WorldWideScience

Sample records for correlation analysis

  1. Spectral analysis by correlation

    International Nuclear Information System (INIS)

    Fauque, J.M.; Berthier, D.; Max, J.; Bonnet, G.

    1969-01-01

    The spectral density of a signal, which represents its power distribution along the frequency axis, is a function which is of great importance, finding many uses in all fields concerned with the processing of the signal (process identification, vibrational analysis, etc...). Amongst all the possible methods for calculating this function, the correlation method (correlation function calculation + Fourier transformation) is the most promising, mainly because of its simplicity and of the results it yields. The study carried out here will lead to the construction of an apparatus which, coupled with a correlator, will constitute a set of equipment for spectral analysis in real time covering the frequency range 0 to 5 MHz. (author) [fr

  2. Multiview Bayesian Correlated Component Analysis

    DEFF Research Database (Denmark)

    Kamronn, Simon Due; Poulsen, Andreas Trier; Hansen, Lars Kai

    2015-01-01

    are identical. Here we propose a hierarchical probabilistic model that can infer the level of universality in such multiview data, from completely unrelated representations, corresponding to canonical correlation analysis, to identical representations as in correlated component analysis. This new model, which...... we denote Bayesian correlated component analysis, evaluates favorably against three relevant algorithms in simulated data. A well-established benchmark EEG data set is used to further validate the new model and infer the variability of spatial representations across multiple subjects....

  3. Intermittency analysis of correlated data

    International Nuclear Information System (INIS)

    Wosiek, B.

    1992-01-01

    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)

  4. Generalized canonical correlation analysis with missing values

    NARCIS (Netherlands)

    M. van de Velden (Michel); Y. Takane

    2012-01-01

    textabstractGeneralized canonical correlation analysis is a versatile technique that allows the joint analysis of several sets of data matrices. The generalized canonical correlation analysis solution can be obtained through an eigenequation and distributional assumptions are not required. When

  5. Functional Multiple-Set Canonical Correlation Analysis

    Science.gov (United States)

    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…

  6. Structural Analysis of Covariance and Correlation Matrices.

    Science.gov (United States)

    Joreskog, Karl G.

    1978-01-01

    A general approach to analysis of covariance structures is considered, in which the variances and covariances or correlations of the observed variables are directly expressed in terms of the parameters of interest. The statistical problems of identification, estimation and testing of such covariance or correlation structures are discussed.…

  7. Correlation analysis in chemistry: recent advances

    National Research Council Canada - National Science Library

    Shorter, John; Chapman, Norman Bellamy

    1978-01-01

    ..., and applications of LFER to polycyclic arenes, heterocyclic compounds, and olefinic systems. Of particular interest is the extensive critical compilation of substituent constants and the numerous applications of correlation analysis to spectroscopy...

  8. General correlation and partial correlation analysis in finding interactions: with Spearman rank correlation and proportion correlation as correlation measures

    OpenAIRE

    WenJun Zhang; Xin Li

    2015-01-01

    Between-taxon interactions can be detected by calculating the sampling data of taxon sample type. In present study, Spearman rank correlation and proportion correlation are chosen as the general correlation measures, and their partial correlations are calculated and compared. The results show that for Spearman rank correlation measure, in all predicted candidate direct interactions by partial correlation, about 16.77% (x, 0-45.4%) of them are not successfully detected by Spearman rank correla...

  9. Generalized canonical correlation analysis with missing values

    NARCIS (Netherlands)

    M. van de Velden (Michel); Y. Takane

    2009-01-01

    textabstractTwo new methods for dealing with missing values in generalized canonical correlation analysis are introduced. The first approach, which does not require iterations, is a generalization of the Test Equating method available for principal component analysis. In the second approach,

  10. Detrended cross-correlation analysis of electroencephalogram

    International Nuclear Information System (INIS)

    Wang Jun; Zhao Da-Qing

    2012-01-01

    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)

  11. Multicollinearity in canonical correlation analysis in maize.

    Science.gov (United States)

    Alves, B M; Cargnelutti Filho, A; Burin, C

    2017-03-30

    The objective of this study was to evaluate the effects of multicollinearity under two methods of canonical correlation analysis (with and without elimination of variables) in maize (Zea mays L.) crop. Seventy-six maize genotypes were evaluated in three experiments, conducted in a randomized block design with three replications, during the 2009/2010 crop season. Eleven agronomic variables (number of days from sowing until female flowering, number of days from sowing until male flowering, plant height, ear insertion height, ear placement, number of plants, number of ears, ear index, ear weight, grain yield, and one thousand grain weight), 12 protein-nutritional variables (crude protein, lysine, methionine, cysteine, threonine, tryptophan, valine, isoleucine, leucine, phenylalanine, histidine, and arginine), and 6 energetic-nutritional variables (apparent metabolizable energy, apparent metabolizable energy corrected for nitrogen, ether extract, crude fiber, starch, and amylose) were measured. A phenotypic correlation matrix was first generated among the 29 variables for each of the experiments. A multicollinearity diagnosis was later performed within each group of variables using methodologies such as variance inflation factor and condition number. Canonical correlation analysis was then performed, with and without the elimination of variables, among groups of agronomic and protein-nutritional, and agronomic and energetic-nutritional variables. The canonical correlation analysis in the presence of multicollinearity (without elimination of variables) overestimates the variability of canonical coefficients. The elimination of variables is an efficient method to circumvent multicollinearity in canonical correlation analysis.

  12. Bayesian Correlation Analysis for Sequence Count Data.

    Directory of Open Access Journals (Sweden)

    Daniel Sánchez-Taltavull

    Full Text Available Evaluating the similarity of different measured variables is a fundamental task of statistics, and a key part of many bioinformatics algorithms. Here we propose a Bayesian scheme for estimating the correlation between different entities' measurements based on high-throughput sequencing data. These entities could be different genes or miRNAs whose expression is measured by RNA-seq, different transcription factors or histone marks whose expression is measured by ChIP-seq, or even combinations of different types of entities. Our Bayesian formulation accounts for both measured signal levels and uncertainty in those levels, due to varying sequencing depth in different experiments and to varying absolute levels of individual entities, both of which affect the precision of the measurements. In comparison with a traditional Pearson correlation analysis, we show that our Bayesian correlation analysis retains high correlations when measurement confidence is high, but suppresses correlations when measurement confidence is low-especially for entities with low signal levels. In addition, we consider the influence of priors on the Bayesian correlation estimate. Perhaps surprisingly, we show that naive, uniform priors on entities' signal levels can lead to highly biased correlation estimates, particularly when different experiments have widely varying sequencing depths. However, we propose two alternative priors that provably mitigate this problem. We also prove that, like traditional Pearson correlation, our Bayesian correlation calculation constitutes a kernel in the machine learning sense, and thus can be used as a similarity measure in any kernel-based machine learning algorithm. We demonstrate our approach on two RNA-seq datasets and one miRNA-seq dataset.

  13. Graphology and personality: a correlational analysis

    OpenAIRE

    2008-01-01

    M.A. The title of this dissertation reads as follows: Graphology and Personality: A Correlational Analysis. The aim of this dissertation is to introduce a different projective technique (as of yet not very widely used) into the psychological arena of assessment. Graphology is a projective technique that allows the analyst to delve into the personality of the individual. Very shortly, graphology can be defined as the assessment or analysis of a person’s handwriting. When a child first attem...

  14. International Space Station Future Correlation Analysis Improvements

    Science.gov (United States)

    Laible, Michael R.; Pinnamaneni, Murthy; Sugavanam, Sujatha; Grygier, Michael

    2018-01-01

    Ongoing modal analyses and model correlation are performed on different configurations of the International Space Station (ISS). These analyses utilize on-orbit dynamic measurements collected using four main ISS instrumentation systems: External Wireless Instrumentation System (EWIS), Internal Wireless Instrumentation System (IWIS), Space Acceleration Measurement System (SAMS), and Structural Dynamic Measurement System (SDMS). Remote Sensor Units (RSUs) are network relay stations that acquire flight data from sensors. Measured data is stored in the Remote Sensor Unit (RSU) until it receives a command to download data via RF to the Network Control Unit (NCU). Since each RSU has its own clock, it is necessary to synchronize measurements before analysis. Imprecise synchronization impacts analysis results. A study was performed to evaluate three different synchronization techniques: (i) measurements visually aligned to analytical time-response data using model comparison, (ii) Frequency Domain Decomposition (FDD), and (iii) lag from cross-correlation to align measurements. This paper presents the results of this study.

  15. Gait Correlation Analysis Based Human Identification

    Directory of Open Access Journals (Sweden)

    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.

  16. International Space Station Model Correlation Analysis

    Science.gov (United States)

    Laible, Michael R.; Fitzpatrick, Kristin; Hodge, Jennifer; Grygier, Michael

    2018-01-01

    This paper summarizes the on-orbit structural dynamic data and the related modal analysis, model validation and correlation performed for the International Space Station (ISS) configuration ISS Stage ULF7, 2015 Dedicated Thruster Firing (DTF). The objective of this analysis is to validate and correlate the analytical models used to calculate the ISS internal dynamic loads and compare the 2015 DTF with previous tests. During the ISS configurations under consideration, on-orbit dynamic measurements were collected using the three main ISS instrumentation systems; Internal Wireless Instrumentation System (IWIS), External Wireless Instrumentation System (EWIS) and the Structural Dynamic Measurement System (SDMS). The measurements were recorded during several nominal on-orbit DTF tests on August 18, 2015. Experimental modal analyses were performed on the measured data to extract modal parameters including frequency, damping, and mode shape information. Correlation and comparisons between test and analytical frequencies and mode shapes were performed to assess the accuracy of the analytical models for the configurations under consideration. These mode shapes were also compared to earlier tests. Based on the frequency comparisons, the accuracy of the mathematical models is assessed and model refinement recommendations are given. In particular, results of the first fundamental mode will be discussed, nonlinear results will be shown, and accelerometer placement will be assessed.

  17. System Reliability Analysis Considering Correlation of Performances

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Saekyeol; Lee, Tae Hee [Hanyang Univ., Seoul (Korea, Republic of); Lim, Woochul [Mando Corporation, Seongnam (Korea, Republic of)

    2017-04-15

    Reliability analysis of a mechanical system has been developed in order to consider the uncertainties in the product design that may occur from the tolerance of design variables, uncertainties of noise, environmental factors, and material properties. In most of the previous studies, the reliability was calculated independently for each performance of the system. However, the conventional methods cannot consider the correlation between the performances of the system that may lead to a difference between the reliability of the entire system and the reliability of the individual performance. In this paper, the joint probability density function (PDF) of the performances is modeled using a copula which takes into account the correlation between performances of the system. The system reliability is proposed as the integral of joint PDF of performances and is compared with the individual reliability of each performance by mathematical examples and two-bar truss example.

  18. Metrics correlation and analysis service (MCAS)

    International Nuclear Information System (INIS)

    Baranovski, Andrew; Dykstra, Dave; Garzoglio, Gabriele; Hesselroth, Ted; Mhashilkar, Parag; Levshina, Tanya

    2010-01-01

    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 pool is disorganized, it is 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 loosely coupled or fully decoupled middleware.

  19. Metrics correlation and analysis service (MCAS)

    International Nuclear Information System (INIS)

    Baranovski, Andrew; Dykstra, Dave; Garzoglio, Gabriele; Hesselroth, Ted; Mhashilkar, Parag; Levshina, Tanya

    2009-01-01

    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.

  20. System Reliability Analysis Considering Correlation of Performances

    International Nuclear Information System (INIS)

    Kim, Saekyeol; Lee, Tae Hee; Lim, Woochul

    2017-01-01

    Reliability analysis of a mechanical system has been developed in order to consider the uncertainties in the product design that may occur from the tolerance of design variables, uncertainties of noise, environmental factors, and material properties. In most of the previous studies, the reliability was calculated independently for each performance of the system. However, the conventional methods cannot consider the correlation between the performances of the system that may lead to a difference between the reliability of the entire system and the reliability of the individual performance. In this paper, the joint probability density function (PDF) of the performances is modeled using a copula which takes into account the correlation between performances of the system. The system reliability is proposed as the integral of joint PDF of performances and is compared with the individual reliability of each performance by mathematical examples and two-bar truss example.

  1. Interpreting canonical correlation analysis through biplots of stucture correlations and weights

    NARCIS (Netherlands)

    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

  2. A new methodology of spatial cross-correlation analysis.

    Science.gov (United States)

    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 derived for geographical cross-correlation modeling. First, two sets of spatial cross-correlation coefficients are defined, including a global spatial cross-correlation coefficient and local spatial cross-correlation coefficients. Second, a pair of scatterplots of spatial cross-correlation is proposed, and the plots can be used to visually reveal the causality behind spatial systems. Based on the global cross-correlation coefficient, Pearson's correlation coefficient can be decomposed into two parts: direct correlation (partial correlation) and indirect correlation (spatial cross-correlation). As an example, the methodology is applied to the relationships between China's urbanization and economic development to illustrate how to model spatial cross-correlation phenomena. This study is an introduction to developing the theory of spatial cross-correlation, and future geographical spatial analysis might benefit from these models and indexes.

  3. A New Methodology of Spatial Cross-Correlation Analysis

    Science.gov (United States)

    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 derived for geographical cross-correlation modeling. First, two sets of spatial cross-correlation coefficients are defined, including a global spatial cross-correlation coefficient and local spatial cross-correlation coefficients. Second, a pair of scatterplots of spatial cross-correlation is proposed, and the plots can be used to visually reveal the causality behind spatial systems. Based on the global cross-correlation coefficient, Pearson’s correlation coefficient can be decomposed into two parts: direct correlation (partial correlation) and indirect correlation (spatial cross-correlation). As an example, the methodology is applied to the relationships between China’s urbanization and economic development to illustrate how to model spatial cross-correlation phenomena. This study is an introduction to developing the theory of spatial cross-correlation, and future geographical spatial analysis might benefit from these models and indexes. PMID:25993120

  4. Correlation analysis of fracture arrangement in space

    Science.gov (United States)

    Marrett, Randall; Gale, Julia F. W.; Gómez, Leonel A.; Laubach, Stephen E.

    2018-03-01

    We present new techniques that overcome limitations of standard approaches to documenting spatial arrangement. The new techniques directly quantify spatial arrangement by normalizing to expected values for randomly arranged fractures. The techniques differ in terms of computational intensity, robustness of results, ability to detect anti-correlation, and use of fracture size data. Variation of spatial arrangement across a broad range of length scales facilitates distinguishing clustered and periodic arrangements-opposite forms of organization-from random arrangements. Moreover, self-organized arrangements can be distinguished from arrangements due to extrinsic organization. Traditional techniques for analysis of fracture spacing are hamstrung because they account neither for the sequence of fracture spacings nor for possible coordination between fracture size and position, attributes accounted for by our methods. All of the new techniques reveal fractal clustering in a test case of veins, or cement-filled opening-mode fractures, in Pennsylvanian Marble Falls Limestone. The observed arrangement is readily distinguishable from random and periodic arrangements. Comparison of results that account for fracture size with results that ignore fracture size demonstrates that spatial arrangement is dominated by the sequence of fracture spacings, rather than coordination of fracture size with position. Fracture size and position are not completely independent in this example, however, because large fractures are more clustered than small fractures. Both spatial and size organization of veins here probably emerged from fracture interaction during growth. The new approaches described here, along with freely available software to implement the techniques, can be applied with effect to a wide range of structures, or indeed many other phenomena such as drilling response, where spatial heterogeneity is an issue.

  5. Analysis of Baryon Angular Correlations with Pythia

    CERN Document Server

    Mccune, Amara

    2017-01-01

    Our current understanding of baryon production is encompassed in the framework of the Lund String Fragmentation Model, which is then encoded in the Monte Carlo event generator program Pythia. In proton-proton collisions, daughter particles of the same baryon number produce an anti-correlation in $\\Delta\\eta\\Delta\\varphi$ space in ALICE data, while Pythia programs predict a correlation. To understand this unusual effect, where it comes from, and where our models of baryon production go wrong, correlation functions were systematically generated with Pythia. Effects of energy scaling, color reconnection, and popcorn parameters were investigated.

  6. Statistical analysis of angular correlation measurements

    International Nuclear Information System (INIS)

    Oliveira, R.A.A.M. de.

    1986-01-01

    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) [pt

  7. Uncertainty analysis with statistically correlated failure data

    International Nuclear Information System (INIS)

    Modarres, M.; Dezfuli, H.; Roush, M.L.

    1987-01-01

    Likelihood of occurrence of the top event of a fault tree or sequences of an event tree is estimated from the failure probability of components that constitute the events of the fault/event tree. Component failure probabilities are subject to statistical uncertainties. In addition, there are cases where the failure data are statistically correlated. At present most fault tree calculations are based on uncorrelated component failure data. This chapter describes a methodology for assessing the probability intervals for the top event failure probability of fault trees or frequency of occurrence of event tree sequences when event failure data are statistically correlated. To estimate mean and variance of the top event, a second-order system moment method is presented through Taylor series expansion, which provides an alternative to the normally used Monte Carlo method. For cases where component failure probabilities are statistically correlated, the Taylor expansion terms are treated properly. Moment matching technique is used to obtain the probability distribution function of the top event through fitting the Johnson Ssub(B) distribution. The computer program, CORRELATE, was developed to perform the calculations necessary for the implementation of the method developed. (author)

  8. A hybrid correlation analysis with application to imaging genetics

    Science.gov (United States)

    Hu, Wenxing; Fang, Jian; Calhoun, Vince D.; Wang, Yu-Ping

    2018-03-01

    Investigating the association between brain regions and genes continues to be a challenging topic in imaging genetics. Current brain region of interest (ROI)-gene association studies normally reduce data dimension by averaging the value of voxels in each ROI. This averaging may lead to a loss of information due to the existence of functional sub-regions. Pearson correlation is widely used for association analysis. However, it only detects linear correlation whereas nonlinear correlation may exist among ROIs. In this work, we introduced distance correlation to ROI-gene association analysis, which can detect both linear and nonlinear correlations and overcome the limitation of averaging operations by taking advantage of the information at each voxel. Nevertheless, distance correlation usually has a much lower value than Pearson correlation. To address this problem, we proposed a hybrid correlation analysis approach, by applying canonical correlation analysis (CCA) to the distance covariance matrix instead of directly computing distance correlation. Incorporating CCA into distance correlation approach may be more suitable for complex disease study because it can detect highly associated pairs of ROI and gene groups, and may improve the distance correlation level and statistical power. In addition, we developed a novel nonlinear CCA, called distance kernel CCA, which seeks the optimal combination of features with the most significant dependence. This approach was applied to imaging genetic data from the Philadelphia Neurodevelopmental Cohort (PNC). Experiments showed that our hybrid approach produced more consistent results than conventional CCA across resampling and both the correlation and statistical significance were increased compared to distance correlation analysis. Further gene enrichment analysis and region of interest (ROI) analysis confirmed the associations of the identified genes with brain ROIs. Therefore, our approach provides a powerful tool for finding

  9. Multifractal detrended cross-correlation analysis in the MENA area

    Science.gov (United States)

    El Alaoui, Marwane; Benbachir, Saâd

    2013-12-01

    In this paper, we investigated multifractal cross-correlations qualitatively and quantitatively using a cross-correlation test and the Multifractal detrended cross-correlation analysis method (MF-DCCA) for markets in the MENA area. We used cross-correlation coefficients to measure the level of this correlation. The analysis concerns four stock market indices of Morocco, Tunisia, Egypt and Jordan. The countries chosen are signatory of the Agadir agreement concerning the establishment of a free trade area comprising Arab Mediterranean countries. We computed the bivariate generalized Hurst exponent, Rényi exponent and spectrum of singularity for each pair of indices to measure quantitatively the cross-correlations. By analyzing the results, we found the existence of multifractal cross-correlations between all of these markets. We compared the spectrum width of these indices; we also found which pair of indices has a strong multifractal cross-correlation.

  10. Thematic mapper studies band correlation analysis

    Science.gov (United States)

    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.

  11. Handwriting: Feature Correlation Analysis for Biometric Hashes

    Science.gov (United States)

    Vielhauer, Claus; Steinmetz, Ralf

    2004-12-01

    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.

  12. Handwriting: Feature Correlation Analysis for Biometric Hashes

    Directory of Open Access Journals (Sweden)

    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.

  13. Semiclassical analysis spectral correlations in mesoscopic systems

    International Nuclear Information System (INIS)

    Argaman, N.; Imry, Y.; Smilansky, U.

    1991-07-01

    We consider the recently developed semiclassical analysis of the quantum mechanical spectral form factor, which may be expressed in terms of classically defiable properties. When applied to electrons whose classical behaviour is diffusive, the results of earlier quantum mechanical perturbative derivations, which were developed under a different set of assumptions, are reproduced. The comparison between the two derivations shows that the results depends not on their specific details, but to a large extent on the principle of quantum coherent superposition, and on the generality of the notion of diffusion. The connection with classical properties facilitates application to many physical situations. (author)

  14. Two-dimensional multifractal cross-correlation analysis

    International Nuclear Information System (INIS)

    Xi, Caiping; Zhang, Shuning; Xiong, Gang; Zhao, Huichang; Yang, Yonghong

    2017-01-01

    Highlights: • We study the mathematical models of 2D-MFXPF, 2D-MFXDFA and 2D-MFXDMA. • Present the definition of the two-dimensional N 2 -partitioned multiplicative cascading process. • Do the comparative analysis of 2D-MC by 2D-MFXPF, 2D-MFXDFA and 2D-MFXDMA. • Provide a reference on the choice and parameter settings of these methods in practice. - Abstract: There are a number of situations in which several signals are simultaneously recorded in complex systems, which exhibit long-term power-law cross-correlations. This paper presents two-dimensional multifractal cross-correlation analysis based on the partition function (2D-MFXPF), two-dimensional multifractal cross-correlation analysis based on the detrended fluctuation analysis (2D-MFXDFA) and two-dimensional multifractal cross-correlation analysis based on the detrended moving average analysis (2D-MFXDMA). We apply these methods to pairs of two-dimensional multiplicative cascades (2D-MC) to do a comparative study. Then, we apply the two-dimensional multifractal cross-correlation analysis based on the detrended fluctuation analysis (2D-MFXDFA) to real images and unveil intriguing multifractality in the cross correlations of the material structures. At last, we give the main conclusions and provide a valuable reference on how to choose the multifractal algorithms in the potential applications in the field of SAR image classification and detection.

  15. Psychobiological Correlates of Vaginismus: An Exploratory Analysis.

    Science.gov (United States)

    Maseroli, Elisa; Scavello, Irene; Cipriani, Sarah; Palma, Manuela; Fambrini, Massimiliano; Corona, Giovanni; Mannucci, Edoardo; Maggi, Mario; Vignozzi, Linda

    2017-11-01

    Evidence concerning the determinants of vaginismus (V), in particular medical conditions, is inconclusive. To investigate, in a cohort of subjects consulting for female sexual dysfunction, whether there is a difference in medical and psychosocial parameters between women with V and women with other sexual complaints. A series of 255 women attending our clinic for female sexual dysfunction was consecutively recruited. V was diagnosed according to Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision criteria. Lifelong and acquired V cases were included. Patients underwent a structured interview and physical, gynecologic, laboratory, and clitoral ultrasound examinations; they completed the Female Sexual Function Index (FSFI), the Middlesex Hospital Questionnaire, the Female Sexual Distress Scale-Revised (FSDS), and the Body Uneasiness Test. V was diagnosed in 20 patients (7.8%). Women with V were significantly younger than the rest of the sample (P Vaginismus: An Exploratory Analysis. J Sex Med 2017;14:1392-1402. Copyright © 2017 International Society for Sexual Medicine. Published by Elsevier Inc. All rights reserved.

  16. Parameter Optimization for Selected Correlation Analysis of Intracranial Pathophysiology

    Directory of Open Access Journals (Sweden)

    Rupert Faltermeier

    2015-01-01

    Full Text Available Recently we proposed a mathematical tool set, called selected correlation analysis, that reliably detects positive and negative correlations between arterial blood pressure (ABP and intracranial pressure (ICP. Such correlations are associated with severe impairment of the cerebral autoregulation and intracranial compliance, as predicted by a mathematical model. The time resolved selected correlation analysis is based on a windowing technique combined with Fourier-based coherence calculations and therefore depends on several parameters. For real time application of this method at an ICU it is inevitable to adjust this mathematical tool for high sensitivity and distinct reliability. In this study, we will introduce a method to optimize the parameters of the selected correlation analysis by correlating an index, called selected correlation positive (SCP, with the outcome of the patients represented by the Glasgow Outcome Scale (GOS. For that purpose, the data of twenty-five patients were used to calculate the SCP value for each patient and multitude of feasible parameter sets of the selected correlation analysis. It could be shown that an optimized set of parameters is able to improve the sensitivity of the method by a factor greater than four in comparison to our first analyses.

  17. Nonlinear canonical correlation analysis with k sets of variables

    NARCIS (Netherlands)

    van der Burg, Eeke; de Leeuw, Jan

    1987-01-01

    The multivariate technique OVERALS is introduced as a non-linear generalization of canonical correlation analysis (CCA). First, two sets CCA is introduced. Two sets CCA is a technique that computes linear combinations of sets of variables that correlate in an optimal way. Two sets CCA is then

  18. Ten Years Trend Analysis of Malaria Prevalence and its Correlation ...

    African Journals Online (AJOL)

    The data were analyzed using SPSS software package 16.0. Pearson's correlation analysis was conducted to see the correlation between plasmodium species and climatic variables. Within the last decade (2004–2013) a total of 30,070 blood films were examined for malaria in Sire health center and of this 6036 (20.07%) ...

  19. Parameter Optimization for Selected Correlation Analysis of Intracranial Pathophysiology.

    Science.gov (United States)

    Faltermeier, Rupert; Proescholdt, Martin A; Bele, Sylvia; Brawanski, Alexander

    2015-01-01

    Recently we proposed a mathematical tool set, called selected correlation analysis, that reliably detects positive and negative correlations between arterial blood pressure (ABP) and intracranial pressure (ICP). Such correlations are associated with severe impairment of the cerebral autoregulation and intracranial compliance, as predicted by a mathematical model. The time resolved selected correlation analysis is based on a windowing technique combined with Fourier-based coherence calculations and therefore depends on several parameters. For real time application of this method at an ICU it is inevitable to adjust this mathematical tool for high sensitivity and distinct reliability. In this study, we will introduce a method to optimize the parameters of the selected correlation analysis by correlating an index, called selected correlation positive (SCP), with the outcome of the patients represented by the Glasgow Outcome Scale (GOS). For that purpose, the data of twenty-five patients were used to calculate the SCP value for each patient and multitude of feasible parameter sets of the selected correlation analysis. It could be shown that an optimized set of parameters is able to improve the sensitivity of the method by a factor greater than four in comparison to our first analyses.

  20. Analytic uncertainty and sensitivity analysis of models with input correlations

    Science.gov (United States)

    Zhu, Yueying; Wang, Qiuping A.; Li, Wei; Cai, Xu

    2018-03-01

    Probabilistic uncertainty analysis is a common means of evaluating mathematical models. In mathematical modeling, the uncertainty in input variables is specified through distribution laws. Its contribution to the uncertainty in model response is usually analyzed by assuming that input variables are independent of each other. However, correlated parameters are often happened in practical applications. In the present paper, an analytic method is built for the uncertainty and sensitivity analysis of models in the presence of input correlations. With the method, it is straightforward to identify the importance of the independence and correlations of input variables in determining the model response. This allows one to decide whether or not the input correlations should be considered in practice. Numerical examples suggest the effectiveness and validation of our analytic method in the analysis of general models. A practical application of the method is also proposed to the uncertainty and sensitivity analysis of a deterministic HIV model.

  1. GIS and correlation analysis of geo-environmental variables ...

    African Journals Online (AJOL)

    Key words: Correlation, GIS, malaria geography, malaria incidence ... problems, as it has created the possibility for geocoding, extracting and spatial analysis of health ...... Bulletin of the World Health Organization, 78(12), 1438–1444. Carter ...

  2. Multiscale Detrended Cross-Correlation Analysis of STOCK Markets

    Science.gov (United States)

    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

  3. Meta-Analysis of Correlations Among Usability Measures

    DEFF Research Database (Denmark)

    Hornbæk, Kasper Anders Søren; Effie Lai Chong, Law

    2007-01-01

    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......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...... ± .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...

  4. [Electroencephalogram Feature Selection Based on Correlation Coefficient Analysis].

    Science.gov (United States)

    Zhou, Jinzhi; Tang, Xiaofang

    2015-08-01

    In order to improve the accuracy of classification with small amount of motor imagery training data on the development of brain-computer interface (BCD systems, we proposed an analyzing method to automatically select the characteristic parameters based on correlation coefficient analysis. Throughout the five sample data of dataset IV a from 2005 BCI Competition, we utilized short-time Fourier transform (STFT) and correlation coefficient calculation to reduce the number of primitive electroencephalogram dimension, then introduced feature extraction based on common spatial pattern (CSP) and classified by linear discriminant analysis (LDA). Simulation results showed that the average rate of classification accuracy could be improved by using correlation coefficient feature selection method than those without using this algorithm. Comparing with support vector machine (SVM) optimization features algorithm, the correlation coefficient analysis can lead better selection parameters to improve the accuracy of classification.

  5. WGCNA: an R package for weighted correlation network analysis.

    Science.gov (United States)

    Langfelder, Peter; Horvath, Steve

    2008-12-29

    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. 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. 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.

  6. Correlation analysis of respiratory signals by using parallel coordinate plots.

    Science.gov (United States)

    Saatci, Esra

    2018-01-01

    The understanding of the bonds and the relationships between the respiratory signals, i.e. the airflow, the mouth pressure, the relative temperature and the relative humidity during breathing may provide the improvement on the measurement methods of respiratory mechanics and sensor designs or the exploration of the several possible applications in the analysis of respiratory disorders. Therefore, the main objective of this study was to propose a new combination of methods in order to determine the relationship between respiratory signals as a multidimensional data. In order to reveal the coupling between the processes two very different methods were used: the well-known statistical correlation analysis (i.e. Pearson's correlation and cross-correlation coefficient) and parallel coordinate plots (PCPs). Curve bundling with the number intersections for the correlation analysis, Least Mean Square Time Delay Estimator (LMS-TDE) for the point delay detection and visual metrics for the recognition of the visual structures were proposed and utilized in PCP. The number of intersections was increased when the correlation coefficient changed from high positive to high negative correlation between the respiratory signals, especially if whole breath was processed. LMS-TDE coefficients plotted in PCP indicated well-matched point delay results to the findings in the correlation analysis. Visual inspection of PCB by visual metrics showed range, dispersions, entropy comparisons and linear and sinusoidal-like relationships between the respiratory signals. It is demonstrated that the basic correlation analysis together with the parallel coordinate plots perceptually motivates the visual metrics in the display and thus can be considered as an aid to the user analysis by providing meaningful views of the data. Copyright © 2017 Elsevier B.V. All rights reserved.

  7. Correlation analysis of the Taurus molecular cloud complex

    International Nuclear Information System (INIS)

    Kleiner, S.C.

    1985-01-01

    Autocorrelation and power spectrum methods were applied to the analysis of the density and velocity structure of the Taurus Complex and Heiles Cloud 2 as traced out by 13 CO J = 1 → 0 molecular line observations obtained with the 14m antenna of the Five College Radio Astronomy Observatory. Statistically significant correlations in the spacing of density fluctuations within the Taurus Complex and Heiles 2 were uncovered. The length scales of the observed correlations correspond in magnitude to the Jeans wavelengths characterizing gravitational instabilities with (i) interstellar atomic hydrogen gas for the case of the Taurus complex, and (ii) molecular hydrogen for Heiles 2. The observed correlations may be the signatures of past and current gravitational instabilities frozen into the structure of the molecular gas. The appendices provide a comprehensive description of the analytical and numerical methods developed for the correlation analysis of molecular clouds

  8. Canonical correlation analysis of course and teacher evaluation

    DEFF Research Database (Denmark)

    Sliusarenko, Tamara; Ersbøll, Bjarne Kjær

    2010-01-01

    At the Technical University of Denmark 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. This study investigates the extent to which...... 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...

  9. Analysis of charge-dependent azimuthal correlations with HADES

    Energy Technology Data Exchange (ETDEWEB)

    Kornas, Frederic [TU Darmstadt (Germany); Selyuzhenkov, Ilya [GSI (Germany); Galatyuk, Tetyana [TU Darmstadt (Germany); GSI (Germany); Collaboration: HADES-Collaboration

    2016-07-01

    Charge-dependent azimuthal correlations relative to the reaction plane have been proposed as a probe in the search for the chiral magnetic effect in relativistic heavy-ion collisions. These type of correlations have been measured at the RHIC BES by STAR and at the LHC by ALICE. This contribution discusses two charged particle correlations with respect to the reaction plane measured with high statistic sample of Au+Au collisions at 1.23 AGeV collected by HADES. The Forward wall detector allows to reconstruct the reaction plane using the spectator fragments. The status of the analysis with protons and charged pions will be presented.

  10. Data analytics using canonical correlation analysis and Monte Carlo simulation

    Science.gov (United States)

    Rickman, Jeffrey M.; Wang, Yan; Rollett, Anthony D.; Harmer, Martin P.; Compson, Charles

    2017-07-01

    A canonical correlation analysis is a generic parametric model used in the statistical analysis of data involving interrelated or interdependent input and output variables. It is especially useful in data analytics as a dimensional reduction strategy that simplifies a complex, multidimensional parameter space by identifying a relatively few combinations of variables that are maximally correlated. One shortcoming of the canonical correlation analysis, however, is that it provides only a linear combination of variables that maximizes these correlations. With this in mind, we describe here a versatile, Monte-Carlo based methodology that is useful in identifying non-linear functions of the variables that lead to strong input/output correlations. We demonstrate that our approach leads to a substantial enhancement of correlations, as illustrated by two experimental applications of substantial interest to the materials science community, namely: (1) determining the interdependence of processing and microstructural variables associated with doped polycrystalline aluminas, and (2) relating microstructural decriptors to the electrical and optoelectronic properties of thin-film solar cells based on CuInSe2 absorbers. Finally, we describe how this approach facilitates experimental planning and process control.

  11. Probabilistic leak-before-break analysis with correlated input parameters

    International Nuclear Information System (INIS)

    Qian Guian; Niffenegger, Markus; Karanki, Durga Rao; Li Shuxin

    2013-01-01

    Highlights: ► The correlation of crack growth has the most significant impact on LBB behavior. ► The correlation impact increases with the correlation coefficients. ► The correlation impact increases with the number of cracks. ► Independent assumption may lead to nonconservative result. - Abstract: The paper presents a probabilistic methodology considering the correlations between the input variables for the analysis of leak-before-break (LBB) behavior of a pressure tube. A computer program based on Monte Carlo (MC) simulation with Nataf transformation has been developed to allow the proposed methodology to calculate both the time from the first leakage to unstable fracture and the time from leakage detection to unstable fracture. The results show that the correlation of the crack growth rates between different cracks has the most significant impact on the LBB behavior of the pressure tube. The impact of the parameters correlation on LBB behavior increases with the crack numbers. If the correlations between different parameters for an individual crack are not considered, the predicted results are nonconservative when the cumulative probability is below 50% and conservative when it is above 50%.

  12. Comparative analysis of heat transfer correlations for forced convection boiling

    International Nuclear Information System (INIS)

    Guglielmini, G.; Nannei, E.; Pisoni, C.

    1978-01-01

    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

  13. The Neural Correlates of Moral Thinking: A Meta-Analysis

    OpenAIRE

    Douglas J. Bryant; Wang F; Kelley Deardeuff; Emily Zoccoli; Chang S. Nam

    2016-01-01

    We conducted a meta-analysis to evaluate current research that aims to map the neural correlates of two typical conditions of moral judgment: right-wrong moral judgments and decision-making in moral dilemmas. Utilizing the activation likelihood estimation (ALE) method, we conducted a meta-analysis using neuroimaging data obtained from twenty-one previous studies that measured responses in one or the other of these conditions. We found that across the studies (n = 400), distinct neural circuit...

  14. GIS and correlation analysis of geo-environmental variables ...

    African Journals Online (AJOL)

    GIS and correlation analysis of geo-environmental variables influencing malaria prevalence in the Saboba district of Northern Ghana. ... The study also applied spline interpolation technique to map malaria prevalence in the district using standardised malaria incidence. The result indicates that distance to marshy areas is ...

  15. Variability, correlation and path coefficient analysis of seedling traits ...

    African Journals Online (AJOL)

    Indirect selection is a useful means for improving yield in cotton crop. The objective of the present study was to determine the genetic variability, broad sense heritability, genetic advance and correlation among the six seedling traits and their direct and indirect effects on cotton yield by using path coefficient analysis.

  16. Use of fuel failure correlations in accident analysis

    International Nuclear Information System (INIS)

    O'Dell, L.D.; Baars, R.E.; Waltar, A.E.

    1975-05-01

    The MELT-III code for analysis of a Transient Overpower (TOP) accident in an LMFBR is briefly described, including failure criteria currently applied in the code. Preliminary results of calculations exploring failure patterns in time and space in the reactor core are reported and compared for the two empirical fuel failure correlations employed in the code. (U.S.)

  17. Model-independent analysis with BPM correlation matrices

    International Nuclear Information System (INIS)

    Irwin, J.; Wang, C.X.; Yan, Y.T.; Bane, K.; Cai, Y.; Decker, F.; Minty, M.; Stupakov, G.; Zimmermann, F.

    1998-06-01

    The authors discuss techniques for Model-Independent Analysis (MIA) of a beamline using correlation matrices of physical variables and Singular Value Decomposition (SVD) of a beamline BPM matrix. The beamline matrix is formed from BPM readings for a large number of pulses. The method has been applied to the Linear Accelerator of the SLAC Linear Collider (SLC)

  18. Registration of prone and supine CT colonography scans using correlation optimized warping and canonical correlation analysis

    International Nuclear Information System (INIS)

    Wang Shijun; Yao Jianhua; Liu Jiamin; Petrick, Nicholas; Van Uitert, Robert L.; Periaswamy, Senthil; Summers, Ronald M.

    2009-01-01

    Purpose: In computed tomographic colonography (CTC), a patient will be scanned twice--Once supine and once prone--to improve the sensitivity for polyp detection. To assist radiologists in CTC reading, in this paper we propose an automated method for colon registration from supine and prone CTC scans. Methods: We propose a new colon centerline registration method for prone and supine CTC scans using correlation optimized warping (COW) and canonical correlation analysis (CCA) based on the anatomical structure of the colon. Four anatomical salient points on the colon are first automatically distinguished. Then correlation optimized warping is applied to the segments defined by the anatomical landmarks to improve the global registration based on local correlation of segments. The COW method was modified by embedding canonical correlation analysis to allow multiple features along the colon centerline to be used in our implementation. Results: We tested the COW algorithm on a CTC data set of 39 patients with 39 polyps (19 training and 20 test cases) to verify the effectiveness of the proposed COW registration method. Experimental results on the test set show that the COW method significantly reduces the average estimation error in a polyp location between supine and prone scans by 67.6%, from 46.27±52.97 to 14.98 mm±11.41 mm, compared to the normalized distance along the colon centerline algorithm (p<0.01). Conclusions: The proposed COW algorithm is more accurate for the colon centerline registration compared to the normalized distance along the colon centerline method and the dynamic time warping method. Comparison results showed that the feature combination of z-coordinate and curvature achieved lowest registration error compared to the other feature combinations used by COW. The proposed method is tolerant to centerline errors because anatomical landmarks help prevent the propagation of errors across the entire colon centerline.

  19. Sparse canonical correlation analysis: new formulation and algorithm.

    Science.gov (United States)

    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.

  20. Information-Pooling Bias in Collaborative Security Incident Correlation Analysis.

    Science.gov (United States)

    Rajivan, Prashanth; Cooke, Nancy J

    2018-03-01

    Incident correlation is a vital step in the cybersecurity threat detection process. This article presents research on the effect of group-level information-pooling bias on collaborative incident correlation analysis in a synthetic task environment. Past research has shown that uneven information distribution biases people to share information that is known to most team members and prevents them from sharing any unique information available with them. The effect of such biases on security team collaborations are largely unknown. Thirty 3-person teams performed two threat detection missions involving information sharing and correlating security incidents. Incidents were predistributed to each person in the team based on the hidden profile paradigm. Participant teams, randomly assigned to three experimental groups, used different collaboration aids during Mission 2. Communication analysis revealed that participant teams were 3 times more likely to discuss security incidents commonly known to the majority. Unaided team collaboration was inefficient in finding associations between security incidents uniquely available to each member of the team. Visualizations that augment perceptual processing and recognition memory were found to mitigate the bias. The data suggest that (a) security analyst teams, when conducting collaborative correlation analysis, could be inefficient in pooling unique information from their peers; (b) employing off-the-shelf collaboration tools in cybersecurity defense environments is inadequate; and (c) collaborative security visualization tools developed considering the human cognitive limitations of security analysts is necessary. Potential applications of this research include development of team training procedures and collaboration tool development for security analysts.

  1. Analysis of the Correlation between GDP and the Final Consumption

    Directory of Open Access Journals (Sweden)

    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.

  2. Linear and Nonlinear Multiset Canonical Correlation Analysis (invited talk)

    DEFF Research Database (Denmark)

    Hilger, Klaus Baggesen; Nielsen, Allan Aasbjerg; Larsen, Rasmus

    2002-01-01

    This paper deals with decompositioning of multiset data. Friedman's alternating conditional expectations (ACE) algorithm is extended to handle multiple sets of variables of different mixtures. The new algorithm finds estimates of the optimal transformations of the involved variables that maximize...... 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...

  3. A multimodal stress monitoring system with canonical correlation analysis.

    Science.gov (United States)

    Unsoo Ha; Changhyeon Kim; Yongsu Lee; Hyunki Kim; Taehwan Roh; Hoi-Jun Yoo

    2015-08-01

    The multimodal stress monitoring headband is proposed for mobile stress management system. It is composed of headband and earplugs. Electroencephalography (EEG), hemoencephalography (HEG) and heart-rate variability (HRV) can be achieved simultaneously in the proposed system for user status estimation. With canonical correlation analysis (CCA) and temporal-kernel CCA (tkCCA) algorithm, those different signals can be combined for maximum correlation. Thanks to the proposed combination algorithm, the accuracy of the proposed system increased up to 19 percentage points than unimodal monitoring system in n-back task.

  4. Cross-correlation analysis of Ge/Li/ spectra

    International Nuclear Information System (INIS)

    MacDonald, R.; Robertson, A.; Kennett, T.J.; Prestwich, W.V.

    1974-01-01

    A sensitive technique is proposed for activation analysis using cross-correlation and improved spectral orthogonality achieved through use of a rectangular zero area digital filter. To test the accuracy and reliability of the cross-correlation procedure five spectra obtained with a Ge/Li detector were combined in different proportions. Gaussian distributed statistics were then added to the composite spectra by means of a pseudo-random number generator. The basis spectra used were 76 As, 82 Br, 72 Ga, 77 Ge, and room background. In general, when the basis spectra were combined in roughly comparable proportions the accuracy of the techique proved to be excelent (>1%). However, of primary importance was the ability of the correlation technique to identify low intensity components in the presence of high intensity components. It was found that the detection threshold for Ge, for example, was not reached until the Ge content in the unfiltered spectrum was <0.16%. (T.G.)

  5. Windowed Multitaper Correlation Analysis of Multimodal Brain Monitoring Parameters

    Directory of Open Access Journals (Sweden)

    Rupert Faltermeier

    2015-01-01

    Full Text Available Although multimodal monitoring sets the standard in daily practice of neurocritical care, problem-oriented analysis tools to interpret the huge amount of data are lacking. Recently a mathematical model was presented that simulates the cerebral perfusion and oxygen supply in case of a severe head trauma, predicting the appearance of distinct correlations between arterial blood pressure and intracranial pressure. In this study we present a set of mathematical tools that reliably detect the predicted correlations in data recorded at a neurocritical care unit. The time resolved correlations will be identified by a windowing technique combined with Fourier-based coherence calculations. The phasing of the data is detected by means of Hilbert phase difference within the above mentioned windows. A statistical testing method is introduced that allows tuning the parameters of the windowing method in such a way that a predefined accuracy is reached. With this method the data of fifteen patients were examined in which we found the predicted correlation in each patient. Additionally it could be shown that the occurrence of a distinct correlation parameter, called scp, represents a predictive value of high quality for the patients outcome.

  6. Windowed multitaper correlation analysis of multimodal brain monitoring parameters.

    Science.gov (United States)

    Faltermeier, Rupert; Proescholdt, Martin A; Bele, Sylvia; Brawanski, Alexander

    2015-01-01

    Although multimodal monitoring sets the standard in daily practice of neurocritical care, problem-oriented analysis tools to interpret the huge amount of data are lacking. Recently a mathematical model was presented that simulates the cerebral perfusion and oxygen supply in case of a severe head trauma, predicting the appearance of distinct correlations between arterial blood pressure and intracranial pressure. In this study we present a set of mathematical tools that reliably detect the predicted correlations in data recorded at a neurocritical care unit. The time resolved correlations will be identified by a windowing technique combined with Fourier-based coherence calculations. The phasing of the data is detected by means of Hilbert phase difference within the above mentioned windows. A statistical testing method is introduced that allows tuning the parameters of the windowing method in such a way that a predefined accuracy is reached. With this method the data of fifteen patients were examined in which we found the predicted correlation in each patient. Additionally it could be shown that the occurrence of a distinct correlation parameter, called scp, represents a predictive value of high quality for the patients outcome.

  7. Message Correlation Analysis Tool for NOvA

    CERN Multimedia

    CERN. Geneva

    2012-01-01

    A complex running system, such as the NOvA online data acquisition, consists of a large number of distributed but closely interacting components. This paper describes a generic realtime correlation analysis and event identification engine, named Message Analyzer. Its purpose is to capture run time abnormalities and recognize system failures based on log messages from participating components. The initial design of analysis engine is driven by the DAQ of the NOvA experiment. The Message Analyzer performs filtering and pattern recognition on the log messages and reacts to system failures identified by associated triggering rules. The tool helps the system maintain a healthy running state and to minimize data corruption. This paper also describes a domain specific language that allows the recognition patterns and correlation rules to be specified in a clear and flexible way. In addition, the engine provides a plugin mechanism for users to implement specialized patterns or rules in generic languages such as C++.

  8. Message Correlation Analysis Tool for NOvA

    International Nuclear Information System (INIS)

    Lu Qiming; Biery, Kurt A; Kowalkowski, James B

    2012-01-01

    A complex running system, such as the NOvA online data acquisition, consists of a large number of distributed but closely interacting components. This paper describes a generic real-time correlation analysis and event identification engine, named Message Analyzer. Its purpose is to capture run time abnormalities and recognize system failures based on log messages from participating components. The initial design of analysis engine is driven by the data acquisition (DAQ) of the NOvA experiment. The Message Analyzer performs filtering and pattern recognition on the log messages and reacts to system failures identified by associated triggering rules. The tool helps the system maintain a healthy running state and to minimize data corruption. This paper also describes a domain specific language that allows the recognition patterns and correlation rules to be specified in a clear and flexible way. In addition, the engine provides a plugin mechanism for users to implement specialized patterns or rules in generic languages such as C++.

  9. Message correlation analysis tool for NOvA

    Energy Technology Data Exchange (ETDEWEB)

    Lu, Qiming [Fermilab; Biery, Kurt A. [Fermilab; Kowalkowski, James B. [Fermilab

    2012-01-01

    A complex running system, such as the NOvA online data acquisition, consists of a large number of distributed but closely interacting components. This paper describes a generic real-time correlation analysis and event identification engine, named Message Analyzer. Its purpose is to capture run time abnormalities and recognize system failures based on log messages from participating components. The initial design of analysis engine is driven by the data acquisition (DAQ) of the NOvA experiment. The Message Analyzer performs filtering and pattern recognition on the log messages and reacts to system failures identified by associated triggering rules. The tool helps the system maintain a healthy running state and to minimize data corruption. This paper also describes a domain specific language that allows the recognition patterns and correlation rules to be specified in a clear and flexible way. In addition, the engine provides a plugin mechanism for users to implement specialized patterns or rules in generic languages such as C++.

  10. Analysis of Cell Phone Usage Using Correlation Techniques

    OpenAIRE

    T S R MURTHY; D. SIVA RAMA KRISHNA

    2011-01-01

    The present paper is a sample survey analysis, examined based on correlation techniques. The usage ofmobile phones is clearly almost un-avoidable these days and as such the authors have made a systematicsurvey through a well prepared questionnaire on making use of mobile phones to the maximum extent.These samples are various economical groups across a population of over one-lakh people. The resultsare scientifically categorized and interpreted to match the ground reality.

  11. Signal correlations in biomass combustion. An information theoretic analysis

    Energy Technology Data Exchange (ETDEWEB)

    Ruusunen, M.

    2013-09-01

    Increasing environmental and economic awareness are driving the development of combustion technologies to efficient biomass use and clean burning. To accomplish these goals, quantitative information about combustion variables is needed. However, for small-scale combustion units the existing monitoring methods are often expensive or complex. This study aimed to quantify correlations between flue gas temperatures and combustion variables, namely typical emission components, heat output, and efficiency. For this, data acquired from four small-scale combustion units and a large circulating fluidised bed boiler was studied. The fuel range varied from wood logs, wood chips, and wood pellets to biomass residue. Original signals and a defined set of their mathematical transformations were applied to data analysis. In order to evaluate the strength of the correlations, a multivariate distance measure based on information theory was derived. The analysis further assessed time-varying signal correlations and relative time delays. Ranking of the analysis results was based on the distance measure. The uniformity of the correlations in the different data sets was studied by comparing the 10-quantiles of the measured signal. The method was validated with two benchmark data sets. The flue gas temperatures and the combustion variables measured carried similar information. The strongest correlations were mainly linear with the transformed signal combinations and explicable by the combustion theory. Remarkably, the results showed uniformity of the correlations across the data sets with several signal transformations. This was also indicated by simulations using a linear model with constant structure to monitor carbon dioxide in flue gas. Acceptable performance was observed according to three validation criteria used to quantify modelling error in each data set. In general, the findings demonstrate that the presented signal transformations enable real-time approximation of the studied

  12. Analysis of input variables of an artificial neural network using bivariate correlation and canonical correlation

    International Nuclear Information System (INIS)

    Costa, Valter Magalhaes

    2011-01-01

    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 using neural networks. (author)

  13. Correlative SEM SERS for quantitative analysis of dimer nanoparticles.

    Science.gov (United States)

    Timmermans, F J; Lenferink, A T M; van Wolferen, H A G M; Otto, C

    2016-11-14

    A Raman microscope integrated with a scanning electron microscope was used to investigate plasmonic structures by correlative SEM-SERS analysis. The integrated Raman-SEM microscope combines high-resolution electron microscopy information with SERS signal enhancement from selected nanostructures with adsorbed Raman reporter molecules. Correlative analysis is performed for dimers of two gold nanospheres. Dimers were selected on the basis of SEM images from multi aggregate samples. The effect of the orientation of the dimer with respect to the polarization state of the laser light and the effect of the particle gap size on the Raman signal intensity is observed. Additionally, calculations are performed to simulate the electric near field enhancement. These simulations are based on the morphologies observed by electron microscopy. In this way the experiments are compared with the enhancement factor calculated with near field simulations and are subsequently used to quantify the SERS enhancement factor. Large differences between experimentally observed and calculated enhancement factors are regularly detected, a phenomenon caused by nanoscale differences between the real and 'simplified' simulated structures. Quantitative SERS experiments reveal the structure induced enhancement factor, ranging from ∼200 to ∼20 000, averaged over the full nanostructure surface. The results demonstrate correlative Raman-SEM microscopy for the quantitative analysis of plasmonic particles and structures, thus enabling a new analytical method in the field of SERS and plasmonics.

  14. Process correlation analysis model for process improvement identification.

    Science.gov (United States)

    Choi, Su-jin; Kim, Dae-Kyoo; Park, Sooyong

    2014-01-01

    Software process improvement aims at improving the development process of software systems. It is initiated by process assessment identifying strengths and weaknesses and based on the findings, improvement plans are developed. In general, a process reference model (e.g., CMMI) is used throughout the process of software process improvement as the base. CMMI defines a set of process areas involved in software development and what to be carried out in process areas in terms of goals and practices. Process areas and their elements (goals and practices) are often correlated due to the iterative nature of software development process. However, in the current practice, correlations of process elements are often overlooked in the development of an improvement plan, which diminishes the efficiency of the plan. This is mainly attributed to significant efforts and the lack of required expertise. In this paper, we present a process correlation analysis model that helps identify correlations of process elements from the results of process assessment. This model is defined based on CMMI and empirical data of improvement practices. We evaluate the model using industrial data.

  15. Correlation analysis between ceramic insulator pollution and acoustic emissions

    Directory of Open Access Journals (Sweden)

    Benjamín Álvarez-Nasrallah

    2015-01-01

    Full Text Available Most of the studies related to insulator pollution are normally performed based on individual analysis among leakage current, relative humidity and equivalent salt deposit density (ESDD. This paper presents a correlation analysis between the leakage current and the acoustic emissions measured in a 230 kV electrical substations in the city of Barranquilla, Colombia. Furthermore, atmospheric variables were considered to develop a characterization model of the insulator contamination process. This model was used to demonstrate that noise emission levels are a reliable indicator to detect and characterize pollution on high voltage insulators. The correlation found amount the atmospheric, electrical and sound variables allowed to determine the relations for the maintenance of ceramic insulators in high-polluted areas. In this article, the results on the behavior of the leakage current in ceramic insulators and the sound produced with different atmospheric conditions are shown, which allow evaluating the best time to clean the insulator at the substation. Furthermore, by experimentation on site and using statistical models, the correlation between ambient variables and the leakage current of insulators in an electrical substation was obtained. Some of the problems that bring the external noise were overcome using multiple microphones and specialized software that enabled properly filter the sound and better measure the variables.

  16. Group sparse canonical correlation analysis for genomic data integration.

    Science.gov (United States)

    Lin, Dongdong; Zhang, Jigang; Li, Jingyao; Calhoun, Vince D; Deng, Hong-Wen; Wang, Yu-Ping

    2013-08-12

    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, canonical correlation analysis (CCA) method for this problem. Conventional CCA method does not work effectively if the number of data samples is significantly less than that of biomarkers, which is a typical case for genomic data (e.g., SNPs). Sparse CCA (sCCA) methods were introduced to overcome such difficulty, mostly using penalizations with l-1 norm (CCA-l1) or the combination of l-1and l-2 norm (CCA-elastic net). However, they overlook the structural or group effect within genomic data in the analysis, which often exist and are important (e.g., SNPs spanning a gene interact and work together as a group). We propose a new group sparse CCA method (CCA-sparse group) along with an effective numerical algorithm to study the mutual relationship between two different types of genomic data (i.e., SNP and gene expression). We then extend the model to a more general formulation that can include the existing sCCA models. We apply the model to feature/variable selection from two data sets and compare our group sparse CCA method with existing sCCA methods on both simulation and two real datasets (human gliomas data and NCI60 data). We use a graphical representation of the samples with a pair of canonical variates to demonstrate the discriminating characteristic of the selected features. Pathway analysis is further performed for biological interpretation of those features. The CCA-sparse group method incorporates group effects of features into the correlation analysis while performs individual feature

  17. Correlation analysis of the physiological factors controlling fundamental voice frequency.

    Science.gov (United States)

    Atkinson, J E

    1978-01-01

    A technique has been developed to obtain a quantitative measure of correlation between electromyographic (EMG) activity of various laryngeal muscles, subglottal air pressure, and the fundamental frequency of vibration of the vocal folds (Fo). Data were collected and analyzed on one subject, a native speaker of American English. The results show that an analysis of this type can provide a useful measure of correlation between the physiological and acoustical events in speech and, furthermore, can yield detailed insights into the organization and nature of the speech production process. In particular, based on these results, a model is suggested of Fo control involving laryngeal state functions that seems to agree with present knowledge of laryngeal control and experimental evidence.

  18. On discriminant analysis techniques and correlation structures in high dimensions

    DEFF Research Database (Denmark)

    Clemmensen, Line Katrine Harder

    This paper compares several recently proposed techniques for performing discriminant analysis in high dimensions, and illustrates that the various sparse methods dier in prediction abilities depending on their underlying assumptions about the correlation structures in the data. The techniques...... the methods in two: Those who assume independence between the variables and thus use a diagonal estimate of the within-class covariance matrix, and those who assume dependence between the variables and thus use an estimate of the within-class covariance matrix, which also estimates the correlations between...... variables. The two groups of methods are compared and the pros and cons are exemplied using dierent cases of simulated data. The results illustrate that the estimate of the covariance matrix is an important factor with respect to choice of method, and the choice of method should thus be driven by the nature...

  19. Long-range correlation analysis of urban traffic data

    International Nuclear Information System (INIS)

    Peng, Sheng; Jun-Feng, Wang; Shu-Long, Zhao; Tie-Qiao, Tang

    2010-01-01

    This paper investigates urban traffic data by analysing the long-range correlation with detrended fluctuation analysis. Through a large number of real data collected by the travel time detection system in Beijing, the variation of flow in different time periods and intersections is studied. According to the long-range correlation in different time scales, it mainly discusses the effect of intersection location in road net, people activity customs and special traffic controls on urban traffic flow. As demonstrated by the obtained results, the urban traffic flow represents three-phase characters similar to highway traffic. Moreover, compared by the two groups of data obtained before and after the special traffic restrictions (vehicles with special numbered plates only run in a special workday) enforcement, it indicates that the rules not only reduce the flow but also avoid irregular fluctuation. (general)

  20. Analysis of input variables of an artificial neural network using bivariate correlation and canonical correlation

    Energy Technology Data Exchange (ETDEWEB)

    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)

  1. Analysis of input variables of an artificial neural network using bivariate correlation and canonical correlation

    International Nuclear Information System (INIS)

    Costa, Valter Magalhaes; Pereira, Iraci Martinez

    2011-01-01

    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)

  2. Protein structure similarity from principle component correlation analysis

    Directory of Open Access Journals (Sweden)

    Chou James

    2006-01-01

    Full Text Available Abstract Background Owing to rapid expansion of protein structure databases in recent years, methods of structure comparison are becoming increasingly effective and important in revealing novel information on functional properties of proteins and their roles in the grand scheme of evolutionary biology. Currently, the structural similarity between two proteins is measured by the root-mean-square-deviation (RMSD in their best-superimposed atomic coordinates. RMSD is the golden rule of measuring structural similarity when the structures are nearly identical; it, however, fails to detect the higher order topological similarities in proteins evolved into different shapes. We propose new algorithms for extracting geometrical invariants of proteins that can be effectively used to identify homologous protein structures or topologies in order to quantify both close and remote structural similarities. Results We measure structural similarity between proteins by correlating the principle components of their secondary structure interaction matrix. In our approach, the Principle Component Correlation (PCC analysis, a symmetric interaction matrix for a protein structure is constructed with relationship parameters between secondary elements that can take the form of distance, orientation, or other relevant structural invariants. When using a distance-based construction in the presence or absence of encoded N to C terminal sense, there are strong correlations between the principle components of interaction matrices of structurally or topologically similar proteins. Conclusion The PCC method is extensively tested for protein structures that belong to the same topological class but are significantly different by RMSD measure. The PCC analysis can also differentiate proteins having similar shapes but different topological arrangements. Additionally, we demonstrate that when using two independently defined interaction matrices, comparison of their maximum

  3. Spatial Distribution Characteristics of Healthcare Facilities in Nanjing: Network Point Pattern Analysis and Correlation Analysis

    Directory of Open Access Journals (Sweden)

    Jianhua Ni

    2016-08-01

    Full Text Available The spatial distribution of urban service facilities is largely constrained by the road network. In this study, network point pattern analysis and correlation analysis were used to analyze the relationship between road network and healthcare facility distribution. The weighted network kernel density estimation method proposed in this study identifies significant differences between the outside and inside areas of the Ming city wall. The results of network K-function analysis show that private hospitals are more evenly distributed than public hospitals, and pharmacy stores tend to cluster around hospitals along the road network. After computing the correlation analysis between different categorized hospitals and street centrality, we find that the distribution of these hospitals correlates highly with the street centralities, and that the correlations are higher with private and small hospitals than with public and large hospitals. The comprehensive analysis results could help examine the reasonability of existing urban healthcare facility distribution and optimize the location of new healthcare facilities.

  4. Partial correlation analysis method in ultrarelativistic heavy-ion collisions

    Science.gov (United States)

    Olszewski, Adam; Broniowski, Wojciech

    2017-11-01

    We argue that statistical data analysis of two-particle longitudinal correlations in ultrarelativistic heavy-ion collisions may be efficiently carried out with the technique of partial covariance. In this method, the spurious event-by-event fluctuations due to imprecise centrality determination are eliminated via projecting out the component of the covariance influenced by the centrality fluctuations. We bring up the relationship of the partial covariance to the conditional covariance. Importantly, in the superposition approach, where hadrons are produced independently from a collection of sources, the framework allows us to impose centrality constraints on the number of sources rather than hadrons, that way unfolding of the trivial fluctuations from statistical hadronization and focusing better on the initial-state physics. We show, using simulated data from hydrodynamics followed with statistical hadronization, that the technique is practical and very simple to use, giving insight into the correlations generated in the initial stage. We also discuss the issues related to separation of the short- and long-range components of the correlation functions and show that in our example the short-range component from the resonance decays is largely reduced by considering pions of the same sign. We demonstrate the method explicitly on the cases where centrality is determined with a single central control bin or with two peripheral control bins.

  5. Automated modal parameter estimation using correlation analysis and bootstrap sampling

    Science.gov (United States)

    Yaghoubi, Vahid; Vakilzadeh, Majid K.; Abrahamsson, Thomas J. S.

    2018-02-01

    The estimation of modal parameters from a set of noisy measured data is a highly judgmental task, with user expertise playing a significant role in distinguishing between estimated physical and noise modes of a test-piece. Various methods have been developed to automate this procedure. The common approach is to identify models with different orders and cluster similar modes together. However, most proposed methods based on this approach suffer from high-dimensional optimization problems in either the estimation or clustering step. To overcome this problem, this study presents an algorithm for autonomous modal parameter estimation in which the only required optimization is performed in a three-dimensional space. To this end, a subspace-based identification method is employed for the estimation and a non-iterative correlation-based method is used for the clustering. This clustering is at the heart of the paper. The keys to success are correlation metrics that are able to treat the problems of spatial eigenvector aliasing and nonunique eigenvectors of coalescent modes simultaneously. The algorithm commences by the identification of an excessively high-order model from frequency response function test data. The high number of modes of this model provides bases for two subspaces: one for likely physical modes of the tested system and one for its complement dubbed the subspace of noise modes. By employing the bootstrap resampling technique, several subsets are generated from the same basic dataset and for each of them a model is identified to form a set of models. Then, by correlation analysis with the two aforementioned subspaces, highly correlated modes of these models which appear repeatedly are clustered together and the noise modes are collected in a so-called Trashbox cluster. Stray noise modes attracted to the mode clusters are trimmed away in a second step by correlation analysis. The final step of the algorithm is a fuzzy c-means clustering procedure applied to

  6. Nanoscale protein diffusion by STED-based pair correlation analysis.

    Directory of Open Access Journals (Sweden)

    Paolo Bianchini

    Full Text Available We describe for the first time the combination between cross-pair correlation function analysis (pair correlation analysis or pCF and stimulated emission depletion (STED to obtain diffusion maps at spatial resolution below the optical diffraction limit (super-resolution. Our approach was tested in systems characterized by high and low signal to noise ratio, i.e. Capsid Like Particles (CLPs bearing several (>100 active fluorescent proteins and monomeric fluorescent proteins transiently expressed in living Chinese Hamster Ovary cells, respectively. The latter system represents the usual condition encountered in living cell studies on fluorescent protein chimeras. Spatial resolution of STED-pCF was found to be about 110 nm, with a more than twofold improvement over conventional confocal acquisition. We successfully applied our method to highlight how the proximity to nuclear envelope affects the mobility features of proteins actively imported into the nucleus in living cells. Remarkably, STED-pCF unveiled the existence of local barriers to diffusion as well as the presence of a slow component at distances up to 500-700 nm from either sides of nuclear envelope. The mobility of this component is similar to that previously described for transport complexes. Remarkably, all these features were invisible in conventional confocal mode.

  7. Scalable and Flexible Multiview MAX-VAR Canonical Correlation Analysis

    Science.gov (United States)

    Fu, Xiao; Huang, Kejun; Hong, Mingyi; Sidiropoulos, Nicholas D.; So, Anthony Man-Cho

    2017-08-01

    Generalized canonical correlation analysis (GCCA) aims at finding latent low-dimensional common structure from multiple views (feature vectors in different domains) of the same entities. Unlike principal component analysis (PCA) that handles a single view, (G)CCA is able to integrate information from different feature spaces. Here we focus on MAX-VAR GCCA, a popular formulation which has recently gained renewed interest in multilingual processing and speech modeling. The classic MAX-VAR GCCA problem can be solved optimally via eigen-decomposition of a matrix that compounds the (whitened) correlation matrices of the views; but this solution has serious scalability issues, and is not directly amenable to incorporating pertinent structural constraints such as non-negativity and sparsity on the canonical components. We posit regularized MAX-VAR GCCA as a non-convex optimization problem and propose an alternating optimization (AO)-based algorithm to handle it. Our algorithm alternates between {\\em inexact} solutions of a regularized least squares subproblem and a manifold-constrained non-convex subproblem, thereby achieving substantial memory and computational savings. An important benefit of our design is that it can easily handle structure-promoting regularization. We show that the algorithm globally converges to a critical point at a sublinear rate, and approaches a global optimal solution at a linear rate when no regularization is considered. Judiciously designed simulations and large-scale word embedding tasks are employed to showcase the effectiveness of the proposed algorithm.

  8. Linearized spectrum correlation analysis for line emission measurements.

    Science.gov (United States)

    Nishizawa, T; Nornberg, M D; Den Hartog, D J; Sarff, J S

    2017-08-01

    A new spectral analysis method, Linearized Spectrum Correlation Analysis (LSCA), for charge exchange and passive ion Doppler spectroscopy is introduced to provide a means of measuring fast spectral line shape changes associated with ion-scale micro-instabilities. This analysis method is designed to resolve the fluctuations in the emission line shape from a stationary ion-scale wave. The method linearizes the fluctuations around a time-averaged line shape (e.g., Gaussian) and subdivides the spectral output channels into two sets to reduce contributions from uncorrelated fluctuations without averaging over the fast time dynamics. In principle, small fluctuations in the parameters used for a line shape model can be measured by evaluating the cross spectrum between different channel groupings to isolate a particular fluctuating quantity. High-frequency ion velocity measurements (100-200 kHz) were made by using this method. We also conducted simulations to compare LSCA with a moment analysis technique under a low photon count condition. Both experimental and synthetic measurements demonstrate the effectiveness of LSCA.

  9. Principal Component Analysis Based Two-Dimensional (PCA-2D) Correlation Spectroscopy: PCA Denoising for 2D Correlation Spectroscopy

    International Nuclear Information System (INIS)

    Jung, Young Mee

    2003-01-01

    Principal component analysis based two-dimensional (PCA-2D) correlation analysis is applied to FTIR spectra of polystyrene/methyl ethyl ketone/toluene solution mixture during the solvent evaporation. Substantial amount of artificial noise were added to the experimental data to demonstrate the practical noise-suppressing benefit of PCA-2D technique. 2D correlation analysis of the reconstructed data matrix from PCA loading vectors and scores successfully extracted only the most important features of synchronicity and asynchronicity without interference from noise or insignificant minor components. 2D correlation spectra constructed with only one principal component yield strictly synchronous response with no discernible a asynchronous features, while those involving at least two or more principal components generated meaningful asynchronous 2D correlation spectra. Deliberate manipulation of the rank of the reconstructed data matrix, by choosing the appropriate number and type of PCs, yields potentially more refined 2D correlation spectra

  10. Comparison of correlation analysis techniques for irregularly sampled time series

    Directory of Open Access Journals (Sweden)

    K. Rehfeld

    2011-06-01

    Full Text Available Geoscientific measurements often provide time series with irregular time sampling, requiring either data reconstruction (interpolation or sophisticated methods to handle irregular sampling. We compare the linear interpolation technique and different approaches for analyzing the correlation functions and persistence of irregularly sampled time series, as Lomb-Scargle Fourier transformation and kernel-based methods. In a thorough benchmark test we investigate the performance of these techniques.

    All methods have comparable root mean square errors (RMSEs for low skewness of the inter-observation time distribution. For high skewness, very irregular data, interpolation bias and RMSE increase strongly. We find a 40 % lower RMSE for the lag-1 autocorrelation function (ACF for the Gaussian kernel method vs. the linear interpolation scheme,in the analysis of highly irregular time series. For the cross correlation function (CCF the RMSE is then lower by 60 %. The application of the Lomb-Scargle technique gave results comparable to the kernel methods for the univariate, but poorer results in the bivariate case. Especially the high-frequency components of the signal, where classical methods show a strong bias in ACF and CCF magnitude, are preserved when using the kernel methods.

    We illustrate the performances of interpolation vs. Gaussian kernel method by applying both to paleo-data from four locations, reflecting late Holocene Asian monsoon variability as derived from speleothem δ18O measurements. Cross correlation results are similar for both methods, which we attribute to the long time scales of the common variability. The persistence time (memory is strongly overestimated when using the standard, interpolation-based, approach. Hence, the Gaussian kernel is a reliable and more robust estimator with significant advantages compared to other techniques and suitable for large scale application to paleo-data.

  11. Meconium microbiome analysis identifies bacteria correlated with premature birth.

    Directory of Open Access Journals (Sweden)

    Alexandria N Ardissone

    Full Text Available Preterm birth is the second leading cause of death in children under the age of five years worldwide, but the etiology of many cases remains enigmatic. The dogma that the fetus resides in a sterile environment is being challenged by recent findings and the question has arisen whether microbes that colonize the fetus may be related to preterm birth. It has been posited that meconium reflects the in-utero microbial environment. In this study, correlations between fetal intestinal bacteria from meconium and gestational age were examined in order to suggest underlying mechanisms that may contribute to preterm birth.Meconium from 52 infants ranging in gestational age from 23 to 41 weeks was collected, the DNA extracted, and 16S rRNA analysis performed. Resulting taxa of microbes were correlated to clinical variables and also compared to previous studies of amniotic fluid and other human microbiome niches.Increased detection of bacterial 16S rRNA in meconium of infants of <33 weeks gestational age was observed. Approximately 61·1% of reads sequenced were classified to genera that have been reported in amniotic fluid. Gestational age had the largest influence on microbial community structure (R = 0·161; p = 0·029, while mode of delivery (C-section versus vaginal delivery had an effect as well (R = 0·100; p = 0·044. Enterobacter, Enterococcus, Lactobacillus, Photorhabdus, and Tannerella, were negatively correlated with gestational age and have been reported to incite inflammatory responses, suggesting a causative role in premature birth.This provides the first evidence to support the hypothesis that the fetal intestinal microbiome derived from swallowed amniotic fluid may be involved in the inflammatory response that leads to premature birth.

  12. Analysis of correlations between sites in models of protein sequences

    International Nuclear Information System (INIS)

    Giraud, B.G.; Lapedes, A.; Liu, L.C.

    1998-01-01

    A criterion based on conditional probabilities, related to the concept of algorithmic distance, is used to detect correlated mutations at noncontiguous sites on sequences. We apply this criterion to the problem of analyzing correlations between sites in protein sequences; however, the analysis applies generally to networks of interacting sites with discrete states at each site. Elementary models, where explicit results can be derived easily, are introduced. The number of states per site considered ranges from 2, illustrating the relation to familiar classical spin systems, to 20 states, suitable for representing amino acids. Numerical simulations show that the criterion remains valid even when the genetic history of the data samples (e.g., protein sequences), as represented by a phylogenetic tree, introduces nonindependence between samples. Statistical fluctuations due to finite sampling are also investigated and do not invalidate the criterion. A subsidiary result is found: The more homogeneous a population, the more easily its average properties can drift from the properties of its ancestor. copyright 1998 The American Physical Society

  13. Forecast Correlation Coefficient Matrix of Stock Returns in Portfolio Analysis

    OpenAIRE

    Zhao, Feng

    2013-01-01

    In Modern Portfolio Theory, the correlation coefficients decide the risk of a set of stocks in the portfolio. So, to understand the correlation coefficients between returns of stocks, is a challenge but is very important for the portfolio management. Usually, the stocks with small correlation coefficients or even negative correlation coefficients are preferred. One can calculate the correlation coefficients of stock returns based on the historical stock data. However, in order to control the ...

  14. A flexible time recording and time correlation analysis system

    International Nuclear Information System (INIS)

    Shenhav, N.J.; Leiferman, G.; Segal, Y.; Notea, A.

    1983-01-01

    A system was developed to digitize and record the time intervals between detection event pulses, feed to its input channels from a detection device. The accumulated data is transferred continuously in real time to a disc through a PDP 11/34 minicomputer. Even though the system was designed for a specific scope, i.e., the comparative study of passive neutron nondestructive assay methods, it can be characterized by its features as a general purpose time series recorder. The time correlation analysis is performed by software after completion of the data accumulation. The digitizing clock period is selectable and any value, larger than a minimum of 100 ns, may be selected. Bursts of up to 128 events with a frequency up to 10 MHz may be recorded. With the present recorder-minicomputer combination, the maximal average recording frequency is 40 kHz. (orig.)

  15. Brillouin optical correlation domain analysis in composite material beams

    DEFF Research Database (Denmark)

    Stern, Yonatan; London, Yosef; Preter, Eyal

    2017-01-01

    Structural health monitoring is a critical requirement in many composites. Numerous monitoring strategies rely on measurements of temperature or strain (or both), however these are often restricted to point-sensing or to the coverage of small areas. Spatially-continuous data can be obtained...... with optical fiber sensors. In this work, we report high-resolution distributed Brillouin sensing over standard fibers that are embedded in composite structures. A phase-coded, Brillouin optical correlation domain analysis (B-OCDA) protocol was employed, with spatial resolution of 2 cm and sensitivity of 1 °K...... or 20 micro-strain. A portable measurement setup was designed and assembled on the premises of a composite structures manufacturer. The setup was successfully utilized in several structural health monitoring scenarios: (a) monitoring the production and curing of a composite beam over 60 h; (b...

  16. A Visual Analytics Approach for Correlation, Classification, and Regression Analysis

    Energy Technology Data Exchange (ETDEWEB)

    Steed, Chad A [ORNL; SwanII, J. Edward [Mississippi State University (MSU); Fitzpatrick, Patrick J. [Mississippi State University (MSU); Jankun-Kelly, T.J. [Mississippi State University (MSU)

    2012-02-01

    New approaches that combine the strengths of humans and machines are necessary to equip analysts with the proper tools for exploring today's increasing complex, multivariate data sets. In this paper, a novel visual data mining framework, called the Multidimensional Data eXplorer (MDX), is described that addresses the challenges of today's data by combining automated statistical analytics with a highly interactive parallel coordinates based canvas. In addition to several intuitive interaction capabilities, this framework offers a rich set of graphical statistical indicators, interactive regression analysis, visual correlation mining, automated axis arrangements and filtering, and data classification techniques. The current work provides a detailed description of the system as well as a discussion of key design aspects and critical feedback from domain experts.

  17. Brillouin Optical Correlation Domain Analysis in Composite Material Beams

    Directory of Open Access Journals (Sweden)

    Yonatan Stern

    2017-10-01

    Full Text Available Structural health monitoring is a critical requirement in many composites. Numerous monitoring strategies rely on measurements of temperature or strain (or both, however these are often restricted to point-sensing or to the coverage of small areas. Spatially-continuous data can be obtained with optical fiber sensors. In this work, we report high-resolution distributed Brillouin sensing over standard fibers that are embedded in composite structures. A phase-coded, Brillouin optical correlation domain analysis (B-OCDA protocol was employed, with spatial resolution of 2 cm and sensitivity of 1 °K or 20 micro-strain. A portable measurement setup was designed and assembled on the premises of a composite structures manufacturer. The setup was successfully utilized in several structural health monitoring scenarios: (a monitoring the production and curing of a composite beam over 60 h; (b estimating the stiffness and Young’s modulus of a composite beam; and (c distributed strain measurements across the surfaces of a model wing of an unmanned aerial vehicle. The measurements are supported by the predictions of structural analysis calculations. The results illustrate the potential added values of high-resolution, distributed Brillouin sensing in the structural health monitoring of composites.

  18. Brillouin Optical Correlation Domain Analysis in Composite Material Beams.

    Science.gov (United States)

    Stern, Yonatan; London, Yosef; Preter, Eyal; Antman, Yair; Diamandi, Hilel Hagai; Silbiger, Maayan; Adler, Gadi; Levenberg, Eyal; Shalev, Doron; Zadok, Avi

    2017-10-02

    Structural health monitoring is a critical requirement in many composites. Numerous monitoring strategies rely on measurements of temperature or strain (or both), however these are often restricted to point-sensing or to the coverage of small areas. Spatially-continuous data can be obtained with optical fiber sensors. In this work, we report high-resolution distributed Brillouin sensing over standard fibers that are embedded in composite structures. A phase-coded, Brillouin optical correlation domain analysis (B-OCDA) protocol was employed, with spatial resolution of 2 cm and sensitivity of 1 °K or 20 micro-strain. A portable measurement setup was designed and assembled on the premises of a composite structures manufacturer. The setup was successfully utilized in several structural health monitoring scenarios: (a) monitoring the production and curing of a composite beam over 60 h; (b) estimating the stiffness and Young's modulus of a composite beam; and (c) distributed strain measurements across the surfaces of a model wing of an unmanned aerial vehicle. The measurements are supported by the predictions of structural analysis calculations. The results illustrate the potential added values of high-resolution, distributed Brillouin sensing in the structural health monitoring of composites.

  19. Interactive Correlation Analysis and Visualization of Climate Data

    Energy Technology Data Exchange (ETDEWEB)

    Ma, Kwan-Liu [Univ. of California, Davis, CA (United States)

    2016-09-21

    The relationship between our ability to analyze and extract insights from visualization of climate model output and the capability of the available resources to make those visualizations has reached a crisis point. The large volume of data currently produced by climate models is overwhelming the current, decades-old visualization workflow. The traditional methods for visualizing climate output also have not kept pace with changes in the types of grids used, the number of variables involved, and the number of different simulations performed with a climate model or the feature-richness of high-resolution simulations. This project has developed new and faster methods for visualization in order to get the most knowledge out of the new generation of high-resolution climate models. While traditional climate images will continue to be useful, there is need for new approaches to visualization and analysis of climate data if we are to gain all the insights available in ultra-large data sets produced by high-resolution model output and ensemble integrations of climate models such as those produced for the Coupled Model Intercomparison Project. Towards that end, we have developed new visualization techniques for performing correlation analysis. We have also introduced highly scalable, parallel rendering methods for visualizing large-scale 3D data. This project was done jointly with climate scientists and visualization researchers at Argonne National Laboratory and NCAR.

  20. Multifractal Detrended Cross-Correlation Analysis of agricultural futures markets

    International Nuclear Information System (INIS)

    He Lingyun; Chen Shupeng

    2011-01-01

    Highlights: → We investigated cross-correlations between China's and US agricultural futures markets. → Power-law cross-correlations are found between the geographically far but correlated markets. → Multifractal features are significant in all the markets. → Cross-correlation exponent is less than averaged GHE when q 0. - Abstract: We investigated geographically far but temporally correlated China's and US agricultural futures markets. We found that there exists a power-law cross-correlation between them, and that multifractal features are significant in all the markets. It is very interesting that the geographically far markets show strong cross-correlations and share much of their multifractal structure. Furthermore, we found that for all the agricultural futures markets in our studies, the cross-correlation exponent is less than the averaged generalized Hurst exponents (GHE) when q 0.

  1. Correlation and network analysis of global financial indices.

    Science.gov (United States)

    Kumar, Sunil; Deo, Nivedita

    2012-08-01

    Random matrix theory (RMT) and network methods are applied to investigate the correlation and network properties of 20 financial indices. The results are compared before and during the financial crisis of 2008. In the RMT method, the components of eigenvectors corresponding to the second largest eigenvalue form two clusters of indices in the positive and negative directions. The components of these two clusters switch in opposite directions during the crisis. The network analysis uses the Fruchterman-Reingold layout to find clusters in the network of indices at different thresholds. At a threshold of 0.6, before the crisis, financial indices corresponding to the Americas, Europe, and Asia-Pacific form separate clusters. On the other hand, during the crisis at the same threshold, the American and European indices combine together to form a strongly linked cluster while the Asia-Pacific indices form a separate weakly linked cluster. If the value of the threshold is further increased to 0.9 then the European indices (France, Germany, and the United Kingdom) are found to be the most tightly linked indices. The structure of the minimum spanning tree of financial indices is more starlike before the crisis and it changes to become more chainlike during the crisis. The average linkage hierarchical clustering algorithm is used to find a clearer cluster structure in the network of financial indices. The cophenetic correlation coefficients are calculated and found to increase significantly, which indicates that the hierarchy increases during the financial crisis. These results show that there is substantial change in the structure of the organization of financial indices during a financial crisis.

  2. Stoichiometric Correlation Analysis: Principles of Metabolic Functionality from Metabolomics Data

    Directory of Open Access Journals (Sweden)

    Kevin Schwahn

    2017-12-01

    Full Text Available Recent advances in metabolomics technologies have resulted in high-quality (time-resolved metabolic profiles with an increasing coverage of metabolic pathways. These data profiles represent read-outs from often non-linear dynamics of metabolic networks. Yet, metabolic profiles have largely been explored with regression-based approaches that only capture linear relationships, rendering it difficult to determine the extent to which the data reflect the underlying reaction rates and their couplings. Here we propose an approach termed Stoichiometric Correlation Analysis (SCA based on correlation between positive linear combinations of log-transformed metabolic profiles. The log-transformation is due to the evidence that metabolic networks can be modeled by mass action law and kinetics derived from it. Unlike the existing approaches which establish a relation between pairs of metabolites, SCA facilitates the discovery of higher-order dependence between more than two metabolites. By using a paradigmatic model of the tricarboxylic acid cycle we show that the higher-order dependence reflects the coupling of concentration of reactant complexes, capturing the subtle difference between the employed enzyme kinetics. Using time-resolved metabolic profiles from Arabidopsis thaliana and Escherichia coli, we show that SCA can be used to quantify the difference in coupling of reactant complexes, and hence, reaction rates, underlying the stringent response in these model organisms. By using SCA with data from natural variation of wild and domesticated wheat and tomato accession, we demonstrate that the domestication is accompanied by loss of such couplings, in these species. Therefore, application of SCA to metabolomics data from natural variation in wild and domesticated populations provides a mechanistic way to understanding domestication and its relation to metabolic networks.

  3. Canonical correlation analysis for gene-based pleiotropy discovery.

    Directory of Open Access Journals (Sweden)

    Jose A Seoane

    2014-10-01

    Full Text Available Genome-wide association studies have identified a wealth of genetic variants involved in complex traits and multifactorial diseases. There is now considerable interest in testing variants for association with multiple phenotypes (pleiotropy and for testing multiple variants for association with a single phenotype (gene-based association tests. Such approaches can increase statistical power by combining evidence for association over multiple phenotypes or genetic variants respectively. Canonical Correlation Analysis (CCA measures the correlation between two sets of multidimensional variables, and thus offers the potential to combine these two approaches. To apply CCA, we must restrict the number of attributes relative to the number of samples. Hence we consider modules of genetic variation that can comprise a gene, a pathway or another biologically relevant grouping, and/or a set of phenotypes. In order to do this, we use an attribute selection strategy based on a binary genetic algorithm. Applied to a UK-based prospective cohort study of 4286 women (the British Women's Heart and Health Study, we find improved statistical power in the detection of previously reported genetic associations, and identify a number of novel pleiotropic associations between genetic variants and phenotypes. New discoveries include gene-based association of NSF with triglyceride levels and several genes (ACSM3, ERI2, IL18RAP, IL23RAP and NRG1 with left ventricular hypertrophy phenotypes. In multiple-phenotype analyses we find association of NRG1 with left ventricular hypertrophy phenotypes, fibrinogen and urea and pleiotropic relationships of F7 and F10 with Factor VII, Factor IX and cholesterol levels.

  4. Prognostic value of correlation analysis of perinatal anamnesis

    Directory of Open Access Journals (Sweden)

    V. V. Sofronov

    2017-01-01

    Full Text Available Objective research: is to establish the prognostic value of the analysis of correlative relationships of qualitative indicators of the perinatal history. Correlative groups of interactions of the investigated qualitative indicators in the antenatal, intranatal and postnatal periods are constructed. It was shown that in antenatal history for newborns 22–37 weeks. gestation (group 1 the most important parameters are the «gestational age», «chronic respiratory diseases in the mother,» «premature birth in an anamnesis,» and «exacerbation of chronic infections during pregnancy»; for newborns 38–41 weeks. gestation (2nd group – «cervical erosion», «ovarian cyst», «fibromyoma» and «colpitis ». In the intranatal history for children of the 1st group, the most important parameters are «anhydrous period» and «prolonged labor»; for children of the second group – only «prolonged labor». In the postnatal history for the first group, the two most important parameters are the «gestational age» and the «zonal elevation of the brain echogenicity,» and for the 2 nd group only the parameter «degree of asphyxia» is as important. The obtained results confirm the main known interrelationships of parameters of the perinatal history. At the same time, nontrivial connections between the parameters of the perinatal history: «allergic diseases in the mother» – «threatened miscarriage » – «ovarian cyst»; «chronic respiratory diseases in the mother» – «allergic diseases of the mother» – «diseases of the digestive system in the father.»

  5. Modal Analysis and Model Correlation of the Mir Space Station

    Science.gov (United States)

    Kim, Hyoung M.; Kaouk, Mohamed

    2000-01-01

    This paper will discuss on-orbit dynamic tests, modal analysis, and model refinement studies performed as part of the Mir Structural Dynamics Experiment (MiSDE). Mir is the Russian permanently manned Space Station whose construction first started in 1986. The MiSDE was sponsored by the NASA International Space Station (ISS) Phase 1 Office and was part of the Shuttle-Mir Risk Mitigation Experiment (RME). One of the main objectives for MiSDE is to demonstrate the feasibility of performing on-orbit modal testing on large space structures to extract modal parameters that will be used to correlate mathematical models. The experiment was performed over a one-year span on the Mir-alone and Mir with a Shuttle docked. A total of 45 test sessions were performed including: Shuttle and Mir thruster firings, Shuttle-Mir and Progress-Mir dockings, crew exercise and pushoffs, and ambient noise during night-to-day and day-to-night orbital transitions. Test data were recorded with a variety of existing and new instrumentation systems that included: the MiSDE Mir Auxiliary Sensor Unit (MASU), the Space Acceleration Measurement System (SAMS), the Russian Mir Structural Dynamic Measurement System (SDMS), the Mir and Shuttle Inertial Measurement Units (IMUs), and the Shuttle payload bay video cameras. Modal analysis was performed on the collected test data to extract modal parameters, i.e. frequencies, damping factors, and mode shapes. A special time-domain modal identification procedure was used on free-decay structural responses. The results from this study show that modal testing and analysis of large space structures is feasible within operational constraints. Model refinements were performed on both the Mir alone and the Shuttle-Mir mated configurations. The design sensitivity approach was used for refinement, which adjusts structural properties in order to match analytical and test modal parameters. To verify the refinement results, the analytical responses calculated using

  6. Asymmetric correlation matrices: an analysis of financial data

    Science.gov (United States)

    Livan, G.; Rebecchi, L.

    2012-06-01

    We analyse the spectral properties of correlation matrices between distinct statistical systems. Such matrices are intrinsically non-symmetric, and lend themselves to extend the spectral analyses usually performed on standard Pearson correlation matrices to the realm of complex eigenvalues. We employ some recent random matrix theory results on the average eigenvalue density of this type of matrix to distinguish between noise and non-trivial correlation structures, and we focus on financial data as a case study. Namely, we employ daily prices of stocks belonging to the American and British stock exchanges, and look for the emergence of correlations between two such markets in the eigenvalue spectrum of their non-symmetric correlation matrix. We find several non trivial results when considering time-lagged correlations over short lags, and we corroborate our findings by additionally studying the asymmetric correlation matrix of the principal components of our datasets.

  7. Multifractal detrended Cross Correlation Analysis of Foreign Exchange and SENSEX fluctuation in Indian perspective

    Science.gov (United States)

    Dutta, Srimonti; Ghosh, Dipak; Chatterjee, Sucharita

    2016-12-01

    The manuscript studies autocorrelation and cross correlation of SENSEX fluctuations and Forex Exchange Rate in respect to Indian scenario. Multifractal detrended fluctuation analysis (MFDFA) and multifractal detrended cross correlation analysis (MFDXA) were employed to study the correlation between the two series. It was observed that the two series are strongly cross correlated. The change of degree of cross correlation with time was studied and the results are interpreted qualitatively.

  8. Provider attributes correlation analysis to their referral frequency and awards.

    Science.gov (United States)

    Wiley, Matthew T; Rivas, Ryan L; Hristidis, Vagelis

    2016-03-14

    There has been a recent growth in health provider search portals, where patients specify filters-such as specialty or insurance-and providers are ranked by patient ratings or other attributes. Previous work has identified attributes associated with a provider's quality through user surveys. Other work supports that intuitive quality-indicating attributes are associated with a provider's quality. We adopt a data-driven approach to study how quality indicators of providers are associated with a rich set of attributes including medical school, graduation year, procedures, fellowships, patient reviews, location, and technology usage. In this work, we only consider providers as individuals (e.g., general practitioners) and not organizations (e.g., hospitals). As quality indicators, we consider the referral frequency of a provider and a peer-nominated quality designation. We combined data from the Centers for Medicare and Medicaid Services (CMS) and several provider rating web sites to perform our analysis. Our data-driven analysis identified several attributes that correlate with and discriminate against referral volume and peer-nominated awards. In particular, our results consistently demonstrate that these attributes vary by locality and that the frequency of an attribute is more important than its value (e.g., the number of patient reviews or hospital affiliations are more important than the average review rating or the ranking of the hospital affiliations, respectively). We demonstrate that it is possible to build accurate classifiers for referral frequency and quality designation, with accuracies over 85 %. Our findings show that a one-size-fits-all approach to ranking providers is inadequate and that provider search portals should calibrate their ranking function based on location and specialty. Further, traditional filters of provider search portals should be reconsidered, and patients should be aware of existing pitfalls with these filters and educated on local

  9. Correlation Between Posttraumatic Growth and Posttraumatic Stress Disorder Symptoms Based on Pearson Correlation Coefficient: A Meta-Analysis.

    Science.gov (United States)

    Liu, An-Nuo; Wang, Lu-Lu; Li, Hui-Ping; Gong, Juan; Liu, Xiao-Hong

    2017-05-01

    The literature on posttraumatic growth (PTG) is burgeoning, with the inconsistencies in the literature of the relationship between PTG and posttraumatic stress disorder (PTSD) symptoms becoming a focal point of attention. Thus, this meta-analysis aims to explore the relationship between PTG and PTSD symptoms through the Pearson correlation coefficient. A systematic search of the literature from January 1996 to November 2015 was completed. We retrieved reports on 63 studies that involved 26,951 patients. The weighted correlation coefficient revealed an effect size of 0.22 with a 95% confidence interval of 0.18 to 0.25. Meta-analysis provides evidence that PTG may be positively correlated with PTSD symptoms and that this correlation may be modified by age, trauma type, and time since trauma. Accordingly, people with high levels of PTG should not be ignored, but rather, they should continue to receive help to alleviate their PTSD symptoms.

  10. Engineering Properties and Correlation Analysis of Fiber Cementitious Materials

    Directory of Open Access Journals (Sweden)

    Wei-Ting Lin

    2014-11-01

    Full Text Available This study focuses on the effect of the amount of silica fume addition and volume fraction of steel fiber on the engineering properties of cementitious materials. Test variables include dosage of silica fume (5% and 10%, water/cement ratio (0.35 and 0.55 and steel fiber dosage (0.5%, 1.0% and 2.0%. The experimental results included: compressive strength, direct tensile strength, splitting tensile strength, surface abrasion and drop-weight test, which were collected to carry out the analysis of variance to realize the relevancy and significance between material parameters and those mechanical properties. Test results illustrate that the splitting tensile strength, direct tensile strength, strain capacity and ability of crack-arresting increase with increasing steel fiber and silica fume dosages, as well as the optimum mixture of the fiber cementitious materials is 5% replacement silica fume and 2% fiber dosage. In addition, the Pearson correlation coefficient was conducted to evaluate the influence of the material variables and corresponds to the experiment result.

  11. Applications of temporal kernel canonical correlation analysis in adherence studies.

    Science.gov (United States)

    John, Majnu; Lencz, Todd; Ferbinteanu, Janina; Gallego, Juan A; Robinson, Delbert G

    2017-10-01

    Adherence to medication is often measured as a continuous outcome but analyzed as a dichotomous outcome due to lack of appropriate tools. In this paper, we illustrate the use of the temporal kernel canonical correlation analysis (tkCCA) as a method to analyze adherence measurements and symptom levels on a continuous scale. The tkCCA is a novel method developed for studying the relationship between neural signals and hemodynamic response detected by functional MRI during spontaneous activity. Although the tkCCA is a powerful tool, it has not been utilized outside the application that it was originally developed for. In this paper, we simulate time series of symptoms and adherence levels for patients with a hypothetical brain disorder and show how the tkCCA can be used to understand the relationship between them. We also examine, via simulations, the behavior of the tkCCA under various missing value mechanisms and imputation methods. Finally, we apply the tkCCA to a real data example of psychotic symptoms and adherence levels obtained from a study based on subjects with a first episode of schizophrenia, schizophreniform or schizoaffective disorder.

  12. An analysis of correlation between occlusion classification and skeletal pattern

    International Nuclear Information System (INIS)

    Lu Xinhua; Cai Bin; Wang Dawei; Wu Liping

    2003-01-01

    Objective: To study the correlation between dental relationship and skeletal pattern of individuals. Methods: 194 cases were selected and classified by angle classification, incisor relationship and skeletal pattern respectively. The correlation of angle classification and incisor relationship to skeletal pattern was analyzed with SPSS 10.0. Results: The values of correlation index (Kappa) were 0.379 and 0.494 respectively. Conclusion: The incisor relationship is more consistent with skeletal pattern than angle classification

  13. Asset correlations and credit portfolio risk: an empirical analysis

    OpenAIRE

    Düllmann, Klaus; Scheicher, Martin; Schmieder, Christian

    2007-01-01

    In credit risk modelling, the correlation of unobservable asset returns is a crucial component for the measurement of portfolio risk. In this paper, we estimate asset correlations from monthly time series of Moody's KMV asset values for around 2,000 European firms from 1996 to 2004. We compare correlation and value-atrisk (VaR) estimates in a one-factor or market model and a multi-factor or sector model. Our main finding is a complex interaction of credit risk correlations and default probabi...

  14. Alarm reduction with correlation analysis; Larmsanering genom korrelationsanalys

    Energy Technology Data Exchange (ETDEWEB)

    Bergquist, Tord; Ahnlund, Jonas; Johansson, Bjoern; Gaardman, Lennart; Raaberg, Martin [Lund Univ. (Sweden). Dept. of Information Technology

    2004-09-01

    This project's main interest is to improve the overall alarm situation in the control rooms. By doing so, the operators working environment is less overstrained, which simplifies the decision-making. According to a study of the British refinery industry, the operators make wrong decisions in four times out of ten due to badly tuned alarm systems, with heavy expenses as a result. Furthermore, a more efficiently alarm handling is estimated to decrease the production loss with between three and eight percent. This sounds, according to Swedish standards, maybe a bit extreme, but there is no doubt about the benefits of having a well-tuned alarm system. This project can be seen as an extension of 'General Methods for Alarm Reduction' (VARMEFORSK--835), where the process improvements were the result of suggestions tailored for every signal. Here, instead causal dependences in the process are examined. A method for this, specially designed to fit process signals, has been developed. It is called MLPC (Multiple Local Property Correlation) and could be seen as an unprejudiced way of increase the information value in the process. There are a number of ways to make use of the additional process understanding a correlation analysis provides. In the report some are mentioned, foremost aiming to improve the alarm situation for operators. Signals from two heating plants have been analyzed with MLPC. In simulations, with the use of the result from these analyses as a base, a large number of alarms have been successfully suppressed. The results have been studied by personal with process knowledge, and they are very positive to the use of MLPC and they express many benefits by the clarification of process relations. It was established in 'General Methods for Alarm Reduction' that low pass filter are superior to mean value filter and time delay when trying to suppress alarms. As a result, a module for signal processing has been developed. The main purpose is

  15. Correlation between detrended fluctuation analysis and the Lempel-Ziv complexity in nonlinear time series analysis

    International Nuclear Information System (INIS)

    Tang You-Fu; Liu Shu-Lin; Jiang Rui-Hong; Liu Ying-Hui

    2013-01-01

    We study the correlation between detrended fluctuation analysis (DFA) and the Lempel-Ziv complexity (LZC) in nonlinear time series analysis in this paper. Typical dynamic systems including a logistic map and a Duffing model are investigated. Moreover, the influence of Gaussian random noise on both the DFA and LZC are analyzed. The results show a high correlation between the DFA and LZC, which can quantify the non-stationarity and the nonlinearity of the time series, respectively. With the enhancement of the random component, the exponent a and the normalized complexity index C show increasing trends. In addition, C is found to be more sensitive to the fluctuation in the nonlinear time series than α. Finally, the correlation between the DFA and LZC is applied to the extraction of vibration signals for a reciprocating compressor gas valve, and an effective fault diagnosis result is obtained

  16. Linear analysis of degree correlations in complex networks

    Indian Academy of Sciences (India)

    Many real-world networks such as the protein–protein interaction networks and metabolic networks often display nontrivial correlations between degrees of vertices connected by edges. Here, we analyse the statistical methods used usually to describe the degree correlation in the networks, and analytically give linear ...

  17. Mutational analysis and clinical correlation of metastatic colorectal cancer.

    Science.gov (United States)

    Russo, Andrea L; Borger, Darrell R; Szymonifka, Jackie; Ryan, David P; Wo, Jennifer Y; Blaszkowsky, Lawrence S; Kwak, Eunice L; Allen, Jill N; Wadlow, Raymond C; Zhu, Andrew X; Murphy, Janet E; Faris, Jason E; Dias-Santagata, Dora; Haigis, Kevin M; Ellisen, Leif W; Iafrate, Anthony J; Hong, Theodore S

    2014-05-15

    Early identification of mutations may guide patients with metastatic colorectal cancer toward targeted therapies that may be life prolonging. The authors assessed tumor genotype correlations with clinical characteristics to determine whether mutational profiling can account for clinical similarities, differences, and outcomes. Under Institutional Review Board approval, 222 patients with metastatic colon adenocarcinoma (n = 158) and rectal adenocarcinoma (n = 64) who underwent clinical tumor genotyping were reviewed. Multiplexed tumor genotyping screened for >150 mutations across 15 commonly mutated cancer genes. The chi-square test was used to assess genotype frequency by tumor site and additional clinical characteristics. Cox multivariate analysis was used to assess the impact of genotype on overall survival. Broad-based tumor genotyping revealed clinical and anatomic differences that could be linked to gene mutations. NRAS mutations were associated with rectal cancer versus colon cancer (12.5% vs 0.6%; P colon cancer (13% vs 3%; P = .024) and older age (15.8% vs 4.6%; P = .006). TP53 mutations were associated with rectal cancer (30% vs 18%; P = .048), younger age (14% vs 28.7%; P = .007), and men (26.4% vs 14%; P = .03). Lung metastases were associated with PIK3CA mutations (23% vs 8.7%; P = .004). Only mutations in BRAF were independently associated with decreased overall survival (hazard ratio, 2.4; 95% confidence interval, 1.09-5.27; P = .029). The current study suggests that underlying molecular profiles can differ between colon and rectal cancers. Further investigation is warranted to assess whether the differences identified are important in determining the optimal treatment course for these patients. © 2014 American Cancer Society.

  18. Random matrix theory analysis of cross-correlations in the US stock market: Evidence from Pearson’s correlation coefficient and detrended cross-correlation coefficient

    Science.gov (United States)

    Wang, Gang-Jin; Xie, Chi; Chen, Shou; Yang, Jiao-Jiao; Yang, Ming-Yan

    2013-09-01

    In this study, we first build two empirical cross-correlation matrices in the US stock market by two different methods, namely the Pearson’s correlation coefficient and the detrended cross-correlation coefficient (DCCA coefficient). Then, combining the two matrices with the method of random matrix theory (RMT), we mainly investigate the statistical properties of cross-correlations in the US stock market. We choose the daily closing prices of 462 constituent stocks of S&P 500 index as the research objects and select the sample data from January 3, 2005 to August 31, 2012. In the empirical analysis, we examine the statistical properties of cross-correlation coefficients, the distribution of eigenvalues, the distribution of eigenvector components, and the inverse participation ratio. From the two methods, we find some new results of the cross-correlations in the US stock market in our study, which are different from the conclusions reached by previous studies. The empirical cross-correlation matrices constructed by the DCCA coefficient show several interesting properties at different time scales in the US stock market, which are useful to the risk management and optimal portfolio selection, especially to the diversity of the asset portfolio. It will be an interesting and meaningful work to find the theoretical eigenvalue distribution of a completely random matrix R for the DCCA coefficient because it does not obey the Marčenko-Pastur distribution.

  19. Correlation Function Analysis of Fiber Networks: Implications for Thermal Conductivity

    Science.gov (United States)

    Martinez-Garcia, Jorge; Braginsky, Leonid; Shklover, Valery; Lawson, John W.

    2011-01-01

    The heat transport in highly porous fiber structures is investigated. The fibers are supposed to be thin, but long, so that the number of the inter-fiber connections along each fiber is large. We show that the effective conductivity of such structures can be found from the correlation length of the two-point correlation function of the local conductivities. Estimation of the parameters, determining the conductivity, from the 2D images of the structures is analyzed.

  20. Approximation generation for correlations in thermal-hydraulic analysis codes

    International Nuclear Information System (INIS)

    Pereira, Luiz C.M.; Carmo, Eduardo G.D. do

    1997-01-01

    A fast and precise evaluation of fluid thermodynamic and transport properties is needed for the efficient mass, energy and momentum transport phenomena simulation related to nuclear plant power generation. A fully automatic code capable to generate suitable approximation for correlations with one or two independent variables is presented. Comparison in terms of access speed and precision with original correlations currently used shows the adequacy of the approximation obtained. (author). 4 refs., 8 figs., 1 tab

  1. Comprehensive analysis of electron correlations in three-electron atoms

    International Nuclear Information System (INIS)

    Morishita, T.; Lin, C.D.

    1999-01-01

    We study the electron correlations in singly, doubly, and triply excited states of a three-electron atom. While electron correlation in general is weak for singly excited states, correlation plays major roles in determining the characteristics of doubly and triply excited states. Using the adiabatic approximation in hyperspherical coordinates, we show that the distinction between singly, doubly, and triply excited states is determined by the radial correlations, while finer distinctions within doubly or triply excited states lie in the angular correlations. Partial projections of the body-fixed frame wave functions are used to demonstrate the characteristic nodal surfaces which provide clues to the energy ordering of the states. We show that doubly excited states of a three-electron atom exhibit correlations that are similar to the doubly excited states of a two-electron atom. For the triply excited states, we show that the motion of the three electrons resemble approximately that of a symmetric top. copyright 1999 The American Physical Society

  2. Development of Test-Analysis Models (TAM) for correlation of dynamic test and analysis results

    Science.gov (United States)

    Angelucci, Filippo; Javeed, Mehzad; Mcgowan, Paul

    1992-01-01

    The primary objective of structural analysis of aerospace applications is to obtain a verified finite element model (FEM). The verified FEM can be used for loads analysis, evaluate structural modifications, or design control systems. Verification of the FEM is generally obtained as the result of correlating test and FEM models. A test analysis model (TAM) is very useful in the correlation process. A TAM is essentially a FEM reduced to the size of the test model, which attempts to preserve the dynamic characteristics of the original FEM in the analysis range of interest. Numerous methods for generating TAMs have been developed in the literature. The major emphasis of this paper is a description of the procedures necessary for creation of the TAM and the correlation of the reduced models with the FEM or the test results. Herein, three methods are discussed, namely Guyan, Improved Reduced System (IRS), and Hybrid. Also included are the procedures for performing these analyses using MSC/NASTRAN. Finally, application of the TAM process is demonstrated with an experimental test configuration of a ten bay cantilevered truss structure.

  3. Analysis of factors correlating with medical radiological examination frequencies

    International Nuclear Information System (INIS)

    Jahnen, A.; Jaervinen, H.; Bly, R.; Olerud, H.; Vassilieva, J.; Vogiatzi, S.; Shannoun, F.

    2015-01-01

    The European Commission (EC) funded project Dose Datamed 2 (DDM2) had two objectives: to collect available data on patient doses from the radiodiagnostic procedures (X-ray and nuclear medicine) in Europe, and to facilitate the implementation of the Radiation Protection 154 Guidelines (RP154). Besides the collection of frequency and dose data, two questionnaires were issued to gather information about medical radiological imaging. This article analyses a possible correlation between the collected frequency data, selected variables from the results of the detailed questionnaire and national economic data. Based on a 35 countries dataset, there is no correlation between the gross domestic product (GDP) and the total number of X-ray examinations in a country. However, there is a significant correlation ( p < 0.01) between the GDP and the overall CT examination frequency. High income countries perform more CT examinations per inhabitant. That suggests that planar X-ray examinations are replaced by CT examinations. (authors)

  4. Thermodynamic correlations for the accident analysis of HTR's

    International Nuclear Information System (INIS)

    Rehm, W.; Jahn, W.; Finken, R.

    1976-12-01

    The thermal properties of Helium and for the case of a depressurized primary circuit, various mixtures of primary cooling gas were taken into consideration. The temperature dependence of the correlations for the thermal properties of the graphite components in the core and for the structural materials in the primary circuit are extrapolated about normal operation conditions. Furthermore the correlations for the effective thermal conductivity, the heat transfer and pressure drop are described for pebble bed HTR's. In addition some important heat transfer data of the steam generator are included. With these correlations, for example accident sequences with failure of the afterheat removal systems are discussed for pebble bed HTR's. It is concluded that the transient temperature behaviour demonstrates the inherent safety features of the HTR in extreme accidents. (orig.) [de

  5. Variability, correlation and path coefficient analysis of seedling traits ...

    African Journals Online (AJOL)

    use

    2011-12-12

    Dec 12, 2011 ... Indirect selection is a useful means for improving yield in cotton crop. The objective of the present study was to determine the genetic variability, broad sense heritability, genetic advance and correlation among the six seedling traits and their direct and indirect effects on cotton yield by using path coefficient ...

  6. Correlation of energy balance method to dynamic pipe rupture analysis

    International Nuclear Information System (INIS)

    Kuo, H.H.; Durkee, M.

    1983-01-01

    When using an energy balance approach in the design of pipe rupture restraints for nuclear power plants, the NRC specifies in its Standard Review Plan 3.6.2 that the input energy to the system must be multiplied by a factor of 1.1 unless a lower value can be justified. Since the energy balance method is already quite conservative, an across-the-board use of 1.1 to amplify the energy input appears unneccessary. The paper's purpose is to show that this 'correlation factor' could be substantially less than unity if certain design parameters are met. In this paper, result of nonlinear dynamic analyses were compared to the results of the corresponding analyses based on the energy balance method which assumes constant blowdown forces and rigid plastic material properties. The appropriate correlation factors required to match the energy balance results with the dynamic analyses results were correlated to design parameters such as restraint location from the break, yield strength of the energy absorbing component, and the restraint gap. It is shown that the correlation factor is related to a single nondimensional design parameter and can be limited to a value below unity if appropriate design parameters are chosen. It is also shown that the deformation of the restraints can be related to dimensionless system parameters. This, therefore, allows the maximum restraint deformation to be evaluated directly for design purposes. (orig.)

  7. Correlation Analysis of some Growth, Yield, Yield Components and ...

    African Journals Online (AJOL)

    three critical growth stages which was imposed by withholding water (at ... November, 5th December, 19th December and 2nd January) laid out in a split ... Simple correlation coefficient ® of different crop parameters and grain yield ... The husk bran and germ are rich sources of ..... heat in 2009/2010 dry season at Fadam a ...

  8. Linear analysis of degree correlations in complex networks

    Indian Academy of Sciences (India)

    2016-11-02

    Nov 2, 2016 ... 4College of Science, Qi Lu University of Technology, Jinan 250353, Shandong, China ... cal methods used usually to describe the degree correlation in the ... Most social networks show assorta- .... a clear but only qualitative description of the degree ... is difficult to give quantitative relation between DCC.

  9. Correlational Analysis of Servant Leadership and School Climate

    Science.gov (United States)

    Black, Glenda Lee

    2010-01-01

    The purpose of this mixed-method research study was to determine the extent that servant leadership was correlated with perceptions of school climate to identify whether there was a relationship between principals' and teachers' perceived practice of servant leadership and of school climate. The study employed a mixed-method approach by first…

  10. Analysis of Current HT9 Creep Correlations and Modification

    International Nuclear Information System (INIS)

    Lee, Cheol Min; Sohn, Dongseong; Cheon, Jin Sik

    2014-01-01

    It has high thermal conductivity, high mechanical strength and low irradiation induced swelling. However high temperature creep of HT9 has always been a life limiting factor. Above 600 .deg. C, the dislocation density in HT9 is decreased and the M 23 C 6 precipitates coarsen, these processes are accelerated if there is irradiation. Finally microstructural changes at high temperature lead to lower creep strength and large creep strain. For HT9 to be used as a future cladding, creep behavior of the HT9 should be predicted accurately based on the physical understanding of the creep phenomenon. Most of the creep correlations are composed of irradiation creep and thermal creep terms. However, it is certain that in-pile thermal creep and out-of-pile thermal creep are different because of the microstructure changes induced from neutron irradiation. To explain creep behavior more accurately, thermal creep contributions other than neutron irradiation should be discriminated in a creep correlation. To perform this work, existing HT9 creep correlations are analyzed, and the results are used to develop more accurate thermal creep correlation. Then, the differences between in-pile thermal creep and out-of-pile thermal creep are examined

  11. Approximate models for the analysis of laser velocimetry correlation functions

    International Nuclear Information System (INIS)

    Robinson, D.P.

    1981-01-01

    Velocity distributions in the subchannels of an eleven pin test section representing a slice through a Fast Reactor sub-assembly were measured with a dual beam laser velocimeter system using a Malvern K 7023 digital photon correlator for signal processing. Two techniques were used for data reduction of the correlation function to obtain velocity and turbulence values. Whilst both techniques were in excellent agreement on the velocity, marked discrepancies were apparent in the turbulence levels. As a consequence of this the turbulence data were not reported. Subsequent investigation has shown that the approximate technique used as the basis of Malvern's Data Processor 7023V is restricted in its range of application. In this note alternative approximate models are described and evaluated. The objective of this investigation was to develop an approximate model which could be used for on-line determination of the turbulence level. (author)

  12. Groundwater travel time uncertainty analysis. Sensitivity of results to model geometry, and correlations and cross correlations among input parameters

    International Nuclear Information System (INIS)

    Clifton, P.M.

    1985-03-01

    This study examines the sensitivity of the travel time distribution predicted by a reference case model to (1) scale of representation of the model parameters, (2) size of the model domain, (3) correlation range of log-transmissivity, and (4) cross correlations between transmissivity and effective thickness. The basis for the reference model is the preliminary stochastic travel time model previously documented by the Basalt Waste Isolation Project. Results of this study show the following. The variability of the predicted travel times can be adequately represented when the ratio between the size of the zones used to represent the model parameters and the log-transmissivity correlation range is less than about one-fifth. The size of the model domain and the types of boundary conditions can have a strong impact on the distribution of travel times. Longer log-transmissivity correlation ranges cause larger variability in the predicted travel times. Positive cross correlation between transmissivity and effective thickness causes a decrease in the travel time variability. These results demonstrate the need for a sound conceptual model prior to conducting a stochastic travel time analysis

  13. Dynamics of market correlations: taxonomy and portfolio analysis.

    Science.gov (United States)

    Onnela, J-P; Chakraborti, A; Kaski, K; Kertész, J; Kanto, A

    2003-11-01

    The time dependence of the recently introduced minimum spanning tree description of correlations between stocks, called the "asset tree" has been studied in order to reflect the financial market taxonomy. The nodes of the tree are identified with stocks and the distance between them is a unique function of the corresponding element of the correlation matrix. By using the concept of a central vertex, chosen as the most strongly connected node of the tree, an important characteristic is defined by the mean occupation layer. During crashes, due to the strong global correlation in the market, the tree shrinks topologically, and this is shown by a low value of the mean occupation layer. The tree seems to have a scale-free structure where the scaling exponent of the degree distribution is different for "business as usual" and "crash" periods. The basic structure of the tree topology is very robust with respect to time. We also point out that the diversification aspect of portfolio optimization results in the fact that the assets of the classic Markowitz portfolio are always located on the outer leaves of the tree. Technical aspects such as the window size dependence of the investigated quantities are also discussed.

  14. Comparison and Correlation Analysis of Different Swine Breeds Meat Quality

    Directory of Open Access Journals (Sweden)

    Y. X. Li

    2013-07-01

    Full Text Available This study was performed to determine the influence of pig breed and gender on the ultimate pH and physicochemical properties of pork. The correlations between pH and pork quality traits directly related to carcass grade, and consumer’s preference were also evaluated. The pH and meat grading scores for cold carcasses of 215 purebred pigs (Duroc, Landrace, and Yorkshire from four different farms were obtained. Meat quality parameters of the pork loin were analyzed. Duroc and female animals were more affected compared to other breeds and male pigs. Duroc animals had the highest ultimate pH, carcass back fat thickness, marbling scores, yellowness, and fat content (p<0.05. Landrace pigs had the highest color lightness and cooking loss values (p<0.05. Among all trait parameters, marbling scores showed the highest significant differences when evaluating the impact of breed and gender on meat quality characteristics (p<0.001. Ultimate pH was positively correlated with carcass weight (0.20, back fat thickness (0.19, marbling score (0.17, and color score (0.16 while negatively correlated with cooking loss (−0.24 and shear force (−0.20. Therefore, pork samples with lower ultimate pH had lower cooking loss, higher lightness, and higher shear force values irrespective of breed.

  15. Dynamics of market correlations: Taxonomy and portfolio analysis

    Science.gov (United States)

    Onnela, J.-P.; Chakraborti, A.; Kaski, K.; Kertész, J.; Kanto, A.

    2003-11-01

    The time dependence of the recently introduced minimum spanning tree description of correlations between stocks, called the “asset tree” has been studied in order to reflect the financial market taxonomy. The nodes of the tree are identified with stocks and the distance between them is a unique function of the corresponding element of the correlation matrix. By using the concept of a central vertex, chosen as the most strongly connected node of the tree, an important characteristic is defined by the mean occupation layer. During crashes, due to the strong global correlation in the market, the tree shrinks topologically, and this is shown by a low value of the mean occupation layer. The tree seems to have a scale-free structure where the scaling exponent of the degree distribution is different for “business as usual” and “crash” periods. The basic structure of the tree topology is very robust with respect to time. We also point out that the diversification aspect of portfolio optimization results in the fact that the assets of the classic Markowitz portfolio are always located on the outer leaves of the tree. Technical aspects such as the window size dependence of the investigated quantities are also discussed.

  16. Correlation analysis on alpha attenuation and nasal skin temperature

    International Nuclear Information System (INIS)

    Nozawa, Akio; Tacano, Munecazu

    2009-01-01

    Some serious accidents caused by declines in arousal level, such as traffic accidents and mechanical control mistakes, have become issues of social concern. The physiological index obtained by human body measurement is expected to offer a leading tool for evaluating arousal level as an objective indicator. In this study, declines in temporal arousal levels were evaluated by nasal skin temperature. As arousal level declines, sympathetic nervous activity is decreased and blood flow in peripheral vessels is increased. Since peripheral vessels exist just under the skin on the fingers and nose, the psychophysiological state can be judged from the displacement of skin temperature caused by changing blood flow volume. Declining arousal level is expected to be observable as a temperature rise in peripheral parts of the body. The objective of this experiment was to obtain assessment criteria for judging declines in arousal level by nasal skin temperature using the alpha attenuation coefficient (AAC) of electroencephalography (EEG) as a reference benchmark. Furthermore, a psychophysical index of sleepiness was also measured using a visual analogue scale (VAS). Correlations between nasal skin temperature index and EEG index were analyzed. AAC and maximum displacement of nasal skin temperature displayed a clear negative correlation, with a correlation coefficient of −0.55

  17. Feynman-α correlation analysis by prompt-photon detection

    International Nuclear Information System (INIS)

    Hashimoto, Kengo; Yamada, Sumasu; Hasegawa, Yasuhiro; Horiguchi, Tetsuo

    1998-01-01

    Two-detector Feynman-α measurements were carried out using the UTR-KINKI reactor, a light-water-moderated and graphite-reflected reactor, by detecting high-energy, prompt gamma rays. For comparison, the conventional measurements by detecting neutrons were also performed. These measurements were carried out in the subcriticality range from 0 to $1.8. The gate-time dependence of the variance-and covariance-to-mean ratios measured by gamma-ray detection were nearly identical with those obtained using standard neutron-detection techniques. Consequently, the prompt-neutron decay constants inferred from the gamma-ray correlation data agreed with those from the neutron data. Furthermore, the correlated-to-uncorrelated amplitude ratios obtained by gamma-ray detection significantly depended on the low-energy discriminator level of the single-channel analyzer. The discriminator level was determined as optimum for obtaining a maximum value of the amplitude ratio. The maximum amplitude ratio was much larger than that obtained by neutron detection. The subcriticality dependence of the decay constant obtained by gamma-ray detection was consistent with that obtained by neutron detection and followed the linear relation based on the one-point kinetic model in the vicinity of delayed critical. These experimental results suggest that the gamma-ray correlation technique can be applied to measure reactor kinetic parameters more efficiently

  18. Strong anticipation and long-range cross-correlation: Application of detrended cross-correlation analysis to human behavioral data

    Science.gov (United States)

    Delignières, Didier; Marmelat, Vivien

    2014-01-01

    In this paper, we analyze empirical data, accounting for coordination processes between complex systems (bimanual coordination, interpersonal coordination, and synchronization with a fractal metronome), by using a recently proposed method: detrended cross-correlation analysis (DCCA). This work is motivated by the strong anticipation hypothesis, which supposes that coordination between complex systems is not achieved on the basis of local adaptations (i.e., correction, predictions), but results from a more global matching of complexity properties. Indeed, recent experiments have evidenced a very close correlation between the scaling properties of the series produced by two coordinated systems, despite a quite weak local synchronization. We hypothesized that strong anticipation should result in the presence of long-range cross-correlations between the series produced by the two systems. Results allow a detailed analysis of the effects of coordination on the fluctuations of the series produced by the two systems. In the long term, series tend to present similar scaling properties, with clear evidence of long-range cross-correlation. Short-term results strongly depend on the nature of the task. Simulation studies allow disentangling the respective effects of noise and short-term coupling processes on DCCA results, and suggest that the matching of long-term fluctuations could be the result of short-term coupling processes.

  19. Low Carbon-Oriented Optimal Reliability Design with Interval Product Failure Analysis and Grey Correlation Analysis

    Directory of Open Access Journals (Sweden)

    Yixiong Feng

    2017-03-01

    Full Text Available The problem of large amounts of carbon emissions causes wide concern across the world, and it has become a serious threat to the sustainable development of the manufacturing industry. The intensive research into technologies and methodologies for green product design has significant theoretical meaning and practical value in reducing the emissions of the manufacturing industry. Therefore, a low carbon-oriented product reliability optimal design model is proposed in this paper: (1 The related expert evaluation information was prepared in interval numbers; (2 An improved product failure analysis considering the uncertain carbon emissions of the subsystem was performed to obtain the subsystem weight taking the carbon emissions into consideration. The interval grey correlation analysis was conducted to obtain the subsystem weight taking the uncertain correlations inside the product into consideration. Using the above two kinds of subsystem weights and different caution indicators of the decision maker, a series of product reliability design schemes is available; (3 The interval-valued intuitionistic fuzzy sets (IVIFSs were employed to select the optimal reliability and optimal design scheme based on three attributes, namely, low carbon, correlation and functions, and economic cost. The case study of a vertical CNC lathe proves the superiority and rationality of the proposed method.

  20. Statistical analysis of latent generalized correlation matrix estimation in transelliptical distribution

    OpenAIRE

    Han, Fang; Liu, Han

    2016-01-01

    Correlation matrices play a key role in many multivariate methods (e.g., graphical model estimation and factor analysis). The current state-of-the-art in estimating large correlation matrices focuses on the use of Pearson's sample correlation matrix. Although Pearson's sample correlation matrix enjoys various good properties under Gaussian models, it is not an effective estimator when facing heavy-tailed distributions. As a robust alternative, Han and Liu [J. Am. Stat. Assoc. 109 (2015) 275-2...

  1. S-matrix analysis of the baryon electric charge correlation

    Science.gov (United States)

    Lo, Pok Man; Friman, Bengt; Redlich, Krzysztof; Sasaki, Chihiro

    2018-03-01

    We compute the correlation of the net baryon number with the electric charge (χBQ) for an interacting hadron gas using the S-matrix formulation of statistical mechanics. The observable χBQ is particularly sensitive to the details of the pion-nucleon interaction, which are consistently incorporated in the current scheme via the empirical scattering phase shifts. Comparing to the recent lattice QCD studies in the (2 + 1)-flavor system, we find that the natural implementation of interactions and the proper treatment of resonances in the S-matrix approach lead to an improved description of the lattice data over that obtained in the hadron resonance gas model.

  2. The Asian crisis contagion: A dynamic correlation approach analysis

    Directory of Open Access Journals (Sweden)

    Essaadi Essahbi

    2009-01-01

    Full Text Available In this paper we are testing for contagion caused by the Thai baht collapse of July 1997. In line with earlier work, shift-contagion is defined as a structural change within the international propagation mechanisms of financial shocks. We adopt Bai and Perron's (1998 structural break approach in order to detect the endogenous break points of the pair-wise time-varying correlations between Thailand and seven Asian stock market returns. Our approach enables us to solve the misspecification problem of the crisis window. Our results illustrate the existence of shift-contagion in the Asian crisis caused by the crisis in Thailand.

  3. Re-analysis of correlations among four impulsivity scales.

    Science.gov (United States)

    Gallardo-Pujol, David; Andrés-Pueyo, Antonio

    2006-08-01

    Impulsivity plays a key role in normal and pathological behavior. Although there is some consensus about its conceptualization, there have been many attempts to build a multidimensional tool due to the lack of agreement in how to measure it. A recent study claimed support for a three-dimensional structure of impulsivity, however with weak empirical support. By re-analysing those data, a four-factor structure was found to describe the correlation matrix much better. The debate remains open and further research is needed to clarify the factor structure. The desirability of constructing new measures, perhaps analogously to the Wechsler Intelligence Scale, is emphasized.

  4. Correlation Analysis between Nominal and Real Convergence. The Romanian Case

    Directory of Open Access Journals (Sweden)

    Marius-Corneliu Marinas

    2006-05-01

    Full Text Available This study aims to analyze the sources of the correlation between the nominal and real convergence, as well as the impact of the macroeconomic politics on it. The perspective of Euro adoption will impose stricter management of monetary and budgetary politics, which will affect negatively the catching up process of the economic delays given the lack of higher economic flexibility. This enables a more rapid adjustment of the economy to some persistent shocks as a result of applying growth aggregate supply politics.

  5. Correlation Analysis between Nominal and Real Convergence. The Romanian Case

    Directory of Open Access Journals (Sweden)

    Marius-Corneliu Marinas

    2006-03-01

    Full Text Available This study aims to analyze the sources of the correlation between the nominal and real convergence, as well as the impact of the macroeconomic politics on it. The perspective of Euro adoption will impose stricter management of monetary and budgetary politics, which will affect negatively the catching up process of the economic delays given the lack of higher economic flexibility. This enables a more rapid adjustment of the economy to some persistent shocks as a result of applying growth aggregate supply politics.

  6. [Determination and correlation analysis of trace elements in Boletus tomentipes].

    Science.gov (United States)

    Li, Tao; Wang, Yuan-zhong; Zhang, Ji; Zhao, Yan-li; Liu, Hong-gao

    2011-07-01

    The contents of eleven trace elements in Boletus tomentipes were determined by inductively coupled plasma atomic emission spectroscopy (ICP-AES). The results showed that the fruiting bodies of B. tomentipes were very rich in Mg and Fe (>100 mg x kg(-1)) and rich in Mn, Zn and Cu (>10 mg x kg(-1)). Cr, Pb, Ni, Cd, and As were relatively minor contents (0.1-10.0 mg x kg(-1)) of this species, while Hg occurred at the smallest content (< 0.1 mg x kg(-1)). Among the determined 11 trace elements, Zn-Cu had significantly positive correlation (r = 0.659, P < 0.05), whereas, Hg-As, Ni-Fe, and Zn-Mg had significantly negative correlation (r = -0.672, -0.610, -0.617, P < 0.05). This paper presented the trace elements properties of B. tomentipes, and is expected to be useful for exploitation and quality evaluation of this species.

  7. Partitioning Water Vapor and Carbon Dioxide Fluxes using Correlation Analysis

    Science.gov (United States)

    Scanlon, T. M.

    2008-12-01

    A variety of methods are currently available to partition water vapor fluxes (into components of transpiration and direct evaporation) and carbon dioxide fluxes (into components of photosynthesis and respiration), using chambers, isotopes, and regression modeling approaches. Here, a methodology is presented that accounts for correlations between high-frequency measurements of water vapor (q) and carbon dioxide (c) concentrations being influenced by their non-identical source-sink distributions and the relative magnitude of their constituent fluxes. Flux-variance similarity assumptions are applied separately to the stomatal and the non-stomatal exchange, and the flux components are identified by considering the q-c correlation. Water use efficiency for the vegetation, and how it varies with respect to vapor pressure deficit, is the only input needed for this approach that uses standard eddy covariance measurements. The method is demonstrated using data collected over a corn field throughout a growing season. In particular, the research focuses on the partitioning of the water flux with the aim of improving how direct evaporation is handled in soil-vegetation- atmosphere transfer models over the course of wetting and dry-down cycles.

  8. Auto-correlation analysis of wave heights in the Bay of Bengal

    Indian Academy of Sciences (India)

    Time series observations of significant wave heights in the Bay of Bengal were subjected to auto- correlation analysis to determine temporal variability scale. The analysis indicates an exponen- tial fall of auto-correlation in the first few hours with a decorrelation time scale of about six hours. A similar figure was found earlier ...

  9. correlation studies and path coefficient analysis for seed yield

    African Journals Online (AJOL)

    Prof. Adipala Ekwamu

    African Crop Science Journal, Vol. 21, No. 1, pp. 51 - 59 ... Yield being a quantitative trait has complex inheritance, which is ... Analysis for seed yield and yield components in Ethiopian coriander. 53 ..... The financial assistance of Canadian.

  10. CORRELATION ANALYSIS OF THE AUDIT COMMITTEE AND STRUCTURAL INDICATORS

    Directory of Open Access Journals (Sweden)

    FÜLÖP MELINDA TIMEA

    2014-02-01

    Full Text Available The main role of corporate governance is to restore market confidence and in this process plays an important role the audit committee. The purpose of this case study is to analyze the correlations between the Audit Committee and structural indicators. Considering the achievement of the objectives proposed in this research, our research is based on a deductive approach from general aspects to particular aspects that combines quantitative and qualitative studies. Theoretical knowledge is used for a better understanding of a phenomenon and not for making assumptions. Thus, in order to achieve our study, we selected 25 companies listed on Berlin Stock Exchange. Following this study, we concluded that the role of the audit committee is crucial.

  11. CORRELATION ANALYSIS OF THE AUDIT COMMITTEE AND PROFITABILITY INDICATORS

    Directory of Open Access Journals (Sweden)

    MELINDA TIMEA FÜLÖP

    2013-10-01

    Full Text Available The main role of corporate governance is to restore market confidence and in this process plays an important role the audit committee. The purpose of this case study is to analyze the correlations between the Audit Committee and profitability indicators. Considering the achievement of the objectives proposed in this research, our research is based on a deductive approach from general aspects to particular aspects that combines quantitative and qualitative studies. Theoretical knowledge is used for a better understanding of a phenomenon and not for making assumptions. Thus, in order to achieve our study, we selected 25 companies listed on Berlin Stock Exchange. Following this study, we concluded that the role of the audit committee is crucial.

  12. The effects of common risk factors on stock returns: A detrended cross-correlation analysis

    Science.gov (United States)

    Ruan, Qingsong; Yang, Bingchan

    2017-10-01

    In this paper, we investigate the cross-correlations between Fama and French three factors and the return of American industries on the basis of cross-correlation statistic test and multifractal detrended cross-correlation analysis (MF-DCCA). Qualitatively, we find that the return series of Fama and French three factors and American industries were overall significantly cross-correlated based on the analysis of a statistic. Quantitatively, we find that the cross-correlations between three factors and the return of American industries were strongly multifractal, and applying MF-DCCA we also investigate the cross-correlation of industry returns and residuals. We find that there exists multifractality of industry returns and residuals. The result of correlation coefficients we can verify that there exist other factors which influence the industry returns except Fama three factors.

  13. Correlation analysis of milk production traits across three ...

    African Journals Online (AJOL)

    The relationship between milk production traits over whole lactations was evaluated across three generations of Simmental cows (between daughters, dams and granddams) by a corelation analysis with whole lactation traits in the daughter generation being used as the dependent variables (x1), and those in ...

  14. Dominating clasp of the financial sector revealed by partial correlation analysis of the stock market.

    Science.gov (United States)

    Kenett, Dror Y; Tumminello, Michele; Madi, Asaf; Gur-Gershgoren, Gitit; Mantegna, Rosario N; Ben-Jacob, Eshel

    2010-12-20

    What are the dominant stocks which drive the correlations present among stocks traded in a stock market? Can a correlation analysis provide an answer to this question? In the past, correlation based networks have been proposed as a tool to uncover the underlying backbone of the market. Correlation based networks represent the stocks and their relationships, which are then investigated using different network theory methodologies. Here we introduce a new concept to tackle the above question--the partial correlation network. Partial correlation is a measure of how the correlation between two variables, e.g., stock returns, is affected by a third variable. By using it we define a proxy of stock influence, which is then used to construct partial correlation networks. The empirical part of this study is performed on a specific financial system, namely the set of 300 highly capitalized stocks traded at the New York Stock Exchange, in the time period 2001-2003. By constructing the partial correlation network, unlike the case of standard correlation based networks, we find that stocks belonging to the financial sector and, in particular, to the investment services sub-sector, are the most influential stocks affecting the correlation profile of the system. Using a moving window analysis, we find that the strong influence of the financial stocks is conserved across time for the investigated trading period. Our findings shed a new light on the underlying mechanisms and driving forces controlling the correlation profile observed in a financial market.

  15. Groundwater travel time uncertainty analysis: Sensitivity of results to model geometry, and correlations and cross correlations among input parameters

    International Nuclear Information System (INIS)

    Clifton, P.M.

    1984-12-01

    The deep basalt formations beneath the Hanford Site are being investigated for the Department of Energy (DOE) to assess their suitability as a host medium for a high level nuclear waste repository. Predicted performance of the proposed repository is an important part of the investigation. One of the performance measures being used to gauge the suitability of the host medium is pre-waste-emplacement groundwater travel times to the accessible environment. Many deterministic analyses of groundwater travel times have been completed by Rockwell and other independent organizations. Recently, Rockwell has completed a preliminary stochastic analysis of groundwater travel times. This document presents analyses that show the sensitivity of the results from the previous stochastic travel time study to: (1) scale of representation of model parameters, (2) size of the model domain, (3) correlation range of log-transmissivity, and (4) cross-correlation between transmissivity and effective thickness. 40 refs., 29 figs., 6 tabs

  16. Data analysis of backscattering LIDAR system correlated with meteorological data

    International Nuclear Information System (INIS)

    Uehara, Sandro Toshio

    2009-01-01

    In these last years, we had an increase in the interest in the monitoring of the effect of the human activity being on the atmosphere and the climate in the planet. The remote sensing techniques has been used in many studies, also related the global changes. A backscattering LIDAR system, the first of this kind in Brazil, has been used to provide the vertical profile of the aerosol backscatter coefficient at 532 nm up to an altitude of 4-6 km above sea level. In this study, data has was collected in the year of 2005. These data had been correlated with data of solar photometer CIMEL and also with meteorological data. The main results had indicated to exist a standard in the behavior of these meteorological data and the vertical distribution of the extinction coefficient gotten through LIDAR. In favorable periods of atmospheric dispersion, that is, rise of the temperature of associated air the fall of relative humidity, increase of the atmospheric pressure and low ventilation tax, was possible to determine with good precision the height of the Planetary Boundary Layer, as much through the vertical profile of the extinction coefficient how much through the technique of the vertical profile of the potential temperature. The technique LIDAR showed to be an important tool in the determination of the thermodynamic structure of the atmosphere, assisting to characterize the evolution of the CLP throughout the day, which had its good space and secular resolution. (author)

  17. Analysis of three particle correlations with the INDRA detector

    International Nuclear Information System (INIS)

    Rahmani, A.; Eudes, Ph.; Lautridou, P.; Lebrun, C.; Reposeur, T.

    1997-01-01

    In the framework of the study of light particle production with the INDRA detector, we have analysed the invariant mass distribution of three particles produced in the Xe + Sn collisions at 50 A.MeV making use of an original interferometric method which offers the possibilities to access the intrinsic parameters of intermediate 'resonances' created during the nuclear collisions. By analyzing the correlations of (α,α,α) it was possible to make evident a signal equivalent to that from 12 C. The study of this signal allows: - to estimate the production rate of αs coming from the 12 C * decay; - accordingly, to introduce a correction for α multiplicity measured by INDRA; - to extract the temperature of the emitting fragment ( 12 C * ); to establish the sequential or direct decay mode of the emitting fragments ( 12 C * → α + 8 Be → α + α + α or 12 C * → α + α + α). Thus, the measured signal is an apparent consequence of the occurrence of the intermediate fragments excited in a metastable state from which the particles are emitted. The emission rate of the α particles coming from the decay of these fragments is estimated to several percents (< 10 %)

  18. Correlation analysis for forced vibration test of the Hualien large scale seismic test (LSST) program

    International Nuclear Information System (INIS)

    Sugawara, Y.; Sugiyama, T.; Kobayashi, T.; Yamaya, H.; Kitamura, E.

    1995-01-01

    The correlation analysis for a forced vibration test of a 1/4-scale containment SSI test model constructed in Hualien, Taiwan was carried out for the case of after backfilling. Prior to this correlation analysis, the structural properties were revised to adjust the calculated fundamental frequency in the fixed base condition to that derived from the test results. A correlation analysis was carried out using the Lattice Model which was able to estimate the soil-structure effects with embedment. The analysis results coincide well with test results and it is concluded that the mathematical soil-structure interaction model established by the correlation analysis is efficient in estimating the dynamic soil-structure interaction effect with embedment. This mathematical model will be applied as a basic model for simulation analysis of earthquake observation records. (author). 3 refs., 12 figs., 2 tabs

  19. NDVI and Panchromatic Image Correlation Using Texture Analysis

    Science.gov (United States)

    2010-03-01

    6 Figure 5. Spectral reflectance of vegetation and soil from 0.4 to 1.1 mm (From Perry...should help the classification methods to be able to classify kelp. Figure 5. Spectral reflectance of vegetation and soil from 0.4 to 1.1 mm...1988). Image processing software for imaging spectrometry analysis. Remote Sensing of Enviroment , 24: 201–210. Perry, C., & Lautenschlager, L. F

  20. Generalization of proposed tendon friction correlation and its application to PCCV structural analysis

    International Nuclear Information System (INIS)

    Kashiwase, Takako; Nagasaka, Hideo

    2000-01-01

    The present paper dealt with the extension of tendon friction coefficient correlation as a function of loading end load and circumferential angle, proposed in the former paper. The extended correlation further included the effects of the number of strands contacted with sheath, tendon diameter, politicization of tendon and tendon local curvature. The validity of the correlation was confirmed by several published measured data. The structural analysis of middle cylinder part of 1/4 PCCV (Prestressed Concrete Containment Vessel) model was conducted using the present friction coefficient correlation. The results were compared with the analysis using constant friction coefficient, focused on the tendon tension force distribution. (author)

  1. Analysis of the influences of thermal correlations on neutronic–thermohydraulic coupling calculation of SCWR

    International Nuclear Information System (INIS)

    Xu, Weifeng; Cai, Jiejin; Liu, Shichang; Tang, Qi

    2015-01-01

    Highlights: • Different thermal correlations for supercritical water are summarized. • Influences of thermal correlations on neutronic–thermohydraulic coupling calculation are analyzed. • Sensitivity analysis has been done for the thermal correlations. - Abstract: The neutronic–thermohydraulic coupling (N–T coupling) calculation is important on core design, security and stability analysis of supercritical water-coolant reactor (SCWR), and a suitable thermal correlation is also necessary for the N–T coupling calculation. In this paper, the scheme of the U.S. SCWR design and the process of the N–T coupling will be introduced as well as some of different thermal correlations firstly. Then, based on the N–T coupling system ARNT, the U.S. SCWR design is simulated to analyze the influences of thermal correlations on N–T coupling calculation of SCWR so as to find out which correlation is best. The result shows that all thermal correlations are suitable. However, using different correlations for calculation leads to a great difference in safety margin of SCWR. What's more, the Bishop and Jackson correlations are more suitable and conservative, but the Griem correlation is not very precise. And the effect of buoyancy lift makes little influence on the calculation of heat transfer of SCWR. This research is also of great significance for the further study of N–T coupling of SCWR

  2. Using beta coefficients to impute missing correlations in meta-analysis research: Reasons for caution.

    Science.gov (United States)

    Roth, Philip L; Le, Huy; Oh, In-Sue; Van Iddekinge, Chad H; Bobko, Philip

    2018-06-01

    Meta-analysis has become a well-accepted method for synthesizing empirical research about a given phenomenon. Many meta-analyses focus on synthesizing correlations across primary studies, but some primary studies do not report correlations. Peterson and Brown (2005) suggested that researchers could use standardized regression weights (i.e., beta coefficients) to impute missing correlations. Indeed, their beta estimation procedures (BEPs) have been used in meta-analyses in a wide variety of fields. In this study, the authors evaluated the accuracy of BEPs in meta-analysis. We first examined how use of BEPs might affect results from a published meta-analysis. We then developed a series of Monte Carlo simulations that systematically compared the use of existing correlations (that were not missing) to data sets that incorporated BEPs (that impute missing correlations from corresponding beta coefficients). These simulations estimated ρ̄ (mean population correlation) and SDρ (true standard deviation) across a variety of meta-analytic conditions. Results from both the existing meta-analysis and the Monte Carlo simulations revealed that BEPs were associated with potentially large biases when estimating ρ̄ and even larger biases when estimating SDρ. Using only existing correlations often substantially outperformed use of BEPs and virtually never performed worse than BEPs. Overall, the authors urge a return to the standard practice of using only existing correlations in meta-analysis. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

  3. DNA microarray data and contextual analysis of correlation graphs

    Directory of Open Access Journals (Sweden)

    Hingamp Pascal

    2003-04-01

    Full Text Available Abstract Background DNA microarrays are used to produce large sets of expression measurements from which specific biological information is sought. Their analysis requires efficient and reliable algorithms for dimensional reduction, classification and annotation. Results We study networks of co-expressed genes obtained from DNA microarray experiments. The mathematical concept of curvature on graphs is used to group genes or samples into clusters to which relevant gene or sample annotations are automatically assigned. Application to publicly available yeast and human lymphoma data demonstrates the reliability of the method in spite of its simplicity, especially with respect to the small number of parameters involved. Conclusions We provide a method for automatically determining relevant gene clusters among the many genes monitored with microarrays. The automatic annotations and the graphical interface improve the readability of the data. A C++ implementation, called Trixy, is available from http://tagc.univ-mrs.fr/bioinformatics/trixy.html.

  4. Multidimensional correlation among plan complexity, quality and deliverability parameters for volumetric-modulated arc therapy using canonical correlation analysis.

    Science.gov (United States)

    Shen, Lanxiao; Chen, Shan; Zhu, Xiaoyang; Han, Ce; Zheng, Xiaomin; Deng, Zhenxiang; Zhou, Yongqiang; Gong, Changfei; Xie, Congying; Jin, Xiance

    2018-03-01

    A multidimensional exploratory statistical method, canonical correlation analysis (CCA), was applied to evaluate the impact of complexity parameters on the plan quality and deliverability of volumetric-modulated arc therapy (VMAT) and to determine parameters in the generation of an ideal VMAT plan. Canonical correlations among complexity, quality and deliverability parameters of VMAT, as well as the contribution weights of different parameters were investigated with 71 two-arc VMAT nasopharyngeal cancer (NPC) patients, and further verified with 28 one-arc VMAT prostate cancer patients. The average MU and MU per control point (MU/CP) for two-arc VMAT plans were 702.6 ± 55.7 and 3.9 ± 0.3 versus 504.6 ± 99.2 and 5.6 ± 1.1 for one-arc VMAT plans, respectively. The individual volume-based 3D gamma passing rates of clinical target volume (γCTV) and planning target volume (γPTV) for NPC and prostate cancer patients were 85.7% ± 9.0% vs 92.6% ± 7.8%, and 88.0% ± 7.6% vs 91.2% ± 7.7%, respectively. Plan complexity parameters of NPC patients were correlated with plan quality (P = 0.047) and individual volume-based 3D gamma indices γ(IV) (P = 0.01), in which, MU/CP and segment area (SA) per control point (SA/CP) were weighted highly in correlation with γ(IV) , and SA/CP, percentage of CPs with SA plan quality with coefficients of 0.98, 0.68 and -0.99, respectively. Further verification with one-arc VMAT plans demonstrated similar results. In conclusion, MU, SA-related parameters and PTV volume were found to have strong effects on the plan quality and deliverability.

  5. Multifractal detrended cross-correlation analysis on gold, crude oil and foreign exchange rate time series

    Science.gov (United States)

    Pal, Mayukha; Madhusudana Rao, P.; Manimaran, P.

    2014-12-01

    We apply the recently developed multifractal detrended cross-correlation analysis method to investigate the cross-correlation behavior and fractal nature between two non-stationary time series. We analyze the daily return price of gold, West Texas Intermediate and Brent crude oil, foreign exchange rate data, over a period of 18 years. The cross correlation has been measured from the Hurst scaling exponents and the singularity spectrum quantitatively. From the results, the existence of multifractal cross-correlation between all of these time series is found. We also found that the cross correlation between gold and oil prices possess uncorrelated behavior and the remaining bivariate time series possess persistent behavior. It was observed for five bivariate series that the cross-correlation exponents are less than the calculated average generalized Hurst exponents (GHE) for q0 and for one bivariate series the cross-correlation exponent is greater than GHE for all q values.

  6. Genome-scale cluster analysis of replicated microarrays using shrinkage correlation coefficient.

    Science.gov (United States)

    Yao, Jianchao; Chang, Chunqi; Salmi, Mari L; Hung, Yeung Sam; Loraine, Ann; Roux, Stanley J

    2008-06-18

    Currently, clustering with some form of correlation coefficient as the gene similarity metric has become a popular method for profiling genomic data. The Pearson correlation coefficient and the standard deviation (SD)-weighted correlation coefficient are the two most widely-used correlations as the similarity metrics in clustering microarray data. However, these two correlations are not optimal for analyzing replicated microarray data generated by most laboratories. An effective correlation coefficient is needed to provide statistically sufficient analysis of replicated microarray data. In this study, we describe a novel correlation coefficient, shrinkage correlation coefficient (SCC), that fully exploits the similarity between the replicated microarray experimental samples. The methodology considers both the number of replicates and the variance within each experimental group in clustering expression data, and provides a robust statistical estimation of the error of replicated microarray data. The value of SCC is revealed by its comparison with two other correlation coefficients that are currently the most widely-used (Pearson correlation coefficient and SD-weighted correlation coefficient) using statistical measures on both synthetic expression data as well as real gene expression data from Saccharomyces cerevisiae. Two leading clustering methods, hierarchical and k-means clustering were applied for the comparison. The comparison indicated that using SCC achieves better clustering performance. Applying SCC-based hierarchical clustering to the replicated microarray data obtained from germinating spores of the fern Ceratopteris richardii, we discovered two clusters of genes with shared expression patterns during spore germination. Functional analysis suggested that some of the genetic mechanisms that control germination in such diverse plant lineages as mosses and angiosperms are also conserved among ferns. This study shows that SCC is an alternative to the Pearson

  7. Authentication of reprocessing plant safeguards data through correlation analysis

    International Nuclear Information System (INIS)

    Burr, T.L.; Wangen, L.E.; Mullen, M.F.

    1995-04-01

    This report investigates the feasibility and benefits of two new approaches to the analysis of safeguards data from reprocessing plants. Both approaches involve some level of plant modeling. All models involve some form of mass balance, either applied in the usual way that leads to material balances for individual process vessels at discrete times or applied by accounting for pipe flow rates that leads to material balances for individual process vessels at continuous times. In the first case, material balances are computed after each tank-to-tank transfer. In the second case, material balances can be computed at any desired time. The two approaches can be described as follows. The first approach considers the application of a new multivariate sequential test. The test statistic is a scalar, but the monitored residual is a vector. The second approach considers the application of recent nonlinear time series methods for the purpose of empirically building a model for the expected magnitude of a material balance or other scalar variable. Although the report restricts attention to monitoring scalar time series, the methodology can be extended to vector time series

  8. Correlation between videogame mechanics and executive functions through EEG analysis.

    Science.gov (United States)

    Mondéjar, Tania; Hervás, Ramón; Johnson, Esperanza; Gutierrez, Carlos; Latorre, José Miguel

    2016-10-01

    This paper addresses a different point of view of videogames, specifically serious games for health. This paper contributes to that area with a multidisciplinary perspective focus on neurosciences and computation. The experiment population has been pre-adolescents between the ages of 8 and 12 without any cognitive issues. The experiment consisted in users playing videogames as well as performing traditional psychological assessments; during these tasks the frontal brain activity was evaluated. The main goal was to analyse how the frontal lobe of the brain (executive function) works in terms of prominent cognitive skills during five types of game mechanics widely used in commercial videogames. The analysis was made by collecting brain signals during the two phases of the experiment, where the signals were analysed with an electroencephalogram neuroheadset. The validated hypotheses were whether videogames can develop executive functioning and if it was possible to identify which kind of cognitive skills are developed during each kind of typical videogame mechanic. The results contribute to the design of serious games for health purposes on a conceptual level, particularly in support of the diagnosis and treatment of cognitive-related pathologies. Copyright © 2016 Elsevier Inc. All rights reserved.

  9. Time-correlated neutron analysis of a multiplying HEU source

    International Nuclear Information System (INIS)

    Miller, E.C.; Kalter, J.M.; Lavelle, C.M.; Watson, S.M.; Kinlaw, M.T.; Chichester, D.L.; Noonan, W.A.

    2015-01-01

    The ability to quickly identify and characterize special nuclear material remains a national security challenge. In counter-proliferation applications, identifying the neutron multiplication of a sample can be a good indication of the level of threat. Currently neutron multiplicity measurements are performed with moderated 3 He proportional counters. These systems rely on the detection of thermalized neutrons, a process which obscures both energy and time information from the source. Fast neutron detectors, such as liquid scintillators, have the ability to detect events on nanosecond time scales, providing more information on the temporal structure of the arriving signal, and provide an alternative method for extracting information from the source. To explore this possibility, a series of measurements were performed on the Idaho National Laboratory's MARVEL assembly, a configurable HEU source. The source assembly was measured in a variety of different HEU configurations and with different reflectors, covering a range of neutron multiplications from 2 to 8. The data was collected with liquid scintillator detectors and digitized for offline analysis. A gap based approach for identifying the bursts of detected neutrons associated with the same fission chain was used. Using this approach, we are able to study various statistical properties of individual fission chains. One of these properties is the distribution of neutron arrival times within a given burst. We have observed two interesting empirical trends. First, this distribution exhibits a weak, but definite, dependence on source multiplication. Second, there are distinctive differences in the distribution depending on the presence and type of reflector. Both of these phenomena might prove to be useful when assessing an unknown source. The physical origins of these phenomena can be illuminated with help of MCNPX-PoliMi simulations

  10. Time-correlated neutron analysis of a multiplying HEU source

    Energy Technology Data Exchange (ETDEWEB)

    Miller, E.C., E-mail: Eric.Miller@jhuapl.edu [Johns Hopkins University Applied Physics Laboratory, Laurel, MD (United States); Kalter, J.M.; Lavelle, C.M. [Johns Hopkins University Applied Physics Laboratory, Laurel, MD (United States); Watson, S.M.; Kinlaw, M.T.; Chichester, D.L. [Idaho National Laboratory, Idaho Falls, ID (United States); Noonan, W.A. [Johns Hopkins University Applied Physics Laboratory, Laurel, MD (United States)

    2015-06-01

    The ability to quickly identify and characterize special nuclear material remains a national security challenge. In counter-proliferation applications, identifying the neutron multiplication of a sample can be a good indication of the level of threat. Currently neutron multiplicity measurements are performed with moderated {sup 3}He proportional counters. These systems rely on the detection of thermalized neutrons, a process which obscures both energy and time information from the source. Fast neutron detectors, such as liquid scintillators, have the ability to detect events on nanosecond time scales, providing more information on the temporal structure of the arriving signal, and provide an alternative method for extracting information from the source. To explore this possibility, a series of measurements were performed on the Idaho National Laboratory's MARVEL assembly, a configurable HEU source. The source assembly was measured in a variety of different HEU configurations and with different reflectors, covering a range of neutron multiplications from 2 to 8. The data was collected with liquid scintillator detectors and digitized for offline analysis. A gap based approach for identifying the bursts of detected neutrons associated with the same fission chain was used. Using this approach, we are able to study various statistical properties of individual fission chains. One of these properties is the distribution of neutron arrival times within a given burst. We have observed two interesting empirical trends. First, this distribution exhibits a weak, but definite, dependence on source multiplication. Second, there are distinctive differences in the distribution depending on the presence and type of reflector. Both of these phenomena might prove to be useful when assessing an unknown source. The physical origins of these phenomena can be illuminated with help of MCNPX-PoliMi simulations.

  11. Time-correlated neutron analysis of a multiplying HEU source

    Science.gov (United States)

    Miller, E. C.; Kalter, J. M.; Lavelle, C. M.; Watson, S. M.; Kinlaw, M. T.; Chichester, D. L.; Noonan, W. A.

    2015-06-01

    The ability to quickly identify and characterize special nuclear material remains a national security challenge. In counter-proliferation applications, identifying the neutron multiplication of a sample can be a good indication of the level of threat. Currently neutron multiplicity measurements are performed with moderated 3He proportional counters. These systems rely on the detection of thermalized neutrons, a process which obscures both energy and time information from the source. Fast neutron detectors, such as liquid scintillators, have the ability to detect events on nanosecond time scales, providing more information on the temporal structure of the arriving signal, and provide an alternative method for extracting information from the source. To explore this possibility, a series of measurements were performed on the Idaho National Laboratory's MARVEL assembly, a configurable HEU source. The source assembly was measured in a variety of different HEU configurations and with different reflectors, covering a range of neutron multiplications from 2 to 8. The data was collected with liquid scintillator detectors and digitized for offline analysis. A gap based approach for identifying the bursts of detected neutrons associated with the same fission chain was used. Using this approach, we are able to study various statistical properties of individual fission chains. One of these properties is the distribution of neutron arrival times within a given burst. We have observed two interesting empirical trends. First, this distribution exhibits a weak, but definite, dependence on source multiplication. Second, there are distinctive differences in the distribution depending on the presence and type of reflector. Both of these phenomena might prove to be useful when assessing an unknown source. The physical origins of these phenomena can be illuminated with help of MCNPX-PoliMi simulations.

  12. Structural Analysis of Correlated Factors: Lessons from the Verbal-Performance Dichotomy of the Wechsler Scales.

    Science.gov (United States)

    Macmann, Gregg M.; Barnett, David W.

    1994-01-01

    Describes exploratory and confirmatory analyses of verbal-performance procedures to illustrate concepts and procedures for analysis of correlated factors. Argues that, based on convergent and discriminant validity criteria, factors should have higher correlations with variables that they purport to measure than with other variables. Discusses…

  13. Detrended partial cross-correlation analysis of two nonstationary time series influenced by common external forces

    Science.gov (United States)

    Qian, Xi-Yuan; Liu, Ya-Min; Jiang, Zhi-Qiang; Podobnik, Boris; Zhou, Wei-Xing; Stanley, H. Eugene

    2015-06-01

    When common factors strongly influence two power-law cross-correlated time series recorded in complex natural or social systems, using detrended cross-correlation analysis (DCCA) without considering these common factors will bias the results. We use detrended partial cross-correlation analysis (DPXA) to uncover the intrinsic power-law cross correlations between two simultaneously recorded time series in the presence of nonstationarity after removing the effects of other time series acting as common forces. The DPXA method is a generalization of the detrended cross-correlation analysis that takes into account partial correlation analysis. We demonstrate the method by using bivariate fractional Brownian motions contaminated with a fractional Brownian motion. We find that the DPXA is able to recover the analytical cross Hurst indices, and thus the multiscale DPXA coefficients are a viable alternative to the conventional cross-correlation coefficient. We demonstrate the advantage of the DPXA coefficients over the DCCA coefficients by analyzing contaminated bivariate fractional Brownian motions. We calculate the DPXA coefficients and use them to extract the intrinsic cross correlation between crude oil and gold futures by taking into consideration the impact of the U.S. dollar index. We develop the multifractal DPXA (MF-DPXA) method in order to generalize the DPXA method and investigate multifractal time series. We analyze multifractal binomial measures masked with strong white noises and find that the MF-DPXA method quantifies the hidden multifractal nature while the multifractal DCCA method fails.

  14. L2 Reading Comprehension and Its Correlates: A Meta-Analysis

    Science.gov (United States)

    Jeon, Eun Hee; Yamashita, Junko

    2014-01-01

    The present meta-analysis examined the overall average correlation (weighted for sample size and corrected for measurement error) between passage-level second language (L2) reading comprehension and 10 key reading component variables investigated in the research domain. Four high-evidence correlates (with 18 or more accumulated effect sizes: L2…

  15. Structure-constrained sparse canonical correlation analysis with an application to microbiome data analysis.

    Science.gov (United States)

    Chen, Jun; Bushman, Frederic D; Lewis, James D; Wu, Gary D; Li, Hongzhe

    2013-04-01

    Motivated by studying the association between nutrient intake and human gut microbiome composition, we developed a method for structure-constrained sparse canonical correlation analysis (ssCCA) in a high-dimensional setting. ssCCA takes into account the phylogenetic relationships among bacteria, which provides important prior knowledge on evolutionary relationships among bacterial taxa. Our ssCCA formulation utilizes a phylogenetic structure-constrained penalty function to impose certain smoothness on the linear coefficients according to the phylogenetic relationships among the taxa. An efficient coordinate descent algorithm is developed for optimization. A human gut microbiome data set is used to illustrate this method. Both simulations and real data applications show that ssCCA performs better than the standard sparse CCA in identifying meaningful variables when there are structures in the data.

  16. Climate Prediction Center (CPC)Ensemble Canonical Correlation Analysis 90-Day Seasonal Forecast of Precipitation

    Data.gov (United States)

    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...

  17. Sparse canonical correlation analysis for identifying, connecting and completing gene-expression networks

    NARCIS (Netherlands)

    Waaijenborg, S.; Zwinderman, A.H.

    2009-01-01

    ABSTRACT: BACKGROUND: We generalized penalized canonical correlation analysis for analyzing microarray gene-expression measurements for checking completeness of known metabolic pathways and identifying candidate genes for incorporation in the pathway. We used Wold's method for calculation of the

  18. Study of relationship between MUF correlation and detection sensitivity of statistical analysis

    International Nuclear Information System (INIS)

    Tamura, Toshiaki; Ihara, Hitoshi; Yamamoto, Yoichi; Ikawa, Koji

    1989-11-01

    Various kinds of statistical analysis are proposed to NRTA (Near Real Time Materials Accountancy) which was devised to satisfy the timeliness goal of one of the detection goals of IAEA. It will be presumed that different statistical analysis results will occur between the case of considered rigorous error propagation (with MUF correlation) and the case of simplified error propagation (without MUF correlation). Therefore, measurement simulation and decision analysis were done using flow simulation of 800 MTHM/Y model reprocessing plant, and relationship between MUF correlation and detection sensitivity and false alarm of statistical analysis was studied. Specific character of material accountancy for 800 MTHM/Y model reprocessing plant was grasped by this simulation. It also became clear that MUF correlation decreases not only false alarm but also detection probability for protracted loss in case of CUMUF test and Page's test applied to NRTA. (author)

  19. Climate Prediction Center(CPC)Ensemble Canonical Correlation Analysis Forecast of Temperature

    Data.gov (United States)

    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...

  20. Serum adiponectin levels are inversely correlated with leukemia: A meta-analysis

    Directory of Open Access Journals (Sweden)

    Jun-Jie Ma

    2016-01-01

    Conclusion: Our meta-analysis suggested that serum ADPN levels may be inversely correlated with leukemia, and ADPN levels can be used as an effective biologic marker in early diagnosis and therapeutic monitoring of leukemia.

  1. Within-Subject Correlation Analysis to Detect Functional Areas Associated With Response Inhibition

    Directory of Open Access Journals (Sweden)

    Tomoko Yamasaki

    2018-05-01

    Full Text Available Functional areas in fMRI studies are often detected by brain-behavior correlation, calculating across-subject correlation between the behavioral index and the brain activity related to a function of interest. Within-subject correlation analysis is also employed in a single subject level, which utilizes cognitive fluctuations in a shorter time period by correlating the behavioral index with the brain activity across trials. In the present study, the within-subject analysis was applied to the stop-signal task, a standard task to probe response inhibition, where efficiency of response inhibition can be evaluated by the stop-signal reaction time (SSRT. Since the SSRT is estimated, by definition, not in a trial basis but from pooled trials, the correlation across runs was calculated between the SSRT and the brain activity related to response inhibition. The within-subject correlation revealed negative correlations in the anterior cingulate cortex and the cerebellum. Moreover, the dissociation pattern was observed in the within-subject analysis when earlier vs. later parts of the runs were analyzed: negative correlation was dominant in earlier runs, whereas positive correlation was dominant in later runs. Regions of interest analyses revealed that the negative correlation in the anterior cingulate cortex, but not in the cerebellum, was dominant in earlier runs, suggesting multiple mechanisms associated with inhibitory processes that fluctuate on a run-by-run basis. These results indicate that the within-subject analysis compliments the across-subject analysis by highlighting different aspects of cognitive/affective processes related to response inhibition.

  2. Econometric analysis of realised covariation: high frequency covariance, regression and correlation in financial economics

    OpenAIRE

    Ole E. Barndorff-Nielsen; Neil Shephard

    2002-01-01

    This paper analyses multivariate high frequency financial data using realised covariation. We provide a new asymptotic distribution theory for standard methods such as regression, correlation analysis and covariance. It will be based on a fixed interval of time (e.g. a day or week), allowing the number of high frequency returns during this period to go to infinity. Our analysis allows us to study how high frequency correlations, regressions and covariances change through time. In particular w...

  3. Non-parametric correlative uncertainty quantification and sensitivity analysis: Application to a Langmuir bimolecular adsorption model

    Science.gov (United States)

    Feng, Jinchao; Lansford, Joshua; Mironenko, Alexander; Pourkargar, Davood Babaei; Vlachos, Dionisios G.; Katsoulakis, Markos A.

    2018-03-01

    We propose non-parametric methods for both local and global sensitivity analysis of chemical reaction models with correlated parameter dependencies. The developed mathematical and statistical tools are applied to a benchmark Langmuir competitive adsorption model on a close packed platinum surface, whose parameters, estimated from quantum-scale computations, are correlated and are limited in size (small data). The proposed mathematical methodology employs gradient-based methods to compute sensitivity indices. We observe that ranking influential parameters depends critically on whether or not correlations between parameters are taken into account. The impact of uncertainty in the correlation and the necessity of the proposed non-parametric perspective are demonstrated.

  4. Non-parametric correlative uncertainty quantification and sensitivity analysis: Application to a Langmuir bimolecular adsorption model

    Directory of Open Access Journals (Sweden)

    Jinchao Feng

    2018-03-01

    Full Text Available We propose non-parametric methods for both local and global sensitivity analysis of chemical reaction models with correlated parameter dependencies. The developed mathematical and statistical tools are applied to a benchmark Langmuir competitive adsorption model on a close packed platinum surface, whose parameters, estimated from quantum-scale computations, are correlated and are limited in size (small data. The proposed mathematical methodology employs gradient-based methods to compute sensitivity indices. We observe that ranking influential parameters depends critically on whether or not correlations between parameters are taken into account. The impact of uncertainty in the correlation and the necessity of the proposed non-parametric perspective are demonstrated.

  5. Non-linear canonical correlation for joint analysis of MEG signals from two subjects

    Directory of Open Access Journals (Sweden)

    Cristina eCampi

    2013-06-01

    Full Text Available We consider the problem of analysing magnetoencephalography (MEG data measured from two persons undergoing the same experiment, and we propose a method that searches for sources with maximally correlated energies. Our method is based on canonical correlation analysis (CCA, which provides linear transformations, one for each subject, such that the correlation between the transformed MEG signals is maximized. Here, we present a nonlinear version of CCA which measures the correlation of energies. Furthermore, we introduce a delay parameter in the modelto analyse, e.g., leader-follower changes in experiments where the two subjects are engaged in social interaction.

  6. Spatio-chromatic adaptation via higher-order canonical correlation analysis of natural images.

    Science.gov (United States)

    Gutmann, Michael U; Laparra, Valero; Hyvärinen, Aapo; Malo, Jesús

    2014-01-01

    Independent component and canonical correlation analysis are two general-purpose statistical methods with wide applicability. In neuroscience, independent component analysis of chromatic natural images explains the spatio-chromatic structure of primary cortical receptive fields in terms of properties of the visual environment. Canonical correlation analysis explains similarly chromatic adaptation to different illuminations. But, as we show in this paper, neither of the two methods generalizes well to explain both spatio-chromatic processing and adaptation at the same time. We propose a statistical method which combines the desirable properties of independent component and canonical correlation analysis: It finds independent components in each data set which, across the two data sets, are related to each other via linear or higher-order correlations. The new method is as widely applicable as canonical correlation analysis, and also to more than two data sets. We call it higher-order canonical correlation analysis. When applied to chromatic natural images, we found that it provides a single (unified) statistical framework which accounts for both spatio-chromatic processing and adaptation. Filters with spatio-chromatic tuning properties as in the primary visual cortex emerged and corresponding-colors psychophysics was reproduced reasonably well. We used the new method to make a theory-driven testable prediction on how the neural response to colored patterns should change when the illumination changes. We predict shifts in the responses which are comparable to the shifts reported for chromatic contrast habituation.

  7. [Correlation analysis of major agronomic characters and the polysaccharide contents in Dendrobium officinale].

    Science.gov (United States)

    Zhang, Lei; Zheng, Xi-Long; Qiu, Dao-Shou; Cai, Shi-Ke; Luo, Huan-Ming; Deng, Rui-Yun; Liu, Xiao-Jin

    2013-10-01

    In order to provide theoretical and technological basis for the germplasm innovation and variety breeding in Dendrobium officinale, a study of the correlation between polysaccharide content and agronomic characters was conducted. Based on the polysaccharide content determination and the agronomic characters investigation of 30 copies (110 individual plants) of Dendrobium officinale germplasm resources, the correlation between polysaccharide content and agronomic characters was analyzed via path and correlation analysis. Correlation analysis results showed that there was a significant negative correlation between average spacing and polysaccharide content, the correlation coefficient was -0.695. And the blade thickness was positively correlated with the polysaccharide content, but the correlation was not significant. The path analysis results showed that the stem length was the maximum influence factor to the polysaccharide, and it was positive effect, the direct path coefficient was 1.568. According to thess results, the polysaccharide content can be easily and intuitively estimated by the agronomic characters investigating data in the germpalsm resources screening and variety breeding. Therefore, it is a visual and practical technology guidance in quality variety breeding of Dendrobium officinale.

  8. Detrended cross-correlation analysis on RMB exchange rate and Hang Seng China Enterprises Index

    Science.gov (United States)

    Ruan, Qingsong; Yang, Bingchan; Ma, Guofeng

    2017-02-01

    In this paper, we investigate the cross-correlations between the Hang Seng China Enterprises Index and RMB exchange markets on the basis of a cross-correlation statistic test and multifractal detrended cross-correlation analysis (MF-DCCA). MF-DCCA has, at best, serious limitations for most of the signals describing complex natural processes and often indicates multifractal cross-correlations when there are none. In order to prevent these false multifractal cross-correlations, we apply MFCCA to verify the cross-correlations. Qualitatively, we find that the return series of the Hang Seng China Enterprises Index and RMB exchange markets were, overall, significantly cross-correlated based on the statistical analysis. Quantitatively, we find that the cross-correlations between the stock index and RMB exchange markets were strongly multifractal, and the multifractal degree of the onshore RMB exchange markets was somewhat larger than the offshore RMB exchange markets. Moreover, we use the absolute return series to investigate and confirm the fact of multifractality. The results from the rolling windows show that the short-term cross-correlations between volatility series remain high.

  9. Irregular Liesegang-type patterns in gas phase revisited. II. Statistical correlation analysis

    Science.gov (United States)

    Torres-Guzmán, José C.; Martínez-Mekler, Gustavo; Müller, Markus F.

    2016-05-01

    We present a statistical analysis of Liesegang-type patterns formed in a gaseous HCl-NH3 system by ammonium chloride precipitation along glass tubes, as described in Paper I [J. C. Torres-Guzmán et al., J. Chem. Phys. 144, 174701 (2016)] of this work. We focus on the detection and characterization of short and long-range correlations within the non-stationary sequence of apparently irregular precipitation bands. To this end we applied several techniques to estimate spatial correlations stemming from different fields, namely, linear auto-correlation via the power spectral density, detrended fluctuation analysis (DFA), and methods developed in the context of random matrix theory (RMT). In particular RMT methods disclose well pronounced long-range correlations over at least 40 bands in terms of both, band positions and intensity values. By using a variant of the DFA we furnish proof of the nonlinear nature of the detected long-range correlations.

  10. Statistical analysis of latent generalized correlation matrix estimation in transelliptical distribution.

    Science.gov (United States)

    Han, Fang; Liu, Han

    2017-02-01

    Correlation matrix plays a key role in many multivariate methods (e.g., graphical model estimation and factor analysis). The current state-of-the-art in estimating large correlation matrices focuses on the use of Pearson's sample correlation matrix. Although Pearson's sample correlation matrix enjoys various good properties under Gaussian models, its not an effective estimator when facing heavy-tail distributions with possible outliers. As a robust alternative, Han and Liu (2013b) advocated the use of a transformed version of the Kendall's tau sample correlation matrix in estimating high dimensional latent generalized correlation matrix under the transelliptical distribution family (or elliptical copula). The transelliptical family assumes that after unspecified marginal monotone transformations, the data follow an elliptical distribution. In this paper, we study the theoretical properties of the Kendall's tau sample correlation matrix and its transformed version proposed in Han and Liu (2013b) for estimating the population Kendall's tau correlation matrix and the latent Pearson's correlation matrix under both spectral and restricted spectral norms. With regard to the spectral norm, we highlight the role of "effective rank" in quantifying the rate of convergence. With regard to the restricted spectral norm, we for the first time present a "sign subgaussian condition" which is sufficient to guarantee that the rank-based correlation matrix estimator attains the optimal rate of convergence. In both cases, we do not need any moment condition.

  11. CORRELATIONS BETWEEN FINDINGS OF OCCLUSAL AND MANUAL ANALYSIS IN TMD-PATIENTS

    Directory of Open Access Journals (Sweden)

    Mariana Dimova

    2016-08-01

    Full Text Available The aim of this study was to investigate and analyze the possible correlations between findings by manual functional analysis and clinical occlusal analysis in TMD-patients. Material and methods: Material of this study are 111 TMD-patients selected after visual diagnostics, functional brief review under Ahlers Jakstatt, intraoral examination and taking periodontal status. In the period September 2014 - March 2016 all patients were subjected to manual functional analysis and clinical occlusal analysis. 17 people (10 women and 7 men underwent imaging with cone-beam computed tomography. Results: There were found many statistically significant correlations between tests of the structural analysis that indicate the relationships between findings. Conclusion: The presence of statistically significant correlations between occlusal relationships, freedom in the centric and condition of the muscle complex of masticatory system and TMJ confirm the relationship between the state of occlusal components and TMD.

  12. Cross-correlation time-of-flight analysis of molecular beam scattering

    International Nuclear Information System (INIS)

    Nowikow, C.V.; Grice, R.

    1979-01-01

    The theory of the cross-correlation method of time-of-flight analysis is presented in a form which highlights its formal similarity to the conventional method. A time-of-flight system for the analysis of crossed molecular beam scattering is described, which is based on a minicomputer interface and can operate in both the cross-correlation and conventional modes. The interface maintains the synchronisation of chopper disc rotation and channel advance indefinitely in the cross-correlation method and can acquire data in phase with the beam modulation in both methods. The shutter function of the cross-correlation method is determined and the deconvolution analysis of the data is discussed. (author)

  13. ADC histogram analysis of muscle lymphoma - Correlation with histopathology in a rare entity.

    Science.gov (United States)

    Meyer, Hans-Jonas; Pazaitis, Nikolaos; Surov, Alexey

    2018-06-21

    Diffusion weighted imaging (DWI) is able to reflect histopathology architecture. A novel imaging approach, namely histogram analysis, is used to further characterize lesion on MRI. The purpose of this study is to correlate histogram parameters derived from apparent diffusion coefficient- (ADC) maps with histopathology parameters in muscle lymphoma. Eight patients (mean age 64.8 years, range 45-72 years) with histopathologically confirmed muscle lymphoma were retrospectively identified. Cell count, total nucleic and average nucleic areas were estimated using ImageJ. Additionally, Ki67-index was calculated. DWI was obtained on a 1.5T scanner by using the b values of 0 and 1000 s/mm2. Histogram analysis was performed as a whole lesion measurement by using a custom-made Matlabbased application. The correlation analysis revealed statistically significant correlation between cell count and ADCmean (p=-0.76, P=0.03) as well with ADCp75 (p=-0.79, P=0.02). Kurtosis and entropy correlated with average nucleic area (p=-0.81, P=0.02, p=0.88, P=0.007, respectively). None of the analyzed ADC parameters correlated with total nucleic area and with Ki67-index. This study identified significant correlations between cellularity and histogram parameters derived from ADC maps in muscle lymphoma. Thus, histogram analysis parameters reflect histopathology in muscle tumors. Advances in knowledge: Whole lesion ADC histogram analysis is able to reflect histopathology parameters in muscle lymphomas.

  14. Cross-Correlations between Energy and Emissions Markets: New Evidence from Fractal and Multifractal Analysis

    Directory of Open Access Journals (Sweden)

    Gang-Jin Wang

    2014-01-01

    Full Text Available We supply a new perspective to describe and understand the behavior of cross-correlations between energy and emissions markets. Namely, we investigate cross-correlations between oil and gas (Oil-Gas, oil and CO2 (Oil-CO2, and gas and CO2 (Gas-CO2 based on fractal and multifractal analysis. We focus our study on returns of the oil, gas, and CO2 during the period of April 22, 2005–April 30, 2013. In the empirical analysis, by using the detrended cross-correlation analysis (DCCA method, we find that cross-correlations for Oil-Gas, Oil-CO2, and Gas-CO2 obey a power-law and are weakly persistent. Then, we adopt the method of DCCA cross-correlation coefficient to quantify cross-correlations between energy and emissions markets. The results show that their cross-correlations are diverse at different time scales. Next, based on the multifractal DCCA method, we find that cross-correlated markets have the nonlinear and multifractal nature and that the multifractality strength for three cross-correlated markets is arranged in the order of Gas-CO2 > Oil-Gas > Oil-CO2. Finally, by employing the rolling windows method, which can be used to investigate time-varying cross-correlation scaling exponents, we analyze short-term and long-term market dynamics and find that the recent global financial crisis has a notable influence on short-term and long-term market dynamics.

  15. Relationship between climatic variables and the variation in bulk tank milk composition using canonical correlation analysis.

    Science.gov (United States)

    Stürmer, Morgana; Busanello, Marcos; Velho, João Pedro; Heck, Vanessa Isabel; Haygert-Velho, Ione Maria Pereira

    2018-06-04

    A number of studies have addressed the relations between climatic variables and milk composition, but these works used univariate statistical approaches. In our study, we used a multivariate approach (canonical correlation) to study the impact of climatic variables on milk composition, price, and monthly milk production at a dairy farm using bulk tank milk data. Data on milk composition, price, and monthly milk production were obtained from a dairy company that purchased the milk from the farm, while climatic variable data were obtained from the National Institute of Meteorology (INMET). The data are from January 2014 to December 2016. Univariate correlation analysis and canonical correlation analysis were performed. Few correlations between the climatic variables and milk composition were found using a univariate approach. However, using canonical correlation analysis, we found a strong and significant correlation (r c  = 0.95, p value = 0.0029). Lactose, ambient temperature measures (mean, minimum, and maximum), and temperature-humidity index (THI) were found to be the most important variables for the canonical correlation. Our study indicated that 10.2% of the variation in milk composition, pricing, and monthly milk production can be explained by climatic variables. Ambient temperature variables, together with THI, seem to have the most influence on variation in milk composition.

  16. Correlations between MRI and Information Processing Speed in MS: A Meta-Analysis

    Directory of Open Access Journals (Sweden)

    S. M. Rao

    2014-01-01

    Full Text Available Objectives. To examine relationships between conventional MRI measures and the paced auditory serial addition test (PASAT and symbol digit modalities test (SDMT. Methods. A systematic literature review was conducted. Included studies had ≥30 multiple sclerosis (MS patients, administered the SDMT or PASAT, and measured T2LV or brain atrophy. Meta-analysis of MRI/information processing speed (IPS correlations, analysis of MRI/IPS significance tests to account for reporting bias, and binomial testing to detect trends when comparing correlation strengths of SDMT versus PASAT and T2LV versus atrophy were conducted. Results. The 39 studies identified frequently reported only significant correlations, suggesting reporting bias. Direct meta-analysis was only feasible for correlations between SDMT and T2LV (r=-0.45, P<0.001 and atrophy in patients with mixed-MS subtypes (r=-0.54, P<0.001. Familywise Holm-Bonferroni testing found that selective reporting was not the source of at least half of significant results reported. Binomial tests (P=0.006 favored SDMT over PASAT in strength of MRI correlations. Conclusions. A moderate-to-strong correlation exists between impaired IPS and MRI in mixed MS populations. Correlations with MRI were stronger for SDMT than for PASAT. Neither heterogeneity among populations nor reporting bias appeared to be responsible for these findings.

  17. Detrended fluctuation analysis made flexible to detect range of cross-correlated fluctuations

    Science.gov (United States)

    Kwapień, Jarosław; Oświecimka, Paweł; DroŻdŻ, Stanisław

    2015-11-01

    The detrended cross-correlation coefficient ρDCCA has recently been proposed to quantify the strength of cross-correlations on different temporal scales in bivariate, nonstationary time series. It is based on the detrended cross-correlation and detrended fluctuation analyses (DCCA and DFA, respectively) and can be viewed as an analog of the Pearson coefficient in the case of the fluctuation analysis. The coefficient ρDCCA works well in many practical situations but by construction its applicability is limited to detection of whether two signals are generally cross-correlated, without the possibility to obtain information on the amplitude of fluctuations that are responsible for those cross-correlations. In order to introduce some related flexibility, here we propose an extension of ρDCCA that exploits the multifractal versions of DFA and DCCA: multifractal detrended fluctuation analysis and multifractal detrended cross-correlation analysis, respectively. The resulting new coefficient ρq not only is able to quantify the strength of correlations but also allows one to identify the range of detrended fluctuation amplitudes that are correlated in two signals under study. We show how the coefficient ρq works in practical situations by applying it to stochastic time series representing processes with long memory: autoregressive and multiplicative ones. Such processes are often used to model signals recorded from complex systems and complex physical phenomena like turbulence, so we are convinced that this new measure can successfully be applied in time-series analysis. In particular, we present an example of such application to highly complex empirical data from financial markets. The present formulation can straightforwardly be extended to multivariate data in terms of the q -dependent counterpart of the correlation matrices and then to the network representation.

  18. Performance of Modified Test Statistics in Covariance and Correlation Structure Analysis under Conditions of Multivariate Nonnormality.

    Science.gov (United States)

    Fouladi, Rachel T.

    2000-01-01

    Provides an overview of standard and modified normal theory and asymptotically distribution-free covariance and correlation structure analysis techniques and details Monte Carlo simulation results on Type I and Type II error control. Demonstrates through the simulation that robustness and nonrobustness of structure analysis techniques vary as a…

  19. Research of diagnosis sensors fault based on correlation analysis of the bridge structural health monitoring system

    Science.gov (United States)

    Hu, Shunren; Chen, Weimin; Liu, Lin; Gao, Xiaoxia

    2010-03-01

    Bridge structural health monitoring system is a typical multi-sensor measurement system due to the multi-parameters of bridge structure collected from the monitoring sites on the river-spanning bridges. Bridge structure monitored by multi-sensors is an entity, when subjected to external action; there will be different performances to different bridge structure parameters. Therefore, the data acquired by each sensor should exist countless correlation relation. However, complexity of the correlation relation is decided by complexity of bridge structure. Traditionally correlation analysis among monitoring sites is mainly considered from physical locations. unfortunately, this method is so simple that it cannot describe the correlation in detail. The paper analyzes the correlation among the bridge monitoring sites according to the bridge structural data, defines the correlation of bridge monitoring sites and describes its several forms, then integrating the correlative theory of data mining and signal system to establish the correlation model to describe the correlation among the bridge monitoring sites quantificationally. Finally, The Chongqing Mashangxi Yangtze river bridge health measurement system is regards as research object to diagnosis sensors fault, and simulation results verify the effectiveness of the designed method and theoretical discussions.

  20. A non linear analysis of human gait time series based on multifractal analysis and cross correlations

    International Nuclear Information System (INIS)

    Munoz-Diosdado, A

    2005-01-01

    We analyzed databases with gait time series of adults and persons with Parkinson, Huntington and amyotrophic lateral sclerosis (ALS) diseases. We obtained the staircase graphs of accumulated events that can be bounded by a straight line whose slope can be used to distinguish between gait time series from healthy and ill persons. The global Hurst exponent of these series do not show tendencies, we intend that this is because some gait time series have monofractal behavior and others have multifractal behavior so they cannot be characterized with a single Hurst exponent. We calculated the multifractal spectra, obtained the spectra width and found that the spectra of the healthy young persons are almost monofractal. The spectra of ill persons are wider than the spectra of healthy persons. In opposition to the interbeat time series where the pathology implies loss of multifractality, in the gait time series the multifractal behavior emerges with the pathology. Data were collected from healthy and ill subjects as they walked in a roughly circular path and they have sensors in both feet, so we have one time series for the left foot and other for the right foot. First, we analyzed these time series separately, and then we compared both results, with direct comparison and with a cross correlation analysis. We tried to find differences in both time series that can be used as indicators of equilibrium problems

  1. A non linear analysis of human gait time series based on multifractal analysis and cross correlations

    Energy Technology Data Exchange (ETDEWEB)

    Munoz-Diosdado, A [Department of Mathematics, Unidad Profesional Interdisciplinaria de Biotecnologia, Instituto Politecnico Nacional, Av. Acueducto s/n, 07340, Mexico City (Mexico)

    2005-01-01

    We analyzed databases with gait time series of adults and persons with Parkinson, Huntington and amyotrophic lateral sclerosis (ALS) diseases. We obtained the staircase graphs of accumulated events that can be bounded by a straight line whose slope can be used to distinguish between gait time series from healthy and ill persons. The global Hurst exponent of these series do not show tendencies, we intend that this is because some gait time series have monofractal behavior and others have multifractal behavior so they cannot be characterized with a single Hurst exponent. We calculated the multifractal spectra, obtained the spectra width and found that the spectra of the healthy young persons are almost monofractal. The spectra of ill persons are wider than the spectra of healthy persons. In opposition to the interbeat time series where the pathology implies loss of multifractality, in the gait time series the multifractal behavior emerges with the pathology. Data were collected from healthy and ill subjects as they walked in a roughly circular path and they have sensors in both feet, so we have one time series for the left foot and other for the right foot. First, we analyzed these time series separately, and then we compared both results, with direct comparison and with a cross correlation analysis. We tried to find differences in both time series that can be used as indicators of equilibrium problems.

  2. Analysis method of high-order collective-flow correlations based on the concept of correlative degree

    International Nuclear Information System (INIS)

    Zhang Weigang

    2000-01-01

    Based on the concept of correlative degree, a new method of high-order collective-flow measurement is constructed, with which azimuthal correlations, correlations of final state transverse momentum magnitude and transverse correlations can be inspected respectively. Using the new method the contributions of the azimuthal correlations of particles distribution and the correlations of transverse momentum magnitude of final state particles to high-order collective-flow correlations are analyzed respectively with 4π experimental events for 1.2 A GeV Ar + BaI 2 collisions at the Bevalac stream chamber. Comparing with the correlations of transverse momentum magnitude, the azimuthal correlations of final state particles distribution dominate high-order collective-flow correlations in experimental samples. The contributions of correlations of transverse momentum magnitude of final state particles not only enhance the strength of the high-order correlations of particle group, but also provide important information for the measurement of the collectivity of collective flow within the more constraint district

  3. On minimizing the influence of the noise tail of correlation functions in operational modal analysis

    DEFF Research Database (Denmark)

    Tarpø, Marius; Olsen, Peter; Amador, Sandro

    2017-01-01

    on the identification results (random errors) when the noise tail is included in the identification. On the other hand, if the correlation function is truncated too much, then important information is lost. In other to minimize this error, a suitable truncation based on manual inspection of the correlation function......In operational modal analysis (OMA) correlation functions are used by all classical time-domain modal identification techniques that uses the impulse response function (free decays) as primary data. However, the main difference between the impulse response and the correlation functions estimated...... from the operational responses is that the latter present a higher noise level. This is due to statistical errors in the estimation of the correlation function and it causes random noise in the end of the function and this is called the noise tail. This noise might have significant influence...

  4. METHODS OF DISTANCE MEASUREMENT’S ACCURACY INCREASING BASED ON THE CORRELATION ANALYSIS OF STEREO IMAGES

    Directory of Open Access Journals (Sweden)

    V. L. Kozlov

    2018-01-01

    Full Text Available To solve the problem of increasing the accuracy of restoring a three-dimensional picture of space using two-dimensional digital images, it is necessary to use new effective techniques and algorithms for processing and correlation analysis of digital images. Actively developed tools that allow you to reduce the time costs for processing stereo images, improve the quality of the depth maps construction and automate their construction. The aim of the work is to investigate the possibilities of using various techniques for processing digital images to improve the measurements accuracy of the rangefinder based on the correlation analysis of the stereo image. The results of studies of the influence of color channel mixing techniques on the distance measurements accuracy for various functions realizing correlation processing of images are presented. Studies on the analysis of the possibility of using integral representation of images to reduce the time cost in constructing a depth map areproposed. The results of studies of the possibility of using images prefiltration before correlation processing when distance measuring by stereo imaging areproposed.It is obtained that using of uniform mixing of channels leads to minimization of the total number of measurement errors, and using of brightness extraction according to the sRGB standard leads to an increase of errors number for all of the considered correlation processing techniques. Integral representation of the image makes it possible to accelerate the correlation processing, but this method is useful for depth map calculating in images no more than 0.5 megapixels. Using of image filtration before correlation processing can provide, depending on the filter parameters, either an increasing of the correlation function value, which is useful for analyzing noisy images, or compression of the correlation function.

  5. An Econometric Analysis of Modulated Realised Covariance, Regression and Correlation in Noisy Diffusion Models

    DEFF Research Database (Denmark)

    Kinnebrock, Silja; Podolskij, Mark

    This paper introduces a new estimator to measure the ex-post covariation between high-frequency financial time series under market microstructure noise. We provide an asymptotic limit theory (including feasible central limit theorems) for standard methods such as regression, correlation analysis...... process can be relaxed and how our method can be applied to non-synchronous observations. We also present an empirical study of how high-frequency correlations, regressions and covariances change through time....

  6. Co-occurrence correlations of heavy metals in sediments revealed using network analysis.

    Science.gov (United States)

    Liu, Lili; Wang, Zhiping; Ju, Feng; Zhang, Tong

    2015-01-01

    In this study, the correlation-based study was used to identify the co-occurrence correlations among metals in marine sediment of Hong Kong, based on the long-term (from 1991 to 2011) temporal and spatial monitoring data. 14 stations out of the total 45 marine sediment monitoring stations were selected from three representative areas, including Deep Bay, Victoria Harbour and Mirs Bay. Firstly, Spearman's rank correlation-based network analysis was conducted as the first step to identify the co-occurrence correlations of metals from raw metadata, and then for further analysis using the normalized metadata. The correlations patterns obtained by network were consistent with those obtained by the other statistic normalization methods, including annual ratios, R-squared coefficient and Pearson correlation coefficient. Both Deep Bay and Victoria Harbour have been polluted by heavy metals, especially for Pb and Cu, which showed strong co-occurrence with other heavy metals (e.g. Cr, Ni, Zn and etc.) and little correlations with the reference parameters (Fe or Al). For Mirs Bay, which has better marine sediment quality compared with Deep Bay and Victoria Harbour, the co-occurrence patterns revealed by network analysis indicated that the metals in sediment dominantly followed the natural geography process. Besides the wide applications in biology, sociology and informatics, it is the first time to apply network analysis in the researches of environment pollutions. This study demonstrated its powerful application for revealing the co-occurrence correlations among heavy metals in marine sediments, which could be further applied for other pollutants in various environment systems. Copyright © 2014 Elsevier Ltd. All rights reserved.

  7. Phenomenological analysis of quantum level correlations and classical repulsion effects in SU(3) model

    International Nuclear Information System (INIS)

    Fujiwara, Shigeyasu; Sakata, Fumihiko

    2003-01-01

    The quantum level fluctuation in various systems has been shown to be characterized by the random matrix theory, and to be related to a regular-to-chaos transition in classical system. We present a new qualitative analysis of quantum and classical fluctuation properties by exploiting correlation coefficients and variances. It is shown that the correlation coefficient of quantum level density is inversely proportional to the variance of consecutive phase-space point spacings on the Poincare section plane. (author)

  8. Quantum diffraction and interference of spatially correlated photon pairs and its Fourier-optical analysis

    International Nuclear Information System (INIS)

    Shimizu, Ryosuke; Edamatsu, Keiichi; Itoh, Tadashi

    2006-01-01

    We present one- and two-photon diffraction and interference experiments involving parametric down-converted photon pairs. By controlling the divergence of the pump beam in parametric down-conversion, the diffraction-interference pattern produced by an object changes from a quantum (perfectly correlated) case to a classical (uncorrelated) one. The observed diffraction and interference patterns are accurately reproduced by Fourier-optical analysis taking into account the quantum spatial correlation. We show that the relation between the spatial correlation and the object size plays a crucial role in the formation of both one- and two-photon diffraction-interference patterns

  9. Application of the Gini correlation coefficient to infer regulatory relationships in transcriptome analysis.

    Science.gov (United States)

    Ma, Chuang; Wang, Xiangfeng

    2012-09-01

    One of the computational challenges in plant systems biology is to accurately infer transcriptional regulation relationships based on correlation analyses of gene expression patterns. Despite several correlation methods that are applied in biology to analyze microarray data, concerns regarding the compatibility of these methods with the gene expression data profiled by high-throughput RNA transcriptome sequencing (RNA-Seq) technology have been raised. These concerns are mainly due to the fact that the distribution of read counts in RNA-Seq experiments is different from that of fluorescence intensities in microarray experiments. Therefore, a comprehensive evaluation of the existing correlation methods and, if necessary, introduction of novel methods into biology is appropriate. In this study, we compared four existing correlation methods used in microarray analysis and one novel method called the Gini correlation coefficient on previously published microarray-based and sequencing-based gene expression data in Arabidopsis (Arabidopsis thaliana) and maize (Zea mays). The comparisons were performed on more than 11,000 regulatory relationships in Arabidopsis, including 8,929 pairs of transcription factors and target genes. Our analyses pinpointed the strengths and weaknesses of each method and indicated that the Gini correlation can compensate for the shortcomings of the Pearson correlation, the Spearman correlation, the Kendall correlation, and the Tukey's biweight correlation. The Gini correlation method, with the other four evaluated methods in this study, was implemented as an R package named rsgcc that can be utilized as an alternative option for biologists to perform clustering analyses of gene expression patterns or transcriptional network analyses.

  10. Application of the Gini Correlation Coefficient to Infer Regulatory Relationships in Transcriptome Analysis[W][OA

    Science.gov (United States)

    Ma, Chuang; Wang, Xiangfeng

    2012-01-01

    One of the computational challenges in plant systems biology is to accurately infer transcriptional regulation relationships based on correlation analyses of gene expression patterns. Despite several correlation methods that are applied in biology to analyze microarray data, concerns regarding the compatibility of these methods with the gene expression data profiled by high-throughput RNA transcriptome sequencing (RNA-Seq) technology have been raised. These concerns are mainly due to the fact that the distribution of read counts in RNA-Seq experiments is different from that of fluorescence intensities in microarray experiments. Therefore, a comprehensive evaluation of the existing correlation methods and, if necessary, introduction of novel methods into biology is appropriate. In this study, we compared four existing correlation methods used in microarray analysis and one novel method called the Gini correlation coefficient on previously published microarray-based and sequencing-based gene expression data in Arabidopsis (Arabidopsis thaliana) and maize (Zea mays). The comparisons were performed on more than 11,000 regulatory relationships in Arabidopsis, including 8,929 pairs of transcription factors and target genes. Our analyses pinpointed the strengths and weaknesses of each method and indicated that the Gini correlation can compensate for the shortcomings of the Pearson correlation, the Spearman correlation, the Kendall correlation, and the Tukey’s biweight correlation. The Gini correlation method, with the other four evaluated methods in this study, was implemented as an R package named rsgcc that can be utilized as an alternative option for biologists to perform clustering analyses of gene expression patterns or transcriptional network analyses. PMID:22797655

  11. Estimation of the biserial correlation and its sampling variance for use in meta-analysis.

    Science.gov (United States)

    Jacobs, Perke; Viechtbauer, Wolfgang

    2017-06-01

    Meta-analyses are often used to synthesize the findings of studies examining the correlational relationship between two continuous variables. When only dichotomous measurements are available for one of the two variables, the biserial correlation coefficient can be used to estimate the product-moment correlation between the two underlying continuous variables. Unlike the point-biserial correlation coefficient, biserial correlation coefficients can therefore be integrated with product-moment correlation coefficients in the same meta-analysis. The present article describes the estimation of the biserial correlation coefficient for meta-analytic purposes and reports simulation results comparing different methods for estimating the coefficient's sampling variance. The findings indicate that commonly employed methods yield inconsistent estimates of the sampling variance across a broad range of research situations. In contrast, consistent estimates can be obtained using two methods that appear to be unknown in the meta-analytic literature. A variance-stabilizing transformation for the biserial correlation coefficient is described that allows for the construction of confidence intervals for individual coefficients with close to nominal coverage probabilities in most of the examined conditions. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

  12. Correlation dimension based nonlinear analysis of network traffics with different application protocols

    International Nuclear Information System (INIS)

    Wang Jun-Song; Yuan Jing; Li Qiang; Yuan Rui-Xi

    2011-01-01

    This paper uses a correlation dimension based nonlinear analysis approach to analyse the dynamics of network traffics with three different application protocols—HTTP, FTP and SMTP. First, the phase space is reconstructed and the embedding parameters are obtained by the mutual information method. Secondly, the correlation dimensions of three different traffics are calculated and the results of analysis have demonstrated that the dynamics of the three different application protocol traffics is different from each other in nature, i.e. HTTP and FTP traffics are chaotic, furthermore, the former is more complex than the later; on the other hand, SMTP traffic is stochastic. It is shown that correlation dimension approach is an efficient method to understand and to characterize the nonlinear dynamics of HTTP, FTP and SMTP protocol network traffics. This analysis provided insight into and a more accurate understanding of nonlinear dynamics of internet traffics which have a complex mixture of chaotic and stochastic components. (general)

  13. Ignoring correlation in uncertainty and sensitivity analysis in life cycle assessment: what is the risk?

    Energy Technology Data Exchange (ETDEWEB)

    Groen, E.A., E-mail: Evelyne.Groen@gmail.com [Wageningen University, P.O. Box 338, Wageningen 6700 AH (Netherlands); Heijungs, R. [Vrije Universiteit Amsterdam, De Boelelaan 1105, Amsterdam 1081 HV (Netherlands); Leiden University, Einsteinweg 2, Leiden 2333 CC (Netherlands)

    2017-01-15

    Life cycle assessment (LCA) is an established tool to quantify the environmental impact of a product. A good assessment of uncertainty is important for making well-informed decisions in comparative LCA, as well as for correctly prioritising data collection efforts. Under- or overestimation of output uncertainty (e.g. output variance) will lead to incorrect decisions in such matters. The presence of correlations between input parameters during uncertainty propagation, can increase or decrease the the output variance. However, most LCA studies that include uncertainty analysis, ignore correlations between input parameters during uncertainty propagation, which may lead to incorrect conclusions. Two approaches to include correlations between input parameters during uncertainty propagation and global sensitivity analysis were studied: an analytical approach and a sampling approach. The use of both approaches is illustrated for an artificial case study of electricity production. Results demonstrate that both approaches yield approximately the same output variance and sensitivity indices for this specific case study. Furthermore, we demonstrate that the analytical approach can be used to quantify the risk of ignoring correlations between input parameters during uncertainty propagation in LCA. We demonstrate that: (1) we can predict if including correlations among input parameters in uncertainty propagation will increase or decrease output variance; (2) we can quantify the risk of ignoring correlations on the output variance and the global sensitivity indices. Moreover, this procedure requires only little data. - Highlights: • Ignoring correlation leads to under- or overestimation of the output variance. • We demonstrated that the risk of ignoring correlation can be quantified. • The procedure proposed is generally applicable in life cycle assessment. • In some cases, ignoring correlation has a minimal effect on decision-making tools.

  14. Econometric analysis of realized covariation: high frequency based covariance, regression, and correlation in financial economics

    DEFF Research Database (Denmark)

    Barndorff-Nielsen, Ole Eiler; Shephard, N.

    2004-01-01

    This paper analyses multivariate high frequency financial data using realized covariation. We provide a new asymptotic distribution theory for standard methods such as regression, correlation analysis, and covariance. It will be based on a fixed interval of time (e.g., a day or week), allowing...... the number of high frequency returns during this period to go to infinity. Our analysis allows us to study how high frequency correlations, regressions, and covariances change through time. In particular we provide confidence intervals for each of these quantities....

  15. Generalized Correlation Coefficient for Non-Parametric Analysis of Microarray Time-Course Data.

    Science.gov (United States)

    Tan, Qihua; Thomassen, Mads; Burton, Mark; Mose, Kristian Fredløv; Andersen, Klaus Ejner; Hjelmborg, Jacob; Kruse, Torben

    2017-06-06

    Modeling complex time-course patterns is a challenging issue in microarray study due to complex gene expression patterns in response to the time-course experiment. We introduce the generalized correlation coefficient and propose a combinatory approach for detecting, testing and clustering the heterogeneous time-course gene expression patterns. Application of the method identified nonlinear time-course patterns in high agreement with parametric analysis. We conclude that the non-parametric nature in the generalized correlation analysis could be an useful and efficient tool for analyzing microarray time-course data and for exploring the complex relationships in the omics data for studying their association with disease and health.

  16. Similarity analysis between chromosomes of Homo sapiens and monkeys with correlation coefficient, rank correlation coefficient and cosine similarity measures

    OpenAIRE

    Someswara Rao, Chinta; Viswanadha Raju, S.

    2016-01-01

    In this paper, we consider correlation coefficient, rank correlation coefficient and cosine similarity measures for evaluating similarity between Homo sapiens and monkeys. We used DNA chromosomes of genome wide genes to determine the correlation between the chromosomal content and evolutionary relationship. The similarity among the H. sapiens and monkeys is measured for a total of 210 chromosomes related to 10 species. The similarity measures of these different species show the relationship b...

  17. Correlation Factor Analysis of Retinal Microvascular Changes in Patients With Essential Hypertension

    Institute of Scientific and Technical Information of China (English)

    Huang Duru; Huang Zhongning

    2006-01-01

    Objectives To investigate correlation between retinal microvascular signs and essential hypertension classification. Methods The retinal microvascular signs in patients with essential hypertension were assessed with the indirect biomicroscopy lens, the direct and the indirect ophthalmoscopes were used to determine the hypertensive retinopathy grades and retinal arteriosclerosis grades.The rank correlation analysis was used to analysis the correlation these grades with the risk factors concerned with hypertension. Results Of 72 cases with essential hypertension, 28 cases complicated with coronary disease, 20 cases diabetes, 41 cases stroke,17 cases renal malfunction. Varying extent retinal arterioscleroses were found in 71 cases, 1 case with retinal hemorrhage, 2 cases with retina edema, 4 cases with retinal hard exudation, 5 cases with retinal hemorrhage complicated by hard exudation, 2 cases with retinal hemorrhage complicated by hard exudation and cotton wool spot, 1 case with retinal hemorrhage complicated by hard exudation and microaneurysms,1 case with retinal edema and hard exudation, 1 case with retinal microaneurysms, 1 case with branch retinal vein occlusion. The rank correlation analysis showed that either hypertensive retinopathy grades or retinal arteriosclerosis grades were correlated with risk factor lamination of hypertension (r=0.25 or 0.31, P<0.05), other correlation factors included age and blood high density lipoprotein concerned about hypertensive retinopathy grades or retinal arteriosclerosis grades, but other parameters, namely systolic or diastolic pressure, total cholesterol, triglyceride, low density lipoprotein cholesterol, fasting blood glucose,blood urea nitrogen and blood creatinine were not confirmed in this correlation analysis (P > 0.05).Conclusions Either hypertensive retinopathy grade or retinal arteriosclerosis grade is close with the hypertension risk factor lamination, suggesting that the fundus examination of patients with

  18. Bleed-through correction for rendering and correlation analysis in multi-colour localization microscopy

    International Nuclear Information System (INIS)

    Kim, Dahan; Curthoys, Nikki M; Parent, Matthew T; Hess, Samuel T

    2013-01-01

    Multi-colour localization microscopy has enabled sub-diffraction studies of colocalization between multiple biological species and quantification of their correlation at length scales previously inaccessible with conventional fluorescence microscopy. However, bleed-through, or misidentification of probe species, creates false colocalization and artificially increases certain types of correlation between two imaged species, affecting the reliability of information provided by colocalization and quantified correlation. Despite the potential risk of these artefacts of bleed-through, neither the effect of bleed-through on correlation nor methods for its correction in correlation analyses have been systematically studied at typical rates of bleed-through reported to affect multi-colour imaging. Here, we present a reliable method of bleed-through correction applicable to image rendering and correlation analysis of multi-colour localization microscopy. Application of our bleed-through correction shows that our method accurately corrects the artificial increase in both types of correlation studied (Pearson coefficient and pair correlation), at all rates of bleed-through tested, in all types of correlation examined. In particular, anti-correlation could not be quantified without our bleed-through correction, even at rates of bleed-through as low as 2%. While it is demonstrated with dichroic-based multi-colour FPALM here, our presented method of bleed-through correction can be applied to all types of localization microscopy (PALM, STORM, dSTORM, GSDIM, etc), including both simultaneous and sequential multi-colour modalities, provided the rate of bleed-through can be reliably determined. (special issue article)

  19. Importance analysis for models with correlated variables and its sparse grid solution

    International Nuclear Information System (INIS)

    Li, Luyi; Lu, Zhenzhou

    2013-01-01

    For structural models involving correlated input variables, a novel interpretation for variance-based importance measures is proposed based on the contribution of the correlated input variables to the variance of the model output. After the novel interpretation of the variance-based importance measures is compared with the existing ones, two solutions of the variance-based importance measures of the correlated input variables are built on the sparse grid numerical integration (SGI): double-loop nested sparse grid integration (DSGI) method and single loop sparse grid integration (SSGI) method. The DSGI method solves the importance measure by decreasing the dimensionality of the input variables procedurally, while SSGI method performs importance analysis through extending the dimensionality of the inputs. Both of them can make full use of the advantages of the SGI, and are well tailored for different situations. By analyzing the results of several numerical and engineering examples, it is found that the novel proposed interpretation about the importance measures of the correlated input variables is reasonable, and the proposed methods for solving importance measures are efficient and accurate. -- Highlights: •The contribution of correlated variables to the variance of the output is analyzed. •A novel interpretation for variance-based indices of correlated variables is proposed. •Two solutions for variance-based importance measures of correlated variables are built

  20. Dysregulated Pathway Identification of Alzheimer's Disease Based on Internal Correlation Analysis of Genes and Pathways.

    Science.gov (United States)

    Kong, Wei; Mou, Xiaoyang; Di, Benteng; Deng, Jin; Zhong, Ruxing; Wang, Shuaiqun

    2017-11-20

    Dysregulated pathway identification is an important task which can gain insight into the underlying biological processes of disease. Current pathway-identification methods focus on a set of co-expression genes and single pathways and ignore the correlation between genes and pathways. The method proposed in this study, takes into account the internal correlations not only between genes but also pathways to identifying dysregulated pathways related to Alzheimer's disease (AD), the most common form of dementia. In order to find the significantly differential genes for AD, mutual information (MI) is used to measure interdependencies between genes other than expression valves. Then, by integrating the topology information from KEGG, the significant pathways involved in the feature genes are identified. Next, the distance correlation (DC) is applied to measure the pairwise pathway crosstalks since DC has the advantage of detecting nonlinear correlations when compared to Pearson correlation. Finally, the pathway pairs with significantly different correlations between normal and AD samples are known as dysregulated pathways. The molecular biology analysis demonstrated that many dysregulated pathways related to AD pathogenesis have been discovered successfully by the internal correlation detection. Furthermore, the insights of the dysregulated pathways in the development and deterioration of AD will help to find new effective target genes and provide important theoretical guidance for drug design. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

  1. Time Correlations of Lightning Flash Sequences in Thunderstorms Revealed by Fractal Analysis

    Science.gov (United States)

    Gou, Xueqiang; Chen, Mingli; Zhang, Guangshu

    2018-01-01

    By using the data of lightning detection and ranging system at the Kennedy Space Center, the temporal fractal and correlation of interevent time series of lightning flash sequences in thunderstorms have been investigated with Allan factor (AF), Fano factor (FF), and detrended fluctuation analysis (DFA) methods. AF, FF, and DFA methods are powerful tools to detect the time-scaling structures and correlations in point processes. Totally 40 thunderstorms with distinguishing features of a single-cell storm and apparent increase and decrease in the total flash rate were selected for the analysis. It is found that the time-scaling exponents for AF (αAF) and FF (αFF) analyses are 1.62 and 0.95 in average, respectively, indicating a strong time correlation of the lightning flash sequences. DFA analysis shows that there is a crossover phenomenon—a crossover timescale (τc) ranging from 54 to 195 s with an average of 114 s. The occurrence of a lightning flash in a thunderstorm behaves randomly at timescales τc but shows strong time correlation at scales >τc. Physically, these may imply that the establishment of an extensive strong electric field necessary for the occurrence of a lightning flash needs a timescale >τc, which behaves strongly time correlated. But the initiation of a lightning flash within a well-established extensive strong electric field may involve the heterogeneities of the electric field at a timescale τc, which behave randomly.

  2. A new detrended semipartial cross-correlation analysis: Assessing the important meteorological factors affecting API

    Energy Technology Data Exchange (ETDEWEB)

    Shen, Chen-Hua, E-mail: shenandchen01@163.com [College of Geographical Science, Nanjing Normal University, Nanjing 210046 (China); Jiangsu Center for Collaborative Innovation in Geographical Information Resource, Nanjing 210046 (China); Key Laboratory of Virtual Geographic Environment of Ministry of Education, Nanjing 210046 (China)

    2015-12-04

    To analyze the unique contribution of meteorological factors to the air pollution index (API), a new method, the detrended semipartial cross-correlation analysis (DSPCCA), is proposed. Based on both a detrended cross-correlation analysis and a DFA-based multivariate-linear-regression (DMLR), this method is improved by including a semipartial correlation technique, which is used to indicate the unique contribution of an explanatory variable to multiple correlation coefficients. The advantages of this method in handling nonstationary time series are illustrated by numerical tests. To further demonstrate the utility of this method in environmental systems, new evidence of the primary contribution of meteorological factors to API is provided through DMLR. Results show that the most important meteorological factors affecting API are wind speed and diurnal temperature range, and the explanatory ability of meteorological factors to API gradually strengthens with increasing time scales. The results suggest that DSPCCA is a useful method for addressing environmental systems. - Highlights: • A detrended multiple linear regression is shown. • A detrended semipartial cross correlation analysis is proposed. • The important meteorological factors affecting API are assessed. • The explanatory ability of meteorological factors to API gradually strengthens with increasing time scales.

  3. A new detrended semipartial cross-correlation analysis: Assessing the important meteorological factors affecting API

    International Nuclear Information System (INIS)

    Shen, Chen-Hua

    2015-01-01

    To analyze the unique contribution of meteorological factors to the air pollution index (API), a new method, the detrended semipartial cross-correlation analysis (DSPCCA), is proposed. Based on both a detrended cross-correlation analysis and a DFA-based multivariate-linear-regression (DMLR), this method is improved by including a semipartial correlation technique, which is used to indicate the unique contribution of an explanatory variable to multiple correlation coefficients. The advantages of this method in handling nonstationary time series are illustrated by numerical tests. To further demonstrate the utility of this method in environmental systems, new evidence of the primary contribution of meteorological factors to API is provided through DMLR. Results show that the most important meteorological factors affecting API are wind speed and diurnal temperature range, and the explanatory ability of meteorological factors to API gradually strengthens with increasing time scales. The results suggest that DSPCCA is a useful method for addressing environmental systems. - Highlights: • A detrended multiple linear regression is shown. • A detrended semipartial cross correlation analysis is proposed. • The important meteorological factors affecting API are assessed. • The explanatory ability of meteorological factors to API gradually strengthens with increasing time scales.

  4. The effects of observational correlated noises on multifractal detrended fluctuation analysis

    Science.gov (United States)

    Gulich, Damián; Zunino, Luciano

    2012-08-01

    We have numerically investigated the effects that observational correlated noises have on the generalized Hurst exponents, h(q), estimated by using the multifractal generalization of detrended fluctuation analysis (MF-DFA). More precisely, artificially generated stochastic binomial multifractals with increased amount of colored noises were analyzed via MF-DFA. It has been recently shown that for moderate additions of white noise, the generalized Hurst exponents are significantly underestimated for qeffects of additive noise, short- term memory and periodic trends, Physica A 390 (2011) 2480-2490]. In this paper, we have found that h(q) with q≥2 are also affected when correlated noises are considered. This is due to the fact that the spurious correlations influence the scaling behaviors associated to large fluctuations. The results obtained are significant for practical situations, where noises with different correlations are inherently present.

  5. Statistical analysis of solid waste composition data: Arithmetic mean, standard deviation and correlation coefficients

    DEFF Research Database (Denmark)

    Edjabou, Maklawe Essonanawe; Martín-Fernández, Josep Antoni; Scheutz, Charlotte

    2017-01-01

    -derived food waste amounted to 2.21 ± 3.12% with a confidence interval of (−4.03; 8.45), which highlights the problem of the biased negative proportions. A Pearson’s correlation test, applied to waste fraction generation (kg mass), indicated a positive correlation between avoidable vegetable food waste...... and plastic packaging. However, correlation tests applied to waste fraction compositions (percentage values) showed a negative association in this regard, thus demonstrating that statistical analyses applied to compositional waste fraction data, without addressing the closed characteristics of these data......, have the potential to generate spurious or misleading results. Therefore, ¨compositional data should be transformed adequately prior to any statistical analysis, such as computing mean, standard deviation and correlation coefficients....

  6. A study on the effect of the CHF correlations to the LOCA analysis

    International Nuclear Information System (INIS)

    Kim, Ho Kee

    1998-02-01

    The critical heat flux (CHF) is a major parameter which determines the cooling performance and therefore the prediction of CHF is of importance for the design and safety analysis in boiling systems; such as nuclear reactors, conventional boilers, and other various two-phase flow systems. Until now, many CHF correlations have been developed and for the actual design a correlation has been selected in consideration of its characteristics. For the analysis of Loss of Coolant Accident (LOCA) in a Nuclear Power Plant, which shows the drastic parameters change during the system transient, a correlation having a reasonable degree of accuracy over a wide range is preferred, rather than that having accuracy for a specific range. It is required to have tangible insight about the effects of the CHF correlation to the LOCA analysis for the purpose of computer code development and nuclear regulation. The related research is further recommended. The purpose of this research is to obtain an insight and/or intuition about the above effect and to evaluate the selected CHF correlations. To achieve these purposes LOCA is analysed for the UL-JIN 3 and 4 nuclear power plant, the Korea Standard Type Nuclear Power Plant and the Loss of Flow Test (LOFT) L2-5 experiment is simulated using the RELAP5/MOD3.1 computer code for each selected CHF correlation. The selected correlations are the AECL-UO Lookup Table, adapted in RELAP5 code; the K110 CHF correlation, developed by KAERI; and the original W-3 CHF correlation, developed by L.S. Tong. LOFT is also simulated using the AECL-UO Lookup Table having the CHF multiplication factors 0.5 and 1.5, and then compared with the result of the original Lookup Table and the experiment result. In the LOCA analysis, the CHF correlations affect the magnitude of peak cladding temperatures, but does not seriously affect the occurrence points of time. The effect of each CHF correlation to the fuel cladding temperature behavior becomes apparent at the end of

  7. Diagrammatic analysis of correlations in polymer fluids: Cluster diagrams via Edwards' field theory

    International Nuclear Information System (INIS)

    Morse, David C.

    2006-01-01

    Edwards' functional integral approach to the statistical mechanics of polymer liquids is amenable to a diagrammatic analysis in which free energies and correlation functions are expanded as infinite sums of Feynman diagrams. This analysis is shown to lead naturally to a perturbative cluster expansion that is closely related to the Mayer cluster expansion developed for molecular liquids by Chandler and co-workers. Expansion of the functional integral representation of the grand-canonical partition function yields a perturbation theory in which all quantities of interest are expressed as functionals of a monomer-monomer pair potential, as functionals of intramolecular correlation functions of non-interacting molecules, and as functions of molecular activities. In different variants of the theory, the pair potential may be either a bare or a screened potential. A series of topological reductions yields a renormalized diagrammatic expansion in which collective correlation functions are instead expressed diagrammatically as functionals of the true single-molecule correlation functions in the interacting fluid, and as functions of molecular number density. Similar renormalized expansions are also obtained for a collective Ornstein-Zernicke direct correlation function, and for intramolecular correlation functions. A concise discussion is given of the corresponding Mayer cluster expansion, and of the relationship between the Mayer and perturbative cluster expansions for liquids of flexible molecules. The application of the perturbative cluster expansion to coarse-grained models of dense multi-component polymer liquids is discussed, and a justification is given for the use of a loop expansion. As an example, the formalism is used to derive a new expression for the wave-number dependent direct correlation function and recover known expressions for the intramolecular two-point correlation function to first-order in a renormalized loop expansion for coarse-grained models of

  8. Prospects of Frequency-Time Correlation Analysis for Detecting Pipeline Leaks by Acoustic Emission Method

    International Nuclear Information System (INIS)

    Faerman, V A; Cheremnov, A G; Avramchuk, V V; Luneva, E E

    2014-01-01

    In the current work the relevance of nondestructive test method development applied for pipeline leak detection is considered. It was shown that acoustic emission testing is currently one of the most widely spread leak detection methods. The main disadvantage of this method is that it cannot be applied in monitoring long pipeline sections, which in its turn complicates and slows down the inspection of the line pipe sections of main pipelines. The prospects of developing alternative techniques and methods based on the use of the spectral analysis of signals were considered and their possible application in leak detection on the basis of the correlation method was outlined. As an alternative, the time-frequency correlation function calculation is proposed. This function represents the correlation between the spectral components of the analyzed signals. In this work, the technique of time-frequency correlation function calculation is described. The experimental data that demonstrate obvious advantage of the time-frequency correlation function compared to the simple correlation function are presented. The application of the time-frequency correlation function is more effective in suppressing the noise components in the frequency range of the useful signal, which makes maximum of the function more pronounced. The main drawback of application of the time- frequency correlation function analysis in solving leak detection problems is a great number of calculations that may result in a further increase in pipeline time inspection. However, this drawback can be partially reduced by the development and implementation of efficient algorithms (including parallel) of computing the fast Fourier transform using computer central processing unit and graphic processing unit

  9. T2 relaxation time analysis in patients with multiple sclerosis: correlation with magnetization transfer ratio

    International Nuclear Information System (INIS)

    Papanikolaou, Nickolas; Papadaki, Eufrosini; Karampekios, Spyros; Maris, Thomas; Prassopoulos, Panos; Gourtsoyiannis, Nicholas; Spilioti, Martha

    2004-01-01

    The aim of the current study was to perform T2 relaxation time measurements in multiple sclerosis (MS) patients and correlate them with magnetization transfer ratio (MTR) measurements, in order to investigate in more detail the various histopathological changes that occur in lesions and normal-appearing white matter (NAWM). A total number of 291 measurements of MTR and T2 relaxation times were performed in 13 MS patients and 10 age-matched healthy volunteers. Measurements concerned MS plaques (105), NAWM (80), and ''dirty'' white matter (DWM; 30), evenly divided between the MS patients, and normal white matter (NWM; 76) in the healthy volunteers. Biexponential T2 relaxation-time analysis was performed, and also possible linearity between MTR and mean T2 relaxation times was evaluated using linear regression analysis in all subgroups. Biexponential relaxation was more pronounced in ''black-hole'' lesions (16.6%) and homogeneous enhancing plaques (10%), whereas DWM, NAWM, and mildly hypointense lesions presented biexponential behavior with a lower frequency(6.6, 5, and 3.1%, respectively). Non-enhancing isointense lesions and normal white matter did not reveal any biexponentional behavior. Linear regression analysis between monoexponential T2 relaxation time and MTR measurements demonstrated excellent correlation for DWM(r=-0.78, p<0.0001), very good correlation for black-hole lesions(r=-0.71, p=0.002), good correlation for isointense lesions(r=-0.60, p=0.005), moderate correlation for mildly hypointense lesions(r=-0.34, p=0.007), and non-significant correlation for homogeneous enhancing plaques, NAWM, and NWM. Biexponential T2 relaxation-time behavior is seen in only very few lesions (mainly on plaques with high degree of demyelination and axonal loss). A strong correlation between MTR and monoexponential T2 values was found in regions where either inflammation or demyelination predominates; however, when both pathological conditions coexist, this linear

  10. Error analysis of supercritical water correlations using ATHLET system code under DHT conditions

    Energy Technology Data Exchange (ETDEWEB)

    Samuel, J., E-mail: jeffrey.samuel@uoit.ca [Univ. of Ontario Inst. of Tech., Oshawa, ON (Canada)

    2014-07-01

    The thermal-hydraulic computer code ATHLET (Analysis of THermal-hydraulics of LEaks and Transients) is used for analysis of anticipated and abnormal plant transients, including safety analysis of Light Water Reactors (LWRs) and Russian Graphite-Moderated High Power Channel-type Reactors (RBMKs). The range of applicability of ATHLET has been extended to supercritical water by updating the fluid-and transport-properties packages, thus enabling the code to the used in analysis of SuperCritical Water-cooled Reactors (SCWRs). Several well-known heat-transfer correlations for supercritical fluids were added to the ATHLET code and a numerical model was created to represent an experimental test section. In this work, the error in the Heat Transfer Coefficient (HTC) calculation by the ATHLET model is studied along with the ability of the various correlations to predict different heat transfer regimes. (author)

  11. Multiset Canonical Correlations Analysis and Multispectral, Truly Multitemporal Remote Sensing Data

    DEFF Research Database (Denmark)

    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...... of the original variables within sets which means, for example, that the R-mode CVs are insensitive to changes over time in offset and gain in a measuring device. In a case study CVs are calculated from Landsat TM data with six spectral bands over six consecutive years. Both R- and T-mode CVs clearly exhibit...

  12. Research on criticality analysis method of CNC machine tools components under fault rate correlation

    Science.gov (United States)

    Gui-xiang, Shen; Xian-zhuo, Zhao; Zhang, Ying-zhi; Chen-yu, Han

    2018-02-01

    In order to determine the key components of CNC machine tools under fault rate correlation, a system component criticality analysis method is proposed. Based on the fault mechanism analysis, the component fault relation is determined, and the adjacency matrix is introduced to describe it. Then, the fault structure relation is hierarchical by using the interpretive structure model (ISM). Assuming that the impact of the fault obeys the Markov process, the fault association matrix is described and transformed, and the Pagerank algorithm is used to determine the relative influence values, combined component fault rate under time correlation can obtain comprehensive fault rate. Based on the fault mode frequency and fault influence, the criticality of the components under the fault rate correlation is determined, and the key components are determined to provide the correct basis for equationting the reliability assurance measures. Finally, taking machining centers as an example, the effectiveness of the method is verified.

  13. Correlation analysis of trace elemental data obtained from blood sera of ovarian cancer patients using PIXE

    International Nuclear Information System (INIS)

    Naidu, B.G.; Sarita, P.; Naga Raju, G.J.

    2017-01-01

    Proton induced X-ray emission (PIXE) technique is used for analysis of trace elements present in the blood sera of ovarian cancer patients and healthy controls. This work is also intended to establish the role played by trace elements in carcinogenic process. It is observed that the concentrations of elements Ti, V, Cr, Mn, Fe, Ni, Rb and Sr are lower and the concentration of Cu is higher in the cancer patients when compared to controls. However, no change in concentration is found in the elements Co, Zn, As, Se and Br. Correlation analysis of the data using SPSS 16.0 has revealed a strong positive correlation between Ti-V, Ni-Co, Cu-Fe, As-Ti, Br-Ti, Br-V and Sr-Fe while strong negative correlations are observed for Cu-Ti, As-Cu and Br-Cu. Changes in trace elemental content are probably associated with ovarian carcinogenesis. (author)

  14. Personality disorders in substance abusers: Validation of the DIP-Q through principal components factor analysis and canonical correlation analysis

    Directory of Open Access Journals (Sweden)

    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.

  15. Pyrcca: regularized kernel canonical correlation analysis in Python and its applications to neuroimaging

    OpenAIRE

    Natalia Y Bilenko; Jack L Gallant; Jack L Gallant

    2016-01-01

    In this article we introduce Pyrcca, an open-source Python package for performing canonical correlation analysis (CCA). CCA is a multivariate analysis method for identifying relationships between sets of variables. Pyrcca supports CCA with or without regularization, and with or without linear, polynomial, or Gaussian kernelization. We first use an abstract example to describe Pyrcca functionality. We then demonstrate how Pyrcca can be used to analyze neuroimaging data. Specifically, we use Py...

  16. A study on association and correlation of lip and finger print pattern analysis for gender identification

    Directory of Open Access Journals (Sweden)

    Surapaneni Ratheesh Kumar Nandan

    2015-01-01

    Conclusion: Lip print analysis is a challenging area in the personal identification during forensic dentistry examination. The study revealed the weaker correlation and approachable significance of lip and finger print pattern in gender identification. Future studies should be encouraged in the direction of software based identification for lip and finger print analysis in gender identification. Such studies may benefit this study pattern in more accurate way.

  17. Generalized Correlation Coefficient for Non-Parametric Analysis of Microarray Time-Course Data

    DEFF Research Database (Denmark)

    Tan, Qihua; Thomassen, Mads; Burton, Mark

    2017-01-01

    the heterogeneous time-course gene expression patterns. Application of the method identified nonlinear time-course patterns in high agreement with parametric analysis. We conclude that the non-parametric nature in the generalized correlation analysis could be an useful and efficient tool for analyzing microarray...... time-course data and for exploring the complex relationships in the omics data for studying their association with disease and health....

  18. Phase synchronization based minimum spanning trees for analysis of financial time series with nonlinear correlations

    Science.gov (United States)

    Radhakrishnan, Srinivasan; Duvvuru, Arjun; Sultornsanee, Sivarit; Kamarthi, Sagar

    2016-02-01

    The cross correlation coefficient has been widely applied in financial time series analysis, in specific, for understanding chaotic behaviour in terms of stock price and index movements during crisis periods. To better understand time series correlation dynamics, the cross correlation matrices are represented as networks, in which a node stands for an individual time series and a link indicates cross correlation between a pair of nodes. These networks are converted into simpler trees using different schemes. In this context, Minimum Spanning Trees (MST) are the most favoured tree structures because of their ability to preserve all the nodes and thereby retain essential information imbued in the network. Although cross correlations underlying MSTs capture essential information, they do not faithfully capture dynamic behaviour embedded in the time series data of financial systems because cross correlation is a reliable measure only if the relationship between the time series is linear. To address the issue, this work investigates a new measure called phase synchronization (PS) for establishing correlations among different time series which relate to one another, linearly or nonlinearly. In this approach the strength of a link between a pair of time series (nodes) is determined by the level of phase synchronization between them. We compare the performance of phase synchronization based MST with cross correlation based MST along selected network measures across temporal frame that includes economically good and crisis periods. We observe agreement in the directionality of the results across these two methods. They show similar trends, upward or downward, when comparing selected network measures. Though both the methods give similar trends, the phase synchronization based MST is a more reliable representation of the dynamic behaviour of financial systems than the cross correlation based MST because of the former's ability to quantify nonlinear relationships among time

  19. The discriminatory analysis about factors correlative with the early hypothyroidism after 131I therapy for hyperthyroidism

    International Nuclear Information System (INIS)

    Xiong Lingjing; Liang Changhua; Deng Haoyu; Li Xinhui; Hu Shuo

    2002-01-01

    Objective: To explore the factors correlative with the early hypothyroidism after 131 I therapy for Graves' hyperthyroidism so as to cure it and decrease the early hypothyroidism occurring and prevent it from becoming irreversible hypothyroidism. Methods: Logistic regression discriminatory analysis by introducing multiple factors from group data and forward stepwise selection of 11 independent variables of 240 hyperthyroidism patients from clinical data and 1 dependent variable from follow-up data after 131 I therapy was conducted. Univariate analysis of each observed factor was performed, too. Results: (1)The results of multivariate analysis showed that the age of patients, the weight of thyroid, the suffering situation, the curve of 131 I absorption rate and the giving 131 I dosage/g thyroid tissue were correlated to early hypothyroidism. The results of univariate analysis showed that the weight of thyroid, the highest absorption of 131 I, the total treatment dosage of 131 I were correlated to early hypothyroidism. (2) The logistic regression equation was statistically significant. (3) The positive and negative predicting accuracy of the early hypothyroidism occurring was 64.08 %, 78.83 %, respectively, the overall predicting accuracy was 72.50%. Conclusions: The dosage of 131 I for treatment of hyperthyroid is the key factor according to the five correlative factors which are relating to the early hypothyroidism and the discriminatory classification. Enhanced follow-up and in time supplement of thyroid hormone are important measures for preventing the early hypothyroidism from becoming irreversible hypothyroidism

  20. Denial-of-service attack detection based on multivariate correlation analysis

    NARCIS (Netherlands)

    Tan, Zhiyuan; Jamdagni, Aruna; He, Xiangjian; Nanda, Priyadarsi; Liu, Ren Ping; Lu, Bao-Liang; Zhang, Liqing; Kwok, James

    2011-01-01

    The reliability and availability of network services are being threatened by the growing number of Denial-of-Service (DoS) attacks. Effective mechanisms for DoS attack detection are demanded. Therefore, we propose a multivariate correlation analysis approach to investigate and extract second-order

  1. Digital image correlation in analysis of striffness in local zones of welded joints

    Czech Academy of Sciences Publication Activity Database

    Milosevic, M.; Milosevic, N.J.; Sedmak, S.; Tatic, U.; Mitrovic, N.; Hloch, Sergej; Jovicic, R.

    2016-01-01

    Roč. 23, č. 1 (2016), s. 19-24 ISSN 1330-3651 Institutional support: RVO:68145535 Keywords : Aramis software * digital image correlation * strain analysis * stiffness * welded joints Subject RIV: JQ - Machines ; Tools Impact factor: 0.723, year: 2016 http://hrcak.srce.hr/file/225545

  2. Generalized canonical analysis based on optimizing matrix correlations and a relation with IDIOSCAL

    NARCIS (Netherlands)

    Kiers, Henk A.L.; Cléroux, R.; Ten Berge, Jos M.F.

    1994-01-01

    Carroll's method for generalized canonical analysis of two or more sets of variables is shown to optimize the sum of squared inner-product matrix correlations between a consensus matrix and matrices with canonical variates for each set of variables. In addition, the method that analogously optimizes

  3. Generalized canonical correlation analysis of matrices with missing rows : A simulation study

    NARCIS (Netherlands)

    van de Velden, Michel; Bijmolt, Tammo H. A.

    A method is presented for generalized canonical correlation analysis of two or more matrices with missing rows. The method is a combination of Carroll's (1968) method and the missing data approach of the OVERALS technique (Van der Burg, 1988). In a simulation study we assess the performance of the

  4. Similarity analysis between chromosomes of Homo sapiens and monkeys with correlation coefficient, rank correlation coefficient and cosine similarity measures.

    Science.gov (United States)

    Someswara Rao, Chinta; Viswanadha Raju, S

    2016-03-01

    In this paper, we consider correlation coefficient, rank correlation coefficient and cosine similarity measures for evaluating similarity between Homo sapiens and monkeys. We used DNA chromosomes of genome wide genes to determine the correlation between the chromosomal content and evolutionary relationship. The similarity among the H. sapiens and monkeys is measured for a total of 210 chromosomes related to 10 species. The similarity measures of these different species show the relationship between the H. sapiens and monkey. This similarity will be helpful at theft identification, maternity identification, disease identification, etc.

  5. Tutorial on Biostatistics: Linear Regression Analysis of Continuous Correlated Eye Data.

    Science.gov (United States)

    Ying, Gui-Shuang; Maguire, Maureen G; Glynn, Robert; Rosner, Bernard

    2017-04-01

    To describe and demonstrate appropriate linear regression methods for analyzing correlated continuous eye data. We describe several approaches to regression analysis involving both eyes, including mixed effects and marginal models under various covariance structures to account for inter-eye correlation. We demonstrate, with SAS statistical software, applications in a study comparing baseline refractive error between one eye with choroidal neovascularization (CNV) and the unaffected fellow eye, and in a study determining factors associated with visual field in the elderly. When refractive error from both eyes were analyzed with standard linear regression without accounting for inter-eye correlation (adjusting for demographic and ocular covariates), the difference between eyes with CNV and fellow eyes was 0.15 diopters (D; 95% confidence interval, CI -0.03 to 0.32D, p = 0.10). Using a mixed effects model or a marginal model, the estimated difference was the same but with narrower 95% CI (0.01 to 0.28D, p = 0.03). Standard regression for visual field data from both eyes provided biased estimates of standard error (generally underestimated) and smaller p-values, while analysis of the worse eye provided larger p-values than mixed effects models and marginal models. In research involving both eyes, ignoring inter-eye correlation can lead to invalid inferences. Analysis using only right or left eyes is valid, but decreases power. Worse-eye analysis can provide less power and biased estimates of effect. Mixed effects or marginal models using the eye as the unit of analysis should be used to appropriately account for inter-eye correlation and maximize power and precision.

  6. The cross-correlation analysis of multi property of stock markets based on MM-DFA

    Science.gov (United States)

    Yang, Yujun; Li, Jianping; Yang, Yimei

    2017-09-01

    In this paper, we propose a new method called DH-MXA based on distribution histograms of Hurst surface and multiscale multifractal detrended fluctuation analysis. The method allows us to investigate the cross-correlation characteristics among multiple properties of different stock time series. It may provide a new way of measuring the nonlinearity of several signals. It also can provide a more stable and faithful description of cross-correlation of multiple properties of stocks. The DH-MXA helps us to present much richer information than multifractal detrented cross-correlation analysis and allows us to assess many universal and subtle cross-correlation characteristics of stock markets. We show DH-MXA by selecting four artificial data sets and five properties of four stock time series from different countries. The results show that our proposed method can be adapted to investigate the cross-correlation of stock markets. In general, the American stock markets are more mature and less volatile than the Chinese stock markets.

  7. Spatial correlation analysis of urban traffic state under a perspective of community detection

    Science.gov (United States)

    Yang, Yanfang; Cao, Jiandong; Qin, Yong; Jia, Limin; Dong, Honghui; Zhang, Aomuhan

    2018-05-01

    Understanding the spatial correlation of urban traffic state is essential for identifying the evolution patterns of urban traffic state. However, the distribution of traffic state always has characteristics of large spatial span and heterogeneity. This paper adapts the concept of community detection to the correlation network of urban traffic state and proposes a new perspective to identify the spatial correlation patterns of traffic state. In the proposed urban traffic network, the nodes represent road segments, and an edge between a pair of nodes is added depending on the result of significance test for the corresponding correlation of traffic state. Further, the process of community detection in the urban traffic network (named GWPA-K-means) is applied to analyze the spatial dependency of traffic state. The proposed method extends the traditional K-means algorithm in two steps: (i) redefines the initial cluster centers by two properties of nodes (the GWPA value and the minimum shortest path length); (ii) utilizes the weight signal propagation process to transfer the topological information of the urban traffic network into a node similarity matrix. Finally, numerical experiments are conducted on a simple network and a real urban road network in Beijing. The results show that GWPA-K-means algorithm is valid in spatial correlation analysis of traffic state. The network science and community structure analysis perform well in describing the spatial heterogeneity of traffic state on a large spatial scale.

  8. Multifractal temporally weighted detrended cross-correlation analysis to quantify power-law cross-correlation and its application to stock markets

    Science.gov (United States)

    Wei, Yun-Lan; Yu, Zu-Guo; Zou, Hai-Long; Anh, Vo

    2017-06-01

    A new method—multifractal temporally weighted detrended cross-correlation analysis (MF-TWXDFA)—is proposed to investigate multifractal cross-correlations in this paper. This new method is based on multifractal temporally weighted detrended fluctuation analysis and multifractal cross-correlation analysis (MFCCA). An innovation of the method is applying geographically weighted regression to estimate local trends in the nonstationary time series. We also take into consideration the sign of the fluctuations in computing the corresponding detrended cross-covariance function. To test the performance of the MF-TWXDFA algorithm, we apply it and the MFCCA method on simulated and actual series. Numerical tests on artificially simulated series demonstrate that our method can accurately detect long-range cross-correlations for two simultaneously recorded series. To further show the utility of MF-TWXDFA, we apply it on time series from stock markets and find that power-law cross-correlation between stock returns is significantly multifractal. A new coefficient, MF-TWXDFA cross-correlation coefficient, is also defined to quantify the levels of cross-correlation between two time series.

  9. Correlation analysis of motor current and chatter vibration in grinding using complex continuous wavelet coherence

    International Nuclear Information System (INIS)

    Liu, Yao; Wang, Xiufeng; Lin, Jing; Zhao, Wei

    2016-01-01

    Motor current is an emerging and popular signal which can be used to detect machining chatter with its multiple advantages. To achieve accurate and reliable chatter detection using motor current, it is important to make clear the quantitative relationship between motor current and chatter vibration, which has not yet been studied clearly. In this study, complex continuous wavelet coherence, including cross wavelet transform and wavelet coherence, is applied to the correlation analysis of motor current and chatter vibration in grinding. Experimental results show that complex continuous wavelet coherence performs very well in demonstrating and quantifying the intense correlation between these two signals in frequency, amplitude and phase. When chatter occurs, clear correlations in frequency and amplitude in the chatter frequency band appear and the phase difference of current signal to vibration signal turns from random to stable. The phase lead of the most correlated chatter frequency is the largest. With the further development of chatter, the correlation grows up in intensity and expands to higher order chatter frequency band. The analyzing results confirm that there is a consistent correlation between motor current and vibration signals in the grinding chatter process. However, to achieve accurate and reliable chatter detection using motor current, the frequency response bandwidth of current loop of the feed drive system must be wide enough to response chatter effectively. (paper)

  10. Inflatable penile prosthesis implant length with baseline characteristic correlations: preliminary analysis of the PROPPER study.

    Science.gov (United States)

    Bennett, Nelson; Henry, Gerard; Karpman, Edward; Brant, William; Jones, LeRoy; Khera, Mohit; Kohler, Tobias; Christine, Brian; Rhee, Eugene; Kansas, Bryan; Bella, Anthony J

    2017-12-01

    "Prospective Registry of Outcomes with Penile Prosthesis for Erectile Restoration" (PROPPER) is a large, multi-institutional, prospective clinical study to collect, analyze, and report real-world outcomes for men implanted with penile prosthetic devices. We prospectively correlated co-morbid conditions and demographic data with implanted penile prosthesis size to enable clinicians to better predict implanted penis size following penile implantation. We present many new data points for the first time in the literature and postulate that radical prostatectomy (RP) is negatively correlated with penile corporal length. Patient demographics, medical history, baseline characteristics and surgical details were compiled prospectively. Pearson correlation coefficient was generated for the correlation between demographic, etiology of ED, duration of ED, co-morbid conditions, pre-operative penile length (flaccid and stretched) and length of implanted penile prosthesis. Multivariate analysis was performed to define predictors of implanted prosthesis length. From June 2011 to June 2017, 1,135 men underwent primary implantation of penile prosthesis at a total of 11 study sites. Malleable (Spectra), 2-piece Ambicor, and 3-piece AMS 700 CX/LGX were included in the analysis. The most common patient comorbidities were CV disease (26.1%), DM (11.1%), and PD (12.4%). Primary etiology of ED: RP (27.4%), DM (20.3%), CVD (18.0%), PD (10.3%), and Priapism (1.4%), others (22.6%). Mean duration of ED is 6.2¡À4.1 years. Implant length was weakly negatively correlated with White/Caucasian (r=-0.18; Pprosthesis length is negatively correlated with some ethnic groups, prostatectomy, and incontinence. Positive correlates include CV disease, preoperative stretched penile length, and flaccid penile length.

  11. Correlation function analysis of the COBE differential microwave radiometer sky maps

    Energy Technology Data Exchange (ETDEWEB)

    Lineweaver, Charles Howe [Univ. of California, Berkeley, CA (United States). Space Sciences Lab.

    1994-08-01

    The Differential Microwave Radiometer (DMR) aboard the COBE satellite has detected anisotropies in the cosmic microwave background (CMB) radiation. A two-point correlation function analysis which helped lead to this discovery is presented in detail. The results of a correlation function analysis of the two year DMR data set is presented. The first and second year data sets are compared and found to be reasonably consistent. The positive correlation for separation angles less than ~20° is robust to Galactic latitude cuts and is very stable from year to year. The Galactic latitude cut independence of the correlation function is strong evidence that the signal is not Galactic in origin. The statistical significance of the structure seen in the correlation function of the first, second and two year maps is respectively > 9σ, > 10σ and > 18σ above the noise. The noise in the DMR sky maps is correlated at a low level. The structure of the pixel temperature covariance matrix is given. The noise covariance matrix of a DMR sky map is diagonal to an accuracy of better than 1%. For a given sky pixel, the dominant noise covariance occurs with the ring of pixels at an angular separation of 60° due to the 60° separation of the DMR horns. The mean covariance of 60° is 0.45%$+0.18\\atop{-0.14}$ of the mean variance. The noise properties of the DMR maps are thus well approximated by the noise properties of maps made by a single-beam experiment. Previously published DMR results are not significantly affected by correlated noise.

  12. Correlation Between Minimum Apparent Diffusion Coefficient (ADCmin) and Tumor Cellularity: A Meta-analysis.

    Science.gov (United States)

    Surov, Alexey; Meyer, Hans Jonas; Wienke, Andreas

    2017-07-01

    Diffusion-weighted imaging (DWI) is a magnetic resonance imaging (MRI) technique based on measure of water diffusion that can provide information about tissue microstructure, especially about cell count. Increase of cell density induces restriction of water diffusion and decreases apparent diffusion coefficient (ADC). ADC can be divided into three sub-parameters: ADC minimum or ADC min , mean ADC or ADC mean and ADC maximum or ADC max Some studies have suggested that ADC min shows stronger correlations with cell count in comparison to other ADC fractions and may be used as a parameter for estimation of tumor cellularity. The aim of the present meta-analysis was to summarize correlation coefficients between ADC min and cellularity in different tumors based on large patient data. For this analysis, MEDLINE database was screened for associations between ADC and cell count in different tumors up to September 2016. For this work, only data regarding ADC min were included. Overall, 12 publications with 317 patients were identified. Spearman's correlation coefficient was used to analyze associations between ADC min and cellularity. The reported Pearson correlation coefficients in some publications were converted into Spearman correlation coefficients. The pooled correlation coefficient for all included studies was ρ=-0.59 (95% confidence interval (CI)=-0.72 to -0.45), heterogeneity Tau 2 =0.04 (pcorrelated moderately with tumor cellularity. The calculated correlation coefficient is not stronger in comparison to the reported coefficient for ADC mean and, therefore, ADC min does not represent a better means to reflect cellularity. Copyright© 2017, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.

  13. Effective and Efficient Correlation Analysis with Application to Market Basket Analysis and Network Community Detection

    Science.gov (United States)

    Duan, Lian

    2012-01-01

    Finding the most interesting correlations among items is essential for problems in many commercial, medical, and scientific domains. For example, what kinds of items should be recommended with regard to what has been purchased by a customer? How to arrange the store shelf in order to increase sales? How to partition the whole social network into…

  14. Correlation, path analysis and heritability estimation for agronomic traits contribute to yield on soybean

    Science.gov (United States)

    Sulistyo, A.; Purwantoro; Sari, K. P.

    2018-01-01

    Selection is a routine activity in plant breeding programs that must be done by plant breeders in obtaining superior plant genotypes. The use of appropriate selection criteria will determine the effectiveness of selection activities. The purpose of this study was to analysis the inheritable agronomic traits that contribute to soybean yield. A total of 91 soybean lines were planted in Muneng Experimental Station, Probolinggo District, East Java Province, Indonesia in 2016. All soybean lines were arranged in randomized complete block design with two replicates. Correlation analysis, path analysis and heritability estimation were performed on days to flowering, days to maturing, plant height, number of branches, number of fertile nodes, number of filled pods, weight of 100 seeds, and yield to determine selection criteria on soybean breeding program. The results showed that the heritability value of almost all agronomic traits observed is high except for the number of fertile nodes with low heritability. The result of correlation analysis shows that days to flowering, plant height and number of fertile nodes have positive correlation with seed yield per plot (0.056, 0.444, and 0.100, respectively). In addition, path analysis showed that plant height and number of fertile nodes have highest positive direct effect on soybean yield. Based on this result, plant height can be selected as one of selection criteria in soybean breeding program to obtain high yielding soybean variety.

  15. Neutron Activation Analysis and Moessbauer Correlations of Archaeological Pottery from Amazon Basin for Classification Studies

    International Nuclear Information System (INIS)

    Bellido, A. V. B.; Latini, R. M.; Nicoli, I.; Scorzelli, R. B.; Solorzano, P. M.

    2011-01-01

    The aim of the present work was to investigate the correlation between data obtained by means of two analytical methods, instrumental neutron activation analysis (INAA) and Moessbauer Spectroscopy of pottery samples combined with multivariate statistical analysis in order to optimize quantitative analysis in the classification studies. Ceramics recently discovered in archaeological earth circular structures sites in Acre state Brazil. 199 samples were analyzed by INAA, allowing simultaneous determination of twenty elements chemical concentrations, and 44 samples by using Moessbauer Spectroscopy, allowing the determination of fourteen hyperfine parameters. For the correlation study, data were treated by two multivariate statistical methods: cluster analysis for the classification and the principal component analysis for the data correlations. INAA data show that some of REE (rare earth elements) were the discriminating variables for this technique. Mossbauer parameters that exhibit the same behavior are being investigated, remarkable improve can be seem for the combined REE and the Mossbauer variables showing a good results considering the limited number of samples. This data matrix is being used for the understanding in the studies of classification and provenance of ceramics prehistory of the Amazonic basin.

  16. Network analysis reveals that bacteria and fungi form modules that correlate independently with soil parameters.

    Science.gov (United States)

    de Menezes, Alexandre B; Prendergast-Miller, Miranda T; Richardson, Alan E; Toscas, Peter; Farrell, Mark; Macdonald, Lynne M; Baker, Geoff; Wark, Tim; Thrall, Peter H

    2015-08-01

    Network and multivariate statistical analyses were performed to determine interactions between bacterial and fungal community terminal restriction length polymorphisms as well as soil properties in paired woodland and pasture sites. Canonical correspondence analysis (CCA) revealed that shifts in woodland community composition correlated with soil dissolved organic carbon, while changes in pasture community composition correlated with moisture, nitrogen and phosphorus. Weighted correlation network analysis detected two distinct microbial modules per land use. Bacterial and fungal ribotypes did not group separately, rather all modules comprised of both bacterial and fungal ribotypes. Woodland modules had a similar fungal : bacterial ribotype ratio, while in the pasture, one module was fungal dominated. There was no correspondence between pasture and woodland modules in their ribotype composition. The modules had different relationships to soil variables, and these contrasts were not detected without the use of network analysis. This study demonstrated that fungi and bacteria, components of the soil microbial communities usually treated as separate functional groups as in a CCA approach, were co-correlated and formed distinct associations in these adjacent habitats. Understanding these distinct modular associations may shed more light on their niche space in the soil environment, and allow a more realistic description of soil microbial ecology and function. © 2014 Society for Applied Microbiology and John Wiley & Sons Ltd.

  17. Robustness analysis of geodetic networks in the case of correlated observations

    Directory of Open Access Journals (Sweden)

    Mevlut Yetkin

    Full Text Available GPS (or GNSS networks are invaluable tools for monitoring natural hazards such as earthquakes. However, blunders in GPS observations may be mistakenly interpreted as deformation. Therefore, robust networks are needed in deformation monitoring using GPS networks. Robustness analysis is a natural merger of reliability and strain and defined as the ability to resist deformations caused by the maximum undetecle errors as determined from internal reliability analysis. However, to obtain rigorously correct results; the correlations among the observations must be considered while computing maximum undetectable errors. Therefore, we propose to use the normalized reliability numbers instead of redundancy numbers (Baarda's approach in robustness analysis of a GPS network. A simple mathematical relation showing the ratio between uncorrelated and correlated cases for maximum undetectable error is derived. The same ratio is also valid for the displacements. Numerical results show that if correlations among observations are ignored, dramatically different displacements can be obtained depending on the size of multiple correlation coefficients. Furthermore, when normalized reliability numbers are small, displacements get large, i.e., observations with low reliability numbers cause bigger displacements compared to observations with high reliability numbers.

  18. Neural Network-Based Coronary Heart Disease Risk Prediction Using Feature Correlation Analysis

    Directory of Open Access Journals (Sweden)

    Jae Kwon Kim

    2017-01-01

    Full Text Available Background. Of the machine learning techniques used in predicting coronary heart disease (CHD, neural network (NN is popularly used to improve performance accuracy. Objective. Even though NN-based systems provide meaningful results based on clinical experiments, medical experts are not satisfied with their predictive performances because NN is trained in a “black-box” style. Method. We sought to devise an NN-based prediction of CHD risk using feature correlation analysis (NN-FCA using two stages. First, the feature selection stage, which makes features acceding to the importance in predicting CHD risk, is ranked, and second, the feature correlation analysis stage, during which one learns about the existence of correlations between feature relations and the data of each NN predictor output, is determined. Result. Of the 4146 individuals in the Korean dataset evaluated, 3031 had low CHD risk and 1115 had CHD high risk. The area under the receiver operating characteristic (ROC curve of the proposed model (0.749 ± 0.010 was larger than the Framingham risk score (FRS (0.393 ± 0.010. Conclusions. The proposed NN-FCA, which utilizes feature correlation analysis, was found to be better than FRS in terms of CHD risk prediction. Furthermore, the proposed model resulted in a larger ROC curve and more accurate predictions of CHD risk in the Korean population than the FRS.

  19. Detection of Impaired Cerebral Autoregulation Using Selected Correlation Analysis: A Validation Study.

    Science.gov (United States)

    Proescholdt, Martin A; Faltermeier, Rupert; Bele, Sylvia; Brawanski, Alexander

    2017-01-01

    Multimodal brain monitoring has been utilized to optimize treatment of patients with critical neurological diseases. However, the amount of data requires an integrative tool set to unmask pathological events in a timely fashion. Recently we have introduced a mathematical model allowing the simulation of pathophysiological conditions such as reduced intracranial compliance and impaired autoregulation. Utilizing a mathematical tool set called selected correlation analysis (sca), correlation patterns, which indicate impaired autoregulation, can be detected in patient data sets (scp). In this study we compared the results of the sca with the pressure reactivity index (PRx), an established marker for impaired autoregulation. Mean PRx values were significantly higher in time segments identified as scp compared to segments showing no selected correlations (nsc). The sca based approach predicted cerebral autoregulation failure with a sensitivity of 78.8% and a specificity of 62.6%. Autoregulation failure, as detected by the results of both analysis methods, was significantly correlated with poor outcome. Sca of brain monitoring data detects impaired autoregulation with high sensitivity and sufficient specificity. Since the sca approach allows the simultaneous detection of both major pathological conditions, disturbed autoregulation and reduced compliance, it may become a useful analysis tool for brain multimodal monitoring data.

  20. Detection of Impaired Cerebral Autoregulation Using Selected Correlation Analysis: A Validation Study

    Directory of Open Access Journals (Sweden)

    Martin A. Proescholdt

    2017-01-01

    Full Text Available Multimodal brain monitoring has been utilized to optimize treatment of patients with critical neurological diseases. However, the amount of data requires an integrative tool set to unmask pathological events in a timely fashion. Recently we have introduced a mathematical model allowing the simulation of pathophysiological conditions such as reduced intracranial compliance and impaired autoregulation. Utilizing a mathematical tool set called selected correlation analysis (sca, correlation patterns, which indicate impaired autoregulation, can be detected in patient data sets (scp. In this study we compared the results of the sca with the pressure reactivity index (PRx, an established marker for impaired autoregulation. Mean PRx values were significantly higher in time segments identified as scp compared to segments showing no selected correlations (nsc. The sca based approach predicted cerebral autoregulation failure with a sensitivity of 78.8% and a specificity of 62.6%. Autoregulation failure, as detected by the results of both analysis methods, was significantly correlated with poor outcome. Sca of brain monitoring data detects impaired autoregulation with high sensitivity and sufficient specificity. Since the sca approach allows the simultaneous detection of both major pathological conditions, disturbed autoregulation and reduced compliance, it may become a useful analysis tool for brain multimodal monitoring data.

  1. Bottomside sinusoidal irregularities in the equatorial F region. II - Cross-correlation and spectral analysis

    Science.gov (United States)

    Cragin, B. L.; Hanson, W. B.; Mcclure, J. P.; Valladares, C. E.

    1985-01-01

    Equatorial bottomside sinusoidal (BSS) irregularities have been studied by applying techniques of cross-correlation and spectral analysis to the Atmosphere Explorer data set. The phase of the cross-correlations of the plasma number density is discussed and the two drift velocity components observed using the retarding potential analyzer and ion drift meter on the satellite are discussed. Morphology is addressed, presenting the geographical distributions of the occurrence of BSS events for the equinoxes and solstices. Physical processes including the ion Larmor flux, interhemispheric plasma flows, and variations in the lower F region Pedersen conductivity are invoked to explain the findings.

  2. Correlation analysis of quantum fluctuations and repulsion effects of classical dynamics in SU(3) model

    International Nuclear Information System (INIS)

    Fujiwara, Shigeyasu; Sakata, Fumihiko

    2003-01-01

    In many quantum systems, random matrix theory has been used to characterize quantum level fluctuations, which is known to be a quantum correspondent to a regular-to-chaos transition in classical systems. We present a new qualitative analysis of quantum and classical fluctuation properties by exploiting correlation coefficients and variances. It is shown that the correlation coefficient of the quantum level density is roughly inversely proportional relation to the variance of consecutive phase-space point spacings on the Poincare section plane. (author)

  3. Detection of non-stationary leak signals at NPP primary circuit by cross-correlation analysis

    International Nuclear Information System (INIS)

    Shimanskij, S.B.

    2007-01-01

    A leak-detection system employing high-temperature microphones has been developed for the RBMK and ATR (Japan) reactors. Further improvement of the system focused on using cross-correlation analysis of the spectral components of the signal to detect a small leak at an early stage of development. Since envelope processes are less affected by distortions than are wave processes, they give a higher-degree of correlation and can be used to detect leaks with lower signal-noise ratios. Many simulation tests performed at nuclear power plants have shown that the proposed methods can be used to detect and find the location of a small leak [ru

  4. Uncertainty evaluation in correlated quantities: application to elemental analysis of atmospheric aerosols

    International Nuclear Information System (INIS)

    Espinosa, A.; Miranda, J.; Pineda, J. C.

    2010-01-01

    One of the aspects that are frequently overlooked in the evaluation of uncertainty in experimental data is the possibility that the involved quantities are correlated among them, due to different causes. An example in the elemental analysis of atmospheric aerosols using techniques like X-ray Fluorescence (X RF) or Particle Induced X-ray Emission (PIXE). In these cases, the measured elemental concentrations are highly correlated, and then are used to obtain information about other variables, such as the contribution from emitting sources related to soil, sulfate, non-soil potassium or organic matter. This work describes, as an example, the method required to evaluate the uncertainty in variables determined from correlated quantities from a set of atmospheric aerosol samples collected in the Metropolitan Area of the Mexico Valley and analyzed with PIXE. The work is based on the recommendations of the Guide for the Evaluation of Uncertainty published by the International Organization for Standardization. (Author)

  5. Multifractal analysis of the long-range correlations in the cardiac dynamics of Drosophila melanogaster

    International Nuclear Information System (INIS)

    Vitanov, Nikolay K.; Yankulova, Elka D.

    2006-01-01

    By means of the multifractal detrended fluctuation analysis (MFDFA) we investigate long-range correlations in the interbeat time series of heart activity of Drosophila melanogaster-the classical object of research in genetics. Our main investigation tool are the fractal spectra f(α) and h(q) by means of which we trace the correlation properties of Drosophila heartbeat dynamics for three consequent generations of species. We observe that opposite to the case of humans the time series of the heartbeat activity of healthy Drosophila do not have scaling properties. Time series from species with genetic defects can be long-range correlated. Different kinds of genetic heart defects lead to different shape of the fractal spectra. The fractal heartbeat dynamics of Drosophila is transferred from generation to generation

  6. Solar activity and terrestrial climate: an analysis of some purported correlations

    DEFF Research Database (Denmark)

    Laut, Peter

    2003-01-01

    claimed to support solar hypotheses. My analyses show that the apparent strong correlations displayed on these graphs have been obtained by an incorrect handling of the physical data. Since the graphs are still widely referred to in the literature and their misleading character has not yet been generally......The last decade has seen a revival of various hypotheses claiming a strong correlation between solar activity and a number of terrestrial climate parameters: Links between cosmic rays and cloud cover, first total cloud cover and then only low clouds, and between solar cycle lengths and Northern...... the existence of important links between solar activity and terrestrial climate. Such links have over the years been demonstrated by many authors. The sole objective of the present analysis is to draw attention to the fact that some of the widely publicized, apparent correlations do not properly reflect...

  7. Analysis of angiography findings in cerebral arteriovenous malformations: Correlation with hemorrhage

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Jae Hyoung; Kim, Hyung Jin; Jung, Jin Myung; Ha, Choong Kun; Chung, Sung Hoon [Gyeongsang National University College of Medicine, Chinju (Korea, Republic of)

    1993-07-15

    Intracerebral hemorrhage is the most serious complication of cerebral arteriovenous malformations (AVM). To identify angiographic characteristics of AVM which correlate with a history of hemorrhage, we retrospectively analyzed angiographic findings of 25 patients with AVM. Nine characteristic were evaluated; these include nidus size, location, arterial aneurysm, intranidal aneurysm, angiomatous change, venous drainage pattern, venous stenosis, delayed drainage and venous ectasia. The characteristic were correlated with hemorrhage,which was seen in 18 (72%) patients on CT or MR images. Venous stenosis (P<0.5) and delaved venous drainage (P<0.5) well correlated with a history of hemorrhage. Arterial aneurysm and intranidal aneurysm also had a tendency hemorrhage although they did not prove to be statistically significant. Detailed analysis of angiographic finding of AVM is important for recognition of characteristic which are related to hemorrhage and may contribute to establishing a prognosis and treatment planning.

  8. Characteristic analysis on UAV-MIMO channel based on normalized correlation matrix.

    Science.gov (United States)

    Gao, Xi jun; Chen, Zi li; Hu, Yong Jiang

    2014-01-01

    Based on the three-dimensional GBSBCM (geometrically based double bounce cylinder model) channel model of MIMO for unmanned aerial vehicle (UAV), the simple form of UAV space-time-frequency channel correlation function which includes the LOS, SPE, and DIF components is presented. By the methods of channel matrix decomposition and coefficient normalization, the analytic formula of UAV-MIMO normalized correlation matrix is deduced. This formula can be used directly to analyze the condition number of UAV-MIMO channel matrix, the channel capacity, and other characteristic parameters. The simulation results show that this channel correlation matrix can be applied to describe the changes of UAV-MIMO channel characteristics under different parameter settings comprehensively. This analysis method provides a theoretical basis for improving the transmission performance of UAV-MIMO channel. The development of MIMO technology shows practical application value in the field of UAV communication.

  9. Design, demonstration and analysis of a modified wavelength-correlating receiver for incoherent OCDMA system.

    Science.gov (United States)

    Zhou, Heng; Qiu, Kun; Wang, Leyang

    2011-03-28

    A novel wavelength-correlating receiver for incoherent Optical Code Division Multiple Access (OCDMA) system is proposed and demonstrated in this paper. Enabled by the wavelength conversion based scheme, the proposed receiver can support various code types including one-dimensional optical codes and time-spreading/wavelength-hopping two dimensional codes. Also, a synchronous detection scheme with time-to- wavelength based code acquisition is proposed, by which code acquisition time can be substantially reduced. Moreover, a novel data-validation methodology based on all-optical pulse-width monitoring is introduced for the wavelength-correlating receiver. Experimental demonstration of the new proposed receiver is presented and low bit error rate data-receiving is achieved without optical hard limiting and electronic power thresholding. For the first time, a detailed theoretical performance analysis specialized for the wavelength-correlating receiver is presented. Numerical results show that the overall performance of the proposed receiver prevails over conventional OCDMA receivers.

  10. Nonlinear Analysis on Cross-Correlation of Financial Time Series by Continuum Percolation System

    Science.gov (United States)

    Niu, Hongli; Wang, Jun

    We establish a financial price process by continuum percolation system, in which we attribute price fluctuations to the investors’ attitudes towards the financial market, and consider the clusters in continuum percolation as the investors share the same investment opinion. We investigate the cross-correlations in two return time series, and analyze the multifractal behaviors in this relationship. Further, we study the corresponding behaviors for the real stock indexes of SSE and HSI as well as the liquid stocks pair of SPD and PAB by comparison. To quantify the multifractality in cross-correlation relationship, we employ multifractal detrended cross-correlation analysis method to perform an empirical research for the simulation data and the real markets data.

  11. A canonical correlation analysis based EMG classification algorithm for eliminating electrode shift effect.

    Science.gov (United States)

    Zhe Fan; Zhong Wang; Guanglin Li; Ruomei Wang

    2016-08-01

    Motion classification system based on surface Electromyography (sEMG) pattern recognition has achieved good results in experimental condition. But it is still a challenge for clinical implement and practical application. Many factors contribute to the difficulty of clinical use of the EMG based dexterous control. The most obvious and important is the noise in the EMG signal caused by electrode shift, muscle fatigue, motion artifact, inherent instability of signal and biological signals such as Electrocardiogram. In this paper, a novel method based on Canonical Correlation Analysis (CCA) was developed to eliminate the reduction of classification accuracy caused by electrode shift. The average classification accuracy of our method were above 95% for the healthy subjects. In the process, we validated the influence of electrode shift on motion classification accuracy and discovered the strong correlation with correlation coefficient of >0.9 between shift position data and normal position data.

  12. Correlation among the spectral parameters for qualitative analysis of Alpha Liquid Scintillation Spectra

    International Nuclear Information System (INIS)

    Bhade, Sonali P.D.; Reddy, P.J.; Kolekar, R.V.; Singh, Rajvir; Pradeepkumar, K.S.

    2014-01-01

    The potential use of alpha LSC technique is nowadays recognized widely. However the energy resolution of α particle is poor with liquid scintillators. Moreover, α peak positions are influenced by the level of quenching in the samples. To overcome this problem, a thorough study of all concerned parameters that affect spectral information was carried out. The parameters such as peak's centroid, quenching, % resolution, energy of α particle were investigated and the correlation between them was evaluated. In the present work, the qualitative analysis of α spectrum was carried out. Correlations between the energy of α particle and various parameters affecting the peaks of the collected spectra with respect to quenching were established. These correlations will be useful for the deconvolution studies of composite samples containing different alpha radionuclides

  13. Outage Performance Analysis of Cooperative Diversity with MRC and SC in Correlated Lognormal Channels

    Directory of Open Access Journals (Sweden)

    Skraparlis D

    2009-01-01

    Full Text Available Abstract The study of relaying systems has found renewed interest in the context of cooperative diversity for communication channels suffering from fading. This paper provides analytical expressions for the end-to-end SNR and outage probability of cooperative diversity in correlated lognormal channels, typically found in indoor and specific outdoor environments. The system under consideration utilizes decode-and-forward relaying and Selection Combining or Maximum Ratio Combining at the destination node. The provided expressions are used to evaluate the gains of cooperative diversity compared to noncooperation in correlated lognormal channels, taking into account the spectral and energy efficiency of the protocols and the half-duplex or full-duplex capability of the relay. Our analysis demonstrates that correlation and lognormal variances play a significant role on the performance gain of cooperative diversity against noncooperation.

  14. fCCAC: functional canonical correlation analysis to evaluate covariance between nucleic acid sequencing datasets.

    Science.gov (United States)

    Madrigal, Pedro

    2017-03-01

    Computational evaluation of variability across DNA or RNA sequencing datasets is a crucial step in genomic science, as it allows both to evaluate reproducibility of biological or technical replicates, and to compare different datasets to identify their potential correlations. Here we present fCCAC, an application of functional canonical correlation analysis to assess covariance of nucleic acid sequencing datasets such as chromatin immunoprecipitation followed by deep sequencing (ChIP-seq). We show how this method differs from other measures of correlation, and exemplify how it can reveal shared covariance between histone modifications and DNA binding proteins, such as the relationship between the H3K4me3 chromatin mark and its epigenetic writers and readers. An R/Bioconductor package is available at http://bioconductor.org/packages/fCCAC/ . pmb59@cam.ac.uk. Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

  15. Analyzing the Cross-Correlation Between Onshore and Offshore RMB Exchange Rates Based on Multifractal Detrended Cross-Correlation Analysis (MF-DCCA)

    Science.gov (United States)

    Xie, Chi; Zhou, Yingying; Wang, Gangjin; Yan, Xinguo

    We use the multifractal detrended cross-correlation analysis (MF-DCCA) method to explore the multifractal behavior of the cross-correlation between exchange rates of onshore RMB (CNY) and offshore RMB (CNH) against US dollar (USD). The empirical data are daily prices of CNY/USD and CNH/USD from May 1, 2012 to February 29, 2016. The results demonstrate that: (i) the cross-correlation between CNY/USD and CNH/USD is persistent and its fluctuation is smaller when the order of fluctuation function is negative than that when the order is positive; (ii) the multifractal behavior of the cross-correlation between CNY/USD and CNH/USD is significant during the sample period; (iii) the dynamic Hurst exponents obtained by the rolling windows analysis show that the cross-correlation is stable when the global economic situation is good and volatile in bad situation; and (iv) the non-normal distribution of original data has a greater effect on the multifractality of the cross-correlation between CNY/USD and CNH/USD than the temporary correlation.

  16. Canonical correlation analysis of synchronous neural interactions and cognitive deficits in Alzheimer's dementia

    Science.gov (United States)

    Karageorgiou, Elissaios; Lewis, Scott M.; Riley McCarten, J.; Leuthold, Arthur C.; Hemmy, Laura S.; McPherson, Susan E.; Rottunda, Susan J.; Rubins, David M.; Georgopoulos, Apostolos P.

    2012-10-01

    In previous work (Georgopoulos et al 2007 J. Neural Eng. 4 349-55) we reported on the use of magnetoencephalographic (MEG) synchronous neural interactions (SNI) as a functional biomarker in Alzheimer's dementia (AD) diagnosis. Here we report on the application of canonical correlation analysis to investigate the relations between SNI and cognitive neuropsychological (NP) domains in AD patients. First, we performed individual correlations between each SNI and each NP, which provided an initial link between SNI and specific cognitive tests. Next, we performed factor analysis on each set, followed by a canonical correlation analysis between the derived SNI and NP factors. This last analysis optimally associated the entire MEG signal with cognitive function. The results revealed that SNI as a whole were mostly associated with memory and language, and, slightly less, executive function, processing speed and visuospatial abilities, thus differentiating functions subserved by the frontoparietal and the temporal cortices. These findings provide a direct interpretation of the information carried by the SNI and set the basis for identifying specific neural disease phenotypes according to cognitive deficits.

  17. Automated vessel segmentation using cross-correlation and pooled covariance matrix analysis.

    Science.gov (United States)

    Du, Jiang; Karimi, Afshin; Wu, Yijing; Korosec, Frank R; Grist, Thomas M; Mistretta, Charles A

    2011-04-01

    Time-resolved contrast-enhanced magnetic resonance angiography (CE-MRA) provides contrast dynamics in the vasculature and allows vessel segmentation based on temporal correlation analysis. Here we present an automated vessel segmentation algorithm including automated generation of regions of interest (ROIs), cross-correlation and pooled sample covariance matrix analysis. The dynamic images are divided into multiple equal-sized regions. In each region, ROIs for artery, vein and background are generated using an iterative thresholding algorithm based on the contrast arrival time map and contrast enhancement map. Region-specific multi-feature cross-correlation analysis and pooled covariance matrix analysis are performed to calculate the Mahalanobis distances (MDs), which are used to automatically separate arteries from veins. This segmentation algorithm is applied to a dual-phase dynamic imaging acquisition scheme where low-resolution time-resolved images are acquired during the dynamic phase followed by high-frequency data acquisition at the steady-state phase. The segmented low-resolution arterial and venous images are then combined with the high-frequency data in k-space and inverse Fourier transformed to form the final segmented arterial and venous images. Results from volunteer and patient studies demonstrate the advantages of this automated vessel segmentation and dual phase data acquisition technique. Copyright © 2011 Elsevier Inc. All rights reserved.

  18. Robust and sparse correlation matrix estimation for the analysis of high-dimensional genomics data.

    Science.gov (United States)

    Serra, Angela; Coretto, Pietro; Fratello, Michele; Tagliaferri, Roberto; Stegle, Oliver

    2018-02-15

    Microarray technology can be used to study the expression of thousands of genes across a number of different experimental conditions, usually hundreds. The underlying principle is that genes sharing similar expression patterns, across different samples, can be part of the same co-expression system, or they may share the same biological functions. Groups of genes are usually identified based on cluster analysis. Clustering methods rely on the similarity matrix between genes. A common choice to measure similarity is to compute the sample correlation matrix. Dimensionality reduction is another popular data analysis task which is also based on covariance/correlation matrix estimates. Unfortunately, covariance/correlation matrix estimation suffers from the intrinsic noise present in high-dimensional data. Sources of noise are: sampling variations, presents of outlying sample units, and the fact that in most cases the number of units is much larger than the number of genes. In this paper, we propose a robust correlation matrix estimator that is regularized based on adaptive thresholding. The resulting method jointly tames the effects of the high-dimensionality, and data contamination. Computations are easy to implement and do not require hand tunings. Both simulated and real data are analyzed. A Monte Carlo experiment shows that the proposed method is capable of remarkable performances. Our correlation metric is more robust to outliers compared with the existing alternatives in two gene expression datasets. It is also shown how the regularization allows to automatically detect and filter spurious correlations. The same regularization is also extended to other less robust correlation measures. Finally, we apply the ARACNE algorithm on the SyNTreN gene expression data. Sensitivity and specificity of the reconstructed network is compared with the gold standard. We show that ARACNE performs better when it takes the proposed correlation matrix estimator as input. The R

  19. Correlates of Unwanted Births in Bangladesh: A Study through Path Analysis.

    Science.gov (United States)

    Roy, Tapan Kumar; Singh, Brijesh P

    2016-01-01

    Unwanted birth is an important public health concern due to its negative association with adverse outcomes of mothers and children as well as socioeconomic development of a country. Although a number of studies have been investigated the determinants of unwanted births through logistic regression analysis, an extensive assessment using path model is lacking. In the current study, we applied path analysis to know the important covariates for unwanted births in Bangladesh. The study used data extracted from Bangladesh Demographic and Health Survey (BDHS) 2011. It considered sub-sample consisted of 7,972 women who had given most recent births five years preceding the date of interview or who were currently pregnant at survey time. Correlation analysis was used to find out the significant association with unwanted births. This study provided the factors affecting unwanted births in Bangladesh. The path model was used to determine the direct, indirect and total effects of socio-demographic factors on unwanted births. The result exhibited that more than one-tenth of the recent births were unwanted in Bangladesh. The differentials of unwanted births were women's age, education, age at marriage, religion, socioeconomic status, exposure of mass-media and use of family planning. In correlation analysis, it showed that unwanted births were positively correlated with women age and place of residence and these relationships were significant. On the contrary, unwanted births were inversely significantly correlated with education and social status. The total effects of endogenous variables such as women age, place of residence and use of family planning methods had favorable effect on unwanted births. Policymakers and program planners need to design programs and services carefully to reduce unwanted births in Bangladesh, especially, service should focus on helping those groups of women who were identified in the analysis as being at increased risks of unwanted births- older women

  20. Correlates of Unwanted Births in Bangladesh: A Study through Path Analysis.

    Directory of Open Access Journals (Sweden)

    Tapan Kumar Roy

    Full Text Available Unwanted birth is an important public health concern due to its negative association with adverse outcomes of mothers and children as well as socioeconomic development of a country. Although a number of studies have been investigated the determinants of unwanted births through logistic regression analysis, an extensive assessment using path model is lacking. In the current study, we applied path analysis to know the important covariates for unwanted births in Bangladesh.The study used data extracted from Bangladesh Demographic and Health Survey (BDHS 2011. It considered sub-sample consisted of 7,972 women who had given most recent births five years preceding the date of interview or who were currently pregnant at survey time. Correlation analysis was used to find out the significant association with unwanted births. This study provided the factors affecting unwanted births in Bangladesh. The path model was used to determine the direct, indirect and total effects of socio-demographic factors on unwanted births.The result exhibited that more than one-tenth of the recent births were unwanted in Bangladesh. The differentials of unwanted births were women's age, education, age at marriage, religion, socioeconomic status, exposure of mass-media and use of family planning. In correlation analysis, it showed that unwanted births were positively correlated with women age and place of residence and these relationships were significant. On the contrary, unwanted births were inversely significantly correlated with education and social status. The total effects of endogenous variables such as women age, place of residence and use of family planning methods had favorable effect on unwanted births.Policymakers and program planners need to design programs and services carefully to reduce unwanted births in Bangladesh, especially, service should focus on helping those groups of women who were identified in the analysis as being at increased risks of unwanted

  1. Correlation of quantitative histopathological morphology and quantitative radiological analysis during aseptic loosening of hip endoprostheses.

    Science.gov (United States)

    Bertz, S; Kriegsmann, J; Eckardt, A; Delank, K-S; Drees, P; Hansen, T; Otto, M

    2006-01-01

    Aseptic hip prosthesis loosening is the most important long-term complication in total hip arthroplasty. Polyethylene (PE) wear is the dominant etiologic factor in aseptic loosening, which together with other factors induces mechanisms resulting in bone loss, and finally in implant loosening. The single-shot radiograph analysis (EBRA, abbreviation for the German term "Einzel-Bild-Röntgenanalyse") is a computerized method for early radiological prediction of aseptic loosening. In this study, EBRA parameters were correlated with histomorphological parameters of the periprosthetic membrane. Periprosthetic membranes obtained from 19 patients during revision surgery of loosened ABG I-type total hip pros-theses were analyzed histologically and morphometrically. The pre-existing EBRA parameters, the thickness of the PE debris lay-er and the dimension of inclination and anteversion, were compared with the density of macrophages and giant cells. Addi-tionally, the semiquantitatively determined density of lymphocytes, plasma cells, giant cells and the size of the necrotic areas were correlated with the EBRA results. All periprosthetic membranes were classified as debris-induced type membranes. We found a positive correlation between the number of giant cells and the thickness of the PE debris layer. There was no significant correlation between the number of macrophages or all semiquantitative parameters and EBRA parameters. The number of giant cells decreased with implant duration. The morphometrically measured number of foreign body giant cells more closely reflects the results of the EBRA. The semiquantitative estimation of giant cell density could not substitute for the morphometrical analysis. The density of macrophages, lymphocytes, plasma cells and the size of necrotic areas did not correlate with the EBRA parameters, indicating that there is no correlation with aseptic loosening.

  2. Correlates of perceived stigma for people living with epilepsy: A meta-analysis.

    Science.gov (United States)

    Shi, Ying; Wang, Shouqi; Ying, Jie; Zhang, Meiling; Liu, Pengcheng; Zhang, Huanhuan; Sun, Jiao

    2017-05-01

    Epilepsy, one of the most common, serious chronic neurological diseases, is accompanied by different levels of perceived stigma that affects people in almost all age groups. This stigma can negatively impact the physical and mental health of people living with epilepsy (PLWE). Good knowledge of perceived stigma for PLWE is important. In this study, we conducted a meta-analysis to identify the correlates of perceived stigma for PLWE. Studies on factors associated with perceived stigma for PLWE, including sociodemographic, psychosocial, and disease-related variables, were searched in PubMed, PsychINFO, EMBASE, and Web of Science. Nineteen variables (k>1) were included in the meta-analysis. For sociodemographic characteristics, findings revealed that the significant weighted mean correlation (R) for "residence" and "poor financial status" were 0.177 and 0.286, respectively. For disease-related characteristics, all variables of significance, including "seizure severity," "seizure frequency," "number of medicines," and "adverse event" (R ranging from 0.190 to 0.362), were positively correlated with perceived stigma. For psychosocial characteristics, "depression" and "anxiety" with R values of 0.414 and 0.369 were significantly associated with perceived stigma. In addition, "social support," "quality of life (QOLIE-31,89)," "knowledge," and "attitude," with R values ranging from -0.444 to -0.200 indicating negative correlation with perceived stigma. The current meta-analysis evaluated the correlates of perceived stigma for PLWE. Results can serve as a basis for policymakers and healthcare professionals for formulating health promotion and prevention strategies. Copyright © 2017 Elsevier Inc. All rights reserved.

  3. A Simple Geotracer Compositional Correlation Analysis Reveals Oil Charge and Migration Pathways

    Science.gov (United States)

    Yang, Yunlai; Arouri, Khaled

    2016-03-01

    A novel approach, based on geotracer compositional correlation analysis is reported, which reveals the oil charge sequence and migration pathways for five oil fields in Saudi Arabia. The geotracers utilised are carbazoles, a family of neutral pyrrolic nitrogen compounds known to occur naturally in crude oils. The approach is based on the concept that closely related fields, with respect to filling sequence, will show a higher carbazole compositional correlation, than those fields that are less related. That is, carbazole compositional correlation coefficients can quantify the charge and filling relationships among different fields. Consequently, oil migration pathways can be defined based on the established filling relationships. The compositional correlation coefficients of isomers of C1 and C2 carbazoles, and benzo[a]carbazole for all different combination pairs of the five fields were found to vary extremely widely (0.28 to 0.94). A wide range of compositional correlation coefficients allows adequate differentiation of separate filling relationships. Based on the established filling relationships, three distinct migration pathways were inferred, with each apparently being charged from a different part of a common source kitchen. The recognition of these charge and migration pathways will greatly aid the search for new accumulations.

  4. Multivariate analysis of correlation between electrophysiological and hemodynamic responses during cognitive processing

    Science.gov (United States)

    Kujala, Jan; Sudre, Gustavo; Vartiainen, Johanna; Liljeström, Mia; Mitchell, Tom; Salmelin, Riitta

    2014-01-01

    Animal and human studies have frequently shown that in primary sensory and motor regions the BOLD signal correlates positively with high-frequency and negatively with low-frequency neuronal activity. However, recent evidence suggests that this relationship may also vary across cortical areas. Detailed knowledge of the possible spectral diversity between electrophysiological and hemodynamic responses across the human cortex would be essential for neural-level interpretation of fMRI data and for informative multimodal combination of electromagnetic and hemodynamic imaging data, especially in cognitive tasks. We applied multivariate partial least squares correlation analysis to MEG–fMRI data recorded in a reading paradigm to determine the correlation patterns between the data types, at once, across the cortex. Our results revealed heterogeneous patterns of high-frequency correlation between MEG and fMRI responses, with marked dissociation between lower and higher order cortical regions. The low-frequency range showed substantial variance, with negative and positive correlations manifesting at different frequencies across cortical regions. These findings demonstrate the complexity of the neurophysiological counterparts of hemodynamic fluctuations in cognitive processing. PMID:24518260

  5. Structured sparse canonical correlation analysis for brain imaging genetics: an improved GraphNet method.

    Science.gov (United States)

    Du, Lei; Huang, Heng; Yan, Jingwen; Kim, Sungeun; Risacher, Shannon L; Inlow, Mark; Moore, Jason H; Saykin, Andrew J; Shen, Li

    2016-05-15

    Structured sparse canonical correlation analysis (SCCA) models have been used to identify imaging genetic associations. These models either use group lasso or graph-guided fused lasso to conduct feature selection and feature grouping simultaneously. The group lasso based methods require prior knowledge to define the groups, which limits the capability when prior knowledge is incomplete or unavailable. The graph-guided methods overcome this drawback by using the sample correlation to define the constraint. However, they are sensitive to the sign of the sample correlation, which could introduce undesirable bias if the sign is wrongly estimated. We introduce a novel SCCA model with a new penalty, and develop an efficient optimization algorithm. Our method has a strong upper bound for the grouping effect for both positively and negatively correlated features. We show that our method performs better than or equally to three competing SCCA models on both synthetic and real data. In particular, our method identifies stronger canonical correlations and better canonical loading patterns, showing its promise for revealing interesting imaging genetic associations. The Matlab code and sample data are freely available at http://www.iu.edu/∼shenlab/tools/angscca/ shenli@iu.edu Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  6. A Simple Geotracer Compositional Correlation Analysis Reveals Oil Charge and Migration Pathways.

    Science.gov (United States)

    Yang, Yunlai; Arouri, Khaled

    2016-03-11

    A novel approach, based on geotracer compositional correlation analysis is reported, which reveals the oil charge sequence and migration pathways for five oil fields in Saudi Arabia. The geotracers utilised are carbazoles, a family of neutral pyrrolic nitrogen compounds known to occur naturally in crude oils. The approach is based on the concept that closely related fields, with respect to filling sequence, will show a higher carbazole compositional correlation, than those fields that are less related. That is, carbazole compositional correlation coefficients can quantify the charge and filling relationships among different fields. Consequently, oil migration pathways can be defined based on the established filling relationships. The compositional correlation coefficients of isomers of C1 and C2 carbazoles, and benzo[a]carbazole for all different combination pairs of the five fields were found to vary extremely widely (0.28 to 0.94). A wide range of compositional correlation coefficients allows adequate differentiation of separate filling relationships. Based on the established filling relationships, three distinct migration pathways were inferred, with each apparently being charged from a different part of a common source kitchen. The recognition of these charge and migration pathways will greatly aid the search for new accumulations.

  7. An efficient sensitivity analysis method for modified geometry of Macpherson suspension based on Pearson correlation coefficient

    Science.gov (United States)

    Shojaeefard, Mohammad Hasan; Khalkhali, Abolfazl; Yarmohammadisatri, Sadegh

    2017-06-01

    The main purpose of this paper is to propose a new method for designing Macpherson suspension, based on the Sobol indices in terms of Pearson correlation which determines the importance of each member on the behaviour of vehicle suspension. The formulation of dynamic analysis of Macpherson suspension system is developed using the suspension members as the modified links in order to achieve the desired kinematic behaviour. The mechanical system is replaced with an equivalent constrained links and then kinematic laws are utilised to obtain a new modified geometry of Macpherson suspension. The equivalent mechanism of Macpherson suspension increased the speed of analysis and reduced its complexity. The ADAMS/CAR software is utilised to simulate a full vehicle, Renault Logan car, in order to analyse the accuracy of modified geometry model. An experimental 4-poster test rig is considered for validating both ADAMS/CAR simulation and analytical geometry model. Pearson correlation coefficient is applied to analyse the sensitivity of each suspension member according to vehicle objective functions such as sprung mass acceleration, etc. Besides this matter, the estimation of Pearson correlation coefficient between variables is analysed in this method. It is understood that the Pearson correlation coefficient is an efficient method for analysing the vehicle suspension which leads to a better design of Macpherson suspension system.

  8. Minimizing the trend effect on detrended cross-correlation analysis with empirical mode decomposition

    International Nuclear Information System (INIS)

    Zhao Xiaojun; Shang Pengjian; Zhao Chuang; Wang Jing; Tao Rui

    2012-01-01

    Highlights: ► Investigate the effects of linear, exponential and periodic trends on DCCA. ► Apply empirical mode decomposition to extract trend term. ► Strong and monotonic trends are successfully eliminated. ► Get the cross-correlation exponent in a persistent behavior without crossover. - Abstract: Detrended cross-correlation analysis (DCCA) is a scaling method commonly used to estimate long-range power law cross-correlation in non-stationary signals. However, the susceptibility of DCCA to trends makes the scaling results difficult to analyze due to spurious crossovers. We artificially generate long-range cross-correlated signals and systematically investigate the effect of linear, exponential and periodic trends. Specifically to the crossovers raised by trends, we apply empirical mode decomposition method which decomposes underlying signals into several intrinsic mode functions (IMF) and a residual trend. After the removal of residual term, strong and monotonic trends such as linear and exponential trends are successfully eliminated. But periodic trend cannot be separated out according to the criterion of IMF, which can be eliminated by Fourier transform. As a special case of DCCA, detrended fluctuation analysis presents similar results.

  9. Correlation between weather and incidence of selected ophthalmological diagnoses: a database analysis

    Directory of Open Access Journals (Sweden)

    Kern C

    2016-08-01

    Full Text Available Christoph Kern, Karsten Kortüm, Michael Müller, Florian Raabe, Wolfgang Johann Mayer, Siegfried Priglinger, Thomas Christian Kreutzer University Eye Hospital Munich, Faculty of Medicine, Ludwig-Maximilians-Universität München, Munich, Germany Purpose: Our aim was to correlate the overall patient volume and the incidence of several ophthalmological diseases in our emergency department with weather data. Patients and methods: For data analysis, we used our clinical data warehouse and weather data. We investigated the weekly overall patient volume and the average weekly incidence of all encoded diagnoses of “conjunctivitis”, “foreign body”, “acute iridocyclitis”, and “corneal abrasion”. A Spearman’s correlation was performed to link these data with the weekly average sunshine duration, temperature, and wind speed. Results: We noticed increased patient volume in correlation with increasing sunshine duration and higher temperature. Moreover, we found a positive correlation between the weekly incidences of conjunctivitis and of foreign body and weather data. Conclusion: The results of this data analysis reveal the possible influence of external conditions on the health of a population and can be used for weather-dependent resource allocation. Keywords: corneal injury, trauma, uveitis, conjunctivitis, weather

  10. Advanced correlation grid: Analysis and visualisation of functional connectivity among multiple spike trains.

    Science.gov (United States)

    Masud, Mohammad Shahed; Borisyuk, Roman; Stuart, Liz

    2017-07-15

    This study analyses multiple spike trains (MST) data, defines its functional connectivity and subsequently visualises an accurate diagram of connections. This is a challenging problem. For example, it is difficult to distinguish the common input and the direct functional connection of two spike trains. The new method presented in this paper is based on the traditional pairwise cross-correlation function (CCF) and a new combination of statistical techniques. First, the CCF is used to create the Advanced Correlation Grid (ACG) correlation where both the significant peak of the CCF and the corresponding time delay are used for detailed analysis of connectivity. Second, these two features of functional connectivity are used to classify connections. Finally, the visualization technique is used to represent the topology of functional connections. Examples are presented in the paper to demonstrate the new Advanced Correlation Grid method and to show how it enables discrimination between (i) influence from one spike train to another through an intermediate spike train and (ii) influence from one common spike train to another pair of analysed spike trains. The ACG method enables scientists to automatically distinguish between direct connections from spurious connections such as common source connection and indirect connection whereas existing methods require in-depth analysis to identify such connections. The ACG is a new and effective method for studying functional connectivity of multiple spike trains. This method can identify accurately all the direct connections and can distinguish common source and indirect connections automatically. Copyright © 2017 Elsevier B.V. All rights reserved.

  11. Statistical analysis of solid waste composition data: Arithmetic mean, standard deviation and correlation coefficients.

    Science.gov (United States)

    Edjabou, Maklawe Essonanawe; Martín-Fernández, Josep Antoni; Scheutz, Charlotte; Astrup, Thomas Fruergaard

    2017-11-01

    Data for fractional solid waste composition provide relative magnitudes of individual waste fractions, the percentages of which always sum to 100, thereby connecting them intrinsically. Due to this sum constraint, waste composition data represent closed data, and their interpretation and analysis require statistical methods, other than classical statistics that are suitable only for non-constrained data such as absolute values. However, the closed characteristics of waste composition data are often ignored when analysed. The results of this study showed, for example, that unavoidable animal-derived food waste amounted to 2.21±3.12% with a confidence interval of (-4.03; 8.45), which highlights the problem of the biased negative proportions. A Pearson's correlation test, applied to waste fraction generation (kg mass), indicated a positive correlation between avoidable vegetable food waste and plastic packaging. However, correlation tests applied to waste fraction compositions (percentage values) showed a negative association in this regard, thus demonstrating that statistical analyses applied to compositional waste fraction data, without addressing the closed characteristics of these data, have the potential to generate spurious or misleading results. Therefore, ¨compositional data should be transformed adequately prior to any statistical analysis, such as computing mean, standard deviation and correlation coefficients. Copyright © 2017 Elsevier Ltd. All rights reserved.

  12. FEM correlation and shock analysis of a VNC MEMS mirror segment

    Science.gov (United States)

    Aguayo, Eduardo J.; Lyon, Richard; Helmbrecht, Michael; Khomusi, Sausan

    2014-08-01

    Microelectromechanical systems (MEMS) are becoming more prevalent in today's advanced space technologies. The Visible Nulling Coronagraph (VNC) instrument, being developed at the NASA Goddard Space Flight Center, uses a MEMS Mirror to correct wavefront errors. This MEMS Mirror, the Multiple Mirror Array (MMA), is a key component that will enable the VNC instrument to detect Jupiter and ultimately Earth size exoplanets. Like other MEMS devices, the MMA faces several challenges associated with spaceflight. Therefore, Finite Element Analysis (FEA) is being used to predict the behavior of a single MMA segment under different spaceflight-related environments. Finite Element Analysis results are used to guide the MMA design and ensure its survival during launch and mission operations. A Finite Element Model (FEM) has been developed of the MMA using COMSOL. This model has been correlated to static loading on test specimens. The correlation was performed in several steps—simple beam models were correlated initially, followed by increasingly complex and higher fidelity models of the MMA mirror segment. Subsequently, the model has been used to predict the dynamic behavior and stresses of the MMA segment in a representative spaceflight mechanical shock environment. The results of the correlation and the stresses associated with a shock event are presented herein.

  13. Statistical analysis of correlated experimental data and neutron cross section evaluation

    International Nuclear Information System (INIS)

    Badikov, S.A.

    1998-01-01

    The technique for evaluation of neutron cross sections on the basis of statistical analysis of correlated experimental data is presented. The most important stages of evaluation beginning from compilation of correlation matrix for measurement uncertainties till representation of the analysis results in the ENDF-6 format are described in details. Special attention is paid to restrictions (positive uncertainty) on covariation matrix of approximate parameters uncertainties generated within the method of least square fit which is derived from physical reasons. The requirements for source experimental data assuring satisfaction of the restrictions mentioned above are formulated. Correlation matrices of measurement uncertainties in particular should be also positively determined. Variants of modelling the positively determined correlation matrices of measurement uncertainties in a situation when their consequent calculation on the basis of experimental information is impossible are discussed. The technique described is used for creating the new generation of estimates of dosimetric reactions cross sections for the first version of the Russian dosimetric file (including nontrivial covariation information)

  14. The correlation between apparent diffusion coefficient and tumor cellularity in patients: a meta-analysis.

    Science.gov (United States)

    Chen, Lihua; Liu, Min; Bao, Jing; Xia, Yunbao; Zhang, Jiuquan; Zhang, Lin; Huang, Xuequan; Wang, Jian

    2013-01-01

    To perform a meta-analysis exploring the correlation between the apparent diffusion coefficient (ADC) and tumor cellularity in patients. We searched medical and scientific literature databases for studies discussing the correlation between the ADC and tumor cellularity in patients. Only studies that were published in English or Chinese prior to November 2012 were considered for inclusion. Summary correlation coefficient (r) values were extracted from each study, and 95% confidence intervals (CIs) were calculated. Sensitivity and subgroup analyses were performed to investigate potential heterogeneity. Of 189 studies, 28 were included in the meta-analysis, comprising 729 patients. The pooled r for all studies was -0.57 (95% CI: -0.62, -0.52), indicating notable heterogeneity (Pcorrelation between the ADC and cellularity for brain tumors. There was no notable evidence of publication bias. There is a strong negative correlation between the ADC and tumor cellularity in patients, particularly in the brain. However, larger, prospective studies are warranted to validate these findings in other cancer types.

  15. An improved method for bivariate meta-analysis when within-study correlations are unknown.

    Science.gov (United States)

    Hong, Chuan; D Riley, Richard; Chen, Yong

    2018-03-01

    Multivariate meta-analysis, which jointly analyzes multiple and possibly correlated outcomes in a single analysis, is becoming increasingly popular in recent years. An attractive feature of the multivariate meta-analysis is its ability to account for the dependence between multiple estimates from the same study. However, standard inference procedures for multivariate meta-analysis require the knowledge of within-study correlations, which are usually unavailable. This limits standard inference approaches in practice. Riley et al proposed a working model and an overall synthesis correlation parameter to account for the marginal correlation between outcomes, where the only data needed are those required for a separate univariate random-effects meta-analysis. As within-study correlations are not required, the Riley method is applicable to a wide variety of evidence synthesis situations. However, the standard variance estimator of the Riley method is not entirely correct under many important settings. As a consequence, the coverage of a function of pooled estimates may not reach the nominal level even when the number of studies in the multivariate meta-analysis is large. In this paper, we improve the Riley method by proposing a robust variance estimator, which is asymptotically correct even when the model is misspecified (ie, when the likelihood function is incorrect). Simulation studies of a bivariate meta-analysis, in a variety of settings, show a function of pooled estimates has improved performance when using the proposed robust variance estimator. In terms of individual pooled estimates themselves, the standard variance estimator and robust variance estimator give similar results to the original method, with appropriate coverage. The proposed robust variance estimator performs well when the number of studies is relatively large. Therefore, we recommend the use of the robust method for meta-analyses with a relatively large number of studies (eg, m≥50). When the

  16. Dynamical Analysis of Stock Market Instability by Cross-correlation Matrix

    Science.gov (United States)

    Takaishi, Tetsuya

    2016-08-01

    We study stock market instability by using cross-correlations constructed from the return time series of 366 stocks traded on the Tokyo Stock Exchange from January 5, 1998 to December 30, 2013. To investigate the dynamical evolution of the cross-correlations, crosscorrelation matrices are calculated with a rolling window of 400 days. To quantify the volatile market stages where the potential risk is high, we apply the principal components analysis and measure the cumulative risk fraction (CRF), which is the system variance associated with the first few principal components. From the CRF, we detected three volatile market stages corresponding to the bankruptcy of Lehman Brothers, the 2011 Tohoku Region Pacific Coast Earthquake, and the FRB QE3 reduction observation in the study period. We further apply the random matrix theory for the risk analysis and find that the first eigenvector is more equally de-localized when the market is volatile.

  17. Dynamical Analysis of Stock Market Instability by Cross-correlation Matrix

    International Nuclear Information System (INIS)

    Takaishi, Tetsuya

    2016-01-01

    We study stock market instability by using cross-correlations constructed from the return time series of 366 stocks traded on the Tokyo Stock Exchange from January 5, 1998 to December 30, 2013. To investigate the dynamical evolution of the cross-correlations, crosscorrelation matrices are calculated with a rolling window of 400 days. To quantify the volatile market stages where the potential risk is high, we apply the principal components analysis and measure the cumulative risk fraction (CRF), which is the system variance associated with the first few principal components. From the CRF, we detected three volatile market stages corresponding to the bankruptcy of Lehman Brothers, the 2011 Tohoku Region Pacific Coast Earthquake, and the FRB QE3 reduction observation in the study period. We further apply the random matrix theory for the risk analysis and find that the first eigenvector is more equally de-localized when the market is volatile. (paper)

  18. Topic Correlation Analysis for Bearing Fault Diagnosis Under Variable Operating Conditions

    Science.gov (United States)

    Chen, Chao; Shen, Fei; Yan, Ruqiang

    2017-05-01

    This paper presents a Topic Correlation Analysis (TCA) based approach for bearing fault diagnosis. In TCA, Joint Mixture Model (JMM), a model which adapts Probability Latent Semantic Analysis (PLSA), is constructed first. Then, JMM models the shared and domain-specific topics using “fault vocabulary” . After that, the correlations between two kinds of topics are computed and used to build a mapping matrix. Furthermore, a new shared space spanned by the shared and mapped domain-specific topics is set up where the distribution gap between different domains is reduced. Finally, a classifier is trained with mapped features which follow a different distribution and then the trained classifier is tested on target bearing data. Experimental results justify the superiority of the proposed approach over the stat-of-the-art baselines and it can diagnose bearing fault efficiently and effectively under variable operating conditions.

  19. Personality Traits as Predictors of Shopping Motivations and Behaviors: A Canonical Correlation Analysis

    Directory of Open Access Journals (Sweden)

    Ali Gohary

    2014-10-01

    Full Text Available This study examines the relationship between Big Five personality traits with shopping motivation variables consisting of compulsive and impulsive buying, hedonic and utilitarian shopping values. Two hundred forty seven college students were recruited to participate in this research. Bivariate correlation demonstrates an overlap between personality traits; consequently, canonical correlation was performed to prevent this phenomenon. The results of multiple regression analysis suggested conscientiousness, neuroticism and openness as predictors of compulsive buying, impulsive buying and utilitarian shopping values. In addition, the results showed significant differences between males and females on conscientiousness, neuroticism, openness, compulsive buying and hedonic shopping value. Besides, using hierarchical regression analysis, we examined sex as moderator between Big Five personality traits and shopping variables, but we didn’t find sufficient evidence to prove it.

  20. Quantifying NMR relaxation correlation and exchange in articular cartilage with time domain analysis

    Science.gov (United States)

    Mailhiot, Sarah E.; Zong, Fangrong; Maneval, James E.; June, Ronald K.; Galvosas, Petrik; Seymour, Joseph D.

    2018-02-01

    Measured nuclear magnetic resonance (NMR) transverse relaxation data in articular cartilage has been shown to be multi-exponential and correlated to the health of the tissue. The observed relaxation rates are dependent on experimental parameters such as solvent, data acquisition methods, data analysis methods, and alignment to the magnetic field. In this study, we show that diffusive exchange occurs in porcine articular cartilage and impacts the observed relaxation rates in T1-T2 correlation experiments. By using time domain analysis of T2-T2 exchange spectroscopy, the diffusive exchange time can be quantified by measurements that use a single mixing time. Measured characteristic times for exchange are commensurate with T1 in this material and so impacts the observed T1 behavior. The approach used here allows for reliable quantification of NMR relaxation behavior in cartilage in the presence of diffusive fluid exchange between two environments.

  1. A learning algorithm for adaptive canonical correlation analysis of several data sets.

    Science.gov (United States)

    Vía, Javier; Santamaría, Ignacio; Pérez, Jesús

    2007-01-01

    Canonical correlation analysis (CCA) is a classical tool in statistical analysis to find the projections that maximize the correlation between two data sets. In this work we propose a generalization of CCA to several data sets, which is shown to be equivalent to the classical maximum variance (MAXVAR) generalization proposed by Kettenring. The reformulation of this generalization as a set of coupled least squares regression problems is exploited to develop a neural structure for CCA. In particular, the proposed CCA model is a two layer feedforward neural network with lateral connections in the output layer to achieve the simultaneous extraction of all the CCA eigenvectors through deflation. The CCA neural model is trained using a recursive least squares (RLS) algorithm. Finally, the convergence of the proposed learning rule is proved by means of stochastic approximation techniques and their performance is analyzed through simulations.

  2. Assessment of SIP Buildings for Sustainable Development in Rural China Using AHP-Grey Correlation Analysis.

    Science.gov (United States)

    Bai, Libiao; Wang, Hailing; Shi, Chunming; Du, Qiang; Li, Yi

    2017-10-25

    Traditional rural residential construction has the problems of high energy consumption and severe pollution. In general, with sustainable development in the construction industry, rural residential construction should be aimed towards low energy consumption and low carbon emissions. To help achieve this objective, in this paper, we evaluated four different possible building structures using AHP-Grey Correlation Analysis, which consists of the Analytic Hierarchy Process (AHP) and the Grey Correlation Analysis. The four structures included the traditional and currently widely used brick and concrete structure, as well as structure insulated panels (SIPs). Comparing the performances of economic benefit and carbon emission, the conclusion that SIPs have the best overall performance can be obtained, providing a reference to help builders choose the most appropriate building structure in rural China.

  3. Potential ligand-binding residues in rat olfactory receptors identified by correlated mutation analysis

    Science.gov (United States)

    Singer, M. S.; Oliveira, L.; Vriend, G.; Shepherd, G. M.

    1995-01-01

    A family of G-protein-coupled receptors is believed to mediate the recognition of odor molecules. In order to identify potential ligand-binding residues, we have applied correlated mutation analysis to receptor sequences from the rat. This method identifies pairs of sequence positions where residues remain conserved or mutate in tandem, thereby suggesting structural or functional importance. The analysis supported molecular modeling studies in suggesting several residues in positions that were consistent with ligand-binding function. Two of these positions, dominated by histidine residues, may play important roles in ligand binding and could confer broad specificity to mammalian odor receptors. The presence of positive (overdominant) selection at some of the identified positions provides additional evidence for roles in ligand binding. Higher-order groups of correlated residues were also observed. Each group may interact with an individual ligand determinant, and combinations of these groups may provide a multi-dimensional mechanism for receptor diversity.

  4. Detecting long-range correlation with detrended fluctuation analysis: Application to BWR stability

    Energy Technology Data Exchange (ETDEWEB)

    Espinosa-Paredes, Gilberto [Departamento de Ingenieria de Procesos e Hidraulica, Universidad Autonoma Metropolitana-Iztapalapa, Apartado Postal 55-534, Mexico, DF 09340 (Mexico)]. E-mail: gepe@xanum.uam.mx; Alvarez-Ramirez, Jose [Departamento de Ingenieria de Procesos e Hidraulica, Universidad Autonoma Metropolitana-Iztapalapa, Apartado Postal 55-534, Mexico, DF 09340 (Mexico); Vazquez, Alejandro [Departamento de Ingenieria de Procesos e Hidraulica, Universidad Autonoma Metropolitana-Iztapalapa, Apartado Postal 55-534, Mexico, DF 09340 (Mexico)

    2006-11-15

    The aim of this paper is to explore the application of detrended fluctuation analysis (DFA) to study boiling water reactor stability. DFA is a scaling method commonly used for detecting long-range correlations in non-stationary time series. This method is based on the random walk theory and was applied to neutronic power signal of Forsmark stability benchmark. Our results shows that the scaling properties breakdown during unstable oscillations.

  5. Detecting long-range correlation with detrended fluctuation analysis: Application to BWR stability

    International Nuclear Information System (INIS)

    Espinosa-Paredes, Gilberto; Alvarez-Ramirez, Jose; Vazquez, Alejandro

    2006-01-01

    The aim of this paper is to explore the application of detrended fluctuation analysis (DFA) to study boiling water reactor stability. DFA is a scaling method commonly used for detecting long-range correlations in non-stationary time series. This method is based on the random walk theory and was applied to neutronic power signal of Forsmark stability benchmark. Our results shows that the scaling properties breakdown during unstable oscillations

  6. Reliability analysis based on a novel density estimation method for structures with correlations

    Directory of Open Access Journals (Sweden)

    Baoyu LI

    2017-06-01

    Full Text Available Estimating the Probability Density Function (PDF of the performance function is a direct way for structural reliability analysis, and the failure probability can be easily obtained by integration in the failure domain. However, efficiently estimating the PDF is still an urgent problem to be solved. The existing fractional moment based maximum entropy has provided a very advanced method for the PDF estimation, whereas the main shortcoming is that it limits the application of the reliability analysis method only to structures with independent inputs. While in fact, structures with correlated inputs always exist in engineering, thus this paper improves the maximum entropy method, and applies the Unscented Transformation (UT technique to compute the fractional moments of the performance function for structures with correlations, which is a very efficient moment estimation method for models with any inputs. The proposed method can precisely estimate the probability distributions of performance functions for structures with correlations. Besides, the number of function evaluations of the proposed method in reliability analysis, which is determined by UT, is really small. Several examples are employed to illustrate the accuracy and advantages of the proposed method.

  7. Improving the clinical correlation of multiple sclerosis black hole volume change by paired-scan analysis.

    Science.gov (United States)

    Tam, Roger C; Traboulsee, Anthony; Riddehough, Andrew; Li, David K B

    2012-01-01

    The change in T 1-hypointense lesion ("black hole") volume is an important marker of pathological progression in multiple sclerosis (MS). Black hole boundaries often have low contrast and are difficult to determine accurately and most (semi-)automated segmentation methods first compute the T 2-hyperintense lesions, which are a superset of the black holes and are typically more distinct, to form a search space for the T 1w lesions. Two main potential sources of measurement noise in longitudinal black hole volume computation are partial volume and variability in the T 2w lesion segmentation. A paired analysis approach is proposed herein that uses registration to equalize partial volume and lesion mask processing to combine T 2w lesion segmentations across time. The scans of 247 MS patients are used to compare a selected black hole computation method with an enhanced version incorporating paired analysis, using rank correlation to a clinical variable (MS functional composite) as the primary outcome measure. The comparison is done at nine different levels of intensity as a previous study suggests that darker black holes may yield stronger correlations. The results demonstrate that paired analysis can strongly improve longitudinal correlation (from -0.148 to -0.303 in this sample) and may produce segmentations that are more sensitive to clinically relevant changes.

  8. NMR-based metabonomics and correlation analysis reveal potential biomarkers associated with chronic atrophic gastritis.

    Science.gov (United States)

    Cui, Jiajia; Liu, Yuetao; Hu, Yinghuan; Tong, Jiayu; Li, Aiping; Qu, Tingli; Qin, Xuemei; Du, Guanhua

    2017-01-05

    Chronic atrophic gastritis (CAG) is one of the most important pre-cancerous states with a high prevalence. Exploring of the underlying mechanism and potential biomarkers is of significant importance for CAG. In the present work, 1 H NMR-based metabonomics with correlative analysis was performed to analyze the metabolic features of CAG. 19 plasma metabolites and 18 urine metabolites were enrolled to construct the circulatory and excretory metabolome of CAG, which was in response to alterations of energy metabolism, inflammation, immune dysfunction, as well as oxidative stress. 7 plasma biomarkers and 7 urine biomarkers were screened to elucidate the pathogenesis of CAG based on the further correlation analysis with biochemical indexes. Finally, 3 plasma biomarkers (arginine, succinate and 3-hydroxybutyrate) and 2 urine biomarkers (α-ketoglutarate and valine) highlighted the potential to indicate risks of CAG in virtue of correlation with pepsin activity and ROC analysis. Here, our results paved a way for elucidating the underlying mechanisms in the development of CAG, and provided new avenues for the diagnosis of CAG and presented potential drug targets for treatment of CAG. Copyright © 2016 Elsevier B.V. All rights reserved.

  9. Correlation of Descriptive Analysis and Instrumental Puncture Testing of Watermelon Cultivars.

    Science.gov (United States)

    Shiu, J W; Slaughter, D C; Boyden, L E; Barrett, D M

    2016-06-01

    The textural properties of 5 seedless watermelon cultivars were assessed by descriptive analysis and the standard puncture test using a hollow probe with increased shearing properties. The use of descriptive analysis methodology was an effective means of quantifying watermelon sensory texture profiles for characterizing specific cultivars' characteristics. Of the 10 cultivars screened, 71% of the variation in the sensory attributes was measured using the 1st 2 principal components. Pairwise correlation of the hollow puncture probe and sensory parameters determined that initial slope, maximum force, and work after maximum force measurements all correlated well to the sensory attributes crisp and firm. These findings confirm that maximum force correlates well with not only firmness in watermelon, but crispness as well. The initial slope parameter also captures the sensory crispness of watermelon, but is not as practical to measure in the field as maximum force. The work after maximum force parameter is thought to reflect cellular arrangement and membrane integrity that in turn impact sensory firmness and crispness. Watermelon cultivar types were correctly predicted by puncture test measurements in heart tissue 87% of the time, although descriptive analysis was correct 54% of the time. © 2016 Institute of Food Technologists®

  10. X-ray texture analysis of paper coating pigments and the correlation with chemical composition analysis

    Science.gov (United States)

    Roine, J.; Tenho, M.; Murtomaa, M.; Lehto, V.-P.; Kansanaho, R.

    2007-10-01

    The present research experiments the applicability of x-ray texture analysis in investigating the properties of paper coatings. The preferred orientations of kaolin, talc, ground calcium carbonate, and precipitated calcium carbonate particles used in four different paper coatings were determined qualitatively based on the measured crystal orientation data. The extent of the orientation, namely, the degree of the texture of each pigment, was characterized quantitatively using a single parameter. As a result, the effect of paper calendering is clearly seen as an increase on the degree of texture of the coating pigments. The effect of calendering on the preferred orientation of kaolin was also evident in an independent energy dispersive spectrometer analysis on micrometer scale and an electron spectroscopy for chemical analysis on nanometer scale. Thus, the present work proves x-ray texture analysis to be a potential research tool for characterizing the properties of paper coating layers.

  11. Reliability Worth Analysis of Distribution Systems Using Cascade Correlation Neural Networks

    DEFF Research Database (Denmark)

    Heidari, Alireza; Agelidis, Vassilios; Pou, Josep

    2018-01-01

    Reliability worth analysis is of great importance in the area of distribution network planning and operation. The reliability worth's precision can be affected greatly by the customer interruption cost model used. The choice of the cost models can change system and load point reliability indices....... In this study, a cascade correlation neural network is adopted to further develop two cost models comprising a probabilistic distribution model and an average or aggregate model. A contingency-based analytical technique is adopted to conduct the reliability worth analysis. Furthermore, the possible effects...

  12. Identifying compromised systems through correlation of suspicious traffic from malware behavioral analysis

    Science.gov (United States)

    Camilo, Ana E. F.; Grégio, André; Santos, Rafael D. C.

    2016-05-01

    Malware detection may be accomplished through the analysis of their infection behavior. To do so, dynamic analysis systems run malware samples and extract their operating system activities and network traffic. This traffic may represent malware accessing external systems, either to steal sensitive data from victims or to fetch other malicious artifacts (configuration files, additional modules, commands). In this work, we propose the use of visualization as a tool to identify compromised systems based on correlating malware communications in the form of graphs and finding isomorphisms between them. We produced graphs from over 6 thousand distinct network traffic files captured during malware execution and analyzed the existing relationships among malware samples and IP addresses.

  13. CONTIN XPCS: Software for Inverse Transform Analysis of X-Ray Photon Correlation Spectroscopy Dynamics.

    Science.gov (United States)

    Andrews, Ross N; Narayanan, Suresh; Zhang, Fan; Kuzmenko, Ivan; Ilavsky, Jan

    2018-02-01

    X-ray photon correlation spectroscopy (XPCS) and dynamic light scattering (DLS) both reveal dynamics using coherent scattering, but X-rays permit investigating of dynamics in a much more diverse array of materials. Heterogeneous dynamics occur in many such materials, and we showed how classic tools employed in analysis of heterogeneous DLS dynamics extend to XPCS, revealing additional information that conventional Kohlrausch exponential fitting obscures. This work presents the software implementation of inverse transform analysis of XPCS data called CONTIN XPCS, an extension of traditional CONTIN that accommodates dynamics encountered in equilibrium XPCS measurements.

  14. Principal component and spatial correlation analysis of spectroscopic-imaging data in scanning probe microscopy

    International Nuclear Information System (INIS)

    Jesse, Stephen; Kalinin, Sergei V

    2009-01-01

    An approach for the analysis of multi-dimensional, spectroscopic-imaging data based on principal component analysis (PCA) is explored. PCA selects and ranks relevant response components based on variance within the data. It is shown that for examples with small relative variations between spectra, the first few PCA components closely coincide with results obtained using model fitting, and this is achieved at rates approximately four orders of magnitude faster. For cases with strong response variations, PCA allows an effective approach to rapidly process, de-noise, and compress data. The prospects for PCA combined with correlation function analysis of component maps as a universal tool for data analysis and representation in microscopy are discussed.

  15. Analysis of Correlation between an Accelerometer-Based Algorithm for Detecting Parkinsonian Gait and UPDRS Subscales

    Directory of Open Access Journals (Sweden)

    Alejandro Rodríguez-Molinero

    2017-09-01

    Full Text Available BackgroundOur group earlier developed a small monitoring device, which uses accelerometer measurements to accurately detect motor fluctuations in patients with Parkinson’s (On and Off state based on an algorithm that characterizes gait through the frequency content of strides. To further validate the algorithm, we studied the correlation of its outputs with the motor section of the Unified Parkinson’s Disease Rating Scale part-III (UPDRS-III.MethodSeventy-five patients suffering from Parkinson’s disease were asked to walk both in the Off and the On state while wearing the inertial sensor on the waist. Additionally, all patients were administered the motor section of the UPDRS in both motor phases. Tests were conducted at the patient’s home. Convergence between the algorithm and the scale was evaluated by using the Spearman’s correlation coefficient.ResultsCorrelation with the UPDRS-III was moderate (rho −0.56; p < 0.001. Correlation between the algorithm outputs and the gait item in the UPDRS-III was good (rho −0.73; p < 0.001. The factorial analysis of the UPDRS-III has repeatedly shown that several of its items can be clustered under the so-called Factor 1: “axial function, balance, and gait.” The correlation between the algorithm outputs and this factor of the UPDRS-III was −0.67 (p < 0.01.ConclusionThe correlation achieved by the algorithm with the UPDRS-III scale suggests that this algorithm might be a useful tool for monitoring patients with Parkinson’s disease and motor fluctuations.

  16. Correlation Analysis of Personality Characteristics of Children with TIC Disorder with Family Factors

    Institute of Scientific and Technical Information of China (English)

    LI Rui; WANG Liqun; MA Chunxia; MA Lixian

    2016-01-01

    Objective To explore the personality characteristics of children with tic disorders and their relationship with family factors.Methods Sixty cases of children with tic disorders diagnosed in our hospital were selected as the case group and 65 cases of normal children were selected as the control group.The children of two groups were assessed using Eysenck Personality Questionnaire (EPQ),Family Environment Scale (FES-CV) and general situation questionnaire of family (GSQ),respectively.The scores of EPQ personality characteristics,FES-CV and GSQ scores were compared for the children in the two groups.The Person correlation analysis method was used to analyze the correlation between personality scores of children in case group and family environment factors.Results The general situation questionnaire results showed that there was significant statistically difference in parenting style,parental education level and family types of the children between case group and control group (P < 0.05);EPQ results showed that the neuroticism and psychoticism scores of children in the case group were significantly higher than those in the control group (P< 0.05) and the lying degree scores in the control group were significantly higher than those in the case group (P< 0.05);FES-CV results showed that the family cohesion scores of the case group were significantly lower than those of the control group (P<0.05),and the family conflict scores in the case group were significantly higher than those in the control group (P<0.05).The Person correlation analysis results indicated that the psychoticism score was negatively correlated with the score of family cohesion (P<0.05),and positively correlated with family conflict (P<0.05),while the neuroticism score was positively correlated with family conflict score (P<0.05).Conclusion The children with tic disorders have significant personality deviation compared to the normal children,and the personality deviation degree is

  17. [Correlation analysis between residual displacement and hip function after reconstruction of acetabular fractures].

    Science.gov (United States)

    Ma, Kunlong; Fang, Yue; Luan, Fujun; Tu, Chongqi; Yang, Tianfu

    2012-03-01

    To investigate the relationships between residual displacement of weight-bearing and non weight-bearing zones (gap displacement and step displacement) and hip function by analyzing the CT images after reconstruction of acetabular fractures. The CT measures and clinical outcome were retrospectively analyzed from 48 patients with displaced acetabular fracture between June 2004 and June 2009. All patients were treated by open reduction and internal fixation, and were followed up 24 to 72 months (mean, 36 months); all fractures healed after operation. The residual displacement involved the weight-bearing zone in 30 cases (weight-bearing group), and involved the non weight-bearing zone in 18 cases (non weight-bearing group). The clinical outcomes were evaluated by Merle d'Aubigné-Postel criteria, and the reduction of articular surface by CT images, including the maximums of two indexes (gap displacement and step displacement). All the data were analyzed in accordance with the Spearman rank correlation coefficient analysis. There was strong negative correlation between the hip function and the residual displacement values in weight-bearing group (r(s) = -0.722, P = 0.001). But there was no correlation between the hip function and the residual displacement values in non weight-bearing group (r(s) = 0.481, P = 0.059). The results of clinical follow-up were similar to the correlation analysis results. In weight-bearing group, the hip function had strong negative correlation with step displacement (r(s) = 0.825, P = 0.002), but it had no correlation with gap displacement (r(s) = 0.577, P = 0.134). In patients with acetabular fracture, the hip function has correlation not only with the extent of the residual displacement but also with the location of the residual displacement, so the residual displacement of weight-bearing zone is a key factor to affect the hip function. In patients with residual displacement in weight-bearing zone, the bigger the step displacement is, the

  18. Multifractal detrended cross-correlation analysis for epileptic patient in seizure and seizure free status

    International Nuclear Information System (INIS)

    Ghosh, Dipak; Dutta, Srimonti; Chakraborty, Sayantan

    2014-01-01

    Highlights: • We analyze EEG of patients during seizure and in seizure free interval. • Data from different sections of the brain and seizure activity was analyzed. • Assessment of cross-correlation in seizure and seizure free interval using MF-DXA technique. - Abstract: This paper reports a study of EEG data of epileptic patients in terms of multifractal detrended cross-correlation analysis (MF-DXA). The EEG clinical data were obtained from the EEG Database available with the Clinic of Epileptology of the University Hospital of Bonn, Germany. The data sets (C, D, and E) were taken from five epileptic patients undergoing presurgical evaluations. The data sets consist of intracranial EEG recordings during seizure-free intervals (interictal periods) from within the epileptogenic zone (D) and from the hippocampal formation of the opposite hemisphere of the epileptic patients’ brain, respectively (C). The data set (E) was recorded during seizure activity (ictal periods). MF-DXA is a very rigorous and robust tool for assessment of cross-correlation among two nonlinear time series. The study reveals the degree of cross-correlation is more among seizure and seizure free interval in epileptogenic zone. These data are very significant for diagnosis, onset and prognosis of epileptic patients

  19. Motivational Basis of Personality Traits: A Meta-Analysis of Value-Personality Correlations.

    Science.gov (United States)

    Fischer, Ronald; Boer, Diana

    2015-10-01

    We investigated the relationships between personality traits and basic value dimensions. Furthermore, we developed novel country-level hypotheses predicting that contextual threat moderates value-personality trait relationships. We conducted a three-level v-known meta-analysis of correlations between Big Five traits and Schwartz's (1992) 10 values involving 9,935 participants from 14 countries. Variations in contextual threat (measured as resource threat, ecological threat, and restrictive social institutions) were used as country-level moderator variables. We found systematic relationships between Big Five traits and human values that varied across contexts. Overall, correlations between Openness traits and the Conservation value dimension and Agreeableness traits and the Transcendence value dimension were strongest across all samples. Correlations between values and all personality traits (except Extraversion) were weaker in contexts with greater financial, ecological, and social threats. In contrast, stronger personality-value links are typically found in contexts with low financial and ecological threats and more democratic institutions and permissive social context. These effects explained on average more than 10% of the variability in value-personality correlations. Our results provide strong support for systematic linkages between personality and broad value dimensions, but they also point out that these relations are shaped by contextual factors. © 2014 Wiley Periodicals, Inc.

  20. Structure function analysis of long-range correlations in plasma turbulence

    International Nuclear Information System (INIS)

    Yu, C.X.; Gilmore, M.; Peebles, W.A.; Rhodes, T.L.

    2003-01-01

    Long-range correlations (temporal and spatial) have been predicted in a number of different turbulence models, both analytical and numerical. These long-range correlations are thought to significantly affect cross-field turbulent transport in magnetically confined plasmas. The Hurst exponent, H - one of a number of methods to identify the existence of long-range correlations in experimental data - can be used to quantify self-similarity scalings and correlations in the mesoscale temporal range. The Hurst exponent can be calculated by several different algorithms, each of which has particular advantages and disadvantages. One method for calculating H is via structure functions (SFs). The SF method is a robust technique for determining H with several inherent advantages that has not yet been widely used in plasma turbulence research. In this article, the SF method and its advantages are discussed in detail, using both simulated and measured fluctuation data from the DIII-D tokamak [J. L. Luxon and L. G. Davis, Fusion Technol. 8, 441 (1985)]. In addition, it is shown that SFs used in conjunction with rescaled range analysis (another method for calculating H) can be used to mitigate the effects of coherent modes in some cases

  1. Multivariate correlation analysis of eye cyclotorsion degree in corneal refractive surgery

    Directory of Open Access Journals (Sweden)

    Xiao-Guang Niu

    2015-06-01

    Full Text Available AIM: To explore the correlation between eye cyclotorsion degrees and patient's age, gender, diopter and other factors in corneal refractive surgery. METHODS: A total of 762 wavefront-guided LASIK patients with 1524 eyes were retrospectively analyzed from January 2010 to December 2013 in our hospital. Iris recognition was accomplished successfully and eye cyclotorsion degrees were recorded intraoperatively for all the patients. The correlations between eye cyclotorsion degrees and patient's age, gender, different eye, diopter and the dominant eye or not were statistically analyzed. In which correlation analysis was used to analyze the relationship between eye cyclotorsion degrees and age and diopter, while the correlations with gender, different eye and the dominant eye or not were analyzed using t-test.RESULTS: The eye cyclotorsion degrees of patients were 0 to 9.7 degrees with an average of 3.08±2.22 degrees. Amongst the average cyclotorsion of 444 men with 888 eyes were 3.05±2.26 degrees, 318 women with 636 eyes were 3.12±2.15 degrees and there were no significant differences(t=1.905, P=0.168. The average age of all the patients was 22.6±5.4y. No significant correlation was found between cyclotorsion degrees and age(r=-0.012, P=0.748. The mean spherical equivalent was -4.76±1.77 degrees, and there was no significant correlation between the eye cyclotorsion degrees and spherical equivalent(r=0.017, P=0.633. The mean cylinder was -0.60±0.64 degrees of no significant correlation with eye cyclotorsion degrees(r=-0.004, P=0.910. The cyclotorsion of dominant eyes of all the patients was 3.0±2.17 degrees, and the non-dominant eyes were 3.11±2.12 degrees. No significant differences were found(t=-0.521,P=0.603. CONCLUSION: The eye cyclotorsion degrees occurred in LASIK surgery had no correlation with age, gender, different eye, diopter and the dominant eye or not.

  2. Information Theory for Correlation Analysis and Estimation of Uncertainty Reduction in Maps and Models

    Directory of Open Access Journals (Sweden)

    J. Florian Wellmann

    2013-04-01

    Full Text Available The quantification and analysis of uncertainties is important in all cases where maps and models of uncertain properties are the basis for further decisions. Once these uncertainties are identified, the logical next step is to determine how they can be reduced. Information theory provides a framework for the analysis of spatial uncertainties when different subregions are considered as random variables. In the work presented here, joint entropy, conditional entropy, and mutual information are applied for a detailed analysis of spatial uncertainty correlations. The aim is to determine (i which areas in a spatial analysis share information, and (ii where, and by how much, additional information would reduce uncertainties. As an illustration, a typical geological example is evaluated: the case of a subsurface layer with uncertain depth, shape and thickness. Mutual information and multivariate conditional entropies are determined based on multiple simulated model realisations. Even for this simple case, the measures not only provide a clear picture of uncertainties and their correlations but also give detailed insights into the potential reduction of uncertainties at each position, given additional information at a different location. The methods are directly applicable to other types of spatial uncertainty evaluations, especially where multiple realisations of a model simulation are analysed. In summary, the application of information theoretic measures opens up the path to a better understanding of spatial uncertainties, and their relationship to information and prior knowledge, for cases where uncertain property distributions are spatially analysed and visualised in maps and models.

  3. Multiset canonical correlations analysis and multispectral, truly multitemporal remote sensing data.

    Science.gov (United States)

    Nielsen, Allan Aasbjerg

    2002-01-01

    This paper describes two- and multiset canonical correlations analysis (CCA) for data fusion, multisource, multiset, or multitemporal 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 of the original variables within sets which means, for example, that the R-mode CVs are insensitive to changes over time in offset and gain in a measuring device. In a case study, CVs are calculated from Landsat Thematic Mapper (TM) data with six spectral bands over six consecutive years. Both Rand T-mode CVs clearly exhibit the desired characteristic: they show maximum similarity for the low-order canonical variates and minimum similarity for the high-order canonical variates. These characteristics are seen both visually and in objective measures. The results from the multiset CCA R- and T-mode analyses are very different. This difference is ascribed to the noise structure in the data. The CCA methods are related to partial least squares (PLS) methods. This paper very briefly describes multiset CCA-based multiset PLS. Also, the CCA methods can be applied as multivariate extensions to empirical orthogonal functions (EOF) techniques. Multiset CCA is well-suited for inclusion in geographical information systems (GIS).

  4. Parent heparin and daughter LMW heparin correlation analysis using LC-MS and NMR

    International Nuclear Information System (INIS)

    Liu, Xinyue; St Ange, Kalib; Wang, Xiaohua; Lin, Lei; Zhang, Fuming

    2017-01-01

    Heparin is a structurally complex, polysaccharide anticoagulant derived from livestock, primarily porcine intestinal tissues. Low molecular weight (LMW) heparins are derived through the controlled partial depolymerization of heparin. Increased manufacturing and regulatory concerns have provided the motivation for the development of more sophisticated analytical methods for determining both their structure and pedigree. A strategy, for the comprehensive comparison of parent heparins and their LMW heparin daughters, is described that relies on the analysis of monosaccharide composition, disaccharide composition, and oligosaccharide composition. Liquid chromatography-mass spectrometry is rapid, robust, and amenable to automated processing and interpretation of both top-down and bottom-up analyses. Nuclear magnetic resonance spectroscopy provides complementary top-down information on the chirality of the uronic acid residues and glucosamine substitution. Principal component analysis (PCA) was applied to the normalized abundance of oligosaccharides, calculated in the bottom-up analysis, to show parent and daughter correlation in oligosaccharide composition. Using these approaches, six pairs of parent heparins and their daughter generic enoxaparins from two different manufacturers were comprehensively analyzed. Enoxaparin is the most widely used LMW heparin and is prepared through controlled chemical β-eliminative cleavage of porcine intestinal heparin. Lovenox"®, the innovator version of enoxaparin marketed in the US, was analyzed as a reference for the daughter LMW heparins. The results, show similarities between LMW heparins from two different manufacturers with Lovenox"®, excellent lot-to-lot consistency of products from each manufacturer, and detects a correlation between each parent heparin and daughter LMW heparin. - Highlights: • Low molecular weight heparins prepared from different heparin parents were analyzed. • An integrated analytical approach relied

  5. Parent heparin and daughter LMW heparin correlation analysis using LC-MS and NMR

    Energy Technology Data Exchange (ETDEWEB)

    Liu, Xinyue, E-mail: liux22@rpi.edu [National Glycoengineering Research Center, Shandong Provincial Key Laboratory of Carbohydrate Chemistry and Glycobiology, State Key Laboratory of Microbial Technology, Shandong University, Jinan, Shandong, 250100 (China); Department of Chemistry and Chemical Biology, Department of Chemical and Biological Engineering, Department of Biology, Department of Biomedical Engineering, Center for Biotechnology and Interdisciplinary Studies, Rensselaer Polytechnic Institute, Troy, NY, 12180 (United States); St Ange, Kalib, E-mail: stangk2@rpi.edu [Department of Chemistry and Chemical Biology, Department of Chemical and Biological Engineering, Department of Biology, Department of Biomedical Engineering, Center for Biotechnology and Interdisciplinary Studies, Rensselaer Polytechnic Institute, Troy, NY, 12180 (United States); Wang, Xiaohua, E-mail: wangx35@rpi.edu [Department of Chemistry and Chemical Biology, Department of Chemical and Biological Engineering, Department of Biology, Department of Biomedical Engineering, Center for Biotechnology and Interdisciplinary Studies, Rensselaer Polytechnic Institute, Troy, NY, 12180 (United States); School of Computer and Information, Hefei University of Technology, Hefei (China); Lin, Lei, E-mail: Linl5@rpi.edu [Department of Chemistry and Chemical Biology, Department of Chemical and Biological Engineering, Department of Biology, Department of Biomedical Engineering, Center for Biotechnology and Interdisciplinary Studies, Rensselaer Polytechnic Institute, Troy, NY, 12180 (United States); Zhang, Fuming, E-mail: zhangf2@rpi.edu [Department of Chemistry and Chemical Biology, Department of Chemical and Biological Engineering, Department of Biology, Department of Biomedical Engineering, Center for Biotechnology and Interdisciplinary Studies, Rensselaer Polytechnic Institute, Troy, NY, 12180 (United States); and others

    2017-04-08

    Heparin is a structurally complex, polysaccharide anticoagulant derived from livestock, primarily porcine intestinal tissues. Low molecular weight (LMW) heparins are derived through the controlled partial depolymerization of heparin. Increased manufacturing and regulatory concerns have provided the motivation for the development of more sophisticated analytical methods for determining both their structure and pedigree. A strategy, for the comprehensive comparison of parent heparins and their LMW heparin daughters, is described that relies on the analysis of monosaccharide composition, disaccharide composition, and oligosaccharide composition. Liquid chromatography-mass spectrometry is rapid, robust, and amenable to automated processing and interpretation of both top-down and bottom-up analyses. Nuclear magnetic resonance spectroscopy provides complementary top-down information on the chirality of the uronic acid residues and glucosamine substitution. Principal component analysis (PCA) was applied to the normalized abundance of oligosaccharides, calculated in the bottom-up analysis, to show parent and daughter correlation in oligosaccharide composition. Using these approaches, six pairs of parent heparins and their daughter generic enoxaparins from two different manufacturers were comprehensively analyzed. Enoxaparin is the most widely used LMW heparin and is prepared through controlled chemical β-eliminative cleavage of porcine intestinal heparin. Lovenox{sup ®}, the innovator version of enoxaparin marketed in the US, was analyzed as a reference for the daughter LMW heparins. The results, show similarities between LMW heparins from two different manufacturers with Lovenox{sup ®}, excellent lot-to-lot consistency of products from each manufacturer, and detects a correlation between each parent heparin and daughter LMW heparin. - Highlights: • Low molecular weight heparins prepared from different heparin parents were analyzed. • An integrated analytical

  6. Pet Bottle Design, Correlation Analysis Of Pet Bottle Characteristics Subjective Judgment

    Directory of Open Access Journals (Sweden)

    Darko Avramović

    2012-06-01

    Full Text Available Ability to predict consumer’s reaction to particular design solution of the product is very important. Gathering andanalysis of subjective judgments of particular characteristics, based on which the aesthetic of the product is judged,is one of predicting the consumer’s reaction in the future. Knowledge gathered this manner can serve as a referencefor further studies of determining factors for aesthetic results and design quality. There are two opposed opinionsregarding prediction of aesthetic impression. One opinion is that taste of individual cannot be discussed because itis extremely variable and the possibility of meaningful analysis of aesthetic impression is rejected. Other opinionstates that there is a consistent preference of certain aesthetic characteristics despite individual and group differences.Main goal of this paper is to examine the correlation between subjective judgments of certain PET bottlecharacteristics. Analysis showed meaningful correlation between some of the PET bottle characteristics while othercharacteristics showed less correlation. It can be concluded that not all of the characteristics have the same influenceon the aesthetics and design quality of the PET bottle form. Emphasizing the characteristics relative to aesthetics ofthe product can produce better market results, taking in to account that consumer’s buy the product they consider tobe more attractive if other parameters of the product are similar.

  7. Analysis on correlation between overall classification on color doppler ultrasound and clinical stages of atherosclerosis obliterans

    International Nuclear Information System (INIS)

    Zhang Dongmei; Liu Meihan; Shi Weidong; Chen Enqi; Li Xinying; Lin Yu

    2010-01-01

    Objective: To investigate the correlation and the clinical significance between the overall classification on color Doppler ultrasound and the clinical stages of atherosclerosis obliterans (ASO), and evaluate the extent of arterial lesions comprehensively. Methods: 125 patients of ASO, who were divided into three groups of mild, moderate and severe with Color Doppler ultrasound according to differences of occlusion, quantity, degree of stenosis and collateral number, were analyzed with clinical stages, then their associations were studied with Spearman rank analysis. Results: The clinical manifestations of ASO patients who were divided into three groups of mild, moderate and severe according to overall classification on color Doppler ultrasound were respectively gradually serious, which had positive correlations with the stages of I, II and III according to clinical stages. Spearman rank analysis showed that the correlation coefficients (rs)was 0.797 2 between two groups (P<0.01), there was good consistency between the overall classification on color Doppler ultrasound and the clinical stagesof ASO. Conclusion: The overall classification of ASO on color Doppler ultrasound has considered impact of many other factors on the clinical symptoms,such as the level of the local narrow, narrow scope, segments of occlusion and collateral arteries, which divides the lesions more objectively, shows good consistency with the clinical stages. (authors)

  8. Analytical X-ray line profile analysis based upon correlated dislocations

    International Nuclear Information System (INIS)

    Rao, S.; Houska, C.R.

    1988-01-01

    Recent advances describing X-ray line profiles analytically, in terms of a minimum number of parameters, are related to a theory based upon correlated dislocations. It is shown that a multiple convolution approach, based upon the Warren-Averbach (W-A) analysis, leads to a form that closely approximates the strain coefficient obtained by Krivoglaz, Martynenko and Ryaboshopka. This connection enables one to determine the dislocation density and the ratio of the correlation range parameter to the mean particle size. These two results are obtained most accurately from previous analytical approaches which make use of a statistical least-squares analysis. The W-A Fourier-series approach provides redundant information and does not focus on the critical parameters that relate to dislocation theory. Results so far are limited to b.c.c. materials. Results for cold-worked W, Mo, Nb, Cr and V are compared with highly imperfect sputtered films of Mo. A major difference is relatable to higher correlation of dislocations in cold-worked metals than is found in sputtered films deposited at low temperatures. However, in each case, the dislocation density is high. (orig.)

  9. Prediction of East African Seasonal Rainfall Using Simplex Canonical Correlation Analysis.

    Science.gov (United States)

    Ntale, Henry K.; Yew Gan, Thian; Mwale, Davison

    2003-06-01

    A linear statistical model, canonical correlation analysis (CCA), was driven by the Nelder-Mead simplex optimization algorithm (called CCA-NMS) to predict the standardized seasonal rainfall totals of East Africa at 3-month lead time using SLP and SST anomaly fields of the Indian and Atlantic Oceans combined together by 24 simplex optimized weights, and then `reduced' by the principal component analysis. Applying the optimized weights to the predictor fields produced better March-April-May (MAM) and September-October-November (SON) seasonal rain forecasts than a direct application of the same, unweighted predictor fields to CCA at both calibration and validation stages. Northeastern Tanzania and south-central Kenya had the best SON prediction results with both validation correlation and Hanssen-Kuipers skill scores exceeding +0.3. The MAM season was better predicted in the western parts of East Africa. The CCA correlation maps showed that low SON rainfall in East Africa is associated with cold SSTs off the Somali coast and the Benguela (Angola) coast, and low MAM rainfall is associated with a buildup of low SSTs in the Indian Ocean adjacent to East Africa and the Gulf of Guinea.

  10. Comparative analysis between different font types and letter styles using a nonlinear invariant digital correlation

    Science.gov (United States)

    Coronel-Beltrán, Ángel; Álvarez-Borrego, Josué

    2010-01-01

    We present, in this paper, a comparative analysis of the letters in Times New Roman (TNR), Courier New (CN) and Arial (Ar) font types in plain and italic style and the effects of five foreground/background color combinations using an invariant digital correlation system with a nonlinear filter with k = 0.3. The evaluation of the output plane with this filter is given by the peak-to-correlation energy (PCE) metric. The results show that the letters in TNR font have a better mean PCE value when compared with the CN and Ar fonts. This result is in agreement with some studies on text legibility and for readability where the reaction time (RT) of some participant individuals reading a text is measured. We conclude that the PCE metric is proportional to 1/RT.

  11. Canonical correlation analysis of the career attitudes and strategies inventory and the adult career concerns inventory

    Directory of Open Access Journals (Sweden)

    Charlene C Lew

    2006-04-01

    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.

  12. Test and Analysis Correlation of Form Impact onto Space Shuttle Wing Leading Edge RCC Panel 8

    Science.gov (United States)

    Fasanella, Edwin L.; Lyle, Karen H.; Gabrys, Jonathan; Melis, Matthew; Carney, Kelly

    2004-01-01

    Soon after the Columbia Accident Investigation Board (CAIB) began their study of the space shuttle Columbia accident, "physics-based" analyses using LS-DYNA were applied to characterize the expected damage to the Reinforced Carbon-Carbon (RCC) leading edge from high-speed foam impacts. Forensic evidence quickly led CAIB investigators to concentrate on the left wing leading edge RCC panels. This paper will concentrate on the test of the left-wing RCC panel 8 conducted at Southwest Research Institute (SwRI) and the correlation with an LS-DYNA analysis. The successful correlation of the LS-DYNA model has resulted in the use of LS-DYNA as a predictive tool for characterizing the threshold of damage for impacts of various debris such as foam, ice, and ablators onto the RCC leading edge for shuttle return-to-flight.

  13. Comprehensive Deployment Method for Technical Characteristics Base on Multi-failure Modes Correlation Analysis

    Science.gov (United States)

    Zheng, W.; Gao, J. M.; Wang, R. X.; Chen, K.; Jiang, Y.

    2017-12-01

    This paper put forward a new method of technical characteristics deployment based on Reliability Function Deployment (RFD) by analysing the advantages and shortages of related research works on mechanical reliability design. The matrix decomposition structure of RFD was used to describe the correlative relation between failure mechanisms, soft failures and hard failures. By considering the correlation of multiple failure modes, the reliability loss of one failure mode to the whole part was defined, and a calculation and analysis model for reliability loss was presented. According to the reliability loss, the reliability index value of the whole part was allocated to each failure mode. On the basis of the deployment of reliability index value, the inverse reliability method was employed to acquire the values of technology characteristics. The feasibility and validity of proposed method were illustrated by a development case of machining centre’s transmission system.

  14. Detecting Distributed Network Traffic Anomaly with Network-Wide Correlation Analysis

    Directory of Open Access Journals (Sweden)

    Yang Dan

    2008-12-01

    Full Text Available Distributed network traffic anomaly refers to a traffic abnormal behavior involving many links of a network and caused by the same source (e.g., DDoS attack, worm propagation. The anomaly transiting in a single link might be unnoticeable and hard to detect, while the anomalous aggregation from many links can be prevailing, and does more harm to the networks. Aiming at the similar features of distributed traffic anomaly on many links, this paper proposes a network-wide detection method by performing anomalous correlation analysis of traffic signals' instantaneous parameters. In our method, traffic signals' instantaneous parameters are firstly computed, and their network-wide anomalous space is then extracted via traffic prediction. Finally, an anomaly is detected by a global correlation coefficient of anomalous space. Our evaluation using Abilene traffic traces demonstrates the excellent performance of this approach for distributed traffic anomaly detection.

  15. COMPARATIVE ANALYSIS OF PERSONALITY CORRELATES OF REFLEXIVITY IN THE CONTEXT OF PROFESSIONAL FORMATION OF THE TEACHER

    Directory of Open Access Journals (Sweden)

    T. V. Mayasova

    2017-01-01

    Full Text Available This article examines the reflexive, the most important professional quality of a teacher's personality in the context of professional development. Reflexivity is a basic property of the individual, whereby the awareness and regulation of the subject of their activities. As a personal correlates of reflexivity studied mental stability, individual styles of decision making (vigilance and avoidance, spontaneity, emotional intelligence (empathy and the ability to manage emotions of other people. The paper conducts a comparative analysis of reflexivity and qualities correlated with her young teachers, working in the specialty from 1 to 5 years and students from different areas of training of pedagogical University. Obtained in the course of the empirical research results confirmed that the process of professional development of teachers is the development of these qualities. Were no significant differences in the indicators options system the reflexivity, alertness,spontaneity, empathy, which differ among teachers and students.

  16. Comparison of JADE and canonical correlation analysis for ECG de-noising.

    Science.gov (United States)

    Kuzilek, Jakub; Kremen, Vaclav; Lhotska, Lenka

    2014-01-01

    This paper explores differences between two methods for blind source separation within frame of ECG de-noising. First method is joint approximate diagonalization of eigenmatrices, which is based on estimation of fourth order cross-cummulant tensor and its diagonalization. Second one is the statistical method known as canonical correlation analysis, which is based on estimation of correlation matrices between two multidimensional variables. Both methods were used within method, which combines the blind source separation algorithm with decision tree. The evaluation was made on large database of 382 long-term ECG signals and the results were examined. Biggest difference was found in results of 50 Hz power line interference where the CCA algorithm completely failed. Thus main power of CCA lies in estimation of unstructured noise within ECG. JADE algorithm has larger computational complexity thus the CCA perfomed faster when estimating the components.

  17. Computer code MLCOSP for multiple-correlation and spectrum analysis with a hybrid computer

    International Nuclear Information System (INIS)

    Oguma, Ritsuo; Fujii, Yoshio; Usui, Hozumi; Watanabe, Koichi

    1975-10-01

    Usage of the computer code MLCOSP(Multiple Correlation and Spectrum) developed is described for a hybrid computer installed in JAERI Functions of the hybrid computer and its terminal devices are utilized ingeniously in the code to reduce complexity of the data handling which occurrs in analysis of the multivariable experimental data and to perform the analysis in perspective. Features of the code are as follows; Experimental data can be fed to the digital computer through the analog part of the hybrid computer by connecting with a data recorder. The computed results are displayed in figures, and hardcopies are taken when necessary. Series-messages to the code are shown on the terminal, so man-machine communication is possible. And further the data can be put in through a keyboard, so case study according to the results of analysis is possible. (auth.)

  18. Making evident and the analysis of correlations between light particles by means of multidetector INDRA

    International Nuclear Information System (INIS)

    Gourio, D.

    1997-01-01

    This thesis reports an light particle interferometric study carried out for the first time by means of an 4π detector. This enabled to extract the proton and deuteron emission time for correctly selected sources. These measurements are extremely worth in the study of hot nuclear matter, particularly for its decaying modes. In this way a clear image of the production chronology of light particles in the heavy ion collision is obtained. In addition, it was possible to make evident the production of fast unstable fragments associated to the decay through pre-equilibrium particles contributing to the very low relative momentum correlation function. This work is the result of a successful event: the association of the 4π INDRA multidetector to the analysis function of the light particle correlation. The real breakthrough achieved by this study was to demonstrate the possibility of full phase space exploration by building the light particle 4 π correlation. In the case of the Xe + Sn system at 45 MeV/u we were able to characterize the collision violence and and to isolate three sources of particle emission. Thus, it was possible to characterize the proton and deuterons emission time for the quasi-target as well as for the quasi-projectile. An important decrease in the characteristic deuteron emission time was observed according as the central collision was approached. Other important results were obtained concerning the proton-proton and proton-deuteron correlation functions as well as the presence of an independent particle dynamical emission of mid-rapidity quasi-targets and quasi- projectiles. Finally, the observation of correlation functions allowed to demonstrate structures at very low relative momentum which can not be understood by the final state interaction only. An explanation could be obtained by a theoretical code taking into account the reaction dynamics, the particle interaction in the final state and the decay of primary excited fragments

  19. Correlation Analysis of Cocoa Consumption Data with Worldwide Incidence Rates of Testicular Cancer and Hypospadias

    Directory of Open Access Journals (Sweden)

    Fabrizio Giannandrea

    2009-02-01

    Full Text Available The underlying reasons for the increasing occurrence of male reproductive diseases (MRD such as hypospadias, cryptorchidism, and testicular cancer (TC over the last decades are still unknown. It has been hypothesized that the risk of MRD is determined in utero and that pregnancy dietary intake could also affect MRD risk in the offspring. Various studies in animals reported that cocoa and theobromine, the main stimulant of cocoa, exert toxic effects on the testis, inducing testicular atrophy and impaired sperm quality. A correlation analysis was conducted to examine the possible role of cocoa consumption on the occurrence of selected MRD during the prenatal and early life period of cases. The incidence rates between 1998-2002 of TC in 18 countries obtained from Cancer Incidence in Five Continents were correlated with the average per-capita consumption of cocoa (kg/capita/year (FAOSTAT-Database in these countries from 1965 to 1980, i.e. the period corresponding to the early life of TC cases. In order to test the above correlation in the case of hypospadias, the mean prevalence at birth in 20 countries (1999-2003 with average per-capita consumption of cocoa in these countries in the same period corresponding to pregnancy were used. The consumption of cocoa in the period 1965–80, was most closely correlated with the incidence of TC in young adults (r=0.859; p<0.001. An analogous significant correlation was also observed between early cocoa consumption and the prevalence rates of hypospadias in the period 1999-2003 (r=0.760; p<0.001. Although the ecological approach used in this study cannot provide an answer on the causal relationship between consumption of cocoa in early life and TC and hypospadias, the results are suggestive and indicate the need of further analytic studies to investigate the role of individual exposure to cocoa, particularly during the prenatal and in early life of the patients.

  20. Correlation analysis of cocoa consumption data with worldwide incidence rates of testicular cancer and hypospadias.

    Science.gov (United States)

    Giannandrea, Fabrizio

    2009-02-01

    The underlying reasons for the increasing occurrence of male reproductive diseases (MRD) such as hypospadias, cryptorchidism, and testicular cancer (TC) over the last decades are still unknown. It has been hypothesized that the risk of MRD is determined in utero and that pregnancy dietary intake could also affect MRD risk in the offspring. Various studies in animals reported that cocoa and theobromine, the main stimulant of cocoa, exert toxic effects on the testis, inducing testicular atrophy and impaired sperm quality. A correlation analysis was conducted to examine the possible role of cocoa consumption on the occurrence of selected MRD during the prenatal and early life period of cases. The incidence rates between 1998-2002 of TC in 18 countries obtained from Cancer Incidence in Five Continents were correlated with the average per-capita consumption of cocoa (kg/capita/year) (FAOSTAT-Database) in these countries from 1965 to 1980, i.e. the period corresponding to the early life of TC cases. In order to test the above correlation in the case of hypospadias, the mean prevalence at birth in 20 countries (1999-2003) with average per-capita consumption of cocoa in these countries in the same period corresponding to pregnancy were used. The consumption of cocoa in the period 1965-80, was most closely correlated with the incidence of TC in young adults (r=0.859; p<0.001). An analogous significant correlation was also observed between early cocoa consumption and the prevalence rates of hypospadias in the period 1999-2003 (r=0.760; p<0.001). Although the ecological approach used in this study cannot provide an answer on the causal relationship between consumption of cocoa in early life and TC and hypospadias, the results are suggestive and indicate the need of further analytic studies to investigate the role of individual exposure to cocoa, particularly during the prenatal and in early life of the patients.

  1. Correlation between Chinese and international energy prices based on a HP filter and time difference analysis

    International Nuclear Information System (INIS)

    He, Yongxiu; Wang, Bing; Wang, Jianhui; Xiong, Wei; Xia, Tian

    2013-01-01

    To establish a reasonable system and mechanism for Chinese energy prices, we use the Granger causality test, Hodrick–Prescott (HP) filter and time difference analysis to research the pricing relationship between Chinese and international energy prices. We find that Chinese and international crude oil prices changed synchronously while Chinese refined oil prices follow the changes of international oil prices with the time difference being about 1 month to 2 months. Further, Australian coal prices Granger causes Chinese coal prices, and there is a high correlation between them. The U.S. electricity price is influenced by the WTI crude oil price, the U.S. gasoline price and the HenryHub gas price. Due to the unreasonable price-setting mechanism and regulation from the central government, China′s terminal market prices for both electricity and natural gas do not reflect the real supply–demand situation. This paper provides quantitative results on the correlation between Chinese and international energy prices to better predict the impact of international energy price fluctuations on China′s domestic energy supply and guide the design of more efficient energy pricing policies. Moreover, it provides references for developing countries to improve their energy market systems and trading, and to coordinate domestic and international energy markets. -- Highlights: •The Hodrick-Prescott filter and time difference analysis are used to research the correlation among energy prices. •Our study finds that the U.S. and British refined oil prices Granger cause the Chinese refined oil price. •Both Chinese and the Australian coal prices play an important role in the international coal market. •The Chinese terminal electric power and terminal natural gas prices are not highly correlated. •The results are useful for guiding the design of more efficient energy pricing policies in China

  2. Analysis of Correlation Tendency between Wind and Solar from Various Spatio-temporal Perspectives

    Science.gov (United States)

    Wang, X.; Weihua, X.; Mei, Y.

    2017-12-01

    Analysis of correlation between wind resources and solar resources could explore their complementary features, enhance the utilization efficiency of renewable energy and further alleviate the carbon emission issues caused by the fossil energy. In this paper, we discuss the correlation between wind and solar from various spatio-temporal perspectives (from east to west, in terms of plain, plateau, hill, and mountain, from hourly to daily, ten days and monthly) with observed data and modeled data from NOAA (National Oceanic and Atmospheric Administration) and NERL (National Renewable Energy Laboratory). With investigation of wind speed time series and solar radiation time series (period: 10 years, resolution: 1h) of 72 stations located in various landform and distributed dispersedly in USA, the results show that the correlation coefficient, Kendall's rank correlation coefficient, changes negative to positive value from east coast to west coast of USA, and this phenomena become more obvious when the time scale of resolution increases from daily to ten days and monthly. Furthermore, considering the differences of landforms which influence the local meteorology the Kendall coefficients of diverse topographies are compared and it is found that the coefficients descend from mountain to hill, plateau and plain. However, no such evident tendencies could be found in daily scale. According to this research, it is proposed that the complementary feature of wind resources and solar resources in the east or in the mountain area of USA is conspicuous. Subsequent study would try to further verify this analysis by investigating the operation status of wind power station and solar power station.

  3. [Correlation analysis between biochemical and biophysical markers of endothelium damage in children with diabetes type 1].

    Science.gov (United States)

    Głowińska-Olszewska, Barbara; Urban, Mirosława; Tołwińska, Joanna; Peczyńska, Jadwiga; Florys, Bozena

    2005-01-01

    Endothelial damage is one of the earliest stages in the atherosclerosis process. Adhesion molecules, secreted from dysfunctional endothelial cells are considered as early markers of atherosclerotic disease. Ultrasonographic evaluation of brachial arteries serves to detect biophysical changes in endothelial function, and evaluation of carotid arteries intima-media thickness allows to evaluate the earliest structural changes in the vessels. The aim of the study was to the evaluate levels of selected adhesion molecules (sICAM-1, sVCAM-1, sE-selectin, sP-selectin) and endothelial function with use of brachial artery dilatation study (flow mediated dilation--FMD, nitroglycerine mediated dilation--NTGMD) and IMT in carotid arteries in children and adolescents with diabetes type 1, as well as the correlation analysis between biochemical and biophysical markers of endothelial dysfunction. We studied 76 children and adolescents, with mean age--15.6+/-2.5 years, suffering from diabetes mean 7.8+/-2.8 years, mean HbA1c--8.4+/-1.5%. Control group consisted of 33 healthy children age and gender matched. Adhesion molecules levels were estimated with the use of immunoenzymatic methods (R&D Systems). Endothelial function was evaluated by study of brachial arteries dilation--FMD, NTGMD, with ultrasonographic evaluation (Hewlett Packard Sonos 4500) after Celermajer method, and IMT after Pignoli method. In the study group we found elevated levels of sICAM-1: 309.54+/-64 vs. 277.85+/-52 ng/ml in the control group (p<00.05) and elevated level of sE-selectin: 87.81+/-35 vs. 66.21+/-22 ng/ml (p<00.05). We found significantly impaired FMD in brachial arteries in the study group--7.51+/-4.52 vs. 12.61+/-4.65% (p<00.05) and significantly higher IMT value: 0.51+/-0.07 vs. 0.42+/-0.05 mm (p<00.001). Correlation analysis revealed a significant negative correlation between sE-selectin and FMD - r=-0.33 (p=0.004), and a positive correlation between E-selectin and IMT: r=0.32 (p=0.005). 1. In

  4. Study on insomnia and sleep quality in adolescents and their correlation analysis

    Directory of Open Access Journals (Sweden)

    Xian LUO

    2017-09-01

    Full Text Available Objective To investigate the correlation between insomnia and sleep quality in adolescents. Methods According to Insomnia Severity Index (ISI Chinese Version, 3342 students technician training in school were divided into non insomnia group (N = 2345 and insomnia group (N = 997. Sleep and emotional state were assessed by ISI Chinese Version, Pittsburgh Sleep Quality Index (PSQI, Epworth Sleepiness Scale (ESS, Self?Rating Anxiety Scale (SAS and Beck Depression Inventory (BDI. The social demographic data were collected simultaneously. Results The number of insomnia, daytime sleepiness, anxiety and depression in the population was 997 (29.83%, 568 (17.00%, 243 (7.27% and 1287 (38.51%, respectively. The comparison of social demographic data between 2 groups showed that the proportion of female (P = 0.000, poor physical condition (P = 0.000, non?only child (P = 0.006, high learning pressure (P = 0.000 and smoking (P = 0.027 in insomnia group were significantly higher than those in non insomnia group. The total scores of ISI Chinese Version (P = 0.000, ESS (P = 0.000, SAS (P = 0.000 and BDI (P = 0.000 in insomnia group were significantly higher than those in non insomnia group. Pearson correlation analysis showed that ISI Chinese Version and PSQI scores were positively correlated with ESS score (r = 0.361, P = 0.000; r = 0.064, P = 0.000, SAS score (r = 0.326, P = 0.000; r = 0.069, P = 0.000 and BDI score (r = 0.529, P = 0.000; r = 0.067, P = 0.000, and ISI Chinese Version had higher correlation (r = 0.300-0.600 with the above scores than PSQI (r < 0.100. Further partial correlation analysis showed that ISI Chinese Version score was negatively correlated with PSQI score (r = - 0.056, P = 0.001. Conclusions Higher proportion of female, worse physical condition, more non?only child, greater learning pressure and higher smoking rate were observed in insomnia group. Daytime sleepiness, anxiety and depression in insomnia group were more serious than those

  5. Quantitative CT analysis of honeycombing area in idiopathic pulmonary fibrosis: Correlations with pulmonary function tests.

    Science.gov (United States)

    Nakagawa, Hiroaki; Nagatani, Yukihiro; Takahashi, Masashi; Ogawa, Emiko; Tho, Nguyen Van; Ryujin, Yasushi; Nagao, Taishi; Nakano, Yasutaka

    2016-01-01

    The 2011 official statement of idiopathic pulmonary fibrosis (IPF) mentions that the extent of honeycombing and the worsening of fibrosis on high-resolution computed tomography (HRCT) in IPF are associated with the increased risk of mortality. However, there are few reports about the quantitative computed tomography (CT) analysis of honeycombing area. In this study, we first proposed a computer-aided method for quantitative CT analysis of honeycombing area in patients with IPF. We then evaluated the correlations between honeycombing area measured by the proposed method with that estimated by radiologists or with parameters of PFTs. Chest HRCTs and pulmonary function tests (PFTs) of 36 IPF patients, who were diagnosed using HRCT alone, were retrospectively evaluated. Two thoracic radiologists independently estimated the honeycombing area as Identified Area (IA) and the percentage of honeycombing area to total lung area as Percent Area (PA) on 3 axial CT slices for each patient. We also developed a computer-aided method to measure the honeycombing area on CT images of those patients. The total honeycombing area as CT honeycombing area (HA) and the percentage of honeycombing area to total lung area as CT %honeycombing area (%HA) were derived from the computer-aided method for each patient. HA derived from three CT slices was significantly correlated with IA (ρ=0.65 for Radiologist 1 and ρ=0.68 for Radiologist 2). %HA derived from three CT slices was also significantly correlated with PA (ρ=0.68 for Radiologist 1 and ρ=0.70 for Radiologist 2). HA and %HA derived from all CT slices were significantly correlated with FVC (%pred.), DLCO (%pred.), and the composite physiologic index (CPI) (HA: ρ=-0.43, ρ=-0.56, ρ=0.63 and %HA: ρ=-0.60, ρ=-0.49, ρ=0.69, respectively). The honeycombing area measured by the proposed computer-aided method was correlated with that estimated by expert radiologists and with parameters of PFTs. This quantitative CT analysis of

  6. Local wavelet correlation: applicationto timing analysis of multi-satellite CLUSTER data

    Directory of Open Access Journals (Sweden)

    J. Soucek

    2004-12-01

    Full Text Available Multi-spacecraft space observations, such as those of CLUSTER, can be used to infer information about local plasma structures by exploiting the timing differences between subsequent encounters of these structures by individual satellites. We introduce a novel wavelet-based technique, the Local Wavelet Correlation (LWC, which allows one to match the corresponding signatures of large-scale structures in the data from multiple spacecraft and determine the relative time shifts between the crossings. The LWC is especially suitable for analysis of strongly non-stationary time series, where it enables one to estimate the time lags in a more robust and systematic way than ordinary cross-correlation techniques. The technique, together with its properties and some examples of its application to timing analysis of bow shock and magnetopause crossing observed by CLUSTER, are presented. We also compare the performance and reliability of the technique with classical discontinuity analysis methods. Key words. Radio science (signal processing – Space plasma physics (discontinuities; instruments and techniques

  7. Analysis of the impact of correlated benchmark experiments on the validation of codes for criticality safety analysis

    International Nuclear Information System (INIS)

    Bock, M.; Stuke, M.; Behler, M.

    2013-01-01

    The validation of a code for criticality safety analysis requires the recalculation of benchmark experiments. The selected benchmark experiments are chosen such that they have properties similar to the application case that has to be assessed. A common source of benchmark experiments is the 'International Handbook of Evaluated Criticality Safety Benchmark Experiments' (ICSBEP Handbook) compiled by the 'International Criticality Safety Benchmark Evaluation Project' (ICSBEP). In order to take full advantage of the information provided by the individual benchmark descriptions for the application case, the recommended procedure is to perform an uncertainty analysis. The latter is based on the uncertainties of experimental results included in most of the benchmark descriptions. They can be performed by means of the Monte Carlo sampling technique. The consideration of uncertainties is also being introduced in the supplementary sheet of DIN 25478 'Application of computer codes in the assessment of criticality safety'. However, for a correct treatment of uncertainties taking into account the individual uncertainties of the benchmark experiments is insufficient. In addition, correlations between benchmark experiments have to be handled correctly. For example, these correlations can arise due to different cases of a benchmark experiment sharing the same components like fuel pins or fissile solutions. Thus, manufacturing tolerances of these components (e.g. diameter of the fuel pellets) have to be considered in a consistent manner in all cases of the benchmark experiment. At the 2012 meeting of the Expert Group on 'Uncertainty Analysis for Criticality Safety Assessment' (UACSA) of the OECD/NEA a benchmark proposal was outlined that aimed for the determination of the impact on benchmark correlations on the estimation of the computational bias of the neutron multiplication factor (k eff ). The analysis presented here is based on this proposal. (orig.)

  8. The Diagnosis of Internal Leakage of Control Valve Based on the Grey Correlation Analysis Method

    Directory of Open Access Journals (Sweden)

    Zheng DING

    2014-07-01

    Full Text Available The valve plays an important part in the industrial automation system. Whether it operates normally or not relates with the quality of the products directly while its faults are relatively common because of bad working conditions. And the internal leakage is one of the common faults. Consequently, this paper sets up the experimental platform to make the valve in different working condition and collect relevant data online. Then, diagnose the internal leakage of the valve by using the grey correlation analysis method. The results show that this method can not only diagnose the internal leakage of valve accurately, but also distinguish fault degree quantitatively.

  9. Two-Dimensional Raman Correlation Analysis of Diseased Esophagus in a Rat

    Science.gov (United States)

    Takanezawa, Sota; Morita, Shin-ichi; Maruyama, Atsushi; Murakami, Takurou N.; Kawashima, Norimichi; Endo, Hiroyuki; Iijima, Katsunori; Asakura, Tohru; Shimosegawa, Tooru; Sato, Hidetoshi

    2010-07-01

    Generalized two-dimensional (2D) Raman correlation analysis effectively distinguished a benign tumor from normal tissue. Line profiling Raman spectra of a rat esophagus, including a benign tumor, were measured and the generalized 2D synchronous and asynchronous spectra were calculated. In the autocorrelation area of the amide I band of proteins in the asynchronous map, a cross-like pattern was observed. A simulation study indicated that the pattern was caused by a sharp band component in the amide I band region. We considered that the benign tumor corresponded to the sharp component.

  10. Thanatophoric dysplasia. Correlation among bone X-ray morphometry, histopathology, and gene analysis

    International Nuclear Information System (INIS)

    Pazzaglia, Ugo E.; Donzelli, Carla M.; Izzi, Claudia; Baldi, Maurizia; Di Gaetano, Giuseppe; Bondioni, MariaPia

    2014-01-01

    Documentation through X-ray morphometry and histology of the steady phenotype expressed by FGFR3 gene mutation and interpolation of mechanical factors on spine and long bones dysmorphism. Long bones and spine of eight thanatophoric dysplasia and three age-matched controls without skeletal dysplasia were studied after pregnancy termination between the 18th and the 22nd week with X-ray morphometry, histology, and molecular analysis. Statistical analysis with comparison between TD cases and controls and intraobserver/interobserver variation were applied to X-ray morphometric data. Generalized shortening of long bones was observed in TD. A variable distribution of axial deformities was correlated with chondrocyte proliferation inhibition, defective seriate cell columns organization, and final formation of the primary metaphyseal trabeculae. The periosteal longitudinal growth was not equally inhibited, so that decoupling with the cartilage growth pattern produced the typical lateral spurs around the metaphyseal growth plates. In spine, platyspondyly was due to a reduced height of the vertebral body anterior ossification center, while its enlargement in the transversal plane was not restricted. The peculiar radiographic and histopathological features of TD bones support the hypothesis of interpolation of mechanical factors with FGFR3 gene mutations. The correlated observations of X-ray morphometry, histopathology, and gene analysis prompted the following diagnostic workup for TD: (1) prenatal sonography suspicion of skeletal dysplasia; (2) post-mortem X-ray morphometry for provisional diagnosis; (3) confirmation by genetic tests (hot-spot exons 7, 10, 15, and 19 analysis with 80-90 % sensibility); (4) in negative cases if histopathology confirms TD diagnosis, research of rare mutations through sequential analysis of FGFR3 gene. (orig.)

  11. Correlation analysis of craniomandibular index and gothic arch tracing in patients with craniomandibular disorders

    Directory of Open Access Journals (Sweden)

    Todić Jelena

    2011-01-01

    Full Text Available Background/Aim. Complex etiology and symptomatology of craniomandibular dysfunction make the diagnosing and therapy of this disorder more difficult. The aim of this work was to assess the value of clinical and instrumental functional analyses in diagnosing of this type of disorders. Methods. In this study 200 subjects were examined, 15 with temporomandibular joint disorder. They were subjected to clinical functional analysis (Fricton-Shiffman and instrumental functional analysis by using the method of gothic arch. The parameters of the gothic arch records were analyzed and subsequently compared among the subjects of the observed groups. Results. In the examined group of the population 7.5% of them were with craniomandibular dysfunction. The most frequent symptoms were sound in temporomandibular joint, painful sensitivity of the muscles on palpation and lateral turning of the lower jaw while opening the mouth. By analyzing the gothic arch records and comparing the obtained values between the observed groups it was assessed that: lateral and protrusion movements, lateral amplitude and the size of gothic arch were much bigger in the healthy subjects, and latero-lateral asymmetry was larger in the sick subjects. Latero-lateral dislocation of apex was recorded only in the sick subjects with average values of 0.22 ± 0.130 mm. The correlation between the values of Fricton-Shiffman craniomandibular index and the parameters of the gothic arch records and latero-lateral amplitude and dislocation of apex records were established by correlative statistical analysis. Conclusion. Functional analysis of orofacial system and instrumental analysis of lower jaw movements (gothic arch method can be recommended as precise and simple methods in diagnosing craniomandibular dysfunctions.

  12. Correlation analysis of craniomandibular index and gothic arch tracing in patients with craniomandibular disorders.

    Science.gov (United States)

    Todić, Jelena; Lazić, Dragoslav; Radosavljević, Radiovoje

    2011-07-01

    Complex etiology and symptomatology of craniomandibular dysfunction make the diagnosing and therapy of this disorder more difficult. The aim of this work was to assess the value of clinical and instrumental functional analyses in diagnosing of this type of disorders. In this study 200 subjects were examined, 15 with temporomandibular joint disorder. They were subjected to clinical functional analysis (Fricton-Shiffman) and instrumental functional analysis by using the method of gothic arch. The parameters of the gothic arch records were analyzed and subsequently compared among the subjects of the observed groups. In the examined group of the population 7.5% of them were with craniomandibular dysfunction. The most frequent symptoms were sound in temporomandibular joint, painful sensitivity of the muscles on palpation and lateral turning of the lower jaw while opening the mouth. By analyzing the gothic arch records and comparing the obtained values between the observed groups it was assessed that: lateral and protrusion movements, lateral amplitude and the size of gothic arch were much bigger in the healthy subjects, and latero-lateral asymmetry was larger in the sick subjects. Latero-lateral dislocation of apex was recorded only in the sick subjects with average values of 0.22 +/- 0.130 mm. The correlation between the values of Fricton-Shiffman craniomandibular index and the parameters of the gothic arch records and latero-lateral amplitude and dislocation of apex records were established by correlative statistical analysis. Functional analysis of orofacial system and instrumental analysis of lower jaw movements (gothic arch method) can be recommended as precise and simple methods in diagnosing craniomandibular dysfunctions.

  13. Thanatophoric dysplasia. Correlation among bone X-ray morphometry, histopathology, and gene analysis

    Energy Technology Data Exchange (ETDEWEB)

    Pazzaglia, Ugo E. [University of Brescia, Orthopaedic Clinic, Department of Medical and Surgical Specialties, Radiological Sciences and Public Health, Brescia (Italy); Donzelli, Carla M. [Spedali Civili di Brescia, Morbid Anatomy Department, Brescia (Italy); Izzi, Claudia [University of Brescia, Prenatal Diagnosis Unit, Department of Obstetrics and Gynaecology, Brescia (Italy); Baldi, Maurizia [Hospital Galliera, Human Genetic Laboratory, Genova (Italy); Di Gaetano, Giuseppe; Bondioni, MariaPia [University of Brescia, Paediatric Radiology, Department of Medical and Surgical Specialties, Radiological Sciences and Public Health, Brescia (Italy)

    2014-09-15

    Documentation through X-ray morphometry and histology of the steady phenotype expressed by FGFR3 gene mutation and interpolation of mechanical factors on spine and long bones dysmorphism. Long bones and spine of eight thanatophoric dysplasia and three age-matched controls without skeletal dysplasia were studied after pregnancy termination between the 18th and the 22nd week with X-ray morphometry, histology, and molecular analysis. Statistical analysis with comparison between TD cases and controls and intraobserver/interobserver variation were applied to X-ray morphometric data. Generalized shortening of long bones was observed in TD. A variable distribution of axial deformities was correlated with chondrocyte proliferation inhibition, defective seriate cell columns organization, and final formation of the primary metaphyseal trabeculae. The periosteal longitudinal growth was not equally inhibited, so that decoupling with the cartilage growth pattern produced the typical lateral spurs around the metaphyseal growth plates. In spine, platyspondyly was due to a reduced height of the vertebral body anterior ossification center, while its enlargement in the transversal plane was not restricted. The peculiar radiographic and histopathological features of TD bones support the hypothesis of interpolation of mechanical factors with FGFR3 gene mutations. The correlated observations of X-ray morphometry, histopathology, and gene analysis prompted the following diagnostic workup for TD: (1) prenatal sonography suspicion of skeletal dysplasia; (2) post-mortem X-ray morphometry for provisional diagnosis; (3) confirmation by genetic tests (hot-spot exons 7, 10, 15, and 19 analysis with 80-90 % sensibility); (4) in negative cases if histopathology confirms TD diagnosis, research of rare mutations through sequential analysis of FGFR3 gene. (orig.)

  14. Correlation analysis between pulmonary function test parameters and CT image parameters of emphysema

    Science.gov (United States)

    Liu, Cheng-Pei; Li, Chia-Chen; Yu, Chong-Jen; Chang, Yeun-Chung; Wang, Cheng-Yi; Yu, Wen-Kuang; Chen, Chung-Ming

    2016-03-01

    Conventionally, diagnosis and severity classification of Chronic Obstructive Pulmonary Disease (COPD) are usually based on the pulmonary function tests (PFTs). To reduce the need of PFT for the diagnosis of COPD, this paper proposes a correlation model between the lung CT images and the crucial index of the PFT, FEV1/FVC, a severity index of COPD distinguishing a normal subject from a COPD patient. A new lung CT image index, Mirage Index (MI), has been developed to describe the severity of COPD primarily with emphysema disease. Unlike conventional Pixel Index (PI) which takes into account all voxels with HU values less than -950, the proposed approach modeled these voxels by different sizes of bullae balls and defines MI as a weighted sum of the percentages of the bullae balls of different size classes and locations in a lung. For evaluation of the efficacy of the proposed model, 45 emphysema subjects of different severity were involved in this study. In comparison with the conventional index, PI, the correlation between MI and FEV1/FVC is -0.75+/-0.08, which substantially outperforms the correlation between PI and FEV1/FVC, i.e., -0.63+/-0.11. Moreover, we have shown that the emphysematous lesion areas constituted by small bullae balls are basically irrelevant to FEV1/FVC. The statistical analysis and special case study results show that MI can offer better assessment in different analyses.

  15. Generalized moment analysis of magnetic field correlations for accumulations of spherical and cylindrical magnetic pertubers

    Directory of Open Access Journals (Sweden)

    Felix Tobias Kurz

    2016-12-01

    Full Text Available In biological tissue, an accumulation of similarly shaped objects with a susceptibility difference to the surrounding tissue generates a local distortion of the external magnetic field in magnetic resonance imaging. It induces stochastic field fluctuations that characteristically influence proton spin diffusion in the vicinity of these magnetic perturbers. The magnetic field correlation that is associated with such local magnetic field inhomogeneities can be expressed in the form of a dynamic frequency autocorrelation function that is related to the time evolution of the measured magnetization. Here, an eigenfunction expansion for two simple magnetic perturber shapes, that of spheres and cylinders, is considered for restricted spin diffusion in a simple model geometry. Then, the concept of generalized moment analysis, an approximation technique that is applied in the study of (non-reactive processes that involve Brownian motion, allows to provide analytical expressions for the correlation function for different exponential decay forms. Results for the biexponential decay for both spherical and cylindrical magnetized objects are derived and compared with the frequently used (less accurate monoexponential decay forms. They are in asymptotic agreement with the numerically exact value of the correlation function for long and short times.

  16. Repeatability, correlation and path analysis of physical and chemical characteristics of peach fruits

    Directory of Open Access Journals (Sweden)

    Rosana Gonçalves Pires Matias

    2014-12-01

    Full Text Available This study aimed to determine the number of measurements necessary to evaluate physical and chemical characteristics of peach fruits, study the relationships between them and their direct and indirect effects on the content of ascorbic acid and total carotenoids. The characteristics skin and pulp color, fruit weight, suture, equatorial and polar diameters, firmness, soluble solids (SS, titratable acidity (TA, SS/TA ratio, ascorbic acid and total carotenoids were evaluated in 39 cultivars of peach and 3 cultivars of nectarine from the orchard of the Universidade Federal de Viçosa. The repeatability coefficient was estimated by ANOVA and CPCOR. Phenotypic correlation coefficients (rf were estimated and, after the multicollinearity diagnostics, they were unfolded to direct and indirect effects of the explanatory variables on the response variable using path analysis. There was agreement on the magnitude of repeatability coefficients obtained by the two methods; however, they varied among the 14 characteristics. The highest correlations were found between FW, SD, ED and PD. Seven fruits are sufficient to evaluate the physical and chemical characteristics of peach with a correlation coefficient of 90%. The characteristics considered in the path diagrams (b* skin, hº skin, b* pulp, hº pulp, ED, PD, FIR, SS, SS/AT and TC are not the main determinants of the ascorbic acid. The yellow hue of the pulp (hº pulp has the potential to be used in indirect selection for total carotenoids.

  17. In Silico Analysis of Correlations between Protein Disorder and Post-Translational Modifications in Algae

    Directory of Open Access Journals (Sweden)

    Atsushi Kurotani

    2015-08-01

    Full Text Available Recent proteome analyses have reported that intrinsically disordered regions (IDRs of proteins play important roles in biological processes. In higher plants whose genomes have been sequenced, the correlation between IDRs and post-translational modifications (PTMs has been reported. The genomes of various eukaryotic algae as common ancestors of plants have also been sequenced. However, no analysis of the relationship to protein properties such as structure and PTMs in algae has been reported. Here, we describe correlations between IDR content and the number of PTM sites for phosphorylation, glycosylation, and ubiquitination, and between IDR content and regions rich in proline, glutamic acid, serine, and threonine (PEST and transmembrane helices in the sequences of 20 algae proteomes. Phosphorylation, O-glycosylation, ubiquitination, and PEST preferentially occurred in disordered regions. In contrast, transmembrane helices were favored in ordered regions. N-glycosylation tended to occur in ordered regions in most of the studied algae; however, it correlated positively with disordered protein content in diatoms. Additionally, we observed that disordered protein content and the number of PTM sites were significantly increased in the species-specific protein clusters compared to common protein clusters among the algae. Moreover, there were specific relationships between IDRs and PTMs among the algae from different groups.

  18. In Silico Analysis of Correlations between Protein Disorder and Post-Translational Modifications in Algae.

    Science.gov (United States)

    Kurotani, Atsushi; Sakurai, Tetsuya

    2015-08-20

    Recent proteome analyses have reported that intrinsically disordered regions (IDRs) of proteins play important roles in biological processes. In higher plants whose genomes have been sequenced, the correlation between IDRs and post-translational modifications (PTMs) has been reported. The genomes of various eukaryotic algae as common ancestors of plants have also been sequenced. However, no analysis of the relationship to protein properties such as structure and PTMs in algae has been reported. Here, we describe correlations between IDR content and the number of PTM sites for phosphorylation, glycosylation, and ubiquitination, and between IDR content and regions rich in proline, glutamic acid, serine, and threonine (PEST) and transmembrane helices in the sequences of 20 algae proteomes. Phosphorylation, O-glycosylation, ubiquitination, and PEST preferentially occurred in disordered regions. In contrast, transmembrane helices were favored in ordered regions. N-glycosylation tended to occur in ordered regions in most of the studied algae; however, it correlated positively with disordered protein content in diatoms. Additionally, we observed that disordered protein content and the number of PTM sites were significantly increased in the species-specific protein clusters compared to common protein clusters among the algae. Moreover, there were specific relationships between IDRs and PTMs among the algae from different groups.

  19. Socio-economic factors of bacillary dysentery based on spatial correlation analysis in Guangxi Province, China.

    Directory of Open Access Journals (Sweden)

    Chengjing Nie

    Full Text Available BACKGROUND: In the past decade, bacillary dysentery was still a big public health problem in China, especially in Guangxi Province, where thousands of severe diarrhea cases occur every year. METHODS: Reported bacillary dysentery cases in Guangxi Province were obtained from local Centers for Diseases Prevention and Control. The 14 socio-economic indexes were selected as potential explanatory variables for the study. The spatial correlation analysis was used to explore the associations between the selected factors and bacillary dysentery incidence at county level, which was based on the software of ArcGIS10.2 and GeoDA 0.9.5i. RESULTS: The proportion of primary industry, the proportion of younger than 5-year-old children in total population, the number of hospitals per thousand persons and the rates of bacillary dysentery incidence show statistically significant positive correlation. But the proportion of secondary industry, per capital GDP, per capital government revenue, rural population proportion, popularization rate of tap water in rural area, access rate to the sanitation toilets in rural, number of beds in hospitals per thousand persons, medical and technical personnel per thousand persons and the rate of bacillary dysentery incidence show statistically significant negative correlation. The socio-economic factors can be divided into four aspects, including economic development, health development, medical development and human own condition. The four aspects were not isolated from each other, but interacted with each other.

  20. Estimation of variation and correlation analysis for yield components in black currant cultivars

    Directory of Open Access Journals (Sweden)

    Rakonjac Vera

    2015-01-01

    Full Text Available Creating genotypes that will be characterized by high yields, good quality and other favorable agronomic characters is a major objective of most currant breeding programs worldwide. For easier and faster achievement of these goals and identification of superior genotypes suitable for use as parents in future hybridization programs, study of genetic parameters seems to be obligatory. In this regard, the aims of our study were to estimate components of variability and heritability, and do correlation analysis for yield components in order to determine efficient strategies for improving yield in black currant breeding programs. Significant differences between cultivars were established for all studied traits. A high proportion of genotypic variance was found with bush width, no. of shoots per bush, bunch weight and berry weight indicating that genetic improvement for these traits through breeding was achievable. Opposite, seasonal variance was high for bush height, no. of bunch per bush and yield. The high heritability coefficients (0.80-0.94 detected for all traits studied reflect the close agreement between their phenotypic and genotypic values. Also, most pairs of traits were similarly correlated at both phenotypic and genotypic levels. So, yield was significantly and positively correlated with bush height, no of bunch per bush and bunch weight. These results imply a rapid response of black currants to selection. [Projekat Ministarstva nauke Republike Srbije, br. 46013 i FP7 Project AREA 316004

  1. Correlation and path coefficient analysis of quantitative characters in spine gourd (Momordica dioica Roxb.).

    Science.gov (United States)

    Aliya, F; Begum, H; Reddy, M T; Sivaraj, N; Pandravada, S R; Narshimulu, G

    2014-05-01

    Fifty genotypes of spine gourd (Momordica dioica Roxb.) were evaluated in a randomized block design with two replications at the Vegetable Research Station, Rajendranagar, Hyderabad, Andhra Pradesh, India during kharif, 2012. Correlation and path coefficient analysis were carried out to study the character association and contribution, respectively for twelve quantitative characters namely vine length (m), number of stems per plant, days to first female flower appearance, first female flowering node, days to first fruit harvest, days to last fruit harvest, fruiting period (days), fruit length (cm), fruit width (cm), fruit weight (g), number of fruits per plant and fruit yield per plant (kg) for identification of the potential selection indices. Correlation and path coefficient analyses revealed that fruiting period and number of fruits per plant not only had positively significant correlation with fruit yield but also had positively high direct effect on it and are regarded as the main determinants of fruit yield. Days to first fruit harvest had positively moderate direct effect on fruit yield and its association was negatively significant, days to last fruit harvest had negatively high direct effect on fruit yield and its association was significant positively, hence restricted simultaneous selection can be made for days to first fruit harvest and days to last fruit harvest. The improvement in fruit yield can be effective if selection is based on days to first fruit harvest, days to last fruit harvest, fruiting period and number of fruits per plant.

  2. Rates and correlates of suicidal ideation among stroke survivors: a meta-analysis.

    Science.gov (United States)

    Bartoli, Francesco; Pompili, Maurizio; Lillia, Nicoletta; Crocamo, Cristina; Salemi, Giuseppe; Clerici, Massimo; Carrà, Giuseppe

    2017-06-01

    A better understanding of the epidemiological impact of suicidal ideation after stroke is required to identify subjects needing personalised interventions. The aim of this meta-analysis was to estimate rates and correlates of suicidal ideation among stroke survivors. We searched via Ovid, Medline, Embase and PsycInfo from database inception until August 2016. Predefined outcomes were (1) rates of suicidal ideation based on random-effects pooled proportion and (2) relevant sociodemographic and clinical correlates, using random-effects odds ratio (OR) or standardised mean difference (SMD) for categorical and continuous variables, respectively. Fifteen studies and 13 independent samples, accounting for 10 400 subjects, were included in meta-analyses. The pooled proportion of suicidal ideation among stroke survivors was 11.8% (7.4% to 16.2%), with high heterogeneity across studies (I 2 =97.3%). Current (OR=11.50; psuicidal ideation. Moreover, suicidal ideation was less likely in stroke survivors who were married (OR=0.63; psuicidal ideation. Thus, there is enough evidence to support the use of routine screening and early interventions to prevent and treat suicidal ideation after stroke, especially among subjects carrying specific correlates. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

  3. Correlations between the signal complexity of cerebral and cardiac electrical activity: a multiscale entropy analysis.

    Directory of Open Access Journals (Sweden)

    Pei-Feng Lin

    Full Text Available The heart begins to beat before the brain is formed. Whether conventional hierarchical central commands sent by the brain to the heart alone explain all the interplay between these two organs should be reconsidered. Here, we demonstrate correlations between the signal complexity of brain and cardiac activity. Eighty-seven geriatric outpatients with healthy hearts and varied cognitive abilities each provided a 24-hour electrocardiography (ECG and a 19-channel eye-closed routine electroencephalography (EEG. Multiscale entropy (MSE analysis was applied to three epochs (resting-awake state, photic stimulation of fast frequencies (fast-PS, and photic stimulation of slow frequencies (slow-PS of EEG in the 1-58 Hz frequency range, and three RR interval (RRI time series (awake-state, sleep and that concomitant with the EEG for each subject. The low-to-high frequency power (LF/HF ratio of RRI was calculated to represent sympatho-vagal balance. With statistics after Bonferroni corrections, we found that: (a the summed MSE value on coarse scales of the awake RRI (scales 11-20, RRI-MSE-coarse were inversely correlated with the summed MSE value on coarse scales of the resting-awake EEG (scales 6-20, EEG-MSE-coarse at Fp2, C4, T6 and T4; (b the awake RRI-MSE-coarse was inversely correlated with the fast-PS EEG-MSE-coarse at O1, O2 and C4; (c the sleep RRI-MSE-coarse was inversely correlated with the slow-PS EEG-MSE-coarse at Fp2; (d the RRI-MSE-coarse and LF/HF ratio of the awake RRI were correlated positively to each other; (e the EEG-MSE-coarse at F8 was proportional to the cognitive test score; (f the results conform to the cholinergic hypothesis which states that cognitive impairment causes reduction in vagal cardiac modulation; (g fast-PS significantly lowered the EEG-MSE-coarse globally. Whether these heart-brain correlations could be fully explained by the central autonomic network is unknown and needs further exploration.

  4. Correlation between Parameters of Calcaneal Quantitative Ultrasound and Hip Structural Analysis in Osteoporotic Fracture Patients.

    Directory of Open Access Journals (Sweden)

    Licheng Zhang

    Full Text Available Calcaneal quantitative ultrasound (QUS, which is used in the evaluation of osteoporosis, is believed to be intimately associated with the characteristics of the proximal femur. However, the specific associations of calcaneal QUS with characteristics of the hip sub-regions remain unclear.A cross-sectional assessment of 53 osteoporotic patients was performed for the skeletal status of the heel and hip.We prospectively enrolled 53 female osteoporotic patients with femoral fractures. Calcaneal QUS, dual energy X-ray absorptiometry (DXA, and hip structural analysis (HSA were performed for each patient. Femoral heads were obtained during the surgery, and principal compressive trabeculae (PCT were extracted by a three-dimensional printing technique-assisted method. Pearson's correlation between QUS measurement with DXA, HSA-derived parameters and Young's modulus were calculated in order to evaluate the specific association of QUS with the parameters for the hip sub-regions, including the femoral neck, trochanteric and Ward's areas, and the femoral shaft, respectively.Significant correlations were found between estimated BMD (Est.BMD and BMD of different sub-regions of proximal femur. However, the correlation coefficient of trochanteric area (r = 0.356, p = 0.009 was higher than that of the neck area (r = 0.297, p = 0.031 and total proximal femur (r = 0.291, p = 0.034. Furthermore, the quantitative ultrasound index (QUI was significantly correlated with the HSA-derived parameters of the trochanteric area (r value: 0.315-0.356, all p<0.05 as well as with the Young's modulus of PCT from the femoral head (r = 0.589, p<0.001.The calcaneal bone had an intimate association with the trochanteric cancellous bone. To a certain extent, the parameters of the calcaneal QUS can reflect the characteristics of the trochanteric area of the proximal hip, although not specifically reflective of those of the femoral neck or shaft.

  5. Early Retirement: A Meta-Analysis of Its Antecedent and Subsequent Correlates

    Science.gov (United States)

    Topa, Gabriela; Depolo, Marco; Alcover, Carlos-Maria

    2018-01-01

    Early or voluntary retirement (ER) can be defined as the full exit from an organizational job or career path of long duration, decided by individuals of a certain age at the mid or late career before mandatory retirement age, with the aim of reducing their attachment to work and closing a process of gradual psychological disengagement from working life. Given the swinging movements that characterize employment policies, the potential effects of ER—both for individuals and society—are still controversial. This meta-analysis examined the relationships between ER and its antecedent and subsequent correlates. Our review of the literature was generated with 151 empirical studies, containing a total number of 706,937 participants, with a wide range of sample sizes (from N = 27 to N = 127,384 participants) and 380 independent effect sizes (ESs), which included 171 independent samples. A negligible ES value for antecedent correlates of early retirement (family pull, job stress, job satisfaction, and income) was obtained (which ranged from r = −0.13 to 0.19), while a fair ES was obtained for workplace timing for retirement, organizational pressures, financial security, and poor physical and mental health, (ranging from r = 0.28 to 0.25). Regarding ER subsequent correlates, poor ESs were obtained, ranging from r = 0.08 to 0.18 for the relationships with subsequent correlates, and fair ESs only for social engagement (r = −0.25). Examination of the potential moderator variables has been conducted. Only a reduced percentage of variability of primary studies has been explained by moderators. Although potential moderator factors were examined, there are several unknown or not measurable factors which contribute to ER and about which there are very little data available. The discussion is aimed to offer theoretical and empirical implications suggestion in order to improve employee's well-being. PMID:29354075

  6. Prevalence and correlates of adult overweight in the Muslim world: analysis of 46 countries.

    Science.gov (United States)

    Kahan, D

    2015-04-01

    The primary objectives of the study were to calculate overweight prevalence (body mass index ≥ 25.0) and simple correlations between 10 demographic, social welfare and behavioural variables and overweight prevalence for Muslim countries (populations >50% Muslim; N = 46). Overweight data for a country's total, male and female populations were extracted from the World Health Organization's (WHO) STEPwise country reports and relevant publications. Country-level data for potential correlates were extracted from multiple sources: Central Intelligence Agency (literacy), Gallup Poll (religiosity), United Nations (agricultural employment, food supply, gender inequality, human development), World Bank (automobile ownership, Internet, labour force) and WHO (physical inactivity). The overall, male and female overweight prevalence was 37.4, 33.0 and 42.1%, respectively. Prevalence estimates significantly differed by economic classification, gender and ethnicity. Middle- and upper income countries were 1.54-7.76 (95% confidence interval [CI]: 1.49-8.07) times more likely overweight than low-income countries, females were 1.48 (CI: 1.45-1.50) times more likely overweight than males and Arab countries were 2.92 (CI: 2.86-2.97) times more likely overweight than non-Arab countries. All 10 of the potential correlates were significantly associated with overweight for at least one permutation (total, economic classification, gender, ethnicity). The greater percentage of poorer countries among non-Arab Muslim countries, which compared with Arab countries have not as rapidly been transformed by globalization, nutrition transition and urbanization, may partially explain prevalence differences. Evaluation of correlational data generally followed associations seen in non-Muslim countries but more complex analysis of subnational data is needed. Arab women are a particularly vulnerable subgroup and governments should act within religious and cultural parameters to provide

  7. Rainfall prediction of Cimanuk watershed regions with canonical correlation analysis (CCA)

    Science.gov (United States)

    Rustiana, Shailla; Nurani Ruchjana, Budi; Setiawan Abdullah, Atje; Hermawan, Eddy; Berliana Sipayung, Sinta; Gede Nyoman Mindra Jaya, I.; Krismianto

    2017-10-01

    Rainfall prediction in Indonesia is very influential on various development sectors, such as agriculture, fisheries, water resources, industry, and other sectors. The inaccurate predictions can lead to negative effects. Cimanuk watershed is one of the main pillar of water resources in West Java. This watersheds divided into three parts, which is a headwater of Cimanuk sub-watershed, Middle of Cimanuk sub-watershed and downstream of Cimanuk sub- watershed. The flow of this watershed will flow through the Jatigede reservoir and will supply water to the north-coast area in the next few years. So, the reliable model of rainfall prediction is very needed in this watershed. Rainfall prediction conducted with Canonical Correlation Analysis (CCA) method using Climate Predictability Tool (CPT) software. The prediction is every 3months on 2016 (after January) based on Climate Hazards group Infrared Precipitation with Stations (CHIRPS) data over West Java. Predictors used in CPT were the monthly data index of Nino3.4, Dipole Mode (DMI), and Monsoon Index (AUSMI-ISMI-WNPMI-WYMI) with initial condition January. The initial condition is chosen by the last data update. While, the predictant were monthly rainfall data CHIRPS region of West Java. The results of prediction rainfall showed by skill map from Pearson Correlation. High correlation of skill map are on MAM (Mar-Apr-May), AMJ (Apr-May-Jun), and JJA (Jun-Jul-Aug) which means the model is reliable to forecast rainfall distribution over Cimanuk watersheds region (over West Java) on those seasons. CCA score over those season prediction mostly over 0.7. The accuracy of the model CPT also indicated by the Relative Operating Characteristic (ROC) curve of the results of Pearson correlation 3 representative point of sub-watershed (Sumedang, Majalengka, and Cirebon), were mostly located in the top line of non-skill, and evidenced by the same of rainfall patterns between observation and forecast. So, the model of CPT with CCA method

  8. Early Retirement: A Meta-Analysis of Its Antecedent and Subsequent Correlates

    Directory of Open Access Journals (Sweden)

    Gabriela Topa

    2018-01-01

    Full Text Available Early or voluntary retirement (ER can be defined as the full exit from an organizational job or career path of long duration, decided by individuals of a certain age at the mid or late career before mandatory retirement age, with the aim of reducing their attachment to work and closing a process of gradual psychological disengagement from working life. Given the swinging movements that characterize employment policies, the potential effects of ER—both for individuals and society—are still controversial. This meta-analysis examined the relationships between ER and its antecedent and subsequent correlates. Our review of the literature was generated with 151 empirical studies, containing a total number of 706,937 participants, with a wide range of sample sizes (from N = 27 to N = 127,384 participants and 380 independent effect sizes (ESs, which included 171 independent samples. A negligible ES value for antecedent correlates of early retirement (family pull, job stress, job satisfaction, and income was obtained (which ranged from r = −0.13 to 0.19, while a fair ES was obtained for workplace timing for retirement, organizational pressures, financial security, and poor physical and mental health, (ranging from r = 0.28 to 0.25. Regarding ER subsequent correlates, poor ESs were obtained, ranging from r = 0.08 to 0.18 for the relationships with subsequent correlates, and fair ESs only for social engagement (r = −0.25. Examination of the potential moderator variables has been conducted. Only a reduced percentage of variability of primary studies has been explained by moderators. Although potential moderator factors were examined, there are several unknown or not measurable factors which contribute to ER and about which there are very little data available. The discussion is aimed to offer theoretical and empirical implications suggestion in order to improve employee's well-being.

  9. Regression analysis of longitudinal data with correlated censoring and observation times.

    Science.gov (United States)

    Li, Yang; He, Xin; Wang, Haiying; Sun, Jianguo

    2016-07-01

    Longitudinal data occur in many fields such as the medical follow-up studies that involve repeated measurements. For their analysis, most existing approaches assume that the observation or follow-up times are independent of the response process either completely or given some covariates. In practice, it is apparent that this may not be true. In this paper, we present a joint analysis approach that allows the possible mutual correlations that can be characterized by time-dependent random effects. Estimating equations are developed for the parameter estimation and the resulted estimators are shown to be consistent and asymptotically normal. The finite sample performance of the proposed estimators is assessed through a simulation study and an illustrative example from a skin cancer study is provided.

  10. Spectral and correlation analysis of soft X-ray signals from the Joint European Torus tokamak

    International Nuclear Information System (INIS)

    Karlsson, J.; Pazsit, I.

    1997-01-01

    Tomographic methods applied to soft X-rays emitted from a fusion plasma have long been used to diagnose and interpret magnetohydrodynamic and other plasma activities. However, fluctuation analysis has recently been proposed as a complementary method to tomography. The novelty of the suggested method is that the various modes can be determined without tomographic inversion. This paper reports on the results of correlation and spectral analysis of soft X-ray data. The seven measurements analyzed were made by the Joint European Torus (JET) Joint Undertaking using their old soft X-ray measurement system. Auto power spectral densities and phase relations were evaluated from the measured signals as functions of the lines of sight. The fundamental mode m=n=1 was identified in several measurements. The corresponding frequency and toroidal rotation velocity were determined. Higher order modes were also observed and identified. Furthermore, simple model calculations were performed and the results compared with evaluated auto-spectra. (orig.)

  11. Pyrcca: regularized kernel canonical correlation analysis in Python and its applications to neuroimaging

    Directory of Open Access Journals (Sweden)

    Natalia Y Bilenko

    2016-11-01

    Full Text Available In this article we introduce Pyrcca, an open-source Python package for performing canonical correlation analysis (CCA. CCA is a multivariate analysis method for identifying relationships between sets of variables. Pyrcca supports CCA with or without regularization, and with or without linear, polynomial, or Gaussian kernelization. We first use an abstract example to describe Pyrcca functionality. We then demonstrate how Pyrcca can be used to analyze neuroimaging data. Specifically, we use Pyrcca to implement cross-subject comparison in a natural movie functional magnetic resonance imaging (fMRI experiment by finding a data-driven set of functional response patterns that are similar across individuals. We validate this cross-subject comparison method in Pyrcca by predicting responses to novel natural movies across subjects. Finally, we show how Pyrcca can reveal retinotopic organization in brain responses to natural movies without the need for an explicit model.

  12. Pyrcca: Regularized Kernel Canonical Correlation Analysis in Python and Its Applications to Neuroimaging.

    Science.gov (United States)

    Bilenko, Natalia Y; Gallant, Jack L

    2016-01-01

    In this article we introduce Pyrcca, an open-source Python package for performing canonical correlation analysis (CCA). CCA is a multivariate analysis method for identifying relationships between sets of variables. Pyrcca supports CCA with or without regularization, and with or without linear, polynomial, or Gaussian kernelization. We first use an abstract example to describe Pyrcca functionality. We then demonstrate how Pyrcca can be used to analyze neuroimaging data. Specifically, we use Pyrcca to implement cross-subject comparison in a natural movie functional magnetic resonance imaging (fMRI) experiment by finding a data-driven set of functional response patterns that are similar across individuals. We validate this cross-subject comparison method in Pyrcca by predicting responses to novel natural movies across subjects. Finally, we show how Pyrcca can reveal retinotopic organization in brain responses to natural movies without the need for an explicit model.

  13. Interconnectivity among Assessments from Rating Agencies: Using Cluster and Correlation Analysis

    Directory of Open Access Journals (Sweden)

    Jaroslav Krejčíř

    2014-09-01

    Full Text Available The aim of this paper is to determine whether there is a dependency among leading rating agencies assessments. Rating agencies are important part of global economy. Great attention has been paid to activities of rating agencies since 2007, when there was a financial crisis. One of the main causes of this crisis was identified credit rating agencies. This paper is focused on an existence of mutual interconnectivity among assessments from three leading rating agencies. The method used for this determines is based on cluster analysis and subsequently correlation analysis and the test of independence. Credit rating assessments of Greece and Spain were chosen to the determination of this mutual interconnectivity due to the fact that these countries are most talked euro­area countries. The significant dependence of the assessment from different rating agencies has been demonstrated.

  14. A New Theoretical Analysis of the Effects of Short Range Correlations in Inclusive Lepton Scattering

    Science.gov (United States)

    Benedetta Mezzetti, Chiara; Ciofi Degli Atti, Claudio

    2009-05-01

    Recently, evidence of short range correlations (SRC) has been provided by experimental data on inclusive lepton A(e, e')X scattering by the observation of a scaling behavior of the ratios of the cross sections on heavy nuclei to those on the deuteron and ^3He. Other attempts to get information on SRC rely on the concept of Y-scaling, whose interest has been renewed by new Jlab data. A new approach to Y-scaling, relying on the definition of a new relativistic scaling variable which incorporates the momentum dependence of the excitation energy of the (A - 1) system is presented, with the resulting scaling function being closely related to the longitudinal momentum distributions. Taking into account final state interaction effects, the new analysis of experimental data on nuclei, ranging from ^3He to Nuclear Matter, provides unique information on the nucleon momentum distributions and confirms the analysis in terms of cross section ratios.

  15. Femtoscopic analysis of baryon correlations in ultra-relativistic heavy-ion collisions registered by ALICE

    CERN Document Server

    AUTHOR|(INSPIRE)INSPIRE-00361630

    Heavy-ion collisions at ultra-relativistic energies give a unique possibility to create and to analyse the Quark-Gluon Plasma predicted by the theory of Quantum Chromodynamics. The research on the properties of such state of matter is crucial for understanding the features of the strongly interacting system. Experimental results reveal the collective behaviour of matter created in the heavy-ion collisions at ultra-relativistic energies. The existence of this effect can be verified by the measurement of the transverse mass dependence of the source size extracted using different particle species. Such characteristics can be determined using the analysis technique called femtoscopy. This method is based on the correlations of particles with small relative momenta which originate from the effects of Quantum Statistics as well as the strong and Coulomb Final State Interactions. A recent analysis of the particle production at the highest available collision energies of heavy-ion collisions reveals the puzzling res...

  16. A retrospective analysis of compact fluorescent lamp experience curves and their correlations to deployment programs

    International Nuclear Information System (INIS)

    Smith, Sarah Josephine; Wei, Max; Sohn, Michael D.

    2016-01-01

    Experience curves are useful for understanding technology development and can aid in the design and analysis of market transformation programs. Here, we employ a novel approach to create experience curves, to examine both global and North American compact fluorescent lamp (CFL) data for the years 1990–2007. We move away from the prevailing method of fitting a single, constant, exponential curve to data and instead search for break points where changes in the learning rate may have occurred. Our analysis suggests a learning rate of approximately 21% for the period of 1990–1997, and 51% and 79% in global and North American datasets, respectively, after 1998. We use price data for this analysis; therefore our learning rates encompass developments beyond typical “learning by doing”, including supply chain impacts such as market competition. We examine correlations between North American learning rates and the initiation of new programs, abrupt technological advances, and economic and political events, and find an increased learning rate associated with design advancements and federal standards programs. Our findings support the use of segmented experience curves for retrospective and prospective technology analysis, and may imply that investments in technology programs have contributed to an increase of the CFL learning rate. - Highlights: • We develop a segmented regression technique to estimate historical CFL learning curves. • CFL experience curves do not have a constant learning rate. • CFLs exhibited a learning rate of approximately 21% from 1990 to 1997. • The CFL learning rate significantly increased after 1998. • Increased CFL learning rate is correlated to technology deployment programs.

  17. On the Analysis of Case-Control Studies in Cluster-correlated Data Settings.

    Science.gov (United States)

    Haneuse, Sebastien; Rivera-Rodriguez, Claudia

    2018-01-01

    In resource-limited settings, long-term evaluation of national antiretroviral treatment (ART) programs often relies on aggregated data, the analysis of which may be subject to ecological bias. As researchers and policy makers consider evaluating individual-level outcomes such as treatment adherence or mortality, the well-known case-control design is appealing in that it provides efficiency gains over random sampling. In the context that motivates this article, valid estimation and inference requires acknowledging any clustering, although, to our knowledge, no statistical methods have been published for the analysis of case-control data for which the underlying population exhibits clustering. Furthermore, in the specific context of an ongoing collaboration in Malawi, rather than performing case-control sampling across all clinics, case-control sampling within clinics has been suggested as a more practical strategy. To our knowledge, although similar outcome-dependent sampling schemes have been described in the literature, a case-control design specific to correlated data settings is new. In this article, we describe this design, discuss balanced versus unbalanced sampling techniques, and provide a general approach to analyzing case-control studies in cluster-correlated settings based on inverse probability-weighted generalized estimating equations. Inference is based on a robust sandwich estimator with correlation parameters estimated to ensure appropriate accounting of the outcome-dependent sampling scheme. We conduct comprehensive simulations, based in part on real data on a sample of N = 78,155 program registrants in Malawi between 2005 and 2007, to evaluate small-sample operating characteristics and potential trade-offs associated with standard case-control sampling or when case-control sampling is performed within clusters.

  18. Analysis of cross-correlations in electroencephalogram signals as an approach to proactive diagnosis of schizophrenia

    Science.gov (United States)

    Timashev, Serge F.; Panischev, Oleg Yu.; Polyakov, Yuriy S.; Demin, Sergey A.; Kaplan, Alexander Ya.

    2012-02-01

    We apply flicker-noise spectroscopy (FNS), a time series analysis method operating on structure functions and power spectrum estimates, to study the clinical electroencephalogram (EEG) signals recorded in children/adolescents (11 to 14 years of age) with diagnosed schizophrenia-spectrum symptoms at the National Center for Psychiatric Health (NCPH) of the Russian Academy of Medical Sciences. The EEG signals for these subjects were compared with the signals for a control sample of chronically depressed children/adolescents. The purpose of the study is to look for diagnostic signs of subjects' susceptibility to schizophrenia in the FNS parameters for specific electrodes and cross-correlations between the signals simultaneously measured at different points on the scalp. Our analysis of EEG signals from scalp-mounted electrodes at locations F3 and F4, which are symmetrically positioned in the left and right frontal areas of cerebral cortex, respectively, demonstrates an essential role of frequency-phase synchronization, a phenomenon representing specific correlations between the characteristic frequencies and phases of excitations in the brain. We introduce quantitative measures of frequency-phase synchronization and systematize the values of FNS parameters for the EEG data. The comparison of our results with the medical diagnoses for 84 subjects performed at NCPH makes it possible to group the EEG signals into 4 categories corresponding to different risk levels of subjects' susceptibility to schizophrenia. We suggest that the introduced quantitative characteristics and classification of cross-correlations may be used for the diagnosis of schizophrenia at the early stages of its development.

  19. Correlation between histological outcome and surgical cartilage repair technique in the knee: A meta-analysis.

    Science.gov (United States)

    DiBartola, Alex C; Everhart, Joshua S; Magnussen, Robert A; Carey, James L; Brophy, Robert H; Schmitt, Laura C; Flanigan, David C

    2016-06-01

    Compare histological outcomes after microfracture (MF), autologous chondrocyte implantation (ACI), and osteochondral autograft transfer (OATS). Literature review using PubMed MEDLINE, SCOPUS, Cumulative Index for Nursing and Allied Health Literature (CINAHL), and Cochrane Collaboration Library. Inclusion criteria limited to English language studies International Cartilage Repair Society (ICRS) grading criteria for cartilage analysis after ACI (autologous chondrocyte implantation), MF (microfracture), or OATS (osteochondral autografting) repair techniques. Thirty-three studies investigating 1511 patients were identified. Thirty evaluated ACI or one of its subtypes, six evaluated MF, and seven evaluated OATS. There was no evidence of publication bias (Begg's p=0.48). No statistically significant correlation was found between percent change in clinical outcome and percent biopsies showing ICRS Excellent scores (R(2)=0.05, p=0.38). Percent change in clinical outcome and percent of biopsies showing only hyaline cartilage were significantly associated (R(2)=0.24, p=0.024). Mean lesion size and histological outcome were not correlated based either on percent ICRS Excellent (R(2)=0.03, p=0.50) or percent hyaline cartilage only (R(2)=0.01, p=0.67). Most common lesion location and histological outcome were not correlated based either on percent ICRS Excellent (R(2)=0.03, p=0.50) or percent hyaline cartilage only (R(2)=0.01, p=0.67). Microfracture has poorer histologic outcomes than other cartilage repair techniques. OATS repairs primarily are comprised of hyaline cartilage, followed closely by cell-based techniques, but no significant difference was found cartilage quality using ICRS grading criteria among OATS, ACI-C, MACI, and ACI-P. IV, meta-analysis. Copyright © 2016 Elsevier B.V. All rights reserved.

  20. Correlative Spectral Analysis of Gamma-Ray Bursts using Swift-BAT and GLAST-GBM

    International Nuclear Information System (INIS)

    Stamatikos, Michael; Sakamoto, Taka; Band, David L.

    2008-01-01

    We discuss the preliminary results of spectral analysis simulations involving anticipated correlated multi-wavelength observations of gamma-ray bursts (GRBs) using Swift's Burst Alert Telescope (BAT) and the Gamma-Ray Large Area Space Telescope's (GLAST) Burst Monitor (GLAST-GBM), resulting in joint spectral fits, including characteristic photon energy (E peak ) values, for a conservative annual estimate of ∼30 GRBs. The addition of BAT's spectral response will (i) complement in-orbit calibration efforts of GBM's detector response matrices, (ii) augment GLAST's low energy sensitivity by increasing the ∼20-100 keV effective area, (iii) facilitate ground-based follow-up efforts of GLAST GRBs by increasing GBM's source localization precision, and (iv) help identify a subset of non-triggered GRBs discovered via off-line GBM data analysis. Such multi-wavelength correlative analyses, which have been demonstrated by successful joint-spectral fits of Swift-BAT GRBs with other higher energy detectors such as Konus-WIND and Suzaku-WAM, would enable the study of broad-band spectral and temporal evolution of prompt GRB emission over three energy decades, thus potentially increasing science return without placing additional demands upon mission resources throughout their contemporaneous orbital tenure over the next decade.

  1. Correlative Spectral Analysis of Gamma-Ray Bursts using Swift-BAT and GLAST-GBM

    International Nuclear Information System (INIS)

    Stamatikos, Michael; Sakamoto, Takanori; Band, David L.

    2008-01-01

    We discuss the preliminary results of spectral analysis simulations involving anticipated correlated multi-wavelength observations of gamma-ray bursts (GRBs) using Swift's Burst Alert Telescope (BAT) and the Gamma-Ray Large Area Space Telescope's (GLAST) Burst Monitor (GLAST-GBM), resulting in joint spectral fits, including characteristic photon energy (E peak ) values, for a conservative annual estimate of ∼30 GRBs. The addition of BAT/s spectral response will (i) complement in-orbit calibration efforts of GBM's detector response matrices, (ii) augment GLAST's low energy sensitivity by increasing the ∼20-100 keV effective area, (iii) facilitate ground-based follow-up efforts of GLAST GRBs by increasing GBM's source localization precision, and (iv) help identify a subset of non-triggered GRBs discovered via off-line GBM data analysis. Such multi-wavelength correlative analyses, which have been demonstrated by successful joint-spectral fits of Swift-BAT GRBs with other higher energy detectors such as Konus-WIND and Suzaku-WAM, would enable the study of broad-band spectral and temporal evolution of prompt GRB emission over three energy decades, thus potentially increasing science return without placing additional demands upon mission resources throughout their contemporaneous orbital tenure over the next decade

  2. Validity studies among hierarchical methods of cluster analysis using cophenetic correlation coefficient

    Energy Technology Data Exchange (ETDEWEB)

    Carvalho, Priscilla R.; Munita, Casimiro S.; Lapolli, André L., E-mail: prii.ramos@gmail.com, E-mail: camunita@ipen.br, E-mail: alapolli@ipen.br [Instituto de Pesquisas Energéticas e Nucleares (IPEN/CNEN-SP), São Paulo, SP (Brazil)

    2017-07-01

    The literature presents many methods for partitioning of data base, and is difficult choose which is the most suitable, since the various combinations of methods based on different measures of dissimilarity can lead to different patterns of grouping and false interpretations. Nevertheless, little effort has been expended in evaluating these methods empirically using an archaeological data base. In this way, the objective of this work is make a comparative study of the different cluster analysis methods and identify which is the most appropriate. For this, the study was carried out using a data base of the Archaeometric Studies Group from IPEN-CNEN/SP, in which 45 samples of ceramic fragments from three archaeological sites were analyzed by instrumental neutron activation analysis (INAA) which were determinate the mass fraction of 13 elements (As, Ce, Cr, Eu, Fe, Hf, La, Na, Nd, Sc, Sm, Th, U). The methods used for this study were: single linkage, complete linkage, average linkage, centroid and Ward. The validation was done using the cophenetic correlation coefficient and comparing these values the average linkage method obtained better results. A script of the statistical program R with some functions was created to obtain the cophenetic correlation. By means of these values was possible to choose the most appropriate method to be used in the data base. (author)

  3. Correlation analysis of Carbon Dioxide, Oxygen, Temperature and Humidity of Yadavaran Oil field in Khuzestan province

    Directory of Open Access Journals (Sweden)

    Mohammad velayatzadeh

    2018-02-01

    Full Text Available Background & Objective:Emission of Carbon dioxide in the atmosphere has an important role in increasing temperatures and, its higher concentration can effect on human health. Due to this issue, this study is aimed to measure the amount of the released carbon dioxide into the atmosphere in different part of Yadavaran Oil field and compare with international standards in 2017. Material & Methods:The present investigation was accomplished in Yadavaran oil field of Khuzestan province of Iran in 2017. In this study measurement of parameters including carbon dioxide, carbon monoxide, oxygen, relative humidity and temperature was done in 64 stations with 3 replications using ALTAIR 4X and Trotec BZ30. Data was analyzed by one-way ANOVA and Kolmogorov–Smirnov tests. Moreover, Correlation analysis was performed using Pearson and Spearman coefficients. Results:The results showed that concentration range of carbon dioxide and oxygen was 490-590 and 19-208ppm respectively. Also, the highest and lowest levels of carbon dioxide were 584.56±6.36 and 453.94±77.7 ppm in wet water camp and S10 wells (P 0.05 in the same order. Conclusion:Pearson and Spearman coefficient analysis showed no significant correlation between temperature, humidity, oxygen and carbon dioxide. According to the results, the concentration of carbon dioxide in different areas of the oil field of Yadavaran was acceptable.

  4. Validity studies among hierarchical methods of cluster analysis using cophenetic correlation coefficient

    International Nuclear Information System (INIS)

    Carvalho, Priscilla R.; Munita, Casimiro S.; Lapolli, André L.

    2017-01-01

    The literature presents many methods for partitioning of data base, and is difficult choose which is the most suitable, since the various combinations of methods based on different measures of dissimilarity can lead to different patterns of grouping and false interpretations. Nevertheless, little effort has been expended in evaluating these methods empirically using an archaeological data base. In this way, the objective of this work is make a comparative study of the different cluster analysis methods and identify which is the most appropriate. For this, the study was carried out using a data base of the Archaeometric Studies Group from IPEN-CNEN/SP, in which 45 samples of ceramic fragments from three archaeological sites were analyzed by instrumental neutron activation analysis (INAA) which were determinate the mass fraction of 13 elements (As, Ce, Cr, Eu, Fe, Hf, La, Na, Nd, Sc, Sm, Th, U). The methods used for this study were: single linkage, complete linkage, average linkage, centroid and Ward. The validation was done using the cophenetic correlation coefficient and comparing these values the average linkage method obtained better results. A script of the statistical program R with some functions was created to obtain the cophenetic correlation. By means of these values was possible to choose the most appropriate method to be used in the data base. (author)

  5. Combined use of correlation dimension and entropy as discriminating measures for time series analysis

    Science.gov (United States)

    Harikrishnan, K. P.; Misra, R.; Ambika, G.

    2009-09-01

    We show that the combined use of correlation dimension (D2) and correlation entropy (K2) as discriminating measures can extract a more accurate information regarding the different types of noise present in a time series data. For this, we make use of an algorithmic approach for computing D2 and K2 proposed by us recently [Harikrishnan KP, Misra R, Ambika G, Kembhavi AK. Physica D 2006;215:137; Harikrishnan KP, Ambika G, Misra R. Mod Phys Lett B 2007;21:129; Harikrishnan KP, Misra R, Ambika G. Pramana - J Phys, in press], which is a modification of the standard Grassberger-Proccacia scheme. While the presence of white noise can be easily identified by computing D2 of data and surrogates, K2 is a better discriminating measure to detect colored noise in the data. Analysis of time series from a real world system involving both white and colored noise is presented as evidence. To our knowledge, this is the first time that such a combined analysis is undertaken on a real world data.

  6. Interdependence between crude oil and world food prices: A detrended cross correlation analysis

    Science.gov (United States)

    Pal, Debdatta; Mitra, Subrata K.

    2018-02-01

    This article explores the changing interdependence between crude oil and world food prices at varying time scales using detrended cross correlation analysis that would answer whether the interdependence (if any) differed significantly between pre and post-crisis period. Unlike the previous studies that exogenously imposed break dates for dividing the time series into sub-samples, we tested whether the mean of the crude oil price changed over time to find evidence for structural changes in the crude oil price series and endogenously determine three break dates with minimum Bayesian information criterion scores. Accordingly, we divided the entire study period in four sample periods - January 1990 to October 1999, November 1999 to February 2005, March 2005 to September 2010, and October 2010 to July 2016, where the third sample period coincided with the period of food crisis and enabled us to compare the fuel-food interdependence across pre-crisis, during the crisis, and post-crisis periods. The results of the detrended cross correlation analysis extended corroborative evidence for increasing positive interdependence between the crude oil price and world food price index along with its sub-categories, namely dairy, cereals, vegetable oil, and sugar. The article ends with the implications of these results in the domain of food policy and the financial sector.

  7. A femtoscopic correlation analysis tool using the Schrödinger equation (CATS)

    Science.gov (United States)

    Mihaylov, D. L.; Mantovani Sarti, V.; Arnold, O. W.; Fabbietti, L.; Hohlweger, B.; Mathis, A. M.

    2018-05-01

    We present a new analysis framework called "Correlation Analysis Tool using the Schrödinger equation" (CATS) which computes the two-particle femtoscopy correlation function C( k), with k being the relative momentum for the particle pair. Any local interaction potential and emission source function can be used as an input and the wave function is evaluated exactly. In this paper we present a study on the sensitivity of C( k) to the interaction potential for different particle pairs: p-p, p-Λ, K^-p, K^+-p, p-Ξ ^- and Λ- Λ. For the p-p Argonne v_{18} and Reid Soft-Core potentials have been tested. For the other pair systems we present results based on strong potentials obtained from effective Lagrangians such as χ EFT for p-Λ, Jülich models for K(\\bar{K})-N and Nijmegen models for Λ-Λ. For the p-Ξ^- pairs we employ the latest lattice results from the HAL QCD collaboration. Our detailed study of different interacting particle pairs as a function of the source size and different potentials shows that femtoscopic measurements can be exploited in order to constrain the final state interactions among hadrons. In particular, small collision systems of the order of 1 fm, as produced in pp collisions at the LHC, seem to provide a suitable environment for quantitative studies of this kind.

  8. Volatility-constrained multifractal detrended cross-correlation analysis: Cross-correlation among Mainland China, US, and Hong Kong stock markets

    Science.gov (United States)

    Cao, Guangxi; Zhang, Minjia; Li, Qingchen

    2017-04-01

    This study focuses on multifractal detrended cross-correlation analysis of the different volatility intervals of Mainland China, US, and Hong Kong stock markets. A volatility-constrained multifractal detrended cross-correlation analysis (VC-MF-DCCA) method is proposed to study the volatility conductivity of Mainland China, US, and Hong Kong stock markets. Empirical results indicate that fluctuation may be related to important activities in real markets. The Hang Seng Index (HSI) stock market is more influential than the Shanghai Composite Index (SCI) stock market. Furthermore, the SCI stock market is more influential than the Dow Jones Industrial Average stock market. The conductivity between the HSI and SCI stock markets is the strongest. HSI was the most influential market in the large fluctuation interval of 1991 to 2014. The autoregressive fractionally integrated moving average method is used to verify the validity of VC-MF-DCCA. Results show that VC-MF-DCCA is effective.

  9. Financial liberalization and stock market cross-correlation: MF-DCCA analysis based on Shanghai-Hong Kong Stock Connect

    Science.gov (United States)

    Ruan, Qingsong; Zhang, Shuhua; Lv, Dayong; Lu, Xinsheng

    2018-02-01

    Based on the implementation of Shanghai-Hong Kong Stock Connect in China, this paper examines the effects of financial liberalization on stock market comovement using both multifractal detrended fluctuation analysis (MF-DFA) and multifractal detrended cross-correlation analysis (MF-DCCA) methods. Results based on MF-DFA confirm the multifractality of Shanghai and Hong Kong stock markets, and the market efficiency of Shanghai stock market increased after the implementation of this connect program. Besides, analysis based on MF-DCCA has verified the existence of persistent cross-correlation between Shanghai and Hong Kong stock markets, and the cross-correlation gets stronger after the launch of this liberalization program. Finally, we find that fat-tail distribution is the main source of multifractality in the cross-correlations before the stock connect program, while long-range correlation contributes to the multifractality after this program.

  10. Investigating the correlation between wastewater analysis and roadside drug testing in South Australia.

    Science.gov (United States)

    Bade, Richard; Tscharke, Benjamin J; Longo, Marie; Cooke, Richard; White, Jason M; Gerber, Cobus

    2018-04-10

    The societal impact of drug use is well known. An example is when drug-intoxicated drivers increase the burden on policing and healthcare services. This work presents the correlation of wastewater analysis (using UHPLC-MS/MS) and positive roadside drug testing results for methamphetamine, 3,4-methylenedioxymethamphetamine (MDMA) and cannabis from December 2011-December 2016 in South Australia. Methamphetamine and MDMA showed similar trends between the data sources with matching increases and decreases, respectively. Cannabis was relatively steady based on wastewater analysis, but the roadside drug testing data started to diverge in the final part of the measurement period. The ability to triangulate data as shown here validates both wastewater analysis and roadside drug testing. This suggests that changes in overall population drug use revealed by WWA is consistent and proportional with changes in drug-driving behaviours. The results show that, at higher levels of drug use as measured by wastewater analysis, there is an increase in drug driving in the community and therefore more strain on health services and police. Copyright © 2018 Elsevier B.V. All rights reserved.

  11. Canonical correlation analysis of factors involved in the occurrence of peptic ulcers.

    Science.gov (United States)

    Bayyurt, Nizamettin; Abasiyanik, M Fatih; Sander, Ersan; Salih, Barik A

    2007-01-01

    The impact of risk factors on the development of peptic ulcers has been shown to vary among different populations. We sought to establish a correlation between these factors and their involvement in the occurrence of peptic ulcers for which a canonical correlation analysis was applied. We included 7,014 patient records (48.6% women, 18.4% duodenal ulcer [DU], 4.6% gastric ulcer [GU]) of those underwent upper gastroendoscopy for the last 5 years. The variables measured are endoscopic findings (DU, GU, antral gastritis, erosive gastritis, pangastritis, pyloric deformity, bulbar deformity, bleeding, atrophy, Barret esophagus and gastric polyp) and risk factors (age, gender, Helicobacter pylori infection, smoking, alcohol, and nonsteroidal anti-inflammatory drugs [NSAIDs] and aspirin intake). We found that DU had significant positive correlation with bulbar deformity (P=2.6 x 10(-23)), pyloric deformity (P=2.6 x 10(-23)), gender (P=2.6 x 10(-23)), H. pylori (P=1.4 x 10(-15)), bleeding (P=6.9 x 10(-15)), smoking (P=1.4 x 10(-7)), aspirin use (P=1.1 x 10(-4)), alcohol intake (P=7.7 x 10(-4)), and NSAIDs (P=.01). GU had a significantly positive correlation with pyloric deformity (P=1,6 x 10(-15)), age (P=2.6 x 10(-14)), bleeding (P=3.7 x 10(-8)), gender (P=1.3 x 10(-7)), aspirin use (P=1.1 x 10(-6)), bulbar deformity (P=7.4 x 10(-4)), alcohol intake (P=.03), smoking (P=.04), and Barret esophagus (P=.03). The level of significance was much higher in some variables with DU than with GU and the correlations with GU in spite of being highly significant the majority, were small in magnitude. In conclusion, Turkish patients with the following endoscopic findings bulbar deformity and pyloric deformity are high-risk patients for peptic ulcers with the risk of the occurrence of DU being higher than that of GU. Factors such as H. pylori, smoking, alcohol use, and NSAIDs use (listed in a decreasing manner) are risk factors that have significant impact on the occurrence of DU

  12. Empirical mode decomposition and long-range correlation analysis of sunspot time series

    International Nuclear Information System (INIS)

    Zhou, Yu; Leung, Yee

    2010-01-01

    Sunspots, which are the best known and most variable features of the solar surface, affect our planet in many ways. The number of sunspots during a period of time is highly variable and arouses strong research interest. When multifractal detrended fluctuation analysis (MF-DFA) is employed to study the fractal properties and long-range correlation of the sunspot series, some spurious crossover points might appear because of the periodic and quasi-periodic trends in the series. However many cycles of solar activities can be reflected by the sunspot time series. The 11-year cycle is perhaps the most famous cycle of the sunspot activity. These cycles pose problems for the investigation of the scaling behavior of sunspot time series. Using different methods to handle the 11-year cycle generally creates totally different results. Using MF-DFA, Movahed and co-workers employed Fourier truncation to deal with the 11-year cycle and found that the series is long-range anti-correlated with a Hurst exponent, H, of about 0.12. However, Hu and co-workers proposed an adaptive detrending method for the MF-DFA and discovered long-range correlation characterized by H≈0.74. In an attempt to get to the bottom of the problem in the present paper, empirical mode decomposition (EMD), a data-driven adaptive method, is applied to first extract the components with different dominant frequencies. MF-DFA is then employed to study the long-range correlation of the sunspot time series under the influence of these components. On removing the effects of these periods, the natural long-range correlation of the sunspot time series can be revealed. With the removal of the 11-year cycle, a crossover point located at around 60 months is discovered to be a reasonable point separating two different time scale ranges, H≈0.72 and H≈1.49. And on removing all cycles longer than 11 years, we have H≈0.69 and H≈0.28. The three cycle-removing methods—Fourier truncation, adaptive detrending and the

  13. Correlation between two-dimensional video analysis and subjective assessment in evaluating knee control among elite female team handball players

    DEFF Research Database (Denmark)

    Stensrud, Silje; Myklebust, Grethe; Kristianslund, Eirik

    2011-01-01

    . The present study investigated the correlation between a two-dimensional (2D) video analysis and subjective assessment performed by one physiotherapist in evaluating knee control. We also tested the correlation between three simple clinical tests using both methods. A cohort of 186 female elite team handball...

  14. Reduced COPD Exacerbation Risk Correlates With Improved FEV1: A Meta-Regression Analysis.

    Science.gov (United States)

    Zider, Alexander D; Wang, Xiaoyan; Buhr, Russell G; Sirichana, Worawan; Barjaktarevic, Igor Z; Cooper, Christopher B

    2017-09-01

    The mechanism by which various classes of medication reduce COPD exacerbation risk remains unknown. We hypothesized a correlation between reduced exacerbation risk and improvement in airway patency as measured according to FEV 1 . By systematic review, COPD trials were identified that reported therapeutic changes in predose FEV 1 (dFEV 1 ) and occurrence of moderate to severe exacerbations. Using meta-regression analysis, a model was generated with dFEV 1 as the moderator variable and the absolute difference in exacerbation rate (RD), ratio of exacerbation rates (RRs), or hazard ratio (HR) as dependent variables. The analysis of RD and RR included 119,227 patients, and the HR analysis included 73,475 patients. For every 100-mL change in predose FEV 1 , the HR decreased by 21% (95% CI, 17-26; P < .001; R 2  = 0.85) and the absolute exacerbation rate decreased by 0.06 per patient per year (95% CI, 0.02-0.11; P = .009; R 2  = 0.05), which corresponded to an RR of 0.86 (95% CI, 0.81-0.91; P < .001; R 2  = 0.20). The relationship with exacerbation risk remained statistically significant across multiple subgroup analyses. A significant correlation between increased FEV 1 and lower COPD exacerbation risk suggests that airway patency is an important mechanism responsible for this effect. Copyright © 2017 American College of Chest Physicians. Published by Elsevier Inc. All rights reserved.

  15. A Unified Approach to Functional Principal Component Analysis and Functional Multiple-Set Canonical Correlation.

    Science.gov (United States)

    Choi, Ji Yeh; Hwang, Heungsun; Yamamoto, Michio; Jung, Kwanghee; Woodward, Todd S

    2017-06-01

    Functional principal component analysis (FPCA) and functional multiple-set canonical correlation analysis (FMCCA) are data reduction techniques for functional data that are collected in the form of smooth curves or functions over a continuum such as time or space. In FPCA, low-dimensional components are extracted from a single functional dataset such that they explain the most variance of the dataset, whereas in FMCCA, low-dimensional components are obtained from each of multiple functional datasets in such a way that the associations among the components are maximized across the different sets. In this paper, we propose a unified approach to FPCA and FMCCA. The proposed approach subsumes both techniques as special cases. Furthermore, it permits a compromise between the techniques, such that components are obtained from each set of functional data to maximize their associations across different datasets, while accounting for the variance of the data well. We propose a single optimization criterion for the proposed approach, and develop an alternating regularized least squares algorithm to minimize the criterion in combination with basis function approximations to functions. We conduct a simulation study to investigate the performance of the proposed approach based on synthetic data. We also apply the approach for the analysis of multiple-subject functional magnetic resonance imaging data to obtain low-dimensional components of blood-oxygen level-dependent signal changes of the brain over time, which are highly correlated across the subjects as well as representative of the data. The extracted components are used to identify networks of neural activity that are commonly activated across the subjects while carrying out a working memory task.

  16. Linear analysis near a steady-state of biochemical networks: control analysis, correlation metrics and circuit theory

    Directory of Open Access Journals (Sweden)

    Qian Hong

    2008-05-01

    Full Text Available Abstract Background: Several approaches, including metabolic control analysis (MCA, flux balance analysis (FBA, correlation metric construction (CMC, and biochemical circuit theory (BCT, have been developed for the quantitative analysis of complex biochemical networks. Here, we present a comprehensive theory of linear analysis for nonequilibrium steady-state (NESS biochemical reaction networks that unites these disparate approaches in a common mathematical framework and thermodynamic basis. Results: In this theory a number of relationships between key matrices are introduced: the matrix A obtained in the standard, linear-dynamic-stability analysis of the steady-state can be decomposed as A = SRT where R and S are directly related to the elasticity-coefficient matrix for the fluxes and chemical potentials in MCA, respectively; the control-coefficients for the fluxes and chemical potentials can be written in terms of RT BS and ST BS respectively where matrix B is the inverse of A; the matrix S is precisely the stoichiometric matrix in FBA; and the matrix eAt plays a central role in CMC. Conclusion: One key finding that emerges from this analysis is that the well-known summation theorems in MCA take different forms depending on whether metabolic steady-state is maintained by flux injection or concentration clamping. We demonstrate that if rate-limiting steps exist in a biochemical pathway, they are the steps with smallest biochemical conductances and largest flux control-coefficients. We hypothesize that biochemical networks for cellular signaling have a different strategy for minimizing energy waste and being efficient than do biochemical networks for biosynthesis. We also discuss the intimate relationship between MCA and biochemical systems analysis (BSA.

  17. Mapping Comparison and Meteorological Correlation Analysis of the Air Quality Index in Mid-Eastern China

    Directory of Open Access Journals (Sweden)

    Zhichen Yu

    2017-02-01

    Full Text Available With the continuous progress of human production and life, air quality has become the focus of attention. In this paper, Beijing, Tianjin, Hebei, Shanxi, Shandong and Henan provinces were taken as the study area, where there are 58 air quality monitoring stations from which daily and monthly data are obtained. Firstly, the temporal characteristics of the air quality index (AQI are explored. Then, the spatial distribution of the AQI is mapped by the inverse distance weighted (IDW method, the ordinary kriging (OK method and the Bayesian maximum entropy (BME method. Additionally, cross-validation is utilized to evaluate the mapping results of these methods with two indexes: mean absolute error and root mean square interpolation error. Furthermore, the correlation analysis of meteorological factors, including precipitation anomaly percentage, precipitation, mean wind speed, average temperature, average water vapor pressure and average relative humidity, potentially affecting the AQI was carried out on both daily and monthly scales. In the study area and period, AQI shows a clear periodicity, although overall, it has a downward trend. The peak of AQI appeared in November, December and January. BME interpolation has a higher accuracy than OK. IDW has the maximum error. Overall, the AQI of winter (November, spring (February is much worse than summer (May and autumn (August. Additionally, the air quality has improved during the study period. The most polluted areas of air quality are concentrated in Beijing, the southern part of Tianjin, the central-southern part of Hebei, the central-northern part of Henan and the western part of Shandong. The average wind speed and average relative humidity have real correlation with AQI. The effect of meteorological factors such as wind, precipitation and humidity on AQI is putative to have temporal lag to different extents. AQI of cities with poor air quality will fluctuate greater than that of others when weather

  18. Implications of the effective one-component analysis of pair correlations in colloidal fluids with polydispersity

    Science.gov (United States)

    Pond, Mark J.; Errington, Jeffrey R.; Truskett, Thomas M.

    2011-09-01

    Partial pair-correlation functions of colloidal suspensions with continuous polydispersity can be challenging to characterize from optical microscopy or computer simulation data due to inadequate sampling. As a result, it is common to adopt an effective one-component description of the structure that ignores the differences between particle types. Unfortunately, whether this kind of simplified description preserves or averages out information important for understanding the behavior of the fluid depends on the degree of polydispersity and can be difficult to assess, especially when the corresponding multicomponent description of the pair correlations is unavailable for comparison. Here, we present a computer simulation study that examines the implications of adopting an effective one-component structural description of a polydisperse fluid. The square-well model that we investigate mimics key aspects of the experimental behavior of suspended colloids with short-range, polymer-mediated attractions. To characterize the partial pair-correlation functions and thermodynamic excess entropy of this system, we introduce a Monte Carlo sampling strategy appropriate for fluids with a large number of pseudo-components. The data from our simulations at high particle concentrations, as well as exact theoretical results for dilute systems, show how qualitatively different trends between structural order and particle attractions emerge from the multicomponent and effective one-component treatments, even with systems characterized by moderate polydispersity. We examine consequences of these differences for excess-entropy based scalings of shear viscosity, and we discuss how use of the multicomponent treatment reveals similarities between the corresponding dynamic scaling behaviors of attractive colloids and liquid water that the effective one-component analysis does not capture.

  19. Correlation analysis of measurement result between accelerator mass spectrometry and gamma counter

    International Nuclear Information System (INIS)

    Minamimoto, Ryogo; Cheng, C.; Oka, Takashi; Inoue, Tomio; Hamabe, Yoshimi; Shimoda, Marika

    2010-01-01

    The guidelines for microdosing in clinical trials were published in Japan in 2008 following the guidelines of the European Medicines Agency and the Food and Drug Administration. They recommend utilizing accelerator mass spectrometry (AMS) and positron emission tomography as candidates for monitoring drug metabolites in preclinical studies. We correlate the two methods by measuring appropriately labeled tissue samples from various mouse organs using both AMS and gamma counter. First, we measured the 14 C background levels in mouse organs using the AMS system. We then clarified the relationship between AMS and gamma counter by simultaneously administering 14 C-2-fluoro-2-deoxyglucose ( 14 C-FDG) and 18 F-2-fluoro-2-deoxyglucose ( 18 F-FDG). Tissue distribution was examined after 30 min, 1 h, 2 h and 4 h using the AMS system for 14 C-FDG and gamma counter for 18 F-FDG. Background 14 C levels were subtracted from the data obtained with radiotracer administration. The background 14 C concentration differed with tissue type measured. Background 14 C concentration in mouse liver was higher than in other organs, and was approximately 1.5-fold that in blood. The correlation coefficient (r) of the measurements between AMS ( 14 C-FDG) and gamma counter ( 18 F-FDG) was high in both normal (0.99 in blood, 0.91 in brain, 0.61 in liver and 0.78 in kidney) and tumor-bearing mice (0.95 in blood and 0.99 in tumor). The clearance profile of 18 F-FDG was nearly identical to that of 14 C-FDG measured with AMS. Accelerator mass spectrometry analysis has an excellent correlation with biodistribution measurements using gamma counter. Our results suggest that the combination of AMS and positron emission tomography (PET) can act as a complementary approach to accelerate drug development. (author)

  20. Quantitative DNA methylation analysis improves epigenotype-phenotype correlations in Beckwith-Wiedemann syndrome

    Science.gov (United States)

    Calvello, Mariarosaria; Tabano, Silvia; Colapietro, Patrizia; Maitz, Silvia; Pansa, Alessandra; Augello, Claudia; Lalatta, Faustina; Gentilin, Barbara; Spreafico, Filippo; Calzari, Luciano; Perotti, Daniela; Larizza, Lidia; Russo, Silvia; Selicorni, Angelo; Sirchia, Silvia M; Miozzo, Monica

    2013-01-01

    Beckwith-Wiedemann syndrome (BWS) is a rare disorder characterized by overgrowth and predisposition to embryonal tumors. BWS is caused by various epigenetic and/or genetic alterations that dysregulate the imprinted genes on chromosome region 11p15.5. Molecular analysis is required to reinforce the clinical diagnosis of BWS and to identify BWS patients with cancer susceptibility. This is particularly crucial prenatally because most signs of BWS cannot be recognized in utero. We established a reliable molecular assay by pyrosequencing to quantitatively evaluate the methylation profiles of ICR1 and ICR2. We explored epigenotype-phenotype correlations in 19 patients that fulfilled the clinical diagnostic criteria for BWS, 22 patients with suspected BWS, and three fetuses with omphalocele. Abnormal methylation was observed in one prenatal case and 19 postnatal cases, including seven suspected BWS. Seven cases showed ICR1 hypermethylation, five cases showed ICR2 hypomethylation, and eight cases showed abnormal methylation of ICR1 and ICR2 indicating paternal uniparental disomy (UPD). More cases of ICR1 alterations and UPD were found than expected. This is likely due to the sensitivity of this approach, which can detect slight deviations in methylation from normal levels. There was a significant correlation (p < 0.001) between the percentage of ICR1 methylation and BWS features: severe hypermethylation (range: 75–86%) was associated with macroglossia, macrosomia, and visceromegaly, whereas mild hypermethylation (range: 55–59%) was associated with umbilical hernia and diastasis recti. Evaluation of ICR1 and ICR2 methylation by pyrosequencing in BWS can improve epigenotype-phenotype correlations, detection of methylation alterations in suspected cases, and identification of UPD. PMID:23917791

  1. Quasar 2175 Å dust absorbers - II. Correlation analysis and relationship with other absorption line systems

    Science.gov (United States)

    Ma, Jingzhe; Ge, Jian; Prochaska, J. Xavier; Zhang, Shaohua; Ji, Tuo; Zhao, Yinan; Zhou, Hongyan; Lu, Honglin; Schneider, Donald P.

    2018-03-01

    We present the cold neutral content (H I and C I gas) of 13 quasar 2175 Å dust absorbers (2DAs) at z = 1.6-2.5 to investigate the correlation between the presence of the UV extinction bump with other physical characteristics. These 2DAs were initially selected from the Sloan Digital Sky Surveys I-III and followed up with the Keck-II telescope and the Multiple Mirror Telescope as detailed in our Paper I. We perform a correlation analysis between metallicity, redshift, depletion level, velocity width, and explore relationships between 2DAs and other absorption line systems. The 2DAs on average have higher metallicity, higher depletion levels, and larger velocity widths than Damped Lyman α absorbers (DLAs) or subDLAs. The correlation between [Zn/H] and [Fe/Zn] or [Zn/H] and logΔV90 can be used as alternative stellar mass estimators based on the well-established mass-metallicity relation. The estimated stellar masses of the 2DAs in this sample are in the range of ˜109 to ˜2 × 1011 M⊙ with a median value of ˜2 × 1010 M⊙. The relationship with other quasar absorption line systems can be described as (1) 2DAs are a subset of Mg II and Fe II absorbers, (2) 2DAs are preferentially metal-strong DLAs/subDLAs, (3) More importantly, all of the 2DAs show C I detections with logN(C I) > 14.0 cm-2, and (4) 2DAs can be used as molecular gas tracers. Their host galaxies are likely to be chemically enriched, evolved, massive (more massive than typical DLA/subDLA galaxies), and presumably star-forming galaxies.

  2. Post analysis simulated correlation of the El-Ganzouri airway difficulty score with difficult airway.

    Science.gov (United States)

    Corso, Ruggero M; Cattano, Davide; Buccioli, Matteo; Carretta, Elisa; Maitan, Stefano

    2016-01-01

    Difficult airway (DA) occurs frequently (5-15%) in clinical practice. The El-Ganzouri Risk Index (EGRI) has a high sensitivity for predicting a difficult intubation (DI). However difficult mask ventilation (DMV) was never included in the EGRI. Since DMV was not included in the EGRI assessment, and obstructive sleep apnea (OSA) is also correlated with DMV, a study correlating the prediction of DA and OSA (identified by STOP-Bang questionnaire, SB) seemed important. We accessed a database previously collected for a post analysis simulation of the airway difficulty predictivity of the EGRI, associated with normal and difficult airway, particularly DMV. As secondary aim, we measured the correlation between the SB prediction system and DA, compared to the EGRI. A total of 2747 patients were included in the study. The proportion of patients with DI was 14.7% (95% CI 13.4-16) and the proportion of patients with DMV was 3.42% (95% CI 2.7-4.1). The incidence of DMV combined with DI was (2.3%). The optimal cutoff value of EGRI was 3. EGRI registered also an higher ability to predict DMV (AUC=0.76 (95% CI 0.71-0.81)). Adding the SB variables in the logistic model, the AUC increases with the inclusion of "observed apnea" variable (0.83 vs. 0.81, p=0.03). The area under the ROC curve for the patients with DI and DMV was 0.77 (95% CI 0.72-0.83). This study confirms that the incidence of DA is not negligible and suggests the use of the EGRI as simple bedside predictive score to improve patient safety. Copyright © 2014 Sociedade Brasileira de Anestesiologia. Published by Elsevier Editora Ltda. All rights reserved.

  3. [Post analysis simulated correlation of the El-Ganzouri airway difficulty score with difficult airway].

    Science.gov (United States)

    Corso, Ruggero M; Cattano, Davide; Buccioli, Matteo; Carretta, Elisa; Maitan, Stefano

    2016-01-01

    Difficult airway (DA) occurs frequently (5-15%) in clinical practice. The El-Ganzouri Risk Index (EGRI) has a high sensitivity for predicting a difficult intubation (DI). However difficult mask ventilation (DMV) was never included in the EGRI. Since DMV was not included in the EGRI assessment, and obstructive sleep apnea (OSA) is also correlated with DMV, a study correlating the prediction of DA and OSA (identified by STOP-Bang questionnaire, SB) seemed important. We accessed a database previously collected for a post analysis simulation of the airway difficulty predictivity of the EGRI, associated with normal and difficult airway, particularly DMV. As secondary aim, we measured the correlation between the SB prediction system and DA, compared to the EGRI. A total of 2747 patients were included in the study. The proportion of patients with DI was 14.7% (95% CI 13.4-16) and the proportion of patients with DMV was 3.42% (95% CI 2.7-4.1). The incidence of DMV combined with DI was (2.3%). The optimal cutoff value of EGRI was 3. EGRI registered also an higher ability to predict DMV (AUC=0.76 (95% CI 0.71-0.81)). Adding the SB variables in the logistic model, the AUC increases with the inclusion of "observed apnea" variable (0.83 vs. 0.81, p=0.03). The area under the ROC curve for the patients with DI and DMV was 0.77 (95% CI 0.72-0.83). This study confirms that the incidence of DA is not negligible and suggests the use of the EGRI as simple bedside predictive score to improve patient safety. Copyright © 2014 Sociedade Brasileira de Anestesiologia. Publicado por Elsevier Editora Ltda. All rights reserved.

  4. Performance analysis of MIMO wireless optical communication system with Q-ary PPM over correlated log-normal fading channel

    Science.gov (United States)

    Wang, Huiqin; Wang, Xue; Lynette, Kibe; Cao, Minghua

    2018-06-01

    The performance of multiple-input multiple-output wireless optical communication systems that adopt Q-ary pulse position modulation over spatial correlated log-normal fading channel is analyzed in terms of its un-coded bit error rate and ergodic channel capacity. The analysis is based on the Wilkinson's method which approximates the distribution of a sum of correlated log-normal random variables to a log-normal random variable. The analytical and simulation results corroborate the increment of correlation coefficients among sub-channels lead to system performance degradation. Moreover, the receiver diversity has better performance in resistance of spatial correlation caused channel fading.

  5. Word-Length Correlations and Memory in Large Texts: A Visibility Network Analysis

    Directory of Open Access Journals (Sweden)

    Lev Guzmán-Vargas

    2015-11-01

    Full Text Available We study the correlation properties of word lengths in large texts from 30 ebooks in the English language from the Gutenberg Project (www.gutenberg.org using the natural visibility graph method (NVG. NVG converts a time series into a graph and then analyzes its graph properties. First, the original sequence of words is transformed into a sequence of values containing the length of each word, and then, it is integrated. Next, we apply the NVG to the integrated word-length series and construct the network. We show that the degree distribution of that network follows a power law, P ( k ∼ k - γ , with two regimes, which are characterized by the exponents γ s ≈ 1 . 7 (at short degree scales and γ l ≈ 1 . 3 (at large degree scales. This suggests that word lengths are much more strongly correlated at large distances between words than at short distances between words. That finding is also supported by the detrended fluctuation analysis (DFA and recurrence time distribution. These results provide new information about the universal characteristics of the structure of written texts beyond that given by word frequencies.

  6. Analysis of magnetic correlations in layered or multiferroic transition element oxides using neutron diffraction

    International Nuclear Information System (INIS)

    Finger, Thomas

    2013-01-01

    Due to a great variety of physical phenomena the material class of transition metal oxides offers a large field of work for researchers, the more so as many underlying mechanisms are not understood yet. Of these materials a set of systems closely related to the manganates is investigated in this thesis via neutron scattering, emphasizing the analysis of magnetic correlations. It is shown, that for doping concentrations 0 ≤ x ≤ 0.5 the Co 2+ -ions in the layered cobaltates always exhibit a high-spin state with S = (3)/(2), whereas existing Co 3+ -ions adopt a low-spin state with S = 0 and stay non-magnetic. Furthermore, the magnetic correlations of three chiral multiferroics are investigated: Firstly, in MnWO 4 a memory effect is described; the crystal remembers its preceding chiral state even in the paramagnetic phase. In TbMnO 3 chiral fluctuations slightly above the multiferroic transition are investigated; it is possible to switch them by an applied external E-field. Finally, in DyMnO 3 the magnetic excitations are examined for the first time; they are comparable to those in TbMnO 3 .

  7. [A multilevel model analysis of correlation between population characteristics and work ability of employees].

    Science.gov (United States)

    Zhang, Lei; Huang, Chunping; Lan, Yajia; Wang, Mianzhen

    2015-12-01

    To analyze the correlation between population characteristics and work ability of employees with a multilevel model, to investigate the important influencing factors for work ability, and to provide a basis for improvement in work ability. Work ability index (WAI)was applied to measure the work ability of 1686 subjects from different companies (n=6). MLwi N2.0 software was applied for two-level variance component model fitting. The WAI of employees showed differences between various companies (χ2=3.378 6, P=0.0660); working years was negatively correlated with WAI (χ2=38.229 2, P=0.0001), and the WAI of the employees with 20 or more working years was 1.63 lower than that of the employees with less than 20 working years; the work ability of manual workers was lower than that of mental-manual workers (χ2=8.2726, P=0.0040), and the work ability showed no significant difference between mental workers and mental-manual workers (χ2=2.086 0, P=0.148 7). From the perspective of probability, the multilevel model analysis reveals the differences in work ability of employees between different companies, and suggests that company, work type, and working years are the important influencing factors for work ability of employees. These factors should be improved and adjusted to protect or enhance the work ability of employees.

  8. Investment Decision Support for Engineering Projects Based on Risk Correlation Analysis

    Directory of Open Access Journals (Sweden)

    Yan Liu

    2012-01-01

    Full Text Available Investment decisions are usually made on the basis of the subjective judgments of experts subjected to the information gap during the preliminary stages of a project. As a consequence, a series of errors in risk prediction and/or decision-making will be generated leading to out of control investment and project failure. In this paper, the variable fuzzy set theory and intelligent algorithms integrated with case-based reasoning are presented. The proposed algorithm manages the numerous fuzzy concepts and variable factors of a project and also sets up the decision-making process in accordance with past cases and experiences. Furthermore, it decreases the calculation difficulty and reduces the decision-making reaction time. Three types of risk correlations combined with different characteristics of engineering projects are summarized, and each of these correlations is expounded at the project investment decision-making stage. Quantitative and qualitative change theories of variable fuzzy sets are also addressed for investment risk warning. The approach presented in this paper enables the risk analysis in a simple and intuitive manner and realizes the integration of objective and subjective risk assessments within the decision-makers' risk expectation.

  9. Canonical Correlation Analysis Between Supply Chain Quality Management And Competitive Advantages

    Directory of Open Access Journals (Sweden)

    Chaghooshi Ahmad Jafarnejad

    2015-06-01

    Full Text Available Competitive environment of today’s organizations, more than ever, is extensive, and the major concern for managers is to preserve and promote the sustainable competitive advantage. Companies have an obligation to improve their product quality and have extensive and close cooperation with other companies involved in the supply chain of products. Supply chain quality management (SCQM is a systematic approach to improve the performance that integrates supply chain partners and uses the opportunity in the best way, establish linkages between upstream and downstream flows, and investigate on creating value and satisfaction of intermediaries and final customers. Furthermore, achieving competitive advantages enables an organization to create a remarkable position in market and differentiate itself from competitors. This paper aims to understand the relationships between SCQM and competitive advantage. Sixty-eight experts of 25 companies in Sahami Alyaf (SA supply chain has been participated in this research. The research method used for this article is descriptive correlation. To assess the relationships between the criteria, canonical correlation analysis was used. The result shows that the SCQM and competitive advantages have a meaningful relationship. It also shows that most important variable in the linear combination of SCQM and competitive advantages are “customer focus and quality,” respectively.

  10. Structure and evolution of a European Parliament via a network and correlation analysis

    Science.gov (United States)

    Puccio, Elena; Pajala, Antti; Piilo, Jyrki; Tumminello, Michele

    2016-11-01

    We present a study of the network of relationships among elected members of the Finnish parliament, based on a quantitative analysis of initiative co-signatures, and its evolution over 16 years. To understand the structure of the parliament, we constructed a statistically validated network of members, based on the similarity between the patterns of initiatives they signed. We looked for communities within the network and characterized them in terms of members' attributes, such as electoral district and party. To gain insight on the nested structure of communities, we constructed a hierarchical tree of members from the correlation matrix. Afterwards, we studied parliament dynamics yearly, with a focus on correlations within and between parties, by also distinguishing between government and opposition. Finally, we investigated the role played by specific individuals, at a local level. In particular, whether they act as proponents who gather consensus, or as signers. Our results provide a quantitative background to current theories in political science. From a methodological point of view, our network approach has proven able to highlight both local and global features of a complex social system.

  11. Fuselage Versus Subcomponent Panel Response Correlation Based on ABAQUS Explicit Progressive Damage Analysis Tools

    Science.gov (United States)

    Gould, Kevin E.; Satyanarayana, Arunkumar; Bogert, Philip B.

    2016-01-01

    Analysis performed in this study substantiates the need for high fidelity vehicle level progressive damage analyses (PDA) structural models for use in the verification and validation of proposed sub-scale structural models and to support required full-scale vehicle level testing. PDA results are presented that capture and correlate the responses of sub-scale 3-stringer and 7-stringer panel models and an idealized 8-ft diameter fuselage model, which provides a vehicle level environment for the 7-stringer sub-scale panel model. Two unique skin-stringer attachment assumptions are considered and correlated in the models analyzed: the TIE constraint interface versus the cohesive element (COH3D8) interface. Evaluating different interfaces allows for assessing a range of predicted damage modes, including delamination and crack propagation responses. Damage models considered in this study are the ABAQUS built-in Hashin procedure and the COmplete STress Reduction (COSTR) damage procedure implemented through a VUMAT user subroutine using the ABAQUS/Explicit code.

  12. Correlations among behavior, performance and environment in broiler breeders using multivariate analysis

    Directory of Open Access Journals (Sweden)

    DF Pereira

    2007-12-01

    Full Text Available Animal welfare issues have received much attention not only to supply farmed animal requirements, but also to ethical and cultural public concerns. Daily collected information, as well as the systematic follow-up of production stages, produces important statistical data for production assessment and control, as well as for improvement possibilities. In this scenario, this research study analyzed behavioral, production, and environmental data using Main Component Multivariable Analysis, which correlated observed behaviors, recorded using video cameras and electronic identification, with performance parameters of female broiler breeders. The aim was to start building a system to support decision-making in broiler breeder housing, based on bird behavioral parameters. Birds were housed in an environmental chamber, with three pens with different controlled environments. Bird sensitivity to environmental conditions were indicated by their behaviors, stressing the importance of behavioral observations for modern poultry management. A strong association between performance parameters and the behavior "at the nest", suggesting that this behavior may be used to predict productivity. The behaviors of "ruffling feathers", "opening wings", "preening", and "at the drinker" were negatively correlated with environmental temperature, suggesting that the increase of in the frequency of these behaviors indicate improvement of thermal welfare.

  13. Pre-analysis techniques applied to area-based correlation aiming Digital Terrain Model generation

    Directory of Open Access Journals (Sweden)

    Maurício Galo

    2005-12-01

    Full Text Available Area-based matching is an useful procedure in some photogrammetric processes and its results are of crucial importance in applications such as relative orientation, phototriangulation and Digital Terrain Model generation. The successful determination of correspondence depends on radiometric and geometric factors. Considering these aspects, the use of procedures that previously estimate the quality of the parameters to be computed is a relevant issue. This paper describes these procedures and it is shown that the quality prediction can be computed before performing matching by correlation, trough the analysis of the reference window. This procedure can be incorporated in the correspondence process for Digital Terrain Model generation and Phototriangulation. The proposed approach comprises the estimation of the variance matrix of the translations from the gray levels in the reference window and the reduction of the search space using the knowledge of the epipolar geometry. As a consequence, the correlation process becomes more reliable, avoiding the application of matching procedures in doubtful areas. Some experiments with simulated and real data are presented, evidencing the efficiency of the studied strategy.

  14. Sparse and smooth canonical correlation analysis through rank-1 matrix approximation

    Science.gov (United States)

    Aïssa-El-Bey, Abdeldjalil; Seghouane, Abd-Krim

    2017-12-01

    Canonical correlation analysis (CCA) is a well-known technique used to characterize the relationship between two sets of multidimensional variables by finding linear combinations of variables with maximal correlation. Sparse CCA and smooth or regularized CCA are two widely used variants of CCA because of the improved interpretability of the former and the better performance of the later. So far, the cross-matrix product of the two sets of multidimensional variables has been widely used for the derivation of these variants. In this paper, two new algorithms for sparse CCA and smooth CCA are proposed. These algorithms differ from the existing ones in their derivation which is based on penalized rank-1 matrix approximation and the orthogonal projectors onto the space spanned by the two sets of multidimensional variables instead of the simple cross-matrix product. The performance and effectiveness of the proposed algorithms are tested on simulated experiments. On these results, it can be observed that they outperform the state of the art sparse CCA algorithms.

  15. Implementation and Initial Testing of Advanced Processing and Analysis Algorithms for Correlated Neutron Counting

    Energy Technology Data Exchange (ETDEWEB)

    Santi, Peter Angelo [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Cutler, Theresa Elizabeth [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Favalli, Andrea [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Koehler, Katrina Elizabeth [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Henzl, Vladimir [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Henzlova, Daniela [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Parker, Robert Francis [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Croft, Stephen [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

    2015-12-01

    In order to improve the accuracy and capabilities of neutron multiplicity counting, additional quantifiable information is needed in order to address the assumptions that are present in the point model. Extracting and utilizing higher order moments (Quads and Pents) from the neutron pulse train represents the most direct way of extracting additional information from the measurement data to allow for an improved determination of the physical properties of the item of interest. The extraction of higher order moments from a neutron pulse train required the development of advanced dead time correction algorithms which could correct for dead time effects in all of the measurement moments in a self-consistent manner. In addition, advanced analysis algorithms have been developed to address specific assumptions that are made within the current analysis model, namely that all neutrons are created at a single point within the item of interest, and that all neutrons that are produced within an item are created with the same energy distribution. This report will discuss the current status of implementation and initial testing of the advanced dead time correction and analysis algorithms that have been developed in an attempt to utilize higher order moments to improve the capabilities of correlated neutron measurement techniques.

  16. Retrospective North American CFL Experience Curve Analysis and Correlation to Deployment Programs

    Energy Technology Data Exchange (ETDEWEB)

    Smith, Sarah J. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Wei, Max [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Sohn, Michael D. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

    2015-07-01

    Retrospective experience curves are a useful tool for understanding historic technology development, and can contribute to investment program analysis and future cost estimation efforts. This work documents our development of an analysis approach for deriving retrospective experience curves with a variable learning rate, and its application to develop an experience curve for compact fluorescent lamps for the global and North American markets over the years 1990-2007. Uncertainties and assumptions involved in interpreting data for our experience curve development are discussed, including the processing and transformation of empirical data, the selection of system boundaries, and the identification of historical changes in the learning rate over the course of 15 years. In the results that follow, we find that that the learning rate has changed at least once from 1990-2007. We also explore if, and to what degree, public deployment programs may have contributed to an increased technology learning rate in North America. We observe correlations between the changes in the learning rate and the initiation of new policies, abrupt technological advances, including improvements to ballast technology, and economic and political events such as trade tariffs and electricity prices. Finally, we discuss how the findings of this work (1) support the use of segmented experience curves for retrospective and prospective analysis and (2) may imply that investments in technological research and development have contributed to a change in market adoption and penetration.

  17. TIME SERIES ANALYSIS ON STOCK MARKET FOR TEXT MINING CORRELATION OF ECONOMY NEWS

    Directory of Open Access Journals (Sweden)

    Sadi Evren SEKER

    2014-01-01

    Full Text Available This paper proposes an information retrieval methodfor the economy news. Theeffect of economy news, are researched in the wordlevel and stock market valuesare considered as the ground proof.The correlation between stock market prices and economy news is an already ad-dressed problem for most of the countries. The mostwell-known approach is ap-plying the text mining approaches to the news and some time series analysis tech-niques over stock market closing values in order toapply classification or cluster-ing algorithms over the features extracted. This study goes further and tries to askthe question what are the available time series analysis techniques for the stockmarket closing values and which one is the most suitable? In this study, the newsand their dates are collected into a database and text mining is applied over thenews, the text mining part has been kept simple with only term frequency – in-verse document frequency method. For the time series analysis part, we havestudied 10 different methods such as random walk, moving average, acceleration,Bollinger band, price rate of change, periodic average, difference, momentum orrelative strength index and their variation. In this study we have also explainedthese techniques in a comparative way and we have applied the methods overTurkish Stock Market closing values for more than a2 year period. On the otherhand, we have applied the term frequency – inversedocument frequency methodon the economy news of one of the high-circulatingnewspapers in Turkey.

  18. Algorithm of reducing the false positives in IDS based on correlation Analysis

    Science.gov (United States)

    Liu, Jianyi; Li, Sida; Zhang, Ru

    2018-03-01

    This paper proposes an algorithm of reducing the false positives in IDS based on correlation Analysis. Firstly, the algorithm analyzes the distinguishing characteristics of false positives and real alarms, and preliminary screen the false positives; then use the method of attribute similarity clustering to the alarms and further reduces the amount of alarms; finally, according to the characteristics of multi-step attack, associated it by the causal relationship. The paper also proposed a reverse causation algorithm based on the attack association method proposed by the predecessors, turning alarm information into a complete attack path. Experiments show that the algorithm simplifies the number of alarms, improve the efficiency of alarm processing, and contribute to attack purposes identification and alarm accuracy improvement.

  19. Data-driven fault detection for industrial processes canonical correlation analysis and projection based methods

    CERN Document Server

    Chen, Zhiwen

    2017-01-01

    Zhiwen Chen aims to develop advanced fault detection (FD) methods for the monitoring of industrial processes. With the ever increasing demands on reliability and safety in industrial processes, fault detection has become an important issue. Although the model-based fault detection theory has been well studied in the past decades, its applications are limited to large-scale industrial processes because it is difficult to build accurate models. Furthermore, motivated by the limitations of existing data-driven FD methods, novel canonical correlation analysis (CCA) and projection-based methods are proposed from the perspectives of process input and output data, less engineering effort and wide application scope. For performance evaluation of FD methods, a new index is also developed. Contents A New Index for Performance Evaluation of FD Methods CCA-based FD Method for the Monitoring of Stationary Processes Projection-based FD Method for the Monitoring of Dynamic Processes Benchmark Study and Real-Time Implementat...

  20. Characterization of the malignity of tumors in the central nervous system utilizing the correlation dimension analysis

    International Nuclear Information System (INIS)

    Pereira, D.; Zambrano, C.; Martin L, M.

    1998-01-01

    In the present work it is proposed a method for the characterization of the irregularities present in the edges of malignant leisure of central nervous system over axial images generated through Nuclear magnetic Resonance by images. Through the use of techniques of digital images processing was possible to locate, extract and generate temporal series. These temporal series were utilized using the correlation dimension concept for producing a parameter which takes different values depending of the leisure type. It is demonstrated that this type of analysis suffers in a very acceptable form independently of the errors which can be generate by the fact that in the practice of temporal series obtained they are composed by a reduced number of points. (Author)

  1. Quantitative analysis of volatile organic compounds using ion mobility spectra and cascade correlation neural networks

    Science.gov (United States)

    Harrington, Peter DEB.; Zheng, Peng

    1995-01-01

    Ion Mobility Spectrometry (IMS) is a powerful technique for trace organic analysis in the gas phase. Quantitative measurements are difficult, because IMS has a limited linear range. Factors that may affect the instrument response are pressure, temperature, and humidity. Nonlinear calibration methods, such as neural networks, may be ideally suited for IMS. Neural networks have the capability of modeling complex systems. Many neural networks suffer from long training times and overfitting. Cascade correlation neural networks train at very fast rates. They also build their own topology, that is a number of layers and number of units in each layer. By controlling the decay parameter in training neural networks, reproducible and general models may be obtained.

  2. Void analysis of target residues at SPS energy -evidence of correlation with fractal behaviour

    International Nuclear Information System (INIS)

    Ghosh, Dipak; Deb, Argha; Das, Rupa . E-mail : dipakghosh_in@yahoo.com

    2007-01-01

    This paper presents an analysis of the target residues in 32 S -AgBr and 16 0 -AgBr interactions at 200 AGeV and 60AGeV respectively in terms of fractal moment by Takagi method and void probability scaling. The study reveals an interesting feature of the production process. In 16 O- AgBr interactions multifractal behaviour is present in both hemispheres and void probability does not show a scaling behaviour, but at high energy the situation changes. In 32 S -AgBr interactions for both hemisphere monofractal behaviour is indicated by that data and void probability also shows good scaling behaviour. This suggests that a possible correlation of void probability with fractal behaviour of target residues. (author)

  3. Adaptive Kernel Canonical Correlation Analysis Algorithms for Nonparametric Identification of Wiener and Hammerstein Systems

    Directory of Open Access Journals (Sweden)

    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.

  4. An ecological analysis of environmental correlates of active commuting in urban U.S.

    Science.gov (United States)

    Fan, Jessie X; Wen, Ming; Kowaleski-Jones, Lori

    2014-11-01

    We conduct a cross-sectional ecological analysis to examine environmental correlates of active commuting in 39,660 urban tracts using data from the 2010 Census, 2007-2011 American Community Survey, and other sources. The five-year average (2007-2011) prevalence is 3.05% for walking, 0.63% for biking, and 7.28% for public transportation to work, with higher prevalence for all modes in lower-income tracts. Environmental factors account for more variances in public transportation to work but economic and demographic factors account for more variances in walking and biking to work. Population density, median housing age, street connectivity, tree canopy, distance to parks, air quality, and county sprawl index are associated with active commuting, but the association can vary in size and direction for different transportation mode and for higher-income and lower-income tracts. Copyright © 2014 Elsevier Ltd. All rights reserved.

  5. The integrated model of sport confidence: a canonical correlation and mediational analysis.

    Science.gov (United States)

    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.

  6. Empirical Analysis Concerning the Correlation Fiscality Rate – Tax Incomes in Romania

    Directory of Open Access Journals (Sweden)

    Raluca Drãcea

    2009-08-01

    Full Text Available In the specialized literature it is reviewed the taxation from all points of view and the question raised by the last decade analysts is: what is the optimum level of taxation? The difficulty in answering to this question stands in the opposite interests: State wants a high level of taxation due to the increasing trend of public expenses while the tax payers wants a low level in order to benefit of greater financial funds.Starting from Leffer theory, the objective of this paper is the empirical analysis of the correlation between fiscality rate and the tax incomes in Romania, using Matlab programand SPSS software. The paper is structured in three parts: first part it is review the specialized literature, in the second part is described the research methodology while the third part compound results and discussions. The paper is finished by conclusions.

  7. Sparse Canonical Correlation Analysis via Truncated ℓ1-norm with Application to Brain Imaging Genetics.

    Science.gov (United States)

    Du, Lei; Zhang, Tuo; Liu, Kefei; Yao, Xiaohui; Yan, Jingwen; Risacher, Shannon L; Guo, Lei; Saykin, Andrew J; Shen, Li

    2016-01-01

    Discovering bi-multivariate associations between genetic markers and neuroimaging quantitative traits is a major task in brain imaging genetics. Sparse Canonical Correlation Analysis (SCCA) is a popular technique in this area for its powerful capability in identifying bi-multivariate relationships coupled with feature selection. The existing SCCA methods impose either the ℓ 1 -norm or its variants. The ℓ 0 -norm is more desirable, which however remains unexplored since the ℓ 0 -norm minimization is NP-hard. In this paper, we impose the truncated ℓ 1 -norm to improve the performance of the ℓ 1 -norm based SCCA methods. Besides, we propose two efficient optimization algorithms and prove their convergence. The experimental results, compared with two benchmark methods, show that our method identifies better and meaningful canonical loading patterns in both simulated and real imaging genetic analyse.

  8. Correlation analysis of the Korean stock market: Revisited to consider the influence of foreign exchange rate

    Science.gov (United States)

    Jo, Sang Kyun; Kim, Min Jae; Lim, Kyuseong; Kim, Soo Yong

    2018-02-01

    We investigated the effect of foreign exchange rate in a correlation analysis of the Korean stock market using both random matrix theory and minimum spanning tree. We collected data sets which were divided into two types of stock price, the original stock price in Korean Won and the price converted into US dollars at contemporary foreign exchange rates. Comparing the random matrix theory based on the two different prices, a few particular sectors exhibited substantial differences while other sectors changed little. The particular sectors were closely related to economic circumstances and the influence of foreign financial markets during that period. The method introduced in this paper offers a way to pinpoint the effect of exchange rate on an emerging stock market.

  9. Analysis of the width correlation in 54Fe(nγ)55Fe reaction

    International Nuclear Information System (INIS)

    Knat'ko, V.A.; Shimanovich, E.A.

    1982-01-01

    To find out structural effects manifesting themselves in the form of correlation between widths of different channels of γ decay of levels and violation of Porter-Thomas distribution, calculated are partial widths of levels for 20 high-energy γ transitions in the 54 Fe(nγ) 55 Fe reaction. Calculations are carried out for widths in relation to γ transitions on 8 low p levels of 55 Fe, for 100 sets of partial γ widths (20 widths in a set). Results of analysis of theoretical values of partial γ widths of s resonances are presented in the form of the table. Results, obtained, show that consideration of contributions into γ decay of one-particle-vibrational configurations improve the accordance with experimental data, in comparison with calculations according to the model of valent capture. It is concluded that properties of γ widths of 55 Fe resonances, calculated in studied model, agree satisfactorily with properties of experimental γ widths [ru

  10. Noise analysis of the measurement of group delay in Fourier white-light interferometric cross correlation

    International Nuclear Information System (INIS)

    Laude, Vincent

    2002-01-01

    The problem of noise analysis in measuring the group delay introduced by a dispersive optical element by use of white-light interferometric cross correlation is investigated. Two noise types, detection noise and position noise, are specifically analyzed. Detection noise is shown to be highly sensitive to the spectral content of the white-light source at the frequency considered and to the temporal acquisition window. Position noise, which arises from the finite accuracy of the measurement of the scanning mirror's position, can severely damage the estimation of the group delay. Such is shown to be the case for fast Fourier transform-based estimation algorithms. A new algorithm that is insensitive to scanning delay errors is proposed, and subfemtosecond accuracy is obtained without any postprocessing

  11. Correlation Relationship of Performance Shaping Factors (PSFs) for Human Reliability Analysis

    Energy Technology Data Exchange (ETDEWEB)

    Bheka, M. Khumalo; Kim, Jonghyun [KEPCO International Nuclear Graduate School, Ulsan (Korea, Republic of)

    2014-10-15

    between PSFs using correlation analysis and identify patterns in the PSFs using Principal Factor Analysis (PFA). The study is specifically based on Operational Performance Information Systems (OPIS) database. This study was conducted to determine causal relationships between PSFs and also find sets of PSFs (error forcing context) which contribute more to human error probabilities. These goals were achieved using correlation and principal factor analysis.

  12. Prevalence and correlates of hypertension in Maharashtra, India: A multilevel analysis.

    Directory of Open Access Journals (Sweden)

    Mahadev D Bhise

    Full Text Available In the last few decades, the prevalence of hypertension has been drastically increased in India. The present study estimates the current prevalence of hypertension and its correlates in the state of Maharashtra. The variation in the prevalence of hypertension associated with individual-level characteristics is explained at the community and district level.Data is used from the recent round of District Level Household & Facility Survey (DLHS-4, 2012-13. The DLHS-4 has used the nationally representative sample, collected through multistage stratified sampling procedure. A similar sampling frame, used in NSSO-2007-08, has been followed. The chi-square test is used to show the significance level of the association between the estimated prevalence of hypertension and its correlates. Multilevel regression analysis is carried out to investigate the effects of individual and community level factors on the prevalence of hypertension.The overall prevalence of hypertension is 25% in Maharashtra, and a huge variation in the prevalence of hypertension is found across the districts. Dhule, Gadchiroli (with a low HDI rank, Mumbai and Satara (with higher HDI rank are the districts with the higher (above 30% prevalence of high blood pressure. The prevalence also significantly varies according to different correlates. The prevalence of high blood pressure is higher among elderly population (40%, among males (28%, in the urban areas (27% and in the richest wealth quintile (28%. The prevalence is also higher among cigarette smokers (31%, alcohol consumers (30% and people with obesity (38% as compared to their counterparts. The results of the multilevel analysis show that the older and obese persons are at four-time higher risk of hypertension. Again, age, sex, marital status, place of residence, wealth status, unhealthy habits (i.e. smoking and alcohol consumption and BMI are significantly associated with hypertension. The results of VPC statistics show that 14% of

  13. Whole-tumour diffusion kurtosis MR imaging histogram analysis of rectal adenocarcinoma: Correlation with clinical pathologic prognostic factors.

    Science.gov (United States)

    Cui, Yanfen; Yang, Xiaotang; Du, Xiaosong; Zhuo, Zhizheng; Xin, Lei; Cheng, Xintao

    2018-04-01

    To investigate potential relationships between diffusion kurtosis imaging (DKI)-derived parameters using whole-tumour volume histogram analysis and clinicopathological prognostic factors in patients with rectal adenocarcinoma. 79 consecutive patients who underwent MRI examination with rectal adenocarcinoma were retrospectively evaluated. Parameters D, K and conventional ADC were measured using whole-tumour volume histogram analysis. Student's t-test or Mann-Whitney U-test, receiver operating characteristic curves and Spearman's correlation were used for statistical analysis. Almost all the percentile metrics of K were correlated positively with nodal involvement, higher histological grades, the presence of lymphangiovascular invasion (LVI) and circumferential margin (CRM) (phistogram analysis, especially K parameters, were associated with important prognostic factors of rectal cancer. • K correlated positively with some important prognostic factors of rectal cancer. • K mean showed higher AUC and specificity for differentiation of nodal involvement. • DKI metrics with whole-tumour volume histogram analysis depicted tumour heterogeneity.

  14. The correlation of social support with mental health: A meta-analysis.

    Science.gov (United States)

    Harandi, Tayebeh Fasihi; Taghinasab, Maryam Mohammad; Nayeri, Tayebeh Dehghan

    2017-09-01

    Social support is an important factor that can affect mental health. In recent decades, many studies have been done on the impact of social support on mental health. The purpose of the present study is to investigate the effect size of the relationship between social support and mental health in studies in Iran. This meta-analysis was carried out in studies that were performed from 1996 through 2015. Databases included SID and Magiran, the comprehensive portal of human sciences, Noor specialized magazine databases, IRANDOC, Proquest, PubMed, Scopus, ERIC, Iranmedex and Google Scholar. The keywords used to search these websites included "mental health or general health," and "Iran" and "social support." In total, 64 studies had inclusion criteria meta-analysis. In order to collect data used from a meta-analysis worksheet that was made by the researcher and for data analysis software, CMA-2 was used. The mean of effect size of the 64 studies in the fixed-effect model and random-effect model was obtained respectively as 0.356 and 0.330, which indicated the moderate effect size of social support on mental health. The studies did not have publication bias, and enjoyed a heterogeneous effect size. The target population and social support questionnaire were moderator variables, but sex, sampling method, and mental health questionnaire were not moderator variables. Regarding relatively high effect size of the correlation between social support and mental health, it is necessary to predispose higher social support, especially for women, the elderly, patients, workers, and students.

  15. The correlation of social support with mental health: A meta-analysis

    Science.gov (United States)

    Harandi, Tayebeh Fasihi; Taghinasab, Maryam Mohammad; Nayeri, Tayebeh Dehghan

    2017-01-01

    Background and aim Social support is an important factor that can affect mental health. In recent decades, many studies have been done on the impact of social support on mental health. The purpose of the present study is to investigate the effect size of the relationship between social support and mental health in studies in Iran. Methods This meta-analysis was carried out in studies that were performed from 1996 through 2015. Databases included SID and Magiran, the comprehensive portal of human sciences, Noor specialized magazine databases, IRANDOC, Proquest, PubMed, Scopus, ERIC, Iranmedex and Google Scholar. The keywords used to search these websites included “mental health or general health,” and “Iran” and “social support.” In total, 64 studies had inclusion criteria meta-analysis. In order to collect data used from a meta-analysis worksheet that was made by the researcher and for data analysis software, CMA-2 was used. Results The mean of effect size of the 64 studies in the fixed-effect model and random-effect model was obtained respectively as 0.356 and 0.330, which indicated the moderate effect size of social support on mental health. The studies did not have publication bias, and enjoyed a heterogeneous effect size. The target population and social support questionnaire were moderator variables, but sex, sampling method, and mental health questionnaire were not moderator variables. Conclusion Regarding relatively high effect size of the correlation between social support and mental health, it is necessary to predispose higher social support, especially for women, the elderly, patients, workers, and students. PMID:29038699

  16. Analysis of Mel-18 expression in prostate cancer tissues and correlation with clinicopathologic features.

    Science.gov (United States)

    Wang, Wei; Lin, Tianxin; Huang, Jian; Hu, Weilie; Xu, Kewei; Liu, Jun

    2011-01-01

    Mel-18 is a member of the polycomb group (PcG) of proteins, which are chromatin regulatory factors that play an important role in development and oncogenesis. This study was designed to investigate the clinical and prognostic significance of Mel-18 in the patients with prostate cancer. Immunostaining with Mel-18 specific antibodies was performed on paraffin sections from 202 patients. Correlations between Mel-18 and the Gleason grading system, clinical stage, serum prostate-specific antigen (PSA) levels, and age were evaluated. PSA recurrence in 76 patients who underwent radical prostatectomy and survival in 59 patients with metastases at diagnosis were analyzed to evaluate the influence of Mel-18 expression in cancer progression using Kaplan-Meier analysis and multivariate Cox regression analysis. Staining was seen in all prostatic tissues. Mel-18 expression was significantly reduced in the prostate cancer patients with PSA levels over 100 ng/ml (P=0.009), advanced clinical stage (>T4, N1, or M1 disease, P=0.029), higher Gleason grade or with a higher Gleason score (P=0.018) than in those with other clinicopathologic features. Negative expression of Mel-18 was associated with significantly higher rates of PSA recurrence after radical prostatectomy than with positive expression of Mel-18 (P = 0.029), and was an independent predictor of PSA recurrence (P=0.034, HR=2.143) in multivariate analysis. Similarly, metastatic prostate cancer patients with negative expression of Mel-18 showed significantly worse survival compared with the positive expression of Mel-18 (P=0.025). In multivariate analysis, negative expression of Mel-18 was an independent predictor of cancer-specific survival (P=0.024, HR=2.365). Our study provides important evidence for the recognition of Mel-18 as a tumor suppressor. The expression of Mel-18 showed potential as a prognostic marker for human prostate cancer. Copyright © 2011 Elsevier Inc. All rights reserved.

  17. Correlation of analysis with high level vibration test results for primary coolant piping

    International Nuclear Information System (INIS)

    Park, Y.J.; Hofmayer, C.H.; Costello, J.F.

    1992-01-01

    Dynamic tests on a modified 1/2.5-scale model of pressurized water reactor (PWR) primary coolant piping were performed using a large shaking table at Tadotsu, Japan. The High Level Vibration Test (HLVT) program was part of a cooperative study between the United States (Nuclear Regulatory Commission/Brookhaven National Laboratory, NRC/BNL) and Japan (Ministry of International Trade and Industry/Nuclear Power Engineering Center). During the test program, the excitation level of each test run was gradually increased up to the limit of the shaking table and significant plastic strains, as well as cracking, were induced in the piping. To fully utilize the test results, NRC/BNL sponsored a project to develop corresponding analytical predictions for the nonlinear dynamic response of the piping for selected test runs. The analyses were performed using both simplified and detailed approaches. The simplified approaches utilize a linear solution and an approximate formulation for nonlinear dynamic effects such as the use of a deamplification factor. The detailed analyses were performed using available nonlinear finite element computer codes, including the MARC, ABAQUS, ADINA and WECAN codes. A comparison of various analysis techniques with the test results shows a higher prediction error in the detailed strain values in the overall response values. A summary of the correlation analyses was presented before the BNL. This paper presents a detailed description of the various analysis results and additional comparisons with test results

  18. Analysis about correlation between the shape and histopathological locations of mammographic microcalcifications

    International Nuclear Information System (INIS)

    Kim, Wha Young; Cho, Young Ah; Choi, Hye Young; Sung, Soon Hee; Bacek, Seung Yeon

    1998-01-01

    To analyze the location of microcalcifications present on pathologic specimens and the relationship between the shape of clustered microcalcifications seen on mammogram and the location of these microcalcifications on pathologic specimen. In 84 female patients aged 25-68, we analysed the location of microcalcifications seen on pathologic speciments. In 65 cases, the shape of these microcalcifications correlated with their location. These shapes, as seen on mammograms, were classified as granular, linear, or branching;the location of microcalcifications was difined as intraductal, stromal, lobular, or a mixture of the three. To determine the difference, if any, between pathologic diagnosis and pathological location and shape as seen on mammograms, statistical analysis using the Chi-square test was performed. Among 84 cases, 51 were benign and 33cases were malignant. In both types of disease, in 45% and 58% of cases, respectively, microcalcifications were located intraductally. There was no statistically significant difference between pathologic diagnosis and pathologic locations (p=3D0.191);analysis of the relationship between shape of microcalcification and pathological location similarly revealed no statistically significant difference(p>0.05). In four of 33 cases of malignant disease(12%), there was microcalcification not only of the tumor itself but also of the adjacent non-tumorous region. Regardless of whether the disease was benign or melignant, microcalcifieations were most commonly intraductal. The relationship between shape and location of microcalcifications seen on pathologic specimens demonstrated no statistical significance.=20

  19. Uncertainty correlation in stochastic safety analysis of natural circulation decay heat removal of liquid metal reactor

    International Nuclear Information System (INIS)

    Takata, Takashi; Yamaguchi, Akira

    2009-01-01

    Since various uncertainties of input variables are involved and nonlinearly-correlated in the Best Estimate (BE) plant dynamics code, it is of importance to evaluate the importance of input uncertainty to the computational results and to estimate the accuracy of the confidence level of the results. In order to estimate the importance and the accuracy, the authors have applied the stochastic safety analysis procedure using the Latin Hypercube sampling method to Liquid Metal Reactor (LMR) natural circulation Decay Heat Removal (DHR) phenomenon in the present paper. 17 input variables are chosen for the analyses and 5 influential variables, which affect the maximum coolant temperature at the core in a short period of time (several tens seconds), are selected to investigate the importance by comparing with the full-scope parametric analysis. As a result, it has been demonstrated that a comparative small number of samples is sufficient enough to estimate the dominant input variable and the confidence level. Furthermore, the influence of the sampling method on the accuracy of the upper tolerance limit (confidence level of 95%) has been examined based on the Wilks' formula. (author)

  20. Correlation between interleukin-6 and primary hepatocellular carcinoma: a meta-analysis

    Directory of Open Access Journals (Sweden)

    LI Xia

    2015-06-01

    Full Text Available ObjectiveTo evaluate the correlation between interleukin (IL6 and primary hepatocellular carcinoma (HCC. MethodsCase-control studies that included quantitative data on plasma or serum IL-6 levels of patients with HCC were identified from PubMed, ISI Web of Knowledge, CBM, and CNKI. A meta-analysis was performed to quantitatively and comprehensively analyze data. ResultsTwenty-five studies were included and the meta-analysis was conducted separately for 3 groups: HCC vs controls, HCC vs liver cirrhosis, and HCC vs hepatitis. The serum IL-6 levels of patients with HCC were significantly higher than those of healthy controls (25 studies, standardized mean difference (SMD 5.02, 95% CI: 4.13-5.91, Z=11.05, P<0.000 1, patients with liver cirrhosis (15 studies, SMD=236, 95% CI: 1.54-3.19, Z=5.60, P<0.000 1, and patients with hepatitis (7 studies, SMD=2.63, 95% CI: 1.24-4.03, Z=369, P=0.000 2. ConclusionThe inflammatory mediator, IL-6, may play an important role in the development and progression of HCC.

  1. Nonlinear Analysis and Post-Test Correlation for a Curved PRSEUS Panel

    Science.gov (United States)

    Gould, Kevin; Lovejoy, Andrew E.; Jegley, Dawn; Neal, Albert L.; Linton, Kim, A.; Bergan, Andrew C.; Bakuckas, John G., Jr.

    2013-01-01

    The Pultruded Rod Stitched Efficient Unitized Structure (PRSEUS) concept, developed by The Boeing Company, has been extensively studied as part of the National Aeronautics and Space Administration's (NASA s) Environmentally Responsible Aviation (ERA) Program. The PRSEUS concept provides a light-weight alternative to aluminum or traditional composite design concepts and is applicable to traditional-shaped fuselage barrels and wings, as well as advanced configurations such as a hybrid wing body or truss braced wings. Therefore, NASA, the Federal Aviation Administration (FAA) and The Boeing Company partnered in an effort to assess the performance and damage arrestments capabilities of a PRSEUS concept panel using a full-scale curved panel in the FAA Full-Scale Aircraft Structural Test Evaluation and Research (FASTER) facility. Testing was conducted in the FASTER facility by subjecting the panel to axial tension loads applied to the ends of the panel, internal pressure, and combined axial tension and internal pressure loadings. Additionally, reactive hoop loads were applied to the skin and frames of the panel along its edges. The panel successfully supported the required design loads in the pristine condition and with a severed stiffener. The panel also demonstrated that the PRSEUS concept could arrest the progression of damage including crack arrestment and crack turning. This paper presents the nonlinear post-test analysis and correlation with test results for the curved PRSEUS panel. It is shown that nonlinear analysis can accurately calculate the behavior of a PRSEUS panel under tension, pressure and combined loading conditions.

  2. Combination of canonical correlation analysis and empirical mode decomposition applied to denoising the labor electrohysterogram.

    Science.gov (United States)

    Hassan, Mahmoud; Boudaoud, Sofiane; Terrien, Jérémy; Karlsson, Brynjar; Marque, Catherine

    2011-09-01

    The electrohysterogram (EHG) is often corrupted by electronic and electromagnetic noise as well as movement artifacts, skeletal electromyogram, and ECGs from both mother and fetus. The interfering signals are sporadic and/or have spectra overlapping the spectra of the signals of interest rendering classical filtering ineffective. In the absence of efficient methods for denoising the monopolar EHG signal, bipolar methods are usually used. In this paper, we propose a novel combination of blind source separation using canonical correlation analysis (BSS_CCA) and empirical mode decomposition (EMD) methods to denoise monopolar EHG. We first extract the uterine bursts by using BSS_CCA then the biggest part of any residual noise is removed from the bursts by EMD. Our algorithm, called CCA_EMD, was compared with wavelet filtering and independent component analysis. We also compared CCA_EMD with the corresponding bipolar signals to demonstrate that the new method gives signals that have not been degraded by the new method. The proposed method successfully removed artifacts from the signal without altering the underlying uterine activity as observed by bipolar methods. The CCA_EMD algorithm performed considerably better than the comparison methods.

  3. Real-Time EEG Signal Enhancement Using Canonical Correlation Analysis and Gaussian Mixture Clustering

    Directory of Open Access Journals (Sweden)

    Chin-Teng Lin

    2018-01-01

    Full Text Available Electroencephalogram (EEG signals are usually contaminated with various artifacts, such as signal associated with muscle activity, eye movement, and body motion, which have a noncerebral origin. The amplitude of such artifacts is larger than that of the electrical activity of the brain, so they mask the cortical signals of interest, resulting in biased analysis and interpretation. Several blind source separation methods have been developed to remove artifacts from the EEG recordings. However, the iterative process for measuring separation within multichannel recordings is computationally intractable. Moreover, manually excluding the artifact components requires a time-consuming offline process. This work proposes a real-time artifact removal algorithm that is based on canonical correlation analysis (CCA, feature extraction, and the Gaussian mixture model (GMM to improve the quality of EEG signals. The CCA was used to decompose EEG signals into components followed by feature extraction to extract representative features and GMM to cluster these features into groups to recognize and remove artifacts. The feasibility of the proposed algorithm was demonstrated by effectively removing artifacts caused by blinks, head/body movement, and chewing from EEG recordings while preserving the temporal and spectral characteristics of the signals that are important to cognitive research.

  4. Correlation analysis of inorganic elements in biological tissue if DMDmdx/J mice using INAA

    International Nuclear Information System (INIS)

    Metairon, Sabrina; Zamboni, Cibele B.; Suzuki, Miriam F.; Bueno Junior, Carlos R.

    2011-01-01

    Instrumental neutron activation analysis technique (INAA) has been used to determine Br, Ca, Cl, K, Mg, Na and S concentrations in bone and other organs samples from DMD mdx /J dystrophic mice as well as C57BL/6J control group mice. The DMD mdx /J mouse strain is relevant as an experimental model for Duchenne Muscular Dystrophy (DMD), which is the most severe and prevalent type of muscular dystrophy. Muscle weakness, premature death and instability of the membrane that involves the muscle fibers - causing functional/structural abnormalities and cell death - are main characteristics of this genetic disease. To show in more details the alterations that this disease may cause in bones (tibiae) and organs (quadriceps and heart), correlations matrixes were generated for both strains permitting a comparison between these groups. A significant change was observed in the analysis of the heart of dystrophic mice suggesting that this dysfunction affects severely the heart muscle. The results emphasize physiologic differences for Na, Ca and Mg and suggest that Br and S results are altered, emphasizing a constant monitoring needs. Other than that, these results may help the researchers to evaluate the efficiency of new treatments and to compare the advantages of different treatment approaches before performing tests in patients with muscular dystrophy. (author)

  5. Importance of the Correlation between Width and Length in the Shape Analysis of Nanorods: Use of a 2D Size Plot To Probe Such a Correlation.

    Science.gov (United States)

    Zhao, Zhihua; Zheng, Zhiqin; Roux, Clément; Delmas, Céline; Marty, Jean-Daniel; Kahn, Myrtil L; Mingotaud, Christophe

    2016-08-22

    Analysis of nanoparticle size through a simple 2D plot is proposed in order to extract the correlation between length and width in a collection or a mixture of anisotropic particles. Compared to the usual statistics on the length associated with a second and independent statistical analysis of the width, this simple plot easily points out the various types of nanoparticles and their (an)isotropy. For each class of nano-objects, the relationship between width and length (i.e., the strong or weak correlations between these two parameters) may suggest information concerning the nucleation/growth processes. It allows one to follow the effect on the shape and size distribution of physical or chemical processes such as simple ripening. Various electron microscopy pictures from the literature or from the authors' own syntheses are used as examples to demonstrate the efficiency and simplicity of the proposed 2D plot combined with a multivariate analysis. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  6. Phenomenological analysis of angular correlations in 7 TeV proton-proton collisions from the CMS experiment

    International Nuclear Information System (INIS)

    Ray, R. L.

    2011-01-01

    A phenomenological analysis is presented of recent two-particle angular correlation data on relative pseudorapidity (η) and azimuth reported by the Compact Muon Solenoid (CMS) Collaboration for √(s)=7 TeV proton-proton collisions. The data are described with an empirical jetlike model developed for similar angular correlation measurements obtained from heavy-ion collisions at the Relativistic Heavy-Ion Collider (RHIC). The sameside (small relative azimuth), η-extended correlation structure, referred to as the ridge, is compared with three phenomenological correlation structures suggested by theoretical analysis. These include additional angular correlations due to soft gluon radiation in 2→3 partonic processes, a one-dimensional sameside correlation ridge on azimuth motivated, for example, by color-glass condensate models, and an azimuth quadrupole similar to that required to describe heavy-ion angular correlations. The quadrupole model provides the best overall description of the CMS data, including the ridge, based on χ 2 minimization in agreement with previous studies. Implications of these results with respect to possible mechanisms for producing the CMS sameside correlation ridge are discussed.

  7. A comprehensive examination of heat transfer correlations suitable for reactor safety analysis

    International Nuclear Information System (INIS)

    Groeneveld, D.C.; Snoek, C.W.

    1986-01-01

    Due to the inadequate understanding of heat transfer mechanisms, an empirical approach is often necessary. This approach requires the derivation of empirical heat transfer correlations for each heat transfer configuration, resulting in numerous correlations for each heat transfer mode. A simplification that is frequently used is to combine these heat transfer correlations using some suitably defined local parameters to characterize the heat transfer process. These local condition correlations, usually encountered in reactor safety codes are discussed in this paper

  8. Psychological Correlates of University Students' Academic Performance: A Systematic Review and Meta-Analysis

    Science.gov (United States)

    Richardson, Michelle; Abraham, Charles; Bond, Rod

    2012-01-01

    A review of 13 years of research into antecedents of university students' grade point average (GPA) scores generated the following: a comprehensive, conceptual map of known correlates of tertiary GPA; assessment of the magnitude of average, weighted correlations with GPA; and tests of multivariate models of GPA correlates within and across…

  9. Analysis of the irradiation data for A302B and A533B correlation monitor materials

    International Nuclear Information System (INIS)

    Wang, J.A.

    1996-04-01

    The results of Charpy V-notch impact tests for A302B and A533B-1 Correlation Monitor Materials (CMM) listed in the surveillance power reactor data base (PR-EDB) and material test reactor data base (TR-EDB) are analyzed. The shift of the transition temperature at 30 ft-lb (T 30 ) is considered as the primary measure of radiation embrittlement in this report. The hyperbolic tangent fitting model and uncertainty of the fitting parameters for Charpy impact tests are presented in this report. For the surveillance CMM data, the transition temperature shifts at 30 ft-lb (ΔT 30 ) generally follow the predictions provided by Revision 2 of Regulatory Guide 1.99 (R.G. 1.99). Difference in capsule temperatures is a likely explanation for large deviations from R.G. 1.99 predictions. Deviations from the R.G. 1.99 predictions are correlated to similar deviations for the accompanying materials in the same capsules, but large random fluctuations prevent precise quantitative determination. Significant scatter is noted in the surveillance data, some of which may be attributed to variations from one specimen set to another, or inherent in Charpy V-notch testing. The major contributions to the uncertainty of the R.G. 1.99 prediction model, and the overall data scatter are from mechanical test results, chemical analysis, irradiation environments, fluence evaluation, and inhomogeneous material properties. Thus in order to improve the prediction model, control of the above-mentioned error sources needs to be improved. In general the embrittlement behavior of both the A302B and A533B-1 plate materials is similar. There is evidence for a fluence-rate effect in the CMM data irradiated in test reactors; thus its implication on power reactor surveillance programs deserves special attention

  10. CORRELATION ANALYSIS BETWEEN DEPRESSIVE MANIFESTATIONS AND MORPHOLOGICAL LESION CHARACTERISTICS IN PATIENTS WITH STROKE

    Directory of Open Access Journals (Sweden)

    Stojanovic Zlatan

    2014-04-01

    Full Text Available Introduction: Knowledge of etiopathogenesis of post-stroke depressive phenomena contributes to early diagnostics which shortens recovery to a great extent and suits the social and professional rehabilitation of patients, if followed by proper psycho/pharmacotherapy. The aim of this work is to research dependence of depressive manifestations considering the size and anatomical localization of lesion. Subjects and Methods: The research included 118 patients with stroke. Lesion localization was defined on computerized axial tomography records, whereas the area and perimeter of lesion were measured by AutoCAD 2004 software. Examinations by means of Hamilton Rating Scale for Depression were carried out by the method of random selection 11–40 days after stroke. Correlation analysis was made by simple linear/nonlinear regression and Cox’s hazard regression model. Results: Negative correlation was observed between the intensity of depressive manifestations and the size of cerebrovascular lesion (Spearman’s r= – 0.263, P= 0.004. By means of Cox’s regression model we determined 4.389 times higher risk for depression occurrence in female patients (P< 0.001, as well as higher risk due to lobus limbicus structure damages (hazard ratio eb(HR = 2.661, P= 0.019. Conclusion: Lower intensity of depressive manifestations with larger cerebrovascular lesions, we have explained by activation of reparation mechanisms with energy savings and decrease (due to neurological deficits of afferent peripheral sensations which antecedent the occurrence of emotions (James-Lange peripheral theory of emotions.

  11. Ultrasound and PET-CT Correlation in Shoulder Pathology: A 5-Year Retrospective Analysis.

    Science.gov (United States)

    Burke, Christopher J; Walter, William R; Adler, Ronald S; Babb, James S; Sanger, Joseph; Ponzo, Fabio

    2017-10-01

    To correlate shoulder ultrasound and radiography with F-FDG PET-CT to establish FDG uptake and therefore range of metabolic activity, as defined by SUV analysis, in various symptomatic shoulder pathologies. Retrospective database query was performed for shoulder ultrasound and PET-CT scans between January 2012 and January 2017. Patients who had both studies within 1 year were included. Age- and sex-matched control patients with PET-CT scans only were also included. Retrospective image review determined shoulder pathology, and F-FDG SUVmax was measured using regions of interest placed at the glenohumeral joint, rotator cuff/bursa, and bicipital groove. Glenohumeral and acromioclavicular osteoarthrosis was assessed by radiography using the Kellgren-Lawrence classification system. Thirty-three patients had both imaging studies within 1 year. Ten patients (11 cases) were included, ranging in age from 56 to 90 years (mean, 67.9 years). Control subjects were selected among patients receiving PET-CT within 1 week of symptomatic patients. Glenohumeral osteoarthrosis was mild in 3 (27%), moderate in 2 (18%), and severe in 2 (18%). Six full-thickness rotator cuff tears (55%) were identified. SUVmax means were compared between the pathologic and control groups and were significantly higher in the former: glenohumeral joint (1.96 vs 1.32; P = 0.016), rotator cuff/bursa (2.80 vs 2.0; P = 0.005), and bicipital groove (2.19 vs 1.48; P = 0.007). The highest values were seen in full-thickness rotator cuff tear and severe biceps tenosynovitis. Increased metabolic activity about the shoulder is associated with a spectrum of rotator cuff, glenohumeral joint, and other soft tissue pathology that can be correlated with diagnostic ultrasound findings.

  12. VOLUME STUDY WITH HIGH DENSITY OF PARTICLES BASED ON CONTOUR AND CORRELATION IMAGE ANALYSIS

    Directory of Open Access Journals (Sweden)

    Tatyana Yu. Nikolaeva

    2014-11-01

    Full Text Available The subject of study is the techniques of particle statistics evaluation, in particular, processing methods of particle images obtained by coherent illumination. This paper considers the problem of recognition and statistical accounting for individual images of small scattering particles in an arbitrary section of the volume in case of high concentrations. For automatic recognition of focused particles images, a special algorithm for statistical analysis based on contouring and thresholding was used. By means of the mathematical formalism of the scalar diffraction theory, coherent images of the particles formed by the optical system with high numerical aperture were simulated. Numerical testing of the method proposed for the cases of different concentrations and distributions of particles in the volume was performed. As a result, distributions of density and mass fraction of the particles were obtained, and the efficiency of the method in case of different concentrations of particles was evaluated. At high concentrations, the effect of coherent superposition of the particles from the adjacent planes strengthens, which makes it difficult to recognize images of particles using the algorithm considered in the paper. In this case, we propose to supplement the method with calculating the cross-correlation function of particle images from adjacent segments of the volume, and evaluating the ratio between the height of the correlation peak and the height of the function pedestal in the case of different distribution characters. The method of statistical accounting of particles considered in this paper is of practical importance in the study of volume with particles of different nature, for example, in problems of biology and oceanography. Effective work in the regime of high concentrations expands the limits of applicability of these methods for practically important cases and helps to optimize determination time of the distribution character and

  13. Genome-wide analysis of esophageal adenocarcinoma yields specific copy number aberrations that correlate with prognosis.

    Science.gov (United States)

    Frankel, Adam; Armour, Nicola; Nancarrow, Derek; Krause, Lutz; Hayward, Nicholas; Lampe, Guy; Smithers, B Mark; Barbour, Andrew

    2014-04-01

    The incidence of esophageal adenocarcinoma (EAC) has been increasing rapidly for the past 3 decades in Western (Caucasian) populations. Curative treatment is based around esophagectomy, which has a major impact on quality of life. For those suitable for treatment with curative intent, 5-year survival is ∼30%. More accurate prognostic tools are therefore needed, and copy number aberrations (CNAs) may offer the ability to act as prospective biomarkers in this regard. We performed a genome-wide examination of CNAs in 54 samples of EAC using single-nucleotide polymorphism (SNP) arrays. Our aims were to describe frequent regions of CNA, to define driver CNAs, and to identify CNAs that correlated with survival. Regions of frequent amplification included oncogenes such as EGFR, MYC, KLF12, and ERBB2, while frequently deleted regions included tumor suppressor genes such as CDKN2A/B, PTPRD, FHIT, and SMAD4. The genomic identification of significant targets in cancer (GISTIC) algorithm identified 24 regions of gain and 28 regions of loss that were likely to contain driver changes. We discovered 61 genes in five regions that, when stratified by CNA type (gain or loss), correlated with a statistically significant difference in survival. Pathway analysis of the genes residing in both the GISTIC and prognostic regions showed they were significantly enriched for cancer-related networks. Finally, we discovered that copy-neutral loss of heterozygosity is a frequent mechanism of CNA in genes currently targetable by chemotherapy, potentially leading to under-reporting of cases suitable for such treatment. Copyright © 2014 Wiley Periodicals, Inc.

  14. Correlating behavioral responses to FMRI signals from human prefrontal cortex: examining cognitive processes using task analysis.

    Science.gov (United States)

    DeSouza, Joseph F X; Ovaysikia, Shima; Pynn, Laura

    2012-06-20

    The aim of this methods paper is to describe how to implement a neuroimaging technique to examine complementary brain processes engaged by two similar tasks. Participants' behavior during task performance in an fMRI scanner can then be correlated to the brain activity using the blood-oxygen-level-dependent signal. We measure behavior to be able to sort correct trials, where the subject performed the task correctly and then be able to examine the brain signals related to correct performance. Conversely, if subjects do not perform the task correctly, and these trials are included in the same analysis with the correct trials we would introduce trials that were not only for correct performance. Thus, in many cases these errors can be used themselves to then correlate brain activity to them. We describe two complementary tasks that are used in our lab to examine the brain during suppression of an automatic responses: the stroop(1) and anti-saccade tasks. The emotional stroop paradigm instructs participants to either report the superimposed emotional 'word' across the affective faces or the facial 'expressions' of the face stimuli(1,2). When the word and the facial expression refer to different emotions, a conflict between what must be said and what is automatically read occurs. The participant has to resolve the conflict between two simultaneously competing processes of word reading and facial expression. Our urge to read out a word leads to strong 'stimulus-response (SR)' associations; hence inhibiting these strong SR's is difficult and participants are prone to making errors. Overcoming this conflict and directing attention away from the face or the word requires the subject to inhibit bottom up processes which typically directs attention to the more salient stimulus. Similarly, in the anti-saccade task(3,4,5,6), where an instruction cue is used to direct only attention to a peripheral stimulus location but then the eye movement is made to the mirror opposite position

  15. 3D spatially-adaptive canonical correlation analysis: Local and global methods.

    Science.gov (United States)

    Yang, Zhengshi; Zhuang, Xiaowei; Sreenivasan, Karthik; Mishra, Virendra; Curran, Tim; Byrd, Richard; Nandy, Rajesh; Cordes, Dietmar

    2018-04-01

    Local spatially-adaptive canonical correlation analysis (local CCA) with spatial constraints has been introduced to fMRI multivariate analysis for improved modeling of activation patterns. However, current algorithms require complicated spatial constraints that have only been applied to 2D local neighborhoods because the computational time would be exponentially increased if the same method is applied to 3D spatial neighborhoods. In this study, an efficient and accurate line search sequential quadratic programming (SQP) algorithm has been developed to efficiently solve the 3D local CCA problem with spatial constraints. In addition, a spatially-adaptive kernel CCA (KCCA) method is proposed to increase accuracy of fMRI activation maps. With oriented 3D spatial filters anisotropic shapes can be estimated during the KCCA analysis of fMRI time courses. These filters are orientation-adaptive leading to rotational invariance to better match arbitrary oriented fMRI activation patterns, resulting in improved sensitivity of activation detection while significantly reducing spatial blurring artifacts. The kernel method in its basic form does not require any spatial constraints and analyzes the whole-brain fMRI time series to construct an activation map. Finally, we have developed a penalized kernel CCA model that involves spatial low-pass filter constraints to increase the specificity of the method. The kernel CCA methods are compared with the standard univariate method and with two different local CCA methods that were solved by the SQP algorithm. Results show that SQP is the most efficient algorithm to solve the local constrained CCA problem, and the proposed kernel CCA methods outperformed univariate and local CCA methods in detecting activations for both simulated and real fMRI episodic memory data. Copyright © 2017 Elsevier Inc. All rights reserved.

  16. Correlation set analysis: detecting active regulators in disease populations using prior causal knowledge

    Directory of Open Access Journals (Sweden)

    Huang Chia-Ling

    2012-03-01

    Full Text Available Abstract Background Identification of active causal regulators is a crucial problem in understanding mechanism of diseases or finding drug targets. Methods that infer causal regulators directly from primary data have been proposed and successfully validated in some cases. These methods necessarily require very large sample sizes or a mix of different data types. Recent studies have shown that prior biological knowledge can successfully boost a method's ability to find regulators. Results We present a simple data-driven method, Correlation Set Analysis (CSA, for comprehensively detecting active regulators in disease populations by integrating co-expression analysis and a specific type of literature-derived causal relationships. Instead of investigating the co-expression level between regulators and their regulatees, we focus on coherence of regulatees of a regulator. Using simulated datasets we show that our method performs very well at recovering even weak regulatory relationships with a low false discovery rate. Using three separate real biological datasets we were able to recover well known and as yet undescribed, active regulators for each disease population. The results are represented as a rank-ordered list of regulators, and reveals both single and higher-order regulatory relationships. Conclusions CSA is an intuitive data-driven way of selecting directed perturbation experiments that are relevant to a disease population of interest and represent a starting point for further investigation. Our findings demonstrate that combining co-expression analysis on regulatee sets with a literature-derived network can successfully identify causal regulators and help develop possible hypothesis to explain disease progression.

  17. The global prevalence and correlates of skin bleaching: a meta-analysis and meta-regression analysis.

    Science.gov (United States)

    Sagoe, Dominic; Pallesen, Ståle; Dlova, Ncoza C; Lartey, Margaret; Ezzedine, Khaled; Dadzie, Ophelia

    2018-06-11

    To estimate and investigate the global lifetime prevalence and correlates of skin bleaching. A meta-analysis and meta-regression analysis was performed based on a systematic and comprehensive literature search conducted in Google Scholar, ISI Web of Science, ProQuest, PsycNET, PubMed, and other relevant websites and reference lists. A total of 68 studies (67,665 participants) providing original data on the lifetime prevalence of skin bleaching were included. Publication bias was corrected using the trim and fill procedure. The pooled (imputed) lifetime prevalence of skin bleaching was 27.7% (95% CI: 19.6-37.5, I 2  = 99.6, P < 0.01). The highest significant prevalences were associated with: males (28.0%), topical corticosteroid use (51.8%), Africa (27.1%), persons aged ≤30 years (55.9%), individuals with only primary school education (31.6%), urban or semiurban residents (74.9%), patients (21.3%), data from 2010-2017 (26.8%), dermatological evaluation and testing-based assessment (24.9%), random sampling methods (29.2%), and moderate quality studies (32.3%). The proportion of females in study samples was significantly related to skin bleaching prevalence. Despite some limitations, our results indicate that the practice of skin bleaching is a serious global public health issue that should be addressed through appropriate public health interventions. © 2018 The International Society of Dermatology.

  18. Correlating multidimensional fetal heart rate variability analysis with acid-base balance at birth

    International Nuclear Information System (INIS)

    Frasch, Martin G; Durosier, Lucien D; Xu, Yawen; Wang, Xiaogang; Gao, Xin; Stampalija, Tamara; Herry, Christophe; Seely, Andrew JE; Casati, Daniela; Ferrazzi, Enrico; Alfirevic, Zarko

    2014-01-01

    Fetal monitoring during labour currently fails to accurately detect acidemia. We developed a method to assess the multidimensional properties of fetal heart rate variability (fHRV) from trans-abdominal fetal electrocardiogram (fECG) during labour. We aimed to assess this novel bioinformatics approach for correlation between fHRV and neonatal pH or base excess (BE) at birth. We enrolled a prospective pilot cohort of uncomplicated singleton pregnancies at 38–42 weeks’ gestation in Milan, Italy, and Liverpool, UK. Fetal monitoring was performed by standard cardiotocography. Simultaneously, with fECG (high sampling frequency) was recorded. To ensure clinician blinding, fECG information was not displayed. Data from the last 60 min preceding onset of second-stage labour were analyzed using clinically validated continuous individualized multiorgan variability analysis (CIMVA) software in 5 min overlapping windows. CIMVA allows simultaneous calculation of 101 fHRV measures across five fHRV signal analysis domains. We validated our mathematical prediction model internally with 80:20 cross-validation split, comparing results to cord pH and BE at birth. The cohort consisted of 60 women with neonatal pH values at birth ranging from 7.44 to 6.99 and BE from −0.3 to −18.7 mmol L −1 . Our model predicted pH from 30 fHRV measures (R 2 = 0.90, P < 0.001) and BE from 21 fHRV measures (R 2 = 0.77, P < 0.001). Novel bioinformatics approach (CIMVA) applied to fHRV derived from trans-abdominal fECG during labor correlated well with acid-base balance at birth. Further refinement and validation in larger cohorts are needed. These new measurements of fHRV might offer a new opportunity to predict fetal acid-base balance at birth. (fast track communication)

  19. Applying big data technologies in the financial sector – using sentiment analysis to identify correlations in the stock market

    Directory of Open Access Journals (Sweden)

    Eszter Katalin Bognár

    2016-06-01

    Full Text Available The aim of this article is to introduce a system that is capable of collecting and analyzing different types of financial data to support traders in their decision - making. Oracle’s Big Data platform Oracle Advanced Analytics was utilized, which extends the Oracle Database with Oracle R, thus providing the opportunity to run embedded R scripts on the database server to speed up data processing. The extract, transform and load (ETL process was combined with a dictionary - based sentiment analysis module to examine cross - correlation and causality between numerical and textual financial data for a 10 week period. A notable correlation (0.42 was found between daily news sentiment scores and daily stock returns. By applying cross - correlation analysis and Granger causality testing, the results show that the news’ impact is incorporated into stock prices rapidly, having the highest correlation on the first day, while the returns’ impact on market sentiment is seen only after a few days.

  20. Parameter motivated mutual correlation analysis: Application to the study of currency exchange rates based on intermittency parameter and Hurst exponent

    Science.gov (United States)

    Cristescu, Constantin P.; Stan, Cristina; Scarlat, Eugen I.; Minea, Teofil; Cristescu, Cristina M.

    2012-04-01

    We present a novel method for the parameter oriented analysis of mutual correlation between independent time series or between equivalent structures such as ordered data sets. The proposed method is based on the sliding window technique, defines a new type of correlation measure and can be applied to time series from all domains of science and technology, experimental or simulated. A specific parameter that can characterize the time series is computed for each window and a cross correlation analysis is carried out on the set of values obtained for the time series under investigation. We apply this method to the study of some currency daily exchange rates from the point of view of the Hurst exponent and the intermittency parameter. Interesting correlation relationships are revealed and a tentative crisis prediction is presented.

  1. Measurement and analysis of quadruple (αγγ) angular correlations for high spin states of 24Mg

    International Nuclear Information System (INIS)

    Wiedenhoever, I.; Wuosmaa, A. H.; Lister, C. J.; Carpenter, M. P.; Janssens, R. V. F.; Amro, H.; Caggiano, J.; Heinz, A.; Kondev, F. G.; Lauritsen, T.; Siem, S.; Sonzogni, A.; Bhattacharyya, P.; Devlin, M.; Sarantites, D. G.; Sobotka, L. G.

    2000-01-01

    The high-lying, α-decaying states in 24 Mg have been studied by measuring the complete decay path of α and γ emissions using five segmented Silicon detectors in conjunction with GAMMASPHERE. The authors analyzed the (αγ) triple angular correlations and, for the first time, (αγγ) quadruple correlations. The data analysis is based on a new Fourier transformation technique. The power of the technique is demonstrated

  2. Correlation analysis of energy indicators for sustainable development using multivariate statistical techniques

    International Nuclear Information System (INIS)

    Carneiro, Alvaro Luiz Guimaraes; Santos, Francisco Carlos Barbosa dos

    2007-01-01

    Energy is an essential input for social development and economic growth. The production and use of energy cause environmental degradation at all levels, being local, regional and global such as, combustion of fossil fuels causing air pollution; hydropower often causes environmental damage due to the submergence of large areas of land; and global climate change associated with the increasing concentration of greenhouse gases in the atmosphere. As mentioned in chapter 9 of Agenda 21, the Energy is essential to economic and social development and improved quality of life. Much of the world's energy, however, is currently produced and consumed in ways that could not be sustained if technologies were remain constant and if overall quantities were to increase substantially. All energy sources will need to be used in ways that respect the atmosphere, human health, and the environment as a whole. The energy in the context of sustainable development needs a set of quantifiable parameters, called indicators, to measure and monitor important changes and significant progress towards the achievement of the objectives of sustainable development policies. The indicators are divided into four dimensions: social, economic, environmental and institutional. This paper shows a methodology of analysis using Multivariate Statistical Technique that provide the ability to analyse complex sets of data. The main goal of this study is to explore the correlation analysis among the indicators. The data used on this research work, is an excerpt of IBGE (Instituto Brasileiro de Geografia e Estatistica) data census. The core indicators used in this study follows The IAEA (International Atomic Energy Agency) framework: Energy Indicators for Sustainable Development. (author)

  3. Vector correlation analysis for inelastic and reactive collisions between partners possessing spin and orbital angular momentum.

    Science.gov (United States)

    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.

  4. Meta-Analysis of the Correlation between Apparent Diffusion Coefficient and Standardized Uptake Value in Malignant Disease

    Directory of Open Access Journals (Sweden)

    Shengming Deng

    2017-01-01

    Full Text Available The objective of this meta-analysis is to explore the correlation between the apparent diffusion coefficient (ADC on diffusion-weighted MR and the standard uptake value (SUV of 18F-FDG on PET/CT in patients with cancer. Databases such as PubMed (MEDLINE included, EMBASE, and Cochrane Database of Systematic Review were searched for relevant original articles that explored the correlation between SUV and ADC in English. After applying Fisher’s r-to-z transformation, correlation coefficient (r values were extracted from each study and 95% confidence intervals (CIs were calculated. Sensitivity and subgroup analyses based on tumor type were performed to investigate the potential heterogeneity. Forty-nine studies were eligible for the meta-analysis, comprising 1927 patients. Pooled r for all studies was −0.35 (95% CI: −0.42–0.28 and exhibited a notable heterogeneity (I2 = 78.4%; P < 0.01. In terms of the cancer type subgroup analysis, combined correlation coefficients of ADC/SUV range from −0.12 (lymphoma, n = 5 to −0.59 (pancreatic cancer, n = 2. We concluded that there is an average negative correlation between ADC and SUV in patients with cancer. Higher correlations were found in the brain tumor, cervix carcinoma, and pancreas cancer. However, a larger, prospective study is warranted to validate these findings in different cancer types.

  5. Petrographic Analysis and Geochemical Source Correlation of Pigeon Peak, Sutter Buttes, CA

    Science.gov (United States)

    Novotny, N. M.; Hausback, B. P.

    2013-12-01

    The Sutter Buttes are a volcanic complex located in the center of the Great Valley north of Sacramento. They are comprised of numerous inter-intruding andesite and rhyolite lava domes of varying compositions surrounded by a shallow rampart of associated tephras. The Pigeon Peak block-and-ash flow sequence is located in the rampart and made up of a porphyritic Biotite bearing Hornblende Andesite. The andesite blocks demonstrate a high degree of propylization in hornblende crystals, highly zoned plagioclase, trace olivine, and display a red to gray color gradation. DAR is an andesite dome located less than one mile from Pigeon Peak. Of the 15 to 25 andesite lava domes within four miles from Pigeon Peak, only DAR displays trace olivine, red to grey color stratification, low biotite content, and propylitized hornblende. These characteristic similarities suggest that DAR may be the source for Pigeon Peak. My investigation used microprobe analysis of the DAR and Pigeon Peak feldspar crystals to identify the magmatic history of the magma body before emplacement. Correlation of the anorthite zoning within the feldspars from both locations support my hypothesis that DAR is the source of the Pigeon Peak block-and-ash flow.

  6. Correlation between Traditional Chinese Medicine Constitution and Dyslipidemia: A Systematic Review and Meta-Analysis

    Directory of Open Access Journals (Sweden)

    Ye-lin Ma

    2017-01-01

    Full Text Available Objective. To study the correlation between Traditional Chinese Medicine (TCM constitution and dyslipidemia. Methods. CNKI, VIP, Wanfang database, CBMdisc, PubMed, and Embase were searched, and meta-analysis was performed by Review Manager 5.2 software. Results. Altogether 11 studies were included with 12890 individuals. The results showed that balanced constitution was a protective factor of dyslipidemia (OR = 0.62, 95% CI 0.47~0.82 while phlegm-dampness constitution was a risk factor of it (OR = 2.50, 95% CI 2.22~2.80, and the effect of phlegm-dampness constitution in South China (OR = 3.31, 95% CI 1.71~6.43 was more obvious than that in East (OR = 2.40, 95% CI 2.06~2.80 and North China (OR = 2.24, 95% CI 1.81~2.78. Conclusion. This study provides evidence for the prevention and treatment of dyslipidemia in TCM. However, most of the studies included are of moderate quality; more high quality, multicenter, large-sample studies are expected to provide higher level evidence.

  7. Viscoelasticity of amyloid plaques in transgenic mouse brain studied by Brillouin microspectroscopy and correlative Raman analysis

    Directory of Open Access Journals (Sweden)

    Sara Mattana

    2017-11-01

    Full Text Available Amyloidopathy is one of the most prominent hallmarks of Alzheimer’s disease (AD, the leading cause of dementia worldwide, and is characterized by the accumulation of amyloid plaques in the brain parenchyma. The plaques consist of abnormal deposits mainly composed of an aggregation-prone protein fragment, β-amyloid 1-40/1-42, into the extracellular matrix. Brillouin microspectroscopy is an all-optical contactless technique that is based on the interaction between visible light and longitudinal acoustic waves or phonons, giving access to the viscoelasticity of a sample on a subcellular scale. Here, we describe the first application of micromechanical mapping based on Brillouin scattering spectroscopy to probe the stiffness of individual amyloid plaques in the hippocampal part of the brain of a β-amyloid overexpressing transgenic mouse. Correlative analysis based on Brillouin and Raman microspectroscopy showed that amyloid plaques have a complex structure with a rigid core of β-pleated sheet conformation (β-amyloid protein surrounded by a softer ring-shaped region richer in lipids and other protein conformations. These preliminary results give a new insight into the plaque biophysics and biomechanics, and a valuable contrast mechanism for the study and diagnosis of amyloidopathy.

  8. Correlation analysis of protein quality characteristics with gluten-free bread properties.

    Science.gov (United States)

    Horstmann, S W; Foschia, M; Arendt, E K

    2017-07-19

    The interest in gluten-free cereal products has increased significantly over the last number of years and there is still a high demand for high quality products. This study aims to establish possible connections between protein properties and dough and bread quality which could advance the knowledge for gluten-free product development. The objective of the present study was to correlate protein properties with bread characteristics. Therefore, a wide range of tests (solubility, emulsifying, foaming, water hydration properties) was performed to characterize a range of food proteins (potato, pea, carob, lupin and soy). Furthermore, the performance of these proteins in a dough matrix (pasting, rheology) and bread formulation (volume, structure, and texture) was analysed. Statistical analysis showed significant (p bread characteristics. The addition of the proteins to the gluten-free bread formulation affected pasting rheological and bread characteristics such as crumb density, crumb hardness and specific volume. The addition of potato and soy protein resulted in the lowest volume with a dense crumb structure and a low consumer acceptance score. However, lupin, pea and carob containing gluten-free breads had a higher specific volume and softer and less dense crumb structure. The protein solubility (r, 0.89; p bread quality.

  9. Comparison of photon correlation spectroscopy with photosedimentation analysis for the determination of aqueous colloid size distributions

    Science.gov (United States)

    Rees, Terry F.

    1990-01-01

    Colloidal materials, dispersed phases with dimensions between 0.001 and 1 μm, are potential transport media for a variety of contaminants in surface and ground water. Characterization of these colloids, and identification of the parameters that control their movement, are necessary before transport simulations can be attempted. Two techniques that can be used to determine the particle-size distribution of colloidal materials suspended in natural waters are compared. Photon correlation Spectroscopy (PCS) utilizes the Doppler frequency shift of photons scattered off particles undergoing Brownian motion to determine the size of colloids suspended in water. Photosedimentation analysis (PSA) measures the time-dependent change in optical density of a suspension of colloidal particles undergoing centrifugation. A description of both techniques, important underlying assumptions, and limitations are given. Results for a series of river water samples show that the colloid-size distribution means are statistically identical as determined by both techniques. This also is true of the mass median diameter (MMD), even though MMD values determined by PSA are consistently smaller than those determined by PCS. Because of this small negative bias, the skew parameters for the distributions are generally smaller for the PCS-determined distributions than for the PSA-determined distributions. Smaller polydispersity indices for the distributions are also determined by PCS.

  10. Analysis of Correlations between Economic Growth (Rate of Real GDP and the Underground Economy

    Directory of Open Access Journals (Sweden)

    Pripoaie Silviu

    2009-06-01

    Full Text Available Analysis of performance of any economy involves the measurement and correlation of threebasic elements: the rate of economic growth, the rate of inflation and unemployment rate. When the rateof growth (rate of real GDP is high, the production of goods and services is growing and thereforeincreasing the number of jobs, decrease unemployment and raise living standards. If the economy is inrecession phase, increasing fiscal pressure to ensure the necessary budgetary funds triggers complexeconomic mechanisms. Rules more strictly is that those who are not able to operate in the normaleconomy to slide towards the underground economy, and this not because he wants to tax evasion, butbecause they simply can not cope with new regulations. It is widely accepted in economic theory andpractice the idea that reliability scale macroeconomic indicators of a country is affected by size ofunderground economy and the various tests made so far on this subject, focusing either on the socialaspect or the economic or moral, or emphasizes the illegal or the edge of legality. This has led to variousstudies in this area do not provide comparable data or provide data to the contrary. Worldwide were putin place, however, some calculation methods provided that applied the same country and same period,the results are rarely consistent, sometimes even in fundamentally different.

  11. Residual strain sensor using Al-packaged optical fiber and Brillouin optical correlation domain analysis.

    Science.gov (United States)

    Choi, Bo-Hun; Kwon, Il-Bum

    2015-03-09

    We propose a distributed residual strain sensor that uses an Al-packaged optical fiber for the first time. The residual strain which causes Brillouin frequency shifts in the optical fiber was measured using Brillouin optical correlation domain analysis with 2 cm spatial resolution. We quantified the Brillouin frequency shifts in the Al-packaged optical fiber by the tensile stress and compared them for a varying number of Al layers in the optical fiber. The Brillouin frequency shift of an optical fiber with one Al layer had a slope of 0.038 MHz/με with respect to tensile stress, which corresponds to 78% of that for an optical fiber without Al layers. After removal of the stress, 87% of the strain remained as residual strain. When different tensile stresses were randomly applied, the strain caused by the highest stress was the only one detected as residual strain. The residual strain was repeatedly measured for a time span of nine months for the purpose of reliability testing, and there was no change in the strain except for a 4% reduction, which is within the error tolerance of the experiment. A composite material plate equipped with our proposed Al-packaged optical fiber sensor was hammered for impact experiment and the residual strain in the plate was successfully detected. We suggest that the Al-packaged optical fiber can be adapted as a distributed strain sensor for smart structures, including aerospace structures.

  12. Multi-Hierarchical Gray Correlation Analysis Applied in the Selection of Green Building Design Scheme

    Science.gov (United States)

    Wang, Li; Li, Chuanghong

    2018-02-01

    As a sustainable form of ecological structure, green building is widespread concerned and advocated in society increasingly nowadays. In the survey and design phase of preliminary project construction, carrying out the evaluation and selection of green building design scheme, which is in accordance with the scientific and reasonable evaluation index system, can improve the ecological benefits of green building projects largely and effectively. Based on the new Green Building Evaluation Standard which came into effect on January 1, 2015, the evaluation index system of green building design scheme is constructed taking into account the evaluation contents related to the green building design scheme. We organized experts who are experienced in construction scheme optimization to mark and determine the weight of each evaluation index through the AHP method. The correlation degree was calculated between each evaluation scheme and ideal scheme by using multilevel gray relational analysis model and then the optimal scheme was determined. The feasibility and practicability of the evaluation method are verified by introducing examples.

  13. Thermal error analysis and compensation for digital image/volume correlation

    Science.gov (United States)

    Pan, Bing

    2018-02-01

    Digital image/volume correlation (DIC/DVC) rely on the digital images acquired by digital cameras and x-ray CT scanners to extract the motion and deformation of test samples. Regrettably, these imaging devices are unstable optical systems, whose imaging geometry may undergo unavoidable slight and continual changes due to self-heating effect or ambient temperature variations. Changes in imaging geometry lead to both shift and expansion in the recorded 2D or 3D images, and finally manifest as systematic displacement and strain errors in DIC/DVC measurements. Since measurement accuracy is always the most important requirement in various experimental mechanics applications, these thermal-induced errors (referred to as thermal errors) should be given serious consideration in order to achieve high accuracy, reproducible DIC/DVC measurements. In this work, theoretical analyses are first given to understand the origin of thermal errors. Then real experiments are conducted to quantify thermal errors. Three solutions are suggested to mitigate or correct thermal errors. Among these solutions, a reference sample compensation approach is highly recommended because of its easy implementation, high accuracy and in-situ error correction capability. Most of the work has appeared in our previously published papers, thus its originality is not claimed. Instead, this paper aims to give a comprehensive overview and more insights of our work on thermal error analysis and compensation for DIC/DVC measurements.

  14. A new randomized Kaczmarz based kernel canonical correlation analysis algorithm with applications to information retrieval.

    Science.gov (United States)

    Cai, Jia; Tang, Yi

    2018-02-01

    Canonical correlation analysis (CCA) is a powerful statistical tool for detecting the linear relationship between two sets of multivariate variables. Kernel generalization of it, namely, kernel CCA is proposed to describe nonlinear relationship between two variables. Although kernel CCA can achieve dimensionality reduction results for high-dimensional data feature selection problem, it also yields the so called over-fitting phenomenon. In this paper, we consider a new kernel CCA algorithm via randomized Kaczmarz method. The main contributions of the paper are: (1) A new kernel CCA algorithm is developed, (2) theoretical convergence of the proposed algorithm is addressed by means of scaled condition number, (3) a lower bound which addresses the minimum number of iterations is presented. We test on both synthetic dataset and several real-world datasets in cross-language document retrieval and content-based image retrieval to demonstrate the effectiveness of the proposed algorithm. Numerical results imply the performance and efficiency of the new algorithm, which is competitive with several state-of-the-art kernel CCA methods. Copyright © 2017 Elsevier Ltd. All rights reserved.

  15. A Hybrid Feature Subset Selection Algorithm for Analysis of High Correlation Proteomic Data

    Science.gov (United States)

    Kordy, Hussain Montazery; Baygi, Mohammad Hossein Miran; Moradi, Mohammad Hassan

    2012-01-01

    Pathological changes within an organ can be reflected as proteomic patterns in biological fluids such as plasma, serum, and urine. The surface-enhanced laser desorption and ionization time-of-flight mass spectrometry (SELDI-TOF MS) has been used to generate proteomic profiles from biological fluids. Mass spectrometry yields redundant noisy data that the most data points are irrelevant features for differentiating between cancer and normal cases. In this paper, we have proposed a hybrid feature subset selection algorithm based on maximum-discrimination and minimum-correlation coupled with peak scoring criteria. Our algorithm has been applied to two independent SELDI-TOF MS datasets of ovarian cancer obtained from the NCI-FDA clinical proteomics databank. The proposed algorithm has used to extract a set of proteins as potential biomarkers in each dataset. We applied the linear discriminate analysis to identify the important biomarkers. The selected biomarkers have been able to successfully diagnose the ovarian cancer patients from the noncancer control group with an accuracy of 100%, a sensitivity of 100%, and a specificity of 100% in the two datasets. The hybrid algorithm has the advantage that increases reproducibility of selected biomarkers and able to find a small set of proteins with high discrimination power. PMID:23717808

  16. Subchannel analysis and correlation of the Rod Bundle Heat Transfer (RBHT) steam cooling experimental data

    Energy Technology Data Exchange (ETDEWEB)

    Riley, M.P.; Mohanta, L.; Miller, D.J.; Cheung, F.B. [Pennsylvania State Univ., University Park, PA (United States); Bajorek, S.M.; Tien, K.; Hoxie, C.L. [U.S. Nuclear Regulatory Commission, Washington, DC (United States). Office of Nuclear Regulatory Research

    2016-07-15

    A subchannel analysis of the steam cooling data obtained in the Rod Bundle Heat Transfer (RBHT) test facility has been performed in this study to capture the effect of spacer grids on heat transfer. The RBHT test facility has a 7 x 7 rod bundle with heater rods and with seven spacer grids equally spaced along the length of the rods. A method based on the concept of momentum and heat transport analogy has been developed for calculating the subchannel bulk mean temperature from the measured steam temperatures. Over the range of inlet Reynolds number, the local Nusselt number was found to exhibit a minimum value between the upstream and downstream spacer grids. The presence of a spacer grid not only affects the local Nusselt number downstream of the grid but also affects the local Nusselt number upstream of the next grid. A new correlation capturing the effect of Reynolds number on the local flow restructuring downstream as well as upstream of the spacer grids was proposed for the minimum Nusselt number. In addition, a new enhancement factor accounting for the effects of the upstream as well as downstream spacer grids was developed from the RBHT data. The new enhancement factor was found to compare well with the data from the ACHILLLES test facility.

  17. [Analysis of grey correlation between energy consumption and economic growth in Liaoning Province, China.

    Science.gov (United States)

    Wang, Li; Xi, Feng Ming; Wang, Jiao Yue

    2016-03-01

    The contradiction between energy consumption and economic growth is increasingly prominent in China. Liaoning Province as one of Chinese heavy industrial bases, consumes a large amount of energy. Its economic development has a strong dependence on energy consumption, but the energy in short supply become more apparent. In order to further understand the relationship between energy consumption and economic growth and put forward scientific suggestions on low carbon development, we used the grey correlation analysis method to separately examine the relevance of economic growth with energy consumption industries and energy consumption varieties through analy sis of energy consumption and economic growth data in Liaoning Province from 2000 to 2012. The results showed that the wholesale and retail sector and hotel and restaurant sector were in the minimum energy consumption in all kinds of sectors, but they presented the closest connection with the economic growth. Although industry energy consumption was the maximum, the degree of connection between industry energy consumption and economic growth was weak. In all types of energy consumption, oil and hydro-power consumption had a significant connection with economic growth. However, the degree of connection of coal consumption with economic growth was not significant, which meant that coal utilization efficiency was low. In order to achieve low carbon and sustainable development, Liaoning Province should transform the economic growth mode, adjust industry structure, optimize energy structure, and improve energy utilization efficiency, especially promote producer services and develop clean and renewable energy.

  18. Extending Local Canonical Correlation Analysis to Handle General Linear Contrasts for fMRI Data

    Directory of Open Access Journals (Sweden)

    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.

  19. Correlation Analysis of Water Demand and Predictive Variables for Short-Term Forecasting Models

    Directory of Open Access Journals (Sweden)

    B. M. Brentan

    2017-01-01

    Full Text Available Operational and economic aspects of water distribution make water demand forecasting paramount for water distribution systems (WDSs management. However, water demand introduces high levels of uncertainty in WDS hydraulic models. As a result, there is growing interest in developing accurate methodologies for water demand forecasting. Several mathematical models can serve this purpose. One crucial aspect is the use of suitable predictive variables. The most used predictive variables involve weather and social aspects. To improve the interrelation knowledge between water demand and various predictive variables, this study applies three algorithms, namely, classical Principal Component Analysis (PCA and machine learning powerful algorithms such as Self-Organizing Maps (SOMs and Random Forest (RF. We show that these last algorithms help corroborate the results found by PCA, while they are able to unveil hidden features for PCA, due to their ability to cope with nonlinearities. This paper presents a correlation study of three district metered areas (DMAs from Franca, a Brazilian city, exploring weather and social variables to improve the knowledge of residential demand for water. For the three DMAs, temperature, relative humidity, and hour of the day appear to be the most important predictive variables to build an accurate regression model.

  20. Oblique rotaton in canonical correlation analysis reformulated as maximizing the generalized coefficient of determination.

    Science.gov (United States)

    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.

  1. Correlation and path analysis on main agronomic traits of progeny from space mutation maize inbred lines

    International Nuclear Information System (INIS)

    Zhang Caibo; Wu Zhangdong; Xu Wei; Rong Tingzhao; Cao Moju

    2013-01-01

    In order to discover and utilize the valuable resources from spaceflight mutagenesis maize offspring effectively, cross combinations derived from the offspring of three different maize inbred lines induced by space flight were made to investigate the yield and related agronomic traits under different environmental conditions. Correlation and path analysis indicated that the factors affecting the yield of combinations varied with different mutagenic materials and environmental effects with larger effect coming from environment. Therefore, different selection strategies should be chosen for different induced maize. For the 08-641 mutagenic material, the 100-kernel weight should be first considered to select while taking into account the number of rows per ear and kernels per row. For the RP125 mutagenic material, the kernels per row should be first selected, and then to select the 100-kernels weight and the number of rows per ear traits. For 18-599 mutagenic material, the 100-seed weight should be first selected, then the plant height, ear diameter, ear height, kernels rate and other traits should be selected in different environments. Combined with field resistance, plant types and other traits, excellent maize inbred lines with high yield potential from space mutagenesis offspring were selected. Thus study has obtained some breeding materials useful for further breeding purpose, and provide a reference method as how to use the spaceflight induced materials for for maize breeding. (authors)

  2. Correlation Analysis of PM10 and the Incidence of Lung Cancer in Nanchang, China

    Science.gov (United States)

    Zhou, Yi; Li, Lianshui; Hu, Lei

    2017-01-01

    Air pollution and lung cancer are closely related. In 2013, the World Health Organization listed outdoor air pollution as carcinogenic and regarded it as the most widespread carcinogen that humans are currently exposed to. Here, grey correlation and data envelopment analysis methods are used to determine the pollution factors causing lung cancer among residents in Nanchang, China, and identify population segments which are more susceptible to air pollution. This study shows that particulate matter with particle sizes below 10 micron (PM10) is most closely related to the incidence of lung cancer among air pollution factors including annual mean concentrations of SO2, NO2, PM10, annual haze days, and annual mean Air Pollution Index/Air Quality Index (API/AQI). Air pollution has a greater impact on urban inhabitants as compared to rural inhabitants. When gender differences are considered, women are more likely to develop lung cancer due to air pollution. Smokers are more likely to suffer from lung cancer. These results provide a reference for the government to formulate policies to reduce air pollutant emissions and strengthen anti-smoking measures. PMID:29048397

  3. Multivariate Meta-Analysis of Brain-Mass Correlations in Eutherian Mammals

    Directory of Open Access Journals (Sweden)

    Charlene Steinhausen

    2016-09-01

    Full Text Available The general assumption that brain size differences are an adequate proxy for subtler differences in brain organization turned neurobiologists towards the question why some groups of mammals such as primates, elephants, and whales have such remarkably large brains. In this meta-analysis, an extensive sample of eutherian mammals (115 species distributed in 14 orders provided data about several different biological traits and measures of brain size such as absolute brain mass (AB, relative brain mass (RB; quotient from AB and body mass, and encephalization quotient (EQ. These data were analyzed by established multivariate statistics without taking specific phylogenetic information into account. Species with high AB tend to (1 feed on protein-rich nutrition, (2 have a long lifespan, (3 delay sexual maturity, and (4 have long and rare pregnancies with small litter sizes. Animals with high RB usually have (1 a short life span, (2 reach sexual maturity early, and (3 have short and frequent gestations. Moreover males of species with high RB also have few potential sexual partners. In contrast, animals with high EQs have (1 a high number of potential sexual partners, (2 delayed sexual maturity, and (3 rare gestations with small litter sizes. Based on these correlations, we conclude that Eutheria with either high AB or high EQ occupy high positions in the network of food chains (high trophic levels. Eutheria of low trophic levels can develop a high RB only if they have small body masses.

  4. Correlations between electrocardiogram and biomarkers in acute pulmonary embolism: Analysis of ZATPOL-2 Registry.

    Science.gov (United States)

    Kukla, Piotr; Kosior, Dariusz A; Tomaszewski, Andrzej; Ptaszyńska-Kopczyńska, Katarzyna; Widejko, Katarzyna; Długopolski, Robert; Skrzyński, Andrzej; Błaszczak, Piotr; Fijorek, Kamil; Kurzyna, Marcin

    2017-07-01

    Electrocardiography (ECG) is still one of the first tests performed at admission, mostly in patients (pts) with chest pain or dyspnea. The aim of this study was to assess the correlation between electrocardiographic abnormalities and cardiac biomarkers as well as echocardiographic parameter in patients with acute pulmonary embolism. We performed a retrospective analysis of 614 pts. (F/M 334/280; mean age of 67.9 ± 16.6 years) with confirmed acute pulmonary embolism (APE) who were enrolled to the ZATPOL-2 Registry between 2012 and 2014. Elevated cardiac biomarkers were observed in 358 pts (74.4%). In this group the presence of atrial fibrillation (p = .008), right axis deviation (p = .004), S 1 Q 3 T 3 sign (p electrocardiogram" were as follows: increased heart rate (OR 1.09, 95% CI 1.02-1.17, p = .012), elevated troponin concentration (OR 3.33, 95% CI 1.94-5.72, p = .000), and right ventricular overload (OR 2.30, 95% CI 1.17-4.53, p = .016). Electrocardiographic signs of right ventricular strain are strongly related to elevated cardiac biomarkers and echocardiographic signs of right ventricular overload. ECG may be used in preliminary risk stratification of patient with intermediate- or high-risk forms of APE. © 2017 Wiley Periodicals, Inc.

  5. Correlation analysis of electronic products with myopia in preschool and school aged children

    Directory of Open Access Journals (Sweden)

    Li-Li Sun

    2016-02-01

    Full Text Available AIM: To explore the influence of electronic products on myopia in preschool and school aged children, and the development regularities of myopia, to formulate reasonable guidelines for using eyes healthily, and lay a solid foundation for the prevention and control work. METHODS: This retrospective analysis enrolled 900 3~12 years old children from outpatients department, and all of them were established individualized archives, recording: uncorrected visual acuity, optometry, slit lamp, ophthalmoscopy, strabismus inspection results; recording eye usage condition on TVs, computers, mobile phones, iPad, homework, extra-curricular books. Statistical analyze the refractive status of each age group, the use of electronic products of different age groups and their correlation with refractive status. RESULTS: The number of preschool children with normal uncorrected visual acuity was more than that of early school-age children, and the difference was statistically significant(PP>0.05; the number of children aged 7~12(early school aged childrenwith myopia was more than that of children aged 3~6(preschool childrenand the difference was statistically significant(PCONCLUSION: For preschool children, it is necessary to conduct early screening, health guidance, the establishment of personalized medical records and one-to-one personalized guidance; it is also needed to avoid the arduous learning task with the stacking usage of eyes, to fight for myopia and to control the development of myopia. Therefore, to reduce the use of electronic products has become a topic worthy of further study.

  6. Correlation Analysis of PM10 and the Incidence of Lung Cancer in Nanchang, China

    Directory of Open Access Journals (Sweden)

    Yi Zhou

    2017-10-01

    Full Text Available Air pollution and lung cancer are closely related. In 2013, the World Health Organization listed outdoor air pollution as carcinogenic and regarded it as the most widespread carcinogen that humans are currently exposed to. Here, grey correlation and data envelopment analysis methods are used to determine the pollution factors causing lung cancer among residents in Nanchang, China, and identify population segments which are more susceptible to air pollution. This study shows that particulate matter with particle sizes below 10 micron (PM10 is most closely related to the incidence of lung cancer among air pollution factors including annual mean concentrations of SO2, NO2, PM10, annual haze days, and annual mean Air Pollution Index/Air Quality Index (API/AQI. Air pollution has a greater impact on urban inhabitants as compared to rural inhabitants. When gender differences are considered, women are more likely to develop lung cancer due to air pollution. Smokers are more likely to suffer from lung cancer. These results provide a reference for the government to formulate policies to reduce air pollutant emissions and strengthen anti-smoking measures.

  7. Correlation Analysis of PM10 and the Incidence of Lung Cancer in Nanchang, China.

    Science.gov (United States)

    Zhou, Yi; Li, Lianshui; Hu, Lei

    2017-10-19

    Air pollution and lung cancer are closely related. In 2013, the World Health Organization listed outdoor air pollution as carcinogenic and regarded it as the most widespread carcinogen that humans are currently exposed to. Here, grey correlation and data envelopment analysis methods are used to determine the pollution factors causing lung cancer among residents in Nanchang, China, and identify population segments which are more susceptible to air pollution. This study shows that particulate matter with particle sizes below 10 micron (PM 10 ) is most closely related to the incidence of lung cancer among air pollution factors including annual mean concentrations of SO₂, NO₂, PM 10 , annual haze days, and annual mean Air Pollution Index/Air Quality Index (API/AQI). Air pollution has a greater impact on urban inhabitants as compared to rural inhabitants. When gender differences are considered, women are more likely to develop lung cancer due to air pollution. Smokers are more likely to suffer from lung cancer. These results provide a reference for the government to formulate policies to reduce air pollutant emissions and strengthen anti-smoking measures.

  8. Multivariate two-part statistics for analysis of correlated mass spectrometry data from multiple biological specimens.

    Science.gov (United States)

    Taylor, Sandra L; Ruhaak, L Renee; Weiss, Robert H; Kelly, Karen; Kim, Kyoungmi

    2017-01-01

    High through-put mass spectrometry (MS) is now being used to profile small molecular compounds across multiple biological sample types from the same subjects with the goal of leveraging information across biospecimens. Multivariate statistical methods that combine information from all biospecimens could be more powerful than the usual univariate analyses. However, missing values are common in MS data and imputation can impact between-biospecimen correlation and multivariate analysis results. We propose two multivariate two-part statistics that accommodate missing values and combine data from all biospecimens to identify differentially regulated compounds. Statistical significance is determined using a multivariate permutation null distribution. Relative to univariate tests, the multivariate procedures detected more significant compounds in three biological datasets. In a simulation study, we showed that multi-biospecimen testing procedures were more powerful than single-biospecimen methods when compounds are differentially regulated in multiple biospecimens but univariate methods can be more powerful if compounds are differentially regulated in only one biospecimen. We provide R functions to implement and illustrate our method as supplementary information CONTACT: sltaylor@ucdavis.eduSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  9. Fractal Analysis on the Correlation of Coastal Line Geometry and Tsunami Impact in Maumere, Flores, Indonesia

    Directory of Open Access Journals (Sweden)

    SARI BAHAGIARTI KUSUMAYUDHA

    2011-12-01

    Full Text Available Almost all of the Indonesian territories are high potential of geologic disaster, such as earthquake, tsunami, volcanic eruptions and landslides, because the country belongs to tectonically active areas of the world. There are three big lithosperic plates interacting one with one another and influencing the tectonic setting of Indonesia. The plates are Indo-Australia plate, Eurasia plate and Pacific plate. Indo-Australia plate moves relatively northward by about 9 cm/year, Eurasia plate creeps south eastward with approximately 7 cm/year speed, and Pacific plate moves to the west with around 11 cm/year velocity. In the meeting line of the plates, about 300 km to the south of Indonesian islands, there is the subduction zone that become places, where earthquake focuses are generated. Earthquakes from submarine source with more than 6.5 magnitude have the potential to generate tsunami. Areas situated along the south coast of Indonesia islands are vulnerable to tsunami, because directly facing the boundary lines between Eurasia plate and Indo-Australia plate. This study verified that there is positive correlation between coastal line geometry and the tsunami impact, based on fractal analysis. The case study is Maumere, Flores island, East Nusa Tenggara, Indonesia. Result of the study is expected to be used for predicting the tsunami impact intensiveness at other areas.

  10. The Smoothing Artifact of Spatially Constrained Canonical Correlation Analysis in Functional MRI

    Directory of Open Access Journals (Sweden)

    Dietmar Cordes

    2012-01-01

    Full Text Available A wide range of studies show the capacity of multivariate statistical methods for fMRI to improve mapping of brain activations in a noisy environment. An advanced method uses local canonical correlation analysis (CCA to encompass a group of neighboring voxels instead of looking at the single voxel time course. The value of a suitable test statistic is used as a measure of activation. It is customary to assign the value to the center voxel; however, this is a choice of convenience and without constraints introduces artifacts, especially in regions of strong localized activation. To compensate for these deficiencies, different spatial constraints in CCA have been introduced to enforce dominance of the center voxel. However, even if the dominance condition for the center voxel is satisfied, constrained CCA can still lead to a smoothing artifact, often called the “bleeding artifact of CCA”, in fMRI activation patterns. In this paper a new method is introduced to measure and correct for the smoothing artif