Structural Analysis of Covariance and Correlation Matrices.

Science.gov (United States)

Joreskog, Karl G.

1978-01-01

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

Generalized Frequency-Domain Correlator for Software GPS Receiver: Preliminary Test Results and Analysis (PREPRINT)

National Research Council Canada - National Science Library

Yang, Chun; Miller, Mikel; Nguyen, Thao; Akos, Dennis

2006-01-01

.... The use of a GFDC can offer several advantages. First, as a generalization of the FFT-implemented correlation with a block repetitive processing capability, it enables fast acquisition through simultaneous code delay and Doppler frequency search...

A general first-order global sensitivity analysis method

International Nuclear Information System (INIS)

Xu Chonggang; Gertner, George Zdzislaw

2008-01-01

Fourier amplitude sensitivity test (FAST) is one of the most popular global sensitivity analysis techniques. The main mechanism of FAST is to assign each parameter with a characteristic frequency through a search function. Then, for a specific parameter, the variance contribution can be singled out of the model output by the characteristic frequency. Although FAST has been widely applied, there are two limitations: (1) the aliasing effect among parameters by using integer characteristic frequencies and (2) the suitability for only models with independent parameters. In this paper, we synthesize the improvement to overcome the aliasing effect limitation [Tarantola S, Gatelli D, Mara TA. Random balance designs for the estimation of first order global sensitivity indices. Reliab Eng Syst Safety 2006; 91(6):717-27] and the improvement to overcome the independence limitation [Xu C, Gertner G. Extending a global sensitivity analysis technique to models with correlated parameters. Comput Stat Data Anal 2007, accepted for publication]. In this way, FAST can be a general first-order global sensitivity analysis method for linear/nonlinear models with as many correlated/uncorrelated parameters as the user specifies. We apply the general FAST to four test cases with correlated parameters. The results show that the sensitivity indices derived by the general FAST are in good agreement with the sensitivity indices derived by the correlation ratio method, which is a non-parametric method for models with correlated parameters

Oblique rotaton in canonical correlation analysis reformulated as maximizing the generalized coefficient of determination.

Science.gov (United States)

Satomura, Hironori; Adachi, Kohei

2013-07-01

To facilitate the interpretation of canonical correlation analysis (CCA) solutions, procedures have been proposed in which CCA solutions are orthogonally rotated to a simple structure. In this paper, we consider oblique rotation for CCA to provide solutions that are much easier to interpret, though only orthogonal rotation is allowed in the existing formulations of CCA. Our task is thus to reformulate CCA so that its solutions have the freedom of oblique rotation. Such a task can be achieved using Yanai's (Jpn. J. Behaviormetrics 1:46-54, 1974; J. Jpn. Stat. Soc. 11:43-53, 1981) generalized coefficient of determination for the objective function to be maximized in CCA. The resulting solutions are proved to include the existing orthogonal ones as special cases and to be rotated obliquely without affecting the objective function value, where ten Berge's (Psychometrika 48:519-523, 1983) theorems on suborthonormal matrices are used. A real data example demonstrates that the proposed oblique rotation can provide simple, easily interpreted CCA solutions.

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

Multifractal detrended cross-correlation analysis in the MENA area

Science.gov (United States)

El Alaoui, Marwane; Benbachir, Saâd

2013-12-01

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

Correlation between generalized joint hypermobility and hallux valgus

Directory of Open Access Journals (Sweden)

A. A. Kardanov

2015-01-01

Full Text Available Purpose: to evaluate correlation between generalized joint hypermobility, forefoot deformities and elasticity of the first ray of the foot. Material and methods. We examined 138 patients with complaints related with deformities at the forefoot level. During this study the medical history was obtained, the elasticity type of the feet was defined and the degree of motion of the medial metatarsal-cuneiform joint was evaluated. Forefoot elasticity was identified by bringing together the heads I and V metatarsal bones with fingers. If convergence occurred with little resistance, those feet were called hyperelastic. The convergence of the heads I and V metatarsal bones of the foot with an average type of elasticity occurred with resistance. It was impossible to converge the heads of I and V metatarsal bones. Due to the results of weight-bearing and non-weight bearing X-ray, analysis of the main radiographic angles of the foot was performed: between I and V metatarsal bones, between the first and second metatarsal bones and between the first metatarsal bone and proximal phalanx of the great toe. Calculation formula of the forefoot flatness index, showing the average ratios of basic radiographic angles of the foot on the x-ray images (weight-bearing and non-weight bearing was created. An assessment of total joint hypermobility using Beighton scale and evaluation of first ray deformity using DuPont scale were performed. Statistical analysis of obtained data was performed, as a result of which significantly strong correlation between total joint hypermobility, forefoot elasticity and valgus deviation of the great toe were revealed. Results. 11% of the feet were hyperelastic. Calculation of the index of forefoot flatness showed that forefoot flatness wasn’t significant for a rigid foot - 5.6 %, for the feet with an average degree of mobility it was 6.0% and it was expressed for hypemobile feet - 12.3 %. Strong correlation relation between the forefeet

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.

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

Science.gov (United States)

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

2014-01-01

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

Generalized laws of thermodynamics in the presence of correlations.

Science.gov (United States)

Bera, Manabendra N; Riera, Arnau; Lewenstein, Maciej; Winter, Andreas

2017-12-19

The laws of thermodynamics, despite their wide range of applicability, are known to break down when systems are correlated with their environments. Here we generalize thermodynamics to physical scenarios which allow presence of correlations, including those where strong correlations are present. We exploit the connection between information and physics, and introduce a consistent redefinition of heat dissipation by systematically accounting for the information flow from system to bath in terms of the conditional entropy. As a consequence, the formula for the Helmholtz free energy is accordingly modified. Such a remedy not only fixes the apparent violations of Landauer's erasure principle and the second law due to anomalous heat flows, but also leads to a generally valid reformulation of the laws of thermodynamics. In this information-theoretic approach, correlations between system and environment store work potential. Thus, in this view, the apparent anomalous heat flows are the refrigeration processes driven by such potentials.

[Correlation between iridology and general pathology].

Science.gov (United States)

Demea, Sorina

2002-01-01

The research proposal is to evaluate the association between certain irian signs and general pathology of studied patients. There were studied 57 hospitalized patients; there was taken over all their iris images, which were analyzed through iridological protocols; in the same time the pathology of these patients was noted from their records in the hospital, concordant with the clinical diagnosis; all these information were included in a database for a computerised processing. The correlations resulted from, shows a high connection between the irian constitution establish through iridological criteria and the existent pathology. Iris examination can be very useful for diagnosis of a certain general pathology, in a holistic approach of the patient.

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.

Generalized interferometry - I: theory for interstation correlations

Science.gov (United States)

Fichtner, Andreas; Stehly, Laurent; Ermert, Laura; Boehm, Christian

2017-02-01

We develop a general theory for interferometry by correlation that (i) properly accounts for heterogeneously distributed sources of continuous or transient nature, (ii) fully incorporates any type of linear and nonlinear processing, such as one-bit normalization, spectral whitening and phase-weighted stacking, (iii) operates for any type of medium, including 3-D elastic, heterogeneous and attenuating media, (iv) enables the exploitation of complete correlation waveforms, including seemingly unphysical arrivals, and (v) unifies the earthquake-based two-station method and ambient noise correlations. Our central theme is not to equate interferometry with Green function retrieval, and to extract information directly from processed interstation correlations, regardless of their relation to the Green function. We demonstrate that processing transforms the actual wavefield sources and actual wave propagation physics into effective sources and effective wave propagation. This transformation is uniquely determined by the processing applied to the observed data, and can be easily computed. The effective forward model, that links effective sources and propagation to synthetic interstation correlations, may not be perfect. A forward modelling error, induced by processing, describes the extent to which processed correlations can actually be interpreted as proper correlations, that is, as resulting from some effective source and some effective wave propagation. The magnitude of the forward modelling error is controlled by the processing scheme and the temporal variability of the sources. Applying adjoint techniques to the effective forward model, we derive finite-frequency Fréchet kernels for the sources of the wavefield and Earth structure, that should be inverted jointly. The structure kernels depend on the sources of the wavefield and the processing scheme applied to the raw data. Therefore, both must be taken into account correctly in order to make accurate inferences on

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.

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...

Testing general relativity at cosmological scales: Implementation and parameter correlations

International Nuclear Information System (INIS)

Dossett, Jason N.; Ishak, Mustapha; Moldenhauer, Jacob

2011-01-01

The testing of general relativity at cosmological scales has become a possible and timely endeavor that is not only motivated by the pressing question of cosmic acceleration but also by the proposals of some extensions to general relativity that would manifest themselves at large scales of distance. We analyze here correlations between modified gravity growth parameters and some core cosmological parameters using the latest cosmological data sets including the refined Cosmic Evolution Survey 3D weak lensing. We provide the parametrized modified growth equations and their evolution. We implement known functional and binning approaches, and propose a new hybrid approach to evolve the modified gravity parameters in redshift (time) and scale. The hybrid parametrization combines a binned redshift dependence and a smooth evolution in scale avoiding a jump in the matter power spectrum. The formalism developed to test the consistency of current and future data with general relativity is implemented in a package that we make publicly available and call ISiTGR (Integrated Software in Testing General Relativity), an integrated set of modified modules for the publicly available packages CosmoMC and CAMB, including a modified version of the integrated Sachs-Wolfe-galaxy cross correlation module of Ho et al. and a new weak-lensing likelihood module for the refined Hubble Space Telescope Cosmic Evolution Survey weak gravitational lensing tomography data. We obtain parameter constraints and correlation coefficients finding that modified gravity parameters are significantly correlated with σ 8 and mildly correlated with Ω m , for all evolution methods. The degeneracies between σ 8 and modified gravity parameters are found to be substantial for the functional form and also for some specific bins in the hybrid and binned methods indicating that these degeneracies will need to be taken into consideration when using future high precision data.

Generalized inequalities for quantum correlations with hidden variables

International Nuclear Information System (INIS)

Vinduska, M.

1991-01-01

Renowned inequalities for quantum correlations are generalized for the case when quantum system cannot be described with an absolute independent measure of the probability. Such a formulation appears to be suitable for the formulation of the hidden variables theory in terms of non-Euclidean geometry. 10 refs

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

Science.gov (United States)

Angelucci, Filippo; Javeed, Mehzad; Mcgowan, Paul

1992-01-01

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

The Correlation between Polybrominated Diphenyl Ethers (PBDEs) and Thyroid Hormones in the General Population: A Meta-Analysis.

Science.gov (United States)

Zhao, Xuemin; Wang, Hailong; Li, Jing; Shan, Zhongyan; Teng, Weiping; Teng, Xiaochun

2015-01-01

Certain epidemiological studies have suggested exposure to polybrominated diphenyl ethers (PBDEs) affect the production and secretion of thyroid hormones (TH); however, conflicting results have been reported in different studies. There is not a convincing conclusion about this debate to date. To perform a meta-analysis determining if there are correlations between PBDEs exposure and the serum levels of TH. Medical and scientific literature databases were searched for articles that met the eligibility criteria. The included articles were assessed for methodological quality. The correlation coefficient values or regression coefficient values between PBDEs and thyroid stimulating hormone (TSH) or total thyroxine (TT4) from each article were used for analysis. Sixteen articles were included in this meta-analysis. Pearson correlation coefficients (r) were directly collected or calculated from data given in the articles. Then, Fisher's z transformation was performed to convert each correlation coefficient to an approximately normal distribution. For z values between PBDEs exposure and TSH levels, the pooled z value for 18 studies was 0.08 (95% CI: -0.06, 0.22), and indicated significant heterogeneity (I2 values = 90.7%). Subgroup analysis was performed based on the median values of serum PBDEs in each study, there was not significant heterogeneity in each of the four subgroups (I2 values <30%). In meta-analysis of z values between PBDEs exposure and the levels of TT4, the pooled z value for 11 studies was -0.02 (95% CI: -0.11, 0.08), and also indicated significant heterogeneity (I2 values = 57.6%). Similar subgroup analysis was done for the PBDEs exposures and the levels of TT4. No significant heterogeneity was shown in either of the two subgroups (I2 values = 0). The findings in our meta-analysis indicate the effects of PBDEs on thyroid function may mainly depend on PBDEs exposure and their levels found in serum. The relationship between PBDEs exposure and changes in

The Correlation between Polybrominated Diphenyl Ethers (PBDEs and Thyroid Hormones in the General Population: A Meta-Analysis.

Directory of Open Access Journals (Sweden)

Xuemin Zhao

Full Text Available Certain epidemiological studies have suggested exposure to polybrominated diphenyl ethers (PBDEs affect the production and secretion of thyroid hormones (TH; however, conflicting results have been reported in different studies. There is not a convincing conclusion about this debate to date.To perform a meta-analysis determining if there are correlations between PBDEs exposure and the serum levels of TH. Medical and scientific literature databases were searched for articles that met the eligibility criteria. The included articles were assessed for methodological quality. The correlation coefficient values or regression coefficient values between PBDEs and thyroid stimulating hormone (TSH or total thyroxine (TT4 from each article were used for analysis.Sixteen articles were included in this meta-analysis. Pearson correlation coefficients (r were directly collected or calculated from data given in the articles. Then, Fisher's z transformation was performed to convert each correlation coefficient to an approximately normal distribution. For z values between PBDEs exposure and TSH levels, the pooled z value for 18 studies was 0.08 (95% CI: -0.06, 0.22, and indicated significant heterogeneity (I2 values = 90.7%. Subgroup analysis was performed based on the median values of serum PBDEs in each study, there was not significant heterogeneity in each of the four subgroups (I2 values <30%. In meta-analysis of z values between PBDEs exposure and the levels of TT4, the pooled z value for 11 studies was -0.02 (95% CI: -0.11, 0.08, and also indicated significant heterogeneity (I2 values = 57.6%. Similar subgroup analysis was done for the PBDEs exposures and the levels of TT4. No significant heterogeneity was shown in either of the two subgroups (I2 values = 0.The findings in our meta-analysis indicate the effects of PBDEs on thyroid function may mainly depend on PBDEs exposure and their levels found in serum. The relationship between PBDEs exposure and changes

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.)

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....

Functional Multiple-Set Canonical Correlation Analysis

Science.gov (United States)

Hwang, Heungsun; Jung, Kwanghee; Takane, Yoshio; Woodward, Todd S.

2012-01-01

We propose functional multiple-set canonical correlation analysis for exploring associations among multiple sets of functions. The proposed method includes functional canonical correlation analysis as a special case when only two sets of functions are considered. As in classical multiple-set canonical correlation analysis, computationally, the…

No Eigenvalues Outside the Limiting Support of Generally Correlated Gaussian Matrices

KAUST Repository

Kammoun, Abla; Alouini, Mohamed-Slim

2016-01-01

This paper investigates the behaviour of the spectrum of generally correlated Gaussian random matrices whose columns are zero-mean independent vectors but have different correlations, under the specific regime where the number of their columns and that of their rows grow at infinity with the same pace. Following the approach proposed in [1], we prove that under some mild conditions, there is no eigenvalue outside the limiting support of generally correlated Gaussian matrices. As an outcome of this result, we establish that the smallest singular value of these matrices is almost surely greater than zero. From a practical perspective, this control of the smallest singular value is paramount to applications from statistical signal processing and wireless communication, in which this kind of matrices naturally arise.

No Eigenvalues Outside the Limiting Support of Generally Correlated Gaussian Matrices

KAUST Repository

Kammoun, Abla

2016-05-04

This paper investigates the behaviour of the spectrum of generally correlated Gaussian random matrices whose columns are zero-mean independent vectors but have different correlations, under the specific regime where the number of their columns and that of their rows grow at infinity with the same pace. Following the approach proposed in [1], we prove that under some mild conditions, there is no eigenvalue outside the limiting support of generally correlated Gaussian matrices. As an outcome of this result, we establish that the smallest singular value of these matrices is almost surely greater than zero. From a practical perspective, this control of the smallest singular value is paramount to applications from statistical signal processing and wireless communication, in which this kind of matrices naturally arise.

Interpreting canonical correlation analysis through biplots of stucture correlations and weights

NARCIS (Netherlands)

Braak, ter C.J.F.

1990-01-01

This paper extends the biplot technique to canonical correlation analysis and redundancy analysis. The plot of structure correlations is shown to the optimal for displaying the pairwise correlations between the variables of the one set and those of the second. The link between multivariate

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

Science.gov (United States)

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

2015-06-01

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

Complexity analysis based on generalized deviation for financial markets

Science.gov (United States)

Li, Chao; Shang, Pengjian

2018-03-01

In this paper, a new modified method is proposed as a measure to investigate the correlation between past price and future volatility for financial time series, known as the complexity analysis based on generalized deviation. In comparison with the former retarded volatility model, the new approach is both simple and computationally efficient. The method based on the generalized deviation function presents us an exhaustive way showing the quantization of the financial market rules. Robustness of this method is verified by numerical experiments with both artificial and financial time series. Results show that the generalized deviation complexity analysis method not only identifies the volatility of financial time series, but provides a comprehensive way distinguishing the different characteristics between stock indices and individual stocks. Exponential functions can be used to successfully fit the volatility curves and quantify the changes of complexity for stock market data. Then we study the influence for negative domain of deviation coefficient and differences during the volatile periods and calm periods. after the data analysis of the experimental model, we found that the generalized deviation model has definite advantages in exploring the relationship between the historical returns and future volatility.

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

NARCIS (Netherlands)

Waaijenborg, S.; Zwinderman, A.H.

2009-01-01

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

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

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.

Generalized linear models with random effects unified analysis via H-likelihood

CERN Document Server

Lee, Youngjo; Pawitan, Yudi

2006-01-01

Since their introduction in 1972, generalized linear models (GLMs) have proven useful in the generalization of classical normal models. Presenting methods for fitting GLMs with random effects to data, Generalized Linear Models with Random Effects: Unified Analysis via H-likelihood explores a wide range of applications, including combining information over trials (meta-analysis), analysis of frailty models for survival data, genetic epidemiology, and analysis of spatial and temporal models with correlated errors.Written by pioneering authorities in the field, this reference provides an introduction to various theories and examines likelihood inference and GLMs. The authors show how to extend the class of GLMs while retaining as much simplicity as possible. By maximizing and deriving other quantities from h-likelihood, they also demonstrate how to use a single algorithm for all members of the class, resulting in a faster algorithm as compared to existing alternatives. Complementing theory with examples, many of...

A Note on McDonald's Generalization of Principal Components Analysis

Science.gov (United States)

Shine, Lester C., II

1972-01-01

It is shown that McDonald's generalization of Classical Principal Components Analysis to groups of variables maximally channels the totalvariance of the original variables through the groups of variables acting as groups. An equation is obtained for determining the vectors of correlations of the L2 components with the original variables.…

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.

The generalized correlation method for estimation of time delay in power plants

International Nuclear Information System (INIS)

Kostic, Lj.

1981-01-01

The generalized correlation estimation is developed for determining time delay between signals received at two spatially separated sensors in the presence of uncorrelated noise in a power plant. This estimator can be realized as a pair of receiver prefilters followed by a cross correlator. The time argument at which the correlator achieves a maximum is the delay estimate. (author)

A Systems-Theoretical Generalization of Non-Local Correlations

Science.gov (United States)

von Stillfried, Nikolaus

Non-local correlations between quantum events are not due to a causal interaction in the sense of one being the cause for the other. In principle, the correlated events can thus occur simultaneously. Generalized Quantum Theory (GQT) formalizes the idea that non-local phenomena are not exclusive to quantum mechanics, e.g. due to some specific properties of (sub)atomic particles, but that they instead arise as a consequence of the way such particles are arranged into systems. Non-local phenomena should hence occur in any system which fulfils the necessary systems-theoretical parameters. The two most important parameters with respect to non-local correlations seem to be a conserved global property of the system as a whole and sufficient degrees of freedom of the corresponding property of its subsystems. Both factors place severe limitations on experimental observability of the phenomena, especially in terms of replicability. It has been suggested that reported phenomena of a so-called synchronistic, parapsychological or paranormal kind could be understood as instances of systems-inherent non-local correlations. From a systems-theoretical perspective, their phenomenology (including the favorable conditions for their occurrence and their lack of replicability) displays substantial similarities to non-local correlations in quantum systems and matches well with systems-theoretical parameters, thus providing circumstantial evidence for this hypothesis.

General classification and analysis of neutron β-decay experiments

International Nuclear Information System (INIS)

Gudkov, V.; Greene, G.L.; Calarco, J.R.

2006-01-01

A general analysis of the sensitivities of neutron β-decay experiments to manifestations of possible interaction beyond the standard model is carried out. In a consistent fashion, we take into account all known radiative and recoil corrections arising in the standard model. This provides a description of angular correlations in neutron decay in terms of one parameter, which is accurate to the level of ∼10 -5 . Based on this general expression, we present an analysis of the sensitivities to new physics for selected neutron decay experiments. We emphasize that the usual parametrization of experiments in terms of the tree-level coefficients a,A, and B is inadequate when the experimental sensitivities are at the same or higher level relative to the size of the corrections to the tree-level description

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

Science.gov (United States)

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

2008-06-18

correlation coefficient and the SD-weighted correlation coefficient, and is particularly useful for clustering replicated microarray data. This computational approach should be generally useful for proteomic data or other high-throughput analysis methodology.

General renormalized statistical approach with finite cross-field correlations

International Nuclear Information System (INIS)

Vakulenko, M.O.

1992-01-01

The renormalized statistical approach is proposed, accounting for finite correlations of potential and magnetic fluctuations. It may be used for analysis of a wide class of nonlinear model equations describing the cross-correlated plasma states. The influence of a cross spectrum on stationary potential and magnetic ones is investigated. 10 refs. (author)

Generalized quantum interference of correlated photon pairs

Science.gov (United States)

Kim, Heonoh; Lee, Sang Min; Moon, Han Seb

2015-01-01

Superposition and indistinguishablility between probability amplitudes have played an essential role in observing quantum interference effects of correlated photons. The Hong-Ou-Mandel interference and interferences of the path-entangled photon number state are of special interest in the field of quantum information technologies. However, a fully generalized two-photon quantum interferometric scheme accounting for the Hong-Ou-Mandel scheme and path-entangled photon number states has not yet been proposed. Here we report the experimental demonstrations of the generalized two-photon interferometry with both the interferometric properties of the Hong-Ou-Mandel effect and the fully unfolded version of the path-entangled photon number state using photon-pair sources, which are independently generated by spontaneous parametric down-conversion. Our experimental scheme explains two-photon interference fringes revealing single- and two-photon coherence properties in a single interferometer setup. Using the proposed interferometric measurement, it is possible to directly estimate the joint spectral intensity of a photon pair source. PMID:25951143

A simulation analysis of an extension of one-dimensional speckle correlation method for detection of general in-plane translation

Czech Academy of Sciences Publication Activity Database

Hamarová, Ivana; Šmíd, Petr; Horváth, P.; Hrabovský, M.

2014-01-01

Roč. 2014, č. 1 (2014), "704368-1"-"704368-12" ISSN 1537-744X R&D Projects: GA ČR GA13-12301S Institutional support: RVO:68378271 Keywords : one-dimensional speckle correlation * speckle * general In-plane translation Subject RIV: BH - Optics, Masers, Lasers Impact factor: 1.219, year: 2013

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.

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

International Nuclear Information System (INIS)

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

2011-01-01

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

Generalized estimating equations: A pragmatic and flexible approach to the marginal GLM modelling of correlated data in the behavioural sciences

Czech Academy of Sciences Publication Activity Database

Pekár, S.; Brabec, Marek

2018-01-01

Roč. 124, č. 2 (2018), s. 86-93 ISSN 0179-1613 Institutional support: RVO:67985807 Keywords : correlated data * generalized estimating equations * marginal model * regression models * statistical analysis Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 1.398, year: 2016

Signal correlations in biomass combustion. An information theoretic analysis

Energy Technology Data Exchange (ETDEWEB)

Ruusunen, M.

2013-09-01

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

MRI correlates of general intelligence in neurotypical adults.

Science.gov (United States)

Malpas, Charles B; Genc, Sila; Saling, Michael M; Velakoulis, Dennis; Desmond, Patricia M; O'Brien, Terence J

2016-02-01

There is growing interest in the neurobiological substrate of general intelligence. Psychometric estimates of general intelligence are reduced in a range of neurological disorders, leading to practical application as sensitive, but non-specific, markers of cerebral disorder. This study examined estimates of general intelligence in neurotypical adults using diffusion tensor imaging and resting-state functional connectivity analysis. General intelligence was related to white matter organisation across multiple brain regions, confirming previous work in older healthy adults. We also found that variation in general intelligence was related to a large functional sub-network involving all cortical lobes of the brain. These findings confirm that individual variance in general intelligence is related to diffusely represented brain networks. Copyright © 2015 Elsevier Ltd. All rights reserved.

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)

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

Science.gov (United States)

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

2010-07-01

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

Contributions to sensitivity analysis and generalized discriminant analysis; Contributions a l'analyse de sensibilite et a l'analyse discriminante generalisee

Energy Technology Data Exchange (ETDEWEB)

Jacques, J

2005-12-15

Two topics are studied in this thesis: sensitivity analysis and generalized discriminant analysis. Global sensitivity analysis of a mathematical model studies how the output variables of this last react to variations of its inputs. The methods based on the study of the variance quantify the part of variance of the response of the model due to each input variable and each subset of input variables. The first subject of this thesis is the impact of a model uncertainty on results of a sensitivity analysis. Two particular forms of uncertainty are studied: that due to a change of the model of reference, and that due to the use of a simplified model with the place of the model of reference. A second problem was studied during this thesis, that of models with correlated inputs. Indeed, classical sensitivity indices not having significance (from an interpretation point of view) in the presence of correlation of the inputs, we propose a multidimensional approach consisting in expressing the sensitivity of the output of the model to groups of correlated variables. Applications in the field of nuclear engineering illustrate this work. Generalized discriminant analysis consists in classifying the individuals of a test sample in groups, by using information contained in a training sample, when these two samples do not come from the same population. This work extends existing methods in a Gaussian context to the case of binary data. An application in public health illustrates the utility of generalized discrimination models thus defined. (author)

A new methodology of spatial cross-correlation analysis.

Science.gov (United States)

Chen, Yanguang

2015-01-01

Spatial correlation modeling comprises both spatial autocorrelation and spatial cross-correlation processes. The spatial autocorrelation theory has been well-developed. It is necessary to advance the method of spatial cross-correlation analysis to supplement the autocorrelation analysis. This paper presents a set of models and analytical procedures for spatial cross-correlation analysis. By analogy with Moran's index newly expressed in a spatial quadratic form, a theoretical framework is derived for geographical cross-correlation modeling. First, two sets of spatial cross-correlation coefficients are defined, including a global spatial cross-correlation coefficient and local spatial cross-correlation coefficients. Second, a pair of scatterplots of spatial cross-correlation is proposed, and the plots can be used to visually reveal the causality behind spatial systems. Based on the global cross-correlation coefficient, Pearson's correlation coefficient can be decomposed into two parts: direct correlation (partial correlation) and indirect correlation (spatial cross-correlation). As an example, the methodology is applied to the relationships between China's urbanization and economic development to illustrate how to model spatial cross-correlation phenomena. This study is an introduction to developing the theory of spatial cross-correlation, and future geographical spatial analysis might benefit from these models and indexes.

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.

A New Methodology of Spatial Cross-Correlation Analysis

Science.gov (United States)

Chen, Yanguang

2015-01-01

Spatial correlation modeling comprises both spatial autocorrelation and spatial cross-correlation processes. The spatial autocorrelation theory has been well-developed. It is necessary to advance the method of spatial cross-correlation analysis to supplement the autocorrelation analysis. This paper presents a set of models and analytical procedures for spatial cross-correlation analysis. By analogy with Moran’s index newly expressed in a spatial quadratic form, a theoretical framework is derived for geographical cross-correlation modeling. First, two sets of spatial cross-correlation coefficients are defined, including a global spatial cross-correlation coefficient and local spatial cross-correlation coefficients. Second, a pair of scatterplots of spatial cross-correlation is proposed, and the plots can be used to visually reveal the causality behind spatial systems. Based on the global cross-correlation coefficient, Pearson’s correlation coefficient can be decomposed into two parts: direct correlation (partial correlation) and indirect correlation (spatial cross-correlation). As an example, the methodology is applied to the relationships between China’s urbanization and economic development to illustrate how to model spatial cross-correlation phenomena. This study is an introduction to developing the theory of spatial cross-correlation, and future geographical spatial analysis might benefit from these models and indexes. PMID:25993120

Attitudes to Mental Illness and Its Demographic Correlates among General Population in Singapore.

Directory of Open Access Journals (Sweden)

Qi Yuan

Full Text Available Public attitudes to mental illness could influence how the public interact with, provide opportunities for, and help people with mental illness.This study aims to explore the underlying factors of the Attitudes to Mental Illness questionnaire among the general population in Singapore and the socio-demographic correlates of each factor.From March 2014 to April 2015, a nation-wide cross-sectional survey on mental health literacy with 3,006 participants was conducted in Singapore.Factor analysis revealed a 4-factor structure for the Attitudes to Mental Illness questionnaire among the Singapore general population, namely social distancing, tolerance/support for community care, social restrictiveness, and prejudice and misconception. Older age, male gender, lower education and socio-economic status were associated with more negative attitudes towards the mentally ill. Chinese showed more negative attitudes than Indians and Malays (except for prejudice and misconception.There is a need for culture-specific interventions, and the associated factors identified in this study should be considered for future attitude campaigns.

Attitudes to Mental Illness and Its Demographic Correlates among General Population in Singapore.

Science.gov (United States)

Yuan, Qi; Abdin, Edimansyah; Picco, Louisa; Vaingankar, Janhavi Ajit; Shahwan, Shazana; Jeyagurunathan, Anitha; Sagayadevan, Vathsala; Shafie, Saleha; Tay, Jenny; Chong, Siow Ann; Subramaniam, Mythily

2016-01-01

Public attitudes to mental illness could influence how the public interact with, provide opportunities for, and help people with mental illness. This study aims to explore the underlying factors of the Attitudes to Mental Illness questionnaire among the general population in Singapore and the socio-demographic correlates of each factor. From March 2014 to April 2015, a nation-wide cross-sectional survey on mental health literacy with 3,006 participants was conducted in Singapore. Factor analysis revealed a 4-factor structure for the Attitudes to Mental Illness questionnaire among the Singapore general population, namely social distancing, tolerance/support for community care, social restrictiveness, and prejudice and misconception. Older age, male gender, lower education and socio-economic status were associated with more negative attitudes towards the mentally ill. Chinese showed more negative attitudes than Indians and Malays (except for prejudice and misconception). There is a need for culture-specific interventions, and the associated factors identified in this study should be considered for future attitude campaigns.

General correlation for prediction of critical heat flux ratio in water cooled channels

Energy Technology Data Exchange (ETDEWEB)

Pernica, R.; Cizek, J.

1995-09-01

The paper present the general empirical Critical Heat Flux Ration (CHFR) correlation which is valid for vertical water upflow through tubes, internally heated concentric annuli and rod bundles geometries with both wide and very tight square and triangular rods lattices. The proposed general PG correlation directly predicts the CHFR, it comprises axial and radial non-uniform heating, and is valid in a wider range of thermal hydraulic conditions than previously published critical heat flux correlations. The PG correlation has been developed using the critical heat flux Czech data bank which includes more than 9500 experimental data on tubes, 7600 data on rod bundles and 713 data on internally heated concentric annuli. Accuracy of the CHFR prediction, statistically assessed by the constant dryout conditions approach, is characterized by the mean value nearing 1.00 and the standard deviation less than 0.06. Moverover, a subchannel form of the PG correlations is statistically verified on Westinghouse and Combustion Engineering rod bundle data bases, i.e. more than 7000 experimental CHF points of Columbia University data bank were used.

Intermittency analysis of correlated data

International Nuclear Information System (INIS)

Wosiek, B.

1992-01-01

We describe the method of the analysis of the dependence of the factorial moments on the bin size in which the correlations between the moments computed for different bin sizes are taken into account. For large multiplicity nucleus-nucleus data inclusion of the correlations does not change the values of the slope parameter, but gives errors significantly reduced as compared to the case of fits with no correlations. (author)

Cosmological measurements with general relativistic galaxy correlations

International Nuclear Information System (INIS)

Raccanelli, Alvise; Montanari, Francesco; Durrer, Ruth; Bertacca, Daniele; Doré, Olivier

2016-01-01

We investigate the cosmological dependence and the constraining power of large-scale galaxy correlations, including all redshift-distortions, wide-angle, lensing and gravitational potential effects on linear scales. We analyze the cosmological information present in the lensing convergence and in the gravitational potential terms describing the so-called ''relativistic effects'', and we find that, while smaller than the information contained in intrinsic galaxy clustering, it is not negligible. We investigate how neglecting them does bias cosmological measurements performed by future spectroscopic and photometric large-scale surveys such as SKA and Euclid. We perform a Fisher analysis using the CLASS code, modified to include scale-dependent galaxy bias and redshift-dependent magnification and evolution bias. Our results show that neglecting relativistic terms, especially lensing convergence, introduces an error in the forecasted precision in measuring cosmological parameters of the order of a few tens of percent, in particular when measuring the matter content of the Universe and primordial non-Gaussianity parameters. The analysis suggests a possible substantial systematic error in cosmological parameter constraints. Therefore, we argue that radial correlations and integrated relativistic terms need to be taken into account when forecasting the constraining power of future large-scale number counts of galaxy surveys.

Correlations Between General Joint Hypermobility and Joint Hypermobility Syndrome and Injury in Contemporary Dance Students.

Science.gov (United States)

Ruemper, Alia; Watkins, Katherine

2012-12-01

The first objective of this study was to ascertain the prevalence of general joint hypermobility (GJH) and joint hypermobility syndrome (JHS) in BA Dance Theatre 1st and 3rd year students at a contemporary dance conservatory. The second objective was to determine the statistical correlation between GJH, JHS, and injury in this population. A total of 85 (female, N = 78; male, N = 7) contemporary dance students participated in the study. The Beighton score (with a forward flexion test modification) was used to determine GJH, and the Brighton criteria were used to verify JHS. Participants completed a self-reported injury questionnaire that included type of injury (physical complaint, medical diagnosis, or time-loss) and injury frequency. Statistical analysis (Pearson correlation) was used to correlate GJH, JHS, and frequency-of-injury scores. Overall, 69% of the students were found to have GJH, and 33% had JHS. A statistical correlation of r = + 0.331 (p dance students and suggests that screening programs should include the Brighton criteria to identify JHS in these dancers. Subsequent injury tracking and injury prevention programs would then provide data for further research in this area.

A general method dealing with correlations in uncertainty propagation in fault trees

International Nuclear Information System (INIS)

Qin Zhang

1989-01-01

This paper deals with the correlations among the failure probabilities (frequencies) of not only the identical basic events but also other basic events in a fault tree. It presents a general and simple method to include these correlations in uncertainty propagation. Two examples illustrate this method and show that neglecting these correlations results in large underestimation of the top event failure probability (frequency). One is the failure of the primary pump in a chemical reactor cooling system, the other example is an accident to a road transport truck carrying toxic waste. (author)

Metabolic correlates of general cognitive function in nondemented elderly subjects: an FDG PET study

International Nuclear Information System (INIS)

Cho, Sang Soo; Kwak, Young Bin; Lee, Eun Ju; Ryu, Chang Hyung; Chey, Jean Yung; Kim, Sang Eun

2004-01-01

While many studies examined the neural correlates of individual cognitive functions, few made efforts to identify the neural networks associated with general cognitive function. General cognitive function decline in the elderly population is not infrequent. This study examined the brain areas associated with general cognitive function in the elderly subjects. Community-dwelling 116 elderly subjects without dementing illnesses (age, 71±5 y; 13 males and 103 females) participated. General cognitive ability was assessed with the Dementia Rating Scale (K-DRS), which is composed of five subtests of attention, initiation and perseveration, construction, conceptualization, and memory. The EVLT (Elderly Verbal Learning Test), a nine-word list learning test, was used for general memory assessment. Brain FDG PET scans were acquired in all subjects. Brain regions where metabolic levels are correlated with the total scores of K-DRS and EVLT were examined using SPM99. There was a significant positive correlation (P < 0.01 uncorrected, k=100) between the total score of K-DRS and glucose metabolism in the bilateral posterior cingulate gyri, bilateral inferior frontal gyri, left caudate, left inferior parietal lobule, right precuneus, bilateral unci, right parahippocampal gyrus, and right anterior cingulate gyrus. A significant positive correlation between the total score of EVLT and glucose metabolism was shown in the right precuneus, right posterior cingulate gyrus, left insula, bilateral inferior parietal lobules, left anterior cingulate gyrus, left caudate, right inferior frontal gyrus (P < 0.01 uncorrected, k=100). Our data showed the brain regions that are associated with general cognitive function in the elderly. Those regions may serve as the neural substrated of cognitive dysfunction associated with neurodegenerative and cerebrovascular diseases in elderly subjects

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

Science.gov (United States)

Yang, Yujun; Li, Jianping; Yang, Yimei

2017-09-01

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

Development of Generalized Correlation Equation for the Local Wall Shear Stress

International Nuclear Information System (INIS)

Jeon, Yu Mi; Park, Ju Hwan

2010-06-01

The pressure drop characteristics for a fuel channel are essential for the design and reliable operation of a nuclear reactor. Over several decades, analytical methods have been developed to predict the friction factor in the fuel bundle flows. In order to enhance the accuracy of prediction for the pressure drop in a rod bundle, the influences of a channel wall and the local shear stress distribution should be considered. Therefore, the correlation equation for a local wall shear stress distribution should be developed in order to secure an analytical solution for the friction factor of a rod bundle. For a side subchannel, which has the influence of the channel wall, the local wall shear stress distribution is dependent on the ratio of wall to diameter (W/D) as well as the ratio of pitch to diameter (P/D). In the case that W/D has the same value with P/D, the local shear stress distribution can be simply correlated with the function of angular position for each value of P/D. While in the case where W/D has a different value than P/D, the correlation equation should be developed for each case of P/D and W/D. Therefore, in the present study, the generalized correlation equation of the local wall shear stress distribution was developed for a side subchannel in the case where W/D has a different value than P/D. Consequently, the generalized correlation equation of a local wall shear stress distribution can be represented by the equivalent pitch to diameter ratio, P'/D for the case that P/D and W/D had a different value

New insights into the correlation structure of DSM-IV depression symptoms in the general population v. subsamples of depressed individuals.

Science.gov (United States)

Foster, S; Mohler-Kuo, M

2018-06-01

Previous research failed to uncover a replicable dimensional structure underlying the symptoms of depression. We aimed to examine two neglected methodological issues in this research: (a) adjusting symptom correlations for overall depression severity; and (b) analysing general population samples v. subsamples of currently depressed individuals. Using population-based cross-sectional and longitudinal data from two nations (Switzerland, 5883 young men; USA, 2174 young men and 2244 young women) we assessed the dimensions of the nine DSM-IV depression symptoms in young adults. In each general-population sample and each subsample of currently depressed participants, we conducted a standardised process of three analytical steps, based on exploratory and confirmatory factor and bifactor analysis, to reveal any replicable dimensional structure underlying symptom correlations while controlling for overall depression severity. We found no evidence of a replicable dimensional structure across samples when adjusting symptom correlations for overall depression severity. In the general-population samples, symptoms correlated strongly and a single dimension of depression severity was revealed. Among depressed participants, symptom correlations were surprisingly weak and no replicable dimensions were identified, regardless of severity-adjustment. First, caution is warranted when considering studies assessing dimensions of depression because general population-based studies and studies of depressed individuals generate different data that can lead to different conclusions. This problem likely generalises to other models based on the symptoms' inter-relationships such as network models. Second, whereas the overall severity aligns individuals on a continuum of disorder intensity that allows non-affected individuals to be distinguished from affected individuals, the clinical evaluation and treatment of depressed individuals should focus directly on each individual's symptom profile.

Contributions to sensitivity analysis and generalized discriminant analysis; Contributions a l'analyse de sensibilite et a l'analyse discriminante generalisee

Energy Technology Data Exchange (ETDEWEB)

Jacques, J

2005-12-15

Two topics are studied in this thesis: sensitivity analysis and generalized discriminant analysis. Global sensitivity analysis of a mathematical model studies how the output variables of this last react to variations of its inputs. The methods based on the study of the variance quantify the part of variance of the response of the model due to each input variable and each subset of input variables. The first subject of this thesis is the impact of a model uncertainty on results of a sensitivity analysis. Two particular forms of uncertainty are studied: that due to a change of the model of reference, and that due to the use of a simplified model with the place of the model of reference. A second problem was studied during this thesis, that of models with correlated inputs. Indeed, classical sensitivity indices not having significance (from an interpretation point of view) in the presence of correlation of the inputs, we propose a multidimensional approach consisting in expressing the sensitivity of the output of the model to groups of correlated variables. Applications in the field of nuclear engineering illustrate this work. Generalized discriminant analysis consists in classifying the individuals of a test sample in groups, by using information contained in a training sample, when these two samples do not come from the same population. This work extends existing methods in a Gaussian context to the case of binary data. An application in public health illustrates the utility of generalized discrimination models thus defined. (author)

Attitudes to Mental Illness and Its Demographic Correlates among General Population in Singapore

Science.gov (United States)

Yuan, Qi; Abdin, Edimansyah; Picco, Louisa; Vaingankar, Janhavi Ajit; Shahwan, Shazana; Jeyagurunathan, Anitha; Sagayadevan, Vathsala; Shafie, Saleha; Tay, Jenny; Chong, Siow Ann; Subramaniam, Mythily

2016-01-01

Background Public attitudes to mental illness could influence how the public interact with, provide opportunities for, and help people with mental illness. Aims This study aims to explore the underlying factors of the Attitudes to Mental Illness questionnaire among the general population in Singapore and the socio-demographic correlates of each factor. Methods From March 2014 to April 2015, a nation-wide cross-sectional survey on mental health literacy with 3,006 participants was conducted in Singapore. Results Factor analysis revealed a 4-factor structure for the Attitudes to Mental Illness questionnaire among the Singapore general population, namely social distancing, tolerance/support for community care, social restrictiveness, and prejudice and misconception. Older age, male gender, lower education and socio-economic status were associated with more negative attitudes towards the mentally ill. Chinese showed more negative attitudes than Indians and Malays (except for prejudice and misconception). Conclusions There is a need for culture-specific interventions, and the associated factors identified in this study should be considered for future attitude campaigns. PMID:27893796

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...

Correlation functions for the fractional generalized Langevin equation in the presence of internal and external noise

International Nuclear Information System (INIS)

Sandev, Trifce; Metzler, Ralf; Tomovski, Živorad

2014-01-01

We study generalized fractional Langevin equations in the presence of a harmonic potential. General expressions for the mean velocity and particle displacement, the mean squared displacement, position and velocity correlation functions, as well as normalized displacement correlation function are derived. We report exact results for the cases of internal and external friction, that is, when the driving noise is either internal and thus the fluctuation-dissipation relation is fulfilled or when the noise is external. The asymptotic behavior of the generalized stochastic oscillator is investigated, and the case of high viscous damping (overdamped limit) is considered. Additional behaviors of the normalized displacement correlation functions different from those for the regular damped harmonic oscillator are observed. In addition, the cases of a constant external force and the force free case are obtained. The validity of the generalized Einstein relation for this process is discussed. The considered fractional generalized Langevin equation may be used to model anomalous diffusive processes including single file-type diffusion

Correlated quadratures of resonance fluorescence and the generalized uncertainty relation

Science.gov (United States)

Arnoldus, Henk F.; George, Thomas F.; Gross, Rolf W. F.

1994-01-01

Resonance fluorescence from a two-state atom has been predicted to exhibit quadrature squeezing below the Heisenberg uncertainty limit, provided that the optical parameters (Rabi frequency, detuning, laser linewidth, etc.) are chosen carefully. When the correlation between two quadratures of the radiation field does not vanish, however, the Heisenberg limit for quantum fluctuations might be an unrealistic lower bound. A generalized uncertainty relation, due to Schroedinger, takes into account the possible correlation between the quadrature components of the radiation, and it suggests a modified definition of squeezing. We show that the coherence between the two levels of a laser-driven atom is responsible for the correlation between the quadrature components of the emitted fluorescence, and that the Schrodinger uncertainty limit increases monotonically with the coherence. On the other hand, the fluctuations in the quadrature field diminish with an increasing coherence, and can disappear completely when the coherence reaches 1/2, provided that certain phase relations hold.

Insight into resolution enhancement in generalized two-dimensional correlation spectroscopy.

Science.gov (United States)

Ma, Lu; Sikirzhytski, Vitali; Hong, Zhenmin; Lednev, Igor K; Asher, Sanford A

2013-03-01

Generalized two-dimensional correlation spectroscopy (2D-COS) can be used to enhance spectral resolution in order to help differentiate highly overlapped spectral bands. Despite the numerous extensive 2D-COS investigations, the origin of the 2D spectral resolution enhancement mechanism(s) is not completely understood. In the work here, we studied the 2D-COS of simulated spectra in order to develop new insights into the dependence of 2D-COS spectral features on the overlapping band separations, their intensities and bandwidths, and their band intensity change rates. We found that the features in the 2D-COS maps that are derived from overlapping bands were determined by the spectral normalized half-intensities and the total intensity changes of the correlated bands. We identified the conditions required to resolve overlapping bands. In particular, 2D-COS peak resolution requires that the normalized half-intensities of a correlating band have amplitudes between the maxima and minima of the normalized half-intensities of the overlapping bands.

A hybrid correlation analysis with application to imaging genetics

Science.gov (United States)

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

2018-03-01

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

General theory of intensity correlation on light scattering

International Nuclear Information System (INIS)

Villaeys, A.A.

1978-01-01

A general theory for spatio-temporal intensity correlations measurements for a scattered beam is developed. A completely quantum mechanical description for both excitation and detection set up is used. This description is essentially valid for weak incident light beams and single photon absorption processes. From a unified point of view both, stationary as well as, time resolved experiments are described. The interest for such experiments in the study of processes like resonance raman scattering and resonance fluorescence is emphasized. Also an observable coherent contribution associated to different final levels of the target-atoms or molecules is obtained a result which cannot be reached by intensity measurements

A generalized Levene's scale test for variance heterogeneity in the presence of sample correlation and group uncertainty.

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Soave, David; Sun, Lei

2017-09-01

We generalize Levene's test for variance (scale) heterogeneity between k groups for more complex data, when there are sample correlation and group membership uncertainty. Following a two-stage regression framework, we show that least absolute deviation regression must be used in the stage 1 analysis to ensure a correct asymptotic χk-12/(k-1) distribution of the generalized scale (gS) test statistic. We then show that the proposed gS test is independent of the generalized location test, under the joint null hypothesis of no mean and no variance heterogeneity. Consequently, we generalize the recently proposed joint location-scale (gJLS) test, valuable in settings where there is an interaction effect but one interacting variable is not available. We evaluate the proposed method via an extensive simulation study and two genetic association application studies. © 2017 The Authors Biometrics published by Wiley Periodicals, Inc. on behalf of International Biometric Society.

From micro-correlations to macro-correlations

International Nuclear Information System (INIS)

Eliazar, Iddo

2016-01-01

Random vectors with a symmetric correlation structure share a common value of pair-wise correlation between their different components. The symmetric correlation structure appears in a multitude of settings, e.g. mixture models. In a mixture model the components of the random vector are drawn independently from a general probability distribution that is determined by an underlying parameter, and the parameter itself is randomized. In this paper we study the overall correlation of high-dimensional random vectors with a symmetric correlation structure. Considering such a random vector, and terming its pair-wise correlation “micro-correlation”, we use an asymptotic analysis to derive the random vector’s “macro-correlation” : a score that takes values in the unit interval, and that quantifies the random vector’s overall correlation. The method of obtaining macro-correlations from micro-correlations is then applied to a diverse collection of frameworks that demonstrate the method’s wide applicability.

Resting-state connectivity of the sustained attention network correlates with disease duration in idiopathic generalized epilepsy.

Directory of Open Access Journals (Sweden)

Mona Maneshi

Full Text Available INTRODUCTION: In idiopathic generalized epilepsy (IGE, a normal electroencephalogram between generalized spike and wave (GSW discharges is believed to reflect normal brain function. However, some studies indicate that even excluding GSW-related errors, IGE patients perform poorly on sustained attention task, the deficit being worse as a function of disease duration. We hypothesized that at least in a subset of structures which are normally involved in sustained attention, resting-state functional connectivity (FC is different in IGE patients compared to controls and that some of the changes are related to disease duration. METHOD: Seeds were selected based on a sustained attention study in controls. Resting-state functional magnetic resonance imaging (fMRI data was obtained from 14 IGE patients and 14 matched controls. After physiological noise removal, the mean time-series of each seed was used as a regressor in a general linear model to detect regions that showed correlation with the seed. In patients, duration factor was defined based on epilepsy duration. Between-group differences weighted by the duration factor were evaluated with mixed-effects model. Correlation was then evaluated in IGE patients between the FC, averaged over each significant cluster, and the duration factor. RESULTS: Eight of 18 seeds showed significant difference in FC across groups. However, only for seeds in the medial superior frontal and precentral gyri and in the medial prefrontal area, average FC taken over significant clusters showed high correlation with the duration factor. These 3 seeds showed changes in FC respectively with the premotor and superior frontal gyrus, the dorsal premotor, and the supplementary motor area plus precentral gyrus. CONCLUSION: Alterations of FC in IGE patients are not limited to the frontal areas. However, as indicated by specificity analysis, patients with long history of disease show changes in FC mainly within the frontal areas.

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

Institute of Scientific and Technical Information of China (English)

LI Rui; WANG Liqun; MA Chunxia; MA Lixian

2016-01-01

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

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

Exploring the squeezed three-point galaxy correlation function with generalized halo occupation distribution models

Science.gov (United States)

Yuan, Sihan; Eisenstein, Daniel J.; Garrison, Lehman H.

2018-04-01

We present the GeneRalized ANd Differentiable Halo Occupation Distribution (GRAND-HOD) routine that generalizes the standard 5 parameter halo occupation distribution model (HOD) with various halo-scale physics and assembly bias. We describe the methodology of 4 different generalizations: satellite distribution generalization, velocity bias, closest approach distance generalization, and assembly bias. We showcase the signatures of these generalizations in the 2-point correlation function (2PCF) and the squeezed 3-point correlation function (squeezed 3PCF). We identify generalized HOD prescriptions that are nearly degenerate in the projected 2PCF and demonstrate that these degeneracies are broken in the redshift-space anisotropic 2PCF and the squeezed 3PCF. We also discuss the possibility of identifying degeneracies in the anisotropic 2PCF and further demonstrate the extra constraining power of the squeezed 3PCF on galaxy-halo connection models. We find that within our current HOD framework, the anisotropic 2PCF can predict the squeezed 3PCF better than its statistical error. This implies that a discordant squeezed 3PCF measurement could falsify the particular HOD model space. Alternatively, it is possible that further generalizations of the HOD model would open opportunities for the squeezed 3PCF to provide novel parameter measurements. The GRAND-HOD Python package is publicly available at https://github.com/SandyYuan/GRAND-HOD.

A bias correction for covariance estimators to improve inference with generalized estimating equations that use an unstructured correlation matrix.

Science.gov (United States)

Westgate, Philip M

2013-07-20

Generalized estimating equations (GEEs) are routinely used for the marginal analysis of correlated data. The efficiency of GEE depends on how closely the working covariance structure resembles the true structure, and therefore accurate modeling of the working correlation of the data is important. A popular approach is the use of an unstructured working correlation matrix, as it is not as restrictive as simpler structures such as exchangeable and AR-1 and thus can theoretically improve efficiency. However, because of the potential for having to estimate a large number of correlation parameters, variances of regression parameter estimates can be larger than theoretically expected when utilizing the unstructured working correlation matrix. Therefore, standard error estimates can be negatively biased. To account for this additional finite-sample variability, we derive a bias correction that can be applied to typical estimators of the covariance matrix of parameter estimates. Via simulation and in application to a longitudinal study, we show that our proposed correction improves standard error estimation and statistical inference. Copyright © 2012 John Wiley & Sons, Ltd.

Nuclear-data evaluation based on direct and indirect measurements with general correlations

International Nuclear Information System (INIS)

Muir, D.W.

1988-01-01

Optimum procedures for the statistical improvement, or updating, of an existing nuclear-data evaluation are reviewed and redeveloped from first principles, consistently employing a minimum-variance viewpoint. A set of equations is derived which provides improved values of the data and their covariances, taking into account information from supplementary measurements and allowing for general correlations among all measurements. The minimum-variance solutions thus obtained, which we call the method of 'partitioned least squares,' are found to be equivalent to a method suggested by Yu. V. Linnik and applied by a number of authors to the analysis of fission-reactor integral experiments; however, up to now, the partitioned-least-squares formulae have not found widespread use in the field of basic data evaluation. This approach is shown to give the same results as the more commonly applied Normal equations, but with reduced matrix inversion requirements. Examples are provided to indicate potential areas of application. (author)

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.

Parameter Optimization for Selected Correlation Analysis of Intracranial Pathophysiology.

Science.gov (United States)

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

2015-01-01

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

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.

Multicollinearity in canonical correlation analysis in maize.

Science.gov (United States)

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

2017-03-30

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

Insight into Resolution Enhancement in Generalized Two-Dimensional Correlation Spectroscopy

OpenAIRE

Ma, Lu; Sikirzhytski, Vitali; Hong, Zhenmin; Lednev, Igor K.; Asher, Sanford A.

2013-01-01

Generalized two-dimensional correlation spectroscopy (2D COS) can be used to enhance spectral resolution in order to help differentiate highly overlapped spectral bands. Despite the numerous extensive 2D COS investigations, the origin of the 2D spectral resolution enhancement mechanism(s) are not completely understood. In the work here we studied the 2D COS of simulated spectra in order to develop new insights into the dependence of the 2D COS spectral features on the overlapping band separat...

Detrended cross-correlation analysis of electroencephalogram

International Nuclear Information System (INIS)

Wang Jun; Zhao Da-Qing

2012-01-01

In the paper we use detrended cross-correlation analysis (DCCA) to study the electroencephalograms of healthy young subjects and healthy old subjects. It is found that the cross-correlation between different leads of a healthy young subject is larger than that of a healthy old subject. It was shown that the cross-correlation relationship decreases with the aging process and the phenomenon can help to diagnose whether the subject's brain function is healthy or not. (interdisciplinary physics and related areas of science and technology)

Generalized extended Navier-Stokes theory: correlations in molecular fluids with intrinsic angular momentum.

Science.gov (United States)

Hansen, J S; Daivis, Peter J; Dyre, Jeppe C; Todd, B D; Bruus, Henrik

2013-01-21

The extended Navier-Stokes theory accounts for the coupling between the translational and rotational molecular degrees of freedom. In this paper, we generalize this theory to non-zero frequencies and wavevectors, which enables a new study of spatio-temporal correlation phenomena present in molecular fluids. To discuss these phenomena in detail, molecular dynamics simulations of molecular chlorine are performed for three different state points. In general, the theory captures the behavior for small wavevector and frequencies as expected. For example, in the hydrodynamic regime and for molecular fluids with small moment of inertia like chlorine, the theory predicts that the longitudinal and transverse intrinsic angular velocity correlation functions are almost identical, which is also seen in the molecular dynamics simulations. However, the theory fails at large wavevector and frequencies. To account for the correlations at these scales, we derive a phenomenological expression for the frequency dependent rotational viscosity and wavevector and frequency dependent longitudinal spin viscosity. From this we observe a significant coupling enhancement between the molecular angular velocity and translational velocity for large frequencies in the gas phase; this is not observed for the supercritical fluid and liquid state points.

General solution of an exact correlation function factorization in conformal field theory

International Nuclear Information System (INIS)

Simmons, Jacob J H; Kleban, Peter

2009-01-01

The correlation function factorization with K a boundary operator product expansion coefficient, is known to hold for certain scaling operators at the two-dimensional percolation point and in a few other cases. Here the correlation functions are evaluated in the upper half-plane (or any conformally equivalent region) with x 1 and x 2 arbitrary points on the real axis, and z an arbitrary point in the interior. This type of result is of interest because it is both exact and universal, relates higher-order correlation functions to lower-order ones and has a simple interpretation in terms of cluster or loop probabilities in several statistical models. This motivated us to use the techniques of conformal field theory to determine the general conditions for its validity. Here, we discover that either (see display) factorizes in this way for any central charge c, generalizing previous results. In particular, the factorization holds for either FK (Fortuin–Kasteleyn) or spin clusters in the Q-state Potts models; it also applies to either the dense or dilute phases of the O(n) loop models. Further, only one other non-trivial set of highest-weight operators (in an irreducible Verma module) factorizes in this way. In this case the operators have negative dimension (for c<1) and do not seem to have a physical realization

[Electroencephalogram Feature Selection Based on Correlation Coefficient Analysis].

Science.gov (United States)

Zhou, Jinzhi; Tang, Xiaofang

2015-08-01

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

On the Analysis of Case-Control Studies in Cluster-correlated Data Settings.

Science.gov (United States)

Haneuse, Sebastien; Rivera-Rodriguez, Claudia

2018-01-01

In resource-limited settings, long-term evaluation of national antiretroviral treatment (ART) programs often relies on aggregated data, the analysis of which may be subject to ecological bias. As researchers and policy makers consider evaluating individual-level outcomes such as treatment adherence or mortality, the well-known case-control design is appealing in that it provides efficiency gains over random sampling. In the context that motivates this article, valid estimation and inference requires acknowledging any clustering, although, to our knowledge, no statistical methods have been published for the analysis of case-control data for which the underlying population exhibits clustering. Furthermore, in the specific context of an ongoing collaboration in Malawi, rather than performing case-control sampling across all clinics, case-control sampling within clinics has been suggested as a more practical strategy. To our knowledge, although similar outcome-dependent sampling schemes have been described in the literature, a case-control design specific to correlated data settings is new. In this article, we describe this design, discuss balanced versus unbalanced sampling techniques, and provide a general approach to analyzing case-control studies in cluster-correlated settings based on inverse probability-weighted generalized estimating equations. Inference is based on a robust sandwich estimator with correlation parameters estimated to ensure appropriate accounting of the outcome-dependent sampling scheme. We conduct comprehensive simulations, based in part on real data on a sample of N = 78,155 program registrants in Malawi between 2005 and 2007, to evaluate small-sample operating characteristics and potential trade-offs associated with standard case-control sampling or when case-control sampling is performed within clusters.

Transform analysis of generalized functions

CERN Document Server

Misra, O P

1986-01-01

Transform Analysis of Generalized Functions concentrates on finite parts of integrals, generalized functions and distributions. It gives a unified treatment of the distributional setting with transform analysis, i.e. Fourier, Laplace, Stieltjes, Mellin, Hankel and Bessel Series.Included are accounts of applications of the theory of integral transforms in a distributional setting to the solution of problems arising in mathematical physics. Information on distributional solutions of differential, partial differential equations and integral equations is conveniently collected here.The volume will

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.

Stochastic wave-function unravelling of the generalized Lindblad equation using correlated states

International Nuclear Information System (INIS)

Moodley, Mervlyn; Nsio Nzundu, T; Paul, S

2012-01-01

We perform a stochastic wave-function unravelling of the generalized Lindblad master equation using correlated states, a combination of the system state vectors and the environment population. The time-convolutionless projection operator method using correlated projection superoperators is applied to a two-state system, a qubit, that is coupled to an environment consisting of two energy bands which are both populated. These results are compared to the data obtained from Monte Carlo wave-function simulations based on the unravelling of the master equation. We also show a typical quantum trajectory and the average time evolution of the state vector on the Bloch sphere. (paper)

Generalized Analysis of a Distribution Separation Method

Directory of Open Access Journals (Sweden)

Peng Zhang

2016-04-01

Full Text Available Separating two probability distributions from a mixture model that is made up of the combinations of the two is essential to a wide range of applications. For example, in information retrieval (IR, there often exists a mixture distribution consisting of a relevance distribution that we need to estimate and an irrelevance distribution that we hope to get rid of. Recently, a distribution separation method (DSM was proposed to approximate the relevance distribution, by separating a seed irrelevance distribution from the mixture distribution. It was successfully applied to an IR task, namely pseudo-relevance feedback (PRF, where the query expansion model is often a mixture term distribution. Although initially developed in the context of IR, DSM is indeed a general mathematical formulation for probability distribution separation. Thus, it is important to further generalize its basic analysis and to explore its connections to other related methods. In this article, we first extend DSM’s theoretical analysis, which was originally based on the Pearson correlation coefficient, to entropy-related measures, including the KL-divergence (Kullback–Leibler divergence, the symmetrized KL-divergence and the JS-divergence (Jensen–Shannon divergence. Second, we investigate the distribution separation idea in a well-known method, namely the mixture model feedback (MMF approach. We prove that MMF also complies with the linear combination assumption, and then, DSM’s linear separation algorithm can largely simplify the EM algorithm in MMF. These theoretical analyses, as well as further empirical evaluation results demonstrate the advantages of our DSM approach.

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.

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.

WGCNA: an R package for weighted correlation network analysis.

Science.gov (United States)

Langfelder, Peter; Horvath, Steve

2008-12-29

Correlation networks are increasingly being used in bioinformatics applications. For example, weighted gene co-expression network analysis is a systems biology method for describing the correlation patterns among genes across microarray samples. Weighted correlation network analysis (WGCNA) can be used for finding clusters (modules) of highly correlated genes, for summarizing such clusters using the module eigengene or an intramodular hub gene, for relating modules to one another and to external sample traits (using eigengene network methodology), and for calculating module membership measures. Correlation networks facilitate network based gene screening methods that can be used to identify candidate biomarkers or therapeutic targets. These methods have been successfully applied in various biological contexts, e.g. cancer, mouse genetics, yeast genetics, and analysis of brain imaging data. While parts of the correlation network methodology have been described in separate publications, there is a need to provide a user-friendly, comprehensive, and consistent software implementation and an accompanying tutorial. The WGCNA R software package is a comprehensive collection of R functions for performing various aspects of weighted correlation network analysis. The package includes functions for network construction, module detection, gene selection, calculations of topological properties, data simulation, visualization, and interfacing with external software. Along with the R package we also present R software tutorials. While the methods development was motivated by gene expression data, the underlying data mining approach can be applied to a variety of different settings. The WGCNA package provides R functions for weighted correlation network analysis, e.g. co-expression network analysis of gene expression data. The R package along with its source code and additional material are freely available at http://www.genetics.ucla.edu/labs/horvath/CoexpressionNetwork/Rpackages/WGCNA.

Deorbitalization strategies for meta-generalized-gradient-approximation exchange-correlation functionals

Science.gov (United States)

Mejia-Rodriguez, Daniel; Trickey, S. B.

2017-11-01

We explore the simplification of widely used meta-generalized-gradient approximation (mGGA) exchange-correlation functionals to the Laplacian level of refinement by use of approximate kinetic-energy density functionals (KEDFs). Such deorbitalization is motivated by the prospect of reducing computational cost while recovering a strictly Kohn-Sham local potential framework (rather than the usual generalized Kohn-Sham treatment of mGGAs). A KEDF that has been rather successful in solid simulations proves to be inadequate for deorbitalization, but we produce other forms which, with parametrization to Kohn-Sham results (not experimental data) on a small training set, yield rather good results on standard molecular test sets when used to deorbitalize the meta-GGA made very simple, Tao-Perdew-Staroverov-Scuseria, and strongly constrained and appropriately normed functionals. We also study the difference between high-fidelity and best-performing deorbitalizations and discuss possible implications for use in ab initio molecular dynamics simulations of complicated condensed phase systems.

Gait Correlation Analysis Based Human Identification

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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.

Correlation analysis in chemistry: recent advances

National Research Council Canada - National Science Library

Shorter, John; Chapman, Norman Bellamy

1978-01-01

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

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.

Correlation Between Protein Intake and Nitrogen Balance of Surgical Patients in Anesthesiology and Intensive Care Installation, Sanglah General Hospital, Denpasar, Bali, Indonesia

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Made Wiryana

2016-06-01

Full Text Available Background: A cell injury from surgical stress in a trauma or a non-trauma case will induce a hyper metabolic response in which the protein degradation increases, the somatic protein synthesis decreases and the amino acid catabolism increases. Thus, the pyper metabolic response contributes to nitrogen loss in urine. This response, without an adequate nutrition, will lead an iatrogenic malnutrition and deterioration. A balance nitrogen formula through urinary urea nitrogen is one of many nutrition evaluation methods. This method aids in evaluating the daily nutrition status and it can be the baseline data for daily intake. Objective: To find a correlation between the protein intake and the nitrogen balance of the surgical patients in anesthesiology and intensive care installation, Sanglah General Hospital, Denpasar, Bali. Methods: Fifty-one surgical patients with trauma and non-trauma cases were observed for their protein intake for 2-3 days continuously. Moreover, they were evaluated for their nitrogen balance based on the urinary urea nitrogen per 24 hours for 2-3 days. For statistical analysis, we utilized Shapiro-Francia, Shapiro-Wilk, Spearman Frank correlation, two-sample t test, and multivariate regression analysis in Strata SE 12.1. Results: The correlation between the protein intake and the nitrogen balance on the first day was ra=0.50 (p<0.05, on the second day ra=0.70 (p<0,05, and on the third day ra=0.740 (p<0,05. Conclusions: There is a correlation between the protein intake and the nitrogen balance of surgical patients in Anesthesiology and Intensive Care Installation Sanglah General Hospital Denpasar. 

Analysis of correlations between sites in models of protein sequences

International Nuclear Information System (INIS)

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

1998-01-01

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

Cumulative trauma, hyperarousal, and suicidality in the general population: a path analysis.

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Briere, John; Godbout, Natacha; Dias, Colin

2015-01-01

Although trauma exposure and posttraumatic stress disorder (PTSD) both have been linked to suicidal thoughts and behavior, the underlying basis for this relationship is not clear. In a sample of 357 trauma-exposed individuals from the general population, younger participant age, cumulative trauma exposure, and all three Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, PTSD clusters (reexperiencing, avoidance, and hyperarousal) were correlated with clinical levels of suicidality. However, logistic regression analysis indicated that when all PTSD clusters were considered simultaneously, only hyperarousal continued to be predictive. A path analysis confirmed that posttraumatic hyperarousal (but not other components of PTSD) fully mediated the relationship between extent of trauma exposure and degree of suicidal thoughts and behaviors.

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.

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

International Nuclear Information System (INIS)

Nowikow, C.V.; Grice, R.

1979-01-01

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

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

Development of generalized correlation equation for the local wall shear stress

International Nuclear Information System (INIS)

Jeon, Yu Mi; Bae, Jun Ho; Park, Joo Hwan

2010-01-01

The pressure drop characteristics for a fuel channel are essential for the design and reliable operation of a nuclear reactor. Over several decades, analytical methods have been developed to predict the friction factor in the fuel bundle flows. In order to enhance the accuracy of prediction for the pressure drop in a rod bundle, the influences of a channel wall and the local shear stress distribution should be considered. Hence, the correlation equation for a local shear stress distribution should be developed in order to secure an analytical solution for the friction factor of a rod bundle. For a side subchannel, which has the influence of the channel wall, the local shear stress distribution is dependent on the ratio of wall to diameter (W/D) as well as the ratio of pitch to diameter (P/D). In the case that W/D has the same value with P/D, the local shear stress distribution can be simply correlated with the function of angular position for each value of P/D. While, in the case that W/D has the different value with P/D, the correlation equation should be developed for each case of P/D and W/D. Hence, in the present study, the generalized correlation equation of a local shear stress distribution is developed for a side subchannel in the case that W/D has the different value with P/D

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

Alterations in white matter volume and its correlation with clinical characteristics in patients with generalized anxiety disorder

International Nuclear Information System (INIS)

Moon, Chung-Man; Jeong, Gwang-Woo

2015-01-01

Only a few morphological studies have focused on changes in white matter (WM) volume in patients with generalized anxiety disorder (GAD). We evaluated alterations in WM volume and its correlation with symptom severity and duration of illness in adults with GAD. The 44 subjects were comprised of 22 patients with GAD (13 males and nine females) diagnosed using the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision (DSM-IV-TR) and 22 age-matched healthy controls (13 males and nine females). High-resolution magnetic resonance imaging (MRI) data were processed by voxel-based morphometry (VBM) analysis based on diffeomorphic anatomical registration using the exponentiated Lie algebra (DARTEL) algorithm in SPM8. Patients with GAD showed significantly reduced WM volume, particularly in the dorsolateral prefrontal cortex (DLPFC), anterior limb of the internal capsule (ALIC), and midbrain. In addition, DLPFC volume was negatively correlated with GAD-7 score and illness duration. ALIC volume was negatively correlated with GAD-7 score. Female patients had significantly less orbitofrontal cortex volume compared to that in male patients. The findings demonstrate localized changes in WM volume associated with cognitive and emotional dysfunction in patients with GAD. The finding will be helpful for understanding the neuropathology in patients with GAD. (orig.)

Alterations in white matter volume and its correlation with clinical characteristics in patients with generalized anxiety disorder

Energy Technology Data Exchange (ETDEWEB)

Moon, Chung-Man [Chonnam National University Hospital, Research Institute for Medical Imaging, Gwangju (Korea, Republic of); Jeong, Gwang-Woo [Chonnam National University Hospital, Research Institute for Medical Imaging, Gwangju (Korea, Republic of); Chonnam National University Medical School, Department of Radiology, Chonnam National University Hospital, Gwangju (Korea, Republic of)

2015-11-15

Only a few morphological studies have focused on changes in white matter (WM) volume in patients with generalized anxiety disorder (GAD). We evaluated alterations in WM volume and its correlation with symptom severity and duration of illness in adults with GAD. The 44 subjects were comprised of 22 patients with GAD (13 males and nine females) diagnosed using the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision (DSM-IV-TR) and 22 age-matched healthy controls (13 males and nine females). High-resolution magnetic resonance imaging (MRI) data were processed by voxel-based morphometry (VBM) analysis based on diffeomorphic anatomical registration using the exponentiated Lie algebra (DARTEL) algorithm in SPM8. Patients with GAD showed significantly reduced WM volume, particularly in the dorsolateral prefrontal cortex (DLPFC), anterior limb of the internal capsule (ALIC), and midbrain. In addition, DLPFC volume was negatively correlated with GAD-7 score and illness duration. ALIC volume was negatively correlated with GAD-7 score. Female patients had significantly less orbitofrontal cortex volume compared to that in male patients. The findings demonstrate localized changes in WM volume associated with cognitive and emotional dysfunction in patients with GAD. The finding will be helpful for understanding the neuropathology in patients with GAD. (orig.)

Clustering stocks using partial correlation coefficients

Science.gov (United States)

Jung, Sean S.; Chang, Woojin

2016-11-01

A partial correlation analysis is performed on the Korean stock market (KOSPI). The difference between Pearson correlation and the partial correlation is analyzed and it is found that when conditioned on the market return, Pearson correlation coefficients are generally greater than those of the partial correlation, which implies that the market return tends to drive up the correlation between stock returns. A clustering analysis is then performed to study the market structure given by the partial correlation analysis and the members of the clusters are compared with the Global Industry Classification Standard (GICS). The initial hypothesis is that the firms in the same GICS sector are clustered together since they are in a similar business and environment. However, the result is inconsistent with the hypothesis and most clusters are a mix of multiple sectors suggesting that the traditional approach of using sectors to determine the proximity between stocks may not be sufficient enough to diversify a portfolio.

Subsystem density functional theory with meta-generalized gradient approximation exchange-correlation functionals.

Science.gov (United States)

Śmiga, Szymon; Fabiano, Eduardo; Laricchia, Savio; Constantin, Lucian A; Della Sala, Fabio

2015-04-21

We analyze the methodology and the performance of subsystem density functional theory (DFT) with meta-generalized gradient approximation (meta-GGA) exchange-correlation functionals for non-bonded molecular systems. Meta-GGA functionals depend on the Kohn-Sham kinetic energy density (KED), which is not known as an explicit functional of the density. Therefore, they cannot be directly applied in subsystem DFT calculations. We propose a Laplacian-level approximation to the KED which overcomes this limitation and provides a simple and accurate way to apply meta-GGA exchange-correlation functionals in subsystem DFT calculations. The so obtained density and energy errors, with respect to the corresponding supermolecular calculations, are comparable with conventional approaches, depending almost exclusively on the approximations in the non-additive kinetic embedding term. An embedding energy error decomposition explains the accuracy of our method.

A flexible time recording and time correlation analysis system

International Nuclear Information System (INIS)

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

1983-01-01

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

Comprehensive analysis of electron correlations in three-electron atoms

International Nuclear Information System (INIS)

Morishita, T.; Lin, C.D.

1999-01-01

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

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.

Closure and ratio correlation analysis of lunar chemical and grain size data

Science.gov (United States)

Butler, J. C.

1976-01-01

Major element and major element plus trace element analyses were selected from the lunar data base for Apollo 11, 12 and 15 basalt and regolith samples. Summary statistics for each of the six data sets were compiled, and the effects of closure on the Pearson product moment correlation coefficient were investigated using the Chayes and Kruskal approximation procedure. In general, there are two types of closure effects evident in these data sets: negative correlations of intermediate size which are solely the result of closure, and correlations of small absolute value which depart significantly from their expected closure correlations which are of intermediate size. It is shown that a positive closure correlation will arise only when the product of the coefficients of variation is very small (less than 0.01 for most data sets) and, in general, trace elements in the lunar data sets exhibit relatively large coefficients of variation.

The General Factor of Personality: A General Critique.

Science.gov (United States)

Revelle, William; Wilt, Joshua

2013-10-01

Recently, it has been proposed that all non-cognitive measures of personality share a general factor of personality. A problem with many of these studies is a lack of clarity in defining a general factor. In this paper we address the multiple ways in which a general factor has been identified and argue that many of these approaches find factors that are not in fact general. Through the use of artificial examples, we show that a general factor is not: The first factor or component of a correlation or covariance matrix.The first factor resulting from a bifactor rotation or biquartimin transformationNecessarily the result of a confirmatory factor analysis forcing a bifactor solution We consider how the definition of what constitutes a general factor can lead to confusion, and we will demonstrate alternative ways of estimating the general factor saturation that are more appropriate.

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

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

Directory of Open Access Journals (Sweden)

Jianhua Ni

2016-08-01

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

Two new bivariate zero-inflated generalized Poisson distributions with a flexible correlation structure

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Chi Zhang

2015-05-01

Full Text Available To model correlated bivariate count data with extra zero observations, this paper proposes two new bivariate zero-inflated generalized Poisson (ZIGP distributions by incorporating a multiplicative factor (or dependency parameter λ, named as Type I and Type II bivariate ZIGP distributions, respectively. The proposed distributions possess a flexible correlation structure and can be used to fit either positively or negatively correlated and either over- or under-dispersed count data, comparing to the existing models that can only fit positively correlated count data with over-dispersion. The two marginal distributions of Type I bivariate ZIGP share a common parameter of zero inflation while the two marginal distributions of Type II bivariate ZIGP have their own parameters of zero inflation, resulting in a much wider range of applications. The important distributional properties are explored and some useful statistical inference methods including maximum likelihood estimations of parameters, standard errors estimation, bootstrap confidence intervals and related testing hypotheses are developed for the two distributions. A real data are thoroughly analyzed by using the proposed distributions and statistical methods. Several simulation studies are conducted to evaluate the performance of the proposed methods.

Graphology and personality: a correlational analysis

OpenAIRE

2008-01-01

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

General and specialized brain correlates for analogical reasoning: A meta-analysis of functional imaging studies.

Science.gov (United States)

Hobeika, Lucie; Diard-Detoeuf, Capucine; Garcin, Béatrice; Levy, Richard; Volle, Emmanuelle

2016-05-01

Reasoning by analogy allows us to link distinct domains of knowledge and to transfer solutions from one domain to another. Analogical reasoning has been studied using various tasks that have generally required the consideration of the relationships between objects and their integration to infer an analogy schema. However, these tasks varied in terms of the level and the nature of the relationships to consider (e.g., semantic, visuospatial). The aim of this study was to identify the cerebral network involved in analogical reasoning and its specialization based on the domains of information and task specificity. We conducted a coordinate-based meta-analysis of 27 experiments that used analogical reasoning tasks. The left rostrolateral prefrontal cortex was one of the regions most consistently activated across the studies. A comparison between semantic and visuospatial analogy tasks showed both domain-oriented regions in the inferior and middle frontal gyri and a domain-general region, the left rostrolateral prefrontal cortex, which was specialized for analogy tasks. A comparison of visuospatial analogy to matrix problem tasks revealed that these two relational reasoning tasks engage, at least in part, distinct right and left cerebral networks, particularly separate areas within the left rostrolateral prefrontal cortex. These findings highlight several cognitive and cerebral differences between relational reasoning tasks that can allow us to make predictions about the respective roles of distinct brain regions or networks. These results also provide new, testable anatomical hypotheses about reasoning disorders that are induced by brain damage. Hum Brain Mapp 37:1953-1969, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

The correlation of pain intensity and quality of life in chronic LBP patients in Adam Malik general hospital

Science.gov (United States)

Nasution, I. K.; Lubis, N. D. A.; Amelia, S.; Hocin, K.

2018-03-01

Low back pain (LBP) is a world health problems and a major cause of disability. The study is to determine the correlation between pain intensity and quality of life (QoL) in patients with chronic LBP. This study was a descriptive, analytical research with the cross sectional design. Twenty-nine chronic LBP outpatients that have visited the Neurology Clinic of Adam Malik General Hospital Medan. Patients from July to November 2015 were selected by consecutive sampling. A questionnaire and interview are asking the information about subjects’ characteristics, diagnosis, medical history, pain intensity and quality of life-based on WHO QoL criteria were used to collect the data. Using Spearman correlation test, we found correlation among VAS and physical function (pphysical problems (phealth (p=0.040, r=-0.330). On the other hand, there was no correlation between VAS and mental health (p=0.110, r=-0.235). We concluded that pain intensity in outpatients with chronic LBP in the Neurology Clinic at Adam Malik General Hospital Medan correlates with the patients’ quality of life.

General Correlation Theorem for Trinion Fourier Transform

OpenAIRE

Bahri, Mawardi

2017-01-01

- The trinion Fourier transform is an extension of the Fourier transform in the trinion numbers setting. In this work we derive the correlation theorem for the trinion Fourier transform by using the relation between trinion convolution and correlation definitions in the trinion Fourier transform domains.

Generalized Fluid System Simulation Program (GFSSP) Version 6 - General Purpose Thermo-Fluid Network Analysis Software

Science.gov (United States)

Majumdar, Alok; Leclair, Andre; Moore, Ric; Schallhorn, Paul

2011-01-01

GFSSP stands for Generalized Fluid System Simulation Program. It is a general-purpose computer program to compute pressure, temperature and flow distribution in a flow network. GFSSP calculates pressure, temperature, and concentrations at nodes and calculates flow rates through branches. It was primarily developed to analyze Internal Flow Analysis of a Turbopump Transient Flow Analysis of a Propulsion System. GFSSP development started in 1994 with an objective to provide a generalized and easy to use flow analysis tool for thermo-fluid systems.

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

Energy Technology Data Exchange (ETDEWEB)

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

2017-01-15

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

Generalized correlation of indefiniteness coordinate-impulse in quantum mechanics and theory of brownian movement

International Nuclear Information System (INIS)

Sukhanov, A.D.

2004-01-01

Generalized correlations of the Schroedinger indefinitenesses are shown to have the meaning of the fundamental restrictions as to characteristics of space of states in any probability-like theory. Quantum mechanics, as well as, theory of the brownian movement at arbitrary space of time fall in the category of the mentioned theories. One compared correlations of coordinates-pulse indefinitenesses within the mentioned theory with the similar correlation of indefinitenesses for microparticle under the Gaussian wave packet state. One determined that in case of profound distinction in mathematical tools of two theories one observes their conceptual resemblance. It manifests itself under the alternative conditions - short times in one theory correspond to long ones in another theory and vice versa, while in any of the mentioned theories uncontrollable effect of either quantum or thermal type is of crucial importance [ru

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.

Data analytics using canonical correlation analysis and Monte Carlo simulation

Science.gov (United States)

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

2017-07-01

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

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.

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

International Nuclear Information System (INIS)

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

2014-01-01

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

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.)

Breakdown of long-range temporal correlations in brain oscillations during general anesthesia.

Science.gov (United States)

Krzemiński, Dominik; Kamiński, Maciej; Marchewka, Artur; Bola, Michał

2017-10-01

Consciousness has been hypothesized to emerge from complex neuronal dynamics, which prevails when brain operates in a critical state. Evidence supporting this hypothesis comes mainly from studies investigating neuronal activity on a short time-scale of seconds. However, a key aspect of criticality is presence of scale-free temporal dependencies occurring across a wide range of time-scales. Indeed, robust long-range temporal correlations (LRTCs) are found in neuronal oscillations during conscious states, but it is not known how LRTCs are affected by loss of consciousness. To further test a relation between critical dynamics and consciousness, we investigated LRTCs in electrocorticography signals recorded from four macaque monkeys during resting wakefulness and general anesthesia induced by various anesthetics (ketamine, medetomidine, or propofol). Detrended Fluctuation Analysis was used to estimate LRTCs in amplitude fluctuations (envelopes) of band-pass filtered signals. We demonstrate two main findings. First, during conscious states all lateral cortical regions are characterized by significant LRTCs of alpha-band activity (7-14 Hz). LRTCs are stronger in the eyes-open than eyes-closed state, but in both states they form a spatial gradient, with anterior brain regions exhibiting stronger LRTCs than posterior regions. Second, we observed a substantial decrease of LRTCs during loss of consciousness, the magnitude of which was associated with the baseline (i.e. pre-anesthesia) state of the brain. Specifically, brain regions characterized by strongest LRTCs during a wakeful baseline exhibited greatest decreases during anesthesia (i.e. "the rich got poorer"), which consequently disturbed the posterior-anterior gradient. Therefore, our results suggest that general anesthesia affects mainly brain areas characterized by strongest LRTCs during wakefulness, which might account for lack of capacities for extensive temporal integration during loss of consciousness. Copyright

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...

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.

Addictive Potential of Internet Applications and Differential Correlates of Problematic Use in Internet Gamers versus Generalized Internet Users in a Representative Sample of Adolescents.

Science.gov (United States)

Rosenkranz, Tabea; Müller, Kai W; Dreier, Michael; Beutel, Manfred E; Wölfling, Klaus

2017-01-01

This paper examines the addictive potential of 8 different Internet applications, distinguishing male and female users. Moreover, differential correlates of problematic use are investigated in Internet gamers (IG) and generalized Internet users (GIU). In a representative sample of 5,667 adolescents aged 12-19 years, use of Internet applications, problematic Internet use, psychopathologic symptoms (emotional problems, hyperactivity/inattention, and psychosomatic complaints), personality (conscientiousness and extraversion), psychosocial correlates (perceived stress and self-efficacy), and coping strategies were assessed. The addictive potential of Internet applications was examined in boys and girls using regression analysis. MANOVAs were conducted to examine differential correlates of problematic Internet use between IG and GIU. Chatting and social networking most strongly predicted problematic Internet use in girls, while gaming was the strongest predictor in boys. Problematic IG exhibited multiple psychosocial problems compared to non-problematic IG. In problematic Internet users, GIU reported even higher psychosocial burden and displayed dysfunctional coping strategies more frequently than gamers. The results extend previous findings on the addictive potential of Internet applications and validate the proposed distinction between specific and generalized problematic Internet use. In addition to Internet gaming disorder, future studies should also focus on other highly addictive Internet applications, that is, chatting or social networking, regarding differential correlates of problematic use. © 2017 S. Karger AG, Basel.

A covariance correction that accounts for correlation estimation to improve finite-sample inference with generalized estimating equations: A study on its applicability with structured correlation matrices.

Science.gov (United States)

Westgate, Philip M

2016-01-01

When generalized estimating equations (GEE) incorporate an unstructured working correlation matrix, the variances of regression parameter estimates can inflate due to the estimation of the correlation parameters. In previous work, an approximation for this inflation that results in a corrected version of the sandwich formula for the covariance matrix of regression parameter estimates was derived. Use of this correction for correlation structure selection also reduces the over-selection of the unstructured working correlation matrix. In this manuscript, we conduct a simulation study to demonstrate that an increase in variances of regression parameter estimates can occur when GEE incorporates structured working correlation matrices as well. Correspondingly, we show the ability of the corrected version of the sandwich formula to improve the validity of inference and correlation structure selection. We also study the relative influences of two popular corrections to a different source of bias in the empirical sandwich covariance estimator.

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

Directory of Open Access Journals (Sweden)

Tomoko Yamasaki

2018-05-01

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

Big Five Traits and Inclusive Generalized Prejudice

OpenAIRE

Brandt, Mark; Crawford, Jarret

2018-01-01

Existing meta-analytic evidence finds that low levels of Openness and Agreeableness correlate with generalized prejudice. However, previous studies relied on restricted operationalizations of generalized prejudice that only assessed prejudice toward disadvantaged, low-status groups. Across four samples (total N = 7,543), we tested the associations between Big Five traits and generalized prejudice using an inclusive operationalization of generalized prejudice. A meta-analysis of these findings...

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.

Discourse analysis in general practice: a sociolinguistic approach.

Science.gov (United States)

Nessa, J; Malterud, K

1990-06-01

It is a simple but important fact that as general practitioners we talk to our patients. The quality of the conversation is of vital importance for the outcome of the consultation. The purpose of this article is to discuss a methodological tool borrowed from sociolinguistics--discourse analysis. To assess the suitability of this method for analysis of general practice consultations, the authors have performed a discourse analysis of one single consultation. Our experiences are presented here.

Generalized Smoluchowski equation with correlation between clusters

International Nuclear Information System (INIS)

Sittler, Lionel

2008-01-01

In this paper we compute new reaction rates of the Smoluchowski equation which takes into account correlations. The new rate K = K MF + K C is the sum of two terms. The first term is the known Smoluchowski rate with the mean-field approximation. The second takes into account a correlation between clusters. For this purpose we introduce the average path of a cluster. We relate the length of this path to the reaction rate of the Smoluchowski equation. We solve the implicit dependence between the average path and the density of clusters. We show that this correlation length is the same for all clusters. Our result depends strongly on the spatial dimension d. The mean-field term K MF i,j = (D i + D j )(r j + r i ) d-2 , which vanishes for d = 1 and is valid up to logarithmic correction for d = 2, is the usual rate found with the Smoluchowski model without correlation (where r i is the radius and D i is the diffusion constant of the cluster). We compute a new rate: the correlation rate K i,j C = (D i +D j )(r j +r i ) d-1 M((d-1)/d f ) is valid for d ≥ 1(where M(α) = Σ +∞ i=1 i α N i is the moment of the density of clusters and d f is the fractal dimension of the cluster). The result is valid for a large class of diffusion processes and mass-radius relations. This approach confirms some analytical solutions in d = 1 found with other methods. We also show Monte Carlo simulations which illustrate some exact new solvable models

Automatic movie skimming with general tempo analysis

Science.gov (United States)

Lee, Shih-Hung; Yeh, Chia-Hung; Kuo, C. C. J.

2003-11-01

Story units are extracted by general tempo analysis including tempos analysis including tempos of audio and visual information in this research. Although many schemes have been proposed to successfully segment video data into shots using basic low-level features, how to group shots into meaningful units called story units is still a challenging problem. By focusing on a certain type of video such as sport or news, we can explore models with the specific application domain knowledge. For movie contents, many heuristic rules based on audiovisual clues have been proposed with limited success. We propose a method to extract story units using general tempo analysis. Experimental results are given to demonstrate the feasibility and efficiency of the proposed technique.

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

Science.gov (United States)

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

2017-05-01

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

Analysis of charge-dependent azimuthal correlations with HADES

Energy Technology Data Exchange (ETDEWEB)

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

2016-07-01

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

General correlations for pressure drop and heat transfer for single-phase turbulent flow in internally ribbed tubes

International Nuclear Information System (INIS)

Ravigururajan, T.S.; Bergles, A.E.

1985-01-01

General correlations for friction factors and heat transfer coefficients for single-phase turbulent flow in internally ribbed tubes are presented. Data from previous investigations are gathered for a wide range of tube parameters with e/d: 0.01 to 0.2; p/d: 0.1 to 7.0; α/90: 0.3 to 1.0, and flow parameters Re: 5000 to 250,000 and Pr: 0.66 to 37.6. The data were applied to a linear model to get normalized correlations that were then modified to fit tubes with extremely small parametric values. A shape function was included in the friction correlation to account for different rib profiles. The friction correlation predicts 96% of the data base to within +. 50% and 77% of the data base to within +. 20%. Corresponding figures for the heat transfer correlation are 99% and 69%. The present correlations are superior, for this extensive data base, to those presented by other investigators

Harmonic Analysis Associated with the Generalized q-Bessel Operator

Directory of Open Access Journals (Sweden)

Ahmed Abouelaz

2016-01-01

Full Text Available In this article, we give a new harmonic analysis associated with the generalized q-Bessel operator. We introduce the generalized $q$-Bessel transform, the generalized q-Bessel translation and the generalized $q$-Bessel convolution product.

Message Correlation Analysis Tool for NOvA

International Nuclear Information System (INIS)

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

2012-01-01

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

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++.

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.

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++.

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.

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

Indian Academy of Sciences (India)

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

Correlated binomial models and correlation structures

International Nuclear Information System (INIS)

Hisakado, Masato; Kitsukawa, Kenji; Mori, Shintaro

2006-01-01

We discuss a general method to construct correlated binomial distributions by imposing several consistent relations on the joint probability function. We obtain self-consistency relations for the conditional correlations and conditional probabilities. The beta-binomial distribution is derived by a strong symmetric assumption on the conditional correlations. Our derivation clarifies the 'correlation' structure of the beta-binomial distribution. It is also possible to study the correlation structures of other probability distributions of exchangeable (homogeneous) correlated Bernoulli random variables. We study some distribution functions and discuss their behaviours in terms of their correlation structures

Generalized Path Analysis and Generalized Simultaneous Equations Model for Recursive Systems with Responses of Mixed Types

Science.gov (United States)

Tsai, Tien-Lung; Shau, Wen-Yi; Hu, Fu-Chang

2006-01-01

This article generalizes linear path analysis (PA) and simultaneous equations models (SiEM) to deal with mixed responses of different types in a recursive or triangular system. An efficient instrumental variable (IV) method for estimating the structural coefficients of a 2-equation partially recursive generalized path analysis (GPA) model and…

Measuring time-of-flight in an ultrasonic LPS system using generalized cross-correlation.

Science.gov (United States)

Villladangos, José Manuel; Ureña, Jesús; García, Juan Jesús; Mazo, Manuel; Hernández, Alvaro; Jiménez, Ana; Ruíz, Daniel; De Marziani, Carlos

2011-01-01

In this article, a time-of-flight detection technique in the frequency domain is described for an ultrasonic local positioning system (LPS) based on encoded beacons. Beacon transmissions have been synchronized and become simultaneous by means of the DS-CDMA (direct-sequence code Division multiple access) technique. Every beacon has been associated to a 255-bit Kasami code. The detection of signal arrival instant at the receiver, from which the distance to each beacon can be obtained, is based on the application of the generalized cross-correlation (GCC), by using the cross-spectral density between the received signal and the sequence to be detected. Prior filtering to enhance the frequency components around the carrier frequency (40 kHz) has improved estimations when obtaining the correlation function maximum, which implies an improvement in distance measurement precision. Positioning has been achieved by using hyperbolic trilateration, based on the time differences of arrival (TDOA) between a reference beacon and the others.

Correlation between General Health with Emotional Intelligence and Creativity in Medical College Students at Islamic Azad University, Sari Branch, Sari, Iran

Directory of Open Access Journals (Sweden)

MK Fakhri

2012-07-01

Full Text Available

Background and Objectives: Medical students are a particular class of students that Because of their specific problems, investigation of their general health has always been considered. This study is concerned with investigation of relationship between general health and emotional intelligence and creativity in medical college students at Islamic Azad University, Sari branch.

Methods: 150 medical college students at Islamic Azad University, Sari branch (45 males and 105 females, were randomly selected and Goldberg general health, Shring emotional intelligence and Abedi creativity questionnaire were completed. For data analysis, Pearson correlation and independent t-test were used.

Results: Results showed that: there is positive relationship between general health and emotional intelligence (r=0.53 and p<0.05, there is a positive relationship between general health and creativity (r=0.60 and p<0.01, and female college students are healthier than males (p<0.05.

Conclusion: results of this research indicated that there is a positive relationship between general health and emotional intelligence and creativity, and since these variables are effective in professional prospect of Medical students, employing cognitive and behavioral methods in promotion of general health in these students seem necessary.

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

International Nuclear Information System (INIS)

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

1989-11-01

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

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

African Journals Online (AJOL)

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

Exploring inter-frame correlation analysis and wavelet-domain modeling for real-time caption detection in streaming video

Science.gov (United States)

Li, Jia; Tian, Yonghong; Gao, Wen

2008-01-01

In recent years, the amount of streaming video has grown rapidly on the Web. Often, retrieving these streaming videos offers the challenge of indexing and analyzing the media in real time because the streams must be treated as effectively infinite in length, thus precluding offline processing. Generally speaking, captions are important semantic clues for video indexing and retrieval. However, existing caption detection methods often have difficulties to make real-time detection for streaming video, and few of them concern on the differentiation of captions from scene texts and scrolling texts. In general, these texts have different roles in streaming video retrieval. To overcome these difficulties, this paper proposes a novel approach which explores the inter-frame correlation analysis and wavelet-domain modeling for real-time caption detection in streaming video. In our approach, the inter-frame correlation information is used to distinguish caption texts from scene texts and scrolling texts. Moreover, wavelet-domain Generalized Gaussian Models (GGMs) are utilized to automatically remove non-text regions from each frame and only keep caption regions for further processing. Experiment results show that our approach is able to offer real-time caption detection with high recall and low false alarm rate, and also can effectively discern caption texts from the other texts even in low resolutions.

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

Science.gov (United States)

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

2015-01-01

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

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

Science.gov (United States)

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

2013-10-01

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

MAGMA: Generalized Gene-Set Analysis of GWAS Data

NARCIS (Netherlands)

de Leeuw, C.A.; Mooij, J.M.; Heskes, T.; Posthuma, D.

2015-01-01

By aggregating data for complex traits in a biologically meaningful way, gene and gene-set analysis constitute a valuable addition to single-marker analysis. However, although various methods for gene and gene-set analysis currently exist, they generally suffer from a number of issues. Statistical

MAGMA: generalized gene-set analysis of GWAS data.

NARCIS (Netherlands)

de Leeuw, C.A.; Mooij, J.M.; Heskes, T.; Posthuma, D.

2015-01-01

By aggregating data for complex traits in a biologically meaningful way, gene and gene-set analysis constitute a valuable addition to single-marker analysis. However, although various methods for gene and gene-set analysis currently exist, they generally suffer from a number of issues. Statistical

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%.

Generalized Langevin dynamics of a nanoparticle using a finite element approach: Thermostating with correlated noise

Science.gov (United States)

Uma, B.; Swaminathan, T. N.; Ayyaswamy, P. S.; Eckmann, D. M.; Radhakrishnan, R.

2011-09-01

A direct numerical simulation (DNS) procedure is employed to study the thermal motion of a nanoparticle in an incompressible Newtonian stationary fluid medium with the generalized Langevin approach. We consider both the Markovian (white noise) and non-Markovian (Ornstein-Uhlenbeck noise and Mittag-Leffler noise) processes. Initial locations of the particle are at various distances from the bounding wall to delineate wall effects. At thermal equilibrium, the numerical results are validated by comparing the calculated translational and rotational temperatures of the particle with those obtained from the equipartition theorem. The nature of the hydrodynamic interactions is verified by comparing the velocity autocorrelation functions and mean square displacements with analytical results. Numerical predictions of wall interactions with the particle in terms of mean square displacements are compared with analytical results. In the non-Markovian Langevin approach, an appropriate choice of colored noise is required to satisfy the power-law decay in the velocity autocorrelation function at long times. The results obtained by using non-Markovian Mittag-Leffler noise simultaneously satisfy the equipartition theorem and the long-time behavior of the hydrodynamic correlations for a range of memory correlation times. The Ornstein-Uhlenbeck process does not provide the appropriate hydrodynamic correlations. Comparing our DNS results to the solution of an one-dimensional generalized Langevin equation, it is observed that where the thermostat adheres to the equipartition theorem, the characteristic memory time in the noise is consistent with the inherent time scale of the memory kernel. The performance of the thermostat with respect to equilibrium and dynamic properties for various noise schemes is discussed.

Model-independent analysis with BPM correlation matrices

International Nuclear Information System (INIS)

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

1998-06-01

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

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

Science.gov (United States)

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

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

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

Science.gov (United States)

Dutta, Srimonti; Ghosh, Dipak; Chatterjee, Sucharita

2016-12-01

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

Analysis of correlation functions in Toda theory and the Alday-Gaiotto-Tachikawa-Wyllard relation for SU(3) quiver

International Nuclear Information System (INIS)

Kanno, Shoichi; Matsuo, Yutaka; Shiba, Shotaro

2010-01-01

We give some evidences of the Alday-Gaiotto-Tachikawa-Wyllard relation between SU(3) quiver gauge theories and A 2 Toda theory. In particular, we derive the explicit form of 5-point correlation functions in the lower orders and confirm the agreement with Nekrasov's partition function for SU(3)xSU(3) quiver gauge theory. The algorithm to derive the correlation functions can be applied to a general n-point function in A 2 Toda theory, which will be useful to establish the relation for more generic quivers. Partial analysis is also given for the SU(3)xSU(2) case, and we comment on some technical issues that need clarification before establishing the relation.

Apparent violation of the sum rule for exchange-correlation charges by generalized gradient approximations.

Science.gov (United States)

Kohut, Sviataslau V; Staroverov, Viktor N

2013-10-28

The exchange-correlation potential of Kohn-Sham density-functional theory, vXC(r), can be thought of as an electrostatic potential produced by the static charge distribution qXC(r) = -(1∕4π)∇(2)vXC(r). The total exchange-correlation charge, QXC = ∫qXC(r) dr, determines the rate of the asymptotic decay of vXC(r). If QXC ≠ 0, the potential falls off as QXC∕r; if QXC = 0, the decay is faster than coulombic. According to this rule, exchange-correlation potentials derived from standard generalized gradient approximations (GGAs) should have QXC = 0, but accurate numerical calculations give QXC ≠ 0. We resolve this paradox by showing that the charge density qXC(r) associated with every GGA consists of two types of contributions: a continuous distribution and point charges arising from the singularities of vXC(r) at each nucleus. Numerical integration of qXC(r) accounts for the continuous charge but misses the point charges. When the point-charge contributions are included, one obtains the correct QXC value. These findings provide an important caveat for attempts to devise asymptotically correct Kohn-Sham potentials by modeling the distribution qXC(r).

Parental Divorce and Generalized Trust

OpenAIRE

Viitanen, Tarja

2011-01-01

This paper examines the effect of parental divorce during childhood on generalized trust later on in life using Australian HILDA panel data. The dependent variable is composed of answers to the statement: “Generally speaking, most people can be trusted”. The main explanatory variables include the occurrence of parental divorce for the whole sample and the age at which parents divorced for the sub-sample. The analysis is conducted using random effects ordered probit, correlated random effects ...

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

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.

Gastroesophageal reflux disease symptoms and dietary behaviors are significant correlates of short sleep duration in the general population: the Nagahama Study.

Science.gov (United States)

Murase, Kimihiko; Tabara, Yasuharu; Takahashi, Yoshimitsu; Muro, Shigeo; Yamada, Ryo; Setoh, Kazuya; Kawaguchi, Takahisa; Kadotani, Hiroshi; Kosugi, Shinji; Sekine, Akihiro; Nakayama, Takeo; Mishima, Michiaki; Chiba, Tsutomu; Chin, Kazuo; Matsuda, Fumihiko

2014-11-01

To examine relationships among gastroesophageal reflux disease (GERD) symptoms, dietary behaviors, and sleep duration in the general population. Cross-sectional. Community-based. There were 9,643 participants selected from the general population (54 ± 13 y). None. Sleep duration, sleep habits, and unfavorable dietary behaviors of each participant were assessed with a structured questionnaire. Participants were categorized into five groups according to their sleep duration: less than 5 h, 5 to less than 6 h, 6 to less than 7 h, 7 to less than 8 h, and 8 or more h per day. GERD was evaluated using the Frequency Scale for the Symptoms of GERD (FSSG) and participants having an FSSG score of 8 or more or those under treatment of GERD were defined as having GERD. Trend analysis showed that both the FSSG score and the number of unfavorable dietary habits increased with decreasing sleep duration. Further, multiple logistic regression analysis showed that both the presence of GERD (odds ratio = 1.19, 95% confidence interval (CI) = 1.07-1.32) and the number of unfavorable dietary behaviors (odds ratio = 1.19, 95% CI = 1.13-1.26) were independent and potent factors to identify participants with short sleep duration even after controlling for other confounding factors. The current study showed that both GERD symptoms and unfavorable dietary behaviors were significant correlates of short sleep duration independently of each other in a large sample from the general population.

L2 Reading Comprehension and Its Correlates: A Meta-Analysis

Science.gov (United States)

Jeon, Eun Hee; Yamashita, Junko

2014-01-01

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

A generalized correlation for steam condensation rates in the presence of air under turbulent free convection - 15549

International Nuclear Information System (INIS)

Dehbi, A.

2015-01-01

In the past several decades, experimentalists have proposed a large number of correlations to estimate steam condensation rates in the presence of noncondensable gases in free convection regimes. These correlations are largely empirical, and usually of limited scope, which often leads to their use outside their range of validity, thus incurring the risk of significant errors. In this investigation, we disregard the correlations altogether, and instead go back to their underlying original data, consolidate them in a single set, and propose a generalized correlation that is compatible with the heat and mass transfer analogy. This best-estimate correlation for steam-air mixtures, based on six different investigations and 350 data points, covers two orders of magnitude in the heat transfer coefficient, and is valid for pressures up to 20 bars and steam mass fraction from 0.1 to 0.95. The consolidated raw data are self-consistent and collapse around a curve with a standard deviation of 16 %, thus well within typical experimental error bands. This demonstrates that there is no physical justification for the large deviations (factor 2 or more) observed sometimes when one compares the heat transfer coefficients predicted by different empirical correlations. (author)

Texture analysis using Renyi's generalized entropies

NARCIS (Netherlands)

Grigorescu, SE; Petkov, N

2003-01-01

We propose a texture analysis method based on Renyi's generalized entropies. The method aims at identifying texels in regular textures by searching for the smallest window through which the minimum number of different visual patterns is observed when moving the window over a given texture. The

Dissecting CFT Correlators and String Amplitudes. Conformal Blocks and On-Shell Recursion for General Tensor Fields

International Nuclear Information System (INIS)

Hansen, Tobias

2015-07-01

This thesis covers two main topics: the tensorial structure of quantum field theory correlators in general spacetime dimensions and a method for computing string theory scattering amplitudes directly in target space. In the first part tensor structures in generic bosonic CFT correlators and scattering amplitudes are studied. To this end arbitrary irreducible tensor representations of SO(d) (traceless mixed-symmetry tensors) are encoded in group invariant polynomials, by contracting with sets of commuting and anticommuting polarization vectors which implement the index symmetries of the tensors. The tensor structures appearing in CFT d correlators can then be inferred by studying these polynomials in a d + 2 dimensional embedding space. It is shown with an example how these correlators can be used to compute general conformal blocks describing the exchange of mixed-symmetry tensors in four-point functions, which are crucial for advancing the conformal bootstrap program to correlators of operators with spin. Bosonic string theory lends itself as an ideal example for applying the same methods to scattering amplitudes, due to its particle spectrum of arbitrary mixed-symmetry tensors. This allows in principle the definition of on-shell recursion relations for string theory amplitudes. A further chapter introduces a different target space definition of string scattering amplitudes. As in the case of on-shell recursion relations, the amplitudes are expressed in terms of their residues via BCFW shifts. The new idea here is that the residues are determined by use of the monodromy relations for open string theory, avoiding the infinite sums over the spectrum arising in on-shell recursion relations. Several checks of the method are presented, including a derivation of the Koba-Nielsen amplitude in the bosonic string. It is argued that this method provides a target space definition of the complete S-matrix of string theory at tree-level in a at background in terms of a small

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%) ...

Generalized Linear Covariance Analysis

Science.gov (United States)

Carpenter, James R.; Markley, F. Landis

2014-01-01

This talk presents a comprehensive approach to filter modeling for generalized covariance analysis of both batch least-squares and sequential estimators. We review and extend in two directions the results of prior work that allowed for partitioning of the state space into solve-for'' and consider'' parameters, accounted for differences between the formal values and the true values of the measurement noise, process noise, and textita priori solve-for and consider covariances, and explicitly partitioned the errors into subspaces containing only the influence of the measurement noise, process noise, and solve-for and consider covariances. In this work, we explicitly add sensitivity analysis to this prior work, and relax an implicit assumption that the batch estimator's epoch time occurs prior to the definitive span. We also apply the method to an integrated orbit and attitude problem, in which gyro and accelerometer errors, though not estimated, influence the orbit determination performance. We illustrate our results using two graphical presentations, which we call the variance sandpile'' and the sensitivity mosaic,'' and we compare the linear covariance results to confidence intervals associated with ensemble statistics from a Monte Carlo analysis.

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.

Development of a generalized correlation for phase-velocity measurements obtained from impedance-probe pairs in two-phase flow systems

International Nuclear Information System (INIS)

Hsu, C.T.; Keshock, E.G.; McGill, R.N.

1983-01-01

A flag type electrical impedance probe has been developed at the Oak Ridge National Lab (ORNL) to measure liquid- and vapor-phase velocities in steam-water mixtures flowing through rod bundles. Measurements are made by utilizing the probes in pairs, installed in line, parallel to the flow direction, and extending out into the flow channel. The present study addresses performance difficulties by examining from a fundamental point of view the two-phase flow system which the impedance probes typically operate in. Specifically, the governing equations (continuity, momentum, energy) were formulated for both air-water and steam-water systems, and then subjected to a scaling analysis. The scaling analysis yielded the appropriate dimensionless parameters of significance in both kinds of systems. Additionally, with the aid of experimental data obtained at ORNL, those parameters of significant magnitude were established. As a result, a generalized correlation was developed for liquid and vapor phase velocities that makes it possible to employ the impedance probe velocity measurement technique in a wide variety of test configurations and fluid combinations

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

African Journals Online (AJOL)

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

Entropy-based derivation of generalized distributions for hydrometeorological frequency analysis

Science.gov (United States)

Chen, Lu; Singh, Vijay P.

2018-02-01

Frequency analysis of hydrometeorological and hydrological extremes is needed for the design of hydraulic and civil infrastructure facilities as well as water resources management. A multitude of distributions have been employed for frequency analysis of these extremes. However, no single distribution has been accepted as a global standard. Employing the entropy theory, this study derived five generalized distributions for frequency analysis that used different kinds of information encoded as constraints. These distributions were the generalized gamma (GG), the generalized beta distribution of the second kind (GB2), and the Halphen type A distribution (Hal-A), Halphen type B distribution (Hal-B) and Halphen type inverse B distribution (Hal-IB), among which the GG and GB2 distribution were previously derived by Papalexiou and Koutsoyiannis (2012) and the Halphen family was first derived using entropy theory in this paper. The entropy theory allowed to estimate parameters of the distributions in terms of the constraints used for their derivation. The distributions were tested using extreme daily and hourly rainfall data. Results show that the root mean square error (RMSE) values were very small, which indicated that the five generalized distributions fitted the extreme rainfall data well. Among them, according to the Akaike information criterion (AIC) values, generally the GB2 and Halphen family gave a better fit. Therefore, those general distributions are one of the best choices for frequency analysis. The entropy-based derivation led to a new way for frequency analysis of hydrometeorological extremes.

A general theory for the construction of best-fit correlation equations for multi-dimensioned numerical data

International Nuclear Information System (INIS)

Moore, S.E.; Moffat, D.G.

2007-01-01

A general theory for the construction of best-fit correlation equations for multi-dimensioned sets of numerical data is presented. This new theory is based on the mathematics of n-dimensional surfaces and goodness-of-fit statistics. It is shown that orthogonal best-fit analytical trend lines for each of the independent parameters of the data can be used to construct an overall best-fit correlation equation that satisfies both physical boundary conditions and best-of-fit statistical measurements. Application of the theory is illustrated by fitting a three-parameter set of numerical finite-element maximum-stress data obtained earlier by Dr. Moffat for pressure vessel nozzles and/or piping system branch connections

Robustness analysis of geodetic networks in the case of correlated observations

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Mevlut Yetkin

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

Correlative SEM SERS for quantitative analysis of dimer nanoparticles.

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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.

Harmonic Analysis Associated with the Generalized Weinstein Operator

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Ahmed Abouelaz

2015-11-01

Full Text Available In this paper we consider a generalized Weinstein operator ∆d,α,n on Rd−1×]0,∞[, which generalizes the Weinstein operator ∆d,α, we define the generalized Weinstein intertwining operator Rα,n which turn out to be transmutation operator between ∆d,α,n and the Laplacian operator ∆d. We build the dual of the generalized Weinstein intertwining operatortRα,n, another hand we prove the formula related Rα,n andtRα,n . We exploit these transmutation operators to develop a new harmonic analysis corresponding to ∆d,α,n.

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

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

2018-06-01

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

Functional Generalized Structured Component Analysis.

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Suk, Hye Won; Hwang, Heungsun

2016-12-01

An extension of Generalized Structured Component Analysis (GSCA), called Functional GSCA, is proposed to analyze functional data that are considered to arise from an underlying smooth curve varying over time or other continua. GSCA has been geared for the analysis of multivariate data. Accordingly, it cannot deal with functional data that often involve different measurement occasions across participants and a large number of measurement occasions that exceed the number of participants. Functional GSCA addresses these issues by integrating GSCA with spline basis function expansions that represent infinite-dimensional curves onto a finite-dimensional space. For parameter estimation, functional GSCA minimizes a penalized least squares criterion by using an alternating penalized least squares estimation algorithm. The usefulness of functional GSCA is illustrated with gait data.

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

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

2018-06-21

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

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

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Delignières, Didier; Marmelat, Vivien

2014-01-01

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

A general computation model based on inverse analysis principle used for rheological analysis of W/O rapeseed and soybean oil emulsions

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Vintila, Iuliana; Gavrus, Adinel

2017-10-01

The present research paper proposes the validation of a rigorous computation model used as a numerical tool to identify rheological behavior of complex emulsions W/O. Considering a three-dimensional description of a general viscoplastic flow it is detailed the thermo-mechanical equations used to identify fluid or soft material's rheological laws starting from global experimental measurements. Analyses are conducted for complex emulsions W/O having generally a Bingham behavior using the shear stress - strain rate dependency based on a power law and using an improved analytical model. Experimental results are investigated in case of rheological behavior for crude and refined rapeseed/soybean oils and four types of corresponding W/O emulsions using different physical-chemical composition. The rheological behavior model was correlated with the thermo-mechanical analysis of a plane-plane rheometer, oil content, chemical composition, particle size and emulsifier's concentration. The parameters of rheological laws describing the industrial oils and the W/O concentrated emulsions behavior were computed from estimated shear stresses using a non-linear regression technique and from experimental torques using the inverse analysis tool designed by A. Gavrus (1992-2000).

The correlation between sports results in swimming and general and special muscle strength

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Wioletta Lubkowska

2017-12-01

Full Text Available Introduction. Swimming as a sport encompasses various styles and distances (from 50 up to 1,500 meters. The correlation between sports results and general/special muscle strength seems unquestionable. Aim. The purpose of this paper is to answer the question related to maintaining the proportion between muscle strength development (which depends mainly on land-based trainings and endurance trainings in water. Material and methods. The study covered 14 leading swimmers from MKP Szczecin who specialized mainly in short and medium distances; they were members of the national senior and junior teams in the 2013/14 training year. The general strength tests were conducted at the beginning and at the end of the winter and summer preparatory periods. The following tests were performed: bench-pressing, pull-ups and bar dips. At the end of the main research period, a thrust test was conducted on land (on a swim bench, as well as a thrust test in the water. Results. All participants demonstrated progress in results between the summer season and the winter season. The range of training loads was higher in the summer due to the length of preparation (by about 100%. The individual progress was, however, very varied. Conclusions. The level of sports progress achieved by individual swimmers was greatly diversified. The relatively high level of general and special strength in the tested swimmers was linked to their need to display these motor skills while swimming. Subjects who showed the greatest progress in the general and special strength trials, displayed the biggest improvement in their swimming performance during the competition season. Swimmers with a fairly high level of strength, but a moderate sports level should analyze and improve their swimming technique. Subjects whose progress in general and special strength tests was the least significant, should try and achieve progress by developing other technical and coordination skills.

Quantum perfect correlations

International Nuclear Information System (INIS)

Ozawa, Masanao

2006-01-01

The notion of perfect correlations between arbitrary observables, or more generally arbitrary POVMs, is introduced in the standard formulation of quantum mechanics, and characterized by several well-established statistical conditions. The transitivity of perfect correlations is proved to generally hold, and applied to a simple articulation for the failure of Hardy's nonlocality proof for maximally entangled states. The notion of perfect correlations between observables and POVMs is used for defining the notion of a precise measurement of a given observable in a given state. A longstanding misconception on the correlation made by the measuring interaction is resolved in the light of the new theory of quantum perfect correlations

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

Institute of Scientific and Technical Information of China (English)

Huang Duru; Huang Zhongning

2006-01-01

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

Multifractality, efficiency analysis of Chinese stock market and its cross-correlation with WTI crude oil price

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Zhuang, Xiaoyang; Wei, Yu; Ma, Feng

2015-07-01

In this paper, the multifractality and efficiency degrees of ten important Chinese sectoral indices are evaluated using the methods of MF-DFA and generalized Hurst exponents. The study also scrutinizes the dynamics of the efficiency of Chinese sectoral stock market by the rolling window approach. The overall empirical findings revealed that all the sectoral indices of Chinese stock market exist different degrees of multifractality. The results of different efficiency measures have agreed on that the 300 Materials index is the least efficient index. However, they have a slight diffidence on the most efficient one. The 300 Information Technology, 300 Telecommunication Services and 300 Health Care indices are comparatively efficient. We also investigate the cross-correlations between the ten sectoral indices and WTI crude oil price based on Multifractal Detrended Cross-correlation Analysis. At last, some relevant discussions and implications of the empirical results are presented.

General aviation air traffic pattern safety analysis

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Parker, L. C.

1973-01-01

A concept is described for evaluating the general aviation mid-air collision hazard in uncontrolled terminal airspace. Three-dimensional traffic pattern measurements were conducted at uncontrolled and controlled airports. Computer programs for data reduction, storage retrieval and statistical analysis have been developed. Initial general aviation air traffic pattern characteristics are presented. These preliminary results indicate that patterns are highly divergent from the expected standard pattern, and that pattern procedures observed can affect the ability of pilots to see and avoid each other.

Statistical analysis of correlated experimental data and neutron cross section evaluation

International Nuclear Information System (INIS)

Badikov, S.A.

1998-01-01

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

MAGMA: generalized gene-set analysis of GWAS data.

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de Leeuw, Christiaan A; Mooij, Joris M; Heskes, Tom; Posthuma, Danielle

2015-04-01

By aggregating data for complex traits in a biologically meaningful way, gene and gene-set analysis constitute a valuable addition to single-marker analysis. However, although various methods for gene and gene-set analysis currently exist, they generally suffer from a number of issues. Statistical power for most methods is strongly affected by linkage disequilibrium between markers, multi-marker associations are often hard to detect, and the reliance on permutation to compute p-values tends to make the analysis computationally very expensive. To address these issues we have developed MAGMA, a novel tool for gene and gene-set analysis. The gene analysis is based on a multiple regression model, to provide better statistical performance. The gene-set analysis is built as a separate layer around the gene analysis for additional flexibility. This gene-set analysis also uses a regression structure to allow generalization to analysis of continuous properties of genes and simultaneous analysis of multiple gene sets and other gene properties. Simulations and an analysis of Crohn's Disease data are used to evaluate the performance of MAGMA and to compare it to a number of other gene and gene-set analysis tools. The results show that MAGMA has significantly more power than other tools for both the gene and the gene-set analysis, identifying more genes and gene sets associated with Crohn's Disease while maintaining a correct type 1 error rate. Moreover, the MAGMA analysis of the Crohn's Disease data was found to be considerably faster as well.

A multimodal stress monitoring system with canonical correlation analysis.

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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.

Cross-cultural differences in the neural correlates of specific and general recognition.

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Paige, Laura E; Ksander, John C; Johndro, Hunter A; Gutchess, Angela H

2017-06-01

Research suggests that culture influences how people perceive the world, which extends to memory specificity, or how much perceptual detail is remembered. The present study investigated cross-cultural differences (Americans vs East Asians) at the time of encoding in the neural correlates of specific versus general memory formation. Participants encoded photos of everyday items in the scanner and 48 h later completed a surprise recognition test. The recognition test consisted of same (i.e., previously seen in scanner), similar (i.e., same name, different features), or new photos (i.e., items not previously seen in scanner). For Americans compared to East Asians, we predicted greater activation in the hippocampus and right fusiform for specific memory at recognition, as these regions were implicated previously in encoding perceptual details. Results revealed that East Asians activated the left fusiform and left hippocampus more than Americans for specific versus general memory. Follow-up analyses ruled out alternative explanations of retrieval difficulty and familiarity for this pattern of cross-cultural differences at encoding. Results overall suggest that culture should be considered as another individual difference that affects memory specificity and modulates neural regions underlying these processes. Copyright © 2017 Elsevier Ltd. All rights reserved.

The correlation of social support with mental health: A meta-analysis.

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Harandi, Tayebeh Fasihi; Taghinasab, Maryam Mohammad; Nayeri, Tayebeh Dehghan

2017-09-01

Social support is an important factor that can affect mental health. In recent decades, many studies have been done on the impact of social support on mental health. The purpose of the present study is to investigate the effect size of the relationship between social support and mental health in studies in Iran. This meta-analysis was carried out in studies that were performed from 1996 through 2015. Databases included SID and Magiran, the comprehensive portal of human sciences, Noor specialized magazine databases, IRANDOC, Proquest, PubMed, Scopus, ERIC, Iranmedex and Google Scholar. The keywords used to search these websites included "mental health or general health," and "Iran" and "social support." In total, 64 studies had inclusion criteria meta-analysis. In order to collect data used from a meta-analysis worksheet that was made by the researcher and for data analysis software, CMA-2 was used. The mean of effect size of the 64 studies in the fixed-effect model and random-effect model was obtained respectively as 0.356 and 0.330, which indicated the moderate effect size of social support on mental health. The studies did not have publication bias, and enjoyed a heterogeneous effect size. The target population and social support questionnaire were moderator variables, but sex, sampling method, and mental health questionnaire were not moderator variables. Regarding relatively high effect size of the correlation between social support and mental health, it is necessary to predispose higher social support, especially for women, the elderly, patients, workers, and students.

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

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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.

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

International Nuclear Information System (INIS)

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

2013-01-01

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

General Nature of Multicollinearity in Multiple Regression Analysis.

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Liu, Richard

1981-01-01

Discusses multiple regression, a very popular statistical technique in the field of education. One of the basic assumptions in regression analysis requires that independent variables in the equation should not be highly correlated. The problem of multicollinearity and some of the solutions to it are discussed. (Author)

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

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.

Validation of general job satisfaction in the Korean Labor and Income Panel Study.

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Park, Shin Goo; Hwang, Sang Hee

2017-01-01

The purpose of this study is to assess the validity and reliability of general job satisfaction (JS) in the Korean Labor and Income Panel Study (KLIPS). We used the data from the 17th wave (2014) of the nationwide KLIPS, which selected a representative panel sample of Korean households and individuals aged 15 or older residing in urban areas. We included in this study 7679 employed subjects (4529 males and 3150 females). The general JS instrument consisted of five items rated on a scale from 1 (strongly disagree) to 5 (strongly agree). The general JS reliability was assessed using the corrected item-total correlation and Cronbach's alpha coefficient. The validity of general JS was assessed using confirmatory factor analysis (CFA) and Pearson's correlation. The corrected item-total correlations ranged from 0.736 to 0.837. Therefore, no items were removed. Cronbach's alpha for general JS was 0.925, indicating excellent internal consistency. The CFA of the general JS model showed a good fit. Pearson's correlation coefficients for convergent validity showed moderate or strong correlations. The results obtained in our study confirm the validity and reliability of general JS.

The fading affect bias shows positive outcomes at the general but not the individual level of analysis in the context of social media.

Science.gov (United States)

Gibbons, Jeffrey A; Horowitz, Kyle A; Dunlap, Spencer M

2017-08-01

Unpleasant affect fades faster than pleasant affect (e.g., Walker, Vogl, & Thompson, 1997); this effect is referred to as the Fading Affect Bias (FAB; Walker, Skowronski, Gibbons, Vogl, & Thompson, 2003a). Research shows that the FAB is consistently related to positive/healthy outcomes at a general but not at a specific level of analysis based on event types and individual differences (e.g., Gibbons et al., 2013). Based on the positive outcomes for FAB and negative outcomes for social media (Bolton et al., 2013; Huang, 2010), the current study examined FAB in the context of social media events along with related individual differences. General positive outcomes were shown in the form of robust FAB effects across social media and non-social media events, a larger FAB for non-social media events than for social media events, negative correlations of FAB with depression, anxiety, and stress as well as a positive correlation of FAB with self-esteem. However, the lack of a negative correlation between FAB and anxiety for social media events in a 3-way interaction did not show positive outcomes at a specific level of analysis. Rehearsal ratings mediated the 3-way interaction. Implications are discussed. Copyright © 2017 Elsevier Inc. All rights reserved.

Functional data analysis of generalized regression quantiles

KAUST Repository

Guo, Mengmeng; Zhou, Lan; Huang, Jianhua Z.; Hä rdle, Wolfgang Karl

2013-01-01

Generalized regression quantiles, including the conditional quantiles and expectiles as special cases, are useful alternatives to the conditional means for characterizing a conditional distribution, especially when the interest lies in the tails. We develop a functional data analysis approach to jointly estimate a family of generalized regression quantiles. Our approach assumes that the generalized regression quantiles share some common features that can be summarized by a small number of principal component functions. The principal component functions are modeled as splines and are estimated by minimizing a penalized asymmetric loss measure. An iterative least asymmetrically weighted squares algorithm is developed for computation. While separate estimation of individual generalized regression quantiles usually suffers from large variability due to lack of sufficient data, by borrowing strength across data sets, our joint estimation approach significantly improves the estimation efficiency, which is demonstrated in a simulation study. The proposed method is applied to data from 159 weather stations in China to obtain the generalized quantile curves of the volatility of the temperature at these stations. © 2013 Springer Science+Business Media New York.

Functional data analysis of generalized regression quantiles

KAUST Repository

Guo, Mengmeng

2013-11-05

Generalized regression quantiles, including the conditional quantiles and expectiles as special cases, are useful alternatives to the conditional means for characterizing a conditional distribution, especially when the interest lies in the tails. We develop a functional data analysis approach to jointly estimate a family of generalized regression quantiles. Our approach assumes that the generalized regression quantiles share some common features that can be summarized by a small number of principal component functions. The principal component functions are modeled as splines and are estimated by minimizing a penalized asymmetric loss measure. An iterative least asymmetrically weighted squares algorithm is developed for computation. While separate estimation of individual generalized regression quantiles usually suffers from large variability due to lack of sufficient data, by borrowing strength across data sets, our joint estimation approach significantly improves the estimation efficiency, which is demonstrated in a simulation study. The proposed method is applied to data from 159 weather stations in China to obtain the generalized quantile curves of the volatility of the temperature at these stations. © 2013 Springer Science+Business Media New York.

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

International Nuclear Information System (INIS)

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

1995-01-01

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

Generalized phase diagram for the rare-earth elements: Calculations and correlations of bulk properties

International Nuclear Information System (INIS)

Johansson, B.; Rosengren, A.

1975-01-01

A ''generalized'' phase diagram is constructed empirically for the lanthanides. This diagram makes it possible, not only in one picture, to assemble a lot of information but also to predict phase transitions not yet experimentally accessible. Further, it clearly illustrates the close relation between the members of the lanthanide group. To account for some of its features, the pseudopotential method is applied. The trend in crystal structure through the lanthanide series can thereby be qualitatively accounted for, as can the trend in crystal structure for an individual element, when compressed. A scaling procedure makes it possible to extend the treatment to elements neighboring the lanthanides in the Periodic Table. In total 25 elements are considered. An atomic parameter f (relatable to the pseudopotential) is introduced, by means of which different phase transitions, both for an individual rare-earth element and intra-rare-earth alloys, can be correlated to certain critical values of this parameter. A nonmagnetic rare-earth series (Sc, Lu, Y, La, and Ac) is introduced and the occurrence of superconductivity is discussed with special emphasis on the pressure dependence of the transition temperature. This temperature can be correlated to the above-mentioned parameter f, both for intra-rare-earth alloys and pure elements at different pressures. The correlation implies that actinium is a superconductor with a critical temperature which could be as high as (11--12) degree K

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

Science.gov (United States)

Ruan, Qingsong; Yang, Bingchan

2017-10-01

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

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.)

Reconstruction of the 3D representative volume element from the generalized two-point correlation function

International Nuclear Information System (INIS)

Staraselski, Y; Brahme, A; Inal, K; Mishra, R K

2015-01-01

This paper presents the first application of three-dimensional (3D) cross-correlation microstructure reconstruction implemented for a representative volume element (RVE) to facilitate the microstructure engineering of materials. This has been accomplished by developing a new methodology for reconstructing 3D microstructure using experimental two-dimensional electron backscatter diffraction data. The proposed methodology is based on the analytical representation of the generalized form of the two-point correlation function—the distance-disorientation function (DDF). Microstructure reconstruction is accomplished by extending the simulated annealing techniques to perform three term reconstruction with a minimization of the DDF. The new 3D microstructure reconstruction algorithm is employed to determine the 3D RVE containing all of the relevant microstructure information for accurately computing the mechanical response of solids, especially when local microstructural variations influence the global response of the material as in the case of fracture initiation. (paper)

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

DEFF Research Database (Denmark)

Nielsen, Allan Aasbjerg

2002-01-01

This paper describes two- and multiset canonical correlations analysis (CCA) for data fusion, multi-source, multiset or multi-temporal exploratory data analysis. These techniques transform multivariate multiset data into new orthogonal variables called canonical variates (CVs) which when applied...... in remote sensing exhibit ever decreasing similarity (as expressed by correlation measures) over sets consisting of 1) spectral variables at fixed points in time (R-mode analysis), or 2) temporal variables with fixed wavelengths (T-mode analysis). The CVs are invariant to linear and affine transformations...... of the original variables within sets which means, for example, that the R-mode CVs are insensitive to changes over time in offset and gain in a measuring device. In a case study CVs are calculated from Landsat TM data with six spectral bands over six consecutive years. Both R- and T-mode CVs clearly exhibit...

Windowed Multitaper Correlation Analysis of Multimodal Brain Monitoring Parameters

Directory of Open Access Journals (Sweden)

Rupert Faltermeier

2015-01-01

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

Windowed multitaper correlation analysis of multimodal brain monitoring parameters.

Science.gov (United States)

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

2015-01-01

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

Visualization of synchronization of the uterine contraction signals: running cross-correlation and wavelet running cross-correlation methods.

Science.gov (United States)

Oczeretko, Edward; Swiatecka, Jolanta; Kitlas, Agnieszka; Laudanski, Tadeusz; Pierzynski, Piotr

2006-01-01

In physiological research, we often study multivariate data sets, containing two or more simultaneously recorded time series. The aim of this paper is to present the cross-correlation and the wavelet cross-correlation methods to assess synchronization between contractions in different topographic regions of the uterus. From a medical point of view, it is important to identify time delays between contractions, which may be of potential diagnostic significance in various pathologies. The cross-correlation was computed in a moving window with a width corresponding to approximately two or three contractions. As a result, the running cross-correlation function was obtained. The propagation% parameter assessed from this function allows quantitative description of synchronization in bivariate time series. In general, the uterine contraction signals are very complicated. Wavelet transforms provide insight into the structure of the time series at various frequencies (scales). To show the changes of the propagation% parameter along scales, a wavelet running cross-correlation was used. At first, the continuous wavelet transforms as the uterine contraction signals were received and afterwards, a running cross-correlation analysis was conducted for each pair of transformed time series. The findings show that running functions are very useful in the analysis of uterine contractions.

System Reliability Analysis Considering Correlation of Performances

Energy Technology Data Exchange (ETDEWEB)

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

2017-04-15

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

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.

General theory for calculating disorder-averaged Green's function correlators within the coherent potential approximation

Science.gov (United States)

Zhou, Chenyi; Guo, Hong

2017-01-01

We report a diagrammatic method to solve the general problem of calculating configurationally averaged Green's function correlators that appear in quantum transport theory for nanostructures containing disorder. The theory treats both equilibrium and nonequilibrium quantum statistics on an equal footing. Since random impurity scattering is a problem that cannot be solved exactly in a perturbative approach, we combine our diagrammatic method with the coherent potential approximation (CPA) so that a reliable closed-form solution can be obtained. Our theory not only ensures the internal consistency of the diagrams derived at different levels of the correlators but also satisfies a set of Ward-like identities that corroborate the conserving consistency of transport calculations within the formalism. The theory is applied to calculate the quantum transport properties such as average ac conductance and transmission moments of a disordered tight-binding model, and results are numerically verified to high precision by comparing to the exact solutions obtained from enumerating all possible disorder configurations. Our formalism can be employed to predict transport properties of a wide variety of physical systems where disorder scattering is important.

Systematic review and meta-analysis of dropout rates in individual psychotherapy for generalized anxiety disorder.

Science.gov (United States)

Gersh, Elon; Hallford, David J; Rice, Simon M; Kazantzis, Nikolaos; Gersh, Hannah; Gersh, Benji; McCarty, Carolyn A

2017-12-01

Despite being a relatively prevalent and debilitating disorder, Generalized Anxiety Disorder (GAD) is the second least studied anxiety disorder and among the most difficult to treat. Dropout from psychotherapy is concerning as it is associated with poorer outcomes, leads to service inefficiencies and can disproportionately affect disadvantaged populations. No study to date has calculated a weighted mean dropout rate for GAD and explored associated correlates. A systematic review was conducted using PsycINFO, Medline and Embase databases, identifying studies investigating individual psychotherapies for adults with GAD. Forty-five studies, involving 2224 participants, were identified for meta-analysis. The weighted mean dropout rate was 16.99% (95% confidence interval 14.42%-19.91%). The Q-statistic indicated significant heterogeneity among studies. Moderator analysis and meta-regressions indicated no statistically significant effect of client age, sex, symptom severity, comorbidity, treatment type, study type (randomized trial or not), study quality, number of sessions or therapist experience. In research investigating psychotherapy for GAD, approximately one in six clients can be expected to drop out of treatment. Dropout rate was not significantly moderated by the client, therapist or treatment variables investigated. Future research should specify the definition of dropout, reasons for dropout and associated correlates to assist the field's progression. Copyright © 2017 Elsevier Ltd. All rights reserved.

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.

Quantitative analysis of volatile organic compounds using ion mobility spectra and cascade correlation neural networks

Science.gov (United States)

Harrington, Peter DEB.; Zheng, Peng

1995-01-01

Ion Mobility Spectrometry (IMS) is a powerful technique for trace organic analysis in the gas phase. Quantitative measurements are difficult, because IMS has a limited linear range. Factors that may affect the instrument response are pressure, temperature, and humidity. Nonlinear calibration methods, such as neural networks, may be ideally suited for IMS. Neural networks have the capability of modeling complex systems. Many neural networks suffer from long training times and overfitting. Cascade correlation neural networks train at very fast rates. They also build their own topology, that is a number of layers and number of units in each layer. By controlling the decay parameter in training neural networks, reproducible and general models may be obtained.

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.

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

Science.gov (United States)

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

2011-04-01

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

Two-particle correlations in reactor systems

International Nuclear Information System (INIS)

Mika, J.

1975-01-01

A study is made of the relationship between the general transport equation and the correlation matrix equation, in reactor systems. How some of the results obtained so far for the generalized transport equation can be simply translated to the correlation matrix equation is indicated. In particular, the semigroup formalism developed for the generalized transport equation is used to prove the existence and uniqueness of solution to the correlation matrix equation. The generalized transport equation is rigorously formulated in a Hilbert space of square integrable functions. The semigroup formalism for that equation is introduced and the solution expressed in terms of the semigroup. The correlation matrix equation is then formulated. It is shown how the semigroup formalism developed for the generalized transport equation can be applied to the correlation matrix equation and used to prove the existence theorem. Some applications of the semigroup formalism are then indicated. Firstly, the simple one point model obtained from the general equations is introduced. Secondly, the well known phenomenon of the linear increase with time of the components of the correlation matrix in a critical reactor is analyzed. Finally, it is shown how the singular perturbation method developed recently for the generalized transport equation can be applied to the correlation matrix equation. (U.K.)

Comparative analysis of general characteristics of ischemic stroke of BAD and non-BAD CISS subtypes.

Science.gov (United States)

Mei, Bin; Liu, Guang-zhi; Yang, Yang; Liu, Yu-min; Cao, Jiang-hui; Zhang, Jun-jian

2015-12-01

Based on the recently proposed Chinese ischemic stroke subclassification (CISS) system, intracranial branch atheromatous disease (BAD) is divided into large artery atherosclerosis (LAA) and penetrating artery disease (PAD). In the current retrospective analysis, we compared the general characteristics of BAD-LAA with BAD-PAD, BAD-LAA with non-BAD-LAA and BAD-PAD with non-BAD-PAD. The study included a total of 80 cases, including 45 cases of BAD and 35 cases of non-BAD. Subjects were classified using CISS system: BAD-LAA, BAD-PAD, non-BAD-LAA and non-BAD-PAD. In addition to analysis of general characteristics, the correlation between the factors and the two subtypes of BAD was evaluated. The number of cases included in the analysis was: 32 cases of BAD-LAA, 13 cases of BAD-PAD, 21 cases of non-BAD-LAA, and 14 cases of non-BAD-PAD. Diabetes mellitus affected more non-BAD-LAA patients than BAD-LAA patients (P=0.035). In comparison with non-BAD-PAD, patients with BAD-PAD were younger (P=0.040), had higher initial NIHSS score (PBAD, the PAD subtype was associated with smoking (OR=0.043; P=0.011), higher low-density lipoprotein (OR=5.339; P=0.029), ischemic heart disease (OR=9.383; P=0.047) and diabetes mellitus (OR=12.59; P=0.020). It was concluded that large artery atherosclerosis was the primary mechanism of BAD. The general characteristics showed no significant differences between the CISS subtypes of LAA and PAD within BAD, as well as between the BAD and non-BAD within LAA subtype. Several differences between PAD subtypes of BAD and non-BAD were revealed.

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.

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.

Generalized structured component analysis a component-based approach to structural equation modeling

CERN Document Server

Hwang, Heungsun

2014-01-01

Winner of the 2015 Sugiyama Meiko Award (Publication Award) of the Behaviormetric Society of Japan Developed by the authors, generalized structured component analysis is an alternative to two longstanding approaches to structural equation modeling: covariance structure analysis and partial least squares path modeling. Generalized structured component analysis allows researchers to evaluate the adequacy of a model as a whole, compare a model to alternative specifications, and conduct complex analyses in a straightforward manner. Generalized Structured Component Analysis: A Component-Based Approach to Structural Equation Modeling provides a detailed account of this novel statistical methodology and its various extensions. The authors present the theoretical underpinnings of generalized structured component analysis and demonstrate how it can be applied to various empirical examples. The book enables quantitative methodologists, applied researchers, and practitioners to grasp the basic concepts behind this new a...

Confinement and correlation effects in the Xe-C{sub 60} generalized oscillator strengths

Energy Technology Data Exchange (ETDEWEB)

Amusia, M. Ya. [Racah Institute of Physics, Hebrew University, 91904 Jerusalem (Israel); A. F. Ioffe Physical-Technical Institute, 194021 St. Petersburg (Russian Federation); Chernysheva, L. V. [A. F. Ioffe Physical-Technical Institute, 194021 St. Petersburg (Russian Federation); Dolmatov, V. K. [Department of Physics and Earth Science, University of North Alabama, Florence, Alabama 35632 (United States)

2011-12-15

The impact of both confinement and electron correlation on generalized oscillator strengths (GOS's) of endohedral atoms, A-C{sub 60}, is theoretically studied choosing the Xe-C{sub 60} 4d, 5s, and 5p fast electron impact ionization as the case study. Calculations are performed in the transferred to the atom energy region beyond the 4d threshold, {omega}=75-175 eV. The calculation methodology combines the plane-wave Born approximation, Hartree-Fock approximation, and random-phase approximation with exchange in the presence of the C{sub 60} confinement. The confinement is modeled by a spherical {delta}-function-like potential as well as by a square well potential to evaluate the effect of the finite thickness of the C{sub 60} cage on the Xe-C{sub 60} GOS's. Dramatic distortion of the 4d, 5p, and 5s GOS's by the confinement is demonstrated, compared to the free atom. Considerable contributions of multipolar transitions beyond dipole transitions in the calculated GOS's are revealed, in some instances. The vitality of accounting for electron correlation in calculation of the Xe-C{sub 60} 5s and 5p GOS's is shown.

Renormalization of correlations in a quasiperiodically forced two-level system: quadratic irrationals

International Nuclear Information System (INIS)

Mestel, B D; Osbaldestin, A H

2004-01-01

Generalizing from the case of golden mean frequency to a wider class of quadratic irrationals, we extend our renormalization analysis of the self-similarity of correlation functions in a quasiperiodically forced two-level system. We give a description of all piecewise-constant periodic orbits of an additive functional recurrence generalizing that present in the golden mean case. We establish a criterion for periodic orbits to be globally bounded, and also calculate the asymptotic height of the main peaks in the correlation function

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...

Comparative analysis of heat transfer correlations for forced convection boiling

International Nuclear Information System (INIS)

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

1978-01-01

A critical survey was conducted of the most relevant correlations of boiling heat transfer in forced convection flow. Most of the investigations carried out on partial nucleate boiling and fully developed nucleate boiling have led to the formulation of correlations that are not able to cover a wide range of operating conditions, due to the empirical approach of the problem. A comparative analysis is therefore required in order to delineate the relative accuracy of the proposed correlations, on the basis of the experimental data presently available. The survey performed allows the evaluation of the accuracy of the different calculating procedure; the results obtained, moreover, indicate the most reliable heat transfer correlations for the different operating conditions investigated. This survey was developed for five pressure range (up to 180bar) and for both saturation and subcooled boiling condition

s-core network decomposition: A generalization of k-core analysis to weighted networks

Science.gov (United States)

Eidsaa, Marius; Almaas, Eivind

2013-12-01

A broad range of systems spanning biology, technology, and social phenomena may be represented and analyzed as complex networks. Recent studies of such networks using k-core decomposition have uncovered groups of nodes that play important roles. Here, we present s-core analysis, a generalization of k-core (or k-shell) analysis to complex networks where the links have different strengths or weights. We demonstrate the s-core decomposition approach on two random networks (ER and configuration model with scale-free degree distribution) where the link weights are (i) random, (ii) correlated, and (iii) anticorrelated with the node degrees. Finally, we apply the s-core decomposition approach to the protein-interaction network of the yeast Saccharomyces cerevisiae in the context of two gene-expression experiments: oxidative stress in response to cumene hydroperoxide (CHP), and fermentation stress response (FSR). We find that the innermost s-cores are (i) different from innermost k-cores, (ii) different for the two stress conditions CHP and FSR, and (iii) enriched with proteins whose biological functions give insight into how yeast manages these specific stresses.

A sensory analysis of butter cookies: An application of generalized procrustes analysis

DEFF Research Database (Denmark)

Juhl, Hans Jørn

1994-01-01

Executive Summary: 1. A sensory analysis is one of the first steps in product development in the food industry. A thorough analysis of the results from such an analysis may give important input to the development process. 2. A sensory analysis on butter cookies is conducted in order to evaluate...... if some butter may be replaced by vegetable fat without a significant change in the sensory profile. The conclusion is that the replacement is possible without a considerable change in the sensory profile. 3. Generalized Procrustes Analysis is used to analyze the results. It is a relatively new technique...

Interactive general-purpose function minimization for the analysis of neutron scattering data

International Nuclear Information System (INIS)

Abel, W.

1981-12-01

An on-line graphic display facility has been employed mainly for the peak analysis of time-of-flight spectra measured by inelastic scattering of thermal neutrons. But it is useful also for the analysis of spectra measured with triple axis spectrometers and of diffraction patterns. The spectral lines may be fitted by the following analytical shape functions: (i) a Gaussian, (ii) a Lorentzian, or (iii) a convolution of a Lorentzian with a Gaussian, plus a background continuum. Data reduction or correction may be invoked optionally. For more general applications in analysing of numerical data there is also the possibility to define the analytical shape functions by the user. Three different minimization methods are available which may be used alone or in combination. The parameters of the shape functions may be kept fixed or variable during the minimization steps. The width of variation may be restricted. Global correlation coefficients, parameter errors and the chi 2 are displayed to inform the user about the quality of the fit. A detailed description of the program operations is given. The programs are written in FORTRAN IV and use an IBM/2250-1 graphic display unit. (orig.) [de

The correlation of social support with mental health: A meta-analysis

Science.gov (United States)

Harandi, Tayebeh Fasihi; Taghinasab, Maryam Mohammad; Nayeri, Tayebeh Dehghan

2017-01-01

Background and aim Social support is an important factor that can affect mental health. In recent decades, many studies have been done on the impact of social support on mental health. The purpose of the present study is to investigate the effect size of the relationship between social support and mental health in studies in Iran. Methods This meta-analysis was carried out in studies that were performed from 1996 through 2015. Databases included SID and Magiran, the comprehensive portal of human sciences, Noor specialized magazine databases, IRANDOC, Proquest, PubMed, Scopus, ERIC, Iranmedex and Google Scholar. The keywords used to search these websites included “mental health or general health,” and “Iran” and “social support.” In total, 64 studies had inclusion criteria meta-analysis. In order to collect data used from a meta-analysis worksheet that was made by the researcher and for data analysis software, CMA-2 was used. Results The mean of effect size of the 64 studies in the fixed-effect model and random-effect model was obtained respectively as 0.356 and 0.330, which indicated the moderate effect size of social support on mental health. The studies did not have publication bias, and enjoyed a heterogeneous effect size. The target population and social support questionnaire were moderator variables, but sex, sampling method, and mental health questionnaire were not moderator variables. Conclusion Regarding relatively high effect size of the correlation between social support and mental health, it is necessary to predispose higher social support, especially for women, the elderly, patients, workers, and students. PMID:29038699

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.

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®

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

International Nuclear Information System (INIS)

Kim, Ho Kee

1998-02-01

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

The Generalization of Mutual Information as the Information between a Set of Variables: The Information Correlation Function Hierarchy and the Information Structure of Multi-Agent Systems

Science.gov (United States)

Wolf, David R.

2004-01-01

The topic of this paper is a hierarchy of information-like functions, here named the information correlation functions, where each function of the hierarchy may be thought of as the information between the variables it depends upon. The information correlation functions are particularly suited to the description of the emergence of complex behaviors due to many- body or many-agent processes. They are particularly well suited to the quantification of the decomposition of the information carried among a set of variables or agents, and its subsets. In more graphical language, they provide the information theoretic basis for understanding the synergistic and non-synergistic components of a system, and as such should serve as a forceful toolkit for the analysis of the complexity structure of complex many agent systems. The information correlation functions are the natural generalization to an arbitrary number of sets of variables of the sequence starting with the entropy function (one set of variables) and the mutual information function (two sets). We start by describing the traditional measures of information (entropy) and mutual information.

Measurement of spatial correlation functions using image processing techniques

International Nuclear Information System (INIS)

Berryman, J.G.

1985-01-01

A procedure for using digital image processing techniques to measure the spatial correlation functions of composite heterogeneous materials is presented. Methods for eliminating undesirable biases and warping in digitized photographs are discussed. Fourier transform methods and array processor techniques for calculating the spatial correlation functions are treated. By introducing a minimal set of lattice-commensurate triangles, a method of sorting and storing the values of three-point correlation functions in a compact one-dimensional array is developed. Examples are presented at each stage of the analysis using synthetic photographs of cross sections of a model random material (the penetrable sphere model) for which the analytical form of the spatial correlations functions is known. Although results depend somewhat on magnification and on relative volume fraction, it is found that photographs digitized with 512 x 512 pixels generally have sufficiently good statistics for most practical purposes. To illustrate the use of the correlation functions, bounds on conductivity for the penetrable sphere model are calculated with a general numerical scheme developed for treating the singular three-dimensional integrals which must be evaluated

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.

A General Approach to Causal Mediation Analysis

Science.gov (United States)

Imai, Kosuke; Keele, Luke; Tingley, Dustin

2010-01-01

Traditionally in the social sciences, causal mediation analysis has been formulated, understood, and implemented within the framework of linear structural equation models. We argue and demonstrate that this is problematic for 3 reasons: the lack of a general definition of causal mediation effects independent of a particular statistical model, the…

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.

Colombeau's generalized functions and non-standard analysis

International Nuclear Information System (INIS)

Todorov, T.D.

1987-10-01

Using some methods of the Non-Standard Analysis we modify one of Colombeau's classes of generalized functions. As a result we define a class ε-circumflex of the so-called meta-functions which possesses all good properties of Colombeau's generalized functions, i.e. (i) ε-circumflex is an associative and commutative algebra over the system of the so-called complex meta-numbers C-circumflex; (ii) Every meta-function has partial derivatives of any order (which are meta-functions again); (iii) Every meta-function is integrable on any compact set of R n and the integral is a number from C-circumflex; (iv) ε-circumflex contains all tempered distributions S', i.e. S' is contained in ε' isomorphically with respect to all linear operations (including the differentiation). Thus, within the class ε-circumflex the problem of multiplication of the tempered distributions is satisfactorily solved (every two distributions in S' have a well-defined product in ε-circumflex). The crucial point is that C-circumflex is a field in contrast to the system of Colombeau's generalized numbers C-bar which is a ring only (C-bar is the counterpart of C-circumflex in Colombeau's theory). In this way we simplify and improve slightly the properties of the integral and notion of ''values of the meta-functions'' as well as the properties of the whole class ε-circumflex itself if compared with the original Colombeau theory. And, what is maybe more important, we clarify the connection between the Non-Standard Analysis and Colombeau's theory of new generalized functions in the framework of which the problem of multiplication of distributions was recently solved. (author). 14 refs

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.

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

Science.gov (United States)

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

2017-01-01

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

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

Directory of Open Access Journals (Sweden)

Martin A. Proescholdt

2017-01-01

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

Nonparametric correlation models for portfolio allocation

DEFF Research Database (Denmark)

Aslanidis, Nektarios; Casas, Isabel

2013-01-01

This article proposes time-varying nonparametric and semiparametric estimators of the conditional cross-correlation matrix in the context of portfolio allocation. Simulations results show that the nonparametric and semiparametric models are best in DGPs with substantial variability or structural ...... currencies. Results show the nonparametric model generally dominates the others when evaluating in-sample. However, the semiparametric model is best for out-of-sample analysis....

A comprehensive analysis of molecule-intrinsic quasi-atomic, bonding, and correlating orbitals. I. Hartree-Fock wave functions

International Nuclear Information System (INIS)

West, Aaron C.; Schmidt, Michael W.; Gordon, Mark S.; Ruedenberg, Klaus

2013-01-01

Through a basis-set-independent web of localizing orbital-transformations, the electronic wave function of a molecule is expressed in terms of a set of orbitals that reveal the atomic structure and the bonding pattern of a molecule. The analysis is based on resolving the valence orbital space in terms of an internal space, which has minimal basis set dimensions, and an external space. In the internal space, oriented quasi-atomic orbitals and split-localized molecular orbitals are determined by new, fast localization methods. The density matrix between the oriented quasi-atomic orbitals as well as the locations of the split-localized orbitals exhibit atomic populations and inter-atomic bonding patterns. A correlation-adapted quasi-atomic basis is determined in the external orbital space. The general formulations are specified in detail for Hartree-Fock wave functions. Applications to specific molecules exemplify the general scheme

Analytical X-ray line profile analysis based upon correlated dislocations

International Nuclear Information System (INIS)

Rao, S.; Houska, C.R.

1988-01-01

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

Biostatistics Series Module 6: Correlation and Linear Regression.

Science.gov (United States)

Hazra, Avijit; Gogtay, Nithya

2016-01-01

Correlation and linear regression are the most commonly used techniques for quantifying the association between two numeric variables. Correlation quantifies the strength of the linear relationship between paired variables, expressing this as a correlation coefficient. If both variables x and y are normally distributed, we calculate Pearson's correlation coefficient ( r ). If normality assumption is not met for one or both variables in a correlation analysis, a rank correlation coefficient, such as Spearman's rho (ρ) may be calculated. A hypothesis test of correlation tests whether the linear relationship between the two variables holds in the underlying population, in which case it returns a P correlation coefficient can also be calculated for an idea of the correlation in the population. The value r 2 denotes the proportion of the variability of the dependent variable y that can be attributed to its linear relation with the independent variable x and is called the coefficient of determination. Linear regression is a technique that attempts to link two correlated variables x and y in the form of a mathematical equation ( y = a + bx ), such that given the value of one variable the other may be predicted. In general, the method of least squares is applied to obtain the equation of the regression line. Correlation and linear regression analysis are based on certain assumptions pertaining to the data sets. If these assumptions are not met, misleading conclusions may be drawn. The first assumption is that of linear relationship between the two variables. A scatter plot is essential before embarking on any correlation-regression analysis to show that this is indeed the case. Outliers or clustering within data sets can distort the correlation coefficient value. Finally, it is vital to remember that though strong correlation can be a pointer toward causation, the two are not synonymous.

Convergence of third order correlation energy in atoms and molecules.

Science.gov (United States)

Kahn, Kalju; Granovsky, Alex A; Noga, Jozef

2007-01-30

We have investigated the convergence of third order correlation energy within the hierarchies of correlation consistent basis sets for helium, neon, and water, and for three stationary points of hydrogen peroxide. This analysis confirms that singlet pair energies converge much slower than triplet pair energies. In addition, singlet pair energies with (aug)-cc-pVDZ and (aug)-cc-pVTZ basis sets do not follow a converging trend and energies with three basis sets larger than aug-cc-pVTZ are generally required for reliable extrapolations of third order correlation energies, making so the explicitly correlated R12 calculations preferable.

Algebraic structures in generalized Clifford analysis and applications to boundary value problems

Directory of Open Access Journals (Sweden)

José Játem

2015-12-01

Full Text Available The present article has a threefold purpose: First it is a survey of the algebraic structures of generalized Clifford-type algebras and shows the main results of the corresponding Clifford-type analysis and its application to boundary value problems known so far. Second it is aimed to implement algorithms to provide the fast and accurate computation of boundary value problems for inhomogeneous equations in the framework of the generalized Clifford analysis. Finally it is also aimed to encourage the development of a generalized discrete Clifford analysis.

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

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

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

Using general-purpose compression algorithms for music analysis

DEFF Research Database (Denmark)

Louboutin, Corentin; Meredith, David

2016-01-01

General-purpose compression algorithms encode files as dictionaries of substrings with the positions of these strings’ occurrences. We hypothesized that such algorithms could be used for pattern discovery in music. We compared LZ77, LZ78, Burrows–Wheeler and COSIATEC on classifying folk song...... in the input data, COSIATEC outperformed LZ77 with a mean F1 score of 0.123, compared with 0.053 for LZ77. However, when the music was processed a voice at a time, the F1 score for LZ77 more than doubled to 0.124. We also discovered a significant correlation between compression factor and F1 score for all...

Relationship between nurses’ spiritual intelligence with hardiness and general health

Directory of Open Access Journals (Sweden)

Fatemeh Akbarizadeh

2012-01-01

Full Text Available Background: Nursing is one of the stressful jobs that affect nurse's general health. The aim of this study was assessment relationship between Spiritual intelligence, Hardiness and General health among nurses in the hospital of Bushehr in 1388. Methods: Cross- sectional study designed and 125 nurses who have been working in different wards of the hospital enrolled in the study. Data was collected using Spiritual intelligence, Hardiness, General health and characteristics demographic questionnaires. Correlation, t-test, ANOVA, Tukey and regression analysis was applied using SPSS-16 soft ware. Results: The results showed there was significant relationship between spiritual intelligence and hardiness (P<0.005, spiritual intelligence and General health (P<0.005, hardiness and General health (P<0.001. Among the demographic characteristics including age, gender, working section, marital status, job experiences, and education only working section showed significantly correlated with patience (P<0.005. Conclusion: Improvement of spiritual intelligence and reinforcement of hardiness could help to increase the general health of nurses.

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.

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.

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

Science.gov (United States)

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

2017-05-01

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

Trends and Correlates of Consenting to Provide Social Security Numbers: Longitudinal Findings from the General Social Survey (1993-2010)

Science.gov (United States)

Kim, Jibum; Shin, Hee-Choon; Rosen, Zohn; Kang, Jeong-han; Dykema, Jennifer; Muennig, Peter

2015-01-01

Privacy and confidentiality are often of great concern to respondents answering sensitive questions posed by interviewers. Using the 1993-2010 General Social Survey, we examined trends in the provision of social security numbers (SSNs) and correlates of those responses. Results indicate that the rate of SSN provision has declined over the past…

FEM correlation and shock analysis of a VNC MEMS mirror segment

Science.gov (United States)

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

2014-08-01

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

A meta-analysis of the relationship between general mental ability and nontask performance.

Science.gov (United States)

Gonzalez-Mulé, Erik; Mount, Michael K; Oh, In-Sue

2014-11-01

Although one of the most well-established research findings in industrial-organizational psychology is that general mental ability (GMA) is a strong and generalizable predictor of job performance, this meta-analytically derived conclusion is based largely on measures of task or overall performance. The primary purpose of this study is to address a void in the research literature by conducting a meta-analysis to determine the direction and magnitude of the correlation of GMA with 2 dimensions of nontask performance: counterproductive work behaviors (CWB) and organizational citizenship behaviors (OCB). Overall, the results show that the true-score correlation between GMA and CWB is essentially 0 (-.02, k = 35), although rating source of CWB moderates this relationship. The true-score correlation between GMA and OCB is positive but modest in magnitude (.23, k = 43). The 2nd purpose of this study is to conduct meta-analytic relative weight analyses to determine the relative importance of GMA and the five-factor model (FFM) of personality traits in predicting nontask and task performance criteria. Results indicate that, collectively, the FFM traits are substantially more important for CWB than GMA, that the FFM traits are roughly equal in importance to GMA for OCB, and that GMA is substantially more important for task and overall job performance than the FFM traits. Implications of these findings for the development of optimal selection systems and the development of comprehensive theories of job performance are discussed along with study limitation and future research directions. (PsycINFO Database Record (c) 2014 APA, all rights reserved).

Simple and Multivariate Relationships Between Spiritual Intelligence with General Health and Happiness.

Science.gov (United States)

Amirian, Mohammad-Elyas; Fazilat-Pour, Masoud

2016-08-01

The present study examined simple and multivariate relationships of spiritual intelligence with general health and happiness. The employed method was descriptive and correlational. King's Spiritual Quotient scales, GHQ-28 and Oxford Happiness Inventory, are filled out by a sample consisted of 384 students, which were selected using stratified random sampling from the students of Shahid Bahonar University of Kerman. Data are subjected to descriptive and inferential statistics including correlations and multivariate regressions. Bivariate correlations support positive and significant predictive value of spiritual intelligence toward general health and happiness. Further analysis showed that among the Spiritual Intelligence' subscales, Existential Critical Thinking Predicted General Health and Happiness, reversely. In addition, happiness was positively predicted by generation of personal meaning and transcendental awareness. The findings are discussed in line with the previous studies and the relevant theoretical background.

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

International Nuclear Information System (INIS)

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

2015-01-01

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

Analysis of Cell Phone Usage Using Correlation Techniques

OpenAIRE

T S R MURTHY; D. SIVA RAMA KRISHNA

2011-01-01

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

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.

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

Directory of Open Access Journals (Sweden)

Jae Kwon Kim

2017-01-01

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

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.

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

Energy Technology Data Exchange (ETDEWEB)

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

2015-12-04

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

Dynamical Analysis of Stock Market Instability by Cross-correlation Matrix

Science.gov (United States)

Takaishi, Tetsuya

2016-08-01

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

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)

Variational analysis and generalized differentiation I basic theory

CERN Document Server

Mordukhovich, Boris S

2006-01-01

Contains a study of the basic concepts and principles of variational analysis and generalized differentiation in both finite-dimensional and infinite-dimensional spaces. This title presents many applications to problems in optimization, equilibria, stability and sensitivity, control theory, economics, mechanics, and more.

Prevalence and correlates of adult overweight in the Muslim world: analysis of 46 countries.

Science.gov (United States)

Kahan, D

2015-04-01

The primary objectives of the study were to calculate overweight prevalence (body mass index ≥ 25.0) and simple correlations between 10 demographic, social welfare and behavioural variables and overweight prevalence for Muslim countries (populations >50% Muslim; N = 46). Overweight data for a country's total, male and female populations were extracted from the World Health Organization's (WHO) STEPwise country reports and relevant publications. Country-level data for potential correlates were extracted from multiple sources: Central Intelligence Agency (literacy), Gallup Poll (religiosity), United Nations (agricultural employment, food supply, gender inequality, human development), World Bank (automobile ownership, Internet, labour force) and WHO (physical inactivity). The overall, male and female overweight prevalence was 37.4, 33.0 and 42.1%, respectively. Prevalence estimates significantly differed by economic classification, gender and ethnicity. Middle- and upper income countries were 1.54-7.76 (95% confidence interval [CI]: 1.49-8.07) times more likely overweight than low-income countries, females were 1.48 (CI: 1.45-1.50) times more likely overweight than males and Arab countries were 2.92 (CI: 2.86-2.97) times more likely overweight than non-Arab countries. All 10 of the potential correlates were significantly associated with overweight for at least one permutation (total, economic classification, gender, ethnicity). The greater percentage of poorer countries among non-Arab Muslim countries, which compared with Arab countries have not as rapidly been transformed by globalization, nutrition transition and urbanization, may partially explain prevalence differences. Evaluation of correlational data generally followed associations seen in non-Muslim countries but more complex analysis of subnational data is needed. Arab women are a particularly vulnerable subgroup and governments should act within religious and cultural parameters to provide

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

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

Volatility-constrained multifractal detrended cross-correlation analysis: Cross-correlation among Mainland China, US, and Hong Kong stock markets

Science.gov (United States)

Cao, Guangxi; Zhang, Minjia; Li, Qingchen

2017-04-01

This study focuses on multifractal detrended cross-correlation analysis of the different volatility intervals of Mainland China, US, and Hong Kong stock markets. A volatility-constrained multifractal detrended cross-correlation analysis (VC-MF-DCCA) method is proposed to study the volatility conductivity of Mainland China, US, and Hong Kong stock markets. Empirical results indicate that fluctuation may be related to important activities in real markets. The Hang Seng Index (HSI) stock market is more influential than the Shanghai Composite Index (SCI) stock market. Furthermore, the SCI stock market is more influential than the Dow Jones Industrial Average stock market. The conductivity between the HSI and SCI stock markets is the strongest. HSI was the most influential market in the large fluctuation interval of 1991 to 2014. The autoregressive fractionally integrated moving average method is used to verify the validity of VC-MF-DCCA. Results show that VC-MF-DCCA is effective.

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.

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...

Nonlinear analysis of generalized cross-field current instability

International Nuclear Information System (INIS)

Yoon, P.H.; Lui, A.T.Y.

1993-01-01

Analysis of the generalized cross-field current instability is carried out in which cross-field drift of both the ions and electrons and their temperatures are permitted to vary in time. The unstable mode under consideration is the electromagnetic generalization of the classical modified-two-stream instability. The generalized instability is made of the modified-two-stream and ion-Weibel modes. The relative importance of the features associated with the ion-Weibel mode and those of the modified-two-stream mode is assessed. Specific applications are made to the Earth's neutral sheet prior to substorm onset and to the Earth's bow shock. The numerical solution indicates that the ion-Weibel mode dominates in the Earth's neutral sheet environment. In contrast, the situation for the bow shock is dominated by the modified-two-stream mode. Notable differences are found between the present calculation and previous results on ion-Weibel mode which restrict the analysis to only parallel propagating waves. However, in the case of Earth's bow shock for which the ion-Weibel mode plays no important role, the inclusion of the electromagnetic ion response is found to differ little from the previous results which treats ions responding only to the electrostatic component of the excited waves

Chaotic correlations in barrier billiards with arbitrary barriers

International Nuclear Information System (INIS)

Osbaldestin, A H; Adamson, L N C

2013-01-01

We study autocorrelation functions in symmetric barrier billiards for golden mean trajectories with arbitrary barriers. Renormalization analysis reveals the presence of a chaotic invariant set and thus that, for a typical barrier, there are chaotic correlations. The chaotic renormalization set is the analogue of the so-called orchid that arises in a generalized Harper equation. (paper)

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

Empirical mode decomposition and long-range correlation analysis of sunspot time series

International Nuclear Information System (INIS)

Zhou, Yu; Leung, Yee

2010-01-01

Sunspots, which are the best known and most variable features of the solar surface, affect our planet in many ways. The number of sunspots during a period of time is highly variable and arouses strong research interest. When multifractal detrended fluctuation analysis (MF-DFA) is employed to study the fractal properties and long-range correlation of the sunspot series, some spurious crossover points might appear because of the periodic and quasi-periodic trends in the series. However many cycles of solar activities can be reflected by the sunspot time series. The 11-year cycle is perhaps the most famous cycle of the sunspot activity. These cycles pose problems for the investigation of the scaling behavior of sunspot time series. Using different methods to handle the 11-year cycle generally creates totally different results. Using MF-DFA, Movahed and co-workers employed Fourier truncation to deal with the 11-year cycle and found that the series is long-range anti-correlated with a Hurst exponent, H, of about 0.12. However, Hu and co-workers proposed an adaptive detrending method for the MF-DFA and discovered long-range correlation characterized by H≈0.74. In an attempt to get to the bottom of the problem in the present paper, empirical mode decomposition (EMD), a data-driven adaptive method, is applied to first extract the components with different dominant frequencies. MF-DFA is then employed to study the long-range correlation of the sunspot time series under the influence of these components. On removing the effects of these periods, the natural long-range correlation of the sunspot time series can be revealed. With the removal of the 11-year cycle, a crossover point located at around 60 months is discovered to be a reasonable point separating two different time scale ranges, H≈0.72 and H≈1.49. And on removing all cycles longer than 11 years, we have H≈0.69 and H≈0.28. The three cycle-removing methods—Fourier truncation, adaptive detrending and the

Phenotypic correlations between egg weight and some egg quality ...

African Journals Online (AJOL)

Eggs were examined for both internal and external egg quality traits.Data obtained were subjected to one-way analysis of variance using the general linear procedure of SAS (2012). Differences in means were ranked using the Duncan's multiple Range test. Phenotypic correlations between egg weight and other egg quality ...

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

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

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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.

Metabolic connectivity by interregional correlation analysis using statistical parametric mapping (SPM) and FDG brain PET; methodological development and patterns of metabolic connectivity in adults

International Nuclear Information System (INIS)

Lee, Dong Soo; Oh, Jungsu S.; Lee, Jae Sung; Lee, Myung Chul; Kang, Hyejin; Kim, Heejung; Park, Hyojin

2008-01-01

Regionally connected areas of the resting brain can be detected by fluorodeoxyglucose-positron emission tomography (FDG-PET). Voxel-wise metabolic connectivity was examined, and normative data were established by performing interregional correlation analysis on statistical parametric mapping of FDG-PET data. Characteristics of seed volumes of interest (VOIs) as functional brain units were represented by their locations, sizes, and the independent methods of their determination. Seed brain areas were identified as population-based gyral VOIs (n=70) or as population-based cytoarchitectonic Brodmann areas (BA; n=28). FDG uptakes in these areas were used as independent variables in a general linear model to search for voxels correlated with average seed VOI counts. Positive correlations were searched in entire brain areas. In normal adults, one third of gyral VOIs yielded correlations that were confined to themselves, but in the others, correlated voxels extended to adjacent areas and/or contralateral homologous regions. In tens of these latter areas with extensive connectivity, correlated voxels were found across midline, and asymmetry was observed in the patterns of connectivity of left and right homologous seed VOIs. Most of the available BAs yielded correlations reaching contralateral homologous regions and/or neighboring areas. Extents of metabolic connectivity were not found to be related to seed VOI size or to the methods used to define seed VOIs. These findings indicate that patterns of metabolic connectivity of functional brain units depend on their regional locations. We propose that interregional correlation analysis of FDG-PET data offers a means of examining voxel-wise regional metabolic connectivity of the resting human brain. (orig.)

Metabolic connectivity by interregional correlation analysis using statistical parametric mapping (SPM) and FDG brain PET; methodological development and patterns of metabolic connectivity in adults

Energy Technology Data Exchange (ETDEWEB)

Lee, Dong Soo; Oh, Jungsu S.; Lee, Jae Sung; Lee, Myung Chul [Seoul National University, College of Medicine, Department of Nuclear Medicine, Jongno-gu, Seoul (Korea); Kang, Hyejin [Seoul National University, College of Medicine, Department of Nuclear Medicine, Jongno-gu, Seoul (Korea); Seoul National University, Programs in Brain and Neuroscience, Seoul (Korea); Kim, Heejung; Park, Hyojin [Seoul National University, College of Medicine, Department of Nuclear Medicine, Jongno-gu, Seoul (Korea); Seoul National University, Interdisciplinary Program in Cognitive Science, Seoul (Korea)

2008-09-15

Regionally connected areas of the resting brain can be detected by fluorodeoxyglucose-positron emission tomography (FDG-PET). Voxel-wise metabolic connectivity was examined, and normative data were established by performing interregional correlation analysis on statistical parametric mapping of FDG-PET data. Characteristics of seed volumes of interest (VOIs) as functional brain units were represented by their locations, sizes, and the independent methods of their determination. Seed brain areas were identified as population-based gyral VOIs (n=70) or as population-based cytoarchitectonic Brodmann areas (BA; n=28). FDG uptakes in these areas were used as independent variables in a general linear model to search for voxels correlated with average seed VOI counts. Positive correlations were searched in entire brain areas. In normal adults, one third of gyral VOIs yielded correlations that were confined to themselves, but in the others, correlated voxels extended to adjacent areas and/or contralateral homologous regions. In tens of these latter areas with extensive connectivity, correlated voxels were found across midline, and asymmetry was observed in the patterns of connectivity of left and right homologous seed VOIs. Most of the available BAs yielded correlations reaching contralateral homologous regions and/or neighboring areas. Extents of metabolic connectivity were not found to be related to seed VOI size or to the methods used to define seed VOIs. These findings indicate that patterns of metabolic connectivity of functional brain units depend on their regional locations. We propose that interregional correlation analysis of FDG-PET data offers a means of examining voxel-wise regional metabolic connectivity of the resting human brain. (orig.)

General parenting styles are not strongly associated with fruit and vegetable intake and social-environmental correlates among 11-year-old children in four countries in Europe.

Science.gov (United States)

De Bourdeaudhuij, I; Te Velde, S J; Maes, L; Pérez-Rodrigo, C; de Almeida, M D V; Brug, J

2009-02-01

To investigate whether fruit and vegetable (F&V) intake in 11-year-olds, and social-environmental correlates of F&V intake such as parental modelling and encouragement, family food rules and home availability, differ according to general parenting styles in Belgium, The Netherlands, Portugal and Spain. Cross-sectional study. Primary schools in four countries. Pupils and one of their parents completed questionnaires to measure F&V intake, related social-environmental correlates and general parenting styles. The sample size was 4555 (49.3 % boys); 1180 for Belgium, 883 for The Netherlands, 1515 for Portugal and 977 for Spain. Parenting styles were divided into authoritative, authoritarian, indulgent and neglectful. No differences were found in F&V intake across parenting styles and only very few significant differences in social-environmental correlates. The authoritarian (more parental encouragement and more demands to eat fruit) and the authoritative (more availability of fruit and vegetables) parenting styles resulted in more favourable correlates. Despite earlier studies suggesting that general parenting styles are associated with health behaviours in children, the present study suggests that this association is weak to non-existent for F&V intakes in four different European countries.

The 7-item generalized anxiety disorder scale as a tool for measuring generalized anxiety in multiple sclerosis.

Science.gov (United States)

Terrill, Alexandra L; Hartoonian, Narineh; Beier, Meghan; Salem, Rana; Alschuler, Kevin

2015-01-01

Generalized anxiety disorder (GAD) is common in multiple sclerosis (MS) but understudied. Reliable and valid measures are needed to advance clinical care and expand research in this area. The objectives of this study were to examine the psychometric properties of the 7-item Generalized Anxiety Disorder Scale (GAD-7) in individuals with MS and to analyze correlates of GAD. Participants (N = 513) completed the anxiety module of the Patient Health Questionnaire (GAD-7). To evaluate psychometric properties of the GAD-7, the sample was randomly split to conduct exploratory and confirmatory factor analyses. Based on the exploratory factor analysis, a one-factor structure was specified for the confirmatory factor analysis, which showed excellent global fit to the data (χ(2) 12 = 15.17, P = .23, comparative fit index = 0.99, root mean square error of approximation = 0.03, standardized root mean square residual = 0.03). The Cronbach alpha (0.75) indicated acceptable internal consistency for the scale. Furthermore, the GAD-7 was highly correlated with the Hospital Anxiety and Depression Scale-Anxiety (r = 0.70). Age and duration of MS were both negatively associated with GAD. Higher GAD-7 scores were observed in women and individuals with secondary progressive MS. Individuals with higher GAD-7 scores also endorsed more depressive symptoms. These findings support the reliability and internal validity of the GAD-7 for use in MS. Correlational analyses revealed important relationships with demographics, disease course, and depressive symptoms, which suggest the need for further anxiety research.

Extension problem for generalized multi-monogenic functions in Clifford analysis

International Nuclear Information System (INIS)

Tran Quyet Thang.

1992-10-01

The main purpose of this paper is to extend some properties of multi-monogenic functions, which is a generalization of monogenic functions in higher dimensions, for a class of functions satisfying Vekua-type generalized Cauchy-Riemann equations in Clifford Analysis. It is proved that the Hartogs theorem is valid for these functions. (author). 7 refs

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.

Texture Analysis Using Rényi’s Generalized Entropies

NARCIS (Netherlands)

Grigorescu, S.E.; Petkov, N.

2003-01-01

We propose a texture analysis method based on Rényi’s generalized entropies. The method aims at identifying texels in regular textures by searching for the smallest window through which the minimum number of different visual patterns is observed when moving the window over a given texture. The

Analysis of Lamellar Structures with Application of Generalized Functions

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Kipiani Gela

2016-12-01

Full Text Available Theory of differential equations in respect of the functional area is based on the basic concepts on generalized functions and splines. There are some basic concepts related to the theory of generalized functions and their properties are considered in relation to the rod systems and lamellar structures. The application of generalized functions gives the possibility to effectively calculate step-variable stiffness lamellar structures. There are also widely applied structures, in that several in which a number of parallel load bearing layers are interconnected by discrete-elastic links. For analysis of system under study, such as design diagrams, there are applied discrete and discrete-continual models.

Smoking prevalence among lesbian, bisexual and queer women in Sydney remains high: Analysis of trends and correlates.

Science.gov (United States)

Deacon, Rachel M; Mooney-Somers, Julie

2017-07-01

To investigate smoking prevalence trends and correlates among lesbian, bisexual and queer-identifying (LBQ) women in Sydney, Australia. Data from 5007 respondents to a repeated cross-sectional community survey were used to examine smoking trends between 2004 and 2014. Multinomial logistic regression was used to examine smoking correlates. Thirty percent of respondents were current smokers, including 48% of 16 to 24-year-olds. A slight decrease in all-ages smoking over time was not reflected in the youngest age group. LBQ women who smoke have fewer economic, social and psychological resources than both women who never smoke and ex-smokers. High levels of alcohol and illicit drug use are also correlated with current smoking. Population-wide interventions have failed to address the persistently high prevalence of smoking among this sample of LBQ women. Tailored interventions may find utility focusing on personal resilience to deal with general and sexuality-specific stressors, as well as attending to poly-substance use. Acknowledgment of LBQ women as a priority group for tobacco reduction is urgently needed. We call on tobacco control agencies to consider sexuality and gender orientation in policy and partner with lesbian, gay, bisexual and transgender community organisations to develop culturally appropriate interventions. [Deacon RM, Mooney-Somers J Smoking prevalence among lesbian, bisexual and queer women in Sydney remains high: Analysis of trends and correlates Drug Alcohol Rev 2017;36:546-554]. © 2017 Australasian Professional Society on Alcohol and other Drugs.

Relationship between Entropy and Dimension of Financial Correlation-Based Network

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Chun-xiao Nie

2018-03-01

Full Text Available We analyze the dimension of a financial correlation-based network and apply our analysis to characterize the complexity of the network. First, we generalize the volume-based dimension and find that it is well defined by the correlation-based network. Second, we establish the relationship between the Rényi index and the volume-based dimension. Third, we analyze the meaning of the dimensions sequence, which characterizes the level of departure from the comparison benchmark based on the randomized time series. Finally, we use real stock market data from three countries for empirical analysis. In some cases, our proposed analysis method can more accurately capture the structural differences of networks than the power law index commonly used in previous studies.

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

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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.

A canonical correlation neural network for multicollinearity and functional data.

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Gou, Zhenkun; Fyfe, Colin

2004-03-01

We review a recent neural implementation of Canonical Correlation Analysis and show, using ideas suggested by Ridge Regression, how to make the algorithm robust. The network is shown to operate on data sets which exhibit multicollinearity. We develop a second model which not only performs as well on multicollinear data but also on general data sets. This model allows us to vary a single parameter so that the network is capable of performing Partial Least Squares regression (at one extreme) to Canonical Correlation Analysis (at the other)and every intermediate operation between the two. On multicollinear data, the parameter setting is shown to be important but on more general data no particular parameter setting is required. Finally, we develop a second penalty term which acts on such data as a smoother in that the resulting weight vectors are much smoother and more interpretable than the weights without the robustification term. We illustrate our algorithms on both artificial and real data.

Correlated motions are a fundamental property of β-sheets

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Fenwick, R. Bryn; Orellana, Laura; Esteban-Martín, Santi; Orozco, Modesto; Salvatella, Xavier

2014-06-01

Correlated motions in proteins can mediate fundamental biochemical processes such as signal transduction and allostery. The mechanisms that underlie these processes remain largely unknown due mainly to limitations in their direct detection. Here, based on a detailed analysis of protein structures deposited in the protein data bank, as well as on state-of-the art molecular simulations, we provide general evidence for the transfer of structural information by correlated backbone motions, mediated by hydrogen bonds, across β-sheets. We also show that the observed local and long-range correlated motions are mediated by the collective motions of β-sheets and investigate their role in large-scale conformational changes. Correlated motions represent a fundamental property of β-sheets that contributes to protein function.

Uncertainty Analysis of Few Group Cross Sections Based on Generalized Perturbation Theory

International Nuclear Information System (INIS)

Han, Tae Young; Lee, Hyun Chul; Noh, Jae Man

2014-01-01

In this paper, the methodology of the sensitivity and uncertainty analysis code based on GPT was described and the preliminary verification calculations on the PMR200 pin cell problem were carried out. As a result, they are in a good agreement when compared with the results by TSUNAMI. From this study, it is expected that MUSAD code based on GPT can produce the uncertainty of the homogenized few group microscopic cross sections for a core simulator. For sensitivity and uncertainty analyses for general core responses, a two-step method is available and it utilizes the generalized perturbation theory (GPT) for homogenized few group cross sections in the first step and stochastic sampling method for general core responses in the second step. The uncertainty analysis procedure based on GPT in the first step needs the generalized adjoint solution from a cell or lattice code. For this, the generalized adjoint solver has been integrated into DeCART in our previous work. In this paper, MUSAD (Modues of Uncertainty and Sensitivity Analysis for DeCART) code based on the classical perturbation theory was expanded to the function of the sensitivity and uncertainty analysis for few group cross sections based on GPT. First, the uncertainty analysis method based on GPT was described and, in the next section, the preliminary results of the verification calculation on a VHTR pin cell problem were compared with the results by TSUNAMI of SCALE 6.1

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

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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.

A general numerical analysis program for the superconducting quasiparticle mixer

Science.gov (United States)

Hicks, R. G.; Feldman, M. J.; Kerr, A. R.

1986-01-01

A user-oriented computer program SISCAP (SIS Computer Analysis Program) for analyzing SIS mixers is described. The program allows arbitrary impedance terminations to be specified at all LO harmonics and sideband frequencies. It is therefore able to treat a much more general class of SIS mixers than the widely used three-frequency analysis, for which the harmonics are assumed to be short-circuited. An additional program, GETCHI, provides the necessary input data to program SISCAP. The SISCAP program performs a nonlinear analysis to determine the SIS junction voltage waveform produced by the local oscillator. The quantum theory of mixing is used in its most general form, treating the large signal properties of the mixer in the time domain. A small signal linear analysis is then used to find the conversion loss and port impedances. The noise analysis includes thermal noise from the termination resistances and shot noise from the periodic LO current. Quantum noise is not considered. Many aspects of the program have been adequately verified and found accurate.

Point-point and point-line moving-window correlation spectroscopy and its applications

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Zhou, Qun; Sun, Suqin; Zhan, Daqi; Yu, Zhiwu

2008-07-01

In this paper, we present a new extension of generalized two-dimensional (2D) correlation spectroscopy. Two new algorithms, namely point-point (P-P) correlation and point-line (P-L) correlation, have been introduced to do the moving-window 2D correlation (MW2D) analysis. The new method has been applied to a spectral model consisting of two different processes. The results indicate that P-P correlation spectroscopy can unveil the details and re-constitute the entire process, whilst the P-L can provide general feature of the concerned processes. Phase transition behavior of dimyristoylphosphotidylethanolamine (DMPE) has been studied using MW2D correlation spectroscopy. The newly proposed method verifies that the phase transition temperature is 56 °C, same as the result got from a differential scanning calorimeter. To illustrate the new method further, a lysine and lactose mixture has been studied under thermo perturbation. Using the P-P MW2D, the Maillard reaction of the mixture was clearly monitored, which has been very difficult using conventional display of FTIR spectra.

DATE analysis: A general theory of biological change applied to microarray data.

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Rasnick, David

2009-01-01

In contrast to conventional data mining, which searches for specific subsets of genes (extensive variables) to correlate with specific phenotypes, DATE analysis correlates intensive state variables calculated from the same datasets. At the heart of DATE analysis are two biological equations of state not dependent on genetic pathways. This result distinguishes DATE analysis from other bioinformatics approaches. The dimensionless state variable F quantifies the relative overall cellular activity of test cells compared to well-chosen reference cells. The variable pi(i) is the fold-change in the expression of the ith gene of test cells relative to reference. It is the fraction phi of the genome undergoing differential expression-not the magnitude pi-that controls biological change. The state variable phi is equivalent to the control strength of metabolic control analysis. For tractability, DATE analysis assumes a linear system of enzyme-connected networks and exploits the small average contribution of each cellular component. This approach was validated by reproducible values of the state variables F, RNA index, and phi calculated from random subsets of transcript microarray data. Using published microarray data, F, RNA index, and phi were correlated with: (1) the blood-feeding cycle of the malaria parasite, (2) embryonic development of the fruit fly, (3) temperature adaptation of Killifish, (4) exponential growth of cultured S. pneumoniae, and (5) human cancers. DATE analysis was applied to aCGH data from the great apes. A good example of the power of DATE analysis is its application to genomically unstable cancers, which have been refractory to data mining strategies. 2009 American Institute of Chemical Engineers Biotechnol.

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)

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.

A generalization of random matrix theory and its application to statistical physics.

Science.gov (United States)

Wang, Duan; Zhang, Xin; Horvatic, Davor; Podobnik, Boris; Eugene Stanley, H

2017-02-01

To study the statistical structure of crosscorrelations in empirical data, we generalize random matrix theory and propose a new method of cross-correlation analysis, known as autoregressive random matrix theory (ARRMT). ARRMT takes into account the influence of auto-correlations in the study of cross-correlations in multiple time series. We first analytically and numerically determine how auto-correlations affect the eigenvalue distribution of the correlation matrix. Then we introduce ARRMT with a detailed procedure of how to implement the method. Finally, we illustrate the method using two examples taken from inflation rates for air pressure data for 95 US cities.

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

OpenAIRE

Ole E. Barndorff-Nielsen; Neil Shephard

2002-01-01

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

Structure function analysis of long-range correlations in plasma turbulence

International Nuclear Information System (INIS)

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

2003-01-01

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

Generalized modeling of the fractional-order memcapacitor and its character analysis

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Guo, Zhang; Si, Gangquan; Diao, Lijie; Jia, Lixin; Zhang, Yanbin

2018-06-01

Memcapacitor is a new type of memory device generalized from the memristor. This paper proposes a generalized fractional-order memcapacitor model by introducing the fractional calculus into the model. The generalized formulas are studied and the two fractional-order parameter α, β are introduced where α mostly affects the fractional calculus value of charge q within the generalized Ohm's law and β generalizes the state equation which simulates the physical mechanism of a memcapacitor into the fractional sense. This model will be reduced to the conventional memcapacitor as α = 1 , β = 0 and to the conventional memristor as α = 0 , β = 1 . Then the numerical analysis of the fractional-order memcapacitor is studied. And the characteristics and output behaviors of the fractional-order memcapacitor applied with sinusoidal charge are derived. The analysis results have shown that there are four basic v - q and v - i curve patterns when the fractional order α, β respectively equal to 0 or 1, moreover all v - q and v - i curves of the other fractional-order models are transition curves between the four basic patterns.

Study of General health, resiliency, and defense mechanisms in patients with migraine headache

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Alireza Aghayusefi

2013-06-01

Full Text Available Background: Migraine is a neurological disease that the etiology, several factors affect its onset or its exacerbation. One of the factors affecting disease is psychological factors such as defense mechanisms, resiliency, and general health. This study assessed the relationship between general health, resiliency, and general defense mechanisms, and also predicts the general health of people with migraine headaches that have a high resiliency and use mature defense mechanisms. Material and Methods: 50 women with migraine headache in the city of Bushehr using defense mechanisms, resiliency, and general health questionnaires were studied. For statistical analysis, Pearson correlation and multiple regression tests were used by SPSS 17 software. Results: The results showed that most of the defense mechanisms of migraine sufferers are Immature and Neuroticism. There is significant negative correlation between the deterioration of general health and resiliency as well as the mature defense mechanism (p=0/003, and also there is a significant positive correlation between this deterioration with neuroticism (p=0/040 and immature defense mechanisms (p=0/041. On the other hand there is significant negative correlation between resiliencies with immature (p=0/009 and neuroticism defense mechanisms (p=0/04, and also with mature defense mechanism has a significant positive correlation (p=0/003. Also, as more people use the mature defense mechanism, their deterioration of general health will be reduced, but this relationship will be stronger with the presence of resiliency. So migraine people use the mature defense mechanisms with high resiliency will have more favorable general health (less deterioration of general health. Conclusion: This study showed that migraine patients use the mature defense mechanisms with high resiliency will have more favorable general health (less deterioration of general health.

CORRELATION ANALYSIS OF THE AUDIT COMMITTEE AND STRUCTURAL INDICATORS

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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.

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.

Multigroup Moderation Test in Generalized Structured Component Analysis

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Angga Dwi Mulyanto

2016-05-01

Full Text Available Generalized Structured Component Analysis (GSCA is an alternative method in structural modeling using alternating least squares. GSCA can be used for the complex analysis including multigroup. GSCA can be run with a free software called GeSCA, but in GeSCA there is no multigroup moderation test to compare the effect between groups. In this research we propose to use the T test in PLS for testing moderation Multigroup on GSCA. T test only requires sample size, estimate path coefficient, and standard error of each group that are already available on the output of GeSCA and the formula is simple so the user does not need a long time for analysis.

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.

Correlation analysis of the urban heat island effect and the spatial and temporal distribution of atmospheric particulates using TM images in Beijing

International Nuclear Information System (INIS)

Xu, L.Y.; Xie, X.D.; Li, S.

2013-01-01

This study combines the methods of observation statistics and remote sensing retrieval, using remote sensing information including the urban heat island (UHI) intensity index, the normalized difference vegetation index (NDVI), the normalized difference water index (NDWI), and the difference vegetation index (DVI) to analyze the correlation between the urban heat island effect and the spatial and temporal concentration distributions of atmospheric particulates in Beijing. The analysis establishes (1) a direct correlation between UHI and DVI; (2) an indirect correlation among UHI, NDWI and DVI; and (3) an indirect correlation among UHI, NDVI, and DVI. The results proved the existence of three correlation types with regional and seasonal effects and revealed an interesting correlation between UHI and DVI, that is, if UHI is below 0.1, then DVI increases with the increase in UHI, and vice versa. Also, DVI changes more with UHI in the two middle zones of Beijing. -- Highlights: •We analyze the correlation from the spatial and temporal views. •We present correlation analyses among UHI, NDWI, NDVI, and DVI from three perspectives. •Three correlations are proven to exist with regional and seasonal effects. •If UHI is below 0.1, then DVI increases with the increase in UHI, and vice versa. •The DVI changes more with UHI in the two middle zones of Beijing. -- Generally, if UHI is below 0.1 in the weak heat island or green island range, then DVI increases with the increase in UHI, and vice versa

Generalization of the Knizhnik-Zamolodchikov-equations

International Nuclear Information System (INIS)

Alekseev, A.Yu.; Recknagel, A.; Schomerus, V.

1996-09-01

In this letter we introduce a generalization of the Knizhnik-Zamolodchikov equations from affine Lie algebras to a wide class of conformal field theories (not necessarily rational). The new equations describe correlation functions of primary fields and of a finite number of their descendents. Our proposal is based on Nahm's concept of small spaces which provide adequate substitutes for the lowest energy subspaces in modules of affine Lie algebras. We explain how to construct the first order differential equations and investigate properties of the associated connections, thereby preparing the grounds for an analysis of quantum symmetries. The general considerations are illustrated in examples of Virasoro minimal models. (orig.)

Correlations between ultrasonic pulse wave velocities and rock properties of quartz-mica schist

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Bharti Chawre

2018-06-01

Full Text Available Physico-mechanical properties are critically important parameters for rocks. This study aims to examine some of the rock properties of quartz-mica schist (QMS rocks in a cost-effective manner by establishing correlations between non-destructive and destructive tests. Using simple regression analysis, good correlations were obtained between the pulse wave velocities and the properties of QMS rocks. The results were further improved by using multiple regression analysis as compared to those obtained by the simple linear regression analysis. The results were also compared to the ones obtained by other empirical equations available. The general equations encompassing all types of rocks did not give reliable results of rock properties and showed large relative errors, ranging from 23% to 1146%. It is suggested that empirical correlations must be investigated separately for different types of rocks. The general empirical equations should not be used for the design and planning purposes before they are verified at least on one rock sample from the project site, as they may contain large unacceptable errors. Keywords: Pulse wave velocity, Physico-mechanical properties, Quartz-mica schist (QMS rocks, Non-destructive methods, Static elastic constants, Dynamic elastic constants

Direct formulation to Cholesky decomposition of a general nonsingular correlation matrix.

Science.gov (United States)

Madar, Vered

2015-08-01

We present two novel and explicit parametrizations of Cholesky factor of a nonsingular correlation matrix. One that uses semi-partial correlation coefficients, and a second that utilizes differences between the successive ratios of two determinants. To each, we offer a useful application.

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

Science.gov (United States)

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

2018-06-04

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

Patterns of stigma toward schizophrenia among the general population: a latent profile analysis.

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Loch, Alexandre A; Wang, Yuan-Pang; Guarniero, Francisco B; Lawson, Fabio L; Hengartner, Michael P; Rössler, Wulf; Gattaz, Wagner F

2014-09-01

Our purpose was to assess stigma toward schizophrenia in a representative sample of the Brazilian general population. The sample consisted of 1015 individuals interviewed by telephone. A vignette describing someone with schizophrenia was read, and four stigma aspects regarding this hypothetical individual were assessed: stereotypes, restrictions, perceived prejudice and social distance. Latent profile analysis searched for stigma profiles among the sample. Multinomial logistic regression was used to find correlates of each class. Four stigma profiles were found; 'no stigma' individuals (n = 251) mostly displayed positive opinions. 'Labelers' (n = 222) scored high on social distance; they more often had familial contact with mental illness and more often labeled the vignette's disorder as schizophrenia. 'Discriminators', the group with the majority of individuals (n = 302), showed high levels of stigmatizing beliefs in all dimensions; discriminators were significantly older. 'Unobtrusive stigma' individuals (n = 240) seemed to demonstrate uncertainty or low commitment since they mostly answered items with the middle/impartial option. Some findings from the international literature were replicated; however, familial contact increased stigma, possibly denoting a locally modulated determinant. Hereby, our study also adds important cross-cultural data by showing that stigma toward schizophrenia is high in a Latin-American setting. We highlight the importance of analyzing the general population as a heterogeneous group, aiming to better elaborate anti-stigma campaigns. © The Author(s) 2013.

Nanoscale protein diffusion by STED-based pair correlation analysis.

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Paolo Bianchini

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

Correlation analysis of the physiological factors controlling fundamental voice frequency.

Science.gov (United States)

Atkinson, J E

1978-01-01

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

An Introduction to Generalized Estimating Equations and an Application to Assess Selectivity Effects in a Longitudinal Study on Very Old Individuals

Science.gov (United States)

Ghisletta, Paolo; Spini, Dario

2004-01-01

Correlated data are very common in the social sciences. Most common applications include longitudinal and hierarchically organized (or clustered) data. Generalized estimating equations (GEE) are a convenient and general approach to the analysis of several kinds of correlated data. The main advantage of GEE resides in the unbiased estimation of…

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.

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

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V. L. Kozlov

2018-01-01

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

Phenomenological analysis of angular correlations in 7 TeV proton-proton collisions from the CMS experiment

International Nuclear Information System (INIS)

Ray, R. L.

2011-01-01

A phenomenological analysis is presented of recent two-particle angular correlation data on relative pseudorapidity (η) and azimuth reported by the Compact Muon Solenoid (CMS) Collaboration for √(s)=7 TeV proton-proton collisions. The data are described with an empirical jetlike model developed for similar angular correlation measurements obtained from heavy-ion collisions at the Relativistic Heavy-Ion Collider (RHIC). The sameside (small relative azimuth), η-extended correlation structure, referred to as the ridge, is compared with three phenomenological correlation structures suggested by theoretical analysis. These include additional angular correlations due to soft gluon radiation in 2→3 partonic processes, a one-dimensional sameside correlation ridge on azimuth motivated, for example, by color-glass condensate models, and an azimuth quadrupole similar to that required to describe heavy-ion angular correlations. The quadrupole model provides the best overall description of the CMS data, including the ridge, based on χ 2 minimization in agreement with previous studies. Implications of these results with respect to possible mechanisms for producing the CMS sameside correlation ridge are discussed.

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

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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.

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

Science.gov (United States)

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

2013-01-01

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

Generalized concavity in fuzzy optimization and decision analysis

CERN Document Server

Ramík, Jaroslav

2002-01-01

Convexity of sets in linear spaces, and concavity and convexity of functions, lie at the root of beautiful theoretical results that are at the same time extremely useful in the analysis and solution of optimization problems, including problems of either single objective or multiple objectives. Not all of these results rely necessarily on convexity and concavity; some of the results can guarantee that each local optimum is also a global optimum, giving these methods broader application to a wider class of problems. Hence, the focus of the first part of the book is concerned with several types of generalized convex sets and generalized concave functions. In addition to their applicability to nonconvex optimization, these convex sets and generalized concave functions are used in the book's second part, where decision-making and optimization problems under uncertainty are investigated. Uncertainty in the problem data often cannot be avoided when dealing with practical problems. Errors occur in real-world data for...

Novel Approaches to Spectral Properties of Correlated Electron Materials: From Generalized Kohn-Sham Theory to Screened Exchange Dynamical Mean Field Theory

Science.gov (United States)

Delange, Pascal; Backes, Steffen; van Roekeghem, Ambroise; Pourovskii, Leonid; Jiang, Hong; Biermann, Silke

2018-04-01

The most intriguing properties of emergent materials are typically consequences of highly correlated quantum states of their electronic degrees of freedom. Describing those materials from first principles remains a challenge for modern condensed matter theory. Here, we review, apply and discuss novel approaches to spectral properties of correlated electron materials, assessing current day predictive capabilities of electronic structure calculations. In particular, we focus on the recent Screened Exchange Dynamical Mean-Field Theory scheme and its relation to generalized Kohn-Sham Theory. These concepts are illustrated on the transition metal pnictide BaCo2As2 and elemental zinc and cadmium.

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

Analysis of Financial Ratio to Distinguish Indonesia Joint Venture General Insurance Company Performance using Discriminant Analysis

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Subiakto Soekarno

2012-01-01

Full Text Available Insurance industry stands as a service business that plays a significant role in Indonesiaeconomical condition. The development of insurance industry in Indonesia, both of generalinsurance and life insurance, has increased very fast. The general insurance industry itselfdivided into two major players which are local private company and Joint Venture Company.Lately, the use of statistical techniques and financial ratios models to asses financial institutionsuch as insurance company have been used as one of the appropriate combination inpredicting the performance of an industry. This research aims to distinguish between JointVenture General Insurance Companies that have a good performance and those who are lessperforming well using Discriminant Analysis. Further, the findings led that DiscriminantAnalysis is able to distinguish Joint Venture General Insurance Companies that have a goodperformance and those who are not performing well. There are also six ratios which are RBC,Technical Reserve to Investment Ratio, Debt Ratio, Return on Equity, Loss Ratio, and ExpenseRatio that stand as the most influential ratios to distinguish the performance of joint venturegeneral insurance companies. In addition, the result suggest business people to be concernedtoward those six ratios, to increase their companies’ performance.Key words: general insurance, financial ratio, discriminant analysis

Systematic review and meta-analysis of studies evaluating diagnostic test accuracy: A practical review for clinical researchers-Part II. general guidance and tips

International Nuclear Information System (INIS)

Kim, Kyung Won; Choi, Sang Hyun; Huh, Jimi; Park, Seong Ho; Lee, June Young

2015-01-01

Meta-analysis of diagnostic test accuracy studies differs from the usual meta-analysis of therapeutic/interventional studies in that, it is required to simultaneously analyze a pair of two outcome measures such as sensitivity and specificity, instead of a single outcome. Since sensitivity and specificity are generally inversely correlated and could be affected by a threshold effect, more sophisticated statistical methods are required for the meta-analysis of diagnostic test accuracy. Hierarchical models including the bivariate model and the hierarchical summary receiver operating characteristic model are increasingly being accepted as standard methods for meta-analysis of diagnostic test accuracy studies. We provide a conceptual review of statistical methods currently used and recommended for meta-analysis of diagnostic test accuracy studies. This article could serve as a methodological reference for those who perform systematic review and meta-analysis of diagnostic test accuracy studies

Extreme learning machine for ranking: generalization analysis and applications.

Science.gov (United States)

Chen, Hong; Peng, Jiangtao; Zhou, Yicong; Li, Luoqing; Pan, Zhibin

2014-05-01

The extreme learning machine (ELM) has attracted increasing attention recently with its successful applications in classification and regression. In this paper, we investigate the generalization performance of ELM-based ranking. A new regularized ranking algorithm is proposed based on the combinations of activation functions in ELM. The generalization analysis is established for the ELM-based ranking (ELMRank) in terms of the covering numbers of hypothesis space. Empirical results on the benchmark datasets show the competitive performance of the ELMRank over the state-of-the-art ranking methods. Copyright © 2014 Elsevier Ltd. All rights reserved.

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

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Baoyu LI

2017-06-01

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

Multivariate covariance generalized linear models

DEFF Research Database (Denmark)

Bonat, W. H.; Jørgensen, Bent

2016-01-01

are fitted by using an efficient Newton scoring algorithm based on quasi-likelihood and Pearson estimating functions, using only second-moment assumptions. This provides a unified approach to a wide variety of types of response variables and covariance structures, including multivariate extensions......We propose a general framework for non-normal multivariate data analysis called multivariate covariance generalized linear models, designed to handle multivariate response variables, along with a wide range of temporal and spatial correlation structures defined in terms of a covariance link...... function combined with a matrix linear predictor involving known matrices. The method is motivated by three data examples that are not easily handled by existing methods. The first example concerns multivariate count data, the second involves response variables of mixed types, combined with repeated...

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

Science.gov (United States)

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

2017-07-01

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

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.

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.

Long memory of abnormal investor attention and the cross-correlations between abnormal investor attention and trading volume, volatility respectively

Science.gov (United States)

Fan, Xiaoqian; Yuan, Ying; Zhuang, Xintian; Jin, Xiu

2017-03-01

Taking Baidu Index as a proxy for abnormal investor attention (AIA), the long memory property in the AIA of Shanghai Stock Exchange (SSE) 50 Index component stocks was empirically investigated using detrended fluctuation analysis (DFA) method. The results show that abnormal investor attention is power-law correlated with Hurst exponents between 0.64 and 0.98. Furthermore, the cross-correlations between abnormal investor attention and trading volume, volatility respectively are studied using detrended cross-correlation analysis (DCCA) and the DCCA cross-correlation coefficient (ρDCCA). The results suggest that there are positive correlations between AIA and trading volume, volatility respectively. In addition, the correlations for trading volume are in general higher than the ones for volatility. By carrying on rescaled range analysis (R/S) and rolling windows analysis, we find that the results mentioned above are effective and significant.

Initial Validation for the Estimation of Resting-State fMRI Effective Connectivity by a Generalization of the Correlation Approach

Directory of Open Access Journals (Sweden)

Nan Xu

2017-05-01

Full Text Available Resting-state functional MRI (rs-fMRI is widely used to noninvasively study human brain networks. Network functional connectivity is often estimated by calculating the timeseries correlation between blood-oxygen-level dependent (BOLD signal from different regions of interest (ROIs. However, standard correlation cannot characterize the direction of information flow between regions. In this paper, we introduce and test a new concept, prediction correlation, to estimate effective connectivity in functional brain networks from rs-fMRI. In this approach, the correlation between two BOLD signals is replaced by a correlation between one BOLD signal and a prediction of this signal via a causal system driven by another BOLD signal. Three validations are described: (1 Prediction correlation performed well on simulated data where the ground truth was known, and outperformed four other methods. (2 On simulated data designed to display the “common driver” problem, prediction correlation did not introduce false connections between non-interacting driven ROIs. (3 On experimental data, prediction correlation recovered the previously identified network organization of human brain. Prediction correlation scales well to work with hundreds of ROIs, enabling it to assess whole brain interregional connectivity at the single subject level. These results provide an initial validation that prediction correlation can capture the direction of information flow and estimate the duration of extended temporal delays in information flow between regions of interest ROIs based on BOLD signal. This approach not only maintains the high sensitivity to network connectivity provided by the correlation analysis, but also performs well in the estimation of causal information flow in the brain.

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

General and gay-related racism experienced by Latino gay men.

Science.gov (United States)

Ibañez, Gladys E; Van Oss Marin, Barbara; Flores, Stephen A; Millett, Gregorio; Diaz, Rafael M

2009-07-01

Latino gay men report experiences of racial discrimination within and outside the gay community. This study focused on correlates of racism within general and gay contexts. Racism was assessed in a probability sample of 911 Latino gay men recruited from 3 U.S. cities. Factor analysis of the 10-item scale produced 2 factors: (a) General Racism Experiences, and (b) Racism Experiences in Gay Contexts. The scale and each factor showed adequate reliability and validity. Latino gay men with darker skin, more Indian features, more time in the United States, and low self-esteem reported more racism in both general and gay contexts. The authors examine the psychometric properties of a measure that assesses interpersonal racism among Latinos, report correlates of racism within a gay context, and provide an assessment tool for understanding the role of racism in the lives of Latino gay men.

Tritium analysis of urine samples from the general Korean public.

Science.gov (United States)

Yoon, Seokwon; Ha, Wi-Ho; Lee, Seung-Sook

2013-11-01

The tritium concentrations of urine samples and the effective dose of the general Korean public were evaluated. To achieve accurate HTO analysis of urine samples, we established the optimal conditions for measuring the HTO content of urine samples. Urine samples from 50 Koreans who do not work at a nuclear facility were analyzed on the basis of the results. The average urine analysis result was 2.8 ±1 .4 Bq/L, and the range was 1.8-5.6 Bq/L. The measured values were lower than those reported for other countries. These results show that environmental factors and lifestyle differences are the main factors affecting the tritium level of the general public. © 2013 Elsevier Ltd. All rights reserved.

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)

Matrix precipitation: a general strategy to eliminate matrix interference for pharmaceutical toxic impurities analysis.

Science.gov (United States)

Yang, Xiaojing; Xiong, Xuewu; Cao, Ji; Luan, Baolei; Liu, Yongjun; Liu, Guozhu; Zhang, Lei

2015-01-30

Matrix interference, which can lead to false positive/negative results, contamination of injector or separation column, incompatibility between sample solution and the selected analytical instrument, and response inhibition or even quenching, is commonly suffered for the analysis of trace level toxic impurities in drug substance. In this study, a simple matrix precipitation strategy is proposed to eliminate or minimize the above stated matrix interference problems. Generally, a sample of active pharmaceutical ingredients (APIs) is dissolved in an appropriate solvent to achieve the desired high concentration and then an anti-solvent is added to precipitate the matrix substance. As a result, the target analyte is extracted into the mixed solution with very less residual of APIs. This strategy has the characteristics of simple manipulation, high recovery and excellent anti-interference capability. It was found that the precipitation ratio (R, representing the ability to remove matrix substance) and the proportion of solvent (the one used to dissolve APIs) in final solution (P, affecting R and also affecting the method sensitivity) are two important factors of the precipitation process. The correlation between R and P was investigated by performing precipitation with various APIs in different solvent/anti-solvent systems. After a detailed mathematical reasoning process, P=20% was proved to be an effective and robust condition to perform the precipitation strategy. The precipitation method with P=20% can be used as a general strategy for toxic impurity analysis in APIs. Finally, several typical examples are described in this article, where the challenging matrix interference issues have been resolved successfully. Copyright © 2014 Elsevier B.V. All rights reserved.

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

Science.gov (United States)

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

2014-01-01

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

Psychological treatment of generalized anxiety disorder: A meta-analysis.

NARCIS (Netherlands)

Cuijpers, P.; Sijbrandij, M.; Koole, S.L.; Huibers, M.J.H.; Berking, M.; Andersson, G.

2014-01-01

Recent years have seen a near-doubling of the number of studies examining the effects of psychotherapies for generalized anxiety disorder (GAD) in adults. The present article integrates this new evidence with the older literature through a quantitative meta-analysis. A total of 41 studies (with 2132

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.

Multivariate Meta-Analysis of Brain-Mass Correlations in Eutherian Mammals

Directory of Open Access Journals (Sweden)

Charlene Steinhausen

2016-09-01

Full Text Available The general assumption that brain size differences are an adequate proxy for subtler differences in brain organization turned neurobiologists towards the question why some groups of mammals such as primates, elephants, and whales have such remarkably large brains. In this meta-analysis, an extensive sample of eutherian mammals (115 species distributed in 14 orders provided data about several different biological traits and measures of brain size such as absolute brain mass (AB, relative brain mass (RB; quotient from AB and body mass, and encephalization quotient (EQ. These data were analyzed by established multivariate statistics without taking specific phylogenetic information into account. Species with high AB tend to (1 feed on protein-rich nutrition, (2 have a long lifespan, (3 delay sexual maturity, and (4 have long and rare pregnancies with small litter sizes. Animals with high RB usually have (1 a short life span, (2 reach sexual maturity early, and (3 have short and frequent gestations. Moreover males of species with high RB also have few potential sexual partners. In contrast, animals with high EQs have (1 a high number of potential sexual partners, (2 delayed sexual maturity, and (3 rare gestations with small litter sizes. Based on these correlations, we conclude that Eutheria with either high AB or high EQ occupy high positions in the network of food chains (high trophic levels. Eutheria of low trophic levels can develop a high RB only if they have small body masses.

Parallel Enhancements of the General Mission Analysis Tool, Phase I

Data.gov (United States)

National Aeronautics and Space Administration — The General Mission Analysis Tool (GMAT) is a state of the art spacecraft mission design tool under active development at NASA's Goddard Space Flight Center (GSFC)....

Cross-Cultural adaptation of the General Functioning Scale of the Family

Directory of Open Access Journals (Sweden)

Thiago Pires

2016-01-01

Full Text Available ABSTRACT OBJECTIVE To describe the process of cross-cultural adaptation of the General Functioning Scale of the Family, a subscale of the McMaster Family Assessment Device, for the Brazilian population. METHODS The General Functioning Scale of the Family was translated into Portuguese and administered to 500 guardians of children in the second grade of elementary school in public schools of Sao Gonçalo, Rio de Janeiro, Southeastern Brazil. The types of equivalences investigated were: conceptual and of items, semantic, operational, and measurement. The study involved discussions with experts, translations and back-translations of the instrument, and psychometric assessment. Reliability and validity studies were carried out by internal consistency testing (Cronbach’s alpha, Guttman split-half correlation model, Pearson correlation coefficient, and confirmatory factor analysis. Associations between General Functioning of the Family and variables theoretically associated with the theme (father’s or mother’s drunkenness and violence between parents were estimated by odds ratio. RESULTS Semantic equivalence was between 90.0% and 100%. Cronbach’s alpha ranged from 0.79 to 0.81, indicating good internal consistency of the instrument. Pearson correlation coefficient ranged between 0.303 and 0.549. Statistical association was found between the general functioning of the family score and the theoretically related variables, as well as good fit quality of the confirmatory analysis model. CONCLUSIONS The results indicate the feasibility of administering the instrument to the Brazilian population, as it is easy to understand and a good measurement of the construct of interest.

Semiclassical analysis spectral correlations in mesoscopic systems

International Nuclear Information System (INIS)

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

1991-07-01

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

On the origin of long-range correlations in texts.

Science.gov (United States)

Altmann, Eduardo G; Cristadoro, Giampaolo; Esposti, Mirko Degli

2012-07-17

The complexity of human interactions with social and natural phenomena is mirrored in the way we describe our experiences through natural language. In order to retain and convey such a high dimensional information, the statistical properties of our linguistic output has to be highly correlated in time. An example are the robust observations, still largely not understood, of correlations on arbitrary long scales in literary texts. In this paper we explain how long-range correlations flow from highly structured linguistic levels down to the building blocks of a text (words, letters, etc..). By combining calculations and data analysis we show that correlations take form of a bursty sequence of events once we approach the semantically relevant topics of the text. The mechanisms we identify are fairly general and can be equally applied to other hierarchical settings.

CORRELATION BETWEEN RAINFALL PATTERNS AND THE WATER TABLE IN THE GENERAL SEPARATIONS AREA OF THE SAVANNAH RIVER SITE

International Nuclear Information System (INIS)

Smith, C.

2009-01-01

The objective of the study was to evaluate rainfall and water table elevation data in search of a correlation that could be used to understand and predict water elevation changes. This information will be useful in placing screen zones for future monitoring wells and operations of groundwater treatment units. Fifteen wells in the General Separations Area (GSA) at Savannah River Site were evaluated from 1986 through 2001. The study revealed that the water table does respond to rainfall with minimal delay. (Water level information was available monthly, which restricted the ability to evaluate a shorter delay period.) Water elevations were found to be related to the cumulative sum (Q-Delta Sum) of the difference between the average rainfall for a specific month and the actual rainfall for that month, calculated from an arbitrary starting point. Water table elevations could also be correlated between wells, but using the right well for correlation was very important. The strongest correlation utilized a quadratic equation that takes into account the rainfall in a specific area and the rainfall from an adjacent area that contributes through a horizontal flow. Specific values vary from well to well as a result of geometry and underground variations. R2's for the best models ranged up to 0.96. The data in the report references only GSA wells but other wells (including confined water tables) on the site have been observed to return similar water level fluctuation patterns

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.

Lectures on general quantum correlations and their applications

CERN Document Server

Pinto, Diogo; Adesso, Gerardo

2017-01-01

This book presents a distinctive way of understanding quantum correlations beyond entanglement, introducing readers to this less explored yet very fundamental aspect of quantum theory. It takes into account most of the new ideas involving quantum phenomena, resources, and applications without entanglement, both from a theoretical and an experimental point of view. This book serves as a reference for both beginner students and experienced researchers in physics and applied mathematics, with an interest in joining this novel venture towards understanding the quantum nature of the world.

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

Energy Technology Data Exchange (ETDEWEB)

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

1993-07-15

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

Generalized Multi-Edge Analysis for K-Edge Densitometry

International Nuclear Information System (INIS)

Collins, M.

1998-01-01

In K-edge densitometry (KED), a continuous-energy x-ray beam is transmitted through a liquid sample. The actinide content of the sample can be measured through analysis of the transmitted portion of the x-ray beam. Traditional methods for KED analysis allow the simultaneous calculation of, at most, two actinide concentrations. A generalized multi-edge KED analytical method is presented, allowing up to six actinide concentrations to be calculated simultaneously. Applications of this method for hybrid KED/x-ray fluorescence (HKED) systems are discussed. Current HKED systems require the operator to know the approximate actinide content of each sample, and manually select the proper analysis mode. The new multi-edge KED technique allows rapid identification of the major actinide components in a sample, independent of actinide content. The proper HKED analysis mode can be selected automatically, without requiring sample content information from the user. Automatic HKED analysis would be especially useful in an analytical laboratory setting, where samples with truly unknown characteristics are encountered. Because this technique requires no hardware modifications, several facilities that use HKED may eventually benefit from this approach

A general psychopathology factor in early adolescence.

Science.gov (United States)

Patalay, Praveetha; Fonagy, Peter; Deighton, Jessica; Belsky, Jay; Vostanis, Panos; Wolpert, Miranda

2015-07-01

Recently, a general psychopathology dimension reflecting common aspects among disorders has been identified in adults. This has not yet been considered in children and adolescents, where the focus has been on externalising and internalising dimensions. To examine the existence, correlates and predictive value of a general psychopathology dimension in young people. Alternative factor models were estimated using self-reports of symptoms in a large community-based sample aged 11-13.5 years (N = 23 477), and resulting dimensions were assessed in terms of associations with external correlates and future functioning. Both a traditional two-factor model and a bi-factor model with a general psychopathology bi-factor fitted the data well. The general psychopathology bi-factor best predicted future psychopathology and academic attainment. Associations with correlates and factor loadings are discussed. A general psychopathology factor, which is equal across genders, can be identified in young people. Its associations with correlates and future functioning indicate that investigating this factor can increase our understanding of the aetiology, risk and correlates of psychopathology. © The Royal College of Psychiatrists 2015.

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

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

Science.gov (United States)

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

2018-05-01

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

Statistical analysis of medical data using SAS

CERN Document Server

Der, Geoff

2005-01-01

An Introduction to SASDescribing and Summarizing DataBasic InferenceScatterplots Correlation: Simple Regression and SmoothingAnalysis of Variance and CovarianceMultiple RegressionLogistic RegressionThe Generalized Linear ModelGeneralized Additive ModelsNonlinear Regression ModelsThe Analysis of Longitudinal Data IThe Analysis of Longitudinal Data II: Models for Normal Response VariablesThe Analysis of Longitudinal Data III: Non-Normal ResponseSurvival AnalysisAnalysis Multivariate Date: Principal Components and Cluster AnalysisReferences

Canonical Information Analysis

DEFF Research Database (Denmark)

Vestergaard, Jacob Schack; Nielsen, Allan Aasbjerg

2015-01-01

is replaced by the information theoretical, entropy based measure mutual information, which is a much more general measure of association. We make canonical information analysis feasible for large sample problems, including for example multispectral images, due to the use of a fast kernel density estimator......Canonical correlation analysis is an established multivariate statistical method in which correlation between linear combinations of multivariate sets of variables is maximized. In canonical information analysis introduced here, linear correlation as a measure of association between variables...... for entropy estimation. Canonical information analysis is applied successfully to (1) simple simulated data to illustrate the basic idea and evaluate performance, (2) fusion of weather radar and optical geostationary satellite data in a situation with heavy precipitation, and (3) change detection in optical...

Neutron activation analysis with k0-standardisation : general formalism and procedure

International Nuclear Information System (INIS)

Pomme, S.; Hardeman, F.; Robouch, P.; Etxebarria, N.; Arana, G.

1997-09-01

Instrumental neutron activation analysis (INAA) with k 0 -standardisation is a powerful tool for multi-element analysis at a broad range of trace element concentrations. An overview is given of the basic principles, fundamental equations, and general procedure of this method. Different aspects of the description of the neutron activation reaction rate are discussed, applying the Hogdahl convention. A general activation-decay formula is derived and its application to INAA is demonstrated. Relevant k 0 -definitions for different activation decay schemes are summarised and upgraded to cases of extremely high fluxes. The main standardisation techniques for INAA are discussed, emphasizing the k 0 -standardisation. Some general aspects of the basic equipment and its calibration are discussed, such as the characterisation of the neutron field and the tuning of the spectrometry part. A method for the prediction and optimisation of the analytical performance of INAA is presented

Correlation with liver scintigram, reticuloendothelial function test, plasma endotoxin level and liver function tests in chronic liver diseases. Multivariate analysis

Energy Technology Data Exchange (ETDEWEB)

Ohmoto, Kenji; Yamamoto, Shinichi; Ideguchi, Seiji and others

1989-02-01

Liver scintigrams with Tc-99m phytate were reviewed in a total of 64 consecutive patients, comprising 28 with chronic hepatitis and 36 with liver cirrhosis. Reticuloendothelial (RES) function, plasma endotoxin (Et) levels and findings of general liver function tests were used as reference parameters to determine the diagnostic ability of liver scintigraphy. Multivariate analyses revealed that liver scintigrams had a strong correlation with RES function and Et levels in terms of morphology of the liver and hepatic and bone marrow Tc-99m uptake. General liver function tests revealed gamma globulin to be correlated with hepatic uptake and the degree of splenogemaly on liver scintigrams; and ICG levels at 15 min to be correlated with bone marrow and splenic uptake. Accuracy of liver scintigraphy was 73% for chronic hepatitis, which was inferior to general liver function tests (83%). When both modalities were combined, diangostic accuracy increased to 95%. Liver scintigraphy seems to be useful as a complementary approach. (Namekawa, K).

Meta-Analysis of the Correlation between Apparent Diffusion Coefficient and Standardized Uptake Value in Malignant Disease

Directory of Open Access Journals (Sweden)

Shengming Deng

2017-01-01

Full Text Available The objective of this meta-analysis is to explore the correlation between the apparent diffusion coefficient (ADC on diffusion-weighted MR and the standard uptake value (SUV of 18F-FDG on PET/CT in patients with cancer. Databases such as PubMed (MEDLINE included, EMBASE, and Cochrane Database of Systematic Review were searched for relevant original articles that explored the correlation between SUV and ADC in English. After applying Fisher’s r-to-z transformation, correlation coefficient (r values were extracted from each study and 95% confidence intervals (CIs were calculated. Sensitivity and subgroup analyses based on tumor type were performed to investigate the potential heterogeneity. Forty-nine studies were eligible for the meta-analysis, comprising 1927 patients. Pooled r for all studies was −0.35 (95% CI: −0.42–0.28 and exhibited a notable heterogeneity (I2 = 78.4%; P < 0.01. In terms of the cancer type subgroup analysis, combined correlation coefficients of ADC/SUV range from −0.12 (lymphoma, n = 5 to −0.59 (pancreatic cancer, n = 2. We concluded that there is an average negative correlation between ADC and SUV in patients with cancer. Higher correlations were found in the brain tumor, cervix carcinoma, and pancreas cancer. However, a larger, prospective study is warranted to validate these findings in different cancer types.

Linking Brief Functional Analysis to Intervention Design in General Education Settings

Science.gov (United States)

Ishuin, Tifanie

2009-01-01

This study focused on the utility and applicability of brief functional analysis in general education settings. The purpose of the study was to first identify the environmental variables maintaining noncompliance through a brief functional analysis, and then to design and implement a functionally equivalent intervention. The participant exhibited…

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

Science.gov (United States)

Macmann, Gregg M.; Barnett, David W.

1994-01-01

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

Kinetic equations with pairing correlations

International Nuclear Information System (INIS)

Fauser, R.

1995-12-01

The Gorkov equations are derived for a general non-equilibrium system. The Gorkov factorization is generalized by the cumulant expansion of the 2-particle correlation and by a generalized Wick theorem in the case of a perturbation expansion. A stationary solution for the Green functions in the Schwinger-Keldysh formalism is presented taking into account pairing correlations. Especially the effects of collisional broadening on the spectral functions and Green functions is discussed. Kinetic equations are derived in the quasi-particle approximation and in the case of particles with width. Explicit expressions for the self-energies are given. (orig.)

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

International Nuclear Information System (INIS)

Zhang Weigang

2000-01-01

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

Application of generalized estimating equations to a study in vitro of radiation sensitivity

International Nuclear Information System (INIS)

Cologne, J.B.; Carter, R.L.; Fujita, Shoichiro; Ban, Sadayuki.

1993-08-01

We describes an application of the generalized estimating equation (GEE) method (Liang K-Y, Zeger SL: Longitudinal data analysis using generalized linear models. Biometrika 73:13-22, 1986) for regression analyses of correlated Poisson data. As an alternative to the use of an arbitrarily chosen working correlation matrix, we demonstrate the use of GEE with a reasonable model for the true covariance structure among repeated observations within individuals. We show that, under such a split-plot design with large clusters, the asymptotic relative efficiency of GEE with simple (independence or exchangeable) working correlation matrices is rather low. We also illustrate the use of GEE with an empirically estimated model for overdispersion in a large study of radiation sensitivity where cluster size is small and a simple working correlation structure is sufficient. We conclude by summarizing issues and needs for further work concerning efficiency of the GEE parameter estimates in practice. (author)

Python tools for rapid development, calibration, and analysis of generalized groundwater-flow models

Science.gov (United States)

Starn, J. J.; Belitz, K.

2014-12-01

National-scale water-quality data sets for the United States have been available for several decades; however, groundwater models to interpret these data are available for only a small percentage of the country. Generalized models may be adequate to explain and project groundwater-quality trends at the national scale by using regional scale models (defined as watersheds at or between the HUC-6 and HUC-8 levels). Coast-to-coast data such as the National Hydrologic Dataset Plus (NHD+) make it possible to extract the basic building blocks for a model anywhere in the country. IPython notebooks have been developed to automate the creation of generalized groundwater-flow models from the NHD+. The notebook format allows rapid testing of methods for model creation, calibration, and analysis. Capabilities within the Python ecosystem greatly speed up the development and testing of algorithms. GeoPandas is used for very efficient geospatial processing. Raster processing includes the Geospatial Data Abstraction Library and image processing tools. Model creation is made possible through Flopy, a versatile input and output writer for several MODFLOW-based flow and transport model codes. Interpolation, integration, and map plotting included in the standard Python tool stack also are used, making the notebook a comprehensive platform within on to build and evaluate general models. Models with alternative boundary conditions, number of layers, and cell spacing can be tested against one another and evaluated by using water-quality data. Novel calibration criteria were developed by comparing modeled heads to land-surface and surface-water elevations. Information, such as predicted age distributions, can be extracted from general models and tested for its ability to explain water-quality trends. Groundwater ages then can be correlated with horizontal and vertical hydrologic position, a relation that can be used for statistical assessment of likely groundwater-quality conditions

Inheritance of grain yield and its correlation with yield components in ...

African Journals Online (AJOL)

SAM

2014-03-19

Mar 19, 2014 ... 7 × 7 incomplete diallel cross of seven wheat parents during the crop season of 2009 to 2010. Mean square of general ... Genetic background and yield traits of the seven parents. Parent. Pedigree. Released year ..... Correlation and path analysis for yield and yield contributing characters in wheat (Triticum ...

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

Whole-tumour diffusion kurtosis MR imaging histogram analysis of rectal adenocarcinoma: Correlation with clinical pathologic prognostic factors.

Science.gov (United States)

Cui, Yanfen; Yang, Xiaotang; Du, Xiaosong; Zhuo, Zhizheng; Xin, Lei; Cheng, Xintao

2018-04-01

To investigate potential relationships between diffusion kurtosis imaging (DKI)-derived parameters using whole-tumour volume histogram analysis and clinicopathological prognostic factors in patients with rectal adenocarcinoma. 79 consecutive patients who underwent MRI examination with rectal adenocarcinoma were retrospectively evaluated. Parameters D, K and conventional ADC were measured using whole-tumour volume histogram analysis. Student's t-test or Mann-Whitney U-test, receiver operating characteristic curves and Spearman's correlation were used for statistical analysis. Almost all the percentile metrics of K were correlated positively with nodal involvement, higher histological grades, the presence of lymphangiovascular invasion (LVI) and circumferential margin (CRM) (phistogram analysis, especially K parameters, were associated with important prognostic factors of rectal cancer. • K correlated positively with some important prognostic factors of rectal cancer. • K mean showed higher AUC and specificity for differentiation of nodal involvement. • DKI metrics with whole-tumour volume histogram analysis depicted tumour heterogeneity.

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)

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)

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.

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

International Nuclear Information System (INIS)

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

2013-01-01

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

Generalization of the Fourier Convergence Analysis in the Neutron Diffusion Eigenvalue Problem

International Nuclear Information System (INIS)

Lee, Hyun Chul; Noh, Jae Man; Joo, Hyung Kook

2005-01-01

Fourier error analysis has been a standard technique for the stability and convergence analysis of linear and nonlinear iterative methods. Lee et al proposed new 2- D/1-D coupling methods and demonstrated several advantages of the new methods by performing a Fourier convergence analysis of the methods as well as two existing methods for a fixed source problem. We demonstrated the Fourier convergence analysis of one of the 2-D/1-D coupling methods applied to a neutron diffusion eigenvalue problem. However, the technique cannot be used directly to analyze the convergence of the other 2-D/1-D coupling methods since some algorithm-specific features were used in our previous study. In this paper we generalized the Fourier convergence analysis technique proposed and analyzed the convergence of the 2-D/1-D coupling methods applied to a neutron diffusion Eigenvalue problem using the generalized technique

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

Science.gov (United States)

Nielsen, Allan Aasbjerg

2002-01-01

This paper describes two- and multiset canonical correlations analysis (CCA) for data fusion, multisource, multiset, or multitemporal exploratory data analysis. These techniques transform multivariate multiset data into new orthogonal variables called canonical variates (CVs) which, when applied in remote sensing, exhibit ever-decreasing similarity (as expressed by correlation measures) over sets consisting of 1) spectral variables at fixed points in time (R-mode analysis), or 2) temporal variables with fixed wavelengths (T-mode analysis). The CVs are invariant to linear and affine transformations of the original variables within sets which means, for example, that the R-mode CVs are insensitive to changes over time in offset and gain in a measuring device. In a case study, CVs are calculated from Landsat Thematic Mapper (TM) data with six spectral bands over six consecutive years. Both Rand T-mode CVs clearly exhibit the desired characteristic: they show maximum similarity for the low-order canonical variates and minimum similarity for the high-order canonical variates. These characteristics are seen both visually and in objective measures. The results from the multiset CCA R- and T-mode analyses are very different. This difference is ascribed to the noise structure in the data. The CCA methods are related to partial least squares (PLS) methods. This paper very briefly describes multiset CCA-based multiset PLS. Also, the CCA methods can be applied as multivariate extensions to empirical orthogonal functions (EOF) techniques. Multiset CCA is well-suited for inclusion in geographical information systems (GIS).

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