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Sample records for bivariate correlation analysis

  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. 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)

  3. 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

  4. 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)

  5. Dissecting the correlation structure of a bivariate phenotype ...

    Indian Academy of Sciences (India)

    Home; Journals; Journal of Genetics; Volume 84; Issue 2. Dissecting the correlation structure of a bivariate phenotype: common genes or shared environment? ... High correlations between two quantitative traits may be either due to common genetic factors or common environmental factors or a combination of both.

  6. Covariate analysis of bivariate survival data

    Energy Technology Data Exchange (ETDEWEB)

    Bennett, L.E.

    1992-01-01

    The methods developed are used to analyze the effects of covariates on bivariate survival data when censoring and ties are present. The proposed method provides models for bivariate survival data that include differential covariate effects and censored observations. The proposed models are based on an extension of the univariate Buckley-James estimators which replace censored data points by their expected values, conditional on the censoring time and the covariates. For the bivariate situation, it is necessary to determine the expectation of the failure times for one component conditional on the failure or censoring time of the other component. Two different methods have been developed to estimate these expectations. In the semiparametric approach these expectations are determined from a modification of Burke's estimate of the bivariate empirical survival function. In the parametric approach censored data points are also replaced by their conditional expected values where the expected values are determined from a specified parametric distribution. The model estimation will be based on the revised data set, comprised of uncensored components and expected values for the censored components. The variance-covariance matrix for the estimated covariate parameters has also been derived for both the semiparametric and parametric methods. Data from the Demographic and Health Survey was analyzed by these methods. The two outcome variables are post-partum amenorrhea and breastfeeding; education and parity were used as the covariates. Both the covariate parameter estimates and the variance-covariance estimates for the semiparametric and parametric models will be compared. In addition, a multivariate test statistic was used in the semiparametric model to examine contrasts. The significance of the statistic was determined from a bootstrap distribution of the test statistic.

  7. Multiresolution transmission of the correlation modes between bivariate time series based on complex network theory

    Science.gov (United States)

    Huang, Xuan; An, Haizhong; Gao, Xiangyun; Hao, Xiaoqing; Liu, Pengpeng

    2015-06-01

    This study introduces an approach to study the multiscale transmission characteristics of the correlation modes between bivariate time series. The correlation between the bivariate time series fluctuates over time. The transmission among the correlation modes exhibits a multiscale phenomenon, which provides richer information. To investigate the multiscale transmission of the correlation modes, this paper describes a hybrid model integrating wavelet analysis and complex network theory to decompose and reconstruct the original bivariate time series into sequences in a joint time-frequency domain and defined the correlation modes at each time-frequency domain. We chose the crude oil spot and futures prices as the sample data. The empirical results indicate that the main duration of volatility (32-64 days) for the strongly positive correlation between the crude oil spot price and the futures price provides more useful information for investors. Moreover, the weighted degree, weighted indegree and weighted outdegree of the correlation modes follow power-law distributions. The correlation fluctuation strengthens the extent of persistence over the long term, whereas persistence weakens over the short and medium term. The primary correlation modes dominating the transmission process and the major intermediary modes in the transmission process are clustered both in the short and long term.

  8. Bivariate Correlation Analysis of the Chemometric Profiles of Chinese Wild Salvia miltiorrhiza Based on UPLC-Qqq-MS and Antioxidant Activities

    Directory of Open Access Journals (Sweden)

    Xiaodan Zhang

    2018-02-01

    Full Text Available To better understand the mechanisms underlying the pharmacological actions of Salvia miltiorrhiza, correlation between the chemical profiles and in vitro antioxidant activities in 50 batches of wild S. miltiorrhiza samples was analyzed. Our ultra-performance liquid chromatography–tandem mass spectrometry analysis detected twelve phenolic acids and five tanshinones and obtained various chemical profiles from different origins. In a principal component analysis (PCA and cluster analysis, the tanshinones cryptotanshinone, tanshinone IIA and dihydrotanshinone I exhibited higher weights in PC1, whereas the phenolic acids danshensu, salvianolic acids A and B and lithospermic acid were highly loaded in PC2. All components could be optimized as markers of different locations and might be suitable for S. miltiorrhiza quality analyses. Additionally, the DPPH and ABTS assays used to comprehensively evaluate antioxidant activities indicated large variations, with mean DPPH and ABTS scavenging potencies of 32.24 and 23.39 μg/mL, respectively, among S. miltiorrhiza extract solutions. Notably, samples that exceeded the mean IC50 values had higher phenolic acid contents. A correlation analysis indicated a strong correlation between the antioxidant activities and phenolic acid contents. Caffeic acid, danshensu, rosmarinic acid, lithospermic acid and salvianolic acid B were major contributors to antioxidant activity. In conclusion, phenolic compounds were the predominant antioxidant components in the investigated plant species. These plants may be sources of potent natural antioxidants and beneficial chemopreventive agents.

  9. Joint association analysis of bivariate quantitative and qualitative traits.

    Science.gov (United States)

    Yuan, Mengdie; Diao, Guoqing

    2011-11-29

    Univariate genome-wide association analysis of quantitative and qualitative traits has been investigated extensively in the literature. In the presence of correlated phenotypes, it is more intuitive to analyze all phenotypes simultaneously. We describe an efficient likelihood-based approach for the joint association analysis of quantitative and qualitative traits in unrelated individuals. We assume a probit model for the qualitative trait, under which an unobserved latent variable and a prespecified threshold determine the value of the qualitative trait. To jointly model the quantitative and qualitative traits, we assume that the quantitative trait and the latent variable follow a bivariate normal distribution. The latent variable is allowed to be correlated with the quantitative phenotype. Simultaneous modeling of the quantitative and qualitative traits allows us to make more precise inference on the pleiotropic genetic effects. We derive likelihood ratio tests for the testing of genetic effects. An application to the Genetic Analysis Workshop 17 data is provided. The new method yields reasonable power and meaningful results for the joint association analysis of the quantitative trait Q1 and the qualitative trait disease status at SNPs with not too small MAF.

  10. Dissecting the correlation structure of a bivariate phenotype ...

    Indian Academy of Sciences (India)

    Unknown

    High correlations between two quantitative traits may be either due to common genetic factors or common environ- mental factors or a combination ... different trait parameters and quantitative trait distributions. An application of the method .... mean vectors have components α1, β1 or – α1 and, α2, β2 or – α2, for the two traits ...

  11. On the Construction of Bivariate Exponential Distributions with an Arbitrary Correlation Coefficient

    DEFF Research Database (Denmark)

    Bladt, Mogens; Nielsen, Bo Friis

    2010-01-01

    In this article we use the concept of multivariate phase-type distributions to define a class of bivariate exponential distributions. This class has the following three appealing properties. Firstly, we may construct a pair of exponentially distributed random variables with any feasible correlation...

  12. A simple approximation to the bivariate normal distribution with large correlation coefficient

    NARCIS (Netherlands)

    Albers, Willem/Wim; Kallenberg, W.C.M.

    1994-01-01

    The bivariate normal distribution function is approximated with emphasis on situations where the correlation coefficient is large. The high accuracy of the approximation is illustrated by numerical examples. Moreover, exact upper and lower bounds are presented as well as asymptotic results on the

  13. Meta-analysis of studies with bivariate binary outcomes: a marginal beta-binomial model approach.

    Science.gov (United States)

    Chen, Yong; Hong, Chuan; Ning, Yang; Su, Xiao

    2016-01-15

    When conducting a meta-analysis of studies with bivariate binary outcomes, challenges arise when the within-study correlation and between-study heterogeneity should be taken into account. In this paper, we propose a marginal beta-binomial model for the meta-analysis of studies with binary outcomes. This model is based on the composite likelihood approach and has several attractive features compared with the existing models such as bivariate generalized linear mixed model (Chu and Cole, 2006) and Sarmanov beta-binomial model (Chen et al., 2012). The advantages of the proposed marginal model include modeling the probabilities in the original scale, not requiring any transformation of probabilities or any link function, having closed-form expression of likelihood function, and no constraints on the correlation parameter. More importantly, because the marginal beta-binomial model is only based on the marginal distributions, it does not suffer from potential misspecification of the joint distribution of bivariate study-specific probabilities. Such misspecification is difficult to detect and can lead to biased inference using currents methods. We compare the performance of the marginal beta-binomial model with the bivariate generalized linear mixed model and the Sarmanov beta-binomial model by simulation studies. Interestingly, the results show that the marginal beta-binomial model performs better than the Sarmanov beta-binomial model, whether or not the true model is Sarmanov beta-binomial, and the marginal beta-binomial model is more robust than the bivariate generalized linear mixed model under model misspecifications. Two meta-analyses of diagnostic accuracy studies and a meta-analysis of case-control studies are conducted for illustration. Copyright © 2015 John Wiley & Sons, Ltd.

  14. Bivariate Drought Analysis Using Streamflow Reconstruction with Tree Ring Indices in the Sacramento Basin, California, USA

    Directory of Open Access Journals (Sweden)

    Jaewon Kwak

    2016-03-01

    Full Text Available Long-term streamflow data are vital for analysis of hydrological droughts. Using an artificial neural network (ANN model and nine tree-ring indices, this study reconstructed the annual streamflow of the Sacramento River for the period from 1560 to 1871. Using the reconstructed streamflow data, the copula method was used for bivariate drought analysis, deriving a hydrological drought return period plot for the Sacramento River basin. Results showed strong correlation among drought characteristics, and the drought with a 20-year return period (17.2 million acre-feet (MAF per year in the Sacramento River basin could be considered a critical level of drought for water shortages.

  15. Multiscale Fluctuation Features of the Dynamic Correlation between Bivariate Time Series

    Directory of Open Access Journals (Sweden)

    Meihui Jiang

    2016-01-01

    Full Text Available The fluctuation of the dynamic correlation between bivariate time series has some special features on the time-frequency domain. In order to study these fluctuation features, this paper built the dynamic correlation network models using two kinds of time series as sample data. After studying the dynamic correlation networks at different time-scales, we found that the correlation between time series is a dynamic process. The correlation is strong and stable in the long term, but it is weak and unstable in the short and medium term. There are key correlation modes which can effectively indicate the trend of the correlation. The transmission characteristics of correlation modes show that it is easier to judge the trend of the fluctuation of the correlation between time series from the short term to long term. The evolution of media capability of the correlation modes shows that the transmission media in the long term have higher value to predict the trend of correlation. This work does not only propose a new perspective to analyze the correlation between time series but also provide important information for investors and decision makers.

  16. On the construction of bivariate exponential distributions with an arbitrary correlation coefficient

    DEFF Research Database (Denmark)

    Bladt, Mogens; Nielsen, Bo Friis

    coefficient (also negative). Secondly, the class satisfies that any linear combination (projection) of the marginal random variables is a phase {type distributions, The latter property is potentially important for the development hypothesis testing in linear models. Thirdly, it is very easy to simulate......In this paper we use a concept of multivariate phase-type distributions to define a class of bivariate exponential distributions. This class has the following three appealing properties. Firstly, we may construct a pair of exponentially distributed random variables with any feasible correlation...

  17. Bivariate extreme value with application to PM10 concentration analysis

    Science.gov (United States)

    Amin, Nor Azrita Mohd; Adam, Mohd Bakri; Ibrahim, Noor Akma; Aris, Ahmad Zaharin

    2015-05-01

    This study is focus on a bivariate extreme of renormalized componentwise maxima with generalized extreme value distribution as a marginal function. The limiting joint distribution of several parametric models are presented. Maximum likelihood estimation is employed for parameter estimations and the best model is selected based on the Akaike Information Criterion. The weekly and monthly componentwise maxima series are extracted from the original observations of daily maxima PM10 data for two air quality monitoring stations located in Pasir Gudang and Johor Bahru. The 10 years data are considered for both stations from year 2001 to 2010. The asymmetric negative logistic model is found as the best fit bivariate extreme model for both weekly and monthly maxima componentwise series. However the dependence parameters show that the variables for weekly maxima series is more dependence to each other compared to the monthly maxima.

  18. Univariate and Bivariate Empirical Mode Decomposition for Postural Stability Analysis

    Directory of Open Access Journals (Sweden)

    Jacques Duchêne

    2008-05-01

    Full Text Available The aim of this paper was to compare empirical mode decomposition (EMD and two new extended methods of  EMD named complex empirical mode decomposition (complex-EMD and bivariate empirical mode decomposition (bivariate-EMD. All methods were used to analyze stabilogram center of pressure (COP time series. The two new methods are suitable to be applied to complex time series to extract complex intrinsic mode functions (IMFs before the Hilbert transform is subsequently applied on the IMFs. The trace of the analytic IMF in the complex plane has a circular form, with each IMF having its own rotation frequency. The area of the circle and the average rotation frequency of IMFs represent efficient indicators of the postural stability status of subjects. Experimental results show the effectiveness of these indicators to identify differences in standing posture between groups.

  19. Inheritance of dermatoglyphic traits in twins: univariate and bivariate variance decomposition analysis.

    Science.gov (United States)

    Karmakar, Bibha; Malkin, Ida; Kobyliansky, Eugene

    2012-01-01

    Dermatoglyphic traits in a sample of twins were analyzed to estimate the resemblance between MZ and DZ twins and to evaluate the mode of inheritance by using the maximum likelihood-based Variance decomposition analysis. The additive genetic variance component was significant in both sexes for four traits--PII, AB_RC, RC_HB, and ATD_L. AB RC and RC_HB had significant sex differences in means, whereas PII and ATD_L did not. The results of the Bivariate Variance decomposition analysis revealed that PII and RC_HB have a significant correlation in both genetic and residual components. Significant correlation in the additive genetic variance between AB_RC and ATD_L was observed. The same analysis only for the females sub-sample in the three traits RBL, RBR and AB_DIS shows that the additive genetic RBR component was significant and the AB_DIS sibling component was not significant while others cannot be constrained to zero. The additive variance for AB DIS sibling component was not significant. The three components additive, sibling and residual were significantly correlated between each pair of traits revealed by the Bivariate Variance decomposition analysis.

  20. A Bivariate Extension to Traditional Empirical Orthogonal Function Analysis

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg; Hilger, Klaus Baggesen; Andersen, Ole Baltazar

    2002-01-01

    This paper describes the application of canonical correlations analysis to the joint analysis of global monthly mean values of 1996-1997 sea surface temperature (SST) and height (SSH) data. The SST data are considered as one set and the SSH data as another set of multivariate observations, both w...... as for example an increase in the SST will lead to an increase in the SSH. The analysis clearly shows the build-up of one of the largest El Niño events on record. Also the analysis indicates a phase lag of approximately one month between the SST and SSH fields....

  1. Assessing the copula selection for bivariate frequency analysis ...

    Indian Academy of Sciences (India)

    58

    37 frequency analysis methods cannot describe the random variable properties that are correlated. 38. (Sarhadi et al., 2016). This approach can lead to high uncertainty or failure of guidelines in. 39 water resources planning, operation and design of hydraulic structures or creating the flood risk. 40 mapping (Chebana and ...

  2. Preparation and bivariate analysis of suspensions of human chromosomes

    Energy Technology Data Exchange (ETDEWEB)

    van den Engh, G.J.; Trask, B.J.; Gray, J.W.; Langlois, R.G.; Yu, L.C.

    1985-01-01

    Chromosomes were isolated from a variety of human cell types using a HEPES-buffered hypotonic solution (pH 8.0) containing KCl, MgSO/sub 4/ dithioerythritol, and RNase. The chromosomes isolated by this procedure could be stained with a variety of fluorescent stains including propidium iodide, chromomycin A3, and Hoeschst 33258. Addition of sodium citrate to the stained chromosomes was found to improve the total fluorescence resolution. High-quality bivariate Hoeschst vs. chromomycin fluorescence distributions were obtained for chromosomes isolated from a human fibroblast cell strain, a human colon carcinoma cell line, and human peripheral blood lymphocyte cultures. Good flow karyotypes were also obtained from primary amniotic cell cultures. The Hoeschst vs. chromomycin flow karyotypes of a given cell line, made at different times and at dye concentrations varying over fourfold ranges, show little variation in the relative peak positions of the chromosomes. The size of the DNA in chromosomes isolated using this procedure ranges from 20 to 50 kilobases. The described isolation procedure is simple, it yields high-quality flow karyotypes, and it can be used to prepare chromosomes from clinical samples. 22 references, 7 figures, 1 table.

  3. Historical and future drought in Bangladesh using copula-based bivariate regional frequency analysis

    Science.gov (United States)

    Mortuza, Md Rubayet; Moges, Edom; Demissie, Yonas; Li, Hong-Yi

    2018-02-01

    The study aims at regional and probabilistic evaluation of bivariate drought characteristics to assess both the past and future drought duration and severity in Bangladesh. The procedures involve applying (1) standardized precipitation index to identify drought duration and severity, (2) regional frequency analysis to determine the appropriate marginal distributions for both duration and severity, (3) copula model to estimate the joint probability distribution of drought duration and severity, and (4) precipitation projections from multiple climate models to assess future drought trends. Since drought duration and severity in Bangladesh are often strongly correlated and do not follow same marginal distributions, the joint and conditional return periods of droughts are characterized using the copula-based joint distribution. The country is divided into three homogeneous regions using Fuzzy clustering and multivariate discordancy and homogeneity measures. For given severity and duration values, the joint return periods for a drought to exceed both values are on average 45% larger, while to exceed either value are 40% less than the return periods from the univariate frequency analysis, which treats drought duration and severity independently. These suggest that compared to the bivariate drought frequency analysis, the standard univariate frequency analysis under/overestimate the frequency and severity of droughts depending on how their duration and severity are related. Overall, more frequent and severe droughts are observed in the west side of the country. Future drought trend based on four climate models and two scenarios showed the possibility of less frequent drought in the future (2020-2100) than in the past (1961-2010).

  4. Analysis of Blood Transfusion Data Using Bivariate Zero-Inflated Poisson Model: A Bayesian Approach.

    Science.gov (United States)

    Mohammadi, Tayeb; Kheiri, Soleiman; Sedehi, Morteza

    2016-01-01

    Recognizing the factors affecting the number of blood donation and blood deferral has a major impact on blood transfusion. There is a positive correlation between the variables "number of blood donation" and "number of blood deferral": as the number of return for donation increases, so does the number of blood deferral. On the other hand, due to the fact that many donors never return to donate, there is an extra zero frequency for both of the above-mentioned variables. In this study, in order to apply the correlation and to explain the frequency of the excessive zero, the bivariate zero-inflated Poisson regression model was used for joint modeling of the number of blood donation and number of blood deferral. The data was analyzed using the Bayesian approach applying noninformative priors at the presence and absence of covariates. Estimating the parameters of the model, that is, correlation, zero-inflation parameter, and regression coefficients, was done through MCMC simulation. Eventually double-Poisson model, bivariate Poisson model, and bivariate zero-inflated Poisson model were fitted on the data and were compared using the deviance information criteria (DIC). The results showed that the bivariate zero-inflated Poisson regression model fitted the data better than the other models.

  5. Bivariable analysis of ventricular late potentials in high resolution ECG records

    International Nuclear Information System (INIS)

    Orosco, L; Laciar, E

    2007-01-01

    In this study the bivariable analysis for ventricular late potentials detection in high-resolution electrocardiographic records is proposed. The standard time-domain analysis and the application of the time-frequency technique to high-resolution ECG records are briefly described as well as their corresponding results. In the proposed technique the time-domain parameter, QRSD and the most significant time-frequency index, EN QRS are used like variables. A bivariable index is defined, that combines the previous parameters. The propose technique allows evaluating the risk of ventricular tachycardia in post-myocardial infarct patients. The results show that the used bivariable index allows discriminating between the patient's population with ventricular tachycardia and the subjects of the control group. Also, it was found that the bivariable technique obtains a good valuation as diagnostic test. It is concluded that comparatively, the valuation of the bivariable technique as diagnostic test is superior to that of the time-domain method and the time-frequency technique evaluated individually

  6. Accuracy of body mass index in predicting pre-eclampsia: bivariate meta-analysis

    NARCIS (Netherlands)

    Cnossen, J. S.; Leeflang, M. M. G.; de Haan, E. E. M.; Mol, B. W. J.; van der Post, J. A. M.; Khan, K. S.; ter Riet, G.

    2007-01-01

    OBJECTIVE: The objective of this study was to determine the accuracy of body mass index (BMI) (pre-pregnancy or at booking) in predicting pre-eclampsia and to explore its potential for clinical application. DESIGN: Systematic review and bivariate meta-analysis. SETTING: Medline, Embase, Cochrane

  7. Meta-analysis for diagnostic accuracy studies: a new statistical model using beta-binomial distributions and bivariate copulas.

    Science.gov (United States)

    Kuss, Oliver; Hoyer, Annika; Solms, Alexander

    2014-01-15

    There are still challenges when meta-analyzing data from studies on diagnostic accuracy. This is mainly due to the bivariate nature of the response where information on sensitivity and specificity must be summarized while accounting for their correlation within a single trial. In this paper, we propose a new statistical model for the meta-analysis for diagnostic accuracy studies. This model uses beta-binomial distributions for the marginal numbers of true positives and true negatives and links these margins by a bivariate copula distribution. The new model comes with all the features of the current standard model, a bivariate logistic regression model with random effects, but has the additional advantages of a closed likelihood function and a larger flexibility for the correlation structure of sensitivity and specificity. In a simulation study, which compares three copula models and two implementations of the standard model, the Plackett and the Gauss copula do rarely perform worse but frequently better than the standard model. We use an example from a meta-analysis to judge the diagnostic accuracy of telomerase (a urinary tumor marker) for the diagnosis of primary bladder cancer for illustration. Copyright © 2013 John Wiley & Sons, Ltd.

  8. Bivariate flow cytometric analysis and sorting of different types of maize starch grains.

    Science.gov (United States)

    Zhang, Xudong; Feng, Jiaojiao; Wang, Heng; Zhu, Jianchu; Zhong, Yuyue; Liu, Linsan; Xu, Shutu; Zhang, Renhe; Zhang, Xinghua; Xue, Jiquan; Guo, Dongwei

    2018-02-01

    Particle-size distribution, granular structure, and composition significantly affect the physicochemical properties, rheological properties, and nutritional function of starch. Flow cytometry and flow sorting are widely considered convenient and efficient ways of classifying and separating natural biological particles or other substances into subpopulations, respectively, based on the differential response of each component to stimulation by a light beam; the results allow for the correlation analysis of parameters. In this study, different types of starches isolated from waxy maize, sweet maize, high-amylose maize, pop maize, and normal maize were initially classified into various subgroups by flow cytometer and then collected through flow sorting to observe their morphology and particle-size distribution. The results showed that a 0.25% Gelzan solution served as an optimal reagent for keeping individual starch particles homogeneously dispersed in suspension for a relatively long time. The bivariate flow cytometric population distributions indicated that the starches of normal maize, sweet maize, and pop maize were divided into two subgroups, whereas high-amylose maize starch had only one subgroup. Waxy maize starch, conversely, showed three subpopulations. The subgroups sorted by flow cytometer were determined and verified in terms of morphology and granule size by scanning electron microscopy and laser particle distribution analyzer. Results showed that flow cytometry can be regarded as a novel method for classifying and sorting starch granules. © 2017 International Society for Advancement of Cytometry. © 2017 International Society for Advancement of Cytometry.

  9. Effect of catchment properties and flood generation regime on copula selection for bivariate flood frequency analysis

    Science.gov (United States)

    Filipova, Valeriya; Lawrence, Deborah; Klempe, Harald

    2018-02-01

    Applying copula-based bivariate flood frequency analysis is advantageous because the results provide information on both the flood peak and volume. More data are, however, required for such an analysis, and it is often the case that only data series with a limited record length are available. To overcome this issue of limited record length, data regarding climatic and geomorphological properties can be used to complement statistical methods. In this paper, we present a study of 27 catchments located throughout Norway, in which we assess whether catchment properties, flood generation processes and flood regime have an effect on the correlation between flood peak and volume and, in turn, on the selection of copulas. To achieve this, the annual maximum flood events were first classified into events generated primarily by rainfall, snowmelt or a combination of these. The catchments were then classified into flood regime, depending on the predominant flood generation process producing the annual maximum flood events. A contingency table and Fisher's exact test were used to determine the factors that affect the selection of copulas in the study area. The results show that the two-parameter copulas BB1 and BB7 are more commonly selected in catchments with high steepness, high mean annual runoff and rainfall flood regime. These findings suggest that in these types of catchments, the dependence structure between flood peak and volume is more complex and cannot be modeled effectively using a one-parameter copula. The results illustrate that by relating copula types to flood regime and catchment properties, additional information can be supplied for selecting copulas in catchments with limited data.

  10. A comparison between multivariate and bivariate analysis used in marketing research

    Directory of Open Access Journals (Sweden)

    Constantin, C.

    2012-01-01

    Full Text Available This paper is about an instrumental research conducted in order to compare the information given by two multivariate data analysis in comparison with the usual bivariate analysis. The outcomes of the research reveal that sometimes the multivariate methods use more information from a certain variable, but sometimes they use only a part of the information considered the most important for certain associations. For this reason, a researcher should use both categories of data analysis in order to obtain entirely useful information.

  11. Genetic determinant of trabecular bone score (TBS) and bone mineral density: A bivariate analysis.

    Science.gov (United States)

    Ho-Pham, Lan T; Hans, Didier; Doan, Minh C; Mai, Linh D; Nguyen, Tuan V

    2016-11-01

    This study sought to estimate the extent of genetic influence on the variation in trabecular bone score (TBS). We found that genetic factors accounted for ~45% of variance in TBS, and that the co-variation between TBS and bone density is partially determined by genetic factors. Trabecular bone score has emerged as an important predictor of fragility fracture, but factors underlying the individual differences in TBS have not been explored. In this study, we sought to determine the genetic contribution to the variation of TBS in the general population. The study included 556 women and 189 men from 265 families. The individuals aged 53years (SD 11). We measured lumbar spine bone mineral density (BMD; Hologic Horizon) and then derived the TBS from the same Hologic scan where BMD was derived. A biometric model was applied to the data to partition the variance of TBS into two components: one due to additive genetic factors, and one due to environmental factors. The index of heritability was estimated as the ratio of genetic variance to total variance of a trait. Bivariate genetic analysis was conducted to estimate the genetic correlation between TBS and BMD measurements. TBS was strongly correlated with lumbar spine BMD (r=0.73; P<0.001). On average TBS in men was higher than women, after adjusting age and height which are significantly associated with both TBS and lumbar spine BMD. The age and height adjusted index of heritability of TBS was 0.46 (95% CI, 0.39-0.54), which was not much different from that of LSBMD (0.44; 95% CI, 0.31-0.55). Moreover, the genetic correlation between TBS and LSBMD was 0.35 (95% CI, 0.21-0.46), between TBS and femoral neck BMD was 0.21 (95% CI, 0.10-0.33). Approximately 45% of the variance in TBS is under genetic influence, and this effect magnitude is similar to that of lumbar spine BMD. This finding provides a scientific justification for the search for specific genetic variants that may be associated with TBS and fracture risk

  12. Bivariate spatial analysis of temperature and precipitation from general circulation models and observation proxies

    KAUST Repository

    Philbin, R.

    2015-05-22

    This study validates the near-surface temperature and precipitation output from decadal runs of eight atmospheric ocean general circulation models (AOGCMs) against observational proxy data from the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis temperatures and Global Precipitation Climatology Project (GPCP) precipitation data. We model the joint distribution of these two fields with a parsimonious bivariate Matérn spatial covariance model, accounting for the two fields\\' spatial cross-correlation as well as their own smoothnesses. We fit output from each AOGCM (30-year seasonal averages from 1981 to 2010) to a statistical model on each of 21 land regions. Both variance and smoothness values agree for both fields over all latitude bands except southern mid-latitudes. Our results imply that temperature fields have smaller smoothness coefficients than precipitation fields, while both have decreasing smoothness coefficients with increasing latitude. Models predict fields with smaller smoothness coefficients than observational proxy data for the tropics. The estimated spatial cross-correlations of these two fields, however, are quite different for most GCMs in mid-latitudes. Model correlation estimates agree well with those for observational proxy data for Australia, at high northern latitudes across North America, Europe and Asia, as well as across the Sahara, India, and Southeast Asia, but elsewhere, little consistent agreement exists.

  13. Obtaining DDF Curves of Extreme Rainfall Data Using Bivariate Copula and Frequency Analysis

    DEFF Research Database (Denmark)

    Sadri, Sara; Madsen, Henrik; Mikkelsen, Peter Steen

    2009-01-01

    , situated near Copenhagen in Denmark. For rainfall extracted using method 2, the marginal distribution of depth was found to fit the Generalized Pareto distribution while duration was found to fit the Gamma distribution, using the method of L-moments. The volume was fit with a generalized Pareto...... with duration for a given return period and name them DDF (depth-duration-frequency) curves. The copula approach does not assume the rainfall variables are independent or jointly normally distributed. Rainfall series are extracted in three ways: (1) by maximum mean intensity; (2) by depth and duration...... distribution and the duration was fit with a Pearson type III distribution for rainfall extracted using method 3. The Clayton copula was found to be appropriate for bivariate analysis of rainfall depth and duration for both methods 2 and 3. DDF curves derived using the Clayton copula for depth and duration...

  14. A composite likelihood method for bivariate meta-analysis in diagnostic systematic reviews.

    Science.gov (United States)

    Chen, Yong; Liu, Yulun; Ning, Jing; Nie, Lei; Zhu, Hongjian; Chu, Haitao

    2017-04-01

    Diagnostic systematic review is a vital step in the evaluation of diagnostic technologies. In many applications, it involves pooling pairs of sensitivity and specificity of a dichotomized diagnostic test from multiple studies. We propose a composite likelihood (CL) method for bivariate meta-analysis in diagnostic systematic reviews. This method provides an alternative way to make inference on diagnostic measures such as sensitivity, specificity, likelihood ratios, and diagnostic odds ratio. Its main advantages over the standard likelihood method are the avoidance of the nonconvergence problem, which is nontrivial when the number of studies is relatively small, the computational simplicity, and some robustness to model misspecifications. Simulation studies show that the CL method maintains high relative efficiency compared to that of the standard likelihood method. We illustrate our method in a diagnostic review of the performance of contemporary diagnostic imaging technologies for detecting metastases in patients with melanoma.

  15. The Role of Wealth and Health in Insurance Choice: Bivariate Probit Analysis in China

    Directory of Open Access Journals (Sweden)

    Yiding Yue

    2014-01-01

    Full Text Available This paper captures the correlation between the choices of health insurance and pension insurance using the bivariate probit model and then studies the effect of wealth and health on insurance choice. Our empirical evidence shows that people who participate in a health care program are more likely to participate in a pension plan at the same time, while wealth and health have different effects on the choices of the health care program and the pension program. Generally, the higher an individual’s wealth level is, the more likelihood he will participate in a health care program; but wealth has no effect on the participation of pension. Health status has opposite effects on choices of health care programs and pension plans; the poorer an individual’s health is, the more likely he is to participate in health care programs, while the better health he enjoys, the more likely he is to participate in pension plans. When the investigation scope narrows down to commercial insurance, there is only a significant effect of health status on commercial health insurance. The commercial insurance choice and the insurance choice of the agricultural population are more complicated.

  16. Bivariate frequency analysis of rainfall intensity and duration for urban stormwater infrastructure design

    Science.gov (United States)

    Jun, Changhyun; Qin, Xiaosheng; Gan, Thian Yew; Tung, Yeou-Koung; De Michele, Carlo

    2017-10-01

    This study presents a storm-event based bivariate frequency analysis approach to determine design rainfalls in which, the number, intensity and duration of actual rainstorm events were considered. To derive more realistic design storms, the occurrence probability of an individual rainstorm event was determined from the joint distribution of storm intensity and duration through a copula model. Hourly rainfall data were used at three climate stations respectively located in Singapore, South Korea and Canada. It was found that the proposed approach could give a more realistic description of rainfall characteristics of rainstorm events and design rainfalls. As results, the design rainfall quantities from actual rainstorm events at the three studied sites are consistently lower than those obtained from the conventional rainfall depth-duration-frequency (DDF) method, especially for short-duration storms (such as 1-h). It results from occurrence probabilities of each rainstorm event and a different angle for rainfall frequency analysis, and could offer an alternative way of describing extreme rainfall properties and potentially help improve the hydrologic design of stormwater management facilities in urban areas.

  17. GIS-based bivariate statistical techniques for groundwater potential analysis (an example of Iran)

    Science.gov (United States)

    Haghizadeh, Ali; Moghaddam, Davoud Davoudi; Pourghasemi, Hamid Reza

    2017-12-01

    Groundwater potential analysis prepares better comprehension of hydrological settings of different regions. This study shows the potency of two GIS-based data driven bivariate techniques namely statistical index (SI) and Dempster-Shafer theory (DST) to analyze groundwater potential in Broujerd region of Iran. The research was done using 11 groundwater conditioning factors and 496 spring positions. Based on the ground water potential maps (GPMs) of SI and DST methods, 24.22% and 23.74% of the study area is covered by poor zone of groundwater potential, and 43.93% and 36.3% of Broujerd region is covered by good and very good potential zones, respectively. The validation of outcomes displayed that area under the curve (AUC) of SI and DST techniques are 81.23% and 79.41%, respectively, which shows SI method has slightly a better performance than the DST technique. Therefore, SI and DST methods are advantageous to analyze groundwater capacity and scrutinize the complicated relation between groundwater occurrence and groundwater conditioning factors, which permits investigation of both systemic and stochastic uncertainty. Finally, it can be realized that these techniques are very beneficial for groundwater potential analyzing and can be practical for water-resource management experts.

  18. Bayesian bivariate meta-analysis of diagnostic test studies using integrated nested Laplace approximations.

    Science.gov (United States)

    Paul, M; Riebler, A; Bachmann, L M; Rue, H; Held, L

    2010-05-30

    For bivariate meta-analysis of diagnostic studies, likelihood approaches are very popular. However, they often run into numerical problems with possible non-convergence. In addition, the construction of confidence intervals is controversial. Bayesian methods based on Markov chain Monte Carlo (MCMC) sampling could be used, but are often difficult to implement, and require long running times and diagnostic convergence checks. Recently, a new Bayesian deterministic inference approach for latent Gaussian models using integrated nested Laplace approximations (INLA) has been proposed. With this approach MCMC sampling becomes redundant as the posterior marginal distributions are directly and accurately approximated. By means of a real data set we investigate the influence of the prior information provided and compare the results obtained by INLA, MCMC, and the maximum likelihood procedure SAS PROC NLMIXED. Using a simulation study we further extend the comparison of INLA and SAS PROC NLMIXED by assessing their performance in terms of bias, mean-squared error, coverage probability, and convergence rate. The results indicate that INLA is more stable and gives generally better coverage probabilities for the pooled estimates and less biased estimates of variance parameters. The user-friendliness of INLA is demonstrated by documented R-code. Copyright (c) 2010 John Wiley & Sons, Ltd.

  19. Bivariate analysis of sensitivity and specificity produces informative summary measures in diagnostic reviews

    NARCIS (Netherlands)

    Reitsma, Johannes B.; Glas, Afina S.; Rutjes, Anne W. S.; Scholten, Rob J. P. M.; Bossuyt, Patrick M.; Zwinderman, Aeilko H.

    2005-01-01

    Background and Objectives: Studies of diagnostic accuracy most often report pairs of sensitivity and specificity. We demonstrate the advantage of using bivariate meta-regression models to analyze such data. Methods: We discuss the methodology of both the summary Receiver Operating Characteristic

  20. Global assessment of predictability of water availability: A bivariate probabilistic Budyko analysis

    Science.gov (United States)

    Wang, Weiguang; Fu, Jianyu

    2018-02-01

    Estimating continental water availability is of great importance for water resources management, in terms of maintaining ecosystem integrity and sustaining society development. To more accurately quantify the predictability of water availability, on the basis of univariate probabilistic Budyko framework, a bivariate probabilistic Budyko approach was developed using copula-based joint distribution model for considering the dependence between parameter ω of Wang-Tang's equation and the Normalized Difference Vegetation Index (NDVI), and was applied globally. The results indicate the predictive performance in global water availability is conditional on the climatic condition. In comparison with simple univariate distribution, the bivariate one produces the lower interquartile range under the same global dataset, especially in the regions with higher NDVI values, highlighting the importance of developing the joint distribution by taking into account the dependence structure of parameter ω and NDVI, which can provide more accurate probabilistic evaluation of water availability.

  1. Bivariate Random Effects Meta-analysis of Diagnostic Studies Using Generalized Linear Mixed Models

    Science.gov (United States)

    GUO, HONGFEI; ZHOU, YIJIE

    2011-01-01

    Bivariate random effect models are currently one of the main methods recommended to synthesize diagnostic test accuracy studies. However, only the logit-transformation on sensitivity and specificity has been previously considered in the literature. In this paper, we consider a bivariate generalized linear mixed model to jointly model the sensitivities and specificities, and discuss the estimation of the summary receiver operating characteristic curve (ROC) and the area under the ROC curve (AUC). As the special cases of this model, we discuss the commonly used logit, probit and complementary log-log transformations. To evaluate the impact of misspecification of the link functions on the estimation, we present two case studies and a set of simulation studies. Our study suggests that point estimation of the median sensitivity and specificity, and AUC is relatively robust to the misspecification of the link functions. However, the misspecification of link functions has a noticeable impact on the standard error estimation and the 95% confidence interval coverage, which emphasizes the importance of choosing an appropriate link function to make statistical inference. PMID:19959794

  2. Ordinal Bivariate Inequality

    DEFF Research Database (Denmark)

    Sonne-Schmidt, Christoffer Scavenius; Tarp, Finn; Østerdal, Lars Peter Raahave

    2016-01-01

    This paper introduces a concept of inequality comparisons with ordinal bivariate categorical data. In our model, one population is more unequal than another when they have common arithmetic median outcomes and the first can be obtained from the second by correlation-increasing switches and....../or median-preserving spreads. For the canonical 2 × 2 case (with two binary indicators), we derive a simple operational procedure for checking ordinal inequality relations in practice. As an illustration, we apply the model to childhood deprivation in Mozambique....

  3. Diagnostic performance of des-γ-carboxy prothrombin (DCP) for hepatocellular carcinoma: a bivariate meta-analysis.

    Science.gov (United States)

    Gao, P; Li, M; Tian, Q B; Liu, Dian-Wu

    2012-01-01

    Serum markers are needed to be developed to specifically diagnose Hepatocellular carcinoma (HCC). Des-γ-carboxy prothrombin (DCP) is a promising tool with limited expense and widely accessibility, but the reported results have been controversial. In order to review the performance of DCP for the diagnosis of HCC, the meta-analysis was performed. After a systematic review of relevant studies, the sensitivity, specificity, positive and negative likelihood ratios (PLR and NLR, respectively) were pooled using a bivariate meta-analysis. Potential between-study heterogeneity was explored by meta-regression model. The post-test probability and the likelihood ratio scattergram to evaluate clinical usefulness were calculated. Based on literature review of 20 publications, the overall sensitivity, specificity, PLR and NLR of DCP for the detection of HCC were 67% (95%CI, 58%-74%), 92% (95%CI, 88%-94%), 7.9 (95%CI, 5.6-11.2) and 0.36 (95%CI, 0.29-0.46), respectively. The area under the bivariate summary receiving operating characteristics curve was 0.89 (95%CI, 0.85-0.92). Significant heterogeneity was present. In conclusion, the major role of DCP is the moderate confirmation of HCC. More prospective studies of DCP are needed in future.

  4. Bivariate analysis of basal serum anti-Mullerian hormone measurements and human blastocyst development after IVF

    LENUS (Irish Health Repository)

    Sills, E Scott

    2011-12-02

    Abstract Background To report on relationships among baseline serum anti-Müllerian hormone (AMH) measurements, blastocyst development and other selected embryology parameters observed in non-donor oocyte IVF cycles. Methods Pre-treatment AMH was measured in patients undergoing IVF (n = 79) and retrospectively correlated to in vitro embryo development noted during culture. Results Mean (+\\/- SD) age for study patients in this study group was 36.3 ± 4.0 (range = 28-45) yrs, and mean (+\\/- SD) terminal serum estradiol during IVF was 5929 +\\/- 4056 pmol\\/l. A moderate positive correlation (0.49; 95% CI 0.31 to 0.65) was noted between basal serum AMH and number of MII oocytes retrieved. Similarly, a moderate positive correlation (0.44) was observed between serum AMH and number of early cleavage-stage embryos (95% CI 0.24 to 0.61), suggesting a relationship between serum AMH and embryo development in IVF. Of note, serum AMH levels at baseline were significantly different for patients who did and did not undergo blastocyst transfer (15.6 vs. 10.9 pmol\\/l; p = 0.029). Conclusions While serum AMH has found increasing application as a predictor of ovarian reserve for patients prior to IVF, its roles to estimate in vitro embryo morphology and potential to advance to blastocyst stage have not been extensively investigated. These data suggest that baseline serum AMH determinations can help forecast blastocyst developmental during IVF. Serum AMH measured before treatment may assist patients, clinicians and embryologists as scheduling of embryo transfer is outlined. Additional studies are needed to confirm these correlations and to better define the role of baseline serum AMH level in the prediction of blastocyst formation.

  5. Bivariate genome-wide association meta-analysis of pediatric musculoskeletal traits reveals pleiotropic effects at the SREBF1/TOM1L2 locus

    DEFF Research Database (Denmark)

    Medina-Gomez, Carolina; Kemp, John P; Dimou, Niki L

    2017-01-01

    Bone mineral density is known to be a heritable, polygenic trait whereas genetic variants contributing to lean mass variation remain largely unknown. We estimated the shared SNP heritability and performed a bivariate GWAS meta-analysis of total-body lean mass (TB-LM) and total-body less head bone...

  6. Bivariate genome-wide association meta-analysis of pediatric musculoskeletal traits reveals pleiotropic effects at the SREBF1/TOM1L2 locus

    NARCIS (Netherlands)

    M.C. Medina-Gomez (Carolina); J.P. Kemp (John); Dimou, N.L. (Niki L.); Kreiner, E. (Eskil); A. Chesi (Alessandra); B.S. Zemel (Babette S.); K. Bønnelykke (Klaus); Boer, C.G. (Cindy G.); T.S. Ahluwalia (Tarunveer Singh); H. Bisgaard; E. Evangelou (Evangelos); D.H.M. Heppe (Denise); Bonewald, L.F. (Lynda F.); Gorski, J.P. (Jeffrey P.); M. Ghanbari (Mohsen); S. Demissie (Serkalem); Duque, G. (Gustavo); M.T. Maurano (Matthew T.); D.P. Kiel (Douglas P.); Y.-H. Hsu (Yi-Hsiang); B.C.J. van der Eerden (Bram); Ackert-Bicknell, C. (Cheryl); S. Reppe (Sjur); K.M. Gautvik (Kaare); Raastad, T. (Truls); D. Karasik (David); J. van de Peppel (Jeroen); V.W.V. Jaddoe (Vincent); A.G. Uitterlinden (André); J.H. Tobias (Jon); S.F.A. Grant (Struan); Bagos, P.G. (Pantelis G.); D.M. Evans (David); F. Rivadeneira Ramirez (Fernando)

    2017-01-01

    markdownabstractBone mineral density is known to be a heritable, polygenic trait whereas genetic variants contributing to lean mass variation remain largely unknown. We estimated the shared SNP heritability and performed a bivariate GWAS meta-analysis of total-body lean mass (TB-LM) and total-body

  7. Quasi-bivariate variational mode decomposition as a tool of scale analysis in wall-bounded turbulence

    Science.gov (United States)

    Wang, Wenkang; Pan, Chong; Wang, Jinjun

    2018-01-01

    The identification and separation of multi-scale coherent structures is a critical task for the study of scale interaction in wall-bounded turbulence. Here, we propose a quasi-bivariate variational mode decomposition (QB-VMD) method to extract structures with various scales from instantaneous two-dimensional (2D) velocity field which has only one primary dimension. This method is developed from the one-dimensional VMD algorithm proposed by Dragomiretskiy and Zosso (IEEE Trans Signal Process 62:531-544, 2014) to cope with a quasi-2D scenario. It poses the feature of length-scale bandwidth constraint along the decomposed dimension, together with the central frequency re-balancing along the non-decomposed dimension. The feasibility of this method is tested on both a synthetic flow field and a turbulent boundary layer at moderate Reynolds number (Re_{τ } = 3458) measured by 2D particle image velocimetry (PIV). Some other popular scale separation tools, including pseudo-bi-dimensional empirical mode decomposition (PB-EMD), bi-dimensional EMD (B-EMD) and proper orthogonal decomposition (POD), are also tested for comparison. Among all these methods, QB-VMD shows advantages in both scale characterization and energy recovery. More importantly, the mode mixing problem, which degrades the performance of EMD-based methods, is avoided or minimized in QB-VMD. Finally, QB-VMD analysis of the wall-parallel plane in the log layer (at y/δ = 0.12) of the studied turbulent boundary layer shows the coexistence of large- or very large-scale motions (LSMs or VLSMs) and inner-scaled structures, which can be fully decomposed in both physical and spectral domains.

  8. Bivariate Kumaraswamy Models via Modified FGM Copulas: Properties and Applications

    Directory of Open Access Journals (Sweden)

    Indranil Ghosh

    2017-11-01

    Full Text Available A copula is a useful tool for constructing bivariate and/or multivariate distributions. In this article, we consider a new modified class of FGM (Farlie–Gumbel–Morgenstern bivariate copula for constructing several different bivariate Kumaraswamy type copulas and discuss their structural properties, including dependence structures. It is established that construction of bivariate distributions by this method allows for greater flexibility in the values of Spearman’s correlation coefficient, ρ and Kendall’s τ .

  9. Bivariate genome-wide association meta-analysis of pediatric musculoskeletal traits reveals pleiotropic effects at the SREBF1/TOM1L2 locus.

    Science.gov (United States)

    Medina-Gomez, Carolina; Kemp, John P; Dimou, Niki L; Kreiner, Eskil; Chesi, Alessandra; Zemel, Babette S; Bønnelykke, Klaus; Boer, Cindy G; Ahluwalia, Tarunveer S; Bisgaard, Hans; Evangelou, Evangelos; Heppe, Denise H M; Bonewald, Lynda F; Gorski, Jeffrey P; Ghanbari, Mohsen; Demissie, Serkalem; Duque, Gustavo; Maurano, Matthew T; Kiel, Douglas P; Hsu, Yi-Hsiang; C J van der Eerden, Bram; Ackert-Bicknell, Cheryl; Reppe, Sjur; Gautvik, Kaare M; Raastad, Truls; Karasik, David; van de Peppel, Jeroen; Jaddoe, Vincent W V; Uitterlinden, André G; Tobias, Jonathan H; Grant, Struan F A; Bagos, Pantelis G; Evans, David M; Rivadeneira, Fernando

    2017-07-25

    Bone mineral density is known to be a heritable, polygenic trait whereas genetic variants contributing to lean mass variation remain largely unknown. We estimated the shared SNP heritability and performed a bivariate GWAS meta-analysis of total-body lean mass (TB-LM) and total-body less head bone mineral density (TBLH-BMD) regions in 10,414 children. The estimated SNP heritability is 43% (95% CI: 34-52%) for TBLH-BMD, and 39% (95% CI: 30-48%) for TB-LM, with a shared genetic component of 43% (95% CI: 29-56%). We identify variants with pleiotropic effects in eight loci, including seven established bone mineral density loci: WNT4, GALNT3, MEPE, CPED1/WNT16, TNFSF11, RIN3, and PPP6R3/LRP5. Variants in the TOM1L2/SREBF1 locus exert opposing effects TB-LM and TBLH-BMD, and have a stronger association with the former trait. We show that SREBF1 is expressed in murine and human osteoblasts, as well as in human muscle tissue. This is the first bivariate GWAS meta-analysis to demonstrate genetic factors with pleiotropic effects on bone mineral density and lean mass.Bone mineral density and lean skeletal mass are heritable traits. Here, Medina-Gomez and colleagues perform bivariate GWAS analyses of total body lean mass and bone mass density in children, and show genetic loci with pleiotropic effects on both traits.

  10. Bivariate genome-wide association meta-analysis of pediatric musculoskeletal traits reveals pleiotropic effects at the SREBF1/TOM1L2 locus

    DEFF Research Database (Denmark)

    Medina-Gomez, Carolina; Kemp, John P; Dimou, Niki L

    2017-01-01

    Bone mineral density is known to be a heritable, polygenic trait whereas genetic variants contributing to lean mass variation remain largely unknown. We estimated the shared SNP heritability and performed a bivariate GWAS meta-analysis of total-body lean mass (TB-LM) and total-body less head bone...... mineral density (TBLH-BMD) regions in 10,414 children. The estimated SNP heritability is 43% (95% CI: 34-52%) for TBLH-BMD, and 39% (95% CI: 30-48%) for TB-LM, with a shared genetic component of 43% (95% CI: 29-56%). We identify variants with pleiotropic effects in eight loci, including seven established...... as in human muscle tissue. This is the first bivariate GWAS meta-analysis to demonstrate genetic factors with pleiotropic effects on bone mineral density and lean mass.Bone mineral density and lean skeletal mass are heritable traits. Here, Medina-Gomez and colleagues perform bivariate GWAS analyses of total...

  11. Ordinal bivariate inequality

    DEFF Research Database (Denmark)

    Sonne-Schmidt, Christoffer Scavenius; Tarp, Finn; Østerdal, Lars Peter Raahave

    This paper introduces a concept of inequality comparisons with ordinal bivariate categorical data. In our model, one population is more unequal than another when they have common arithmetic median outcomes and the first can be obtained from the second by correlationincreasing switches and/or median......-preserving spreads. For the canonical 2x2 case (with two binary indicators), we derive a simple operational procedure for checking ordinal inequality relations in practice. As an illustration, we apply the model to childhood deprivation in Mozambique....

  12. Effectiveness of enforcement levels of speed limit and drink driving laws and associated factors – Exploratory empirical analysis using a bivariate ordered probit model

    Directory of Open Access Journals (Sweden)

    Behram Wali

    2017-06-01

    Full Text Available The contemporary traffic safety research comprises little information on quantifying the simultaneous association between drink driving and speeding among fatally injured drivers. Potential correlation between driver's drink driving and speeding behavior poses a substantial methodological concern which needs investigation. This study therefore focused on investigating the simultaneous impact of socioeconomic factors, fatalities, vehicle ownership, health services and highway agency road safety policies on enforcement levels of speed limit and drink driving laws. The effectiveness of enforcement levels of speed limit and drink driving laws has been investigated through development of bivariate ordered probit model using data extricated from WHO's global status report on road safety in 2013. The consistent and intuitive parameter estimates along with statistically significant correlation between response outcomes validates the statistical supremacy of bivariate ordered probit model. The results revealed that fatalities per thousand registered vehicles, hospital beds per hundred thousand population and road safety policies are associated with a likely medium or high effectiveness of enforcement levels of speed limit and drink driving laws, respectively. Also, the model encapsulates the effect of several other agency related variables and socio-economic status on the response outcomes. Marginal effects are reported for analyzing the impact of such factors on intermediate categories of response outcomes. The results of this study are expected to provide necessary insights to elemental enforcement programs. Also, marginal effects of explanatory variables may provide useful directions for formulating effective policy countermeasures for overcoming driver's speeding and drink driving behavior.

  13. 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

  14. 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.

  15. Monitoring bivariate process

    Directory of Open Access Journals (Sweden)

    Marcela A. G. Machado

    2009-12-01

    Full Text Available The T² chart and the generalized variance |S| chart are the usual tools for monitoring the mean vector and the covariance matrix of multivariate processes. The main drawback of these charts is the difficulty to obtain and to interpret the values of their monitoring statistics. In this paper, we study control charts for monitoring bivariate processes that only requires the computation of sample means (the ZMAX chart for monitoring the mean vector, sample variances (the VMAX chart for monitoring the covariance matrix, or both sample means and sample variances (the MCMAX chart in the case of the joint control of the mean vector and the covariance matrix.Os gráficos de T² e da variância amostral generalizada |S| são as ferramentas usualmente utilizadas no monitoramento do vetor de médias e da matriz de covariâncias de processos multivariados. A principal desvantagem desses gráficos é a dificuldade em obter e interpretar os valores de suas estatísticas de monitoramento. Neste artigo, estudam-se gráficos de controle para o monitoramento de processos bivariados que necessitam somente do cálculo de médias amostrais (gráfico ZMAX para o monitoramento do vetor de médias, ou das variâncias amostrais (gráfico VMAX para o monitoramento da matriz de covariâncias, ou então das médias e variâncias amostrais (gráfico MCMAX para o caso do monitoramento conjunto do vetor de médias e da matriz de covariâncias.

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

    OpenAIRE

    Ali Gohary; Kambiz Heidarzadeh Hanzaee

    2014-01-01

    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 consci...

  17. Diagnostic value of sTREM-1 in bronchoalveolar lavage fluid in ICU patients with bacterial lung infections: a bivariate meta-analysis.

    Science.gov (United States)

    Shi, Jia-Xin; Li, Jia-Shu; Hu, Rong; Li, Chun-Hua; Wen, Yan; Zheng, Hong; Zhang, Feng; Li, Qin

    2013-01-01

    The serum soluble triggering receptor expressed on myeloid cells-1 (sTREM-1) is a useful biomarker in differentiating bacterial infections from others. However, the diagnostic value of sTREM-1 in bronchoalveolar lavage fluid (BALF) in lung infections has not been well established. We performed a meta-analysis to assess the accuracy of sTREM-1 in BALF for diagnosis of bacterial lung infections in intensive care unit (ICU) patients. We searched PUBMED, EMBASE and Web of Knowledge (from January 1966 to October 2012) databases for relevant studies that reported diagnostic accuracy data of BALF sTREM-1 in the diagnosis of bacterial lung infections in ICU patients. Pooled sensitivity, specificity, and positive and negative likelihood ratios were calculated by a bivariate regression analysis. Measures of accuracy and Q point value (Q*) were calculated using summary receiver operating characteristic (SROC) curve. The potential between-studies heterogeneity was explored by subgroup analysis. Nine studies were included in the present meta-analysis. Overall, the prevalence was 50.6%; the sensitivity was 0.87 (95% confidence interval (CI), 0.72-0.95); the specificity was 0.79 (95% CI, 0.56-0.92); the positive likelihood ratio (PLR) was 4.18 (95% CI, 1.78-9.86); the negative likelihood ratio (NLR) was 0.16 (95% CI, 0.07-0.36), and the diagnostic odds ratio (DOR) was 25.60 (95% CI, 7.28-89.93). The area under the SROC curve was 0.91 (95% CI, 0.88-0.93), with a Q* of 0.83. Subgroup analysis showed that the assay method and cutoff value influenced the diagnostic accuracy of sTREM-1. BALF sTREM-1 is a useful biomarker of bacterial lung infections in ICU patients. Further studies are needed to confirm the optimized cutoff value.

  18. Association of Supply Type with Fecal Contamination of Source Water and Household Stored Drinking Water in Developing Countries: A Bivariate Meta-analysis.

    Science.gov (United States)

    Shields, Katherine F; Bain, Robert E S; Cronk, Ryan; Wright, Jim A; Bartram, Jamie

    2015-12-01

    Access to safe drinking water is essential for health. Monitoring access to drinking water focuses on water supply type at the source, but there is limited evidence on whether quality differences at the source persist in water stored in the household. We assessed the extent of fecal contamination at the source and in household stored water (HSW) and explored the relationship between contamination at each sampling point and water supply type. We performed a bivariate random-effects meta-analysis of 45 studies, identified through a systematic review, that reported either the proportion of samples free of fecal indicator bacteria and/or individual sample bacteria counts for source and HSW, disaggregated by supply type. Water quality deteriorated substantially between source and stored water. The mean percentage of contaminated samples (noncompliance) at the source was 46% (95% CI: 33, 60%), whereas mean noncompliance in HSW was 75% (95% CI: 64, 84%). Water supply type was significantly associated with noncompliance at the source (p water (OR = 0.2; 95% CI: 0.1, 0.5) and HSW (OR = 0.3; 95% CI: 0.2, 0.8) from piped supplies had significantly lower odds of contamination compared with non-piped water, potentially due to residual chlorine. Piped water is less likely to be contaminated compared with other water supply types at both the source and in HSW. A focus on upgrading water services to piped supplies may help improve safety, including for those drinking stored water.

  19. Landslide susceptibility analysis in central Vietnam based on an incomplete landslide inventory: Comparison of a new method to calculate weighting factors by means of bivariate statistics

    Science.gov (United States)

    Meinhardt, Markus; Fink, Manfred; Tünschel, Hannes

    2015-04-01

    Vietnam is regarded as a country strongly impacted by climate change. Population and economic growth result in additional pressures on the ecosystems in the region. In particular, changes in landuse and precipitation extremes lead to a higher landslide susceptibility in the study area (approx. 12,400 km2), located in central Vietnam and impacted by a tropical monsoon climate. Hence, this natural hazard is a serious problem in the study area. A probability assessment of landslides is therefore undertaken through the use of bivariate statistics. However, the landslide inventory based only on field campaigns does not cover the whole area. To avoid a systematic bias due to the limited mapping area, the investigated regions are depicted as the viewshed in the calculations. On this basis, the distribution of the landslides is evaluated in relation to the maps of 13 parameters, showing the strongest correlation to distance to roads and precipitation increase. An additional weighting of the input parameters leads to better results, since some parameters contribute more to landslides than others. The method developed in this work is based on the validation of different parameter sets used within the statistical index method. It is called "omit error" because always omitting another parameter leads to the weightings, which describe how strong every single parameter improves or reduces the objective function. Furthermore, this approach is used to find a better input parameter set by excluding some parameters. After this optimization, nine input parameters are left, and they are weighted by the omit error method, providing the best susceptibility map with a success rate of 92.9% and a prediction rate of 92.3%. This is an improvement of 4.4% and 4.2%, respectively, compared to the basic statistical index method with the 13 input parameters.

  20. A comparison of bivariate and univariate QTL mapping in livestock populations

    Directory of Open Access Journals (Sweden)

    Sorensen Daniel

    2003-11-01

    Full Text Available Abstract This study presents a multivariate, variance component-based QTL mapping model implemented via restricted maximum likelihood (REML. The method was applied to investigate bivariate and univariate QTL mapping analyses, using simulated data. Specifically, we report results on the statistical power to detect a QTL and on the precision of parameter estimates using univariate and bivariate approaches. The model and methodology were also applied to study the effectiveness of partitioning the overall genetic correlation between two traits into a component due to many genes of small effect, and one due to the QTL. It is shown that when the QTL has a pleiotropic effect on two traits, a bivariate analysis leads to a higher statistical power of detecting the QTL and to a more precise estimate of the QTL's map position, in particular in the case when the QTL has a small effect on the trait. The increase in power is most marked in cases where the contributions of the QTL and of the polygenic components to the genetic correlation have opposite signs. The bivariate REML analysis can successfully partition the two components contributing to the genetic correlation between traits.

  1. Regularized Generalized Canonical Correlation Analysis

    Science.gov (United States)

    Tenenhaus, Arthur; Tenenhaus, Michel

    2011-01-01

    Regularized generalized canonical correlation analysis (RGCCA) is a generalization of regularized canonical correlation analysis to three or more sets of variables. It constitutes a general framework for many multi-block data analysis methods. It combines the power of multi-block data analysis methods (maximization of well identified criteria) and…

  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. Association of Supply Type with Fecal Contamination of Source Water and Household Stored Drinking Water in Developing Countries: A Bivariate Meta-analysis

    OpenAIRE

    Shields, Katherine F.; Bain, Robert E.S.; Cronk, Ryan; Wright, Jim A.; Bartram, Jamie

    2015-01-01

    Background Access to safe drinking water is essential for health. Monitoring access to drinking water focuses on water supply type at the source, but there is limited evidence on whether quality differences at the source persist in water stored in the household. Objectives We assessed the extent of fecal contamination at the source and in household stored water (HSW) and explored the relationship between contamination at each sampling point and water supply type. Methods We performed a bivari...

  4. Bivariate value-at-risk

    Directory of Open Access Journals (Sweden)

    Giuseppe Arbia

    2007-10-01

    Full Text Available In this paper we extend the concept of Value-at-risk (VaR to bivariate return distributions in order to obtain measures of the market risk of an asset taking into account additional features linked to downside risk exposure. We first present a general definition of risk as the probability of an adverse event over a random distribution and we then introduce a measure of market risk (b-VaR that admits the traditional b of an asset in portfolio management as a special case when asset returns are normally distributed. Empirical evidences are provided by using Italian stock market data.

  5. Comparison between two bivariate Poisson distributions through the ...

    African Journals Online (AJOL)

    To remedy this problem, Berkhout and Plug proposed a bivariate Poisson distribution accepting the correlation as well negative, equal to zero, that positive. In this paper, we show that these models are nearly everywhere asymptotically equal. From this survey that the ø-divergence converges toward zero, both models are ...

  6. Accuracy of serum uric acid as a predictive test for maternal complications in pre-eclampsia: Bivariate meta-analysis and decision analysis

    NARCIS (Netherlands)

    Koopmans, Corine M.; van Pampus, Maria G.; Groen, Henk; Aarnoudse, Jan G.; van den Berg, Paul P.; Mol, Ben W. J.

    2009-01-01

    The aim of this study is to determine the accuracy and clinical value of serum uric acid in predicting maternal complications in women with pre-eclampsia. An existing meta-analysis on the subject was updated. The accuracy of serum uric acid for the prediction of maternal complications was assessed

  7. Accuracy of serum uric acid as a predictive test for maternal complications in pre-eclampsia : Bivariate meta-analysis and decision analysis

    NARCIS (Netherlands)

    Koopmans, C.M.; van Pampus, Maria; Groen, H.; Aarnoudse, J.G.; van den Berg, P.P.; Mol, B.W.J.

    The aim of this study is to determine the accuracy and clinical value of serum uric acid in predicting maternal complications in women with pre-eclampsia. An existing meta-analysis on the subject was updated. The accuracy of serum uric acid for the prediction of maternal complications was assessed

  8. Flash flood susceptibility analysis and its mapping using different bivariate models in Iran: a comparison between Shannon's entropy, statistical index, and weighting factor models.

    Science.gov (United States)

    Khosravi, Khabat; Pourghasemi, Hamid Reza; Chapi, Kamran; Bahri, Masoumeh

    2016-12-01

    Flooding is a very common worldwide natural hazard causing large-scale casualties every year; Iran is not immune to this thread as well. Comprehensive flood susceptibility mapping is very important to reduce losses of lives and properties. Thus, the aim of this study is to map susceptibility to flooding by different bivariate statistical methods including Shannon's entropy (SE), statistical index (SI), and weighting factor (Wf). In this regard, model performance evaluation is also carried out in Haraz Watershed, Mazandaran Province, Iran. In the first step, 211 flood locations were identified by the documentary sources and field inventories, of which 70% (151 positions) were used for flood susceptibility modeling and 30% (60 positions) for evaluation and verification of the model. In the second step, ten influential factors in flooding were chosen, namely slope angle, plan curvature, altitude, topographic wetness index (TWI), stream power index (SPI), distance from river, rainfall, geology, land use, and normalized difference vegetation index (NDVI). In the next step, flood susceptibility maps were prepared by these four methods in ArcGIS. As the last step, receiver operating characteristic (ROC) curve was drawn and the area under the curve (AUC) was calculated for quantitative assessment of each model. The results showed that the best model to estimate the susceptibility to flooding in Haraz Watershed was SI model with the prediction and success rates of 99.71 and 98.72%, respectively, followed by Wf and SE models with the AUC values of 98.1 and 96.57% for the success rate, and 97.6 and 92.42% for the prediction rate, respectively. In the SI and Wf models, the highest and lowest important parameters were the distance from river and geology. Flood susceptibility maps are informative for managers and decision makers in Haraz Watershed in order to contemplate measures to reduce human and financial losses.

  9. GIS-based bivariate statistical techniques for groundwater potential ...

    Indian Academy of Sciences (India)

    Groundwater potential analysis prepares better comprehension of hydrological settings of different regions. This study shows the potency of two GIS-based data driven bivariate techniques namely statistical index (SI) and Dempster–Shafer theory (DST) to analyze groundwater potential in Broujerd region of Iran.

  10. Bivariate hard thresholding in wavelet function estimation

    OpenAIRE

    Piotr Fryzlewicz

    2007-01-01

    We propose a generic bivariate hard thresholding estimator of the discrete wavelet coefficients of a function contaminated with i.i.d. Gaussian noise. We demonstrate its good risk properties in a motivating example, and derive upper bounds for its mean-square error. Motivated by the clustering of large wavelet coefficients in real-life signals, we propose two wavelet denoising algorithms, both of which use specific instances of our bivariate estimator. The BABTE algorithm uses basis averaging...

  11. Multifractal detrending moving-average cross-correlation analysis.

    Science.gov (United States)

    Jiang, Zhi-Qiang; Zhou, Wei-Xing

    2011-07-01

    There are a number of situations in which several signals are simultaneously recorded in complex systems, which exhibit long-term power-law cross correlations. The multifractal detrended cross-correlation analysis (MFDCCA) approaches can be used to quantify such cross correlations, such as the MFDCCA based on the detrended fluctuation analysis (MFXDFA) method. We develop in this work a class of MFDCCA algorithms based on the detrending moving-average analysis, called MFXDMA. The performances of the proposed MFXDMA algorithms are compared with the MFXDFA method by extensive numerical experiments on pairs of time series generated from bivariate fractional Brownian motions, two-component autoregressive fractionally integrated moving-average processes, and binomial measures, which have theoretical expressions of the multifractal nature. In all cases, the scaling exponents h(xy) extracted from the MFXDMA and MFXDFA algorithms are very close to the theoretical values. For bivariate fractional Brownian motions, the scaling exponent of the cross correlation is independent of the cross-correlation coefficient between two time series, and the MFXDFA and centered MFXDMA algorithms have comparative performances, which outperform the forward and backward MFXDMA algorithms. For two-component autoregressive fractionally integrated moving-average processes, we also find that the MFXDFA and centered MFXDMA algorithms have comparative performances, while the forward and backward MFXDMA algorithms perform slightly worse. For binomial measures, the forward MFXDMA algorithm exhibits the best performance, the centered MFXDMA algorithms performs worst, and the backward MFXDMA algorithm outperforms the MFXDFA algorithm when the moment order q0. We apply these algorithms to the return time series of two stock market indexes and to their volatilities. For the returns, the centered MFXDMA algorithm gives the best estimates of h(xy)(q) since its h(xy)(2) is closest to 0.5, as expected, and

  12. Spectrum-based estimators of the bivariate Hurst exponent

    Czech Academy of Sciences Publication Activity Database

    Krištoufek, Ladislav

    2014-01-01

    Roč. 90, č. 6 (2014), art. 062802 ISSN 1539-3755 R&D Projects: GA ČR(CZ) GP14-11402P Institutional support: RVO:67985556 Keywords : bivariate Hurst exponent * power- law cross-correlations * estimation Subject RIV: AH - Economics Impact factor: 2.288, year: 2014 http://library.utia.cas.cz/separaty/2014/E/kristoufek-0436818.pdf

  13. 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

  14. Influence of Four Radiotracers in PET/CT on Diagnostic Accuracy for Prostate Cancer: A Bivariate Random-Effects Meta-Analysis

    Directory of Open Access Journals (Sweden)

    Junzhong Liu

    2016-07-01

    Full Text Available Background/Aims: To date, several positron emission tomography/computed tomography (PET/CT radiotracers including fluorine-18 fluorodeoxyglucose (18F-FDG, carbon-11 labeled choline (11C-choline, 18-F fluorocholine (18F-FCH and carbon-11 acetate (11C-acetate have already been assessed in the application of prostate cancer (PCa diagnosis to some extent, the diagnostic efficiency of these radiotracers still remain controversial. As a result of this, we carried out this meta-analysis for the purpose of comparing the diagnostic accuracy among four PET/CT radiotracers. Methods: A systematical literature search for articles was performed until July 3, 2015. We implemented all analysis using the statistical software of STATA12 and quality assessment was performed using QUADAS-2. Results: A total of 56 studies containing 3,586 patients were included in this meta-analysis. Parameter estimates of the overall analysis are as follows: sensitivity, 0.80 (95% CI: 0.74-0.85; specificity, 0.84 (95% CI: 0.77-0.89 and area under roc curve-AUC of SROC, 0.89 (95% CI: 0.86-0.91, indicating a relatively high level of accuracy in diagnosis of PCa. When different radiotracers of PET/CT were compared, 18F-FCH-PET/CT was ranked as the most favorable with the highest value of AUC (AUC = 0.94; 95% CI: 0.92-0.96 whereas 18F-FDG was the least favorable (AUC = 0.73, 95% CI: 0.69-0.77. Conclusion: This study suggested that PET/CT imaging plays an invaluable role in the diagnosis of PCa and 18F-FCH-PET/CT was considered as a superior diagnostic tool over other radiotracers. More attention should be paid to the diagnostic efficiency of the four radiotracers particularly for PCa patients with different clinical stages.

  15. Influence of Four Radiotracers in PET/CT on Diagnostic Accuracy for Prostate Cancer: A Bivariate Random-Effects Meta-Analysis.

    Science.gov (United States)

    Liu, Junzhong; Chen, Zhongfeng; Wang, Tianyu; Liu, Li; Zhao, Lei; Guo, Guangtao; Wang, Dongqing

    2016-01-01

    To date, several positron emission tomography/computed tomography (PET/CT) radiotracers including fluorine-18 fluorodeoxyglucose (18F-FDG), carbon-11 labeled choline (11C-choline), 18-F fluorocholine (18F-FCH) and carbon-11 acetate (11C-acetate) have already been assessed in the application of prostate cancer (PCa) diagnosis to some extent, the diagnostic efficiency of these radiotracers still remain controversial. As a result of this, we carried out this meta-analysis for the purpose of comparing the diagnostic accuracy among four PET/CT radiotracers. A systematical literature search for articles was performed until July 3, 2015. We implemented all analysis using the statistical software of STATA12 and quality assessment was performed using QUADAS-2. A total of 56 studies containing 3,586 patients were included in this meta-analysis. Parameter estimates of the overall analysis are as follows: sensitivity, 0.80 (95% CI: 0.74-0.85); specificity, 0.84 (95% CI: 0.77-0.89) and area under roc curve-AUC of SROC, 0.89 (95% CI: 0.86-0.91), indicating a relatively high level of accuracy in diagnosis of PCa. When different radiotracers of PET/CT were compared, 18F-FCH-PET/CT was ranked as the most favorable with the highest value of AUC (AUC = 0.94; 95% CI: 0.92-0.96) whereas 18F-FDG was the least favorable (AUC = 0.73, 95% CI: 0.69-0.77). This study suggested that PET/CT imaging plays an invaluable role in the diagnosis of PCa and 18F-FCH-PET/CT was considered as a superior diagnostic tool over other radiotracers. More attention should be paid to the diagnostic efficiency of the four radiotracers particularly for PCa patients with different clinical stages. © 2016 The Author(s) Published by S. Karger AG, Basel.

  16. Bivariate analysis of the genetic variability among some accessions of African Yam Bean (Sphenostylis stenocarpa (Hochst ex A. RichHarms

    Directory of Open Access Journals (Sweden)

    Solomon Tayo AKINYOSOYE

    2017-12-01

    Full Text Available Variability is an important factor to consider in crop improvement programmes. This study was conducted in two years to assess genetic variability and determine relationship between seed yield, its components and tuber production characters among twelve accessions of African yam bean. Data collected were subjected to combined analysis of variance (ANOVA, Principal Component Analysis (PCA, hierarchical and K-means clustering analyses. Results obtained revealed that genotype by year (G × Y interaction had significant effects on some of variables measured (days to first flowering, days to 50 % flowering, number of pod per plant, pod length, seed yield and tuber yield per plant in this study.The first five principal components (PC with Eigen values greater than 1.0 accounted for about 66.70 % of the total variation, where PC1 and PC 2 accounted for 39.48 % of variation and were associated with seed and tuber yield variables. Three heterotic groups were clearly delineated among genotypes with accessions AY03 and AY10 identified for high seed yield and tuber yield respectively. Non-significant relationship that existed between tuber and seed yield per plant of these accessions was recommended for further test in various agro-ecologies for their suitability, adaptability and possible exploitation of heterosis to further improve the accessions.

  17. Correlative feature analysis on FFDM

    International Nuclear Information System (INIS)

    Yuan Yading; Giger, Maryellen L.; Li Hui; Sennett, Charlene

    2008-01-01

    Identifying the corresponding images of a lesion in different views is an essential step in improving the diagnostic ability of both radiologists and computer-aided diagnosis (CAD) systems. Because of the nonrigidity of the breasts and the 2D projective property of mammograms, this task is not trivial. In this pilot study, we present a computerized framework that differentiates between corresponding images of the same lesion in different views and noncorresponding images, i.e., images of different lesions. A dual-stage segmentation method, which employs an initial radial gradient index (RGI) based segmentation and an active contour model, is applied to extract mass lesions from the surrounding parenchyma. Then various lesion features are automatically extracted from each of the two views of each lesion to quantify the characteristics of density, size, texture and the neighborhood of the lesion, as well as its distance to the nipple. A two-step scheme is employed to estimate the probability that the two lesion images from different mammographic views are of the same physical lesion. In the first step, a correspondence metric for each pairwise feature is estimated by a Bayesian artificial neural network (BANN). Then, these pairwise correspondence metrics are combined using another BANN to yield an overall probability of correspondence. Receiver operating characteristic (ROC) analysis was used to evaluate the performance of the individual features and the selected feature subset in the task of distinguishing corresponding pairs from noncorresponding pairs. Using a FFDM database with 123 corresponding image pairs and 82 noncorresponding pairs, the distance feature yielded an area under the ROC curve (AUC) of 0.81±0.02 with leave-one-out (by physical lesion) evaluation, and the feature metric subset, which included distance, gradient texture, and ROI-based correlation, yielded an AUC of 0.87±0.02. The improvement by using multiple feature metrics was statistically

  18. A Vehicle for Bivariate Data Analysis

    Science.gov (United States)

    Roscoe, Matt B.

    2016-01-01

    Instead of reserving the study of probability and statistics for special fourth-year high school courses, the Common Core State Standards for Mathematics (CCSSM) takes a "statistics for all" approach. The standards recommend that students in grades 6-8 learn to summarize and describe data distributions, understand probability, draw…

  19. Probability distributions with truncated, log and bivariate extensions

    CERN Document Server

    Thomopoulos, Nick T

    2018-01-01

    This volume presents a concise and practical overview of statistical methods and tables not readily available in other publications. It begins with a review of the commonly used continuous and discrete probability distributions. Several useful distributions that are not so common and less understood are described with examples and applications in full detail: discrete normal, left-partial, right-partial, left-truncated normal, right-truncated normal, lognormal, bivariate normal, and bivariate lognormal. Table values are provided with examples that enable researchers to easily apply the distributions to real applications and sample data. The left- and right-truncated normal distributions offer a wide variety of shapes in contrast to the symmetrically shaped normal distribution, and a newly developed spread ratio enables analysts to determine which of the three distributions best fits a particular set of sample data. The book will be highly useful to anyone who does statistical and probability analysis. This in...

  20. Reliability for some bivariate beta distributions

    Directory of Open Access Journals (Sweden)

    Nadarajah Saralees

    2005-01-01

    Full Text Available In the area of stress-strength models there has been a large amount of work as regards estimation of the reliability R=Pr( Xbivariate distribution with dependence between X and Y . In particular, we derive explicit expressions for R when the joint distribution is bivariate beta. The calculations involve the use of special functions.

  1. Reliability for some bivariate gamma distributions

    Directory of Open Access Journals (Sweden)

    Nadarajah Saralees

    2005-01-01

    Full Text Available In the area of stress-strength models, there has been a large amount of work as regards estimation of the reliability R=Pr( Xbivariate distribution with dependence between X and Y . In particular, we derive explicit expressions for R when the joint distribution is bivariate gamma. The calculations involve the use of special functions.

  2. Financial Applications of Bivariate Markov Processes

    OpenAIRE

    Ortobelli Lozza, Sergio; Angelelli, Enrico; Bianchi, Annamaria

    2011-01-01

    This paper describes a methodology to approximate a bivariate Markov process by means of a proper Markov chain and presents possible financial applications in portfolio theory, option pricing and risk management. In particular, we first show how to model the joint distribution between market stochastic bounds and future wealth and propose an application to large-scale portfolio problems. Secondly, we examine an application to VaR estimation. Finally, we propose a methodology...

  3. A new method for correlation analysis of compositional (environmental) data - a worked example.

    Science.gov (United States)

    Reimann, C; Filzmoser, P; Hron, K; Kynčlová, P; Garrett, R G

    2017-12-31

    Most data in environmental sciences and geochemistry are compositional. Already the unit used to report the data (e.g., μg/l, mg/kg, wt%) implies that the analytical results for each element are not free to vary independently of the other measured variables. This is often neglected in statistical analysis, where a simple log-transformation of the single variables is insufficient to put the data into an acceptable geometry. This is also important for bivariate data analysis and for correlation analysis, for which the data need to be appropriately log-ratio transformed. A new approach based on the isometric log-ratio (ilr) transformation, leading to so-called symmetric coordinates, is presented here. Summarizing the correlations in a heat-map gives a powerful tool for bivariate data analysis. Here an application of the new method using a data set from a regional geochemical mapping project based on soil O and C horizon samples is demonstrated. Differences to 'classical' correlation analysis based on log-transformed data are highlighted. The fact that some expected strong positive correlations appear and remain unchanged even following a log-ratio transformation has probably led to the misconception that the special nature of compositional data can be ignored when working with trace elements. The example dataset is employed to demonstrate that using 'classical' correlation analysis and plotting XY diagrams, scatterplots, based on the original or simply log-transformed data can easily lead to severe misinterpretations of the relationships between elements. Copyright © 2017 Elsevier B.V. All rights reserved.

  4. Bivariate functional data clustering: grouping streams based on a varying coefficient model of the stream water and air temperature relationship

    Science.gov (United States)

    H. Li; X. Deng; Andy Dolloff; E. P. Smith

    2015-01-01

    A novel clustering method for bivariate functional data is proposed to group streams based on their water–air temperature relationship. A distance measure is developed for bivariate curves by using a time-varying coefficient model and a weighting scheme. This distance is also adjusted by spatial correlation of streams via the variogram. Therefore, the proposed...

  5. Spectral density regression for bivariate extremes

    KAUST Repository

    Castro Camilo, Daniela

    2016-05-11

    We introduce a density regression model for the spectral density of a bivariate extreme value distribution, that allows us to assess how extremal dependence can change over a covariate. Inference is performed through a double kernel estimator, which can be seen as an extension of the Nadaraya–Watson estimator where the usual scalar responses are replaced by mean constrained densities on the unit interval. Numerical experiments with the methods illustrate their resilience in a variety of contexts of practical interest. An extreme temperature dataset is used to illustrate our methods. © 2016 Springer-Verlag Berlin Heidelberg

  6. 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.

  7. Multiple imputation methods for bivariate outcomes in cluster randomised trials.

    Science.gov (United States)

    DiazOrdaz, K; Kenward, M G; Gomes, M; Grieve, R

    2016-09-10

    Missing observations are common in cluster randomised trials. The problem is exacerbated when modelling bivariate outcomes jointly, as the proportion of complete cases is often considerably smaller than the proportion having either of the outcomes fully observed. Approaches taken to handling such missing data include the following: complete case analysis, single-level multiple imputation that ignores the clustering, multiple imputation with a fixed effect for each cluster and multilevel multiple imputation. We contrasted the alternative approaches to handling missing data in a cost-effectiveness analysis that uses data from a cluster randomised trial to evaluate an exercise intervention for care home residents. We then conducted a simulation study to assess the performance of these approaches on bivariate continuous outcomes, in terms of confidence interval coverage and empirical bias in the estimated treatment effects. Missing-at-random clustered data scenarios were simulated following a full-factorial design. Across all the missing data mechanisms considered, the multiple imputation methods provided estimators with negligible bias, while complete case analysis resulted in biased treatment effect estimates in scenarios where the randomised treatment arm was associated with missingness. Confidence interval coverage was generally in excess of nominal levels (up to 99.8%) following fixed-effects multiple imputation and too low following single-level multiple imputation. Multilevel multiple imputation led to coverage levels of approximately 95% throughout. © 2016 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd. © 2016 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

  8. Solving Bivariate Polynomial Systems on a GPU

    International Nuclear Information System (INIS)

    Moreno Maza, Marc; Pan Wei

    2012-01-01

    We present a CUDA implementation of dense multivariate polynomial arithmetic based on Fast Fourier Transforms over finite fields. Our core routine computes on the device (GPU) the subresultant chain of two polynomials with respect to a given variable. This subresultant chain is encoded by values on a FFT grid and is manipulated from the host (CPU) in higher-level procedures. We have realized a bivariate polynomial system solver supported by our GPU code. Our experimental results (including detailed profiling information and benchmarks against a serial polynomial system solver implementing the same algorithm) demonstrate that our strategy is well suited for GPU implementation and provides large speedup factors with respect to pure CPU code.

  9. Bivariate Rayleigh Distribution and its Properties

    Directory of Open Access Journals (Sweden)

    Ahmad Saeed Akhter

    2007-01-01

    Full Text Available Rayleigh (1880 observed that the sea waves follow no law because of the complexities of the sea, but it has been seen that the probability distributions of wave heights, wave length, wave induce pitch, wave and heave motions of the ships follow the Rayleigh distribution. At present, several different quantities are in use for describing the state of the sea; for example, the mean height of the waves, the root mean square height, the height of the “significant waves” (the mean height of the highest one-third of all the waves the maximum height over a given interval of the time, and so on. At present, the ship building industry knows less than any other construction industry about the service conditions under which it must operate. Only small efforts have been made to establish the stresses and motions and to incorporate the result of such studies in to design. This is due to the complexity of the problem caused by the extensive variability of the sea and the corresponding response of the ships. Although the problem appears feasible, yet it is possible to predict service conditions for ships in an orderly and relatively simple manner Rayleigh (1980 derived it from the amplitude of sound resulting from many independent sources. This distribution is also connected with one or two dimensions and is sometimes referred to as “random walk” frequency distribution. The Rayleigh distribution can be derived from the bivariate normal distribution when the variate are independent and random with equal variances. We try to construct bivariate Rayleigh distribution with marginal Rayleigh distribution function and discuss its fundamental properties.

  10. Dissecting the correlation structure of a bivariate phenotype ...

    Indian Academy of Sciences (India)

    Unknown

    We use Monte-Carlo simulations to evaluate the performance of the proposed test under different trait parameters and quantitative trait distributions. An application of the method is illustrated using data on two alcohol-related phenotypes from a project on the collaborative study on the genetics of alcoholism. [Ghosh S 2005 ...

  11. 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,

  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. 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.

  14. A bivariate model for analyzing recurrent multi-type automobile failures

    Science.gov (United States)

    Sunethra, A. A.; Sooriyarachchi, M. R.

    2017-09-01

    The failure mechanism in an automobile can be defined as a system of multi-type recurrent failures where failures can occur due to various multi-type failure modes and these failures are repetitive such that more than one failure can occur from each failure mode. In analysing such automobile failures, both the time and type of the failure serve as response variables. However, these two response variables are highly correlated with each other since the timing of failures has an association with the mode of the failure. When there are more than one correlated response variables, the fitting of a multivariate model is more preferable than separate univariate models. Therefore, a bivariate model of time and type of failure becomes appealing for such automobile failure data. When there are multiple failure observations pertaining to a single automobile, such data cannot be treated as independent data because failure instances of a single automobile are correlated with each other while failures among different automobiles can be treated as independent. Therefore, this study proposes a bivariate model consisting time and type of failure as responses adjusted for correlated data. The proposed model was formulated following the approaches of shared parameter models and random effects models for joining the responses and for representing the correlated data respectively. The proposed model is applied to a sample of automobile failures with three types of failure modes and up to five failure recurrences. The parametric distributions that were suitable for the two responses of time to failure and type of failure were Weibull distribution and multinomial distribution respectively. The proposed bivariate model was programmed in SAS Procedure Proc NLMIXED by user programming appropriate likelihood functions. The performance of the bivariate model was compared with separate univariate models fitted for the two responses and it was identified that better performance is secured by

  15. Stress-strength reliability for general bivariate distributions

    Directory of Open Access Journals (Sweden)

    Alaa H. Abdel-Hamid

    2016-10-01

    Full Text Available An expression for the stress-strength reliability R=P(X1bivariate distribution. Such distribution includes bivariate compound Weibull, bivariate compound Gompertz, bivariate compound Pareto, among others. In the parametric case, the maximum likelihood estimates of the parameters and reliability function R are obtained. In the non-parametric case, point and interval estimates of R are developed using Govindarajulu's asymptotic distribution-free method when X1 and X2 are dependent. An example is given when the population distribution is bivariate compound Weibull. Simulation is performed, based on different sample sizes to study the performance of estimates.

  16. 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.

  17. Can the bivariate Hurst exponent be higher than an average of the separate Hurst exponents?

    Czech Academy of Sciences Publication Activity Database

    Krištoufek, Ladislav

    2015-01-01

    Roč. 431, č. 1 (2015), s. 124-127 ISSN 0378-4371 R&D Projects: GA ČR(CZ) GP14-11402P Institutional support: RVO:67985556 Keywords : Correlations * Power- law cross-correlations * Bivariate Hurst exponent * Spectrum coherence Subject RIV: AH - Economics Impact factor: 1.785, year: 2015 http://library.utia.cas.cz/separaty/2015/E/kristoufek-0452314.pdf

  18. Face hallucination using orthogonal canonical correlation analysis

    Science.gov (United States)

    Zhou, Huiling; Lam, Kin-Man

    2016-05-01

    A two-step face-hallucination framework is proposed to reconstruct a high-resolution (HR) version of a face from an input low-resolution (LR) face, based on learning from LR-HR example face pairs using orthogonal canonical correlation analysis (orthogonal CCA) and linear mapping. In the proposed algorithm, face images are first represented using principal component analysis (PCA). Canonical correlation analysis (CCA) with the orthogonality property is then employed, to maximize the correlation between the PCA coefficients of the LR and the HR face pairs to improve the hallucination performance. The original CCA does not own the orthogonality property, which is crucial for information reconstruction. We propose using orthogonal CCA, which is proven by experiments to achieve a better performance in terms of global face reconstruction. In addition, in the residual-compensation process, a linear-mapping method is proposed to include both the inter- and intrainformation about manifolds of different resolutions. Compared with other state-of-the-art approaches, the proposed framework can achieve a comparable, or even better, performance in terms of global face reconstruction and the visual quality of face hallucination. Experiments on images with various parameter settings and blurring distortions show that the proposed approach is robust and has great potential for real-world applications.

  19. STUDI PERBANDINGAN ANTARA ALGORITMA BIVARIATE MARGINAL DISTRIBUTION DENGAN ALGORITMA GENETIKA

    Directory of Open Access Journals (Sweden)

    Chastine Fatichah

    2006-01-01

    Full Text Available Bivariate Marginal Distribution Algorithm is extended from Estimation of Distribution Algorithm. This heuristic algorithm proposes the new approach for recombination of generate new individual that without crossover and mutation process such as genetic algorithm. Bivariate Marginal Distribution Algorithm uses connectivity variable the pair gene for recombination of generate new individual. Connectivity between variable is doing along optimization process. In this research, genetic algorithm performance with one point crossover is compared with Bivariate Marginal Distribution Algorithm performance in case Onemax, De Jong F2 function, and Traveling Salesman Problem. In this research, experimental results have shown performance the both algorithm is dependence of parameter respectively and also population size that used. For Onemax case with size small problem, Genetic Algorithm perform better with small number of iteration and more fast for get optimum result. However, Bivariate Marginal Distribution Algorithm perform better of result optimization for case Onemax with huge size problem. For De Jong F2 function, Genetic Algorithm perform better from Bivariate Marginal Distribution Algorithm of a number of iteration and time. For case Traveling Salesman Problem, Bivariate Marginal Distribution Algorithm have shown perform better from Genetic Algorithm of optimization result. Abstract in Bahasa Indonesia : Bivariate Marginal Distribution Algorithm merupakan perkembangan lebih lanjut dari Estimation of Distribution Algorithm. Algoritma heuristik ini mengenalkan pendekatan baru dalam melakukan rekombinasi untuk membentuk individu baru, yaitu tidak menggunakan proses crossover dan mutasi seperti pada Genetic Algorithm. Bivariate Marginal Distribution Algorithm menggunakan keterkaitan pasangan variabel dalam melakukan rekombinasi untuk membentuk individu baru. Keterkaitan antar variabel tersebut ditemukan selama proses optimasi berlangsung. Aplikasi yang

  20. 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.

  1. 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.

  2. CORRELATION ANALYSIS OF VEHICLE FRONTAL IMPACT PARAMETERS

    Directory of Open Access Journals (Sweden)

    Josef Mík

    2017-12-01

    Full Text Available The article considers a possible improvement of road vehicle safety by using eCall – a system which initiates an emergency call in case of traffic accident. A possible way of better description of a frontal impact accident of a vehicle is examined and enriched by the information from the onboard e-call unit. In this article, we analyze results of frontal crash tests with different types of barriers and overlapping area and look for the correlation between the individual vehicle and collision parameters in order to provide a better description of the severity of the accident by the eCall system. The relation among the selected parameters is described using the correlation analysis.

  3. Metrics correlation and analysis service (MCAS)

    Energy Technology Data Exchange (ETDEWEB)

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

    2009-05-01

    The complexity of Grid workflow activities and their associated software stacks inevitably involves multiple organizations, ownership, and deployment domains. In this setting, important and common tasks such as the correlation and display of metrics and debugging information (fundamental ingredients of troubleshooting) are challenged by the informational entropy inherent to independently maintained and operated software components. Because such an information 'pond' is disorganized, it a difficult environment for business intelligence analysis i.e. troubleshooting, incident investigation and trend spotting. The mission of the MCAS project is to deliver a software solution to help with adaptation, retrieval, correlation, and display of workflow-driven data and of type-agnostic events, generated by disjoint middleware.

  4. 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.

  5. 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.

  6. 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.

  7. Approximation of bivariate copulas by patched bivariate Fréchet copulas

    KAUST Repository

    Zheng, Yanting

    2011-03-01

    Bivariate Fréchet (BF) copulas characterize dependence as a mixture of three simple structures: comonotonicity, independence and countermonotonicity. They are easily interpretable but have limitations when used as approximations to general dependence structures. To improve the approximation property of the BF copulas and keep the advantage of easy interpretation, we develop a new copula approximation scheme by using BF copulas locally and patching the local pieces together. Error bounds and a probabilistic interpretation of this approximation scheme are developed. The new approximation scheme is compared with several existing copula approximations, including shuffle of min, checkmin, checkerboard and Bernstein approximations and exhibits better performance, especially in characterizing the local dependence. The utility of the new approximation scheme in insurance and finance is illustrated in the computation of the rainbow option prices and stop-loss premiums. © 2010 Elsevier B.V.

  8. Parameter estimation and statistical test of geographically weighted bivariate Poisson inverse Gaussian regression models

    Science.gov (United States)

    Amalia, Junita; Purhadi, Otok, Bambang Widjanarko

    2017-11-01

    Poisson distribution is a discrete distribution with count data as the random variables and it has one parameter defines both mean and variance. Poisson regression assumes mean and variance should be same (equidispersion). Nonetheless, some case of the count data unsatisfied this assumption because variance exceeds mean (over-dispersion). The ignorance of over-dispersion causes underestimates in standard error. Furthermore, it causes incorrect decision in the statistical test. Previously, paired count data has a correlation and it has bivariate Poisson distribution. If there is over-dispersion, modeling paired count data is not sufficient with simple bivariate Poisson regression. Bivariate Poisson Inverse Gaussian Regression (BPIGR) model is mix Poisson regression for modeling paired count data within over-dispersion. BPIGR model produces a global model for all locations. In another hand, each location has different geographic conditions, social, cultural and economic so that Geographically Weighted Regression (GWR) is needed. The weighting function of each location in GWR generates a different local model. Geographically Weighted Bivariate Poisson Inverse Gaussian Regression (GWBPIGR) model is used to solve over-dispersion and to generate local models. Parameter estimation of GWBPIGR model obtained by Maximum Likelihood Estimation (MLE) method. Meanwhile, hypothesis testing of GWBPIGR model acquired by Maximum Likelihood Ratio Test (MLRT) method.

  9. Bivariate Developmental Relations between Calculations and Word Problems: A Latent Change Approach.

    Science.gov (United States)

    Gilbert, Jennifer K; Fuchs, Lynn S

    2017-10-01

    The relation between 2 forms of mathematical cognition, calculations and word problems, was examined. Across grades 2-3, performance of 328 children (mean starting age 7.63 [ SD =0.43]) was assessed 3 times. Comparison of a priori latent change score models indicated a dual change model, with consistently positive but slowing growth, described development in each domain better than a constant or proportional change model. The bivariate model including change models for both calculations and word problems indicated prior calculation performance and change were not predictors of subsequent word-problem change, and prior word-problem performance and change were not predictors of subsequent calculation change. Results were comparable for boys versus girls. The bivariate model, along with correlations among intercepts and slopes, suggest calculation and word-problem development are related, but through an external set of overlapping factors. Exploratory supplemental analyses corroborate findings and provide direction for future study.

  10. 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 pain and FSDS total scores, even after adjusting for age (P pain domain, and sex-related distress. A history of abuse, relational parameters, gynecologic diseases, and hormonal and metabolic alterations do not seem to play a role in the development of V. Maseroli E, Scavello I, Cipriani S, et al. Psychobiological Correlates of 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.

  11. An efficient algorithm for generating random number pairs drawn from a bivariate normal distribution

    Science.gov (United States)

    Campbell, C. W.

    1983-01-01

    An efficient algorithm for generating random number pairs from a bivariate normal distribution was developed. Any desired value of the two means, two standard deviations, and correlation coefficient can be selected. Theoretically the technique is exact and in practice its accuracy is limited only by the quality of the uniform distribution random number generator, inaccuracies in computer function evaluation, and arithmetic. A FORTRAN routine was written to check the algorithm and good accuracy was obtained. Some small errors in the correlation coefficient were observed to vary in a surprisingly regular manner. A simple model was developed which explained the qualities aspects of the errors.

  12. 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.

  13. mitants of Order Statistics from Bivariate Inverse Rayleigh Distribution

    Directory of Open Access Journals (Sweden)

    Muhammad Aleem

    2006-01-01

    Full Text Available The probability density function (pdf of the rth, 1 r n and joint pdf of the rth and sth, 1 rBivariate Inverse Rayleigh Distribution and their moments, product moments are obtained. Its percentiles are also obtained.

  14. Modelling of Uncertainty and Bi-Variable Maps

    Science.gov (United States)

    Nánásiová, Ol'ga; Pykacz, Jarosław

    2016-05-01

    The paper gives an overview and compares various bi-varilable maps from orthomodular lattices into unit interval. It focuses mainly on such bi-variable maps that may be used for constructing joint probability distributions for random variables which are not defined on the same Boolean algebra.

  15. An assessment on the use of bivariate, multivariate and soft ...

    Indian Academy of Sciences (India)

    Conditional probability (CP), logistic regression (LR) and artificial neural networks (ANN) models representing the bivariate, multivariate and soft computing techniques were used in GIS based collapse susceptibility mapping in an area from Sivas basin (Turkey). Collapse-related factors, directly or indirectly related to the ...

  16. An assessment on the use of bivariate, multivariate and soft ...

    Indian Academy of Sciences (India)

    The paper presented herein compares and discusses the use of bivariate, multivariate and soft computing techniques for ... map is a useful tool in urban planning. ..... 381. Table 1. Frequency ratio of geological factors to collapse occurrences and results of the P(A/Bi) obtained from the. Conditional Probability model. Class.

  17. About some properties of bivariate splines with shape parameters

    Science.gov (United States)

    Caliò, F.; Marchetti, E.

    2017-07-01

    The paper presents and proves geometrical properties of a particular bivariate function spline, built and algorithmically implemented in previous papers. The properties typical of this family of splines impact the field of computer graphics in particular that of the reverse engineering.

  18. Bayesian analysis of a correlated binomial model

    OpenAIRE

    Diniz, Carlos A. R.; Tutia, Marcelo H.; Leite, Jose G.

    2010-01-01

    In this paper a Bayesian approach is applied to the correlated binomial model, CB(n, p, ρ), proposed by Luceño (Comput. Statist. Data Anal. 20 (1995) 511–520). The data augmentation scheme is used in order to overcome the complexity of the mixture likelihood. MCMC methods, including Gibbs sampling and Metropolis within Gibbs, are applied to estimate the posterior marginal for the probability of success p and for the correlation coefficient ρ. The sensitivity of the posterior is studied taking...

  19. Auto-correlation analysis of ocean surface wind vectors

    Indian Academy of Sciences (India)

    M. Senthilkumar (Newgen Imaging) 1461 1996 Oct 15 13:05:22

    In this work, an auto-correlation analysis of a time series data of surface winds measured in situ by a deep water buoy in the Indian Ocean has been carried out. Hourly time series data available for 240 hours in the month of May, 1999 were subjected to an auto-correlation analysis. The analysis indicates an exponential fall ...

  20. 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)

  1. Correlation and path coefficient analysis of some quantitative traits ...

    African Journals Online (AJOL)

    Thirty-seven wheat genotypes and three check varieties were studied for correlation and path coefficient analysis of some quantitative traits in wheat at Kisan (P.G), College, Simbhaoli in India. Generally, the estimates of genotypic correlation coefficients were higher than the corresponding phenotypic correlation coefficients ...

  2. QTL mapping and correlation analysis for 1000-grain weight and ...

    Indian Academy of Sciences (India)

    In this study, a set of introgression lines (ILs), derived from Sasanishiki/Habataki with Sasanishiki as the recurrent parent, were used to detect correlations and quantitative trait loci (QTL) on TGW and PGWC in two different environments. Phenotypic correlation analysis showed that there was no significant correlation ...

  3. Fatality analysis reporting system and roadway inventory correlation.

    Science.gov (United States)

    2013-01-01

    In this project, we developed an integrated database to provide new analysis capabilities : for discovering correlations between roadway characteristics and the occurrence of : fatality collisions. Specifically, the aim of this data analysis project ...

  4. Bivariate return periods of temperature and precipitation explain a large fraction of European crop yields

    Science.gov (United States)

    Zscheischler, Jakob; Orth, Rene; Seneviratne, Sonia I.

    2017-07-01

    Crops are vital for human society. Crop yields vary with climate and it is important to understand how climate and crop yields are linked to ensure future food security. Temperature and precipitation are among the key driving factors of crop yield variability. Previous studies have investigated mostly linear relationships between temperature and precipitation and crop yield variability. Other research has highlighted the adverse impacts of climate extremes, such as drought and heat waves, on crop yields. Impacts are, however, often non-linearly related to multivariate climate conditions. Here we derive bivariate return periods of climate conditions as indicators for climate variability along different temperature-precipitation gradients. We show that in Europe, linear models based on bivariate return periods of specific climate conditions explain on average significantly more crop yield variability (42 %) than models relying directly on temperature and precipitation as predictors (36 %). Our results demonstrate that most often crop yields increase along a gradient from hot and dry to cold and wet conditions, with lower yields associated with hot and dry periods. The majority of crops are most sensitive to climate conditions in summer and to maximum temperatures. The use of bivariate return periods allows the integration of non-linear impacts into climate-crop yield analysis. This offers new avenues to study the link between climate and crop yield variability and suggests that they are possibly more strongly related than what is inferred from conventional linear models.

  5. 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.

  6. Texture and coarse fraction composition of Nile Delta deposits: facies analysis and stratigraphic correlation

    Science.gov (United States)

    Frihy, Omran E.; Stanley, Daniel Jean

    This study distinguishes some of the major late Pleistocene and Holocene lithofacies in the northeastern Nile Delta of Egypt by evaluating quantitatively the texture and the coarse fraction composition of 375 samples in 14 cores. Seventeen petrologic variables (three textural and 14 mineralogical, faunal and floral) were considered for each of the samples. For facies discrimination the raw data were evaluated with descriptive statistics and with numerous (>300) computer-generated bivariate and ternary diagrams. This treatment, and Q-mode factor analysis, were applied separately to two facies groups: one comprised coastal-organic rich, lagoonal/marsh, delta-front, prodelta and alluvial delta plain muds; the other comprised upper Holocene progradational coastal sands, lower Holocene transgressive coastal sands and late Pleistocene alluvial sands. Discrimination of the five mud facies is generally good (except that of the upper Holocene lagoonal/marsh muds), while that of the three sand types is only moderately successful. As a test of the method used here for facies analysis, we were able to satisfactorily identify and interpret the origin of 38 small "unknown" samples in two additional poorly-preserved cores in the study area. Having identified most of the facies, normalized factor components were used to correlate some of the sedimentary sections between cores. The investigation indicates that discrimination of Nile Delta facies and their correlation from core-to-core are most precise when the textural and compositional data are merged with the visually more obvious features (sedimentary structures, hardness, color, etc.), and when the petrologic data are placed within a chronostratigraphic framework of radiocarbon-dated subsurface sequence.

  7. Meta-Analysis of Correlations Among Usability Measures

    DEFF Research Database (Denmark)

    Hornbæk, Kasper Anders Søren; Effie Lai Chong, Law

    2007-01-01

    Understanding the relation between usability measures seems crucial to deepen our conception of usability and to select the right measures for usability studies. We present a meta-analysis of correlations among usability measures calculated from the raw data of 73 studies. Correlations are genera......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...

  8. Assessing the copula selection for bivariate frequency analysis ...

    Indian Academy of Sciences (India)

    58

    upper tail copulas (Frank, Clayton and Gaussian), if there exists asymptotic dependence in the. 24 flood characteristics. ... characteristics and Frank, Clayton and Gaussian copulas are the appropriate copula models in. 30 ..... The mean of daily discharge of Trian stream gauge from 1978 to 2013 is 527.4 m3/s and the. 181.

  9. Computational approach to Thornley's problem by bivariate operational calculus

    Science.gov (United States)

    Bazhlekova, E.; Dimovski, I.

    2012-10-01

    Thornley's problem is an initial-boundary value problem with a nonlocal boundary condition for linear onedimensional reaction-diffusion equation, used as a mathematical model of spiral phyllotaxis in botany. Applying a bivariate operational calculus we find explicit representation of the solution, containing two convolution products of special solutions and the arbitrary initial and boundary functions. We use a non-classical convolution with respect to the space variable, extending in this way the classical Duhamel principle. The special solutions involved are represented in the form of fast convergent series. Numerical examples are considered to show the application of the present technique and to analyze the character of the solution.

  10. Meta-Analysis of Correlations Among Usability Measures

    DEFF Research Database (Denmark)

    Hornbæk, Kasper Anders Søren; Effie Lai Chong, Law

    2007-01-01

    Understanding the relation between usability measures seems crucial to deepen our conception of usability and to select the right measures for usability studies. We present a meta-analysis of correlations among usability measures calculated from the raw data of 73 studies. Correlations are genera......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...

  11. 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.

  12. 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%) ...

  13. 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

  14. 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.

  15. Bivariate generalized Pareto distribution for extreme atmospheric particulate matter

    Science.gov (United States)

    Amin, Nor Azrita Mohd; Adam, Mohd Bakri; Ibrahim, Noor Akma; Aris, Ahmad Zaharin

    2015-02-01

    The high particulate matter (PM10) level is the prominent issue causing various impacts to human health and seriously affecting the economics. The asymptotic theory of extreme value is apply for analyzing the relation of extreme PM10 data from two nearby air quality monitoring stations. The series of daily maxima PM10 for Johor Bahru and Pasir Gudang stations are consider for year 2001 to 2010 databases. The 85% and 95% marginal quantile apply to determine the threshold values and hence construct the series of exceedances over the chosen threshold. The logistic, asymmetric logistic, negative logistic and asymmetric negative logistic models areconsidered as the dependence function to the joint distribution of a bivariate observation. Maximum likelihood estimation is employed for parameter estimations. The best fitted model is chosen based on the Akaike Information Criterion and the quantile plots. It is found that the asymmetric logistic model gives the best fitted model for bivariate extreme PM10 data and shows the weak dependence between two stations.

  16. 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.

  17. correlation and path coefficient analysis of yield characters of bambara

    African Journals Online (AJOL)

    Finance DAC

    academicjournals.org/AJEST. African Journal of Environmental Science and. Technology. Full Length Research Paper. Correlation and path coefficient analysis of yield characters of bambara (Vigna subterranea L.Verdc.) S. M. Maunde. 1. *, B. Tanimu.

  18. 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

  19. Bivariate spline solution of time dependent nonlinear PDE for a population density over irregular domains.

    Science.gov (United States)

    Gutierrez, Juan B; Lai, Ming-Jun; Slavov, George

    2015-12-01

    We study a time dependent partial differential equation (PDE) which arises from classic models in ecology involving logistic growth with Allee effect by introducing a discrete weak solution. Existence, uniqueness and stability of the discrete weak solutions are discussed. We use bivariate splines to approximate the discrete weak solution of the nonlinear PDE. A computational algorithm is designed to solve this PDE. A convergence analysis of the algorithm is presented. We present some simulations of population development over some irregular domains. Finally, we discuss applications in epidemiology and other ecological problems. Copyright © 2015 Elsevier Inc. All rights reserved.

  20. 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.

  1. Efficient estimation of semiparametric copula models for bivariate survival data

    KAUST Repository

    Cheng, Guang

    2014-01-01

    A semiparametric copula model for bivariate survival data is characterized by a parametric copula model of dependence and nonparametric models of two marginal survival functions. Efficient estimation for the semiparametric copula model has been recently studied for the complete data case. When the survival data are censored, semiparametric efficient estimation has only been considered for some specific copula models such as the Gaussian copulas. In this paper, we obtain the semiparametric efficiency bound and efficient estimation for general semiparametric copula models for possibly censored data. We construct an approximate maximum likelihood estimator by approximating the log baseline hazard functions with spline functions. We show that our estimates of the copula dependence parameter and the survival functions are asymptotically normal and efficient. Simple consistent covariance estimators are also provided. Numerical results are used to illustrate the finite sample performance of the proposed estimators. © 2013 Elsevier Inc.

  2. Bell-Type Inequalities for Bivariate Maps on Orthomodular Lattices

    Science.gov (United States)

    Pykacz, Jarosław; Valášková, L'ubica; Nánásiová, Ol'ga

    2015-08-01

    Bell-type inequalities on orthomodular lattices, in which conjunctions of propositions are not modeled by meets but by maps for simultaneous measurements (-maps), are studied. It is shown, that the most simple of these inequalities, that involves only two propositions, is always satisfied, contrary to what happens in the case of traditional version of this inequality in which conjunctions of propositions are modeled by meets. Equivalence of various Bell-type inequalities formulated with the aid of bivariate maps on orthomodular lattices is studied. Our investigations shed new light on the interpretation of various multivariate maps defined on orthomodular lattices already studied in the literature. The paper is concluded by showing the possibility of using -maps and -maps to represent counterfactual conjunctions and disjunctions of non-compatible propositions about quantum systems.

  3. Selection effects in the bivariate brightness distribution for spiral galaxies

    International Nuclear Information System (INIS)

    Phillipps, S.; Disney, M.

    1986-01-01

    The joint distribution of total luminosity and characteristic surface brightness (the bivariate brightness distribution) is investigated for a complete sample of spiral galaxies in the Virgo cluster. The influence of selection and physical limits of various kinds on the apparent distribution are detailed. While the distribution of surface brightness for bright galaxies may be genuinely fairly narrow, faint galaxies exist right across the (quite small) range of accessible surface brightnesses so no statement can be made about the true extent of the distribution. The lack of high surface brightness bright galaxies in the Virgo sample relative to an overall RC2 sample (mostly field galaxies) supports the contention that the star-formation rate is reduced in the inner region of the cluster for environmental reasons. (author)

  4. 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

  5. A non-stationary cost-benefit based bivariate extreme flood estimation approach

    Science.gov (United States)

    Qi, Wei; Liu, Junguo

    2018-02-01

    Cost-benefit analysis and flood frequency analysis have been integrated into a comprehensive framework to estimate cost effective design values. However, previous cost-benefit based extreme flood estimation is based on stationary assumptions and analyze dependent flood variables separately. A Non-Stationary Cost-Benefit based bivariate design flood estimation (NSCOBE) approach is developed in this study to investigate influence of non-stationarities in both the dependence of flood variables and the marginal distributions on extreme flood estimation. The dependence is modeled utilizing copula functions. Previous design flood selection criteria are not suitable for NSCOBE since they ignore time changing dependence of flood variables. Therefore, a risk calculation approach is proposed based on non-stationarities in both marginal probability distributions and copula functions. A case study with 54-year observed data is utilized to illustrate the application of NSCOBE. Results show NSCOBE can effectively integrate non-stationarities in both copula functions and marginal distributions into cost-benefit based design flood estimation. It is also found that there is a trade-off between maximum probability of exceedance calculated from copula functions and marginal distributions. This study for the first time provides a new approach towards a better understanding of influence of non-stationarities in both copula functions and marginal distributions on extreme flood estimation, and could be beneficial to cost-benefit based non-stationary bivariate design flood estimation across the world.

  6. An integrated user-friendly ArcMAP tool for bivariate statistical modeling in geoscience applications

    Science.gov (United States)

    Jebur, M. N.; Pradhan, B.; Shafri, H. Z. M.; Yusof, Z.; Tehrany, M. S.

    2014-10-01

    Modeling and classification difficulties are fundamental issues in natural hazard assessment. A geographic information system (GIS) is a domain that requires users to use various tools to perform different types of spatial modeling. Bivariate statistical analysis (BSA) assists in hazard modeling. To perform this analysis, several calculations are required and the user has to transfer data from one format to another. Most researchers perform these calculations manually by using Microsoft Excel or other programs. This process is time consuming and carries a degree of uncertainty. The lack of proper tools to implement BSA in a GIS environment prompted this study. In this paper, a user-friendly tool, BSM (bivariate statistical modeler), for BSA technique is proposed. Three popular BSA techniques such as frequency ratio, weights-of-evidence, and evidential belief function models are applied in the newly proposed ArcMAP tool. This tool is programmed in Python and is created by a simple graphical user interface, which facilitates the improvement of model performance. The proposed tool implements BSA automatically, thus allowing numerous variables to be examined. To validate the capability and accuracy of this program, a pilot test area in Malaysia is selected and all three models are tested by using the proposed program. Area under curve is used to measure the success rate and prediction rate. Results demonstrate that the proposed program executes BSA with reasonable accuracy. The proposed BSA tool can be used in numerous applications, such as natural hazard, mineral potential, hydrological, and other engineering and environmental applications.

  7. 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...... with changes in teaching methods from one year to another....

  8. Delay correlation analysis and representation for vital complaint VHDL models

    Science.gov (United States)

    Rich, Marvin J.; Misra, Ashutosh

    2004-11-09

    A method and system unbind a rise/fall tuple of a VHDL generic variable and create rise time and fall time generics of each generic variable that are independent of each other. Then, according to a predetermined correlation policy, the method and system collect delay values in a VHDL standard delay file, sort the delay values, remove duplicate delay values, group the delay values into correlation sets, and output an analysis file. The correlation policy may include collecting all generic variables in a VHDL standard delay file, selecting each generic variable, and performing reductions on the set of delay values associated with each selected generic variable.

  9. Process Correlation Analysis Model for Process Improvement Identification

    Directory of Open Access Journals (Sweden)

    Su-jin Choi

    2014-01-01

    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.

  10. 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%.

  11. Evaluation of Test/Analysis Correlation Methods for Crash Applications

    Science.gov (United States)

    Lyle, Karen H.; Bark, Lindley W.; Jackson, Karen E.

    2001-01-01

    A project has been initiated to improve crash test and analysis correlation. The work in this paper concentrated on the test and simulation results for a fuselage section. Two drop tests of the section were conducted. The first test was designed to excite the linear structural response for comparison with finite element modal analysis results. The second test was designed to provide data for correlation with crash simulations. An MSC.Dytran model was developed to generate nonlinear transient dynamic results. Following minor modifications, the same model was executed in MSC.Nastran to generate modal analysis results. The results presented in this paper concentrate on evaluation of correlation methodologies for crash test data and finite element simulation results.

  12. A bivariate measurement error model for semicontinuous and continuous variables: Application to nutritional epidemiology.

    Science.gov (United States)

    Kipnis, Victor; Freedman, Laurence S; Carroll, Raymond J; Midthune, Douglas

    2016-03-01

    Semicontinuous data in the form of a mixture of a large portion of zero values and continuously distributed positive values frequently arise in many areas of biostatistics. This article is motivated by the analysis of relationships between disease outcomes and intakes of episodically consumed dietary components. An important aspect of studies in nutritional epidemiology is that true diet is unobservable and commonly evaluated by food frequency questionnaires with substantial measurement error. Following the regression calibration approach for measurement error correction, unknown individual intakes in the risk model are replaced by their conditional expectations given mismeasured intakes and other model covariates. Those regression calibration predictors are estimated using short-term unbiased reference measurements in a calibration substudy. Since dietary intakes are often "energy-adjusted," e.g., by using ratios of the intake of interest to total energy intake, the correct estimation of the regression calibration predictor for each energy-adjusted episodically consumed dietary component requires modeling short-term reference measurements of the component (a semicontinuous variable), and energy (a continuous variable) simultaneously in a bivariate model. In this article, we develop such a bivariate model, together with its application to regression calibration. We illustrate the new methodology using data from the NIH-AARP Diet and Health Study (Schatzkin et al., 2001, American Journal of Epidemiology 154, 1119-1125), and also evaluate its performance in a simulation study. © 2015, The International Biometric Society.

  13. Semiparametric probit models with univariate and bivariate current-status data.

    Science.gov (United States)

    Liu, Hao; Qin, Jing

    2018-03-01

    Multivariate current-status data are frequently encountered in biomedical and public health studies. Semiparametric regression models have been extensively studied for univariate current-status data, but most existing estimation procedures are computationally intensive, involving either penalization or smoothing techniques. It becomes more challenging for the analysis of multivariate current-status data. In this article, we study the maximum likelihood estimations for univariate and bivariate current-status data under the semiparametric probit regression models. We present a simple computational procedure combining the expectation-maximization algorithm with the pool-adjacent-violators algorithm for solving the monotone constraint on the baseline function. Asymptotic properties of the maximum likelihood estimators are investigated, including the calculation of the explicit information bound for univariate current-status data, as well as the asymptotic consistency and convergence rate for bivariate current-status data. Extensive simulation studies showed that the proposed computational procedures performed well under small or moderate sample sizes. We demonstrate the estimation procedure with two real data examples in the areas of diabetic and HIV research. © 2017, The International Biometric Society.

  14. A method of moments to estimate bivariate survival functions: the copula approach

    Directory of Open Access Journals (Sweden)

    Silvia Angela Osmetti

    2013-05-01

    Full Text Available In this paper we discuss the problem on parametric and non parametric estimation of the distributions generated by the Marshall-Olkin copula. This copula comes from the Marshall-Olkin bivariate exponential distribution used in reliability analysis. We generalize this model by the copula and different marginal distributions to construct several bivariate survival functions. The cumulative distribution functions are not absolutely continuous and they unknown parameters are often not be obtained in explicit form. In order to estimate the parameters we propose an easy procedure based on the moments. This method consist in two steps: in the first step we estimate only the parameters of marginal distributions and in the second step we estimate only the copula parameter. This procedure can be used to estimate the parameters of complex survival functions in which it is difficult to find an explicit expression of the mixed moments. Moreover it is preferred to the maximum likelihood one for its simplex mathematic form; in particular for distributions whose maximum likelihood parameters estimators can not be obtained in explicit form.

  15. Intelligent data analysis based on rough correlativity matrix

    Science.gov (United States)

    Geng, Zhiqiang; Zhu, Qunxiong

    2003-09-01

    This paper proposes a new data analysis method based on rough sets by rough correlativity matrix. In rough set theory, a table called information system or database is used as a special kind of formal language to represent knowledge, a rough correlativity matrix (RCM) can be seen as an internal representation of equivalence relations. Furthermore, this paper provides a new heuristic attributes reduction algorithm based on matrix computing, such as using matrix correlative implements to replace the relations computing between sets. Finally the paper adopts information transition matrix (ITM) of information theory to represent the certainty or uncertainty decision rules based on probability theory, namely, the information matrix composed of certainty factors gives the degree of belief of decision rules, on the contrary the "invert" ITM composed of coverage factor gives the interpretation of decision rules. The result of instance analysis is shown that it is an efficient and feasible method to deal with decision information table.

  16. 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...

  17. Correlation and Path Analysis in Shallot (Allium cepa var ...

    African Journals Online (AJOL)

    Field experiments were conducted on forty nine shallot genotypes to study the nature of correlations between bulb yield and other related characters at Sirinka and Girana in northeastern Ethiopia. Observations were made on ten plant samples for data analysis. At Girana, total bulb yield per plant showed high and positive ...

  18. 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.

  19. Drivers and Outcomes of Scenario Planning: A Canonical Correlation Analysis

    Science.gov (United States)

    Chermack, Thomas J.; Nimon, Kim

    2013-01-01

    Purpose: The paper's aim is to report a research study on the mediator and outcome variable sets in scenario planning. Design/methodology/approach: This is a cannonical correlation analysis (CCA) Findings Two sets of variables; one as a predictor set that explained a significant amount of variability in the second, or outcome set of variables were…

  20. Auto-correlation analysis of ocean surface wind vectors

    Indian Academy of Sciences (India)

    The nature of the inherent temporal variability of surface winds is analyzed by comparison of winds obtained through different measurement methods. In this work, an auto-correlation analysis of a time series data of surface winds measured in situ by a deep water buoy in the Indian Ocean has been carried out. Hourly time ...

  1. Analysis of embryo, cytoplasmic and maternal correlations for quality ...

    Indian Academy of Sciences (India)

    Home; Journals; Journal of Genetics; Volume 85; Issue 2. Analysis of embryo, cytoplasmic and maternal correlations for quality traits of rapeseed (Brassica napus L.) across environments. C. H. Shi H. Z. Zhang J. G. Wu. Research Note Volume 85 Issue 2 August 2006 pp 147-151 ...

  2. 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.)

  3. Linear analysis of degree correlations in complex networks

    Indian Academy of Sciences (India)

    2016-11-02

    Nov 2, 2016 ... interaction network and the Internet map. Ma and Szeta. [25] gave a linear analysis of the total degrees of the nearest neighbours as a function of vertex degree by extending the Aboav–Wearie law to complex networks. The studies provide alternative ways to analyse the degree correlation in the networks, ...

  4. A bivariate optimal replacement policy for a multistate repairable system

    International Nuclear Information System (INIS)

    Zhang Yuanlin; Yam, Richard C.M.; Zuo, Ming J.

    2007-01-01

    In this paper, a deteriorating simple repairable system with k+1 states, including k failure states and one working state, is studied. It is assumed that the system after repair is not 'as good as new' and the deterioration of the system is stochastic. We consider a bivariate replacement policy, denoted by (T,N), in which the system is replaced when its working age has reached T or the number of failures it has experienced has reached N, whichever occurs first. The objective is to determine the optimal replacement policy (T,N)* such that the long-run expected profit per unit time is maximized. The explicit expression of the long-run expected profit per unit time is derived and the corresponding optimal replacement policy can be determined analytically or numerically. We prove that the optimal policy (T,N)* is better than the optimal policy N* for a multistate simple repairable system. We also show that a general monotone process model for a multistate simple repairable system is equivalent to a geometric process model for a two-state simple repairable system in the sense that they have the same structure for the long-run expected profit (or cost) per unit time and the same optimal policy. Finally, a numerical example is given to illustrate the theoretical results

  5. Epileptic seizure prediction based on a bivariate spectral power methodology.

    Science.gov (United States)

    Bandarabadi, Mojtaba; Teixeira, Cesar A; Direito, Bruno; Dourado, Antonio

    2012-01-01

    The spectral power of 5 frequently considered frequency bands (Alpha, Beta, Gamma, Theta and Delta) for 6 EEG channels is computed and then all the possible pairwise combinations among the 30 features set, are used to create a 435 dimensional feature space. Two new feature selection methods are introduced to choose the best candidate features among those and to reduce the dimensionality of this feature space. The selected features are then fed to Support Vector Machines (SVMs) that classify the cerebral state in preictal and non-preictal classes. The outputs of the SVM are regularized using a method that accounts for the classification dynamics of the preictal class, also known as "Firing Power" method. The results obtained using our feature selection approaches are compared with the ones obtained using minimum Redundancy Maximum Relevance (mRMR) feature selection method. The results in a group of 12 patients of the EPILEPSIAE database, containing 46 seizures and 787 hours multichannel recording for out-of-sample data, indicate the efficiency of the bivariate approach as well as the two new feature selection methods. The best results presented sensitivity of 76.09% (35 of 46 seizures predicted) and a false prediction rate of 0.15(-1).

  6. 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.

  7. 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.

  8. 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.

  9. 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...

  10. 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.

  11. 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.

  12. 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.)

  13. [Phenotypic Trait Variation, Correlation and Path Analysis of Clerodendranthus spicatus].

    Science.gov (United States)

    Wang, Yan-fang; Li, Ge; Tang, Ling; Yang, Chun-Yong; Li, Rong-Ying; Ma, Xiao-jun

    2015-10-01

    To investigate the phenotypic trait variation range of Clerodendranthus spicatus, and to look for phenotypic traits closely related with its yield and quality, in order to provide reference for its breeding. Randomly labelled plants of Clerodendranthus spicatus, observed its phenotypic traits and analyzed by variation, principal component, correlation and path analysis. 13 phenotypic traits in the 15 germplasms of Clerodendranthus spicatus had great variations, the variations mainly distributed in yield, growth and genetic characteristics. Correlation and path analysis showed that, the plant dry weight had an extremely significantly positive correlation with fresh weight, and a positive correlation with stem height, stem diameter and root diameter. Plant fresh weight had a majorly direct contribution to the plant dry weight, stem height, stem diameter and root diameter also had a direct contribution to the plant dry weight. The other characters, including root length, branches, the number of leaf nodes, leaf number, leaf length, leaf width, fresh weight/dry weight ratio, rosmarinic acid content and ursolic acid content all had a negatively direct contribution to the plant dry weight. Rosmarinic acid content had a positive correlation with fresh weight, and a significantly positive correlation with fresh weight/dry weight ratio. Fresh weight had a majorly direct contribution to the rosmarinic acid content, stem height and stem diameter also had a direct contribution to the plant rosmarinic acid content. The other characters, including root length, root diameter, branches, the number of leaf nodes, leaf length, leaf width, dry weight, fresh weight/dry weight ratio, and ursolic acid content all had a negatively direct contribution to the rosmarinic acid content. The phenotypic traits of Clerodendranthus spicatus had rich variations on yield, growth and genetic characteristics. When choosing good germplasm, plant fresh weight, stem height, stem diameter and plant fresh

  14. Bivariate Gaussian bridges: directional factorization of diffusion in Brownian bridge models.

    Science.gov (United States)

    Kranstauber, Bart; Safi, Kamran; Bartumeus, Frederic

    2014-01-01

    In recent years high resolution animal tracking data has become the standard in movement ecology. The Brownian Bridge Movement Model (BBMM) is a widely adopted approach to describe animal space use from such high resolution tracks. One of the underlying assumptions of the BBMM is isotropic diffusive motion between consecutive locations, i.e. invariant with respect to the direction. Here we propose to relax this often unrealistic assumption by separating the Brownian motion variance into two directional components, one parallel and one orthogonal to the direction of the motion. Our new model, the Bivariate Gaussian bridge (BGB), tracks movement heterogeneity across time. Using the BGB and identifying directed and non-directed movement within a trajectory resulted in more accurate utilisation distributions compared to dynamic Brownian bridges, especially for trajectories with a non-isotropic diffusion, such as directed movement or Lévy like movements. We evaluated our model with simulated trajectories and observed tracks, demonstrating that the improvement of our model scales with the directional correlation of a correlated random walk. We find that many of the animal trajectories do not adhere to the assumptions of the BBMM. The proposed model improves accuracy when describing the space use both in simulated correlated random walks as well as observed animal tracks. Our novel approach is implemented and available within the "move" package for R.

  15. Inland dissolved salt chemistry: statistical evaluation of bivariate and ternary diagram models for surface and subsurface waters

    Directory of Open Access Journals (Sweden)

    Stephen T. THRELKELD

    2000-08-01

    Full Text Available We compared the use of ternary and bivariate diagrams to distinguish the effects of atmospheric precipitation, rock weathering, and evaporation on inland surface and subsurface water chemistry. The three processes could not be statistically differentiated using bivariate models even if large water bodies were evaluated separate from small water bodies. Atmospheric precipitation effects were identified using ternary diagrams in water with total dissolved salts (TDS 1000 mg l-1. A principal components analysis showed that the variability in the relative proportions of the major ions was related to atmospheric precipitation, weathering, and evaporation. About half of the variation in the distribution of inorganic ions was related to rock weathering. By considering most of the important inorganic ions, ternary diagrams are able to distinguish the contributions of atmospheric precipitation, rock weathering, and evaporation to inland water chemistry.

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

    DEFF Research Database (Denmark)

    Clemmensen, Line Katrine Harder

    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......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...... generally focus on two things: Obtaining sparsity (variable selection) and regularizing the estimate of the within-class covariance matrix. For high-dimensional data, this gives rise to increased interpretability and generalization ability over standard linear discriminant analysis. Here, we group...

  17. 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++.

  18. 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++.

  19. 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.

  20. An integrated user-friendly ArcMAP tool for bivariate statistical modelling in geoscience applications

    Science.gov (United States)

    Jebur, M. N.; Pradhan, B.; Shafri, H. Z. M.; Yusoff, Z. M.; Tehrany, M. S.

    2015-03-01

    Modelling and classification difficulties are fundamental issues in natural hazard assessment. A geographic information system (GIS) is a domain that requires users to use various tools to perform different types of spatial modelling. Bivariate statistical analysis (BSA) assists in hazard modelling. To perform this analysis, several calculations are required and the user has to transfer data from one format to another. Most researchers perform these calculations manually by using Microsoft Excel or other programs. This process is time-consuming and carries a degree of uncertainty. The lack of proper tools to implement BSA in a GIS environment prompted this study. In this paper, a user-friendly tool, bivariate statistical modeler (BSM), for BSA technique is proposed. Three popular BSA techniques, such as frequency ratio, weight-of-evidence (WoE), and evidential belief function (EBF) models, are applied in the newly proposed ArcMAP tool. This tool is programmed in Python and created by a simple graphical user interface (GUI), which facilitates the improvement of model performance. The proposed tool implements BSA automatically, thus allowing numerous variables to be examined. To validate the capability and accuracy of this program, a pilot test area in Malaysia is selected and all three models are tested by using the proposed program. Area under curve (AUC) is used to measure the success rate and prediction rate. Results demonstrate that the proposed program executes BSA with reasonable accuracy. The proposed BSA tool can be used in numerous applications, such as natural hazard, mineral potential, hydrological, and other engineering and environmental applications.

  1. Brillouin optical correlation domain analysis in composite material beams

    DEFF Research Database (Denmark)

    Stern, Yonatan; London, Yosef; Preter, Eyal

    2017-01-01

    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......) 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...

  2. Comparison of Model Reliabilities from Single-Step and Bivariate Blending Methods

    DEFF Research Database (Denmark)

    Taskinen, Matti; Mäntysaari, Esa; Lidauer, Martin

    2013-01-01

    the production trait evaluation of Nordic Red dairy cattle. Genotyped bulls with daughters are used as training animals, and genotyped bulls and producing cows as candidate animals. For simplicity, size of the data is chosen so that the full inverses of the mixed model equation coefficient matrices can......Model based reliabilities in genetic evaluation are compared between three methods: animal model BLUP, single-step BLUP, and bivariate blending after genomic BLUP. The original bivariate blending is revised in this work to better account animal models. The study data is extracted from...... be calculated. Model reliabilities by the single-step and the bivariate blending methods were higher than by animal model due to genomic information. Compared to the single-step method, the bivariate blending method reliability estimates were, in general, lower. Computationally bivariate blending method was...

  3. 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.

  4. 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.

  5. 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

  6. Bivariate return periods of temperature and precipitation explain a large fraction of European crop yields

    Directory of Open Access Journals (Sweden)

    J. Zscheischler

    2017-07-01

    Full Text Available Crops are vital for human society. Crop yields vary with climate and it is important to understand how climate and crop yields are linked to ensure future food security. Temperature and precipitation are among the key driving factors of crop yield variability. Previous studies have investigated mostly linear relationships between temperature and precipitation and crop yield variability. Other research has highlighted the adverse impacts of climate extremes, such as drought and heat waves, on crop yields. Impacts are, however, often non-linearly related to multivariate climate conditions. Here we derive bivariate return periods of climate conditions as indicators for climate variability along different temperature–precipitation gradients. We show that in Europe, linear models based on bivariate return periods of specific climate conditions explain on average significantly more crop yield variability (42 % than models relying directly on temperature and precipitation as predictors (36 %. Our results demonstrate that most often crop yields increase along a gradient from hot and dry to cold and wet conditions, with lower yields associated with hot and dry periods. The majority of crops are most sensitive to climate conditions in summer and to maximum temperatures. The use of bivariate return periods allows the integration of non-linear impacts into climate–crop yield analysis. This offers new avenues to study the link between climate and crop yield variability and suggests that they are possibly more strongly related than what is inferred from conventional linear models.

  7. 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)

  8. 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

  9. 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.

  10. 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

  11. Environmental Correlation Analysis for Genes Associated with Protection against Malaria.

    Science.gov (United States)

    Mackinnon, Margaret J; Ndila, Carolyne; Uyoga, Sophie; Macharia, Alex; Snow, Robert W; Band, Gavin; Rautanen, Anna; Rockett, Kirk A; Kwiatkowski, Dominic P; Williams, Thomas N

    2016-05-01

    Genome-wide searches for loci involved in human resistance to malaria are currently being conducted on a large scale in Africa using case-control studies. Here, we explore the utility of an alternative approach-"environmental correlation analysis, ECA," which tests for clines in allele frequencies across a gradient of an environmental selection pressure-to identify genes that have historically protected against death from malaria. We collected genotype data from 12,425 newborns on 57 candidate malaria resistance loci and 9,756 single nucleotide polymorphisms (SNPs) selected at random from across the genome, and examined their allele frequencies for geographic correlations with long-term malaria prevalence data based on 84,042 individuals living under different historical selection pressures from malaria in coastal Kenya. None of the 57 candidate SNPs showed significant (P < 0.05) correlations in allele frequency with local malaria transmission intensity after adjusting for population structure and multiple testing. In contrast, two of the random SNPs that had highly significant correlations (P < 0.01) were in genes previously linked to malaria resistance, namely, CDH13, encoding cadherin 13, and HS3ST3B1, encoding heparan sulfate 3-O-sulfotransferase 3B1. Both proteins play a role in glycoprotein-mediated cell-cell adhesion which has been widely implicated in cerebral malaria, the most life-threatening form of this disease. Other top genes, including CTNND2 which encodes δ-catenin, a molecular partner to cadherin, were significantly enriched in cadherin-mediated pathways affecting inflammation of the brain vascular endothelium. These results demonstrate the utility of ECA in the discovery of novel genes and pathways affecting infectious disease. © The Author 2016. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

  12. Correlation analysis between ionospheric scintillation levels and receiver tracking performance

    Science.gov (United States)

    Sreeja, V.; Aquino, M.; Elmas, Z. G.; Forte, B.

    2012-06-01

    Rapid fluctuations in the amplitude and phase of a transionospheric radio signal caused by small scale plasma density irregularities in the ionosphere are known as scintillation. Scintillation can seriously impair a GNSS (Global Navigation Satellite Systems) receiver tracking performance, thus affecting the required levels of availability, accuracy and integrity, and consequently the reliability of modern day GNSS based applications. This paper presents an analysis of correlation between scintillation levels and tracking performance of a GNSS receiver for GPS L1C/A, L2C and GLONASS L1, L2 signals. The analyses make use of data recorded over Presidente Prudente (22.1°S, 51.4°W, dip latitude ˜12.3°S) in Brazil, a location close to the Equatorial Ionisation Anomaly (EIA) crest in Latin America. The study presents for the first time this type of correlation analysis for GPS L2C and GLONASS L1, L2 signals. The scintillation levels are defined by the amplitude scintillation index, S4 and the receiver tracking performance is evaluated by the phase tracking jitter. Both S4 and the phase tracking jitter are estimated from the post correlation In-Phase (I) and Quadra-Phase (Q) components logged by the receiver at a high rate. Results reveal that the dependence of the phase tracking jitter on the scintillation levels can be represented by a quadratic fit for the signals. The results presented in this paper are of importance to GNSS users, especially in view of the forthcoming high phase of solar cycle 24 (predicted for 2013).

  13. 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.

  14. 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.

  15. Powerful bivariate genome-wide association analyses suggest the SOX6 gene influencing both obesity and osteoporosis phenotypes in males.

    Directory of Open Access Journals (Sweden)

    Yao-Zhong Liu

    2009-08-01

    Full Text Available Current genome-wide association studies (GWAS are normally implemented in a univariate framework and analyze different phenotypes in isolation. This univariate approach ignores the potential genetic correlation between important disease traits. Hence this approach is difficult to detect pleiotropic genes, which may exist for obesity and osteoporosis, two common diseases of major public health importance that are closely correlated genetically.To identify such pleiotropic genes and the key mechanistic links between the two diseases, we here performed the first bivariate GWAS of obesity and osteoporosis. We searched for genes underlying co-variation of the obesity phenotype, body mass index (BMI, with the osteoporosis risk phenotype, hip bone mineral density (BMD, scanning approximately 380,000 SNPs in 1,000 unrelated homogeneous Caucasians, including 499 males and 501 females. We identified in the male subjects two SNPs in intron 1 of the SOX6 (SRY-box 6 gene, rs297325 and rs4756846, which were bivariately associated with both BMI and hip BMD, achieving p values of 6.82x10(-7 and 1.47x10(-6, respectively. The two SNPs ranked at the top in significance for bivariate association with BMI and hip BMD in the male subjects among all the approximately 380,000 SNPs examined genome-wide. The two SNPs were replicated in a Framingham Heart Study (FHS cohort containing 3,355 Caucasians (1,370 males and 1,985 females from 975 families. In the FHS male subjects, the two SNPs achieved p values of 0.03 and 0.02, respectively, for bivariate association with BMI and femoral neck BMD. Interestingly, SOX6 was previously found to be essential to both cartilage formation/chondrogenesis and obesity-related insulin resistance, suggesting the gene's dual role in both bone and fat.Our findings, together with the prior biological evidence, suggest the SOX6 gene's importance in co-regulation of obesity and osteoporosis.

  16. 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

  17. Correlating Detergent Fiber Analysis and Dietary Fiber Analysis Data for Corn Stover

    Energy Technology Data Exchange (ETDEWEB)

    Wolfrum, E. J.; Lorenz, A. J.; deLeon, N.

    2009-01-01

    There exist large amounts of detergent fiber analysis data [neutral detergent fiber (NDF), acid detergent fiber (ADF), acid detergent lignin (ADL)] for many different potential cellulosic ethanol feedstocks, since these techniques are widely used for the analysis of forages. Researchers working in the area of cellulosic ethanol are interested in the structural carbohydrates in a feedstock (principally glucan and xylan), which are typically determined by acid hydrolysis of the structural fraction after multiple extractions of the biomass. These so-called dietary fiber analysis methods are significantly more involved than detergent fiber analysis methods. The purpose of this study was to determine whether it is feasible to correlate detergent fiber analysis values to glucan and xylan content determined by dietary fiber analysis methods for corn stover. In the detergent fiber analysis literature cellulose is often estimated as the difference between ADF and ADL, while hemicellulose is often estimated as the difference between NDF and ADF. Examination of a corn stover dataset containing both detergent fiber analysis data and dietary fiber analysis data predicted using near infrared spectroscopy shows that correlations between structural glucan measured using dietary fiber techniques and cellulose estimated using detergent techniques, and between structural xylan measured using dietary fiber techniques and hemicellulose estimated using detergent techniques are high, but are driven largely by the underlying correlation between total extractives measured by fiber analysis and NDF/ADF. That is, detergent analysis data is correlated to dietary fiber analysis data for structural carbohydrates, but only indirectly; the main correlation is between detergent analysis data and solvent extraction data produced during the dietary fiber analysis procedure.

  18. On the matched pairs sign test using bivariate ranked set sampling ...

    African Journals Online (AJOL)

    BVRSS) is introduced and investigated. We show that this test is asymptotically more efficient than its counterpart sign test based on a bivariate simple random sample (BVSRS). The asymptotic null distribution and the efficiency of the test are derived.

  19. 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.

  20. Predicting the Size of Sunspot Cycle 24 on the Basis of Single- and Bi-Variate Geomagnetic Precursor Methods

    Science.gov (United States)

    Wilson, Robert M.; Hathaway, David H.

    2009-01-01

    Examined are single- and bi-variate geomagnetic precursors for predicting the maximum amplitude (RM) of a sunspot cycle several years in advance. The best single-variate fit is one based on the average of the ap index 36 mo prior to cycle minimum occurrence (E(Rm)), having a coefficient of correlation (r) equal to 0.97 and a standard error of estimate (se) equal to 9.3. Presuming cycle 24 not to be a statistical outlier and its minimum in March 2008, the fit suggests cycle 24 s RM to be about 69 +/- 20 (the 90% prediction interval). The weighted mean prediction of 11 statistically important single-variate fits is 116 +/- 34. The best bi-variate fit is one based on the maximum and minimum values of the 12-mma of the ap index; i.e., APM# and APm*, where # means the value post-E(RM) for the preceding cycle and * means the value in the vicinity of cycle minimum, having r = 0.98 and se = 8.2. It predicts cycle 24 s RM to be about 92 +/- 27. The weighted mean prediction of 22 statistically important bi-variate fits is 112 32. Thus, cycle 24's RM is expected to lie somewhere within the range of about 82 to 144. Also examined are the late-cycle 23 behaviors of geomagnetic indices and solar wind velocity in comparison to the mean behaviors of cycles 2023 and the geomagnetic indices of cycle 14 (RM = 64.2), the weakest sunspot cycle of the modern era.

  1. Raster image correlation spectroscopy and number and brightness analysis.

    Science.gov (United States)

    Digman, Michelle A; Stakic, Milka; Gratton, Enrico

    2013-01-01

    The raster image correlation spectroscopy (RICS) and number and molecular brightness (N&B) methods are used to measure molecular diffusion in complex biological environments such as the cell interior, detect the formation of molecular aggregates, establish the stoichiometry of the aggregates, spatially map the number of mobile molecules, and quantify the relative fraction of molecules participating in molecular complexes. These methods are based on correlation of fluorescence intensity fluctuations from microscope images that can be measured in a conventional laser-scanning confocal microscope. In this chapter, we discuss the mathematical framework used for data analysis as well as the parameters need for data acquisition. We demonstrate the information obtainable by the N&B method using simulation in which different regions of an image have different numbers of interacting molecules. Then, using an example of two interacting proteins in the cell, we show in a real case how the RICS and N&B analyses work step by step to detect the existence of molecular complexes to quantify their properties and spatially map their interactions. We also discuss common control experiments needed to rule out instrumental artifacts and how to calibrate the microscope in terms of relative molecular brightness. Copyright © 2013 Elsevier Inc. All rights reserved.

  2. Interpreting Bivariate Regression Coefficients: Going beyond the Average

    Science.gov (United States)

    Halcoussis, Dennis; Phillips, G. Michael

    2010-01-01

    Statistics, econometrics, investment analysis, and data analysis classes often review the calculation of several types of averages, including the arithmetic mean, geometric mean, harmonic mean, and various weighted averages. This note shows how each of these can be computed using a basic regression framework. By recognizing when a regression model…

  3. 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.

  4. Estimating twin concordance for bivariate competing risks twin data

    DEFF Research Database (Denmark)

    Scheike, Thomas; Holst, Klaus K.; Hjelmborg, Jacob B.

    2014-01-01

    For twin time-to-event data, we consider different concordance probabilities, such as the casewise concordance that are routinely computed as a measure of the lifetime dependence/correlation for specific diseases. The concordance probability here is the probability that both twins have experienced...... over time, and covariates may be further influential on the marginal risk and dependence structure. We establish the estimators large sample properties and suggest various tests, for example, for inferring familial influence. The method is demonstrated and motivated by specific twin data on cancer...

  5. Correlation and spectra analysis of climate data sets

    Science.gov (United States)

    Byalko, Alexey

    2014-05-01

    In January 2013 O.Humlum, K.Stordahl, and J.Solheim published [1] a correlation and spectral analysis of inter-annual oscillations for multiple climate data sets covering the time span from 1980 to December 2011. A similar but independent study of other climate data was published in September last year [2]. Here the ENSO-index [3], global surface temperatures (GST) [4], and the Mauna Loa CO2 monthly data [5] were analyzed for the period 1958-2012. Methods of trend extraction in these two studies were similar but not the same. Nevertheless, three spectral lines coincided in [1, 2] within the exactness of the calculations. The corresponding periods are equal to 2.48(width 1%), 3.64(width 1%), and 9(width 2%) years. The line half-widths turned out to be from two to four times the theoretical limit related to the data length. The inter-correlation functions (covariance) showed lags in the order ENSO/GST/CO2. Analysis of longer data sets reveals higher covariance maximums (up to 0.74 for GST/CO2) with significantly lower lags than in [1]. We also seek a relation between the ENSO index and the 1962-2013 length of day (LOD) data [6]. The LOD/ENSO covariance reveals a rather low maximum about 0.2 with lag of +1 and width of 2 months. Such a nearly simultaneous covariance indicates a possible weak, coupled interaction between the Moon dynamics and the Pacific temperature and pressure oscillations. All the correlations mentioned above could provide better probability predictions for climate changes at the inter-annual scale. Literature 1. Humlum O., Stordahl K., Solheim J. The phase relation between atmospheric carbon dioxide and global temperature. Global and Planetary Change. V.100, 51-69 (2013). 2. Byalko A.V. Spectra of the Earth climate system perturbations. Priroda, No9, 23-32 (2013, in Russian). 3. Earth System Research Laboratory Extended Multivariate ENSO Index: http://www.esrl.noaa.gov/psd/enso/mei/table.html 4. National Climatic Data Center: ftp://ftp

  6. Classification of Knee Joint Vibration Signals Using Bivariate Feature Distribution Estimation and Maximal Posterior Probability Decision Criterion

    Directory of Open Access Journals (Sweden)

    Fang Zheng

    2013-04-01

    Full Text Available Analysis of knee joint vibration or vibroarthrographic (VAG signals using signal processing and machine learning algorithms possesses high potential for the noninvasive detection of articular cartilage degeneration, which may reduce unnecessary exploratory surgery. Feature representation of knee joint VAG signals helps characterize the pathological condition of degenerative articular cartilages in the knee. This paper used the kernel-based probability density estimation method to model the distributions of the VAG signals recorded from healthy subjects and patients with knee joint disorders. The estimated densities of the VAG signals showed explicit distributions of the normal and abnormal signal groups, along with the corresponding contours in the bivariate feature space. The signal classifications were performed by using the Fisher’s linear discriminant analysis, support vector machine with polynomial kernels, and the maximal posterior probability decision criterion. The maximal posterior probability decision criterion was able to provide the total classification accuracy of 86.67% and the area (Az of 0.9096 under the receiver operating characteristics curve, which were superior to the results obtained by either the Fisher’s linear discriminant analysis (accuracy: 81.33%, Az: 0.8564 or the support vector machine with polynomial kernels (accuracy: 81.33%, Az: 0.8533. Such results demonstrated the merits of the bivariate feature distribution estimation and the superiority of the maximal posterior probability decision criterion for analysis of knee joint VAG signals.

  7. 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.

  8. Evaluation of Factors Affecting E-Bike Involved Crash and E-Bike License Plate Use in China Using a Bivariate Probit Model

    OpenAIRE

    Guo, Yanyong; Zhou, Jibiao; Wu, Yao; Chen, Jingxu

    2017-01-01

    The primary objective of this study is to evaluate factors affecting e-bike involved crash and license plate use in China. E-bike crashes data were collected from police database and completed through a telephone interview. Noncrash samples were collected by a questionnaire survey. A bivariate probit (BP) model was developed to simultaneously examine the significant factors associated with e-bike involved crash and e-bike license plate and to account for the correlations between them. Margina...

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. 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

  14. Perceived social support and academic achievement: cross-lagged panel and bivariate growth curve analyses.

    Science.gov (United States)

    Mackinnon, Sean P

    2012-04-01

    As students transition to post-secondary education, they experience considerable stress and declines in academic performance. Perceived social support is thought to improve academic achievement by reducing stress. Longitudinal designs with three or more waves are needed in this area because they permit stronger causal inferences and help disentangle the direction of relationships. This study uses a cross-lagged panel and a bivariate growth curve analysis with a three-wave longitudinal design. Participants include 10,445 students (56% female; 12.6% born outside of Canada) transitioning to post-secondary education from ages 15-19. Self-report measures of academic achievement and a generalized measure of perceived social support were used. An increase in average relative standing in academic achievement predicted an increase in average relative standing on perceived social support 2 years later, but the reverse was not true. High levels of perceived social support at age 15 did not protect against declines in academic achievement over time. In sum, perceived social support appears to have no bearing on adolescents' future academic performance, despite commonly held assumptions of its importance.

  15. Bivariate empirical mode decomposition for ECG-based biometric identification with emotional data.

    Science.gov (United States)

    Ferdinando, Hany; Seppanen, Tapio; Alasaarela, Esko

    2017-07-01

    Emotions modulate ECG signals such that they might affect ECG-based biometric identification in real life application. It motivated in finding good feature extraction methods where the emotional state of the subjects has minimum impacts. This paper evaluates feature extraction based on bivariate empirical mode decomposition (BEMD) for biometric identification when emotion is considered. Using the ECG signal from the Mahnob-HCI database for affect recognition, the features were statistical distributions of dominant frequency after applying BEMD analysis to ECG signals. The achieved accuracy was 99.5% with high consistency using kNN classifier in 10-fold cross validation to identify 26 subjects when the emotional states of the subjects were ignored. When the emotional states of the subject were considered, the proposed method also delivered high accuracy, around 99.4%. We concluded that the proposed method offers emotion-independent features for ECG-based biometric identification. The proposed method needs more evaluation related to testing with other classifier and variation in ECG signals, e.g. normal ECG vs. ECG with arrhythmias, ECG from various ages, and ECG from other affective databases.

  16. Long-lead station-scale prediction of hydrological droughts in South Korea based on bivariate pattern-based downscaling

    Science.gov (United States)

    Sohn, Soo-Jin; Tam, Chi-Yung

    2016-05-01

    Capturing climatic variations in boreal winter to spring (December-May) is essential for properly predicting droughts in South Korea. This study investigates the variability and predictability of the South Korean climate during this extended season, based on observations from 60 station locations and multi-model ensemble (MME) hindcast experiments (1983/1984-2005/2006) archived at the APEC Climate Center (APCC). Multivariate empirical orthogonal function (EOF) analysis results based on observations show that the first two leading modes of winter-to-spring precipitation and temperature variability, which together account for ~80 % of the total variance, are characterized by regional-scale anomalies covering the whole South Korean territory. These modes were also closely related to some of the recurrent large-scale circulation changes in the northern hemisphere during the same season. Consistent with the above, examination of the standardized precipitation evapotranspiration index (SPEI) indicates that drought conditions in South Korea tend to be accompanied by regional-to-continental-scale circulation anomalies over East Asia to the western north Pacific. Motivated by the aforementioned findings on the spatial-temporal coherence among station-scale precipitation and temperature anomalies, a new bivariate and pattern-based downscaling method was developed. The novelty of this method is that precipitation and temperature data were first filtered using multivariate EOFs to enhance their spatial-temporal coherence, before being linked to large-scale circulation variables using canonical correlation analysis (CCA). To test its applicability and to investigate its related potential predictability, a perfect empirical model was first constructed with observed datasets as predictors. Next, a model output statistics (MOS)-type hybrid dynamical-statistical model was developed, using products from nine one-tier climate models as inputs. It was found that, with model sea

  17. Analysis of intermediate period correlations of coda from deep earthquakes

    Science.gov (United States)

    Poli, Piero; Campillo, Michel; de Hoop, Maarten

    2017-11-01

    We aim at assessing quantitatively the nature of the signals that appear in coda wave correlations at periods >20 s. These signals contain transient constituents with arrival times corresponding to deep seismic phases. These (body-wave) constituents can be used for imaging. To evaluate this approach, we calculate the autocorrelations of the vertical component seismograms for the Mw 8.4 sea of Okhotsk earthquake at 400 stations in the Eastern US, using data from 1 h before to 50 h after the earthquake. By using array analysis and modes identification, we discover the dominant role played by high quality factor normal modes in the emergence of strong coherent phases as ScS-like, and P'P'df-like. We then make use of geometrical quantization to derive the constituent rays associated with particular modes, and gain insights about the ballistic reverberation of the rays that contributes to the emergence of body waves. Our study indicates that the signals measured in the spatially averaged autocorrelations have a physical significance, but a direct interpretation of ScS-like and P'P'df-like is not trivial. Indeed, even a single simple measurement of long period late coda in a limited period band could provide valuable information on the deep structure by using the temporal information of its autocorrelation, a procedure that could be also useful for planetary exploration.

  18. Engineering Properties and Correlation Analysis of Fiber Cementitious Materials.

    Science.gov (United States)

    Lin, Wei-Ting; Wu, Yuan-Chieh; Cheng, An; Chao, Sao-Jeng; Hsu, Hui-Mi

    2014-11-20

    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.

  19. 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.

  20. Analysis of Consistency of Printing Blankets using Correlation Technique

    Directory of Open Access Journals (Sweden)

    Lalitha Jayaraman

    2010-01-01

    Full Text Available This paper presents the application of an analytical tool to quantify material consistency of offset printing blankets. Printing blankets are essentially viscoelastic rubber composites of several laminas. High levels of material consistency are expected from rubber blankets for quality print and for quick recovery from smash encountered during the printing process. The present study aims at determining objectively the consistency of printing blankets at three specific torque levels of tension under two distinct stages; 1. under normal printing conditions and 2. on recovery after smash. The experiment devised exhibits a variation in tone reproduction properties of each blanket signifying the levels of inconsistency also in thicknessdirection. Correlation technique was employed on ink density variations obtained from the blanket on paper. Both blankets exhibited good consistency over three torque levels under normal printing conditions. However on smash the recovery of blanket and its consistency was a function of manufacturing and torque levels. This study attempts to provide a new metrics for failure analysis of offset printing blankets. It also underscores the need for optimizing the torque for blankets from different manufacturers.

  1. Functional connectivity analysis of fMRI data based on regularized multiset canonical correlation analysis.

    Science.gov (United States)

    Deleus, Filip; Van Hulle, Marc M

    2011-04-15

    In this paper we describe a method for functional connectivity analysis of fMRI data between given brain regions-of-interest (ROIs). The method relies on nonnegativity constrained- and spatially regularized multiset canonical correlation analysis (CCA), and assigns weights to the fMRI signals of the ROIs so that their representative signals become simultaneously maximally correlated. The different pairwise correlations between the representative signals of the ROIs are combined using the maxvar approach for multiset CCA, which has been shown to be equivalent to the generalized eigenvector formulation of CCA. The eigenvector in the maxvar approach gives an indication of the relative importance of each ROI in obtaining a maximal overall correlation, and hence, can be interpreted as a functional connectivity pattern of the ROIs. The successive canonical correlations define subsequent functional connectivity patterns, in decreasing order of importance. We apply our method on synthetic data and real fMRI data and show its advantages compared to unconstrained CCA and to PCA. Furthermore, since the representative signals for the ROIs are optimized for maximal correlation they are also ideally suited for further effective connectivity analyses, to assess the information flows between the ROIs in the brain. Copyright © 2011 Elsevier B.V. All rights reserved.

  2. 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

  3. Analysis of embryo, cytoplasmic and maternal genetic correlations ...

    Indian Academy of Sciences (India)

    maintenance, reproduction and immunity in farm animals. (Wu 2009). An accurate ... Keywords. genetic main correlations; genotype × environment interaction correlations; rapeseed meal; amino acids contents; nutrient quality. Journal of ... cytoplasmic effects, maternal additive and dominance effects for individual amino ...

  4. Linear analysis of degree correlations in complex networks

    Indian Academy of Sciences (India)

    2016-11-02

    world property, the transitivity (or clustering), the scale-free .... To show their dif- ference, one can naturally define a correlation function, p(j, k) = ejk qj qk . (1) p(j, k) ≡ 1 means that the degree correlation is absent in the network ...

  5. 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 ...

  6. Towards a software approach to mitigate correlation power analysis

    CSIR Research Space (South Africa)

    Frieslaar, I

    2016-07-01

    Full Text Available been increased and in both scenarios the countermeasure has reduced the correlation accuracy and forced the CPA to predict the incorect key. The correlation accuracy has decreased from 97.6% to 53.6% on the ATmega microntroller and from 82% to 51...

  7. 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.

  8. A note on finding peakedness in bivariate normal distribution using Mathematica

    Directory of Open Access Journals (Sweden)

    Anwer Khurshid

    2007-07-01

    Full Text Available Peakedness measures the concentration around the central value. A classical standard measure of peakedness is kurtosis which is the degree of peakedness of a probability distribution. In view of inconsistency of kurtosis in measuring of the peakedness of a distribution, Horn (1983 proposed a measure of peakedness for symmetrically unimodal distributions. The objective of this paper is two-fold. First, Horn’s method has been extended for bivariate normal distribution. Secondly, to show that computer algebra system Mathematica can be extremely useful tool for all sorts of computation related to bivariate normal distribution. Mathematica programs are also provided.

  9. Causal networks clarify productivity-richness interrelations, bivariate plots do not

    Science.gov (United States)

    Grace, James B.; Adler, Peter B.; Harpole, W. Stanley; Borer, Elizabeth T.; Seabloom, Eric W.

    2014-01-01

    Perhaps no other pair of variables in ecology has generated as much discussion as species richness and ecosystem productivity, as illustrated by the reactions by Pierce (2013) and others to Adler et al.'s (2011) report that empirical patterns are weak and inconsistent. Adler et al. (2011) argued we need to move beyond a focus on simplistic bivariate relationships and test mechanistic, multivariate causal hypotheses. We feel the continuing debate over productivity–richness relationships (PRRs) provides a focused context for illustrating the fundamental difficulties of using bivariate relationships to gain scientific understanding.

  10. 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.

  11. 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

  12. 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.

  13. Analysis of transverse momentum correlations in hadronic Z decays

    CERN Document Server

    Barate, R; Décamp, D; Ghez, P; Goy, C; Lees, J P; Lucotte, A; Merle, E; Minard, M N; Nief, J Y; Perrodo, P; Pietrzyk, B; Alemany, R; Casado, M P; Chmeissani, M; Crespo, J M; Delfino, M C; Fernández, E; Fernández-Bosman, M; Garrido, L; Graugès-Pous, E; Juste, A; Martínez, M; Merino, G; Miquel, R; Mir, L M; Pacheco, A; Park, I C; Pascual, A; Riu, I; Sánchez, F; Colaleo, A; Creanza, D; De Palma, M; Gelao, G; Iaselli, Giuseppe; Maggi, G; Maggi, M; Nuzzo, S; Ranieri, A; Raso, G; Ruggieri, F; Selvaggi, G; Silvestris, L; Tempesta, P; Tricomi, A; Zito, G; Huang, X; Lin, J; Ouyang, Q; Wang, T; Xie, Y; Xu, R; Xue, S; Zhang, J; Zhang, L; Zhao, W; Abbaneo, D; Becker, U; Boix, G; Cattaneo, M; Cerutti, F; Ciulli, V; Dissertori, G; Drevermann, H; Forty, Roger W; Frank, M; Hagelberg, R; Halley, A W; Hansen, J B; Harvey, J; Janot, P; Jost, B; Lehraus, Ivan; Leroy, O; Mato, P; Minten, Adolf G; Moneta, L; Moutoussi, A; Ranjard, F; Rolandi, Luigi; Rousseau, D; Schlatter, W D; Schmitt, M; Schneider, O; Tejessy, W; Teubert, F; Tomalin, I R; Tournefier, E; Vreeswijk, M; Wachsmuth, H W; Ajaltouni, Ziad J; Badaud, F; Chazelle, G; Deschamps, O; Dessagne, S; Falvard, A; Ferdi, C; Gay, P; Guicheney, C; Henrard, P; Jousset, J; Michel, B; Monteil, S; Montret, J C; Pallin, D; Perret, P; Podlyski, F; Hansen, J D; Hansen, J R; Hansen, P H; Nilsson, B S; Rensch, B; Wäänänen, A; Daskalakis, G; Kyriakis, A; Markou, C; Simopoulou, Errietta; Siotis, I; Vayaki, Anna; Blondel, A; Bonneaud, G R; Brient, J C; Machefert, F P; Rougé, A; Rumpf, M; Swynghedauw, M; Tanaka, R; Valassi, Andrea; Verderi, M; Videau, H L; Focardi, E; Parrini, G; Zachariadou, K; Cavanaugh, R J; Corden, M; Georgiopoulos, C H; Hühn, T; Jaffe, D E; Antonelli, A; Bencivenni, G; Bologna, G; Bossi, F; Campana, P; Capon, G; Chiarella, V; Laurelli, P; Mannocchi, G; Murtas, F; Murtas, G P; Passalacqua, L; Pepé-Altarelli, M; Chalmers, M; Curtis, L; Lynch, J G; Negus, P; O'Shea, V; Raine, C; Scarr, J M; Teixeira-Dias, P; Thompson, A S; Thomson, E; Ward, J J; Buchmüller, O L; Dhamotharan, S; Geweniger, C; Hanke, P; Hansper, G; Hepp, V; Kluge, E E; Putzer, A; Sommer, J; Tittel, K; Werner, S; Wunsch, M; Beuselinck, R; Binnie, David M; Cameron, W; Dornan, Peter J; Girone, M; Goodsir, S M; Marinelli, N; Martin, E B; Nash, J; Sedgbeer, J K; Spagnolo, P; Williams, M D; Ghete, V M; Girtler, P; Kneringer, E; Kuhn, D; Rudolph, G; Betteridge, A P; Bowdery, C K; Buck, P G; Colrain, P; Crawford, G; Ellis, G; Finch, A J; Foster, F; Hughes, G; Jones, R W L; Robertson, N A; Williams, M; Van Gemmeren, P; Giehl, I; Hoffmann, C; Jakobs, K; Kleinknecht, K; Quast, G; Renk, B; Rohne, E; Sander, H G; Zeitnitz, C; Aubert, Jean-Jacques; Benchouk, C; Bonissent, A; Carr, J; Coyle, P; Etienne, F; Ealet, A; Motsch, F; Payre, P; Talby, M; Thulasidas, M; Aleppo, M; Antonelli, M; Ragusa, F; Berlich, R; Büscher, V; Dietl, H; Ganis, G; Hüttmann, K; Lütjens, G; Mannert, C; Männer, W; Moser, H G; Schael, S; Settles, Ronald; Seywerd, H C J; Stenzel, H; Wiedenmann, W; Wolf, G; Azzurri, P; Boucrot, J; Callot, O; Chen, S; Cordier, A; Davier, M; Duflot, L; Grivaz, J F; Heusse, P; Jacholkowska, A; Kim, D W; Le Diberder, F R; Lefrançois, J; Lutz, A M; Schune, M H; Veillet, J J; Videau, I; Zerwas, D; Bagliesi, G; Bettarini, S; Boccali, T; Bozzi, C; Calderini, G; Dell'Orso, R; Ferrante, I; Foà, L; Giassi, A; Gregorio, A; Ligabue, F; Lusiani, A; Marrocchesi, P S; Messineo, A; Palla, Fabrizio; Rizzo, G; Sanguinetti, G; Sciabà, A; Sguazzoni, G; Tenchini, Roberto; Vannini, C; Venturi, A; Verdini, P G; Blair, G A; Chambers, J T; Cowan, G D; Green, M G; Medcalf, T; Strong, J A; Von Wimmersperg-Töller, J H; Botterill, David R; Clifft, R W; Edgecock, T R; Norton, P R; Thompson, J C; Wright, A E; Bloch-Devaux, B; Colas, P; Emery, S; Kozanecki, Witold; Lançon, E; Lemaire, M C; Locci, E; Pérez, P; Rander, J; Renardy, J F; Roussarie, A; Schuller, J P; Schwindling, J; Trabelsi, A; Vallage, B; Black, S N; Dann, J H; Johnson, R P; Kim, H Y; Konstantinidis, N P; Litke, A M; McNeil, M A; Taylor, G; Booth, C N; Cartwright, S L; Combley, F; Kelly, M S; Lehto, M H; Thompson, L F; Affholderbach, K; Böhrer, A; Brandt, S; Grupen, Claus; Prange, G; Saraiva, P; Smolik, L; Stephan, F; Giannini, G; Gobbo, B; Rothberg, J E; Wasserbaech, S R; Armstrong, S R; Charles, E; Elmer, P; Ferguson, D P S; Gao, Y; González, S; Greening, T C; Hayes, O J; Hu, H; Jin, S; McNamara, P A; Nachtman, J M; Nielsen, J; Orejudos, W; Pan, Y B; Saadi, Y; Scott, I J; Walsh, J; Wu Sau Lan; Wu, X; Zobernig, G

    1999-01-01

    In a recent paper, evidence was presented for a significant,positive correlation between the total transverse momenta of particleson opposite hemispheres of hadronic events. A new, model independentanalysis of the data has been made. Two components can be distinguishedin the correlation, and quantitative estimates of each are given.The results form a significant test of Monte Carlo models and some of the physics behind them.

  14. Is the Meta-Analysis of Correlation Coefficients Accurate When Population Correlations Vary?

    Science.gov (United States)

    Field, Andy P.

    2005-01-01

    One conceptualization of meta-analysis is that studies within the meta-analysis are sampled from populations with mean effect sizes that vary (random-effects models). The consequences of not applying such models and the comparison of different methods have been hotly debated. A Monte Carlo study compared the efficacy of Hedges and Vevea's…

  15. New Colors for Histology: Optimized Bivariate Color Maps Increase Perceptual Contrast in Histological Images.

    Directory of Open Access Journals (Sweden)

    Jakob Nikolas Kather

    Full Text Available Accurate evaluation of immunostained histological images is required for reproducible research in many different areas and forms the basis of many clinical decisions. The quality and efficiency of histopathological evaluation is limited by the information content of a histological image, which is primarily encoded as perceivable contrast differences between objects in the image. However, the colors of chromogen and counterstain used for histological samples are not always optimally distinguishable, even under optimal conditions.In this study, we present a method to extract the bivariate color map inherent in a given histological image and to retrospectively optimize this color map. We use a novel, unsupervised approach based on color deconvolution and principal component analysis to show that the commonly used blue and brown color hues in Hematoxylin-3,3'-Diaminobenzidine (DAB images are poorly suited for human observers. We then demonstrate that it is possible to construct improved color maps according to objective criteria and that these color maps can be used to digitally re-stain histological images.To validate whether this procedure improves distinguishability of objects and background in histological images, we re-stain phantom images and N = 596 large histological images of immunostained samples of human solid tumors. We show that perceptual contrast is improved by a factor of 2.56 in phantom images and up to a factor of 2.17 in sets of histological tumor images.Thus, we provide an objective and reliable approach to measure object distinguishability in a given histological image and to maximize visual information available to a human observer. This method could easily be incorporated in digital pathology image viewing systems to improve accuracy and efficiency in research and diagnostics.

  16. New Colors for Histology: Optimized Bivariate Color Maps Increase Perceptual Contrast in Histological Images.

    Science.gov (United States)

    Kather, Jakob Nikolas; Weis, Cleo-Aron; Marx, Alexander; Schuster, Alexander K; Schad, Lothar R; Zöllner, Frank Gerrit

    2015-01-01

    Accurate evaluation of immunostained histological images is required for reproducible research in many different areas and forms the basis of many clinical decisions. The quality and efficiency of histopathological evaluation is limited by the information content of a histological image, which is primarily encoded as perceivable contrast differences between objects in the image. However, the colors of chromogen and counterstain used for histological samples are not always optimally distinguishable, even under optimal conditions. In this study, we present a method to extract the bivariate color map inherent in a given histological image and to retrospectively optimize this color map. We use a novel, unsupervised approach based on color deconvolution and principal component analysis to show that the commonly used blue and brown color hues in Hematoxylin-3,3'-Diaminobenzidine (DAB) images are poorly suited for human observers. We then demonstrate that it is possible to construct improved color maps according to objective criteria and that these color maps can be used to digitally re-stain histological images. To validate whether this procedure improves distinguishability of objects and background in histological images, we re-stain phantom images and N = 596 large histological images of immunostained samples of human solid tumors. We show that perceptual contrast is improved by a factor of 2.56 in phantom images and up to a factor of 2.17 in sets of histological tumor images. Thus, we provide an objective and reliable approach to measure object distinguishability in a given histological image and to maximize visual information available to a human observer. This method could easily be incorporated in digital pathology image viewing systems to improve accuracy and efficiency in research and diagnostics.

  17. The Effects of Selection Strategies for Bivariate Loglinear Smoothing Models on NEAT Equating Functions

    Science.gov (United States)

    Moses, Tim; Holland, Paul W.

    2010-01-01

    In this study, eight statistical strategies were evaluated for selecting the parameterizations of loglinear models for smoothing the bivariate test score distributions used in nonequivalent groups with anchor test (NEAT) equating. Four of the strategies were based on significance tests of chi-square statistics (Likelihood Ratio, Pearson,…

  18. First-order dominance: stronger characterization and a bivariate checking algorithm

    DEFF Research Database (Denmark)

    Range, Troels Martin; Østerdal, Lars Peter Raahave

    2018-01-01

    distributions. Utilizing that this problem can be formulated as a transportation problem with a special structure, we provide a stronger characterization of multivariate first-order dominance and develop a linear time complexity checking algorithm for the bivariate case. We illustrate the use of the checking...

  19. Semi-automated detection of aberrant chromosomes in bivariate flow karyotypes

    NARCIS (Netherlands)

    Boschman, G. A.; Manders, E. M.; Rens, W.; Slater, R.; Aten, J. A.

    1992-01-01

    A method is described that is designed to compare, in a standardized procedure, bivariate flow karyotypes of Hoechst 33258 (HO)/Chromomycin A3 (CA) stained human chromosomes from cells with aberrations with a reference flow karyotype of normal chromosomes. In addition to uniform normalization of

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

    African Journals Online (AJOL)

    Analysing the significance of geo-environmental variables influencing malaria incidence will help decision makers design area-specific interventions for tackling the menace, particularly in high-risk areas. This study applied geocoding and raster extraction functionalities in GIS (ArcMap) and Pearson correlation in SPSS to ...

  1. QTL mapping and correlation analysis for 1000-grain weight and ...

    Indian Academy of Sciences (India)

    Abstract. The study of 1000-grain weight (TGW) and percentage of grains with chalkiness (PGWC) is very important in rice. In this study, a set of introgression lines (ILs), derived from Sasanishiki/Habataki with Sasanishiki as the recurrent parent, were used to detect correlations and quantitative trait loci (QTL) on TGW and ...

  2. Correlation and path coefficient analysis of yield and agronomic ...

    African Journals Online (AJOL)

    A two-year study was conducted on maize (Zea mays L.) at the University of Ilorin Teaching and Research Farm Ilorin, Nigeria, during 2005 and 2006 growing seasons. The objective was to investigate correlation between grain yield and other agronomic parameters using 10 open-pollinated maize varieties and their 45 F1 ...

  3. microsatellite analysis of the correlation between molecular and ...

    African Journals Online (AJOL)

    Administrator

    correlation. The dissimilarity calculated using SSR markers had a mean morphological dissimilarity of 0.895403, an r value of -0.1421 and a p -0.9840. The dissimilarity between the molecular and morphological traits was. 0.860465. Comparison between the molecular and morphological data had a dissimilarity matrix with ...

  4. Analysis of embryo, cytoplasmic and maternal genetic correlations ...

    Indian Academy of Sciences (India)

    2School of Agriculture and Food Science, Zhejiang A & F University, Linan, 311300, People's Republic of China. Abstract. Genetic correlations of nutrient quality traits including lysine, ...... spectroscopy (NIRS) enables the fast and accurate prediction of essential amino acid contents. 2. Results for wheat, barley, corn, triticale ...

  5. Analysis of embryo, cytoplasmic and maternal genetic correlations ...

    Indian Academy of Sciences (India)

    Genetic correlations of nutrient quality traits including lysine, methionine, leucine, isoleucine, phenylalanine, valine and threonine contents in rapeseed meal were analysed by the genetic model for quantitative traits of diploid plants using a diallel design with nine parents of Brassica napus L. These results indicated that the ...

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

    African Journals Online (AJOL)

    Correlation studies provide a better understanding of the association of different characters with grain yield (Dixet and Dubey, 1984). The study of associations ... of 120 kg ha-1. The date of sowing was as prescribed by the treatments. Four irrigations were applied to the crop before withholding water to allow for proper ...

  7. 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)

  8. Finding Efficient Nonlinear Visual Operators using Canonical Correlation Analysis

    OpenAIRE

    Borga, Magnus; Knutsson, Hans

    2000-01-01

    This paper presents a general strategy for designing efficient visual operators. The approach is highly task oriented and what constitutes the relevant information is defined by a set of examples. The examples are pairs of images displaying a strong dependence in the chosen feature but are otherwise independent. Particularly important concepts in the work are mutual information and canonical correlation. Visual operators learned from examples are presented, e.g. local shift invariant orientat...

  9. 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

  10. 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

  11. 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.

  12. 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...

  13. 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.

  14. Carryover rate fraction correlation for LOFT safety analysis calculations

    International Nuclear Information System (INIS)

    Lin, J.C.; White, J.R.

    1979-01-01

    The Loss-of-Fluid Test (LOFT) facility contains a pressurized water nuclear reactor designed to scale the nuclear, thermal-hydraulic phenomena which would take place in a large pressurized water reactor (PWR) during a hypothetical loss-of-coolant accident (LOCA). This summary describes the development of a carryover rate fraction (CRF) correlation suitable for use in an evaluation model calculation for the reflooding phase of a LOFT experiment as well as the 3.6576-m core skewed axial power shape case. The CRF is defined as the ratio of mass rate entrained out of the core to the mass rate into the core

  15. 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.

  16. Cochlear otosclerosis (otospongiosis): CT analysis with audiometric correlation

    Energy Technology Data Exchange (ETDEWEB)

    Swartz, J.D.; Mandell, D.W.; Berman, S.E.; Wolfson, R.J.; Marlowe, F.I.; Popky, G.L.

    1985-04-01

    Ninety patients who had suspected or confirmed fenestral or cochlear otosclerosis underwent CT examination. Foci of demineralization in the otic capsule were discovered in 20 ears (12 patients). Audiometric studies of the 12 patients revealed sensorineural hearing loss (SNHL) with distinct correlation of CT findings with progressivity and with involvement of the frequency level subtended by the specific area of the cochlea involved. Foci of abnormal increased density, presumably representing the healed phase of this disorder, were found less frequently than expected. There was a predilection for the basilar turn. All patients had static SNHL in the higher frequencies. The healed phase of this disorder is probably not consistently diagnosable with CT.

  17. Bone calcium measurement: correlation between compartimental analysis and neutron activation determinations

    International Nuclear Information System (INIS)

    Fauran-Clavel, M.-J.; Oustrin, Jean; Maziere, Bernard; CEA, 91 - Orsay

    1980-01-01

    In cadmium exposed rats correlation analysis of calcium deep bone assessed by compartimental analysis and results of bone calcium determination by neutron activation shows a significative relationship between both values [fr

  18. Genetic analysis in retinoblastoma and peripheral blood correlation.

    Science.gov (United States)

    Ruiz del Río, N; Abelairas Gómez, J M; Alonso García de la Rosa, F J; Peralta Calvo, J M; de las Heras Martín, A

    2015-12-01

    To determine the importance of intratumoral genetic analysis in the diagnosis of germ-line mutations in patients with retinoblastoma. To underline the importance of performing these genetic tests in every case of retinoblastoma. Intratumoral genetic analysis of RB1 mutation was performed on 17 enucleated eyes that were non-responsive to conservative treatment. Patients had no family history of retinoblastoma, and lesions were always single. The identified mutations were then also studied in peripheral blood analysis. There were 12 (70.6%) cases with positive results in intratumoral analysis. In 8 cases (47.1%) mutation of both RB1 alelli were detected, and in 4 (23.5%) cases only one allele was found mutated. In 5 patients (29.4%) no mutation was identified. In the first hit, mutations comprised 7 frameshift or nonsense and 2 splice, whereas in the second hit, one splice mutation, 2 nonsense and 8 loss of heterozygosity were identified. Among 6 patients where intratumoral analysis detected a single mutation associated with a loss of heterozygosity, the peripheral blood analysis was able to detect the same mutation in 3 cases (50%). Intratumoral genetic analysis of sporadic retinoblastoma can detect germ-line mutations. These patients are at higher risk of bilateralization and development of second tumors or trilateral retinoblastoma. Genetic screening is recommended in every patient diagnosed with retinoblastoma. Copyright © 2013 Sociedad Española de Oftalmología. Published by Elsevier España, S.L.U. All rights reserved.

  19. 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.

  20. [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.

  1. correlation studies and path coefficient analysis for seed yield

    African Journals Online (AJOL)

    Prof. Adipala Ekwamu

    4.00 ... Yield being a quantitative trait has complex inheritance, which is subjected to environmental fluctuations ... Analysis for seed yield and yield components in Ethiopian coriander. 53 longest basal leaf, plant height at full maturity,.

  2. 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.

  3. 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.

  4. Correlative Analysis of GRBs detected by Swift, Konus and HETE

    Science.gov (United States)

    Krimm, Hans A.; Barthelmy, S. D.; Gehrels, N.; Hullinger, D.; Sakamoto, T.; Donaghy, T.; Lamb, D. Q.; Pal'shin, V.; Golenetskii, S.; Ricker, G. R.

    2005-01-01

    Swift has now detected a large enough sample of gamma-ray bursts (GRBs) to allow correlation studies of burst parameters. Such studies of earlier data sets have yielded important results leading to further understanding of burst parameters and classifications. This work focuses on seventeen Swift bursts that have also been detected either by Konus-Wind or HETE-II, providing high energy spectra and fits to E(sub peak). Eight of these bursts have spectroscopic redshifts and for others we can estimate redshifts using the variability/luminosity relationship. We can also compare E(sub peak) with E(sub iso), and for those bursts for which a jet break was observed in the afterglow we can derive E(sub g) and test the relationship between E(peak) and E(sub gamma). For all bursts we can derive durations and hardness ratios from the prompt emission.

  5. Correlation of the CT analysis and audiometry in otosclerosis

    Energy Technology Data Exchange (ETDEWEB)

    Kiyomizu, Kensuke; Tono, Tetsuya; Yang, Dewen; Haruta, Atsushi; Kodama, Takao; Kato, Eiji; Komune, Shizuo [Miyazaki Medical Coll., Kiyotake (Japan)

    1998-11-01

    Thirty-three patients (62 ears) with surgically confirmed otosclerosis underwent a preoperative CT examination in order to determine the presence of any correlation between the audiometric and CT findings. Based on the CT findings, the ears were classified into five groups as follows: group A; 25 ears (40.3%) with normal CT findings, group B1; 15 ears (24.2%) with demineralization in the region of the fissula antefenestram, group B2; 12 ears (19.4%) with demineralization around the anterior to the oval window, group B3; 4 ears (6.5%) with demineralization surrounding the cochlea, and group C; 6 ears (9.7%) with thick anterior and posterior plaques. The expansion of demineralization led to an increase in average bone conduction hearing level: group A ; 27.1 dB, group B1; 30.6 dB, group B2; 34.6 dB, group B3; 36.7 dB, and group C; 30.3 dB. This increase is most likely due to progressive labyrinthine otosclerosis. Group C in the average air-bone gap was greater (37.5 dB) than that in the patients with demineralization, group B1 (21.6 dB), group B2 (28.2 dB), group B3 (26.7 dB), the Carhart effect of group C was smaller than that of any other groups, thus suggesting the mode of otosclerosis progression in group C to be different from that in patients with demineralization. The results of the present study indicate that the preoperative CT findings of otosclerosis correlate with the audiometry findings, thus proving the usefulness of CT in diagnosing otosclerosis. (author)

  6. The approximation of bivariate Chlodowsky-Sz?sz-Kantorovich-Charlier-type operators

    OpenAIRE

    Agrawal, Purshottam Narain; Baxhaku, Behar; Chauhan, Ruchi

    2017-01-01

    Abstract In this paper, we introduce a bivariate Kantorovich variant of combination of Szász and Chlodowsky operators based on Charlier polynomials. Then, we study local approximation properties for these operators. Also, we estimate the approximation order in terms of Peetre’s K-functional and partial moduli of continuity. Furthermore, we introduce the associated GBS-case (Generalized Boolean Sum) of these operators and study the degree of approximation by means of the Lipschitz class of Bög...

  7. On minimum divergence adaptation of discrete bivariate distributions to given marginals

    Czech Academy of Sciences Publication Activity Database

    Vajda, Igor; van der Meulen, E. C.

    2005-01-01

    Roč. 51, č. 1 (2005), s. 313-320 ISSN 0018-9448 R&D Projects: GA ČR GA201/02/1391; GA MŠk 1M0572 Institutional research plan: CEZ:AV0Z10750506 Keywords : approximation of contingency tables * bivariate discrete distributions * minimization of divergences Subject RIV: BD - Theory of Information Impact factor: 2.183, year: 2005

  8. Robust bivariate error detection in skewed data with application to historical radiosonde winds

    KAUST Repository

    Sun, Ying

    2017-01-18

    The global historical radiosonde archives date back to the 1920s and contain the only directly observed measurements of temperature, wind, and moisture in the upper atmosphere, but they contain many random errors. Most of the focus on cleaning these large datasets has been on temperatures, but winds are important inputs to climate models and in studies of wind climatology. The bivariate distribution of the wind vector does not have elliptical contours but is skewed and heavy-tailed, so we develop two methods for outlier detection based on the bivariate skew-t (BST) distribution, using either distance-based or contour-based approaches to flag observations as potential outliers. We develop a framework to robustly estimate the parameters of the BST and then show how the tuning parameter to get these estimates is chosen. In simulation, we compare our methods with one based on a bivariate normal distribution and a nonparametric approach based on the bagplot. We then apply all four methods to the winds observed for over 35,000 radiosonde launches at a single station and demonstrate differences in the number of observations flagged across eight pressure levels and through time. In this pilot study, the method based on the BST contours performs very well.

  9. 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 ...

  10. Kinetics and correlation analysis of reactivity in the oxidation of ...

    Indian Academy of Sciences (India)

    Administrator

    Department of Chemistry, J.N.V. University, Jodhpur 342 005. 1. 4F/13, New Power House Road, Jodhpur 342 ... The rates of oxidation of sulfides were determined in nineteen organic solvents. An analysis of the solvent effect by ... report the kinetics of the oxidation of 34 organic sul- fides by BTPPD in dimethyl sulphoxide ...

  11. A Latent Growth Analysis of Social Correlates for Early Literacy

    Science.gov (United States)

    Townsend, Monika

    2010-01-01

    Reading growth from preschool to Grade 5 was evaluated in a sample of 964 children using multi-group latent growth curve analysis. Groups consisted of children assigned to six different school readiness profiles based on social and cognitive characteristics. Results indicate modes interrelationships between kindergarten readiness profiles, teacher…

  12. Kinetics and correlation analysis of reactivity in the oxidation of ...

    Indian Academy of Sciences (India)

    The rates of oxidation of sulfides were determined in nineteen organic solvents. An analysis of the solvent effect by multi-parametric equations indicated the relatively greater importance of the cation-solvating power of the solvents. A mechanism involving a single-step electrophilic oxygen transfer from BTPPD to the sulfide ...

  13. analysis and correlation of stability parameters in malting barley

    African Journals Online (AJOL)

    Administrator

    Interaction principal component axis (IPCA) scores,. Additive .... TABLE 1. Additive main effects and multiplicative interactions (AMMI) analysis of variance for grain yield of 20 genotypes of ... BLE 2. Mean grain yield and genotypic stability parameters for 20 malting barley genotypes grown over 12 environments in Ethiopia.

  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. Rankings and preferences new results in weighted correlation and weighted principal component analysis with applications

    CERN Document Server

    Pinto da Costa, Joaquim

    2015-01-01

    This book examines in detail the correlation, more precisely the weighted correlation, and applications involving rankings. A general application is the evaluation of methods to predict rankings. Others involve rankings representing human preferences to infer user preferences; the use of weighted correlation with microarray data and those in the domain of time series. In this book we present new weighted correlation coefficients and new methods of weighted principal component analysis. We also introduce new methods of dimension reduction and clustering for time series data, and describe some theoretical results on the weighted correlation coefficients in separate sections.

  18. Correlative Analysis of GRBs Detected by Swift and Suzaku- WAM

    Science.gov (United States)

    Krimm, H.A.; Sakamoto, T.; Yamaoka, K.; Sugita, S.; Ohno, M.; Sato, G.; Hara, R.; Ohmori, N.; Tanaka, H.; Yamauchi, M.; hide

    2009-01-01

    It is now well known that a complete understanding of the energetics of the prompt phase of gamma-ray bursts (GRBs) requires full knowledge of the spectrum, extending at least as high as the peak energy (Epeak) of the vF(v) spectrum. Since most gamma-ray bursts (GRBs) have Epeak above the energy range (15-150 keV) of the Burst Alert Telescope (BAT) on Swift, a full understanding of the prompt emission from Swift GRBs requires spectral fits over as broad an energy range as possible. This can be completed for bursts which are simultaneously detected by Swift BAT and the Suzaku Wide-band All-Sky Monitor (WAM), which covers the energy range from 50-5000 keV. Between the launch of Suzaku in July 2005 and the end of 2008, there were 44 gamma-ray bursts (GRBs) which triggered both Swift and WAM and an additional 41 bursts which triggered Swift and were detected by WAM, but did not trigger. A joint BAT-WAM team has cross-calibrated the two instruments using GRBs, and we are now able to perform joint fits on these bursts to determine spectral parameters including Epeak. The results of broad spectral fits allows us to understand the distribution of Epeak for Swift bursts and to calibrate Epeak estimators when Epeak is within the BAT energy range. For those bursts with spectroscopic redshifts, we can calculate the isotropic energy and study various correlations between Epeak and other global burst parameters. Here we present the results of joint Swift/BAT-Suzaku/WAM spectral fits for 77 of the bursts jointly detected by the two instruments. We show that the distribution of spectral fit parameters is consistent with distributions from earlier missions and confirm that Swift bursts are consistent with earlier reported relationships between Epeak and isotropic energy. We show through time-resolved spectroscopy that individual burst pulses are also consistent with this relationship.

  19. Subjective facial analysis and its correlation with dental relationships

    Directory of Open Access Journals (Sweden)

    Gustavo Silva Siécola

    Full Text Available ABSTRACT INTRODUCTION: Subjective facial analysis is a diagnostic method that provides morphological analysis of the face. Thus, the aim of the present study was to compare the facial and dental diagnoses and investigate their relationship. METHODS: This sample consisted of 151 children (7 to 13 years old, without previous orthodontic treatment, analyzed by an orthodontist. Standardized extraoral and intraoral photographs were taken for the subjective facial classification according to Facial Pattern classification and occlusal analyses. It has been researched the occurrence of different Facial Patterns, the relationship between Facial Pattern classification in frontal and profile views, the relationship between Facial Patterns and Angle classification, and between anterior open bite and Long Face Pattern. RESULTS: Facial Pattern I was verified in 64.24% of the children, Pattern II in 21.29%, Pattern III in 6.62%, Long Face Pattern in 5.96% and Short Face Pattern in 1.99%. A substantial strength of agreement of approximately 84% between frontal and profile classification of Facial Pattern was observed (Kappa = 0.69. Agreement between the Angle classification and the Facial Pattern was seen in approximately 63% of the cases (Kappa = 0.27. Long Face Pattern did not present more open bite prevalence. CONCLUSION: Facial Patterns I and II were the most prevalent in children and the less prevalent was the Short Face Pattern. A significant concordance was observed between profile and frontal subjective facial analysis. There was slight concordance between the Facial Pattern and the sagittal dental relationships. The anterior open bite (AOB was not significantly prevalent in any Facial Pattern.

  20. The use of bivariate spatial modeling of questionnaire and parasitology data to predict the distribution of Schistosoma haematobium in Coastal Kenya.

    Directory of Open Access Journals (Sweden)

    Hugh J W Sturrock

    Full Text Available Questionnaires of reported blood in urine (BIU distributed through the existing school system provide a rapid and reliable method to classify schools according to the prevalence of Schistosoma haematobium, thereby helping in the targeting of schistosomiasis control. However, not all schools return questionnaires and it is unclear whether treatment is warranted in such schools. This study investigates the use of bivariate spatial modelling of available and multiple data sources to predict the prevalence of S. haematobium at every school along the Kenyan coast.Data from a questionnaire survey conducted by the Kenya Ministry of Education in Coast Province in 2009 were combined with available parasitological and environmental data in a Bayesian bivariate spatial model. This modeled the relationship between BIU data and environmental covariates, as well as the relationship between BIU and S. haematobium infection prevalence, to predict S. haematobium infection prevalence at all schools in the study region. Validation procedures were implemented to assess the predictive accuracy of endemicity classification.The prevalence of BIU was negatively correlated with distance to nearest river and there was considerable residual spatial correlation at small (~15 km spatial scales. There was a predictable relationship between the prevalence of reported BIU and S. haematobium infection. The final model exhibited excellent sensitivity (0.94 but moderate specificity (0.69 in identifying low (<10% prevalence schools, and had poor performance in differentiating between moderate and high prevalence schools (sensitivity 0.5, specificity 1.Schistosomiasis is highly focal and there is a need to target treatment on a school-by-school basis. The use of bivariate spatial modelling can supplement questionnaire data to identify schools requiring mass treatment, but is unable to distinguish between moderate and high prevalence schools.

  1. 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

    2018-01-25

    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).

  2. 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.

  3. A correlation analysis on chlorophyll content and SPAD value in tomato leaves

    OpenAIRE

    JIANG, Chengyao; JOHKAN, Masahumi; HOHJO, Masaaki; TSUKAGOSHI, Satoru; MATURO, Toru

    2017-01-01

    [Abstract] To investigate relationship between tomato (Solanum lycopersicum) leaf chlorophyll content and Minolta SPAD-502 plus chlorophyll meter, we studied leaves at plant vegetative growth stage and reproductive growth stage, and conducted correlation analysis to establish most optimal function model. The results showed that the correlation of SPAD value and the content of chlorophyll a, chlorophyll b and total chlorophyll content were significantly correlated in tomato leaves. At plant ve...

  4. Statistical power analyses using G*Power 3.1: tests for correlation and regression analyses.

    Science.gov (United States)

    Faul, Franz; Erdfelder, Edgar; Buchner, Axel; Lang, Albert-Georg

    2009-11-01

    G*Power is a free power analysis program for a variety of statistical tests. We present extensions and improvements of the version introduced by Faul, Erdfelder, Lang, and Buchner (2007) in the domain of correlation and regression analyses. In the new version, we have added procedures to analyze the power of tests based on (1) single-sample tetrachoric correlations, (2) comparisons of dependent correlations, (3) bivariate linear regression, (4) multiple linear regression based on the random predictor model, (5) logistic regression, and (6) Poisson regression. We describe these new features and provide a brief introduction to their scope and handling.

  5. 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.

  6. 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

  7. 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.

  8. 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

  9. Canonical correlation analysis in education: associations between student evaluations of courses and instructors

    DEFF Research Database (Denmark)

    Sliusarenko, Tamara; Clemmensen, Line Katrine Harder

    correlation analysis (CCA) to investigate the association between how students evaluate the course and how students evaluate the teacher and to reveal the structure of this association. Student’s evaluation data is characterized by high correlation between the variables (questions) and insufficient sample...

  10. Calculation and optimization of sample identification by laser induced breakdown spectroscopy via correlation analysis

    NARCIS (Netherlands)

    Lentjes, M.; Dickmann, K.; Meijer, J.

    2007-01-01

    Linear correlation analysis may be used as a technique for the identification of samples with a very similar chemical composition by laser induced breakdown spectroscopy. The spectrum of the “unknown” sample is correlated with a library of reference spectra. The probability of identification by

  11. Dissection of genomic correlation matrices of US Holsteins using multivariate factor analysis

    Science.gov (United States)

    Aim of the study was to compare correlation matrices between direct genomic predictions for 31 production, fitness and conformation traits both at genomic and chromosomal level in US Holstein bulls. Multivariate factor analysis was used to quantify basic features of correlation matrices. Factor extr...

  12. Effects of Correlated Errors on the Analysis of Space Geodetic Data

    Science.gov (United States)

    Romero-Wolf, Andres; Jacobs, C. S.

    2011-01-01

    As thermal errors are reduced instrumental and troposphere correlated errors will increasingly become more important. Work in progress shows that troposphere covariance error models improve data analysis results. We expect to see stronger effects with higher data rates. Temperature modeling of delay errors may further reduce temporal correlations in the data.

  13. 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.

  14. 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.

  15. Binary naive Bayesian classifiers for correlated Gaussian features: a theoretical analysis

    CSIR Research Space (South Africa)

    Van Dyk, E

    2008-11-01

    Full Text Available We investigate the use of Naive Bayesian classifiers for correlated Gaussian feature spaces and derive error estimates for these classifiers. The error analysis is done by developing an exact expression for the error performance of a binary...

  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. 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...

  18. Vapor Pressure Data Analysis and Correlation Methodology for Data Spanning the Melting Point

    Science.gov (United States)

    2013-10-01

    specimen is adequately degassed, the liquid menisci in the U-tube are brought to the same level and the pressure read on the manometer . The measurement...VAPOR PRESSURE DATA ANALYSIS AND CORRELATION METHODOLOGY FOR DATA SPANNING THE MELTING POINT ECBC-CR-135 David E...REPORT TYPE Final 3. DATES COVERED (From - To) Mar 2013 - June 2013 4. TITLE AND SUBTITLE Vapor Pressure Data Analysis and Correlation Methodology

  19. 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.

  20. 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.

  1. 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.

  2. Cross-correlation in flow-injection analysis with parallel flow streams and amperometric detection.

    Science.gov (United States)

    McKean, R E; Curran, D J

    1992-03-01

    Cross-correlation was implemented for flow-injection analysis by using two parallel flow lines, each with amperometric detectors, and driven by peristaltic pumps. One flow line was used to generate the reference signal for an analog correlator circuit and the other to generate the analyte signal. Cross-correlation was performed by multiplying these signals together at a time delay of zero, followed by low pass filtering. Using dopamine as a test system, improvements in signal-to-noise ratios of about two orders of magnitude were found for the correlation signal over the direct measurement of the electrode current.

  3. A COMPARISON OF SOME ROBUST BIVARIATE CONTROL CHARTS FOR INDIVIDUAL OBSERVATIONS

    Directory of Open Access Journals (Sweden)

    Moustafa Omar Ahmed Abu - Shawiesh

    2014-06-01

    Full Text Available This paper proposed and considered some bivariate control charts to monitor individual observations from a statistical process control. Usual control charts which use mean and variance-covariance estimators are sensitive to outliers. We consider the following robust alternatives to the classical Hoteling's T2: T2MedMAD, T2MCD, T2MVE a simulation study has been conducted to compare the performance of these control charts. Two real life data are analyzed to illustrate the application of these robust alternatives.

  4. The approximation of bivariate Chlodowsky-Szász-Kantorovich-Charlier-type operators

    Directory of Open Access Journals (Sweden)

    Purshottam Narain Agrawal

    2017-08-01

    Full Text Available Abstract In this paper, we introduce a bivariate Kantorovich variant of combination of Szász and Chlodowsky operators based on Charlier polynomials. Then, we study local approximation properties for these operators. Also, we estimate the approximation order in terms of Peetre’s K-functional and partial moduli of continuity. Furthermore, we introduce the associated GBS-case (Generalized Boolean Sum of these operators and study the degree of approximation by means of the Lipschitz class of Bögel continuous functions. Finally, we present some graphical examples to illustrate the rate of convergence of the operators under consideration.

  5. The approximation of bivariate Chlodowsky-Szász-Kantorovich-Charlier-type operators.

    Science.gov (United States)

    Agrawal, Purshottam Narain; Baxhaku, Behar; Chauhan, Ruchi

    2017-01-01

    In this paper, we introduce a bivariate Kantorovich variant of combination of Szász and Chlodowsky operators based on Charlier polynomials. Then, we study local approximation properties for these operators. Also, we estimate the approximation order in terms of Peetre's K-functional and partial moduli of continuity. Furthermore, we introduce the associated GBS-case (Generalized Boolean Sum) of these operators and study the degree of approximation by means of the Lipschitz class of Bögel continuous functions. Finally, we present some graphical examples to illustrate the rate of convergence of the operators under consideration.

  6. 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.

  7. A Universal High-Performance Correlation Analysis Detection Model and Algorithm for Network Intrusion Detection System

    Directory of Open Access Journals (Sweden)

    Hongliang Zhu

    2017-01-01

    Full Text Available In big data era, the single detection techniques have already not met the demand of complex network attacks and advanced persistent threats, but there is no uniform standard to make different correlation analysis detection be performed efficiently and accurately. In this paper, we put forward a universal correlation analysis detection model and algorithm by introducing state transition diagram. Based on analyzing and comparing the current correlation detection modes, we formalize the correlation patterns and propose a framework according to data packet timing and behavior qualities and then design a new universal algorithm to implement the method. Finally, experiment, which sets up a lightweight intrusion detection system using KDD1999 dataset, shows that the correlation detection model and algorithm can improve the performance and guarantee high detection rates.

  8. 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.

  9. Bivariate tensor product [Formula: see text]-analogue of Kantorovich-type Bernstein-Stancu-Schurer operators.

    Science.gov (United States)

    Cai, Qing-Bo; Xu, Xiao-Wei; Zhou, Guorong

    2017-01-01

    In this paper, we construct a bivariate tensor product generalization of Kantorovich-type Bernstein-Stancu-Schurer operators based on the concept of [Formula: see text]-integers. We obtain moments and central moments of these operators, give the rate of convergence by using the complete modulus of continuity for the bivariate case and estimate a convergence theorem for the Lipschitz continuous functions. We also give some graphs and numerical examples to illustrate the convergence properties of these operators to certain functions.

  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. A bivariate space-time downscaler under space and time misalignment.

    Science.gov (United States)

    Berrocal, Veronica J; Gelfand, Alan E; Holland, David M

    2010-12-01

    Ozone and particulate matter PM(2.5) are co-pollutants that have long been associated with increased public health risks. Information on concentration levels for both pollutants come from two sources: monitoring sites and output from complex numerical models that produce concentration surfaces over large spatial regions. In this paper, we offer a fully-model based approach for fusing these two sources of information for the pair of co-pollutants which is computationally feasible over large spatial regions and long periods of time. Due to the association between concentration levels of the two environmental contaminants, it is expected that information regarding one will help to improve prediction of the other. Misalignment is an obvious issue since the monitoring networks for the two contaminants only partly intersect and because the collection rate for PM(2.5) is typically less frequent than that for ozone.Extending previous work in Berrocal et al. (2009), we introduce a bivariate downscaler that provides a flexible class of bivariate space-time assimilation models. We discuss computational issues for model fitting and analyze a dataset for ozone and PM(2.5) for the ozone season during year 2002. We show a modest improvement in predictive performance, not surprising in a setting where we can anticipate only a small gain.

  13. Probabilistic modeling using bivariate normal distributions for identification of flow and displacement intervals in longwall overburden

    Energy Technology Data Exchange (ETDEWEB)

    Karacan, C.O.; Goodman, G.V.R. [NIOSH, Pittsburgh, PA (United States). Off Mine Safety & Health Research

    2011-01-15

    Gob gas ventholes (GGV) are used to control methane emissions in longwall mines by capturing it within the overlying fractured strata before it enters the work environment. In order for GGVs to effectively capture more methane and less mine air, the length of the slotted sections and their proximity to top of the coal bed should be designed based on the potential gas sources and their locations, as well as the displacements in the overburden that will create potential flow paths for the gas. In this paper, an approach to determine the conditional probabilities of depth-displacement, depth-flow percentage, depth-formation and depth-gas content of the formations was developed using bivariate normal distributions. The flow percentage, displacement and formation data as a function of distance from coal bed used in this study were obtained from a series of borehole experiments contracted by the former US Bureau of Mines as part of a research project. Each of these parameters was tested for normality and was modeled using bivariate normal distributions to determine all tail probabilities. In addition, the probability of coal bed gas content as a function of depth was determined using the same techniques. The tail probabilities at various depths were used to calculate conditional probabilities for each of the parameters. The conditional probabilities predicted for various values of the critical parameters can be used with the measurements of flow and methane percentage at gob gas ventholes to optimize their performance.

  14. Xp21 contiguous gene syndromes: Deletion quantitation with bivariate flow karyotyping allows mapping of patient breakpoints

    Energy Technology Data Exchange (ETDEWEB)

    McCabe, E.R.B.; Towbin, J.A. (Baylor College of Medicine, Houston, TX (United States)); Engh, G. van den; Trask, B.J. (Lawrence Livermore National Lab., CA (United States))

    1992-12-01

    Bivariate flow karyotyping was used to estimate the deletion sizes for a series of patients with Xp21 contiguous gene syndromes. The deletion estimates were used to develop an approximate scale for the genomic map in Xp21. The bivariate flow karyotype results were compared with clinical and molecular genetic information on the extent of the patients' deletions, and these various types of data were consistent. The resulting map spans >15 Mb, from the telomeric interval between DXS41 (99-6) and DXS68 (1-4) to a position centromeric to the ornithine transcarbamylase locus. The deletion sizing was considered to be accurate to [plus minus]1 Mb. The map provides information on the relative localization of genes and markers within this region. For example, the map suggests that the adrenal hypoplasia congenita and glycerol kinase genes are physically close to each other, are within 1-2 Mb of the telomeric end of the Duchenne muscular dystrophy (DMD) gene, and are nearer to the DMD locus than to the more distal marker DXS28 (C7). Information of this type is useful in developing genomic strategies for positional cloning in Xp21. These investigations demonstrate that the DNA from patients with Xp21 contiguous gene syndromes can be valuable reagents, not only for ordering loci and markers but also for providing an approximate scale to the map of the Xp21 region surrounding DMD. 44 refs., 3 figs.

  15. Bivariate pointing movements on large touch screens: investigating the validity of a refined Fitts' Law.

    Science.gov (United States)

    Bützler, Jennifer; Vetter, Sebastian; Jochems, Nicole; Schlick, Christopher M

    2012-01-01

    On the basis of three empirical studies Fitts' Law was refined for bivariate pointing tasks on large touch screens. In the first study different target width parameters were investigated. The second study considered the effect of the motion angle. Based on the results of the two studies a refined model for movement time in human-computer interaction was formulated. A third study, which is described here in detail, concerns the validation of the refined model. For the validation study 20 subjects had to execute a bivariate pointing task on a large touch screen. In the experimental task 250 rectangular target objects were displayed at a randomly chosen position on the screen covering a broad range of ID values (ID= [1.01; 4.88]). Compared to existing refinements of Fitts' Law, the new model shows highest predictive validity. A promising field of application of the model is the ergonomic design and evaluation of project management software. By using the refined model, software designers can calculate a priori the appropriate angular position and the size of buttons, menus or icons.

  16. Non-stationary random vibration analysis of structures under multiple correlated normal random excitations

    Science.gov (United States)

    Li, Yanbin; Mulani, Sameer B.; Kapania, Rakesh K.; Fei, Qingguo; Wu, Shaoqing

    2017-07-01

    An algorithm that integrates Karhunen-Loeve expansion (KLE) and the finite element method (FEM) is proposed to perform non-stationary random vibration analysis of structures under excitations, represented by multiple random processes that are correlated in both time and spatial domains. In KLE, the auto-covariance functions of random excitations are discretized using orthogonal basis functions. The KLE for multiple correlated random excitations relies on expansions in terms of correlated sets of random variables reflecting the cross-covariance of the random processes. During the response calculations, the eigenfunctions of KLE used to represent excitations are applied as forcing functions to the structure. The proposed algorithm is applied to a 2DOF system, a 2D cantilever beam and a 3D aircraft wing under both stationary and non-stationary correlated random excitations. Two methods are adopted to obtain the structural responses: a) the modal method and b) the direct method. Both the methods provide the statistics of the dynamic response with sufficient accuracy. The structural responses under the same type of correlated random excitations are bounded by the response obtained by perfectly correlated and uncorrelated random excitations. The structural response increases with a decrease in the correlation length and with an increase in the correlation magnitude. The proposed methodology can be applied for the analysis of any complex structure under any type of random excitation.

  17. 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.

  18. 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.

  19. 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

  20. Identification of extragalactic sources of the highest energy EGRET photons by correlation analysis

    CERN Document Server

    Gorbunov, D.S.; Tkachev, I.I.; Troitsky, Sergey V.

    2005-01-01

    We found significant correlations between the arrival directions of the highest energy photons (E>10 GeV) observed by EGRET and positions of the BL Lac type objects (BL Lacs). The observed correlations imply that not less than three per cent of extragalactic photons at these energies originate from BL Lacs. Some of the correlating BL Lacs have no counterparts in the EGRET source catalog, i.e. do not coincide with strong emitters of gamma-rays at lower energy. The study of correlating BL Lacs suggests that they may form a subset which is statistically different from the total BL Lac catalog; we argue that they are prominent candidates for TeV gamma-ray sources. Our results demonstrate that the analysis of positional correlations is a powerful approach indispensable in cases when low statistics limits or even prohibits the standard case-by-case identification.

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

    Science.gov (United States)

    Kern, Christoph; Kortüm, Karsten; Müller, Michael; Raabe, Florian; Mayer, Wolfgang Johann; Priglinger, Siegfried; Kreutzer, Thomas Christian

    2016-01-01

    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. PMID:27601872

  2. Multifractal Detrended Cross-Correlation Analysis for Large-Scale Warehouse-Out Behaviors

    Science.gov (United States)

    Yao, Can-Zhong; Lin, Ji-Nan; Zheng, Xu-Zhou

    2015-09-01

    Based on cross-correlation algorithm, we analyze the correlation property of warehouse-out quantity of different warehouses, respectively, and different products of each warehouse. Our study identifies that significant cross-correlation relationship for warehouse-out quantity exists among different warehouses and different products of a warehouse. Further, we take multifractal detrended cross-correlation analysis for warehouse-out quantity among different warehouses and different products of a warehouse. The results show that for the warehouse-out behaviors of total amount, different warehouses and different products of a warehouse significantly follow multifractal property. Specifically for each warehouse, the coupling relationships of rebar and wire rod reveal long-term memory characteristics, no matter for large fluctuation or small one. The cross-correlation effect on long-range memory property among warehouses probably has less to do with product types,and the long-term memory of YZ warehouse is greater than others especially in total amount and wire rod product. Finally, we shuffle and surrogate data to explore the source of multifractal cross-correlation property in logistics system. Taking the total amount of warehouse-out quantity as example, we confirm that the fat-tail distribution of warehouse-out quantity sequences is the main factor for multifractal cross-correlation. Through comparing the performance of the multifractal detrended cross-correlation analysis (MF-DCCA), centered multifractal detrending moving average cross-correlation analysis (MF-X-DMA) algorithms, the forward and backward MF-X-DMA algorithms, we find that the forward and backward MF-X-DMA algorithms exhibit a better performance than the other ones.

  3. Multifractal detrended cross-correlation analysis between the Chinese stock market and surrounding stock markets

    Science.gov (United States)

    Ma, Feng; Wei, Yu; Huang, Dengshi

    2013-04-01

    In this paper, we investigate the cross-correlations between the stock market in China and markets in Japan, South Korea and Hong Kong. We use not only the qualitative analysis of the cross-correlation test, but also the quantitative analysis of the MF-X-DFA. Our findings confirm the existence of cross-correlations between the stock market in China and markets in Japan, South Korea and Hong Kong, which have strongly multifractal features. We find that the cross-correlations display the characteristic of multifractality in the short term. Moreover, the cross-correlations of small fluctuations are persistent and those of large fluctuations are anti-persistent in the short term, while the cross-correlations of all kinds of fluctuations are persistent in the long term. Furthermore, based on the multifractal spectrum, we also find that the multifractality of cross-correlation between stock markets in China and Japan are stronger than those between China and South Korea, as well as between China and Hong Kong.

  4. Path analysis and canonical correlations for indirect selection of Jatropha genotypes with higher oil yield.

    Science.gov (United States)

    Silva, L A; Peixoto, L A; Teodoro, P E; Rodrigues, E V; Laviola, B G; Bhering, L L

    2017-03-22

    Jatropha is a species with great potential for biodiesel production, and the knowledge on how the main agronomic traits are correlated will contribute to its improvement. Therefore, the objectives of this study were to estimate the genetic parameters of the traits: plant height at 12 and 40 months, canopy projection on the row at 12 and 40 months, canopy projection between the row at 12 and 40 months, number of branches at 40 months, grain yield, and oil yield; to verify the existence of phenotypic correlation between these traits; to verify the influence of the morphological traits on oil yield by means of path analysis; and to evaluate the relationship between the productive traits in Jatropha and the morphological traits measured at different ages. Sixty-seven half-sib families were evaluated using a completely randomized block design with two replications and five plants per plot. Analysis of variance was used to estimate the genetic value. Phenotypic correlations were given by the Pearson correlation between traits. For the canonical correlation analysis, two groups of traits were established: group I, consisting of traits of economic importance for the culture, and group II, consisting of morphological traits. Path analysis was carried out considering oil yield as the main dependent variable. Genetic variability was observed among Jatropha families. Productive traits can be indirectly selected via morphological traits due to the correlation between these two groups of traits. Therefore, canonical correlations and path analysis are two strategies that may be useful in Jatropha-breeding program when the objective is to select productive traits via morphological traits.

  5. A Bivariate Chebyshev Spectral Collocation Quasilinearization Method for Nonlinear Evolution Parabolic Equations

    Directory of Open Access Journals (Sweden)

    S. S. Motsa

    2014-01-01

    Full Text Available This paper presents a new method for solving higher order nonlinear evolution partial differential equations (NPDEs. The method combines quasilinearisation, the Chebyshev spectral collocation method, and bivariate Lagrange interpolation. In this paper, we use the method to solve several nonlinear evolution equations, such as the modified KdV-Burgers equation, highly nonlinear modified KdV equation, Fisher's equation, Burgers-Fisher equation, Burgers-Huxley equation, and the Fitzhugh-Nagumo equation. The results are compared with known exact analytical solutions from literature to confirm accuracy, convergence, and effectiveness of the method. There is congruence between the numerical results and the exact solutions to a high order of accuracy. Tables were generated to present the order of accuracy of the method; convergence graphs to verify convergence of the method and error graphs are presented to show the excellent agreement between the results from this study and the known results from literature.

  6. Comparison between different uncertainty propagation methods in multivariate analysis: An application in the bivariate case

    International Nuclear Information System (INIS)

    Mullor, R.; Sanchez, A.; Martorell, S.; Martinez-Alzamora, N.

    2011-01-01

    Safety related systems performance optimization is classically based on quantifying the effects that testing and maintenance activities have on reliability and cost (R+C). However, R+C quantification is often incomplete in the sense that important uncertainties may not be considered. An important number of studies have been published in the last decade in the field of R+C based optimization considering uncertainties. They have demonstrated that inclusion of uncertainties in the optimization brings the decision maker insights concerning how uncertain the R+C results are and how this uncertainty does matter as it can result in differences in the outcome of the decision making process. Several methods of uncertainty propagation based on the theory of tolerance regions have been proposed in the literature depending on the particular characteristics of the variables in the output and their relations. In this context, the objective of this paper focuses on the application of non-parametric and parametric methods to analyze uncertainty propagation, which will be implemented on a multi-objective optimization problem where reliability and cost act as decision criteria and maintenance intervals act as decision variables. Finally, a comparison of results of these applications and the conclusions obtained are presented.

  7. Comparison between different uncertainty propagation methods in multivariate analysis: An application in the bivariate case

    Energy Technology Data Exchange (ETDEWEB)

    Mullor, R. [Dpto. Estadistica e Investigacion Operativa, Universidad Alicante (Spain); Sanchez, A., E-mail: aisanche@eio.upv.e [Dpto. Estadistica e Investigacion Operativa Aplicadas y Calidad, Universidad Politecnica Valencia, Camino de Vera s/n 46022 (Spain); Martorell, S. [Dpto. Ingenieria Quimica y Nuclear, Universidad Politecnica Valencia (Spain); Martinez-Alzamora, N. [Dpto. Estadistica e Investigacion Operativa Aplicadas y Calidad, Universidad Politecnica Valencia, Camino de Vera s/n 46022 (Spain)

    2011-06-15

    Safety related systems performance optimization is classically based on quantifying the effects that testing and maintenance activities have on reliability and cost (R+C). However, R+C quantification is often incomplete in the sense that important uncertainties may not be considered. An important number of studies have been published in the last decade in the field of R+C based optimization considering uncertainties. They have demonstrated that inclusion of uncertainties in the optimization brings the decision maker insights concerning how uncertain the R+C results are and how this uncertainty does matter as it can result in differences in the outcome of the decision making process. Several methods of uncertainty propagation based on the theory of tolerance regions have been proposed in the literature depending on the particular characteristics of the variables in the output and their relations. In this context, the objective of this paper focuses on the application of non-parametric and parametric methods to analyze uncertainty propagation, which will be implemented on a multi-objective optimization problem where reliability and cost act as decision criteria and maintenance intervals act as decision variables. Finally, a comparison of results of these applications and the conclusions obtained are presented.

  8. Attenuation of vagal modulation with aging: Univariate and bivariate analysis of HRV.

    Science.gov (United States)

    Junior, E C; Oliveira, F M

    2017-07-01

    The aging process leads to diverse changes in the human organism, including in autonomic system modulation. In this study, we calculated indices of HRV in frequency (power spectral density, PSD) and time (the impulse response (IR) method) domains, using data from healthy young and elderly volunteers (Fantasia database from Physionet). The results obtained showed that aging leads to an attenuation of vagal modulation of elderly individuals when compared to young volunteers.

  9. Correlation of Ultrasound Shear Wave Elastography with Pathological Analysis in a Xenografic Tumour Model

    DEFF Research Database (Denmark)

    Elyas, Eli; Papaevangelou, Efthymia; Alles, Erwin J

    2017-01-01

    The objective of this study was to evaluate the potential value of ultrasound (US) shear wave elastography (SWE) in assessing the relative change in elastic modulus in colorectal adenocarcinoma xenograft models in vivo and investigate any correlation with histological analysis. We sought to test...... = 0.37, p = 0.008). Irinotecan administration caused significant delay in the tumour growth (p = 0.02) when compared to control, but no significant difference in elastic modulus was detected. Histological analysis revealed a significant correlation between tumour necrosis and elastic modulus (r = -0...

  10. Temporal correlation analysis between malaria and meteorological factors in Motuo County, Tibet

    Directory of Open Access Journals (Sweden)

    Tang Linhua

    2011-03-01

    Full Text Available Abstract Background Malaria has been endemic in Linzhi Prefecture in the Tibet Autonomous Region (TAR over the past 20 years, especially in Motou County with a highest incidence in the country in recent years. Meteorological factors, such as rainfall, temperature and relative humidity in Motou County were unique compared to other areas in Tibet as well as other parts of China, thus the objective of this work was to analyse the temporal correlation between malaria incidence and meteorological factors in Motou County, in order to seek the particular interventions for malaria control. Methods The meteorological and malaria data during 1986-2009 in Motuo County were studied to analyse the statistical relationship between meteorological data time series and malaria incidence data series. Temporal correlation between malaria incidence and meteorological factors were analyzed using several statistical methods. Spearman correlation analysis was conducted to examine the association between monthly malaria incidence and meteorological variables. Cross-correlation analysis of monthly malaria incidence series and monthly meteorological data time series revealed the time lag(s of meteorological factors preceding malaria at which the series showed strongest correlation. Multiplicative seasonal auto-regressive integrated moving average (SARIMA models were used in the cross-correlation analysis with pre-whitening which remove seasonality and auto-correlation of meteorological data series. Differenced data analysis which called inter-annual analysis was carried out to find underlying relationship between malaria data series and meteorological data series. Results It has been revealed that meteorological variables, such as temperature, relative humidity and rainfall were the important environmental factors in the transmission of malaria. Spearman correlation analysis demonstrated relative humidity was greatest relative to malaria incidence and the correlation

  11. 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)

  12. Nonlinear Analysis of Diastolic Heart Sounds Based on EMD and Correlation Dimension

    Directory of Open Access Journals (Sweden)

    Zhidong Zhao

    2014-06-01

    Full Text Available Recent studies have applied nonlinear analysis methods for heart sounds to diagnose coronary artery disease (CAD. Coronary artery occlusion may cause diastolic heart murmurs, so analysis of diastolic heart murmurs has important significance to noninvasive diagnosis of CAD. Heart sound signal is typical nonlinear and non-stationary time series, nonlinear analysis method - correlation dimension can effectively describe the nonlinear characteristics of heart sound signals, but the analysis of the correlation dimension shows that trend terms in the heart sound signals may lead to erroneous results. Empirical mode decomposition (EMD is adaptive to remove trend for non-stationary signal, so a method combining EMD and correlation dimension was proposed for nonlinear analysis of diastolic heart sound signals. The EMD method was applied to reconstruct heart sound signals after removing trend, and the correlation dimension for reconstructed heart sound signals was used as characteristics to distinguish between normal heart sound signals and CAD heart sound signals. The diastolic heart sounds of 15 normal people and 15 patients with CAD were analyzed in the experiment, and the results showed that the proposed method can effectively distinguish between normal people and patients with CAD.

  13. Constructing ecological interaction networks by correlation analysis: hints from community sampling

    Directory of Open Access Journals (Sweden)

    WenJun Zhang

    2011-09-01

    Full Text Available A set of methodology for constructing ecological interaction networks by correlation analysis of community sampling data was presented in this study. Nearly 30 data sets at different levels of taxa for different sampling seasons and locations were used to construct networks and find network properties. I defined the network constructed by Pearson linear correlation is the linear network, and the network constructed by quasi-linear correlation measure (e.g., Spearman correlation is the quasi-linear network. Two taxa with statistically significant linear or quasi-linear correlation are determined to interact. The quasi-linear network is more general than linear network.The results reveled that correlation distributions of Pearson linear correlation and partial linear correlation constructed networks are unimodal functions and most of them are short-head (mostly negative correlations and long-tailed (mostly positive correlations. Spearman correlation distributions are either long-head and short-tailed unimodal functions or monotonically increasing functions. It was found that both mean partial linear correlation and mean Pearson linear correlation were approximately 0. The proportion of positive (partial linear correlations declined significantly with the increase in taxa. The mean (partial linear correlation declined significantly with the increase of taxa. More than 90% of network interactions are positive interactions. The average connectance was 9.8% (9.3% for (partial linear correlation constructed network. The parameter λ in power low distribution (L(x=x-λ increased as the decline of taxon level (from functional group to species for the partial linear correlation constructed network. λ is in average 0.8 to 0.9. The number of (positive interactions increased with the number of taxa for both linear and partial linear correlations constructed networks. The addition of a taxon would result in an increase of 0.4 (0.3 interactions (positive

  14. 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

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. 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

  20. 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

  1. 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

  2. Phenotypic and genotypic correlations between soybean agronomic traits and path analysis.

    Science.gov (United States)

    Machado, B Q V; Nogueira, A P O; Hamawaki, O T; Rezende, G F; Jorge, G L; Silveira, I C; Medeiros, L A; Hamawaki, R L; Hamawaki, C D L

    2017-06-20

    The goals of this research were to evaluate the phenotypic and genotypic correlations between agronomic traits, to perform path analysis, having as main character grain yield, and to identify indirect selection criteria for grain yield. The experiment was carried out in an experimental area located at Capim Branco farm, which belongs to Federal University of Uberlândia, during the growing season of 2015/2016.Twenty-four soybean genotypes were evaluated under randomized complete block design with three repetitions, of which agronomic traits and grain yield were measured. There was genetic variability for all traits at 5% probability level through the F-test. Thirty significant phenotypic correlations were also observed with values oscillating from 0.42 to 0.87, which indicated a high level of association between some evaluated traits. Additionally, we verified that phenotypic and genotypic correlations were essential of the same direction, being the genotypic ones of superior magnitudes. Plants with superior vegetative cycle had longer life cycles; this fact could be explained by the significant phenotypic correlations between the number of days to the blooming and number of days to maturity (0.76). Significantly positive phenotypic and genotypic correlations for the total number of pods per plant and grain yield per plant (0.84) were observed. Through the path analysis, the trait that contributed the most over grain yield was the number of pods with three seeds as it showed the highest direct effect on grain yield per plant, as well as a strong indirect effect on the total number of pods. Therefore, the phenotypic and genotypic correlations suggested high correlations between grain yield and number of branched nodes, the number of pods with two and three seeds, and the total number of pods. Also, the path analysis determined the number of pods with three seeds as having the highest favorable effect on grain yield, and thus, being useful for indirect selection

  3. Analysis of the enhanced negative correlation between electron density and electron temperature related to earthquakes

    Science.gov (United States)

    Shen, X. H.; Zhang, X.; Liu, J.; Zhao, S. F.; Yuan, G. P.

    2015-04-01

    Ionospheric perturbations in plasma parameters have been observed before large earthquakes, but the correlation between different parameters has been less studied in previous research. The present study is focused on the relationship between electron density (Ne) and temperature (Te) observed by the DEMETER (Detection of Electro-Magnetic Emissions Transmitted from Earthquake Regions) satellite during local nighttime, in which a positive correlation has been revealed near the equator and a weak correlation at mid- and low latitudes over both hemispheres. Based on this normal background analysis, the negative correlation with the lowest percent in all Ne and Te points is studied before and after large earthquakes at mid- and low latitudes. The multiparameter observations exhibited typical synchronous disturbances before the Chile M8.8 earthquake in 2010 and the Pu'er M6.4 in 2007, and Te varied inversely with Ne over the epicentral areas. Moreover, statistical analysis has been done by selecting the orbits at a distance of 1000 km and ±7 days before and after the global earthquakes. Enhanced negative correlation coefficients lower than -0.5 between Ne and Te are found in 42% of points to be connected with earthquakes. The correlation median values at different seismic levels show a clear decrease with earthquakes larger than 7. Finally, the electric-field-coupling model is discussed; furthermore, a digital simulation has been carried out by SAMI2 (Sami2 is Another Model of the Ionosphere), which illustrates that the external electric field in the ionosphere can strengthen the negative correlation in Ne and Te at a lower latitude relative to the disturbed source due to the effects of the geomagnetic field. Although seismic activity is not the only source to cause the inverse Ne-Te variations, the present results demonstrate one possibly useful tool in seismo-electromagnetic anomaly differentiation, and a comprehensive analysis with multiple parameters helps to

  4. 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)

  5. Genetic correlation and path analysis of common bean collected from Caceres Mato Grosso State, Brazil

    Directory of Open Access Journals (Sweden)

    Danilo de Lima Gonçalves

    Full Text Available ABSTRACT: The aim of the study was to determine genetic correlations of agronomic traits and to evaluate direct and indirect effects, through path analysis, between variables analyzed with grain yield. Forty accessions of common bean, cultivated at Caceres County were evaluated, by using randomized complete blocks design with three repetitions. Coefficient magnitudes of genotypic correlations were superior to phenotypic and environmental ones for most correlations, suggesting greater influence of genetic factor than environmental factors. In order to determine the importance of direct and indirect effects, path analysis was performed, which provided greater reliability in interpretations of cause and effect between studied traits, indicating that grain yield may be explained by the effects of analyzed traits. Number of seeds per plant (0.801 and grain weight (0.641 showed higher favorable effect over grain yield, allowing its use in direct or indirect selection for grain yield in common bean.

  6. Spatiotemporal image correlation analysis of blood flow in branched vessel networks of zebrafish embryos

    Science.gov (United States)

    Ceffa, Nicolo G.; Cesana, Ilaria; Collini, Maddalena; D'Alfonso, Laura; Carra, Silvia; Cotelli, Franco; Sironi, Laura; Chirico, Giuseppe

    2017-10-01

    Ramification of blood circulation is relevant in a number of physiological and pathological conditions. The oxygen exchange occurs largely in the capillary bed, and the cancer progression is closely linked to the angiogenesis around the tumor mass. Optical microscopy has made impressive improvements in in vivo imaging and dynamic studies based on correlation analysis of time stacks of images. Here, we develop and test advanced methods that allow mapping the flow fields in branched vessel networks at the resolution of 10 to 20 μm. The methods, based on the application of spatiotemporal image correlation spectroscopy and its extension to cross-correlation analysis, are applied here to the case of early stage embryos of zebrafish.

  7. 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.

  8. 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.

  9. Particle image identification and correlation analysis in microscopic holographic particle image velocimetry

    International Nuclear Information System (INIS)

    Wormald, S. Andrew; Coupland, Jeremy

    2009-01-01

    This paper discusses the different analysis methods used in holographic particle image velocimetry to measure particle displacement and compares their relative performance. A digital holographic microscope is described and is used to record the light scattered by particles deposited on cover slides that are displaced between exposures. In this way, particle position and displacement are controlled and a numerical data set is generated. Data extraction using nearest neighbor analysis and correlation of either the reconstructed complex amplitude or intensity fields is then investigated.

  10. Particle image identification and correlation analysis in microscopic holographic particle image velocimetry

    Energy Technology Data Exchange (ETDEWEB)

    Wormald, S. Andrew; Coupland, Jeremy

    2009-11-20

    This paper discusses the different analysis methods used in holographic particle image velocimetry to measure particle displacement and compares their relative performance. A digital holographic microscope is described and is used to record the light scattered by particles deposited on cover slides that are displaced between exposures. In this way, particle position and displacement are controlled and a numerical data set is generated. Data extraction using nearest neighbor analysis and correlation of either the reconstructed complex amplitude or intensity fields is then investigated.

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

    Indian Academy of Sciences (India)

    tion in numerical models and validation exercises of physical parameters obtained by different means. An auto-correlation analysis of ocean surface winds based on available time series over the Bay of Bengal was reported in our earlier work (Sarkar et al 2002). The present note attempts to carry out a similar exercise for ...

  12. Bootstrap Confidence Intervals for Ordinary Least Squares Factor Loadings and Correlations in Exploratory Factor Analysis

    Science.gov (United States)

    Zhang, Guangjian; Preacher, Kristopher J.; Luo, Shanhong

    2010-01-01

    This article is concerned with using the bootstrap to assign confidence intervals for rotated factor loadings and factor correlations in ordinary least squares exploratory factor analysis. Coverage performances of "SE"-based intervals, percentile intervals, bias-corrected percentile intervals, bias-corrected accelerated percentile…

  13. 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...

  14. 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

  15. 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

  16. 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

  17. Variability, correlation and path co-eeficient analysis for yield and its ...

    African Journals Online (AJOL)

    this study, fourteen rice (Oryza sativa L.) genotypes at the Gezira Research Station Farm (GRSF), Sudan were assessed for genetic variability and correlations between yield and yield components among phenotypic markers and polygenic trait analysis. A wider genetic variability was observed among the genotypes for most ...

  18. 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

  19. Thermal Analysis and Correlation of the Mars Odyssey Spacecraft's Solar Array During Aerobraking Operations

    Science.gov (United States)

    Dec, John A.; Gasbarre, Joseph F.; George, Benjamin E.

    2002-01-01

    The Mars Odyssey spacecraft made use of multipass aerobraking to gradually reduce its orbit period from a highly elliptical insertion orbit to its final science orbit. Aerobraking operations provided an opportunity to apply advanced thermal analysis techniques to predict the temperature of the spacecraft's solar array for each drag pass. Odyssey telemetry data was used to correlate the thermal model. The thermal analysis was tightly coupled to the flight mechanics, aerodynamics, and atmospheric modeling efforts being performed during operations. Specifically, the thermal analysis predictions required a calculation of the spacecraft's velocity relative to the atmosphere, a prediction of the atmospheric density, and a prediction of the heat transfer coefficients due to aerodynamic heating. Temperature correlations were performed by comparing predicted temperatures of the thermocouples to the actual thermocouple readings from the spacecraft. Time histories of the spacecraft relative velocity, atmospheric density, and heat transfer coefficients, calculated using flight accelerometer and quaternion data, were used to calculate the aerodynamic heating. During aerobraking operations, the correlations were used to continually update the thermal model, thus increasing confidence in the predictions. This paper describes the thermal analysis that was performed and presents the correlations to the flight data.

  20. 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.

  1. Contributory fault and level of personal injury to drivers involved in head-on collisions: Application of copula-based bivariate ordinal models.

    Science.gov (United States)

    Wali, Behram; Khattak, Asad J; Xu, Jingjing

    2018-01-01

    The main objective of this study is to simultaneously investigate the degree of injury severity sustained by drivers involved in head-on collisions with respect to fault status designation. This is complicated to answer due to many issues, one of which is the potential presence of correlation between injury outcomes of drivers involved in the same head-on collision. To address this concern, we present seemingly unrelated bivariate ordered response models by analyzing the joint injury severity probability distribution of at-fault and not-at-fault drivers. Moreover, the assumption of bivariate normality of residuals and the linear form of stochastic dependence implied by such models may be unduly restrictive. To test this, Archimedean copula structures and normal mixture marginals are integrated into the joint estimation framework, which can characterize complex forms of stochastic dependencies and non-normality in residual terms. The models are estimated using 2013 Virginia police reported two-vehicle head-on collision data, where exactly one driver is at-fault. The results suggest that both at-fault and not-at-fault drivers sustained serious/fatal injuries in 8% of crashes, whereas, in 4% of the cases, the not-at-fault driver sustained a serious/fatal injury with no injury to the at-fault driver at all. Furthermore, if the at-fault driver is fatigued, apparently asleep, or has been drinking the not-at-fault driver is more likely to sustain a severe/fatal injury, controlling for other factors and potential correlations between the injury outcomes. While not-at-fault vehicle speed affects injury severity of at-fault driver, the effect is smaller than the effect of at-fault vehicle speed on at-fault injury outcome. Contrarily, and importantly, the effect of at-fault vehicle speed on injury severity of not-at-fault driver is almost equal to the effect of not-at-fault vehicle speed on injury outcome of not-at-fault driver. Compared to traditional ordered probability

  2. Bivariate tensor product ( p , q $(p, q$ -analogue of Kantorovich-type Bernstein-Stancu-Schurer operators

    Directory of Open Access Journals (Sweden)

    Qing-Bo Cai

    2017-11-01

    Full Text Available Abstract In this paper, we construct a bivariate tensor product generalization of Kantorovich-type Bernstein-Stancu-Schurer operators based on the concept of ( p , q $(p, q$ -integers. We obtain moments and central moments of these operators, give the rate of convergence by using the complete modulus of continuity for the bivariate case and estimate a convergence theorem for the Lipschitz continuous functions. We also give some graphs and numerical examples to illustrate the convergence properties of these operators to certain functions.

  3. 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.

  4. Neuroimaging support for discrete neural correlates of basic emotions: a voxel-based meta-analysis.

    Science.gov (United States)

    Vytal, Katherine; Hamann, Stephan

    2010-12-01

    What is the basic structure of emotional experience and how is it represented in the human brain? One highly influential theory, discrete basic emotions, proposes a limited set of basic emotions such as happiness and fear, which are characterized by unique physiological and neural profiles. Although many studies using diverse methods have linked particular brain structures with specific basic emotions, evidence from individual neuroimaging studies and from neuroimaging meta-analyses has been inconclusive regarding whether basic emotions are associated with both consistent and discriminable regional brain activations. We revisited this question, using activation likelihood estimation (ALE), which allows spatially sensitive, voxelwise statistical comparison of results from multiple studies. In addition, we examined substantially more studies than previous meta-analyses. The ALE meta-analysis yielded results consistent with basic emotion theory. Each of the emotions examined (fear, anger, disgust, sadness, and happiness) was characterized by consistent neural correlates across studies, as defined by reliable correlations with regional brain activations. In addition, the activation patterns associated with each emotion were discrete (discriminable from the other emotions in pairwise contrasts) and overlapped substantially with structure-function correspondences identified using other approaches, providing converging evidence that discrete basic emotions have consistent and discriminable neural correlates. Complementing prior studies that have demonstrated neural correlates for the affective dimensions of arousal and valence, the current meta-analysis results indicate that the key elements of basic emotion views are reflected in neural correlates identified by neuroimaging studies.

  5. Statistical analysis of fluorescence correlation spectroscopy: the standard deviation and bias.

    Science.gov (United States)

    Saffarian, Saveez; Elson, Elliot L

    2003-03-01

    We present a detailed statistical analysis of fluorescence correlation spectroscopy for a wide range of timescales. The derivation is completely analytical and can provide an excellent tool for planning and analysis of FCS experiments. The dependence of the signal-to-noise ratio on different measurement conditions is extensively studied. We find that in addition to the shot noise and the noise associated with correlated molecular dynamics there is another source of noise that appears at very large lag times. We call this the "particle noise," as its behavior is governed by the number of particles that have entered and left the laser beam sample volume during large dwell times. The standard deviations of all the points on the correlation function are calculated analytically and shown to be in good agreement with experiments. We have also investigated the bias associated with experimental correlation function measurements. A "phase diagram" for FCS experiments is constructed that demonstrates the significance of the bias for any given experiment. We demonstrate that the value of the bias can be calculated and added back as a first-order correction to the experimental correlation function.

  6. Correlation between gait analysis and clinical questionnaires in patients with spontaneous osteonecrosis of the knee.

    Science.gov (United States)

    Debi, Ronen; Mor, Amit; Elbaz, Avi; Segal, Ganit; Lubovsky, Omri; Kahn, Gadi; Peskin, Bezalel; Beer, Yiftah; Atoun, Ehud

    2017-05-01

    Spontaneous osteonecrosis of the knee is usually verified by magnetic resonance imaging accompanied by clinical questionnaires to assess the level of pain and functional limitation. There is a lack however, in an objective functional test that will reflect the functional severity of spontaneous osteonecrosis of the knee. The purpose of the current study was to examine the correlation between spatiotemporal gait parameters and clinical questionnaires in patients with spontaneous osteonecrosis of the knee. 28 patients (16 females and 12 males) were included in the analysis. Patients had unilateral spontaneous osteonecrosis of the knee of the medial femoral condyle confirmed by magnetic resonance imaging. All patients performed a computerized spatiotemporal gait analysis and completed the Western Ontario and McMaster University Osteoarthritis Index and the Short-Form 36. Relationships between selected spatiotemporal gait measures and self-assessment questionnaires were assessed by Spearman non-parametric correlations. Significant correlations were found between selected spatiotemporal gait parameters and clinical questionnaires (r ranged between 0.28 and 0.79). Single limb support was the gait measure with the strongest correlation to pain (r=0.58), function (r=0.56) and quality of life. Spatiotemporal gait assessment for patients with spontaneous osteonecrosis of the knee correlates with the patient's level of pain and functional limitation there by adding objective information regarding the functional condition of these patients. Copyright © 2017 Elsevier Ltd. All rights reserved.

  7. 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.

  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. Space-time correlation analysis of traffic flow on road network

    Science.gov (United States)

    Su, Fei; Dong, Honghui; Jia, Limin; Tian, Zhao; Sun, Xuan

    2017-02-01

    Space-time correlation analysis has become a basic and critical work in the research on road traffic congestion. It plays an important role in improving traffic management quality. The aim of this research is to examine the space-time correlation of road networks to determine likely requirements for building a suitable space-time traffic model. In this paper, it is carried out using traffic flow data collected on Beijing’s road network. In the framework, the space-time autocorrelation function (ST-ACF) is introduced as global measure, and cross-correlation function (CCF) as local measure to reveal the change mechanism of space-time correlation. Through the use of both measures, the correlation is found to be dynamic and heterogeneous in space and time. The finding of seasonal pattern present in space-time correlation provides a theoretical assumption for traffic forecasting. Besides, combined with Simpson’s rule, the CCF is also applied to finding the critical sections in the road network, and the experiments prove that it is feasible in computability, rationality and practicality.

  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. 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…

  13. 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.

  14. Anatomy-Correlated Breast Imaging and Visual Grading Analysis Using Quantitative Transmission Ultrasound™

    Directory of Open Access Journals (Sweden)

    John C. Klock

    2016-01-01

    Full Text Available Objectives. This study presents correlations between cross-sectional anatomy of human female breasts and Quantitative Transmission (QT Ultrasound, does discriminate classifier analysis to validate the speed of sound correlations, and does a visual grading analysis comparing QT Ultrasound with mammography. Materials and Methods. Human cadaver breasts were imaged using QT Ultrasound, sectioned, and photographed. Biopsies confirmed microanatomy and areas were correlated with QT Ultrasound images. Measurements were taken in live subjects from QT Ultrasound images and values of speed of sound for each identified anatomical structure were plotted. Finally, a visual grading analysis was performed on images to determine whether radiologists’ confidence in identifying breast structures with mammography (XRM is comparable to QT Ultrasound. Results. QT Ultrasound identified all major anatomical features of the breast, and speed of sound calculations showed specific values for different breast tissues. Using linear discriminant analysis overall accuracy is 91.4%. Using visual grading analysis readers scored the image quality on QT Ultrasound as better than on XRM in 69%–90% of breasts for specific tissues. Conclusions. QT Ultrasound provides accurate anatomic information and high tissue specificity using speed of sound information. Quantitative Transmission Ultrasound can distinguish different types of breast tissue with high resolution and accuracy.

  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. Effects of Tropospheric Spatio-Temporal Correlated Noise on the Analysis of Space Geodetic Data

    Science.gov (United States)

    Romero-Wolf, A.; Jacobs, C. S.; Ratcliff, J. T.

    2012-01-01

    The standard VLBI analysis models the distribution of measurement noise as Gaussian. Because the price of recording bits is steadily decreasing, thermal errors will soon no longer dominate. As a result, it is expected that troposphere and instrumentation/clock errors will increasingly become more dominant. Given that both of these errors have correlated spectra, properly modeling the error distributions will become increasingly relevant for optimal analysis. We discuss the advantages of modeling the correlations between tropospheric delays using a Kolmogorov spectrum and the frozen flow assumption pioneered by Treuhaft and Lanyi. We then apply these correlated noise spectra to the weighting of VLBI data analysis for two case studies: X/Ka-band global astrometry and Earth orientation. In both cases we see improved results when the analyses are weighted with correlated noise models vs. the standard uncorrelated models. The X/Ka astrometric scatter improved by approx.10% and the systematic Delta delta vs. delta slope decreased by approx. 50%. The TEMPO Earth orientation results improved by 17% in baseline transverse and 27% in baseline vertical.

  17. A Pragmatic Bayesian Perspective on Correlation Analysis : The exoplanetary gravity - stellar activity case.

    Science.gov (United States)

    Figueira, P; Faria, J P; Adibekyan, V Zh; Oshagh, M; Santos, N C

    2016-11-01

    We apply the Bayesian framework to assess the presence of a correlation between two quantities. To do so, we estimate the probability distribution of the parameter of interest, ρ, characterizing the strength of the correlation. We provide an implementation of these ideas and concepts using python programming language and the pyMC module in a very short (∼ 130 lines of code, heavily commented) and user-friendly program. We used this tool to assess the presence and properties of the correlation between planetary surface gravity and stellar activity level as measured by the log([Formula: see text]) indicator. The results of the Bayesian analysis are qualitatively similar to those obtained via p-value analysis, and support the presence of a correlation in the data. The results are more robust in their derivation and more informative, revealing interesting features such as asymmetric posterior distributions or markedly different credible intervals, and allowing for a deeper exploration. We encourage the reader interested in this kind of problem to apply our code to his/her own scientific problems. The full understanding of what the Bayesian framework is can only be gained through the insight that comes by handling priors, assessing the convergence of Monte Carlo runs, and a multitude of other practical problems. We hope to contribute so that Bayesian analysis becomes a tool in the toolkit of researchers, and they understand by experience its advantages and limitations.

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

    Directory of Open Access Journals (Sweden)

    Zwinderman Aeilko H

    2009-09-01

    Full Text Available 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 canonical variates, and we applied ridge penalization to the regression of pathway genes on canonical variates of the non-pathway genes, and the elastic net to the regression of non-pathway genes on the canonical variates of the pathway genes. Results We performed a small simulation to illustrate the model's capability to identify new candidate genes to incorporate in the pathway: in our simulations it appeared that a gene was correctly identified if the correlation with the pathway genes was 0.3 or more. We applied the methods to a gene-expression microarray data set of 12, 209 genes measured in 45 patients with glioblastoma, and we considered genes to incorporate in the glioma-pathway: we identified more than 25 genes that correlated > 0.9 with canonical variates of the pathway genes. Conclusion We concluded that penalized canonical correlation analysis is a powerful tool to identify candidate genes in pathway analysis.

  19. 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

  20. Semiparametric bivariate zero-inflated Poisson models with application to studies of abundance for multiple species

    Science.gov (United States)

    Arab, Ali; Holan, Scott H.; Wikle, Christopher K.; Wildhaber, Mark L.

    2012-01-01

    Ecological studies involving counts of abundance, presence–absence or occupancy rates often produce data having a substantial proportion of zeros. Furthermore, these types of processes are typically multivariate and only adequately described by complex nonlinear relationships involving externally measured covariates. Ignoring these aspects of the data and implementing standard approaches can lead to models that fail to provide adequate scientific understanding of the underlying ecological processes, possibly resulting in a loss of inferential power. One method of dealing with data having excess zeros is to consider the class of univariate zero-inflated generalized linear models. However, this class of models fails to address the multivariate and nonlinear aspects associated with the data usually encountered in practice. Therefore, we propose a semiparametric bivariate zero-inflated Poisson model that takes into account both of these data attributes. The general modeling framework is hierarchical Bayes and is suitable for a broad range of applications. We demonstrate the effectiveness of our model through a motivating example on modeling catch per unit area for multiple species using data from the Missouri River Benthic Fishes Study, implemented by the United States Geological Survey.

  1. Modeling both of the number of pausibacillary and multibacillary leprosy patients by using bivariate poisson regression

    Science.gov (United States)

    Winahju, W. S.; Mukarromah, A.; Putri, S.

    2015-03-01

    Leprosy is a chronic infectious disease caused by bacteria of leprosy (Mycobacterium leprae). Leprosy has become an important thing in Indonesia because its morbidity is quite high. Based on WHO data in 2014, in 2012 Indonesia has the highest number of new leprosy patients after India and Brazil with a contribution of 18.994 people (8.7% of the world). This number makes Indonesia automatically placed as the country with the highest number of leprosy morbidity of ASEAN countries. The province that most contributes to the number of leprosy patients in Indonesia is East Java. There are two kind of leprosy. They consist of pausibacillary and multibacillary. The morbidity of multibacillary leprosy is higher than pausibacillary leprosy. This paper will discuss modeling both of the number of multibacillary and pausibacillary leprosy patients as responses variables. These responses are count variables, so modeling will be conducted by using bivariate poisson regression method. Unit experiment used is in East Java, and predictors involved are: environment, demography, and poverty. The model uses data in 2012, and the result indicates that all predictors influence significantly.

  2. Improved deadzone modeling for bivariate wavelet shrinkage-based image denoising

    Science.gov (United States)

    DelMarco, Stephen

    2016-05-01

    Modern image processing performed on-board low Size, Weight, and Power (SWaP) platforms, must provide high- performance while simultaneously reducing memory footprint, power consumption, and computational complexity. Image preprocessing, along with downstream image exploitation algorithms such as object detection and recognition, and georegistration, place a heavy burden on power and processing resources. Image preprocessing often includes image denoising to improve data quality for downstream exploitation algorithms. High-performance image denoising is typically performed in the wavelet domain, where noise generally spreads and the wavelet transform compactly captures high information-bearing image characteristics. In this paper, we improve modeling fidelity of a previously-developed, computationally-efficient wavelet-based denoising algorithm. The modeling improvements enhance denoising performance without significantly increasing computational cost, thus making the approach suitable for low-SWAP platforms. Specifically, this paper presents modeling improvements to the Sendur-Selesnick model (SSM) which implements a bivariate wavelet shrinkage denoising algorithm that exploits interscale dependency between wavelet coefficients. We formulate optimization problems for parameters controlling deadzone size which leads to improved denoising performance. Two formulations are provided; one with a simple, closed form solution which we use for numerical result generation, and the second as an integral equation formulation involving elliptic integrals. We generate image denoising performance results over different image sets drawn from public domain imagery, and investigate the effect of wavelet filter tap length on denoising performance. We demonstrate denoising performance improvement when using the enhanced modeling over performance obtained with the baseline SSM model.

  3. Neural Systems with Numerically Matched Input-Output Statistic: Isotonic Bivariate Statistical Modeling

    Directory of Open Access Journals (Sweden)

    Simone Fiori

    2007-07-01

    Full Text Available Bivariate statistical modeling from incomplete data is a useful statistical tool that allows to discover the model underlying two data sets when the data in the two sets do not correspond in size nor in ordering. Such situation may occur when the sizes of the two data sets do not match (i.e., there are “holes” in the data or when the data sets have been acquired independently. Also, statistical modeling is useful when the amount of available data is enough to show relevant statistical features of the phenomenon underlying the data. We propose to tackle the problem of statistical modeling via a neural (nonlinear system that is able to match its input-output statistic to the statistic of the available data sets. A key point of the new implementation proposed here is that it is based on look-up-table (LUT neural systems, which guarantee a computationally advantageous way of implementing neural systems. A number of numerical experiments, performed on both synthetic and real-world data sets, illustrate the features of the proposed modeling procedure.

  4. A Basic Bivariate Structure of Personality Attributes Evident Across Nine Languages.

    Science.gov (United States)

    Saucier, Gerard; Thalmayer, Amber Gayle; Payne, Doris L; Carlson, Robert; Sanogo, Lamine; Ole-Kotikash, Leonard; Church, A Timothy; Katigbak, Marcia S; Somer, Oya; Szarota, Piotr; Szirmák, Zsofia; Zhou, Xinyue

    2014-02-01

    Here, two studies seek to characterize a parsimonious common-denominator personality structure with optimal cross-cultural replicability. Personality differences are observed in all human populations and cultures, but lexicons for personality attributes contain so many distinctions that parsimony is lacking. Models stipulating the most important attributes have been formulated by experts or by empirical studies drawing on experience in a very limited range of cultures. Factor analyses of personality lexicons of nine languages of diverse provenance (Chinese, Korean, Filipino, Turkish, Greek, Polish, Hungarian, Maasai, and Senoufo) were examined, and their common structure was compared to that of several prominent models in psychology. A parsimonious bivariate model showed evidence of substantial convergence and ubiquity across cultures. Analyses involving key markers of these dimensions in English indicate that they are broad dimensions involving the overlapping content of the interpersonal circumplex, models of communion and agency, and morality/warmth and competence. These "Big Two" dimensions-Social Self-Regulation and Dynamism-provide a common-denominator model involving the two most crucial axes of personality variation, ubiquitous across cultures. The Big Two might serve as an umbrella model serving to link diverse theoretical models and associated research literatures. © 2013 Wiley Periodicals, Inc.

  5. Spatial factor analysis: a new tool for estimating joint species distributions and correlations in species range

    DEFF Research Database (Denmark)

    Thorson, James T.; Scheuerell, Mark D.; Shelton, Andrew O.

    2015-01-01

    1. Predicting and explaining the distribution and density of species is one of the oldest concerns in ecology. Species distributions can be estimated using geostatistical methods, which estimate a latent spatial variable explaining observed variation in densities, but geostatistical methods may...... be imprecise for species with low densities or few observations. Additionally, simple geostatistical methods fail to account for correlations in distribution among species and generally estimate such cross-correlations as a post hoc exercise. 2. We therefore present spatial factor analysis (SFA), a spatial...... model for estimating a low-rank approximation to multivariate data, and use it to jointly estimate the distribution of multiple species simultaneously. We also derive an analytic estimate of cross-correlations among species from SFA parameters. 3. As a first example, we show that distributions for 10...

  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. 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.

  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. Characteristic Analysis on UAV-MIMO Channel Based on Normalized Correlation Matrix

    Science.gov (United States)

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

    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. PMID:24977185

  10. Two-dimensional correlation analysis of spectra collected without knowing sampling order

    Science.gov (United States)

    Noda, Isao

    2018-03-01

    Two-dimensional correlation spectroscopy (2DCOS) without a priori knowledge of meaningful spectral sampling order is considered. Construction of synchronous 2D correlation spectrum does not require the knowledge of sampling order, and disrelation spectrum derived from synchronous spectrum possesses useful features similar to those of asynchronous spectrum. Disrelation analysis may provide enhanced spectral resolution and distinction of bands arising from different sources but not the sequential order of intensity variations. Dataset sampled in an arbitrary or scrambled order may be reassembled into a more structured form by rank ordering the spectra with the intensity of a select band. If there is no meaningful data structure, asynchronous 2D correlation should not be attempted, although synchronous and disrelation spectra may still be useful. The intrinsic ambiguity in the direction of sampling order may sometimes be resolved using additional physical information known about the sample system.

  11. 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.

  12. 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.

  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. Correlation between adherence rates measured by MEMS and self-reported questionnaires: a meta-analysis

    Directory of Open Access Journals (Sweden)

    Shi Lizheng

    2010-09-01

    Full Text Available Abstract Purpose It is vital to understand the associations between the medication event monitoring systems (MEMS and self-reported questionnaires (SRQs because both are often used to measure medication adherence and can produce different results. In addition, the economic implication of using alternative measures is important as the cost of electronic monitoring devices is not covered by insurance, while self-reports are the most practical and cost-effective method in the clinical settings. This meta-analysis examined the correlations of two measurements of medication adherence: MEMS and SRQs. Methods The literature search (1980-2009 used PubMed, OVID MEDLINE, PsycINFO (EBSCO, CINAHL (EBSCO, OVID HealthStar, EMBASE (Elsevier, and Cochrane Databases. Studies were included if the correlation coefficients [Pearson (rp or Spearman (rs] between adherences measured by both MEMS and SRQs were available or could be calculated from other statistics in the articles. Data were independently abstracted in duplicate with standardized protocol and abstraction form including 1 first author's name; 2 year of publication; 3 disease status of participants; 4 sample size; 5 mean age (year; 6 duration of trials (month; 7 SRQ names if available; 8 adherence (% measured by MEMS; 9 adherence (% measured by SRQ; 10 correlation coefficient and relative information, including p-value, 95% confidence interval (CI. A meta-analysis was conducted to pool the correlation coefficients using random-effect model. Results Eleven studies (N = 1,684 patients met the inclusion criteria. The mean of adherence measured by MEMS was 74.9% (range 53.4%-92.9%, versus 84.0% by SRQ (range 68.35%-95%. The correlation between adherence measured by MEMS and SRQs ranged from 0.24 to 0.87. The pooled correlation coefficient for 11 studies was 0.45 (p = 0.001, 95% confidence interval [95% CI]: 0.34-0.56. The subgroup meta-analysis on the seven studies reporting rp and four studies reporting rs

  15. 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.

  16. 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

  17. 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

  18. 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

  19. Correlating the EMC analysis and testing methods for space systems in MIL-STD-1541A

    Science.gov (United States)

    Perez, Reinaldo J.

    A study was conducted to improve the correlation between the electromagnetic compatibility (EMC) analysis models stated in MIL-STD-1541A and the suggested testing methods used for space systems. The test and analysis methods outlined in MIL-STD-1541A are described, and a comparative assessment of testing and analysis techniques as they relate to several EMC areas is presented. Suggestions on present analysis and test methods are introduced to harmonize and bring the analysis and testing tools in MIL-STD-1541A into closer agreement. It is suggested that test procedures in MIL-STD-1541A must be improved by providing alternatives to the present use of shielded enclosures as the primary site for such tests. In addition, the alternate use of anechoic chambers and open field test sites must be considered.

  20. Correlating the EMC analysis and testing methods for space systems in MIL-STD-1541A

    Science.gov (United States)

    Perez, Reinaldo J.

    1990-01-01

    A study was conducted to improve the correlation between the electromagnetic compatibility (EMC) analysis models stated in MIL-STD-1541A and the suggested testing methods used for space systems. The test and analysis methods outlined in MIL-STD-1541A are described, and a comparative assessment of testing and analysis techniques as they relate to several EMC areas is presented. Suggestions on present analysis and test methods are introduced to harmonize and bring the analysis and testing tools in MIL-STD-1541A into closer agreement. It is suggested that test procedures in MIL-STD-1541A must be improved by providing alternatives to the present use of shielded enclosures as the primary site for such tests. In addition, the alternate use of anechoic chambers and open field test sites must be considered.

  1. Long-term forecasting of meteorological time series using Nonlinear Canonical Correlation Analysis (NLCCA)

    Science.gov (United States)

    Woldesellasse, H. T.; Marpu, P. R.; Ouarda, T.

    2016-12-01

    Wind is one of the crucial renewable energy sources which is expected to bring solutions to the challenges of clean energy and the global issue of climate change. A number of linear and nonlinear multivariate techniques has been used to predict the stochastic character of wind speed. A wind forecast with good accuracy has a positive impact on the reduction of electricity system cost and is essential for the effective grid management. Over the past years, few studies have been done on the assessment of teleconnections and its possible effects on the long-term wind speed variability in the UAE region. In this study Nonlinear Canonical Correlation Analysis (NLCCA) method is applied to study the relationship between global climate oscillation indices and meteorological variables, with a major emphasis on wind speed and wind direction, of Abu Dhabi, UAE. The wind dataset was obtained from six ground stations. The first mode of NLCCA is capable of capturing the nonlinear mode of the climate indices at different seasons, showing the symmetry between the warm states and the cool states. The strength of the nonlinear canonical correlation between the two sets of variables varies with the lead/lag time. The performance of the models is assessed by calculating error indices such as the root mean square error (RMSE) and Mean absolute error (MAE). The results indicated that NLCCA models provide more accurate information about the nonlinear intrinsic behaviour of the dataset of variables than linear CCA model in terms of the correlation and root mean square error. Key words: Nonlinear Canonical Correlation Analysis (NLCCA), Canonical Correlation Analysis, Neural Network, Climate Indices, wind speed, wind direction

  2. Frequency domain analysis of electrooculogram and its correlation with cardiac sympathetic function.

    Science.gov (United States)

    Kuo, Terry B J; Yang, Cheryl C H

    2009-05-01

    To test the hypothesis that electrooculogram contains information on autonomic functions, correlation analyses of electrooculogram and heart rate variability (HRV) parameters during night sleep and over 24 h were performed on 24 healthy young volunteers (12 women and 12 men). Continuous frequency-domain analysis revealed repeated emergence of electrooculogram low-frequency power (PEOG, 0.05-0.5 Hz) during night sleep. The change in the PEOG, when natural log transformed, was graded rather than all or nothing. The PEOG was not correlated with high-frequency power (HF, 0.15-0.4 Hz) of HRV. In contrast, the PEOG was significantly correlated with R-R interval (r=-0.46+/-0.15; mean+/-SD, PHz) to HF ratio (LF/HF) of HRV (r=0.49+/-0.10, P<0.05). The correlation coefficient between PEOG and R-R interval and between PEOG and LF/HF became even larger (r=-0.68+/-0.08 and 0.58+/-0.09, respectively) when 24-h recordings were analyzed. There was no significant difference in the correlation between women and men. We concluded that the electrooculogram, as analyzed in the frequency domain, contains information on sympathetic activity not only during night sleep but also throughout day and night in healthy young people.

  3. 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.

  4. Statistical analysis of data from dilution assays with censored correlated counts.

    Science.gov (United States)

    Quiroz, Jorge; Wilson, Jeffrey R; Roychoudhury, Satrajit

    2012-01-01

    Frequently, count data obtained from dilution assays are subject to an upper detection limit, and as such, data obtained from these assays are usually censored. Also, counts from the same subject at different dilution levels are correlated. Ignoring the censoring and the correlation may provide unreliable and misleading results. Therefore, any meaningful data modeling requires that the censoring and the correlation be simultaneously addressed. Such comprehensive approaches of modeling censoring and correlation are not widely used in the analysis of dilution assays data. Traditionally, these data are analyzed using a general linear model on a logarithmic-transformed average count per subject. However, this traditional approach ignores the between-subject variability and risks, providing inconsistent results and unreliable conclusions. In this paper, we propose the use of a censored negative binomial model with normal random effects to analyze such data. This model addresses, in addition to the censoring and the correlation, any overdispersion that may be present in count data. The model is shown to be widely accessible through the use of several modern statistical software. Copyright © 2012 John Wiley & Sons, Ltd.

  5. 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.

  6. 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.

  7. 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.

  8. 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

  9. 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.

  10. Correlation of central venous pressure with venous blood gas analysis parameters; a diagnostic study

    Directory of Open Access Journals (Sweden)

    Sima Rahim-Taleghani

    2017-03-01

    Full Text Available Objective: This study was conducted to assess the correlation between central venous pressure (CVP and venous blood gas (VBG analysis parameters, to facilitate management of severe sepsis and septic shock in emergency department. Material and methods: This diagnostic study was conducted from January 2014 until June 2015 in three major educational medical centers, Tehran, Iran. For patients selected with diagnosis of septic shock, peripheral blood sample was taken for testing the VBG parameters and the anion gap (AG was calculated. All the mentioned parameters were measured again after infusion of 500 cc of normal saline 0.9% in about 1 h. Results: Totally, 93 patients with septic shock were enrolled, 63 male and 30 female. The mean age was 72.53 ± 13.03 and the mean Shock Index (SI before fluid therapy was 0.79 ± 0.30. AG and pH showed significant negative correlations with CVP, While HCO3 showed a significant positive correlation with CVP. These relations can be affected by the treatment modalities used in shock management such as fluid therapy, mechanical ventilation and vasopressor treatment. Conclusion: It is likely that there is a significant statistical correlation between VBG parameters and AG with CVP, but further research is needed before implementation of the results of this study. Keywords: Shock, Septic, Central venous pressure, Blood gas analysis, Emergency department, Emergency medicine

  11. 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.

  12. 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.

  13. 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.

  14. 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)

  15. 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.

  16. 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

    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......, 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....... 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...... 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...

  17. Bivariate genome-wide association analyses identified genetic pleiotropic effects for bone mineral density and alcohol drinking in Caucasians.

    Science.gov (United States)

    Lu, Shan; Zhao, Lan-Juan; Chen, Xiang-Ding; Papasian, Christopher J; Wu, Ke-Hao; Tan, Li-Jun; Wang, Zhuo-Er; Pei, Yu-Fang; Tian, Qing; Deng, Hong-Wen

    2017-11-01

    Several studies indicated bone mineral density (BMD) and alcohol intake might share common genetic factors. The study aimed to explore potential SNPs/genes related to both phenotypes in US Caucasians at the genome-wide level. A bivariate genome-wide association study (GWAS) was performed in 2069 unrelated participants. Regular drinking was graded as 1, 2, 3, 4, 5, or 6, representing drinking alcohol never, less than once, once or twice, three to six times, seven to ten times, or more than ten times per week respectively. Hip, spine, and whole body BMDs were measured. The bivariate GWAS was conducted on the basis of a bivariate linear regression model. Sex-stratified association analyses were performed in the male and female subgroups. In males, the most significant association signal was detected in SNP rs685395 in DYNC2H1 with bivariate spine BMD and alcohol drinking (P = 1.94 × 10 -8 ). SNP rs685395 and five other SNPs, rs657752, rs614902, rs682851, rs626330, and rs689295, located in the same haplotype block in DYNC2H1 were the top ten most significant SNPs in the bivariate GWAS in males. Additionally, two SNPs in GRIK4 in males and three SNPs in OPRM1 in females were suggestively associated with BMDs (of the hip, spine, and whole body) and alcohol drinking. Nine SNPs in IL1RN were only suggestively associated with female whole body BMD and alcohol drinking. Our study indicated that DYNC2H1 may contribute to the genetic mechanisms of both spine BMD and alcohol drinking in male Caucasians. Moreover, our study suggested potential pleiotropic roles of OPRM1 and IL1RN in females and GRIK4 in males underlying variation of both BMD and alcohol drinking.

  18. Feasibility and reproducibility of fetal lung texture analysis by Automatic Quantitative Ultrasound Analysis and correlation with gestational age.

    Science.gov (United States)

    Cobo, Teresa; Bonet-Carne, Elisenda; Martínez-Terrón, Mónica; Perez-Moreno, Alvaro; Elías, Núria; Luque, Jordi; Amat-Roldan, Ivan; Palacio, Montse

    2012-01-01

    To evaluate the feasibility and reproducibility of fetal lung texture analysis using a novel automatic quantitative ultrasound analysis and to assess its correlation with gestational age. Prospective cross-sectional observational study. To evaluate texture features, 957 left and right lung images in a 2D four-cardiac-chamber view plane were previously delineated from fetuses between 20 and 41 weeks of gestation. Quantification of lung texture was performed by the Automatic Quantitative Ultrasound Analysis (AQUA) software to extract image features. A standard learning approach composed of feature transformation and a regression model was used to evaluate the association between texture features and gestational age. The association between weeks of gestation and fetal lung texture quantified by the AQUA software presented a Pearson correlation of 0.97. The association was not influenced by delineation parameters such as region of interest (ROI) localization, ROI size, right/left lung selected or sonographic parameters such as ultrasound equipment or transducer used. Fetal lung texture analysis measured by the AQUA software demonstrated a strong correlation with gestational age. This supports further research to explore the use of this technology to the noninvasive prediction of fetal lung maturity. Copyright © 2012 S. Karger AG, Basel.

  19. 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.

  20. Calibration model transfer for near-infrared spectra based on canonical correlation analysis.

    Science.gov (United States)

    Fan, Wei; Liang, Yizeng; Yuan, Dalin; Wang, Jiajun

    2008-08-08

    In order to solve the calibration transformation problem in near-infrared (NIR) spectroscopy, a method based on canonical correlation analysis (CCA) for calibration model transfer is developed in this work. Two real NIR data sets were tested. A comparative study between the proposed method and piecewise direct standardization (PDS) was conducted. It is shown that the transfer results obtained with the proposed method based on CCA were better than those obtained by PDS when the subset had sufficient samples.

  1. Novel plasma torch diagnostic method based on multiple exposition CCD and correlation analysis

    Czech Academy of Sciences Publication Activity Database

    Šonský, Jiří; Něnička, Václav

    2006-01-01

    Roč. 56, - (2006), B1371-B1376 ISSN 0011-4626. [Symposium on Plasma Physics and Technology /22./. Prague, 26.06.2006-29.06.2006] R&D Projects: GA ČR(CZ) GA202/04/1341 Institutional research plan: CEZ:AV0Z20570509 Keywords : plasma torch * CCD * correlation analysis Subject RIV: BL - Plasma and Gas Discharge Physics Impact factor: 0.568, year: 2006

  2. Correlation analysis of dual-energy CT iodine maps with quantitative pulmonary perfusion MRI.

    Science.gov (United States)

    Hansmann, Jan; Apfaltrer, Paul; Zoellner, Frank G; Henzler, Thomas; Meyer, Mathias; Weisser, Gerald; Schoenberg, Stefan O; Attenberger, Ulrike I

    2013-05-28

    To correlate dual-energy computed tomography (DECT) pulmonary angiography derived iodine maps with parameter maps of quantitative pulmonary perfusion magnetic resonance imaging (MRI). Eighteen patients with pulmonary perfusion defects detected on DECT derived iodine maps were included in this prospective study and additionally underwent time-resolved contrast-enhanced pulmonary MRI [dynamic contrast enhanced (DCE)-MRI]. DCE-MRI data were quantitatively analyzed using a pixel-by-pixel deconvolution analysis calculating regional pulmonary blood flow (PBF), pulmonary blood volume (PBV) and mean transit time (MTT) in visually normal lung parenchyma and perfusion defects. Perfusion parameters were correlated to mean attenuation values of normal lung and perfusion defects on DECT iodine maps. Two readers rated the concordance of perfusion defects in a visual analysis using a 5-point Likert-scale (1 = no correlation, 5 = excellent correlation). In visually normal pulmonary tissue mean DECT and MRI values were: 22.6 ± 8.3 Hounsfield units (HU); PBF: 58.8 ± 36.0 mL/100 mL per minute; PBV: 16.6 ± 8.5 mL; MTT: 17.1 ± 10.3 s. In areas with restricted perfusion mean DECT and MRI values were: 4.0 ± 3.9 HU; PBF: 10.3 ± 5.5 mL/100 mL per minute, PBV: 5 ± 4 mL, MTT: 21.6 ± 14.0 s. The differences between visually normal parenchyma and areas of restricted perfusion were statistically significant for PBF, PBV and DECT (P < 0.0001). No linear correlation was found between MRI perfusion parameters and attenuation values of DECT iodine maps (PBF: r = 0.35, P = 0.15; PBV: r = 0.34, P = 0.16; MTT: r = 0.41, P = 0.08). Visual analysis revealed a moderate correlation between perfusion defects on DECT iodine maps and the parameter maps of DCE-MRI (mean score 3.6, κ 0.45). There is a moderate visual but not statistically significant correlation between DECT iodine maps and perfusion parameter maps of DCE-MRI.

  3. Analysis of the enhanced negative correlation between electron density and electron temperature related to earthquakes

    Directory of Open Access Journals (Sweden)

    X. H. Shen

    2015-04-01

    Full Text Available Ionospheric perturbations in plasma parameters have been observed before large earthquakes, but the correlation between different parameters has been less studied in previous research. The present study is focused on the relationship between electron density (Ne and temperature (Te observed by the DEMETER (Detection of Electro-Magnetic Emissions Transmitted from Earthquake Regions satellite during local nighttime, in which a positive correlation has been revealed near the equator and a weak correlation at mid- and low latitudes over both hemispheres. Based on this normal background analysis, the negative correlation with the lowest percent in all Ne and Te points is studied before and after large earthquakes at mid- and low latitudes. The multiparameter observations exhibited typical synchronous disturbances before the Chile M8.8 earthquake in 2010 and the Pu'er M6.4 in 2007, and Te varied inversely with Ne over the epicentral areas. Moreover, statistical analysis has been done by selecting the orbits at a distance of 1000 km and ±7 days before and after the global earthquakes. Enhanced negative correlation coefficients lower than −0.5 between Ne and Te are found in 42% of points to be connected with earthquakes. The correlation median values at different seismic levels show a clear decrease with earthquakes larger than 7. Finally, the electric-field-coupling model is discussed; furthermore, a digital simulation has been carried out by SAMI2 (Sami2 is Another Model of the Ionosphere, which illustrates that the external electric field in the ionosphere can strengthen the negative correlation in Ne and Te at a lower latitude relative to the disturbed source due to the effects of the geomagnetic field. Although seismic activity is not the only source to cause the inverse Ne–Te variations, the present results demonstrate one possibly useful tool in seismo-electromagnetic anomaly differentiation, and a comprehensive analysis with multiple

  4. 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.

  5. 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®

  6. Morphology Development in Model Polyethylene via Two-Dimensional Correlation Analysis

    Energy Technology Data Exchange (ETDEWEB)

    D Smirnova; J Kornfield; D Lohse

    2011-12-31

    Two-dimensional (2D) correlation analysis is applied to synchrotron X-ray scattering data to characterize morphological regimes during nonisothermal crystallization of a model ethylene copolymer (hydrogenated polybutadiene, HPBD). The 2D correlation patterns highlight relationships among multiple characteristics of structure evolution, particularly the extent to which separate features change simultaneously versus sequentially. By visualizing these relationships during cooling, evidence is obtained for two separate physical processes occurring in what is known as 'irreversible crystallization' in random ethylene copolymers. Initial growth of primarily lamellae into unconstrained melt ('primary-irreversible crystallization') is distinguished from subsequent secondary lamellae formation in the constrained, noncrystalline regions between the primary lamellae ('secondary-irreversible crystallization'). At successively lower temperatures ('reversible crystallization'), growth of the crystalline reflections is found to occur simultaneously with the change in shape of the amorphous halo, which is inconsistent with the formation of an additional phase. Rather, the synchronous character supports the view that growth of frustrated crystals distorts the adjacent noncrystalline material. Furthermore, heterocorrelation analysis of small-angle and wide-angle X-ray scattering data from the reversible crystallization regime reveals that the size of new crystals is consistent with fringed-micellar structures (9 nm). Thus, 2D correlation analysis provides new insights into morphology development in polymeric systems.

  7. 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....... This difference is ascribed to the noise structure in the data. The CCA methods are related to partial least squares (PLS) methods. The paper very briefly describes multiset CCA based multiset PLS. Also, the CCA methods can be applied as multivariate extensions to empirical orthogonal functions (EOF) techniques....... (Multiset) CCA is well suited for inclusion in geographical information systems, GIS....

  8. A bivariate approach to the widening of the frontal lobes in the genus Homo.

    Science.gov (United States)

    Bruner, Emiliano; Holloway, Ralph L

    2010-02-01

    Within the genus Homo, the most encephalized taxa (Neandertals and modern humans) show relatively wider frontal lobes than either Homo erectus or australopithecines. The present analysis considers whether these changes are associated with a single size-based or allometric pattern (positive allometry of the width of the anterior endocranial fossa) or with a more specific and non-allometric pattern. The relationship between hemispheric length, maximum endocranial width, and frontal width at Broca's area was investigated in extant and extinct humans. Our results do not support positive allometry for the frontal lobe's width in relation to the main endocranial diameters within modern humans (Homo sapiens). Also, the correlation between frontal width and hemispheric length is lower than the correlation between frontal width and parieto-temporal width. When compared with the australopithecines, the genus Homo could have experienced a non-allometric widening of the brain at the temporo-parietal areas, which is most evident in Neandertals. Modern humans and Neandertals also display a non-allometric widening of the anterior endocranial fossa at the Broca's cap when compared with early hominids, again more prominent in the latter group. Taking into account the contrast between the intra-specific patterns and the between-species differences, the relative widening of the anterior fossa can be interpreted as a definite evolutionary character instead of a passive consequence of brain size increase. This expansion is most likely associated with correspondent increments of the underlying neural mass, or at least with a geometrical reallocation of the frontal cortical volumes. Although different structural changes of the cranial architecture can be related to such variations, the widening of the frontal areas is nonetheless particularly interesting when some neural functions (like language or working memory, decision processing, etc.) and related fronto-parietal cortico

  9. Quantitative Analysis of the Cervical Texture by Ultrasound and Correlation with Gestational Age.

    Science.gov (United States)

    Baños, Núria; Perez-Moreno, Alvaro; Migliorelli, Federico; Triginer, Laura; Cobo, Teresa; Bonet-Carne, Elisenda; Gratacos, Eduard; Palacio, Montse

    2017-01-01

    Quantitative texture analysis has been proposed to extract robust features from the ultrasound image to detect subtle changes in the textures of the images. The aim of this study was to evaluate the feasibility of quantitative cervical texture analysis to assess cervical tissue changes throughout pregnancy. This was a cross-sectional study including singleton pregnancies between 20.0 and 41.6 weeks of gestation from women who delivered at term. Cervical length was measured, and a selected region of interest in the cervix was delineated. A model to predict gestational age based on features extracted from cervical images was developed following three steps: data splitting, feature transformation, and regression model computation. Seven hundred images, 30 per gestational week, were included for analysis. There was a strong correlation between the gestational age at which the images were obtained and the estimated gestational age by quantitative analysis of the cervical texture (R = 0.88). This study provides evidence that quantitative analysis of cervical texture can extract features from cervical ultrasound images which correlate with gestational age. Further research is needed to evaluate its applicability as a biomarker of the risk of spontaneous preterm birth, as well as its role in cervical assessment in other clinical situations in which cervical evaluation might be relevant. © 2016 S. Karger AG, Basel.

  10. Electro-optic correlator for large-format microwave interferometry: Up-conversion and correlation stages performance analysis

    Science.gov (United States)

    Ortiz, D.; Casas, Francisco J.; Ruiz-Lombera, R.; Mirapeix, J.

    2017-04-01

    In this paper, a microwave interferometer prototype with a near-infra-red optical correlator is proposed as a solution to get a large-format interferometer with hundreds of receivers for radio astronomy applications. A 10 Gbits/s Lithium Niobate modulator has been tested as part of an electro-optic correlator up-conversion stage that will be integrated in the interferometer prototype. Its internal circuitry consists of a single-drive modulator biased by a SubMiniature version A (SMA) connector allowing to up-convert microwave signals with bandwidths up to 12.5 GHz to the near infrared band. In order to characterize it, a 12 GHz tone and a bias voltage were applied to the SMA input using a polarization tee. Two different experimental techniques to stabilize the modulator operation point in its minimum optical carrier output power are described. The best achieved results showed a rather stable spectrum in amplitude and wavelength at the output of the modulator with an optical carrier level 23 dB lower than the signal of interest. On the other hand, preliminary measurements were made to analyze the correlation stage, using 4f and 6f optical configurations to characterize both the antenna/fiber array configuration and the corresponding point spread function.

  11. The correlation analysis on the landscape pattern index and hydrological processes in the Yanhe watershed, China

    Science.gov (United States)

    Zhou, Z. X.; Li, J.

    2015-05-01

    Yanhe watershed, as a typical and experimental district of Soil and Water Conservation District, has long been plagued by soil erosion due to severe human disturbances. Exploring the relationship between watershed landscape pattern and hydrological processes can find effective ways to solve soil erosion problems. At first, with remote sensing and GIS (Geographic Information System) technology and based on SWAT model, this paper analyzed and simulated ecological hydrological processes in Yanhe watershed. It is on subbasin scale that the runoff and sediment yields were simulated monthly in Yanhe watershed using SWAT model. Secondly, it quantified landscape pattern with landscape indices. The seven landscape indices at the landscape level were selected with principal component factor analysis, including Disjunct Core Area Density (DCAD), Radius of gyration (GYRATE_SD), Patch Cohesion Index (COHESION), Shannon's diversity index (SHEI), Total Core Area (TCA), Perimeter-Area Fractal dimension index (PAFRAC), Interspersion and Juxtaposition Index (IJI), etc. Thirdly, a new composite landscape index was constructed on the basis of eco-hydrological processes, which was closely related to soil erosion. The results are as follows: (1) Coupled analysis on the relationship of landscape indices and annual runoff as well as annual sediment yields in each subbasin, the correlation coefficient of seven selected landscape indices and runoff is very small, no passing all significant tests. But the correlation between sediment yields and the indices except for TCA and IJI is significant, and the absolute value of the correlation coefficient is between 0.3 and 0.5. (2) According to the "source-sink" theory of soil erosion, Slope-HRUs landscape index (SHLI) was built and can reflect the relationship between landscape pattern and soil erosion processes to a certain extent. The coupling relationship between Slope-HRUs landscape index (SHLI) and annual sediment yields in each subbasin is

  12. 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.

  13. A Deploying Process Analysis Using Sub-PixelCross-Correlation Method

    Science.gov (United States)

    Kimura, Shinichi; Takeuchi, Makoto; Fukase, Yutaro; Harima, Koichi; Sato, Hitoshi; Yoshida, Tetsuji; Miyasaka, Akihiro; Noda, Hiroyuki; Sunakawa, Kei; Homma, Masanori

    To establish a large deployable antenna, monitoring and collimation are essentially important for reliable and precise deployment. We have developed an analysis method to detect shifts in several images, in which the combination of cross-correlations between images and approximation at sub-pixel precision enables us to detect shifts in images with a precision of up to 0.01 pixels. The LDREX mission, which was a preliminary experiment for the large deployable antenna of ETS-VIII, was performed in December 2001. During this experiment, anomalies occurred in the deployable antenna, and deployment was aborted. To understand the cause of the anomalies, we used our visual analysis method. Using this analysis, we detected vibrating features of the deployable antenna, which were useful for explaining the anomalies. In this paper, we outline our visual analysis method and discuss its application to monitoring of the deployable antenna.

  14. Multivariate Analysis and Visualization of Splicing Correlations in Single-Gene Transcriptomes

    Directory of Open Access Journals (Sweden)

    Agnew William S

    2007-01-01

    Full Text Available Abstract Background RNA metabolism, through 'combinatorial splicing', can generate enormous structural diversity in the proteome. Alternative domains may interact, however, with unpredictable phenotypic consequences, necessitating integrated RNA-level regulation of molecular composition. Splicing correlations within transcripts of single genes provide valuable clues to functional relationships among molecular domains as well as genomic targets for higher-order splicing regulation. Results We present tools to visualize complex splicing patterns in full-length cDNA libraries. Developmental changes in pair-wise correlations are presented vectorially in 'clock plots' and linkage grids. Higher-order correlations are assessed statistically through Monte Carlo analysis of a log-linear model with an empirical-Bayes estimate of the true probabilities of observed and unobserved splice forms. Log-linear coefficients are visualized in a 'spliceprint,' a signature of splice correlations in the transcriptome. We present two novel metrics: the linkage change index, which measures the directional change in pair-wise correlation with tissue differentiation, and the accuracy index, a very simple goodness-of-fit metric that is more sensitive than the integrated squared error when applied to sparsely populated tables, and unlike chi-square, does not diverge at low variance. Considerable attention is given to sparse contingency tables, which are inherent to single-gene libraries. Conclusion Patterns of splicing correlations are revealed, which span a broad range of interaction order and change in development. The methods have a broad scope of applicability, beyond the single gene – including, for example, multiple gene interactions in the complete transcriptome.

  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. Assessing protein conformational sampling methods based on bivariate lag-distributions of backbone angles

    KAUST Repository

    Maadooliat, Mehdi

    2012-08-27

    Despite considerable progress in the past decades, protein structure prediction remains one of the major unsolved problems in computational biology. Angular-sampling-based methods have been extensively studied recently due to their ability to capture the continuous conformational space of protein structures. The literature has focused on using a variety of parametric models of the sequential dependencies between angle pairs along the protein chains. In this article, we present a thorough review of angular-sampling-based methods by assessing three main questions: What is the best distribution type to model the protein angles? What is a reasonable number of components in a mixture model that should be considered to accurately parameterize the joint distribution of the angles? and What is the order of the local sequence-structure dependency that should be considered by a prediction method? We assess the model fits for different methods using bivariate lag-distributions of the dihedral/planar angles. Moreover, the main information across the lags can be extracted using a technique called Lag singular value decomposition (LagSVD), which considers the joint distribution of the dihedral/planar angles over different lags using a nonparametric approach and monitors the behavior of the lag-distribution of the angles using singular value decomposition. As a result, we developed graphical tools and numerical measurements to compare and evaluate the performance of different model fits. Furthermore, we developed a web-tool (http://www.stat.tamu. edu/~madoliat/LagSVD) that can be used to produce informative animations. © The Author 2012. Published by Oxford University Press.

  17. 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.

  18. Study on soil water characteristics of tobacco fields based on canonical correlation analysis

    Directory of Open Access Journals (Sweden)

    Xiao-hou Shao

    2009-06-01

    Full Text Available In order to identify the principal factors influencing soil water characteristics (SWC and evaluate SWC effectively, the multivariate-statistical canonical correlation analysis (CCA method was used to study and analyze the correlation between SWC and soil physical and chemical properties. Twenty-two soil samples were taken from 11 main tobacco-growing areas in Guizhou Province in China and the soil water characteristic curves (SWCC and basic physical and chemical properties of the soil samples were determined. The results show that: (1 The soil bulk density, soil total porosity and soil capillary porosity have significant effects on SWC of tobacco fiels. Bulk density and total porosity are positively correlated with soil water retention characteristics (SWRC, and soil capillary porosity is positively correlated with soil water supply characteristics (SWSC. (2 Soil samples from different soil layers at the same soil sampling point show similarity or consistency in SWC. Inadequate soil water supply capability and imbalance between SWRC and SWSC are problems of tobacco soil. (3 The SWC of loamy clay are generally superior to those of silty clay loam.

  19. An analysis of the correlation between CT images and clinical findings in spinal trauma patients

    International Nuclear Information System (INIS)

    Turek, T.; Sasiadek, M.; Sasiadek, M.

    2004-01-01

    Computed tomography (CT) is an accurate and safe method of diagnostic imaging in spinal trauma patients. The purpose of the study was to analyze correlations between CT appearance of spine injuries and clinical findings. CT was performed in 193 patients after spinal trauma. In 166 cases (86%) neurological disturbances were present, including 77 (39.9%) patients with signs of spinal cord injury, and 48 (24.9%) with radicular symptoms. Correlations between the clinical findings and the results of CT examinations were analyzed. CT revealed pathological changes in 156 patients (80.8 %). Fractures were found in 128 (66.3%) cases, facet joint injuries in 57 (29.5%), and intervertebral disc lesions in 24 (12.4%) patients. Statistical analysis showed a significant correlation between local pain, as well as minor and transient neurological signs, and normal CT appearance (p<0.05). In patients with radicular symptoms there were positive correlations with intervertebral disc injuries (p<0.001) and degenerative stenosis (p<0.05), while negative correlations with facet joint injuries (p<0.001) and normal CT appearance (p<0.05). Symptoms of spinal cord injury correlated positively with facet joint injuries (p<0.001) while negatively with normal CT appearance and intervertebral disc injuries (p<0.05). Consciousness disturbances correlated positively with brain injuries (p<0.001) and normal CT appearance of the spine (p<0.05), while negatively with the spinal fractures (p<0.05). There is a high correlation between CT results and severity of neurological state of spinal trauma patients. CT should be performed in patients with signs of spinal cord injury as well as in adult patients with radicular symptoms in lumbar spine region. Patients with local pain and minor or transient neurological disturbances should not be examined by CT. There are also no indications to simultaneous CT study of the head and the spine in unconscious patients, unless the kind of trauma, clinical findings or

  20. 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

  1. 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

  2. Latent profile analysis in frontotemporal lobar degeneration and related disorders: clinical presentation and SPECT functional correlates

    Directory of Open Access Journals (Sweden)

    Di Luca Monica

    2007-05-01

    Full Text Available Abstract Background Frontotemporal Lobar Degeneration (FTLD thus recently renamed, refers to a spectrum of heterogeneous conditions. This same heterogeneity of presentation represents the major methodological limit for the correct evaluation of clinical designation and brain functional correlates. At present, no study has investigated clinical clusters due to specific cognitive and behavioural disturbances beyond current clinical criteria. The aim of this study was to identify clinical FTLD presentation, based on cognitive and behavioural profile, and to define their SPECT functional correlations. Methods Ninety-seven FTLD patients entered the study. A clinical evaluation and standardised assessment were preformed, as well as a brain SPECT perfusion imaging study. Latent Profile Analysis on clinical, neuropsychological, and behavioural data was performed. Voxel-basis analysis of SPECT data was computed. Results Three specific clusters were identified and named "pseudomanic behaviour" (LC1, "cognitive" (LC2, and "pseudodepressed behaviour" (LC3 endophenotypes. These endophenotypes showed a comparable hypoperfusion in left temporal lobe, but a specific pattern involving: medial and orbitobasal frontal cortex in LC1, subcortical brain region in LC2, and right dorsolateral frontal cortex and insula in LC3. Conclusion These findings provide evidence that specific functional-cluster symptom relationship can be delineated in FTLD patients by a standardised assessment. The understanding of the different functional correlates of clinical presentations will hopefully lead to the possibility of individuating diagnostic and treatment algorithms.

  3. 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.

  4. Group Study of Simulated Driving fMRI Data by Multiset Canonical Correlation Analysis.

    Science.gov (United States)

    Li, Yi-Ou; Adalı, Tulay; Calhoun, Vince D

    2012-07-01

    In this work, we apply a novel statistical method, multiset canonical correlation analysis (M-CCA), to study a group of functional magnetic resonance imaging (fMRI) datasets acquired during simulated driving task. The M-CCA method jointly decomposes fMRI datasets from different subjects/sessions into brain activation maps and their associated time courses, such that the correlation in each group of estimated activation maps across datasets is maximized. Therefore, the functional activations across all datasets are extracted in the order of consistency across different dataset. On the other hand, M-CCA preserves the uniqueness of the functional maps estimated from each dataset by avoiding concatenation of different datasets in the analysis. Hence, the cross-dataset variation of the functional activations can be used to test the hypothesis of functional-behavioral association. In this work, we study 120 simulated driving fMRI datasets and identify parietal-occipital regions and frontal lobe as the most consistently engaged areas across all the subjects and sessions during simulated driving. The functional-behavioral association study indicates that all the estimated brain activations are significantly correlated with the steering operation during the driving task. M-CCA thus provides a new approach to investigate the complex relationship between the brain functions and multiple behavioral variables, especially in naturalistic tasks as demonstrated by the simulated driving study.

  5. Frequency recognition in SSVEP-based BCI using multiset canonical correlation analysis.

    Science.gov (United States)

    Zhang, Yu; Zhou, Guoxu; Jin, Jing; Wang, Xingyu; Cichocki, Andrzej

    2014-06-01

    Canonical correlation analysis (CCA) has been one of the most popular methods for frequency recognition in steady-state visual evoked potential (SSVEP)-based brain-computer interfaces (BCIs). Despite its efficiency, a potential problem is that using pre-constructed sine-cosine waves as the required reference signals in the CCA method often does not result in the optimal recognition accuracy due to their lack of features from the real electro-encephalo-gram (EEG) data. To address this problem, this study proposes a novel method based on multiset canonical correlation analysis (MsetCCA) to optimize the reference signals used in the CCA method for SSVEP frequency recognition. The MsetCCA method learns multiple linear transforms that implement joint spatial filtering to maximize the overall correlation among canonical variates, and hence extracts SSVEP common features from multiple sets of EEG data recorded at the same stimulus frequency. The optimized reference signals are formed by combination of the common features and completely based on training data. Experimental study with EEG data from 10 healthy subjects demonstrates that the MsetCCA method improves the recognition accuracy of SSVEP frequency in comparison with the CCA method and other two competing methods (multiway CCA (MwayCCA) and phase constrained CCA (PCCA)), especially for a small number of channels and a short time window length. The superiority indicates that the proposed MsetCCA method is a new promising candidate for frequency recognition in SSVEP-based BCIs.

  6. Single-Trial Linear Correlation Analysis: Application to characterization of stimulus modality effects

    Directory of Open Access Journals (Sweden)

    Christoforos eChristoforou

    2013-03-01

    Full Text Available A key objective in systems and cognitive neuroscience is to establish associations between behavioral measures and concurrent neuronal activity. Single-trial analysis has been proposed as a novel method for characterizing such correlates by first extracting neural components that maximally discriminate trials on a categorical variable, (e.g., hard vs. easy, correct vs. incorrect etc., and then correlate those components to a continues dependent variable of interest , e.g. reaction time, difficulty Index, etc. However, often times in experiment design it is difficult to either define meaningful categorical variables, or to record enough trials for the method to extract the discriminant components. Experiments designed for the study of the effects of stimulus presentation modality in working memory provide such a scenario, as will be exemplified. In this paper, we proposed a new approach to single-trial analysis in which we directly extract neural activity that maximally correlates to single-trial manual response times; eliminating the need to define an arbitrary categorical variable. We demonstrate our method on real EEG data recordings from the study of stimulus presentation modality effect.

  7. 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.

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

    Science.gov (United States)

    Zonglin, Li; Guangmin, Hu; Xingmiao, Yao; Dan, Yang

    2008-12-01

    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.

  9. 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.

  10. 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...... and covariance, for which we obtain the optimal rate of convergence. We demonstrate some positive semidefinite estimators of the covariation and construct a positive semidefinite estimator of the conditional covariance matrix in the central limit theorem. Furthermore, we indicate how the assumptions on the noise...... 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....

  11. 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.

  12. 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.

  13. 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.

  14. 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.)

  15. 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.

  16. Automatic detection of noisy channels in fNIRS signal based on correlation analysis.

    Science.gov (United States)

    Guerrero-Mosquera, Carlos; Borragán, Guillermo; Peigneux, Philippe

    2016-09-15

    fNIRS signals can be contaminated by distinct sources of noise. While most of the noise can be corrected using digital filters, optimized experimental paradigms or pre-processing methods, few approaches focus on the automatic detection of noisy channels. In the present study, we propose a new method that detect automatically noisy fNIRS channels by combining the global correlations of the signal obtained from sliding windows (Cui et al., 2010) with correlation coefficients extracted experimental conditions defined by triggers. The validity of the method was evaluated on test data from 17 participants, for a total of 16 NIRS channels per subject, positioned over frontal, dorsolateral prefrontal, parietal and occipital areas. Additionally, the detection of noisy channels was tested in the context of different levels of cognitive requirement in a working memory N-back paradigm. Bad channels detection accuracy, defined as the proportion of bad NIRS channels correctly detected among the total number of channels examined, was close to 91%. Under different cognitive conditions the area under the Receiver Operating Curve (AUC) increased from 60.5% (global correlations) to 91.2% (local correlations). Our results show that global correlations are insufficient for detecting potentially noisy channels when the whole data signal is included in the analysis. In contrast, adding specific local information inherent to the experimental paradigm (e.g., cognitive conditions in a block or event-related design), improved detection performance for noisy channels. Also, we show that automated fNIRS channel detection can be achieved with high accuracy at low computational cost. Copyright © 2016 Elsevier B.V. All rights reserved.

  17. 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.

  18. 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

  19. Bayesian analysis on meta-analysis of case-control studies accounting for within-study correlation.

    Science.gov (United States)

    Chen, Yong; Chu, Haitao; Luo, Sheng; Nie, Lei; Chen, Sining

    2015-12-01

    In retrospective studies, odds ratio is often used as the measure of association. Under independent beta prior assumption, the exact posterior distribution of odds ratio given a single 2 × 2 table has been derived in the literature. However, independence between risks within the same study may be an oversimplified assumption because cases and controls in the same study are likely to share some common factors and thus to be correlated. Furthermore, in a meta-analysis of case-control studies, investigators usually have multiple 2 × 2 tables. In this article, we first extend the published results on a single 2 × 2 table to allow within study prior correlation while retaining the advantage of closed-form posterior formula, and then extend the results to multiple 2 × 2 tables and regression setting. The hyperparameters, including within study correlation, are estimated via an empirical Bayes approach. The overall odds ratio and the exact posterior distribution of the study-specific odds ratio are inferred based on the estimated hyperparameters. We conduct simulation studies to verify our exact posterior distribution formulas and investigate the finite sample properties of the inference for the overall odds ratio. The results are illustrated through a twin study for genetic heritability and a meta-analysis for the association between the N-acetyltransferase 2 (NAT2) acetylation status and colorectal cancer. © The Author(s) 2011.

  20. 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

  1. Improving the Measurement of Shared Cultural Schemas with Correlational Class Analysis: Theory and Method

    Directory of Open Access Journals (Sweden)

    Andrei Boutyline

    2017-05-01

    Full Text Available Measurement of shared cultural schemas is a central methodological challenge for the sociology of culture. Relational Class Analysis (RCA is a recently developed technique for identifying such schemas in survey data. However, existing work lacks a clear definition of such schemas, which leaves RCA’s accuracy largely unknown. Here, I build on the theoretical intuitions behind RCA to arrive at this definition. I demonstrate that shared schemas should result in linear dependencies between survey rows—the relationship usually measured with Pearson’s correlation. I thus modify RCA into a “Correlational Class Analysis” (CCA. When I compare the methods using a broad set of simulations, results show that CCA is reliably more accurate at detecting shared schemas than RCA, even in scenarios that substantially violate CCA’s assumptions. I find no evidence of theoretical settings where RCA is more accurate. I then revisit a previous RCA analysis of the 1993 General Social Survey musical tastes module. Whereas RCA partitioned these data into three schematic classes, CCA partitions them into four. I compare these results with a multiple-groups analysis in structural equation modeling and find that CCA’s partition yields greatly improved model fit over RCA. I conclude with a parsimonious framework for future work.

  2. Correlations of Ezrin Expression with Pathological Characteristics and Prognosis of Osteosarcoma: A Meta-Analysis

    Directory of Open Access Journals (Sweden)

    Da-Hang Zhao

    2014-01-01

    Full Text Available We conducted a meta-analysis to comprehensively evaluate the correlations of ezrin expression with pathological characteristics and the prognosis of osteosarcoma. The MEDLINE (1966–2013, the Cochrane Library Database, EMBASE, CINAHL, Web of Science (1945–2013, and the Chinese Biomedical Database were searched without language restrictions. Meta-analyses conducted using STATA software were calculated. Ten studies met the inclusion criteria, including 459 patients with osteosarcoma. Meta-analysis results illustrated that ezrin expression may be closely associated with the recurrence of osteosarcoma or metastasis in osteosarcoma. Our findings also demonstrated that patients with grade III-IV osteosarcoma showed a higher frequency of ezrin expression than those with histological grade I-II osteosarcoma. Furthermore, we found that patients with positive expression of ezrin exhibited a shorter overall survival than those with negative ezrin expression. The results also indicated that positive ezrin expression was strongly correlated with poorer metastasis-free survival. Nevertheless, no significant relationships were observed between ezrin expression and clinical variables (age and gender. In the current meta-analysis, our results illustrated significant relationships of ezrin expression with pathological characteristics and prognosis of osteosarcoma. Thus, ezrin expression could be a promising marker in predicting the clinical outcome of patients with osteosarcoma.

  3. A non-parametric conditional bivariate reference region with an application to height/weight measurements on normal girls

    DEFF Research Database (Denmark)

    Petersen, Jørgen Holm

    2009-01-01

    A conceptually simple two-dimensional conditional reference curve is described. The curve gives a decision basis for determining whether a bivariate response from an individual is "normal" or "abnormal" when taking into account that a third (conditioning) variable may influence the bivariate...... response. The reference curve is not only characterized analytically but also by geometric properties that are easily communicated to medical doctors - the users of such curves. The reference curve estimator is completely non-parametric, so no distributional assumptions are needed about the two......-dimensional response. An example that will serve to motivate and illustrate the reference is the study of the height/weight distribution of 7-8-year-old Danish school girls born in 1930, 1950, or 1970....

  4. Effects of imputation on correlation: implications for analysis of mass spectrometry data from multiple biological matrices.

    Science.gov (United States)

    Taylor, Sandra L; Ruhaak, L Renee; Kelly, Karen; Weiss, Robert H; Kim, Kyoungmi

    2017-03-01

    With expanded access to, and decreased costs of, mass spectrometry, investigators are collecting and analyzing multiple biological matrices from the same subject such as serum, plasma, tissue and urine to enhance biomarker discoveries, understanding of disease processes and identification of therapeutic targets. Commonly, each biological matrix is analyzed separately, but multivariate methods such as MANOVAs that combine information from multiple biological matrices are potentially more powerful. However, mass spectrometric data typically contain large amounts of missing values, and imputation is often used to create complete data sets for analysis. The effects of imputation on multiple biological matrix analyses have not been studied. We investigated the effects of seven imputation methods (half minimum substitution, mean substitution, k-nearest neighbors, local least squares regression, Bayesian principal components analysis, singular value decomposition and random forest), on the within-subject correlation of compounds between biological matrices and its consequences on MANOVA results. Through analysis of three real omics data sets and simulation studies, we found the amount of missing data and imputation method to substantially change the between-matrix correlation structure. The magnitude of the correlations was generally reduced in imputed data sets, and this effect increased with the amount of missing data. Significant results from MANOVA testing also were substantially affected. In particular, the number of false positives increased with the level of missing data for all imputation methods. No one imputation method was universally the best, but the simple substitution methods (Half Minimum and Mean) consistently performed poorly. © The Author 2016. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

  5. Bivariate Extension of the Quadrature Method of Moments for Modeling Simultaneous Coagulation and Sintering of Particle Populations.

    Science.gov (United States)

    Wright, Douglas L.; McGraw, Robert; Rosner, Daniel E.

    2001-04-15

    We extendthe application of moment methods to multivariate suspended particle population problems-those for which size alone is insufficient to specify the state of a particle in the population. Specifically, a bivariate extension of the quadrature method of moments (QMOM) (R. McGraw, Aerosol Sci. Technol. 27, 255 (1997)) is presented for efficiently modeling the dynamics of a population of inorganic nanoparticles undergoing simultaneous coagulation and particle sintering. Continuum regime calculations are presented for the Koch-Friedlander-Tandon-Rosner model, which includes coagulation by Brownian diffusion (evaluated for particle fractal dimensions, D(f), in the range 1.8-3) and simultaneous sintering of the resulting aggregates (P. Tandon and D. E. Rosner, J. Colloid Interface Sci. 213, 273 (1999)). For evaluation purposes, and to demonstrate the computational efficiency of the bivariate QMOM, benchmark calculations are carried out using a high-resolution discrete method to evolve the particle distribution function n(nu, a) for short to intermediate times (where nu and a are particle volume and surface area, respectively). Time evolution of a selected set of 36 low-order mixed moments is obtained by integration of the full bivariate distribution and compared with the corresponding moments obtained directly using two different extensions of the QMOM. With the more extensive treatment, errors of less than 1% are obtained over substantial aerosol evolution, while requiring only a few minutes (rather than days) of CPU time. Longer time QMOM simulations lend support to the earlier finding of a self-preserving limit for the dimensionless joint (nu, a) particle distribution function under simultaneous coagulation and sintering (Tandon and Rosner, 1999; D. E. Rosner and S. Yu, AIChE J., 47 (2001)). We demonstrate that, even in the bivariate case, it is possible to use the QMOM to rapidly model the approach to asymptotic behavior, allowing an immediate assessment of

  6. 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.

  7. [The optimization of guanosine fermentation based on process parameter correlation analysis].

    Science.gov (United States)

    Cai, Xianpeng; Chen, Shuangxi; Chu, Ju; Zhuang, Yingping; Zhang, Siliang; Wang, Huanzhang; Liu, Yongmei

    2002-04-01

    The characteristic of Bacillus subtilis fermentation process of guanosine on 50 L fermentor was analyzed. Based on determination of on-line and off-line parameter, using correlation analysis, the technology study of physiologic regulation was combined with the metabolic flux distribution of synthesis process. The metabolic flux shift from HMP to EMP and TCA cycle during fermentation was found. The reason of the flux shift was preliminary analyzed, based on which the procedure was optimized to increase the yield of guanosine to 30 g/L.

  8. Tracing correlations of corrosion products and microclimate data on outdoor bronze monuments by Principal Component Analysis

    International Nuclear Information System (INIS)

    Polikreti, Kyriaki; Argyropoulos, Vassilike; Charalambous, Demetres; Vossou, Aggelina; Perdikatsis, Vassilis; Apostolaki, Chryssa

    2009-01-01

    Although the corrosion of outdoor bronzes has been extensively studied for the last decades, there is no quantitative correlation of corrosion products to microclimatic factors. The present work aims to demonstrate how Principal Component Analysis (PCA) can serve this purpose. Thirty corrosion product samples were collected from the bronze monument of Theodoros Kolokotronis (Nafplio, Greece) and analysed using X-Ray Diffractometry (XRD). The quantitative XRD data together with data on surface orientation and exposure to rain or wind were treated by PCA and three distinct groups were found. Each group includes samples of similar composition and microclimate characteristics showing that PCA may give useful information on corrosion mechanisms.

  9. 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.)

  10. 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.

  11. 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.

  12. Comparing Johnson’s SBB, Weibull and Logit-Logistic bivariate distributions for modeling tree diameters and heights using copulas

    Directory of Open Access Journals (Sweden)

    Jose Javier Gorgoso-Varela

    2016-04-01

    Full Text Available Aim of study: In this study we compare the accuracy of three bivariate distributions: Johnson’s SBB, Weibull-2P and LL-2P functions for characterizing the joint distribution of tree diameters and heights.Area of study: North-West of Spain.Material and methods: Diameter and height measurements of 128 plots of pure and even-aged Tasmanian blue gum (Eucalyptus globulus Labill. stands located in the North-west of Spain were considered in the present study. The SBB bivariate distribution was obtained from SB marginal distributions using a Normal Copula based on a four-parameter logistic transformation. The Plackett Copula was used to obtain the bivariate models from the Weibull and Logit-logistic univariate marginal distributions. The negative logarithm of the maximum likelihood function was used to compare the results and the Wilcoxon signed-rank test was used to compare the related samples of these logarithms calculated for each sample plot and each distribution.Main results: The best results were obtained by using the Plackett copula and the best marginal distribution was the Logit-logistic.Research highlights: The copulas used in this study have shown a good performance for modeling the joint distribution of tree diameters and heights. They could be easily extended for modelling multivariate distributions involving other tree variables, such as tree volume or biomass.

  13. Comparing Johnson’s SBB, Weibull and Logit-Logistic bivariate distributions for modeling tree diameters and heights using copulas

    Energy Technology Data Exchange (ETDEWEB)

    Cardil Forradellas, A.; Molina Terrén, D.M.; Oliveres, J.; Castellnou, M.

    2016-07-01

    Aim of study: In this study we compare the accuracy of three bivariate distributions: Johnson’s SBB, Weibull-2P and LL-2P functions for characterizing the joint distribution of tree diameters and heights. Area of study: North-West of Spain. Material and methods: Diameter and height measurements of 128 plots of pure and even-aged Tasmanian blue gum (Eucalyptus globulus Labill.) stands located in the North-west of Spain were considered in the present study. The SBB bivariate distribution was obtained from SB marginal distributions using a Normal Copula based on a four-parameter logistic transformation. The Plackett Copula was used to obtain the bivariate models from the Weibull and Logit-logistic univariate marginal distributions. The negative logarithm of the maximum likelihood function was used to compare the results and the Wilcoxon signed-rank test was used to compare the related samples of these logarithms calculated for each sample plot and each distribution. Main results: The best results were obtained by using the Plackett copula and the best marginal distribution was the Logit-logistic. Research highlights: The copulas used in this study have shown a good performance for modeling the joint distribution of tree diameters and heights. They could be easily extended for modelling multivariate distributions involving other tree variables, such as tree volume or biomass. (Author)

  14. 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.

  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. Analysis combining correlated glaucoma traits identifies five new risk loci for open-angle glaucoma.

    Science.gov (United States)

    Gharahkhani, Puya; Burdon, Kathryn P; Cooke Bailey, Jessica N; Hewitt, Alex W; Law, Matthew H; Pasquale, Louis R; Kang, Jae H; Haines, Jonathan L; Souzeau, Emmanuelle; Zhou, Tiger; Siggs, Owen M; Landers, John; Awadalla, Mona; Sharma, Shiwani; Mills, Richard A; Ridge, Bronwyn; Lynn, David; Casson, Robert; Graham, Stuart L; Goldberg, Ivan; White, Andrew; Healey, Paul R; Grigg, John; Lawlor, Mitchell; Mitchell, Paul; Ruddle, Jonathan; Coote, Michael; Walland, Mark; Best, Stephen; Vincent, Andrea; Gale, Jesse; RadfordSmith, Graham; Whiteman, David C; Montgomery, Grant W; Martin, Nicholas G; Mackey, David A; Wiggs, Janey L; MacGregor, Stuart; Craig, Jamie E

    2018-02-15

    Open-angle glaucoma (OAG) is a major cause of blindness worldwide. To identify new risk loci for OAG, we performed a genome-wide association study in 3,071 OAG cases and 6,750 unscreened controls, and meta-analysed the results with GWAS data for intraocular pressure (IOP) and optic disc parameters (the overall meta-analysis sample size varying between 32,000 to 48,000 participants), which are glaucoma-related traits. We identified and independently validated four novel genome-wide significant associations within or near MYOF and CYP26A1, LINC02052 and CRYGS, LMX1B, and LMO7 using single variant tests, one additional locus (C9) using gene-based tests, and two genetic pathways - "response to fluid shear stress" and "abnormal retina morphology" - in pathway-based tests. Interestingly, some of the new risk loci contribute to risk of other genetically-correlated eye diseases including myopia and age-related macular degeneration. To our knowledge, this study is the first integrative study to combine genetic data from OAG and its correlated traits to identify new risk variants and genetic pathways, highlighting the future potential of combining genetic data from genetically-correlated eye traits for the purpose of gene discovery and mapping.

  17. 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.

  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. On the mode I fracture analysis of cracked Brazilian disc using a digital image correlation method

    Science.gov (United States)

    Abshirini, Mohammad; Soltani, Nasser; Marashizadeh, Parisa

    2016-03-01

    Mode I of fracture of centrally cracked Brazilian disc was investigated experimentally using a digital image correlation (DIC) method. Experiments were performed on PMMA polymers subjected to diametric-compression load. The displacement fields were determined by a correlation between the reference and the deformed images captured before and during loading. The stress intensity factors were calculated by displacement fields using William's equation and the least square algorithm. The parameters involved in the accuracy of SIF calculation such as number of terms in William's equation and the region of analysis around the crack were discussed. The DIC results were compared with the numerical results available in literature and a very good agreement between them was observed. By extending the tests up to the critical state, mode I fracture toughness was determined by analyzing the image of specimen captured at the moment before fracture. The results showed that the digital image correlation was a reliable technique for the calculation of the fracture toughness of brittle materials.

  20. 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.

  1. Elastic-plastic finite element analysis-to-test correlation for structures subjected to dynamic loading

    Energy Technology Data Exchange (ETDEWEB)

    Hodge, S.C.; Minicucci, J.M. [Electric Boat Corp., Groton, CT (United States)

    1997-11-01

    A test program was undertaken to demonstrate the ability of elastic-plastic finite element methods to predict dynamic inelastic response for simple structural members. Cantilever and fixed-beam specimens were tested to levels that produced plastic straining in the range of 2.0% and to 3.0% and permanent sets. Acceleration, strain, and displacement data were recorded for use in analytical correlation. Correlation analyses were performed using the ABAQUS finite element code. Results of the correlation show that current elastic-plastic analysis techniques accurately capture dynamic inelastic response (displacement, acceleration) due to rapidly applied dynamic loading. Peak elastic and inelastic surface strains are accurately predicted. To accurately capture inelastic straining near connections, a solid model, including fillet welds, is necessary. The hardening models currently available in the ABAQUS code (isotropic, kinematic) do not accurately capture inelastic strain reversals caused by specimen rebound. Analyses performed consistently underpredicted the peak strain level of the first inelastic reversal and the rebound deflection and overpredicted the permanent set of structures experiencing inelastic rebound. Based on these findings, an improved hardening model is being implemented in the ABAQUS code by the developers. The intent of this model upgrade is to improve the ability of the program to capture inelastic strain reversals and to predict permanent sets.

  2. Evaluation of Factors Affecting E-Bike Involved Crash and E-Bike License Plate Use in China Using a Bivariate Probit Model

    Directory of Open Access Journals (Sweden)

    Yanyong Guo

    2017-01-01

    Full Text Available The primary objective of this study is to evaluate factors affecting e-bike involved crash and license plate use in China. E-bike crashes data were collected from police database and completed through a telephone interview. Noncrash samples were collected by a questionnaire survey. A bivariate probit (BP model was developed to simultaneously examine the significant factors associated with e-bike involved crash and e-bike license plate and to account for the correlations between them. Marginal effects for contributory factors were calculated to quantify their impacts on the outcomes. The results show that several contributory factors, including gender, age, education level, driver license, car in household, experiences in using e-bike, law compliance, and aggressive driving behaviors, are found to have significant impacts on both e-bike involved crash and license plate use. Moreover, type of e-bike, frequency of using e-bike, impulse behavior, degree of riding experience, and risk perception scale are found to be associated with e-bike involved crash. It is also found that e-bike involved crash and e-bike license plate use are strongly correlated and are negative in direction. The result enhanced our comprehension of the factors related to e-bike involved crash and e-bike license plate use.

  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. 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

  5. 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.

  6. 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.

  7. Correlation, path coefficient analysis and heritability for agronomic characters of oil palm (Elaeis guineensis Jacq.

    Directory of Open Access Journals (Sweden)

    Chaumongkol, Y.

    2001-11-01

    Full Text Available A study of correlation, path coefficient analysis and heritablity for some agronomic characters of oil palm was investigated during February 1998 to January 2002. The oil palm population used in this experiment was derived from F1 tenera hybrids which were collected from various oil palm plantations in Southern Thailand. One good performance bunch (i.e., big bunch, thin shell was selected from each plantation and four to six seeds per selected bunch were used for cultivation. One thousand thirty eight plants were grown at Klong Hoi Khong Research Station, Faculty of Natural Resources, Prince of Songkla University, Songkhla, in 1989. Forty five palms consisted of Dura, Tenera and Pisifera types with 18, 18 and 9 plants respectively, were selected by randomization and tagged for investigation. The oil palm bunch yield and yield component characters were observed from individual palm for 4 years (February 1998 to January 2002. The bunch composition characters were analysed from a single bunch of each palm, sampled between June to October 1999. The results showed that in F2 plants of oil palm, the correlation and the path coefficient between characters relating to oil yield and %oil/bunch varied according to oil palm types (Dura, Tenera and Pisifera. In Dura and Tenera palms, the characters which gave highly positive correlation with a large direct and indirect positive effects on oil yield and %oil/bunch were total bunch weight, %oil/bunch, %fruit/bunch and %oil/fruit. In case of Pisifera palms, the characters which gave highly positive correlation with a large direct and indirect positive effects on oil yield and %oil/bunch were total bunch weight, number of bunches, single bunch weight, %oil/bunch and %fruit/bunch. However, from all investigated characters in F2 plants, only %mesocarp/fruit, %oil/fruit and %fruit/bunch showed the high values of broad sense heritabilities.

  8. 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...

  9. 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.

  10. Full correlation matrix analysis (FCMA): An unbiased method for task-related functional connectivity.

    Science.gov (United States)

    Wang, Yida; Cohen, Jonathan D; Li, Kai; Turk-Browne, Nicholas B

    2015-08-15

    The analysis of brain imaging data often requires simplifying assumptions because exhaustive analyses are computationally intractable. Standard univariate and multivariate analyses of brain activity ignore interactions between regions and analyses of interactions (functional connectivity) reduce the computational challenge by using seed regions of interest or brain parcellations. To meet this challenge, we developed full correlation matrix analysis (FCMA), which leverages and optimizes algorithms from parallel computing and machine learning to efficiently analyze the pairwise correlations of all voxels in the brain during different cognitive tasks, with the goal of identifying task-related interactions in an unbiased manner. When applied to a localizer dataset on a small compute cluster, FCMA accelerated a naive, serial approach by four orders of magnitude, reducing running time from two years to one hour. In addition to this performance gain, FCMA emphasized different brain areas than existing methods. In particular, beyond replicating known category selectivity in visual cortex, FCMA also revealed a region of medial prefrontal cortex whose selectivity derived from differential patterns of functional connectivity across categories. For benchmarking, we started with a naive approach and progressively built up to the complete FCMA procedure by adding optimized classifier algorithms, multi-threaded parallelism, and multi-node parallelism. To evaluate what can be learned with FCMA, we compared it against multivariate pattern analysis of activity and seed-based analysis of functional connectivity. FCMA demonstrates how advances in computer science can alleviate computational bottlenecks in neuroscience. We have released a software toolbox to help others evaluate FCMA. Copyright © 2015 Elsevier B.V. All rights reserved.

  11. Finite Element Analysis and Test Correlation of a 10-Meter Inflation-Deployed Solar Sail

    Science.gov (United States)

    Sleight, David W.; Michii, Yuki; Lichodziejewski, David; Derbes, Billy; Mann. Troy O.; Slade, Kara N.; Wang, John T.

    2005-01-01

    Under the direction of the NASA In-Space Propulsion Technology Office, the team of L Garde, NASA Jet Propulsion Laboratory, Ball Aerospace, and NASA Langley Research Center has been developing a scalable solar sail configuration to address NASA's future space propulsion needs. Prior to a flight experiment of a full-scale solar sail, a comprehensive phased test plan is currently being implemented to advance the technology readiness level of the solar sail design. These tests consist of solar sail component, subsystem, and sub-scale system ground tests that simulate the vacuum and thermal conditions of the space environment. Recently, two solar sail test articles, a 7.4-m beam assembly subsystem test article and a 10-m four-quadrant solar sail system test article, were tested in vacuum conditions with a gravity-offload system to mitigate the effects of gravity. This paper presents the structural analyses simulating the ground tests and the correlation of the analyses with the test results. For programmatic risk reduction, a two-prong analysis approach was undertaken in which two separate teams independently developed computational models of the solar sail test articles using the finite element analysis software packages: NEiNastran and ABAQUS. This paper compares the pre-test and post-test analysis predictions from both software packages with the test data including load-deflection curves from static load tests, and vibration frequencies and mode shapes from vibration tests. The analysis predictions were in reasonable agreement with the test data. Factors that precluded better correlation of the analyses and the tests were uncertainties in the material properties, test conditions, and modeling assumptions used in the analyses.

  12. Clinical value of magnetoencephalographic spike propagation represented by spatiotemporal source analysis: correlation with surgical outcome.

    Science.gov (United States)

    Tanaka, Naoaki; Peters, Jurriaan M; Prohl, Anna K; Takaya, Shigetoshi; Madsen, Joseph R; Bourgeois, Blaise F; Dworetzky, Barbara A; Hämäläinen, Matti S; Stufflebeam, Steven M

    2014-02-01

    To investigate the correlation between spike propagation represented by spatiotemporal source analysis of magnetoencephalographic (MEG) spikes and surgical outcome in patients with temporal lobe epilepsy. Thirty-seven patients were divided into mesial (n=27) and non-mesial (n=10) groups based on the presurgical evaluation. In each patient, ten ipsilateral spikes were averaged, and spatiotemporal source maps of the averaged spike were obtained by using minimum norm estimate. Regions of interest (ROIs) were created including temporoparietal, inferior frontal, mesial temporal, anterior and posterior part of the lateral temporal cortex. We extracted activation values from the source maps and the threshold was set at half of the maximum activation at the peak latency. The leading and propagated areas of the spike were defined as those ROIs with activation reaching the threshold at the earliest and at the peak latencies, respectively. Surgical outcome was assessed based on Engel's classification. Binary variables were created from leading areas (restricted to the anterior and mesial temporal ROIs or not) and from propagation areas (involving the temporoparietal ROI or not), and for surgical outcome (Class I or not). Fisher's exact test was used for significance testing. In total and mesial group, restricted anterior/mesial temporal leading areas were correlated with Class I (p<0.05). Temporoparietal propagation was correlated with Class II-IV (p<0.05). For the non-mesial group, no significant relation was found. Spike propagation patterns represented by spatiotemporal source analysis of MEG spikes may provide useful information for prognostic implication in presurgical evaluation of epilepsy. Copyright © 2013 Elsevier B.V. All rights reserved.

  13. 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.

  14. 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.

  15. Improving defect visibility in square pulse thermography of metallic components using correlation analysis

    Science.gov (United States)

    Xu, Changhang; Xie, Jing; Huang, Weiping; Chen, Guoming; Gong, Xumei

    2018-03-01

    Infrared (IR) thermography has gained wide applications as an important non-destructive testing (NDT) technique. Improving defect visibility is critical to achieving an accurate detection result through IR thermography. In this study, we propose a novel approach to improving defect visibility in square pulse thermography (SPT) of metallic components. In the proposed approach, the correlation function of contrast (CFC) is defined for the first time. Based on the theories of heat conduction and of correlation analysis, the differences of CFC between defects and sound regions are determined. We found that the peak lag time of the CFC is an effective feature for discriminating defects and sound regions in SPT. A new image is then constructed using the peak lag time of the CFC to improve defect visibility. To verify the efficiency of the proposed approach, an experiment was conducted on a steel specimen, and the principle component analysis (PCA) and the presented approach were compared. The results show that through the proposed approach, defects in metallic components can be indicated more clearly and detected more accurately.

  16. 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.

  17. Principal component regression analysis with SPSS.

    Science.gov (United States)

    Liu, R X; Kuang, J; Gong, Q; Hou, X L

    2003-06-01

    The paper introduces all indices of multicollinearity diagnoses, the basic principle of principal component regression and determination of 'best' equation method. The paper uses an example to describe how to do principal component regression analysis with SPSS 10.0: including all calculating processes of the principal component regression and all operations of linear regression, factor analysis, descriptives, compute variable and bivariate correlations procedures in SPSS 10.0. The principal component regression analysis can be used to overcome disturbance of the multicollinearity. The simplified, speeded up and accurate statistical effect is reached through the principal component regression analysis with SPSS.

  18. 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.

  19. 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.

  20. Spatial correlation analysis of the pharmacological conversion of sustained atrial fibrillation in conscious goats by cibenzoline.

    Science.gov (United States)

    Hoekstra, B P; Diks, C G; Allessie, M A; DeGoede, J

    2000-10-01

    The nonlinear spatial redundancy and the linear spatial correlation function were used to investigate to what extent non-linearity was involved in the coupling of atrial regions and how organization in activation patterns of sustained atrial fibrillation (AF) had been modified by administration of the class IC agent cibenzoline in the experimental model of sustained AF in instrumented conscious goats. Electrograms were measured in five goats during sustained AF and when the fibrillation interval had been prolonged to about 25%, 50% and 85% (CIB25, CIB50, CIB85) with respect to control. The nonlinear association length and linear correlation length were estimated along the principal axes of two-dimensional correlation maps estimated from the spatial redundancy and the spatial correlation function, respectively. The estimated short axis association length in the right atrium increased already shortly after the start of infusion (CIB25, +61%), and remained significantly different from control during the experiment, including the effects of non-simultaneous interaction. At CIB85 the association length had almost become twice as long with respect to control (increase from 16 to 29 mm, 89%), while in the left atrium changes were less pronounced (increase from 9 to 12 mm, +32%). The linearized association length which was estimated using multivariate surrogate data increased more gradually and was less sensitive to changes in spatial organization. The results of the spatial correlation analysis suggest that the drug-induced nonlinearity in the spatio-temporal dynamics of sustained AF is related to activation patterns which are characterized by extended uniformly propagating fibrillation wavefronts (AF type I). We conclude that cibenzoline enhanced the spatial organization of sustained AF associated with a transition from type II to type I AF activation patterns. This may destabilize the perpetuation of AF since an increase in association length is equivalent to a