erich; Muenke, Maximilian
2010-01-01
Since the discovery of the first gene causing holoprosencephaly (HPE), over 500 patients with mutations in genes associated with non-chromosomal, non-syndromic HPE have been described, with detailed descriptions available in over 300. Comprehensive clinical analysis of these individuals allows examination for the presence of genotype-phenotype correlations. These correlations allow a degree of differentiation between patients with mutations in different HPE-associated genes and for the applic...
A new quantum model for light particle correlation analysis
The study of the light particle correlations allows determining the space-time characteristics of the hot sources produced in heavy ion collisions. The quantum statistical effects (in the case of identical particles) and the final-state interaction (Coulomb and nuclear) are at the origin of the particle correlations. A new quantum model dedicated to the interferometry analysis has been developed at SUBATECH. It provides an original way to take into account the influence of the emitter Coulomb field in two-particle correlation functions. We have shown that the shape is particularly affected for unlike-particle pairs and particles emitted by sources of short lifetimes
Analysis of community structure in networks of correlated data
Gomez, S.; Jensen, P.; Arenas, A.
2008-12-25
We present a reformulation of modularity that allows the analysis of the community structure in networks of correlated data. The new modularity preserves the probabilistic semantics of the original definition even when the network is directed, weighted, signed, and has self-loops. This is the most general condition one can find in the study of any network, in particular those defined from correlated data. We apply our results to a real network of correlated data between stores in the city of Lyon (France).
Basic Canonical Brackets Without Canonical Conjugate Momenta: Supersymmetric Harmonic Oscillator
Shukla, A; Malik, R P
2014-01-01
We exploit the ideas of spin-statistics theorem, normal-ordering and the key concepts behind the symmetry principles to derive the canonical (anti)commutators for the case of a one (0 + 1)-dimensional (1D) supersymmetric (SUSY) harmonic oscillator without taking the help of the mathematical definition of the canonical conjugate momenta with respect to the bosonic and fermionic variables of this toy model for the Hodge theory (where the continuous and discrete symmetries of the theory provide the physical realizations of the de Rham cohomological operators of differential geometry). In our present endeavor, it is the full set of continuous symmetries and their corresponding generators that lead to the derivation of basic (anti)commutators amongst the creation and annihilation operators that appear in the normal mode expansions of the dynamical variables of our theory.
Statistical thermodynamics in relativistic particle and ion physics: Canonical or grand canonical
We consider relativistic statistical thermodynamics of an ideal Boltzmann gas consisting of the particles K, Λ, A, Σ and their antiparticles. Baryon number (B) and strangeness (S) are conserved. While any relativistic gas is necessarily grand canonical with respect to particle numbers, conservation laws can be treated canonically or grand canonically. We construct the partition function for canonical BxS conservation and compare it with the grand canonical one. It is found that the grand canonical partition function is equivalent to a large B approximation of the canonical one. The relative difference between canonical and grand canonical quantities seems to decrease like const/B (two numerical examples) and from this a simple thumb rule for computing canonical quantities from grand canonical ones is guessed. For precise calculations, an integral representation is given. (orig.)
Canonical and non-canonical pathways of osteoclast formation
Knowles, H.J.; Athanasou, N A
2009-01-01
Physiological and pathological bone resorption is mediated by osteoclasts, multinucleated cells which are formed by the fusion of monocyte / macrophage precursors. The canonical pathway of osteoclast formation requires the presence of the receptor activator for NFkB ligand (RANKL) and macrophage colony stimulating factor (M-CSF). Noncanonical pathways of osteoclast formation have been described in which cytokines / growth factors can substitute for RANKL or M-CSF to...
CORRELATION AND PATH COEFFICIENT ANALYSIS IN GROUNDNUT (ARACHIS HYPOGAEA L.
C. Pavan Kumar
2014-02-01
Full Text Available Sixty six genotypes of groundnut were used to study the correlation and path analysis for yield and yield contributing characters. Correlation studies revealed that kernel yield was significantly and positively associated with pod yield per plant, number of mature pods per plant, shelling percentage, harvest index, sound mature kernel percentage, specific leaf weight at 60 DAS, protein content and oil content. Path coefficient analysis indicated that pod yield per plant and shelling percentage had high positive direct effect on kernel yield signifying the importance of these traits in the improvement of seed yield.
Canonical proper time quantum gravitation
Lindesay, James
2015-05-01
At the root of the tensions involved in modeling the quantum dynamics of gravitating systems are the subtleties of quantum locality. Quantum mechanics describes physical phenomena using a theory of non-local phase relationships (non-local in the sense that quantum states maintain a space-like coherence that is acausal). However, the principle of equivalence in general relativity asserts that freely falling frames are locally inertial frames of reference. Thus, gravitating systems are often described using constituents that are freely falling, undergoing geodesic motion defining well localized trajectories. The canonical proper time formulation of relativistic dynamics is particularly useful for describing such inertial constituents using the coordinates of non-inertial observers. The physics of the simplest of gravitating inertial quantum systems, consistent with presented experimental evidence, will be examined. Subsequently, descriptions of both weakly and strongly gravitating quantum systems will be developed using canonical proper gravitation.
Canonical computations of cerebral cortex.
Miller, Kenneth D
2016-04-01
The idea that there is a fundamental cortical circuit that performs canonical computations remains compelling though far from proven. Here we review evidence for two canonical operations within sensory cortical areas: a feedforward computation of selectivity; and a recurrent computation of gain in which, given sufficiently strong external input, perhaps from multiple sources, intracortical input largely, but not completely, cancels this external input. This operation leads to many characteristic cortical nonlinearities in integrating multiple stimuli. The cortical computation must combine such local processing with hierarchical processing across areas. We point to important changes in moving from sensory cortex to motor and frontal cortex and the possibility of substantial differences between cortex in rodents vs. species with columnar organization of selectivity. PMID:26868041
Comparative analysis of heat transfer correlations for forced convection boiling
A critical survey was conducted of the most relevant correlations of boiling heat transfer in forced convection flow. Most of the investigations carried out on partial nucleate boiling and fully developed nucleate boiling have led to the formulation of correlations that are not able to cover a wide range of operating conditions, due to the empirical approach of the problem. A comparative analysis is therefore required in order to delineate the relative accuracy of the proposed correlations, on the basis of the experimental data presently available. The survey performed allows the evaluation of the accuracy of the different calculating procedure; the results obtained, moreover, indicate the most reliable heat transfer correlations for the different operating conditions investigated. This survey was developed for five pressure range (up to 180bar) and for both saturation and subcooled boiling condition
Three Dimensional Canonical Quantum Gravity
Matschull, Hans-Juergen
1995-01-01
General aspects of vielbein representation, ADM formulation and canonical quantization of gravity are reviewed using pure gravity in three dimensions as a toy model. The classical part focusses on the role of observers in general relativity, which will later be identified with quantum observers. A precise definition of gauge symmetries and a classification of inequivalent solutions of Einstein's equations in dreibein formalism is given as well. In the quantum part the construction of the phys...
Pressure-energy correlations in liquids. II. Analysis and consequences
Bailey, Nicholas; Pedersen, Ulf Rørbæk; Gnan, Nicoletta; Schrøder, Thomas; Dyre, J.C.
2008-01-01
We present an analysis and discuss consequences of the strong correlations of the configurational parts of pressure and energy in their equilibrium fluctuations at fixed volume reported for simulations of several liquids in the companion paper [arXiv:0807.0550]. The analysis concentrates specifically on the single-component Lennard-Jones system. We demonstrate that the potential may be replaced, at fixed volume, by an effective power-law, but not because only short distance encounters dominat...
Auto-correlation analysis of ocean surface wind vectors
Abhijit Sarkar; Sujit Basu; A K Varma; Jignesh Kshatriya
2002-09-01
The nature of the inherent temporal variability of surface winds is analyzed by comparison of winds obtained through different measurement methods. In this work, an auto-correlation analysis of a time series data of surface winds measured in situ by a deep water buoy in the Indian Ocean has been carried out. Hourly time series data available for 240 hours in the month of May, 1999 were subjected to an auto-correlation analysis. The analysis indicates an exponential fall of the auto- correlation in the first few hours with a decorrelation time scale of about 6 hours. For a meaningful comparison between satellite derived products and in situ data, satellite data acquired at different time intervals should be used with appropriate `weights', rather than treating the data as concurrent in time. This paper presents a scheme for temporal weighting using the auto-correlation analysis. These temporal `weights' can potentially improve the root mean square (rms) deviation between satellite and in situ measurements. A case study using the TRMM Microwave Imager (TMI) and Indian Ocean buoy wind speed data resulted in an improvement of about 10%.
Correlational Analysis and Interpretation: Graphs Prevent Gaffes. Faculty Forum.
Peden, Blaine F.
2001-01-01
Describes an activity that enables students to exercise their data entry, computational, graphical, and writing skills to learn the importance of graphs in good statistical analysis. Students use four data sets to enter data, compute Pearson correlation values, plot scatter graphs, and write results paragraphs. (CMK)
Derivation of Mayer Series from Canonical Ensemble
Xian-Zhi, Wang
2016-02-01
Mayer derived the Mayer series from both the canonical ensemble and the grand canonical ensemble by use of the cluster expansion method. In 2002, we conjectured a recursion formula of the canonical partition function of a fluid (X.Z. Wang, Phys. Rev. E 66 (2002) 056102). In this paper we give a proof for this formula by developing an appropriate expansion of the integrand of the canonical partition function. We further derive the Mayer series solely from the canonical ensemble by use of this recursion formula.
Superfast robust digital image correlation analysis with parallel computing
Pan, Bing; Tian, Long
2015-03-01
Existing digital image correlation (DIC) using the robust reliability-guided displacement tracking (RGDT) strategy for full-field displacement measurement is a path-dependent process that can only be executed sequentially. This path-dependent tracking strategy not only limits the potential of DIC for further improvement of its computational efficiency but also wastes the parallel computing power of modern computers with multicore processors. To maintain the robustness of the existing RGDT strategy and to overcome its deficiency, an improved RGDT strategy using a two-section tracking scheme is proposed. In the improved RGDT strategy, the calculated points with correlation coefficients higher than a preset threshold are all taken as reliably computed points and given the same priority to extend the correlation analysis to their neighbors. Thus, DIC calculation is first executed in parallel at multiple points by separate independent threads. Then for the few calculated points with correlation coefficients smaller than the threshold, DIC analysis using existing RGDT strategy is adopted. Benefiting from the improved RGDT strategy and the multithread computing, superfast DIC analysis can be accomplished without sacrificing its robustness and accuracy. Experimental results show that the presented parallel DIC method performed on a common eight-core laptop can achieve about a 7 times speedup.
Stock Markets Correlation: before and during the Crisis Analysis
Ioana MOLDOVAN
2011-08-01
Full Text Available The article studies the correlations between the stock markets of the greatest financial centers in the world, namely New York, London and Tokyo, in two different time intervals, namely before the global crisis that erupted in 2007 and during it, in order to determine whether the stock markets correlate more strongly during increasing or decreasing trends. The results of the analysis, carried out by means of multiple regressions, show that the links between the three stock markets were more intense during the crisis, on a decreasing trend respectively, than before the financial turmoil, when the stock indexes had an upward trend.
Analysis of the Correlation between GDP and the Final Consumption
Constantin ANGHELACHE
2011-09-01
Full Text Available This paper presents the results of the researches performed by the author regarding the evolution of Gross Domestic Product. One of the main aspects of GDP analysis is the correlation with the final consumption, an important macroeconomic indicator. The evolution of the Gross Domestic Product is highly influenced by the evolution of the final consumption. To analyze the correlation, the paper proposes the use of the linear regression model, as one of the most appropriate instruments for such scientific approach. The regression model described in the article uses the GDP as resultant variable and the final consumption as factorial variable.
Balint-Kurti, Gabriel G; Vasyutinskii, Oleg S
2009-12-31
A general reactive collision of the type A + B --> C + D is considered where both the collision partners (A and B) or the products (C and D) may possess internal, i.e., spin, orbital or rotational, angular momenta. Compact expressions are derived using a rigorous quantum mechanical analysis for the angular momentum anisotropy of either of the products (C or D) arising from an initially polarized distribution of the reactant angular momentum. The angular momentum distribution of the product is expressed in terms of canonical spherical tensors multiplied by anisotropy-transforming coefficients c(K(i)q(k))(K)(K(r),L). These coefficients act as transformation coefficients between the angular momentum anisotropy of the reactants and that of the product. They are independent of scattering angle but depend on the details of the scattering dynamics. The relationship between the coefficients c(K(i)q(k))(K)(K(r),L) and the body-fixed scattering S matrix is given and the methodology for the quantum mechanical calculation of the anisotropy-transforming coefficients is clearly laid out. The anisotropy-transforming coefficients are amenable to direct experimental measurement in a similar manner to vector correlation and alignment parameters in photodissociation processes. A key aspect of the theory is the use of projections of both reactant and product angular momenta onto the product recoil vector direction. An important new conservation rule is revealed through the analysis, namely that if the state multipole for reactant angular momentum distribution has a projection q(k) onto the product recoil vector the state multipoles for the product angular momentum distribution all have this same projection. Expressions are also presented for the distribution of the product angular momentum when its components are evaluated relative to the space-fixed Z-axis. Notes with detailed derivations of all the formulas are available as Supporting Information. PMID:19642631
Alorizi, Seyed Morteza Emami; Nimruzi, Majid
2016-01-01
Background: Stroke has a huge negative impact on the society and more adversely affect women. There is scarce evidence about any neuroprotective effects of commonly used drug in acute stroke. Bushnell et al. provided a guideline focusing on the risk factors of stroke unique to women, including reproductive factors, metabolic syndrome, obesity, atrial fibrillation, and migraine with aura. The ten variables cited by Avicenna in Canon of Medicine would compensate for the gaps mentioned in this guideline. The prescribed drugs should be selected qualitatively opposite to Mizaj (warm-cold and wet-dry qualities induced by disease state) of the disease and according to ten variables, including the nature of the affected organ, intensity of disease, sex, age, habit, season, place of living, occupation, stamina and physical status. Methods: Information related to stroke was searched in Canon of Medicine, which is an outstanding book in traditional Persian medicine written by Avicenna. Results: A hemorrhagic stroke is the result of increasing sanguine humor in the body. Sanguine has warm-wet quality, and should be treated with food and drugs that quench the abundance of blood in the body. An acute episode of ischemic stroke is due to the abundance of phlegm that causes a blockage in the cerebral vessels. Phlegm has cold-wet quality and treatment should be started with compound medicines that either solve the phlegm or eject it from the body. Conclusion: Avicenna has cited in Canon of Medicine that women have cold and wet temperament compared to men. For this reason, they are more prone to accumulation of phlegm in their body organs including the liver, joints and vessels, and consequently in the risk of fatty liver, degenerative joint disease, atherosclerosis, and stroke especially the ischemic one. This is in accordance with epidemiological studies that showed higher rate of ischemic stroke in women rather than hemorrhagic one. PMID:26722147
Multifractal detrending moving-average cross-correlation analysis
Jiang, Zhi-Qiang; Zhou, Wei-Xing
2011-07-01
There are a number of situations in which several signals are simultaneously recorded in complex systems, which exhibit long-term power-law cross correlations. The multifractal detrended cross-correlation analysis (MFDCCA) approaches can be used to quantify such cross correlations, such as the MFDCCA based on the detrended fluctuation analysis (MFXDFA) method. We develop in this work a class of MFDCCA algorithms based on the detrending moving-average analysis, called MFXDMA. The performances of the proposed MFXDMA algorithms are compared with the MFXDFA method by extensive numerical experiments on pairs of time series generated from bivariate fractional Brownian motions, two-component autoregressive fractionally integrated moving-average processes, and binomial measures, which have theoretical expressions of the multifractal nature. In all cases, the scaling exponents hxy extracted from the MFXDMA and MFXDFA algorithms are very close to the theoretical values. For bivariate fractional Brownian motions, the scaling exponent of the cross correlation is independent of the cross-correlation coefficient between two time series, and the MFXDFA and centered MFXDMA algorithms have comparative performances, which outperform the forward and backward MFXDMA algorithms. For two-component autoregressive fractionally integrated moving-average processes, we also find that the MFXDFA and centered MFXDMA algorithms have comparative performances, while the forward and backward MFXDMA algorithms perform slightly worse. For binomial measures, the forward MFXDMA algorithm exhibits the best performance, the centered MFXDMA algorithms performs worst, and the backward MFXDMA algorithm outperforms the MFXDFA algorithm when the moment order q0. We apply these algorithms to the return time series of two stock market indexes and to their volatilities. For the returns, the centered MFXDMA algorithm gives the best estimates of hxy(q) since its hxy(2) is closest to 0.5, as expected, and the
Dibaryons as canonically quantized biskyrmions
Krupovnickas, T; Riska, D O
2000-01-01
The characteristic feature of the ground state configuration of the Skyrme model description of nuclei is the absence of recognizable individual nucleons. The ground state of the skyrmion with baryon number 2 is axially symmetric, and is well approximated by a simple rational map, which represents a direct generalization of Skyrme's hedgehog ansatz for the nucleon. If the Lagrangian density is canonically quantized this configuration may support excitations that lie close and possible below the threshold for pion decay, and therefore describe dibaryons. The quantum corrections stabilize these solutions, the mass density of which have the correct exponential fall off at large distances.
Canonical metrics on complex manifold
YAU Shing-Tung
2008-01-01
@@ Complex manifolds are topological spaces that are covered by coordinate charts where the Coordinate changes are given by holomorphic transformations. For example, Riemann surfaces are one dimensional complex manifolds. In order to understand complex manifolds, it is useful to introduce metrics that are compatible with the complex structure. In general, we should have a pair (M, ds2M) where ds2M is the metric. The metric is said to be canonical if any biholomorphisms of the complex manifolds are automatically isometries. Such metrics can naturally be used to describe invariants of the complex structures of the manifold.