Multiview Bayesian Correlated Component Analysis
DEFF Research Database (Denmark)
Kamronn, Simon Due; Poulsen, Andreas Trier; Hansen, Lars Kai
2015-01-01
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....... 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...
Interpretation of correlation analysis results
Kılıç, Selim
2012-01-01
Correlation analysis is used to quantify the degree of linear association between two variables. Correlation coefficient is showed as “r” and it may have values between (-) 1 and (+)1. The symbols (-) or (+) in front of “r coefficient” show the direction of correlation. The direction of association does not affect the strength of association. A “ r coefficient” which is equal or greater than 0.70 is accepted as a good association. Correlation coeefficient only remarks the strength of associat...
Analysis of Negative Correlation Learning
Institute of Scientific and Technical Information of China (English)
Liu Yong; Zou Xiu-fen
2003-01-01
This paper describes negative correlation learning for designing neural network ensembles. Negative correlation learning has been firstly analysed in terms of minimising mutual information on a regression task. By ninimising the mutual information between variables extracted by two neural networks, they are forced to convey different information about some features of their input. Based on the decision boundaries and correct response sets, negative correlation learning has been further studied on two pattern classification problems. The purpose of examining the decision boundaries and the correct response sets is not only to illustrate the learning behavior of negative correlation learning, but also to cast light on how to design more effective neural network ensembles. The experimental results showed the decision boundary of the trained neural network ensemble by negative correlation learning is almost as good as the optimum decision boundary.
Spectral analysis by correlation; Analyse spectrale par correlation
Energy Technology Data Exchange (ETDEWEB)
Fauque, J.M.; Berthier, D.; Max, J.; Bonnet, G. [Commissariat a l' Energie Atomique, Grenoble (France). Centre d' Etudes Nucleaires
1969-07-01
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) [French] La densite spectrale d'un signal qui represente la repartition de sa puissance sur l'axe des frequences est une fonction de premiere importance, constamment utilisee dans tout ce qui touche le traitement du signal (identification de processus, analyse de vibrations, etc...). Parmi toutes les methodes possibles de calcul de cette fonction, la methode par correlation (calcul de la fonction de correlation + transformation de Fourier) est tres seduisante par sa simplicite et ses performances. L'etude qui est faite ici va deboucher sur la realisation d'un appareil qui, couple a un correlateur, constituera un ensemble d'analyse spectrale en temps reel couvrant la gamme de frequence 0 a 5 MHz. (auteur)
AN IMPROVED ALGORITHM FOR DPIV CORRELATION ANALYSIS
Institute of Scientific and Technical Information of China (English)
WU Long-hua
2007-01-01
In a Digital Particle Image Velocimetry (DPIV) system, the correlation of digital images is normally used to acquire the displacement information of particles and give estimates of the flow field. The accuracy and robustness of the correlation algorithm directly affect the validity of the analysis result. In this article, an improved algorithm for the correlation analysis was proposed which could be used to optimize the selection/determination of the correlation window, analysis area and search path. This algorithm not only reduces largely the amount of calculation, but also improves effectively the accuracy and reliability of the correlation analysis. The algorithm was demonstrated to be accurate and efficient in the measurement of the velocity field in a flocculation pool.
Detrended cross-correlation analysis of electroencephalogram
Institute of Scientific and Technical Information of China (English)
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.
Regularized canonical correlation analysis with unlabeled data
Institute of Scientific and Technical Information of China (English)
Xi-chuan ZHOU; Hai-bin SHEN
2009-01-01
In standard canonical correlation analysis (CCA), the data from definite datasets are used to estimate their canonical correlation. In real applications, for example in bilingual text retrieval, it may have a great portion of data that we do not know which set it belongs to. This part of data is called unlabeled data, while the rest from definite datasets is called labeled data. We propose a novel method called regularized canonical correlation analysis (RCCA), which makes use of both labeled and unlabeled samples. Specifically, we learn to approximate canonical correlation as if all data were labeled. Then. we describe a generalization of RCCA for the multi-set situation. Experiments on four real world datasets, Yeast, Cloud, Iris, and Haberman, demonstrate that,by incorporating the unlabeled data points, the accuracy of correlation coefficients can be improved by over 30%.
WenJun Zhang; Xin Li
2015-01-01
Between-taxon interactions can be detected by calculating the sampling data of taxon sample type. In present study, Spearman rank correlation and proportion correlation are chosen as the general correlation measures, and their partial correlations are calculated and compared. The results show that for Spearman rank correlation measure, in all predicted candidate direct interactions by partial correlation, about 16.77% (x, 0-45.4%) of them are not successfully detected by Spearman rank correla...
Correlated Data Analysis Modeling, Analytics, and Applications
Song, Peter X-K
2007-01-01
Presents developments in correlated data analysis. This book provides a systematic treatment for the topic of estimating functions. In addition to marginal models and mixed-effects models, it covers topics on joint regression analysis based on Gaussian copulas and generalized state space models for longitudinal data from long time series.
Regularized Multiple-Set Canonical Correlation Analysis
Takane, Yoshio; Hwang, Heungsun; Abdi, Herve
2008-01-01
Multiple-set canonical correlation analysis (Generalized CANO or GCANO for short) is an important technique because it subsumes a number of interesting multivariate data analysis techniques as special cases. More recently, it has also been recognized as an important technique for integrating information from multiple sources. In this paper, we…
Generalized canonical correlation analysis with missing values
M. van de Velden (Michel); Y. Takane
2009-01-01
textabstractTwo new methods for dealing with missing values in generalized canonical correlation analysis are introduced. The first approach, which does not require iterations, is a generalization of the Test Equating method available for principal component analysis. In the second approach, missing
Refined Multifractal Cross-Correlation Analysis
Oświȩcimka, Paweł; Forczek, Marcin; Jadach, Stanisław; Kwapień, Jarosław
2013-01-01
We propose a modified algorithm - Multifractal Cross-Correlation Analysis (MFCCA) - that is able to consistently identify and quantify multifractal cross-correlations between two time series. Our motivation for introducing this algorithm is that the already existing methods like MF-DXA have serious limitations for most of the signals describing complex natural processes. The principal component of the related improvement is proper incorporation of the sign of fluctuations. We present a broad analysis of the model fractal stochastic processes as well as of the real-world signals and show that MFCCA is a robust tool and allows a reliable quantification of the cross-correlative structure of analyzed processes. We, in particular, analyze a relation between the generalized Hurst exponent and the MFCCA parameter $\\lambda_q$. This relation provides information about the character of potential multifractality in cross-correlations of the processes under study and thus enables selective insight into their dynamics. Us...
Multivariate Longitudinal Analysis with Bivariate Correlation Test.
Adjakossa, Eric Houngla; Sadissou, Ibrahim; Hounkonnou, Mahouton Norbert; Nuel, Gregory
2016-01-01
In the context of multivariate multilevel data analysis, this paper focuses on the multivariate linear mixed-effects model, including all the correlations between the random effects when the dimensional residual terms are assumed uncorrelated. Using the EM algorithm, we suggest more general expressions of the model's parameters estimators. These estimators can be used in the framework of the multivariate longitudinal data analysis as well as in the more general context of the analysis of multivariate multilevel data. By using a likelihood ratio test, we test the significance of the correlations between the random effects of two dependent variables of the model, in order to investigate whether or not it is useful to model these dependent variables jointly. Simulation studies are done to assess both the parameter recovery performance of the EM estimators and the power of the test. Using two empirical data sets which are of longitudinal multivariate type and multivariate multilevel type, respectively, the usefulness of the test is illustrated.
Face hallucination using orthogonal canonical correlation analysis
Zhou, Huiling; Lam, Kin-Man
2016-05-01
A two-step face-hallucination framework is proposed to reconstruct a high-resolution (HR) version of a face from an input low-resolution (LR) face, based on learning from LR-HR example face pairs using orthogonal canonical correlation analysis (orthogonal CCA) and linear mapping. In the proposed algorithm, face images are first represented using principal component analysis (PCA). Canonical correlation analysis (CCA) with the orthogonality property is then employed, to maximize the correlation between the PCA coefficients of the LR and the HR face pairs to improve the hallucination performance. The original CCA does not own the orthogonality property, which is crucial for information reconstruction. We propose using orthogonal CCA, which is proven by experiments to achieve a better performance in terms of global face reconstruction. In addition, in the residual-compensation process, a linear-mapping method is proposed to include both the inter- and intrainformation about manifolds of different resolutions. Compared with other state-of-the-art approaches, the proposed framework can achieve a comparable, or even better, performance in terms of global face reconstruction and the visual quality of face hallucination. Experiments on images with various parameter settings and blurring distortions show that the proposed approach is robust and has great potential for real-world applications.
Gait Correlation Analysis Based Human Identification
Directory of Open Access Journals (Sweden)
Jinyan Chen
2014-01-01
Full Text Available Human gait identification aims to identify people by a sequence of walking images. Comparing with fingerprint or iris based identification, the most important advantage of gait identification is that it can be done at a distance. In this paper, silhouette correlation analysis based human identification approach is proposed. By background subtracting algorithm, the moving silhouette figure can be extracted from the walking images sequence. Every pixel in the silhouette has three dimensions: horizontal axis (x, vertical axis (y, and temporal axis (t. By moving every pixel in the silhouette image along these three dimensions, we can get a new silhouette. The correlation result between the original silhouette and the new one can be used as the raw feature of human gait. Discrete Fourier transform is used to extract features from this correlation result. Then, these features are normalized to minimize the affection of noise. Primary component analysis method is used to reduce the features’ dimensions. Experiment based on CASIA database shows that this method has an encouraging recognition performance.
Metrics correlation and analysis service (MCAS)
Energy Technology Data Exchange (ETDEWEB)
Baranovski, Andrew; Dykstra, Dave; Garzoglio, Gabriele; Hesselroth, Ted; Mhashilkar, Parag; Levshina, Tanya; /Fermilab
2009-05-01
The complexity of Grid workflow activities and their associated software stacks inevitably involves multiple organizations, ownership, and deployment domains. In this setting, important and common tasks such as the correlation and display of metrics and debugging information (fundamental ingredients of troubleshooting) are challenged by the informational entropy inherent to independently maintained and operated software components. Because such an information 'pond' is disorganized, it a difficult environment for business intelligence analysis i.e. troubleshooting, incident investigation and trend spotting. The mission of the MCAS project is to deliver a software solution to help with adaptation, retrieval, correlation, and display of workflow-driven data and of type-agnostic events, generated by disjoint middleware.
Multivariate Longitudinal Analysis with Bivariate Correlation Test
Adjakossa, Eric Houngla; Sadissou, Ibrahim; Hounkonnou, Mahouton Norbert; Nuel, Gregory
2016-01-01
In the context of multivariate multilevel data analysis, this paper focuses on the multivariate linear mixed-effects model, including all the correlations between the random effects when the dimensional residual terms are assumed uncorrelated. Using the EM algorithm, we suggest more general expressions of the model’s parameters estimators. These estimators can be used in the framework of the multivariate longitudinal data analysis as well as in the more general context of the analysis of multivariate multilevel data. By using a likelihood ratio test, we test the significance of the correlations between the random effects of two dependent variables of the model, in order to investigate whether or not it is useful to model these dependent variables jointly. Simulation studies are done to assess both the parameter recovery performance of the EM estimators and the power of the test. Using two empirical data sets which are of longitudinal multivariate type and multivariate multilevel type, respectively, the usefulness of the test is illustrated. PMID:27537692
Genome-wide analysis correlates Ayurveda Prakriti.
Govindaraj, Periyasamy; Nizamuddin, Sheikh; Sharath, Anugula; Jyothi, Vuskamalla; Rotti, Harish; Raval, Ritu; Nayak, Jayakrishna; Bhat, Balakrishna K; Prasanna, B V; Shintre, Pooja; Sule, Mayura; Joshi, Kalpana S; Dedge, Amrish P; Bharadwaj, Ramachandra; Gangadharan, G G; Nair, Sreekumaran; Gopinath, Puthiya M; Patwardhan, Bhushan; Kondaiah, Paturu; Satyamoorthy, Kapaettu; Valiathan, Marthanda Varma Sankaran; Thangaraj, Kumarasamy
2015-10-29
The practice of Ayurveda, the traditional medicine of India, is based on the concept of three major constitutional types (Vata, Pitta and Kapha) defined as "Prakriti". To the best of our knowledge, no study has convincingly correlated genomic variations with the classification of Prakriti. In the present study, we performed genome-wide SNP (single nucleotide polymorphism) analysis (Affymetrix, 6.0) of 262 well-classified male individuals (after screening 3416 subjects) belonging to three Prakritis. We found 52 SNPs (p ≤ 1 × 10(-5)) were significantly different between Prakritis, without any confounding effect of stratification, after 10(6) permutations. Principal component analysis (PCA) of these SNPs classified 262 individuals into their respective groups (Vata, Pitta and Kapha) irrespective of their ancestry, which represent its power in categorization. We further validated our finding with 297 Indian population samples with known ancestry. Subsequently, we found that PGM1 correlates with phenotype of Pitta as described in the ancient text of Caraka Samhita, suggesting that the phenotypic classification of India's traditional medicine has a genetic basis; and its Prakriti-based practice in vogue for many centuries resonates with personalized medicine.
Interpreting canonical correlation analysis through biplots of stucture correlations and weights
Braak, ter C.J.F.
1990-01-01
This paper extends the biplot technique to canonical correlation analysis and redundancy analysis. The plot of structure correlations is shown to the optimal for displaying the pairwise correlations between the variables of the one set and those of the second. The link between multivariate regressio
Asymmetric matrices in an analysis of financial correlations
2006-01-01
Financial markets are highly correlated systems that reveal both the inter-market dependencies and the correlations among their different components. Standard analyzing techniques include correlation coefficients for pairs of signals and correlation matrices for rich multivariate data. In the latter case one constructs a real symmetric matrix with real non-negative eigenvalues describing the correlation structure of the data. However, if one performs a correlation-function-like analysis of mu...
A New Methodology of Spatial Cross-Correlation Analysis
Chen, Yanguang
2015-01-01
Spatial correlation modeling comprises both spatial autocorrelation and spatial cross-correlation processes. The spatial autocorrelation theory has been well-developed. It is necessary to advance the method of spatial cross-correlation analysis to supplement the autocorrelation analysis. This paper presents a set of models and analytical procedures for spatial cross-correlation analysis. By analogy with Moran’s index newly expressed in a spatial quadratic form, a theoretical framework is 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
Analysis of Baryon Angular Correlations with Pythia
Mccune, Amara
2017-01-01
Our current understanding of baryon production is encompassed in the framework of the Lund String Fragmentation Model, which is then encoded in the Monte Carlo event generator program Pythia. In proton-proton collisions, daughter particles of the same baryon number produce an anti-correlation in $\\Delta\\eta\\Delta\\varphi$ space in ALICE data, while Pythia programs predict a correlation. To understand this unusual effect, where it comes from, and where our models of baryon production go wrong, correlation functions were systematically generated with Pythia. Effects of energy scaling, color reconnection, and popcorn parameters were investigated.
Reliability Distribution of Numerical Control Lathe Based on Correlation Analysis
Institute of Scientific and Technical Information of China (English)
Xiaoyan Qi; Guixiang Shen; Yingzhi Zhang; Shuguang Sun; Bingkun Chen
2016-01-01
Combined Reliability distribution with correlation analysis, a new method has been proposed to make Reliability distribution where considering the elements about structure correlation and failure correlation of subsystems. Firstly, we make a sequence for subsystems by means of TOPSIS which comprehends the considerations of Reliability allocation, and introducing a Copula connecting function to set up a distribution model based on structure correlation, failure correlation and target correlation, and then acquiring reliability target area of all subsystems by Matlab. In this method, not only the traditional distribution considerations are concerned, but also correlation influences are involved, to achieve supplementing information and optimizing distribution.
Premaceral contents of peats correlated with proximate and ultimate analysis
Energy Technology Data Exchange (ETDEWEB)
Cohen, A.D.; Andrejko, M.J.
1983-01-01
Preliminary correlations of petrographic characteristics of peats (i.e., peat types, premaceral proportions, and premaceral types) with proximate analysis, ultimate analysis, and Btu content are reported. These correlations suggest the following trends: (1) peats with the highest proportions of birefringent macerals tend to have highest volatile matter (and H and O contents); (2) fluorescence of macerals seems to correlate only slightly with proximate and ultimate analyses; (3) higher previtrinite contents tend to correlate with higher volatile matter contents; (4) peats with higher preinertinities, prephlobaphenites (and precorpocollinites), and presclerotinites have the highest fixed carbon; and (5) Btu correlates strongly with ash content and only slightly with maceral content. (BLM)
Elastic sequence correlation for human action analysis.
Wang, Li; Cheng, Li; Wang, Liang
2011-06-01
This paper addresses the problem of automatically analyzing and understanding human actions from video footage. An "action correlation" framework, elastic sequence correlation (ESC), is proposed to identify action subsequences from a database of (possibly long) video sequences that are similar to a given query video action clip. In particular, we show that two well-known algorithms, namely approximate pattern matching in computer and information sciences and dynamic time warping (DTW) method in signal processing, are special cases of our ESC framework. The proposed framework is applied to two important real-world applications: action pattern retrieval, as well as action segmentation and recognition, where, on average, its run time speed (in matlab) is about 3.3 frames per second. In addition, comparing with the state-of-the-art algorithms on a number of challenging data sets, our approach is demonstrated to perform competitively.
OPERATIONAL MODAL ANALYSIS SCHEMES USING CORRELATION TECHNIQUE
Institute of Scientific and Technical Information of China (English)
Zheng Min; Shen Fan; Chen Huaihai
2005-01-01
For some large-scale engineering structures in operating conditions, modal parameters estimation must base itself on response-only data. This problem has received a considerable amount of attention in the past few years. It is well known that the cross-correlation function between the measured responses is a sum of complex exponential functions of the same form as the impulse response function of the original system. So this paper presents a time-domain operating modal identification global scheme and a frequency-domain scheme from output-only by coupling the cross-correlation function with conventional modal parameter estimation. The outlined techniques are applied to an airplane model to estimate modal parameters from response-only data.
Asymmetric matrices in an analysis of financial correlations
Kwapien, J; Górski, A Z; Oswiecimka, P
2006-01-01
Financial markets are highly correlated systems that reveal both the inter-market dependencies and the correlations among their different components. Standard analyzing techniques include correlation coefficients for pairs of signals and correlation matrices for rich multivariate data. In the latter case one constructs a real symmetric matrix with real non-negative eigenvalues describing the correlation structure of the data. However, if one performs a correlation-function-like analysis of multivariate data, when a stress is put on investigation of delayed dependencies among different types of signals, one can calculate an asymmetric correlation matrix with complex eigenspectrum. From the Random Matrix Theory point of view this kind of matrices is closely related to Ginibre Orthogonal Ensemble (GinOE). We present an example of practical application of such matrices in correlation analyses of empirical data. By introducing the time lag, we are able to identify temporal structure of the inter-market correlation...
Handwriting: Feature Correlation Analysis for Biometric Hashes
Directory of Open Access Journals (Sweden)
Ralf Steinmetz
2004-04-01
Full Text Available In the application domain of electronic commerce, biometric authentication can provide one possible solution for the key management problem. Besides server-based approaches, methods of deriving digital keys directly from biometric measures appear to be advantageous. In this paper, we analyze one of our recently published specific algorithms of this category based on behavioral biometrics of handwriting, the biometric hash. Our interest is to investigate to which degree each of the underlying feature parameters contributes to the overall intrapersonal stability and interpersonal value space. We will briefly discuss related work in feature evaluation and introduce a new methodology based on three components: the intrapersonal scatter (deviation, the interpersonal entropy, and the correlation between both measures. Evaluation of the technique is presented based on two data sets of different size. The method presented will allow determination of effects of parameterization of the biometric system, estimation of value space boundaries, and comparison with other feature selection approaches.
Multifractal cross-correlation analysis in electricity spot market
Fan, Qingju; Li, Dan
2015-07-01
In this paper, we investigate the multiscale cross-correlations between electricity price and trading volume in Czech market based on a newly developed algorithm, called Multifractal Cross-Correlation Analysis (MFCCA). The new algorithm is a natural multifractal generalization of the Detrended Cross-Correlation Analysis (DCCA), and is sensitive to cross-correlation structure and free from limitations of other algorithms. By considering the original sign of the cross-covariance, it allows us to properly quantify and detect the subtle characteristics of two simultaneous recorded time series. First, the multifractality and the long range anti-persistent auto-correlations of price return and trading volume variation are confirmed using Multifractal Detrended Fluctuation Analysis (MF-DFA). Furthermore, we show that there exist long-range anti-persistent cross-correlations between price return and trading volume variation by MFCCA. And we also identify that the cross-correlations disappear on the level of relative small fluctuations. In order to obtain deeper insight into the dynamics of the electricity market, we analyze the relation between generalized Hurst exponent and the multifractal cross-correlation scaling exponent λq. We find that the difference between the generalized Hurst exponent and the multifractal cross-correlation scaling exponent is significantly different for smaller fluctuation, which indicates that the multifractal character of cross-correlations resembles more each other for electricity price and trading volume on the level of large fluctuations and weakens for the smaller ones.
Sensitivity analysis of a sound absorption model with correlated inputs
Chai, W.; Christen, J.-L.; Zine, A.-M.; Ichchou, M.
2017-04-01
Sound absorption in porous media is a complex phenomenon, which is usually addressed with homogenized models, depending on macroscopic parameters. Since these parameters emerge from the structure at microscopic scale, they may be correlated. This paper deals with sensitivity analysis methods of a sound absorption model with correlated inputs. Specifically, the Johnson-Champoux-Allard model (JCA) is chosen as the objective model with correlation effects generated by a secondary micro-macro semi-empirical model. To deal with this case, a relatively new sensitivity analysis method Fourier Amplitude Sensitivity Test with Correlation design (FASTC), based on Iman's transform, is taken into application. This method requires a priori information such as variables' marginal distribution functions and their correlation matrix. The results are compared to the Correlation Ratio Method (CRM) for reference and validation. The distribution of the macroscopic variables arising from the microstructure, as well as their correlation matrix are studied. Finally the results of tests shows that the correlation has a very important impact on the results of sensitivity analysis. Assessment of correlation strength among input variables on the sensitivity analysis is also achieved.
Correlation and principal component analysis in ceramic tiles characterization
Directory of Open Access Journals (Sweden)
Podunavac-Kuzmanović Sanja O.
2015-01-01
Full Text Available The present study deals with the analysis of the characteristics of ceramic wall and floor tiles on the basis of their quality parameters: breaking force, flexural strenght, absorption and shrinking. Principal component analysis was applied in order to detect potential similarities and dissimilarities among the analyzed tile samples, as well as the firing regimes. Correlation analysis was applied in order to find correlations among the studied quality parameters of the tiles. The obtained results indicate particular differences between the samples on the basis of the firing regimes. However, the correlation analysis points out that there is no statistically significant correlation among the quality parameters of the studied samples of the wall and floor ceramic tiles.[Projekat Ministarstva nauke Republike Srbije, br. 172012 i br. III 45008
On the correlation analysis of electric field inside jet engine
A Krishna; Khattab, T.; Abdelaziz, A.F.; Guizani, M.
2014-01-01
A Simple channel modeling method based on correlation analysis of the electric field inside jet engine is presented. The analysis of the statistical propagation characteristics of electromagnetic field inside harsh jet engine environment is presented by using `Ansys® HFSS'. In this paper, we propose a method to locate the best position for receiving probes inside jet engine with minimum correlation between the receiver points which have strong average electric field. Moreover, a MIMO system c...
Multiscale Detrended Cross-Correlation Analysis of STOCK Markets
Yin, Yi; Shang, Pengjian
2014-06-01
In this paper, we employ the detrended cross-correlation analysis (DCCA) to investigate the cross-correlations between different stock markets. We report the results of cross-correlated behaviors in US, Chinese and European stock markets in period 1997-2012 by using DCCA method. The DCCA shows the cross-correlated behaviors of intra-regional and inter-regional stock markets in the short and long term which display the similarities and differences of cross-correlated behaviors simply and roughly and the persistence of cross-correlated behaviors of fluctuations. Then, because of the limitation and inapplicability of DCCA method, we propose multiscale detrended cross-correlation analysis (MSDCCA) method to avoid "a priori" selecting the ranges of scales over which two coefficients of the classical DCCA method are identified, and employ MSDCCA to reanalyze these cross-correlations to exhibit some important details such as the existence and position of minimum, maximum and bimodal distribution which are lost if the scale structure is described by two coefficients only and essential differences and similarities in the scale structures of cross-correlation of intra-regional and inter-regional markets. More statistical characteristics of cross-correlation obtained by MSDCCA method help us to understand how two different stock markets influence each other and to analyze the influence from thus two inter-regional markets on the cross-correlation in detail, thus we get a richer and more detailed knowledge of the complex evolutions of dynamics of the cross-correlations between stock markets. The application of MSDCCA is important to promote our understanding of the internal mechanisms and structures of financial markets and helps to forecast the stock indices based on our current results demonstrated the cross-correlations between stock indices. We also discuss the MSDCCA methods of secant rolling window with different sizes and, lastly, provide some relevant implications and
Model independent analysis of nearly L\\'evy correlations
Novák, T; Eggers, H C; de Kock, M
2016-01-01
A model-independent method for the analysis of the two-particle short-range correlations is presented, that can be utilized to describe e.g. Bose-Einstein (HBT), dynamical (ridge) or other correlation functions, that have a nearly L\\'evy or streched exponential shape. For the special case of L\\'evy exponent alpha = 1, the earlier Laguerre expansions are recovered, for the alpha = 2 special case, a new expansion method is obtained for nearly Gaussian correlation functions. Multi-dimensional L\\'evy expansions are also introduced and their potential application to analyze rigde correlation data is discussed.
Linear analysis of degree correlations in complex networks
Indian Academy of Sciences (India)
JU XIANG; TAO HU; YAN ZHANG; KE HU; YAN-NI TANG; YUAN-YUAN GAO; KE DENG
2016-12-01
Many real-world networks such as the protein–protein interaction networks and metabolic networks often display nontrivial correlations between degrees of vertices connected by edges. Here, we analyse the statistical methods used usually to describe the degree correlation in the networks, and analytically give linear relation in the degree correlation. It provides a simple and interesting perspective on the analysis of the degree correlation in networks, which is usefully complementary to the existing methods for degree correlation in networks. Especially, the slope in the linear relation corresponds exactly to the degree correlation coefficient in networks, meaning that it can not only characterize the level of degree correlation in networks, but also reflects the speed that the average nearest neighbours’ degree varies with the vertex degree. Finally, we applied our results to several real-world networks, validating the conclusions of the linear analysis of degree correlation. We hope that the work in this paper can be helpful for further understanding the degree correlation in complex networks.
Analysis and perturbation of degree correlation in complex networks
Xiang, Ju; Hu, Tao; Zhang, Yan
2015-01-01
Degree correlation is an important topological property common to many real-world networks. In this paper, the statistical measures for characterizing the degree correlation in networks are investigated analytically. We give an exact proof of the consistency for the statistical measures, reveal the general linear relation in the degree correlation, which provide a simple and interesting perspective on the analysis of the degree correlation in complex networks. By using the general linear analysis, we investigate the perturbation of the degree correlation in complex networks caused by the addition of few nodes and the rich club. The results show that the assortativity of homogeneous networks such as the ER graphs is easily to be affected strongly by the simple structural changes, while it has only slight variation for heterogeneous networks with broad degree distribution such as the scale-free networks. Clearly, the homogeneous networks are more sensitive for the perturbation than the heterogeneous networks.
Meta-Analysis of Correlations Among Usability Measures
DEFF Research Database (Denmark)
Hornbæk, Kasper Anders Søren; Effie Lai Chong, Law
2007-01-01
are generally low: effectiveness measures (e.g., errors) and efficiency measures (e.g., time) has a correlation of .247 ± .059 (Pearson's product-moment correlation with 95% confidence interval), efficiency and satisfaction (e.g., preference) one of .196 ± .064, and effectiveness and satisfaction one of .164......Understanding the relation between usability measures seems crucial to deepen our conception of usability and to select the right measures for usability studies. We present a meta-analysis of correlations among usability measures calculated from the raw data of 73 studies. Correlations...... ± .062. Changes in task complexity do not influence these correlations, but use of more complex measures attenuates them. Standard questionnaires for measuring satisfaction appear more reliable than homegrown ones. Measures of users' perceptions of phenomena are generally not correlated with objective...
[Electroencephalogram Feature Selection Based on Correlation Coefficient Analysis].
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.
Correlation Analysis between TCM Syndromes and Physicochemical Parameters
Institute of Scientific and Technical Information of China (English)
SUN Zhan-quan; XI Guang-cheng; Li Hai-xia; YI Jian-qiang; WANG jie
2006-01-01
Traditionally, differentiation of syndromes of Traditional Chinese Medicine (TCM) mainly depends on the information obtained from four diagnosis methods. Now many physicochemical parameters are available in clinic. There exists great correlation between TCM syndromes and physicochemical parameters.The objective of the paper is to analyze the correlation between TCM syndromes and physicochemical parameters quantitatively. Correlation analysis has been widely studied and many analysis methods have been developed. Mutual information based on entropy can measure arbitrary dependence between variables. It has been applied to many kinds of fields, especially to pattern recognition. But most works are restricted to discrete variables and little work has been done to study the relation between discrete and continuous variables. A novel algorithm is proposed to calculate the mutual information between discrete and continuous variables. It is used to analyze the correlation between TCM syndromes and physicochemical parameters.
Correlation and path coefficient analysis in coconut (Cocos nucifera L.
Directory of Open Access Journals (Sweden)
S. Geethanjali, D. Rajkumar and N.Shoba
2014-12-01
Full Text Available A total of 43 coconut germplasm accessions were characterized for nut yield and fruit component traits. Correlation analysis showed that most of the fruit traits viz., fruit length, fruit breadth, fruit weight, nut weight, kernel weight and copra weight per nut were positively correlated with each other but showed significant negative correlation with the number of nuts produced per palm per annum. Shell thickness and husk thickness were not correlated with any of the fruit component traits. Path analysis revealed that nut yield and copra content per nut had positive direct effect on the total copra yield per palm. The results of this study showed that equal consideration should be given for both nut yield and copra content per nut while selecting elite genotypes for dual purpose viz., tender nut or culinary use and copra for oil extraction.
Interval arithmetic operations for uncertainty analysis with correlated interval variables
Institute of Scientific and Technical Information of China (English)
Chao Jiang; Chun-Ming Fu; Bing-Yu Ni; Xu Han
2016-01-01
A new interval arithmetic method is proposed to solve interval functions with correlated intervals through which the overestimation problem existing in interval analy-sis could be significantly alleviated. The correlation between interval parameters is defined by the multidimensional par-allelepiped model which is convenient to describe the correlative and independent interval variables in a unified framework. The original interval variables with correlation are transformed into the standard space without correlation, and then the relationship between the original variables and the standard interval variables is obtained. The expressions of four basic interval arithmetic operations, namely addi-tion, subtraction, multiplication, and division, are given in the standard space. Finally, several numerical examples and a two-step bar are used to demonstrate the effectiveness of the proposed method.
DGCA: A comprehensive R package for Differential Gene Correlation Analysis.
McKenzie, Andrew T; Katsyv, Igor; Song, Won-Min; Wang, Minghui; Zhang, Bin
2016-11-15
Dissecting the regulatory relationships between genes is a critical step towards building accurate predictive models of biological systems. A powerful approach towards this end is to systematically study the differences in correlation between gene pairs in more than one distinct condition. In this study we develop an R package, DGCA (for Differential Gene Correlation Analysis), which offers a suite of tools for computing and analyzing differential correlations between gene pairs across multiple conditions. To minimize parametric assumptions, DGCA computes empirical p-values via permutation testing. To understand differential correlations at a systems level, DGCA performs higher-order analyses such as measuring the average difference in correlation and multiscale clustering analysis of differential correlation networks. Through a simulation study, we show that the straightforward z-score based method that DGCA employs significantly outperforms the existing alternative methods for calculating differential correlation. Application of DGCA to the TCGA RNA-seq data in breast cancer not only identifies key changes in the regulatory relationships between TP53 and PTEN and their target genes in the presence of inactivating mutations, but also reveals an immune-related differential correlation module that is specific to triple negative breast cancer (TNBC). DGCA is an R package for systematically assessing the difference in gene-gene regulatory relationships under different conditions. This user-friendly, effective, and comprehensive software tool will greatly facilitate the application of differential correlation analysis in many biological studies and thus will help identification of novel signaling pathways, biomarkers, and targets in complex biological systems and diseases.
Detrended cross-correlation analysis consistently extended to multifractality.
Oświecimka, Paweł; Drożdż, Stanisław; Forczek, Marcin; Jadach, Stanisław; Kwapień, Jarosław
2014-02-01
We propose an algorithm, multifractal cross-correlation analysis (MFCCA), which constitutes a consistent extension of the detrended cross-correlation analysis and is able to properly identify and quantify subtle characteristics of multifractal cross-correlations between two time series. Our motivation for introducing this algorithm is that the already existing methods, like multifractal extension, have at best serious limitations for most of the signals describing complex natural processes and often indicate multifractal cross-correlations when there are none. The principal component of the present extension is proper incorporation of the sign of fluctuations to their generalized moments. Furthermore, we present a broad analysis of the model fractal stochastic processes as well as of the real-world signals and show that MFCCA is a robust and selective tool at the same time and therefore allows for a reliable quantification of the cross-correlative structure of analyzed processes. In particular, it allows one to identify the boundaries of the multifractal scaling and to analyze a relation between the generalized Hurst exponent and the multifractal scaling parameter λ(q). This relation provides information about the character of potential multifractality in cross-correlations and thus enables a deeper insight into dynamics of the analyzed processes than allowed by any other related method available so far. By using examples of time series from the stock market, we show that financial fluctuations typically cross-correlate multifractally only for relatively large fluctuations, whereas small fluctuations remain mutually independent even at maximum of such cross-correlations. Finally, we indicate possible utility of MFCCA to study effects of the time-lagged cross-correlations.
Analysis of transverse momentum correlations in hadronic Z decays
ALEPH Collaboration; Barate, R.; Buskulic, D.; Decamp, D.; Ghez, P.; Goy, C.; Lees, J.-P.; Lucotte, A.; Merle, E.; Minard, M.-N.; Nief, J.-Y.; Perrodo, P.; Pietrzyk, B.; Alemany, R.; Casado, M. P.; Chmeissani, M.; Crespo, J. M.; Delfino, M.; Fernandez, E.; Fernandez-Bosman, M.; Garrido, Ll.; Graugès, E.; Juste, A.; Martinez, M.; Merino, G.; Miquel, R.; Mir, Ll. M.; Pacheco, A.; Park, I. C.; Pascual, A.; Riu, I.; Sanchez, F.; Colaleo, A.; Creanza, D.; de Palma, M.; Gelao, G.; Iaselli, G.; Maggi, G.; Maggi, M.; Nuzzo, S.; Ranieri, A.; Raso, G.; Ruggieri, F.; Selvaggi, G.; Silvestris, L.; Tempesta, P.; Tricomi, A.; Zito, G.; Huang, X.; Lin, J.; Ouyang, Q.; Wang, T.; Xie, Y.; Xu, R.; Xue, S.; Zhang, J.; Zhang, L.; Zhao, W.; Abbaneo, D.; Becker, U.; Boix, G.; Cattaneo, M.; Cerutti, F.; Ciulli, V.; Dissertori, G.; Drevermann, H.; Forty, R. W.; Frank, M.; Halley, A. W.; Hansen, J. B.; Harvey, J.; Janot, P.; Jost, B.; Lehraus, I.; Leroy, O.; Mato, P.; Minten, A.; Moneta, L.; Moutoussi, A.; Ranjard, F.; Rolandi, L.; Rousseau, D.; Schlatter, D.; Schmitt, M.; Schneider, O.; Tejessy, W.; Teubert, F.; Tomalin, I. R.; Tournefier, E.; Wachsmuth, H.; Ajaltouni, Z.; Badaud, F.; Chazelle, G.; Deschamps, O.; Falvard, A.; Ferdi, C.; Gay, P.; Guicheney, C.; Henrard, P.; Jousset, J.; Michel, B.; Monteil, S.; Montret, J.-C.; Pallin, D.; Perret, P.; Podlyski, F.; Hansen, J. D.; Hansen, J. R.; Hansen, P. H.; Nilsson, B. S.; Rensch, B.; Wäänänen, A.; Daskalakis, G.; Kyriakis, A.; Markou, C.; Simopoulou, E.; Siotis, I.; Vayaki, A.; Blondel, A.; Bonneaud, G.; Brient, J.-C.; Rougé, A.; Rumpf, M.; Swynghedauw, M.; Valassi, A.; Verderi, M.; Videau, H.; Focardi, E.; Parrini, G.; Zachariadou, K.; Corden, M.; Georgiopoulos, C.; Jaffe, D. E.; Antonelli, A.; Bencivenni, G.; Bologna, G.; Bossi, F.; Campana, P.; Capon, G.; Chiarella, V.; Laurelli, P.; Mannocchi, G.; Murtas, F.; Murtas, G. P.; Passalacqua, L.; Pepe-Altarelli, M.; Curtis, L.; Lynch, J. G.; Negus, P.; O'Shea, V.; Raine, C.; Teixeira-Dias, P.; Thompson, A. S.; Thomson, E.; Buchmüller, O.; Dhamotharan, S.; Geweniger, C.; Hanke, P.; Hansper, G.; Hepp, V.; Kluge, E. E.; Putzer, A.; Sommer, J.; Tittel, K.; Werner, S.; Wunsch, M.; Beuselinck, R.; Binnie, D. M.; Cameron, W.; Dornan, P. J.; Girone, M.; Goodsir, S.; Martin, E. B.; Marinelli, N.; Nash, J.; Sedgbeer, J. K.; Spagnolo, P.; Williams, M. D.; Ghete, V. M.; Girtler, P.; Kneringer, E.; Kuhn, D.; Rudolph, G.; Betteridge, A. P.; Bowdery, C. K.; Buck, P. G.; Colrain, P.; Crawford, G.; Finch, A. J.; Foster, F.; Hughes, G.; Jones, R. W. L.; Robertson, N. A.; Williams, M. I.; Giehl, I.; Hoffmann, C.; Jakobs, K.; Kleinknecht, K.; Quast, G.; Renk, B.; Rohne, E.; Sander, H.-G.; van Gemmeren, P.; Zeitnitz, C.; Aubert, J. J.; Benchouk, C.; Bonissent, A.; Carr, J.; Coyle, P.; Etienne, F.; Motsch, F.; Payre, P.; Talby, M.; Thulasidas, M.; Aleppo, M.; Antonelli, M.; Ragusa, F.; Berlich, R.; Büscher, V.; Dietl, H.; Ganis, G.; Hüttmann, K.; Lütjens, G.; Mannert, C.; Männer, W.; Moser, H.-G.; Schael, S.; Settles, R.; Seywerd, H.; Stenzel, H.; Wiedenmann, W.; Wolf, G.; Azzurri, P.; Boucrot, J.; Callot, O.; Chen, S.; Cordier, A.; Davier, M.; Duflot, L.; Grivaz, J.-F.; Heusse, Ph.; Jacholkowska, A.; Kim, D. W.; Le Diberder, F.; Lefrançois, J.; Lutz, A.-M.; Schune, M.-H.; Veillet, J.-J.; Videau, I.; Zerwas, D.; Bagliesi, G.; Bettarini, S.; Boccali, T.; Bozzi, C.; Calderini, G.; dell'Orso, R.; Ferrante, I.; Foà, L.; Giassi, A.; Gregorio, A.; Ligabue, F.; Lusiani, A.; Marrocchesi, P. S.; Messineo, A.; Palla, F.; Rizzo, G.; Sanguinetti, G.; Sciabà, A.; Sguazzoni, G.; Tenchini, R.; Vannini, C.; Venturi, A.; Verdini, P. G.; Blair, G. A.; Chambers, J. T.; Cowan, G.; Green, M. G.; Medcalf, T.; Strong, J. A.; von Wimmersperg-Toeller, J. H.; Botterill, D. R.; Clifft, R. W.; Edgecock, T. R.; Norton, P. R.; Thompson, J. C.; Wright, A. E.; Bloch-Devaux, B.; Colas, P.; Emery, S.; Kozanecki, W.; Lançon, E.; Lemaire, M.-C.; Locci, E.; Perez, P.; Rander, J.; Renardy, J.-F.; Roussarie, A.; Schuller, J.-P.; Schwindling, J.; Trabelsi, A.; Vallage, B.; Black, S. N.; Dann, J. H.; Johnson, R. P.; Kim, H. Y.; Konstantinidis, N.; Litke, A. M.; McNeil, M. A.; Taylor, G.; Booth, C. N.; Cartwright, S.; Combley, F.; Kelly, M. S.; Lehto, M.; Thompson, L. F.; Affholderbach, K.; Böhrer, A.; Brandt, S.; Grupen, C.; Prange, G.; Saraiva, P.; Smolik, L.; Stephan, F.; Giannini, G.; Gobbo, B.; Rothberg, J.; Wasserbaech, S.; Armstrong, S. R.; Charles, E.; Elmer, P.; Ferguson, D. P. S.; Gao, Y.; González, S.; Greening, T. C.; Hayes, O. J.; Hu, H.; Jin, S.; McNamara, P. A., III; Nachtman, J. M.; Nielsen, J.; Orejudos, W.; Pan, Y. B.; Saadi, Y.; Scott, I. J.; Walsh, J.; Wu, Sau Lan; Wu, X.; Zobernig, G.
1999-02-01
In a recent paper, evidence was presented for a significant, positive correlation between the total transverse momenta of particles on opposite hemispheres of hadronic events. A new, model independent analysis of the data has been made. Two components can be distinguished in the correlation, and quantitative estimates of each are given. The results form a significant test of Monte Carlo models and some of the physics behind them.
Model independent analysis of nearly L\\'evy correlations
Novák, T.; Csörgő, T.; Eggers, H. C.; Kock, M.
2016-01-01
A model-independent method for the analysis of the two-particle short-range correlations is presented, that can be utilized to describe e.g. Bose-Einstein (HBT), dynamical (ridge) or other correlation functions, that have a nearly L\\'evy or streched exponential shape. For the special case of L\\'evy exponent alpha = 1, the earlier Laguerre expansions are recovered, for the alpha = 2 special case, a new expansion method is obtained for nearly Gaussian correlation functions. Multi-dimensional L\\...
Analysis of community structure in networks of correlated data
Energy Technology Data Exchange (ETDEWEB)
Gomez, S.; Jensen, P.; Arenas, A.
2008-12-25
We present a reformulation of modularity that allows the analysis of the community structure in networks of correlated data. The new modularity preserves the probabilistic semantics of the original definition even when the network is directed, weighted, signed, and has self-loops. This is the most general condition one can find in the study of any network, in particular those defined from correlated data. We apply our results to a real network of correlated data between stores in the city of Lyon (France).
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...
Delay correlation analysis and representation for vital complaint VHDL models
Rich, Marvin J.; Misra, Ashutosh
2004-11-09
A method and system unbind a rise/fall tuple of a VHDL generic variable and create rise time and fall time generics of each generic variable that are independent of each other. Then, according to a predetermined correlation policy, the method and system collect delay values in a VHDL standard delay file, sort the delay values, remove duplicate delay values, group the delay values into correlation sets, and output an analysis file. The correlation policy may include collecting all generic variables in a VHDL standard delay file, selecting each generic variable, and performing reductions on the set of delay values associated with each selected generic variable.
Correlation failure analysis of an uncertain hysteretic vibration system
Institute of Scientific and Technical Information of China (English)
Zhang Xufang; Zhang Yimin; Hao Qiuju
2008-01-01
In this paper, a numerical method for correlation sensitivity analysis of a nonlinear random vibration system is presented. Based on the first passage failure model, the probability perturbation method is employed to determine the statistical characteristics of failure modes and the correlation between them. The sensitivity of correlation between failure modes with respect to random parameters characterizing the uncertainty of the hysteretic loop is discussed. In a numerical example, a two-DOF shear structure with uncertain hysteretic restoring force is considered. The statistical characteristics of response, failure modes and the sensitivity of random hysteretic loop parameters are provided, and also compared with a Monte Carlo simulation.
Process Correlation Analysis Model for Process Improvement Identification
Directory of Open Access Journals (Sweden)
Su-jin Choi
2014-01-01
software development process. However, in the current practice, correlations of process elements are often overlooked in the development of an improvement plan, which diminishes the efficiency of the plan. This is mainly attributed to significant efforts and the lack of required expertise. In this paper, we present a process correlation analysis model that helps identify correlations of process elements from the results of process assessment. This model is defined based on CMMI and empirical data of improvement practices. We evaluate the model using industrial data.
Wavelet multiple correlation and cross-correlation: A multiscale analysis of Eurozone stock markets
Fernández-Macho, Javier
2012-02-01
Statistical studies that consider multiscale relationships among several variables use wavelet correlations and cross-correlations between pairs of variables. This procedure needs to calculate and compare a large number of wavelet statistics. The analysis can then be rather confusing and even frustrating since it may fail to indicate clearly the multiscale overall relationship that might exist among the variables. This paper presents two new statistical tools that help to determine the overall correlation for the whole multivariate set on a scale-by-scale basis. This is illustrated in the analysis of a multivariate set of daily Eurozone stock market returns during a recent period. Wavelet multiple correlation analysis reveals the existence of a nearly exact linear relationship for periods longer than the year, which can be interpreted as perfect integration of these Euro stock markets at the longest time scales. It also shows that small inconsistencies between Euro markets seem to be just short within-year discrepancies possibly due to the interaction of different agents with different trading horizons.
Correlation Spectroscopy of Minor Species: Signal Purification and Distribution Analysis
Energy Technology Data Exchange (ETDEWEB)
Laurence, T A; Kwon, Y; Yin, E; Hollars, C; Camarero, J A; Barsky, D
2006-06-21
We are performing experiments that use fluorescence resonance energy transfer (FRET) and fluorescence correlation spectroscopy (FCS) to monitor the movement of an individual donor-labeled sliding clamp protein molecule along acceptor-labeled DNA. In addition to the FRET signal sought from the sliding clamp-DNA complexes, the detection channel for FRET contains undesirable signal from free sliding clamp and free DNA. When multiple fluorescent species contribute to a correlation signal, it is difficult or impossible to distinguish between contributions from individual species. As a remedy, we introduce ''purified FCS'' (PFCS), which uses single molecule burst analysis to select a species of interest and extract the correlation signal for further analysis. We show that by expanding the correlation region around a burst, the correlated signal is retained and the functional forms of FCS fitting equations remain valid. We demonstrate the use of PFCS in experiments with DNA sliding clamps. We also introduce ''single molecule FCS'', which obtains diffusion time estimates for each burst using expanded correlation regions. By monitoring the detachment of weakly-bound 30-mer DNA oligomers from a single-stranded DNA plasmid, we show that single molecule FCS can distinguish between bursts from species that differ by a factor of 5 in diffusion constant.
Analysis of correlation between corneal topographical data and visual performance
Zhou, Chuanqing; Yu, Lei; Ren, Qiushi
2007-02-01
Purpose: To study correlation among corneal asphericity, higher-order aberrations and visual performance for eyes of virgin myopia and postoperative laser in situ keratomileusis (LASIK). Methods: There were 320 candidates 590 eyes for LASIK treatment included in this study. The mean preoperative spherical equivalence was -4.35+/-1.51D (-1.25 to -9.75), with astigmatism less than 2.5 D. Corneal topography maps and contrast sensitivity were measured and analyzed for every eye before and one year after LASIK for the analysis of corneal asphericity and wavefront aberrations. Results: Preoperatively, only 4th and 6th order aberration had significant correlation with corneal asphericity and apical radius of curvature (pcorneal asphericity (pcorneal aberrations had no significant correlation with visual acuity and area under the log contrast sensitivity (AULCSF) (P>0.05). Postoperatively, corneal aberrations still didn't have significant correlation with visual acuity (P>0.05), but had significantly negative correlation with AULCSF (PCorneal asphericity had no significant correlation with AULCSF before and after the treatment (P>0.05). Conclusions: Corneal aberrations had different correlation with corneal profile and visual performance for eyes of virgin myopia and postoperative LASIK, which may be due to changed corneal profile and limitation of metrics of corneal aberrations.
Topology Studies of Hydrodynamics Using Two-Particle Correlation Analysis
Takahashi, J.; Tavares, B. M.; Qian, W. L.; Andrade, R.; Grassi, F.; Hama, Y.; Kodama, T.; Xu, N.
2009-12-01
The effects of fluctuating initial conditions are studied in the context of relativistic heavy ion collisions where a rapidly evolving system is formed. Two-particle correlation analysis is applied to events generated with the NEXSPHERIO hydrodynamic code, starting with fluctuating nonsmooth initial conditions (IC). The results show that the nonsmoothness in the IC survives the hydroevolution and can be seen as topological features of the angular correlation function of the particles emerging from the evolving system. A long range correlation is observed in the longitudinal direction and in the azimuthal direction a double peak structure is observed in the opposite direction to the trigger particle. This analysis provides clear evidence that these are signatures of the combined effect of tubular structures present in the IC and the proceeding collective dynamics of the hot and dense medium.
Topology studies of hydrodynamics using two particle correlation analysis
Takahashi, J; Qian, W L; Grassi, F; Hama, Y; Kodama, T; Xu, N
2009-01-01
Two particle correlation analysis is applied to events generated with the NEXSPHERIO hydrodynamic evolution code starting with fluctuating non-smooth initial conditions. Results show that the non-smoothness in the initial distributions survives the hydro-evolution and can be seen as topological features in the correlation function. Long range angular correlation in the longitudinal direction and a double peak structure in the azimuthal direction opposite to the trigger particle direction were observed, similar to features observed in the experimental data. This analysis provides clear evidence that these are signatures of the combined effect of tubular structures present in initial conditions, originated from the interactions of the energetic particles, and the proceeding collective dynamics of the hot and dense medium created in heavy ion collisions.
Sliding window correlation analysis for dengue-climate variable relationship
Thiruchelvam, Loshini; Asirvadam, Vijanth S.; Dass, Sarat C.; Daud, Hanita; Gill, Balvinder S.
2016-11-01
This study discussed building of sliding windows to analyze the relationship between dengue incidences and weather variables of mean temperature, relative humidity and rainfall, across the timeline. A window sized of 20 was selected and applied to find correlation between dengue incidences and each of the weather variable. A few time lag of zero, two, four, six, and eight is compared and the time lag with best correlation is selected for each weather variable. Study did not found a good insight for analysis using mean temperature and relative humidity. For both these variables, it was suggested dengue incidences is better measured using fluctuation of maximum and minimum values. Analysis using rainfall variable was found to vary across the timeline in magnitude and direction of the correlation. Time lag of eight was found to be the most significant explaining the relationship between dengue incidences and rainfall variable.
On discriminant analysis techniques and correlation structures in high dimensions
DEFF Research Database (Denmark)
Clemmensen, Line Katrine Harder
This paper compares several recently proposed techniques for performing discriminant analysis in high dimensions, and illustrates that the various sparse methods dier in prediction abilities depending on their underlying assumptions about the correlation structures in the data. The techniques...... generally focus on two things: Obtaining sparsity (variable selection) and regularizing the estimate of the within-class covariance matrix. For high-dimensional data, this gives rise to increased interpretability and generalization ability over standard linear discriminant analysis. Here, we group...
Auto-correlation analysis of ocean surface wind vectors
Indian Academy of Sciences (India)
Abhijit Sarkar; Sujit Basu; A K Varma; Jignesh Kshatriya
2002-09-01
The nature of the inherent temporal variability of surface winds is analyzed by comparison of winds obtained through different measurement methods. In this work, an auto-correlation analysis of a time series data of surface winds measured in situ by a deep water buoy in the Indian Ocean has been carried out. Hourly time series data available for 240 hours in the month of May, 1999 were subjected to an auto-correlation analysis. The analysis indicates an exponential fall of the auto- correlation in the first few hours with a decorrelation time scale of about 6 hours. For a meaningful comparison between satellite derived products and in situ data, satellite data acquired at different time intervals should be used with appropriate `weights', rather than treating the data as concurrent in time. This paper presents a scheme for temporal weighting using the auto-correlation analysis. These temporal `weights' can potentially improve the root mean square (rms) deviation between satellite and in situ measurements. A case study using the TRMM Microwave Imager (TMI) and Indian Ocean buoy wind speed data resulted in an improvement of about 10%.
Drivers and Outcomes of Scenario Planning: A Canonical Correlation Analysis
Chermack, Thomas J.; Nimon, Kim
2013-01-01
Purpose: The paper's aim is to report a research study on the mediator and outcome variable sets in scenario planning. Design/methodology/approach: This is a cannonical correlation analysis (CCA) Findings Two sets of variables; one as a predictor set that explained a significant amount of variability in the second, or outcome set of variables were…
Time series analysis : Smoothed correlation integrals, autocovariances, and power spectra
Takens, F; Dumortier, F; Broer, H; Mawhin, J; Vanderbauwhede, A; Lunel, SV
2005-01-01
In this paper we relate notions from linear time series analyses, like autocovariances and power spectra, with notions from nonlinear times series analysis, like (smoothed) correlation integrals and the corresponding dimensions and entropies. The complete proofs of the results announced in this pape
Stock Markets Correlation: before and during the Crisis Analysis
Directory of Open Access Journals (Sweden)
Ioana MOLDOVAN
2011-08-01
Full Text Available The article studies the correlations between the stock markets of the greatest financial centers in the world, namely New York, London and Tokyo, in two different time intervals, namely before the global crisis that erupted in 2007 and during it, in order to determine whether the stock markets correlate more strongly during increasing or decreasing trends. The results of the analysis, carried out by means of multiple regressions, show that the links between the three stock markets were more intense during the crisis, on a decreasing trend respectively, than before the financial turmoil, when the stock indexes had an upward trend.
Analysis of the Correlation between GDP and the Final Consumption
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.
Correlative Peak Interval Prediction and Analysis of Chaotic Sequences
Directory of Open Access Journals (Sweden)
Qun Ding
2011-07-01
Full Text Available The paper proposes a digital circuit design for the logistic-map module used in chaotic stream ciphers, analyzes the factors that may affect the output of the sequences, and develops a calculation method for estimating the output sequential correlative peak interval. With the respective tests using different initial values, the values of parameter u and the computational precisions, extensive experiments have been carried out. A formula for calculating correlative peak interval is proposed. Moreover, the relationships among precision, parameter u and correlative peak interval is provided. To ensure the security of the plaintext which is encrypted by the output sequence of the logistic-map, a proper precision could be chosen according to the formula. It provides a theoretic basis for the actual application of the chaos cryptology. The basic theory and methods have a significant implication on the statistical analysis and practical applications of the digital chaotic sequences. A diagram that presents the relationship among precision, parameter u and correlative peak interval has been generated for analysis.
Strength Reliability Analysis of Stiffened Cylindrical Shells Considering Failure Correlation
Institute of Scientific and Technical Information of China (English)
Xu Bai; Liping Sun; Wei Qin; Yongkun Lv
2014-01-01
The stiffened cylindrical shell is commonly used for the pressure hull of submersibles and the legs of offshore platforms. There are various failure modes because of uncertainty with the structural size and material properties, uncertainty of the calculation model and machining errors. Correlations among failure modes must be considered with the structural reliability of stiffened cylindrical shells. However, the traditional method cannot consider the correlations effectively. The aim of this study is to present a method of reliability analysis for stiffened cylindrical shells which considers the correlations among failure modes. Firstly, the joint failure probability calculation formula of two related failure modes is derived through use of the 2D joint probability density function. Secondly, the full probability formula of the tandem structural system is given with consideration to the correlations among failure modes. At last, the accuracy of the system reliability calculation is verified through use of the Monte Carlo simulation. Result of the analysis shows the failure probability of stiffened cylindrical shells can be gained through adding the failure probability of each mode.
Message Correlation Analysis Tool for NOvA
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++.
Process correlation analysis model for process improvement identification.
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.
NIRS-BASED CORTICAL ACTIVATION ANALYSIS BY TEMPORAL CROSS CORRELATION
Directory of Open Access Journals (Sweden)
Raul Fernandez-Rojas
2016-02-01
Full Text Available In this study we present a method of signal processing to determine dominant channels in near infrared spectroscopy (NIRS. To compare measuring channels and identify delays between them, cross correlation is computed. Furthermore, to find out possible dominant channels, a visual inspection was performed. The outcomes demonstrated that the visual inspection exhibited evoked-related activations in the primary somatosensory cortex (S1 after stimulation which is consistent with comparable studies and the cross correlation study discovered dominant channels on both cerebral hemispheres. The analysis also showed a relationship between dominant channels and adjacent channels. For that reason, our results present a new method to identify dominant regions in the cerebral cortex using near-infrared spectroscopy. These findings have also implications in the decrease of channels by eliminating irrelevant channels for the experiment.
A Correlation Analysis Model for Multidisciplinary Data in Disaster Research
Directory of Open Access Journals (Sweden)
Hongyue Zhang
2015-05-01
Full Text Available Data play an important role in disaster mitigation applications, and the integrated employment of multidisciplinary data promotes the development of disaster science. Therefore it is very useful to identify the multidisciplinary data usage in the research of disaster events. In order to discover the correlation between multidisciplinary data and disaster research, three earthquake events, the Tangshan earthquake, the Wenchuan earthquake, and the Haidi earthquake were selected as typical study cases for this paper. A knowledge model for literature data mining was applied to analyze the correlation between earthquake events and multidisciplinary data types. The results indicate that high-cited papers show different data usage trends when compared with whole-set papers and also that data usage for the three earthquake events varies. According to analysis results, the factors that influence multidisciplinary data usage include the characteristics of spatial and temporal elements as well as differing interests of the data users.
Dimensions of Emotional Intelligence and Transformational Leadership: A Correlation Analysis
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John N. N. Ugoani
2015-06-01
Full Text Available The study was designed to explore the degree of relationship between emotional intelligence and transformational leadership style. Goleman who popularized the concept of the science of emotional intelligence and brought it to its academic zenith drew on a wealth of research to argue that successful leaders need emotional intelligence, or the attributes of self-awareness, impulse control, persistence, confidence, self-motivation empathy, social deftness, trust worthiness, adaptability, and a talent of collaboration. Data were generated through 5 – point Likert-type questionnaire based on Schutte, Self Report questionnaire. Pearson’s correlation analysis was carried out through the Statistical Package for Social Sciences, and a strong positive correlation of r = .90, was found between emotional intelligence and transformational leadership style.
Analysis and correlation of SA349/2 helicopter vibration
Heffernan, Ruth; Precetti, Dominique; Johnson, Wayne
1991-01-01
Helicopter airframe vibration is examined using calculation and measurements for the SA349/2 research helicopter. The hub loads, which transmit excitation to the fuselage, are predicted using a comprehensive rotorcraft analysis and correlated with measured hub loads. The predicted and measured hub loads are then coupled with finite element models representing the SA349/2 fuselage. The resulting vertical acceleration at the pilot seat is examined. Adjustments are made to the airframe structural models to examine the sensitivity of predicted vertical acceleration to the model. Changes of a few percent to the damping and frequency of specific modes lead to large reductions in predicted vibration and to major improvements in the correlations with measured pilot seat vertical acceleration.
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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)
A Comparative Study of Kernel and Robust Canonical Correlation Analysis
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Ashad M. Alam
2010-02-01
Full Text Available A number of measures of canonical correlation coefficient are now used in multimedia related fields like object recognition, image segmentation facial expression recognition and pattern recognition in the different literature. Some robust forms of classical canonical correlation coefficient are introduced recently to address the robustness issue of the canonical coefficient in the presence of outliers and departure from normality. Also a few number of kernels are used in canonical analysis to capture nonlinear relationship in data space, which is linear in some higher dimensional feature space. But not much work has been done to investigate their relative performances through i simulation from the view point of sensitivity, breakdown analysis as well as ii using real data sets. In this paper an attempt has been made to compare performances of kernel canonical correlation coefficients (Gaussian function, Laplacian function and Polynomial function with that of robust and classical canonical correlation coefficient measures using simulation with five sample sizes (50, 500, 1000, 1500 and 2000, influence function, breakdown point along with several real data and a multi-modal data sets, focusing on the specific case of segmented images with associated text. We investigate the bias, mean square error(MISE, qualitative robustness index (RI, sensitivity curve of each estimator under a variety of situations and also employ box plots and scatter plots of canonical variates to judge their performances. We have observed that the class of kernel estimators perform better than the class of classical and robust estimators in general and the kernel estimator with Laplacian function has shown the best performance for large sample size and break down is high in case of nonlinear data.
Multifractal detrending moving-average cross-correlation analysis.
Jiang, Zhi-Qiang; Zhou, Wei-Xing
2011-07-01
There are a number of situations in which several signals are simultaneously recorded in complex systems, which exhibit long-term power-law cross correlations. The multifractal detrended cross-correlation analysis (MFDCCA) approaches can be used to quantify such cross correlations, such as the MFDCCA based on the detrended fluctuation analysis (MFXDFA) method. We develop in this work a class of MFDCCA algorithms based on the detrending moving-average analysis, called MFXDMA. The performances of the proposed MFXDMA algorithms are compared with the MFXDFA method by extensive numerical experiments on pairs of time series generated from bivariate fractional Brownian motions, two-component autoregressive fractionally integrated moving-average processes, and binomial measures, which have theoretical expressions of the multifractal nature. In all cases, the scaling exponents h(xy) extracted from the MFXDMA and MFXDFA algorithms are very close to the theoretical values. For bivariate fractional Brownian motions, the scaling exponent of the cross correlation is independent of the cross-correlation coefficient between two time series, and the MFXDFA and centered MFXDMA algorithms have comparative performances, which outperform the forward and backward MFXDMA algorithms. For two-component autoregressive fractionally integrated moving-average processes, we also find that the MFXDFA and centered MFXDMA algorithms have comparative performances, while the forward and backward MFXDMA algorithms perform slightly worse. For binomial measures, the forward MFXDMA algorithm exhibits the best performance, the centered MFXDMA algorithms performs worst, and the backward MFXDMA algorithm outperforms the MFXDFA algorithm when the moment order q0. We apply these algorithms to the return time series of two stock market indexes and to their volatilities. For the returns, the centered MFXDMA algorithm gives the best estimates of h(xy)(q) since its h(xy)(2) is closest to 0.5, as expected, and
Madhu, Basetti; Narita, Masako; Jauhiainen, Alexandra; Menon, Suraj; Stubbs, Marion; Tavaré, Simon; Narita, Masashi; Griffiths, John R
To investigate metabolic changes during cellular transformation, we used a (1)H NMR based metabolite-metabolite correlation analysis (MMCA) method, which permits analysis of homeostatic mechanisms in cells at the steady state, in an inducible cell transformation model. Transcriptomic data were used to further explain the results. Transformed cells showed many more metabolite-metabolite correlations than control cells. Some had intuitively plausible explanations: a shift from glycolysis to amino acid oxidation after transformation was accompanied by a strongly positive correlation between glucose and glutamine and a strongly negative one between lactate and glutamate; there were also many correlations between the branched chain amino acids and the aromatic amino acids. Others remain puzzling: after transformation strong positive correlations developed between choline and a group of five amino acids, whereas the same amino acids showed negative correlations with phosphocholine, a membrane phospholipid precursor. MMCA in conjunction with transcriptome analysis has opened a new window into the metabolome.
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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.
Ni, Jianhua; Qian, Tianlu; Xi, Changbai; Rui, Yikang; Wang, Jiechen
2016-01-01
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. PMID:27548197
Ni, Jianhua; Qian, Tianlu; Xi, Changbai; Rui, Yikang; Wang, Jiechen
2016-08-18
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.
Protein structure similarity from principle component correlation analysis
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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
Error analysis in correlation computation of single particle reconstruction technique
Institute of Scientific and Technical Information of China (English)
胡悦; 隋森芳
1999-01-01
The single particle reconstruction technique has become particularly important in the structure analysis of hiomaeromolecules. The problem of reconstructing a picture from identical samples polluted by colored noises is studied, and the alignment error in the correlation computation of single particle reconstruction technique is analyzed systematically. The concept of systematic error is introduced, and the explicit form of the systematic error is given under the weak noise approximation. The influence of the systematic error on the reconstructed picture is discussed also, and an analytical formula for correcting the distortion in the picture reconstruction is obtained.
Multiple window correlation analysis of HRV power and respiratory frequency.
Hansson-Sandsten, Maria; Jönsson, Peter
2007-10-01
In this paper, we evaluate the correlation estimate, based on multiple window spectrum analysis, between the respiratory center frequency and the high-frequency band of the heartrate variability (HRV) power. One aim is to examine whether a more restricted frequency range would better capture respiratory related HR variation, especially when the HR variation is changing rapidly. The respiratory peak is detected and a narrow-banded measure of the high-frequency (HF) band of the HRV is defined as the respiratory frequency +/-0.05 Hz. We compare the mean square error of the correlation estimate between the frequency of the respiratory peak and the power of the HRV with the power in the usual 0.12-0.4 Hz frequency band. Different multiple window spectrum techniques are used for the estimation of the respiratory frequency as well as for the power of the HRV. We compare the peak-matched multiple windows with the Welch method while evaluating the two different HF-power estimates mentioned above. The results show that using a more narrow band for the power estimation gives stronger correlation which indicates that the estimate of the power is more robust.
Sperm penetration assay and its correlation with semen analysis parameters
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Laxmi Kant Pandey
2015-11-01
Full Text Available Background: Aim of current study was to determine whether the Sperm Penetration Assay (SPA can be used as a test to discriminate the infertile male from fertile one. We have also correlated the SPA with semen analysis. Methods: Sperm characteristics namely Semen analysis and the sperm penetration assay were tested in 44 infertile and 10 fertile men. Sperm penetration assay was determined by using zona free hamster eggs. Results: With decreasing spermatozoa concentration in the semen there was significant decrease in percentage penetration of zona free Hamster eggs (p0.05. Conclusions: The Sperm penetration assay could discriminate the infertile group from fertile group significantly (p<0.001. The test appeared to be highly reproducible and probably identifies a truly infertile male. [Int J Res Med Sci 2015; 3(11.000: 3197-3201
Fluorescence correlation spectroscopy: Statistical analysis and biological applications
Saffarian, Saveez
2002-01-01
The experimental design and realization of an apparatus which can be used both for single molecule fluorescence detection and also fluorescence correlation and cross correlation spectroscopy is presented. A thorough statistical analysis of the fluorescence correlation functions including the analysis of bias and errors based on analytical derivations has been carried out. Using the methods developed here, the mechanism of binding and cleavage site recognition of matrix metalloproteinases (MMP) for their substrates has been studied. We demonstrate that two of the MMP family members, Collagenase (MMP-1) and Gelatinase A (MMP-2) exhibit diffusion along their substrates, the importance of this diffusion process and its biological implications are discussed. We show through truncation mutants that the hemopexin domain of the MMP-2 plays and important role in the substrate diffusion of this enzyme. Single molecule diffusion of the collagenase MMP-1 has been observed on collagen fibrils and shown to be biased. The discovered biased diffusion would make the MMP-1 molecule an active motor, thus making it the first active motor that is not coupled to ATP hydrolysis. The possible sources of energy for this enzyme and their implications are discussed. We propose that a possible source of energy for the enzyme can be in the rearrangement of the structure of collagen fibrils. In a separate application, using the methods developed here, we have observed an intermediate in the intestinal fatty acid binding protein folding process through the changes in its hydrodynamic radius also the fluctuations in the structure of the IFABP in solution were measured using FCS.
Correlation analysis between ionospheric scintillation levels and receiver tracking performance
Sreeja, V.; Aquino, M.; Elmas, Z. G.; Forte, B.
2012-06-01
Rapid fluctuations in the amplitude and phase of a transionospheric radio signal caused by small scale plasma density irregularities in the ionosphere are known as scintillation. Scintillation can seriously impair a GNSS (Global Navigation Satellite Systems) receiver tracking performance, thus affecting the required levels of availability, accuracy and integrity, and consequently the reliability of modern day GNSS based applications. This paper presents an analysis of correlation between scintillation levels and tracking performance of a GNSS receiver for GPS L1C/A, L2C and GLONASS L1, L2 signals. The analyses make use of data recorded over Presidente Prudente (22.1°S, 51.4°W, dip latitude ˜12.3°S) in Brazil, a location close to the Equatorial Ionisation Anomaly (EIA) crest in Latin America. The study presents for the first time this type of correlation analysis for GPS L2C and GLONASS L1, L2 signals. The scintillation levels are defined by the amplitude scintillation index, S4 and the receiver tracking performance is evaluated by the phase tracking jitter. Both S4 and the phase tracking jitter are estimated from the post correlation In-Phase (I) and Quadra-Phase (Q) components logged by the receiver at a high rate. Results reveal that the dependence of the phase tracking jitter on the scintillation levels can be represented by a quadratic fit for the signals. The results presented in this paper are of importance to GNSS users, especially in view of the forthcoming high phase of solar cycle 24 (predicted for 2013).
Interpreting Canonical Correlation Analysis through Biplots of Structure Correlations and Weights.
ter Braak, Cajo J. F.
1990-01-01
Canonical weights and structure correlations are used to construct low dimensional views of the relationships between two sets of variables. These views, in the form of biplots, display familiar statistics: correlations between pairs of variables, and regression coefficients. (SLD)
Correlating Detergent Fiber Analysis and Dietary Fiber Analysis Data for Corn Stover
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Wolfrum, E. J.; Lorenz, A. J.; deLeon, N.
2009-01-01
There exist large amounts of detergent fiber analysis data [neutral detergent fiber (NDF), acid detergent fiber (ADF), acid detergent lignin (ADL)] for many different potential cellulosic ethanol feedstocks, since these techniques are widely used for the analysis of forages. Researchers working in the area of cellulosic ethanol are interested in the structural carbohydrates in a feedstock (principally glucan and xylan), which are typically determined by acid hydrolysis of the structural fraction after multiple extractions of the biomass. These so-called dietary fiber analysis methods are significantly more involved than detergent fiber analysis methods. The purpose of this study was to determine whether it is feasible to correlate detergent fiber analysis values to glucan and xylan content determined by dietary fiber analysis methods for corn stover. In the detergent fiber analysis literature cellulose is often estimated as the difference between ADF and ADL, while hemicellulose is often estimated as the difference between NDF and ADF. Examination of a corn stover dataset containing both detergent fiber analysis data and dietary fiber analysis data predicted using near infrared spectroscopy shows that correlations between structural glucan measured using dietary fiber techniques and cellulose estimated using detergent techniques, and between structural xylan measured using dietary fiber techniques and hemicellulose estimated using detergent techniques are high, but are driven largely by the underlying correlation between total extractives measured by fiber analysis and NDF/ADF. That is, detergent analysis data is correlated to dietary fiber analysis data for structural carbohydrates, but only indirectly; the main correlation is between detergent analysis data and solvent extraction data produced during the dietary fiber analysis procedure.
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Arif Billah Dar
2014-01-01
Full Text Available This paper investigates the synchronization of fixed income markets within Eurozone countries using the new wavelet based methodology. Conventional wavelet methods that use multivariate set of variables to calculate pairwise correlation and cross correlation lead to spurious correlation due to possible relationships with other variables, amplification of type-1 errors, and results, in the form of large set of erroneous graphs. Given these disadvantages of conventional wavelet based pairwise correlation and cross-correlation method, we avoid these limitations by using wavelet multiple correlation and multiple cross correlations to analyze the relationships in Eurozone fixed income markets. Our results based on this methodology indicate that Eurozone fixed income markets are highly integrated and this integration grows with timescales, and hence there is almost no scope for independent monetary policy and bond diversification in these countries.
Meconium microbiome analysis identifies bacteria correlated with premature birth.
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Alexandria N Ardissone
Full Text Available Preterm birth is the second leading cause of death in children under the age of five years worldwide, but the etiology of many cases remains enigmatic. The dogma that the fetus resides in a sterile environment is being challenged by recent findings and the question has arisen whether microbes that colonize the fetus may be related to preterm birth. It has been posited that meconium reflects the in-utero microbial environment. In this study, correlations between fetal intestinal bacteria from meconium and gestational age were examined in order to suggest underlying mechanisms that may contribute to preterm birth.Meconium from 52 infants ranging in gestational age from 23 to 41 weeks was collected, the DNA extracted, and 16S rRNA analysis performed. Resulting taxa of microbes were correlated to clinical variables and also compared to previous studies of amniotic fluid and other human microbiome niches.Increased detection of bacterial 16S rRNA in meconium of infants of <33 weeks gestational age was observed. Approximately 61·1% of reads sequenced were classified to genera that have been reported in amniotic fluid. Gestational age had the largest influence on microbial community structure (R = 0·161; p = 0·029, while mode of delivery (C-section versus vaginal delivery had an effect as well (R = 0·100; p = 0·044. Enterobacter, Enterococcus, Lactobacillus, Photorhabdus, and Tannerella, were negatively correlated with gestational age and have been reported to incite inflammatory responses, suggesting a causative role in premature birth.This provides the first evidence to support the hypothesis that the fetal intestinal microbiome derived from swallowed amniotic fluid may be involved in the inflammatory response that leads to premature birth.
Comparison of correlation analysis techniques for irregularly sampled time series
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K. Rehfeld
2011-06-01
Full Text Available Geoscientific measurements often provide time series with irregular time sampling, requiring either data reconstruction (interpolation or sophisticated methods to handle irregular sampling. We compare the linear interpolation technique and different approaches for analyzing the correlation functions and persistence of irregularly sampled time series, as Lomb-Scargle Fourier transformation and kernel-based methods. In a thorough benchmark test we investigate the performance of these techniques.
All methods have comparable root mean square errors (RMSEs for low skewness of the inter-observation time distribution. For high skewness, very irregular data, interpolation bias and RMSE increase strongly. We find a 40 % lower RMSE for the lag-1 autocorrelation function (ACF for the Gaussian kernel method vs. the linear interpolation scheme,in the analysis of highly irregular time series. For the cross correlation function (CCF the RMSE is then lower by 60 %. The application of the Lomb-Scargle technique gave results comparable to the kernel methods for the univariate, but poorer results in the bivariate case. Especially the high-frequency components of the signal, where classical methods show a strong bias in ACF and CCF magnitude, are preserved when using the kernel methods.
We illustrate the performances of interpolation vs. Gaussian kernel method by applying both to paleo-data from four locations, reflecting late Holocene Asian monsoon variability as derived from speleothem δ^{18}O measurements. Cross correlation results are similar for both methods, which we attribute to the long time scales of the common variability. The persistence time (memory is strongly overestimated when using the standard, interpolation-based, approach. Hence, the Gaussian kernel is a reliable and more robust estimator with significant advantages compared to other techniques and suitable for large scale application to paleo-data.
Meconium microbiome analysis identifies bacteria correlated with premature birth.
Ardissone, Alexandria N; de la Cruz, Diomel M; Davis-Richardson, Austin G; Rechcigl, Kevin T; Li, Nan; Drew, Jennifer C; Murgas-Torrazza, Roberto; Sharma, Renu; Hudak, Mark L; Triplett, Eric W; Neu, Josef
2014-01-01
Preterm birth is the second leading cause of death in children under the age of five years worldwide, but the etiology of many cases remains enigmatic. The dogma that the fetus resides in a sterile environment is being challenged by recent findings and the question has arisen whether microbes that colonize the fetus may be related to preterm birth. It has been posited that meconium reflects the in-utero microbial environment. In this study, correlations between fetal intestinal bacteria from meconium and gestational age were examined in order to suggest underlying mechanisms that may contribute to preterm birth. Meconium from 52 infants ranging in gestational age from 23 to 41 weeks was collected, the DNA extracted, and 16S rRNA analysis performed. Resulting taxa of microbes were correlated to clinical variables and also compared to previous studies of amniotic fluid and other human microbiome niches. Increased detection of bacterial 16S rRNA in meconium of infants of premature birth. This provides the first evidence to support the hypothesis that the fetal intestinal microbiome derived from swallowed amniotic fluid may be involved in the inflammatory response that leads to premature birth.
Correlation Analysis of Groundwater Colouration from Mountainous Areas, Ghana
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R. Amfo-Otu
2014-03-01
Full Text Available Access to potable water is important for human development but inhabitants of mountainous areas face challenges of water supply due to inadequacy of the available surface water. Groundwater thus becomes the other alternative. The research was done on the groundwater quality with respect to colouration in five boreholes in some second cycle schools located in mountainous areas of the Akuapim North district. Four samples each were taken from the five boreholes for laboratory analysis. Colour, iron, manganese and some physical parameters were analysed and the results were compared with the World Health Organisation guidelines and the Ghana Urban Water Limited standard for drinking water. The results showed that conductivity and turbidity were all within the acceptable standards for drinking water. Colour strongly correlated positively with iron (r = 0.869, turbidity (r = 0.858, conductivity (r = 0.727 and manganese (r = 0.681, but pH (r = -0.715 strongly correlated negatively. Even though iron and manganese have no known health effects, they were associated with the colouration of the groundwater causing aesthetic problems for the users of the boreholes. Construction of a simple filter bed with aeration facility is critical to remove iron and manganese from the water to make it potable to the consumers. DOI: http://dx.doi.org/10.5755/j01.erem.67.1.4545
Correlation Analysis of Sleep Quality and Youth Ischemic Stroke
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Shunqing Zhang
2014-01-01
Full Text Available Objective. To study risk factors related to ischemic stroke (IS in youth and the influence of sleep quality on youth ischemic stroke incidence. Methods. 223 patients aged 18 to 45 years who were admitted to Puyang People’s Hospital from June 2011 to February 2013 with a first-ever ischemic stroke were selected as the research cases. 158 young people with a normal physical examination were selected as the control group. The Pittsburgh Sleep Quality Index (PSQI questionnaire was used to analyse the correlation between sleep quality and youth IS incidence. The US National Institutes of Health Stroke Scale (NIHSS and modified Rankin Scale (MRS scores were used to assess cases’ state of illness and prognosis three months after IS. Results. Univariate and multivariate logistic regression analysis showed that the association of these risk factors with youth IS incidence, from highest to lowest, was hypertension, hyperlipidaemia, smoking history, high homocysteine, the quality of sleep, family history of stroke, and alcoholism. Poor sleep quality ranked fifth among all risk factors and was positively correlated with poor prognosis for youth IS patients. Conclusion. The results of this study showed that sleep quality is an important factor in the pathogenesis and prognosis of youth IS.
A Visual Analytics Approach for Correlation, Classification, and Regression Analysis
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Steed, Chad A [ORNL; SwanII, J. Edward [Mississippi State University (MSU); Fitzpatrick, Patrick J. [Mississippi State University (MSU); Jankun-Kelly, T.J. [Mississippi State University (MSU)
2012-02-01
New approaches that combine the strengths of humans and machines are necessary to equip analysts with the proper tools for exploring today's increasing complex, multivariate data sets. In this paper, a novel visual data mining framework, called the Multidimensional Data eXplorer (MDX), is described that addresses the challenges of today's data by combining automated statistical analytics with a highly interactive parallel coordinates based canvas. In addition to several intuitive interaction capabilities, this framework offers a rich set of graphical statistical indicators, interactive regression analysis, visual correlation mining, automated axis arrangements and filtering, and data classification techniques. The current work provides a detailed description of the system as well as a discussion of key design aspects and critical feedback from domain experts.
Correlation Analysis between Rural Tourism and Agricultural Food Marketing
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Hui Song
2015-04-01
Full Text Available Rural tourism has much economic benefits, the development of rural tourism can fully utilize rural natural resources, optimizing the agricultural structure and expanding agricultural function. In this study, we make correlation analysis between rural tourism and agricultural food marketing by using time series model. The result shows that: First, rural tourism development will promote the agricultural food marketing in short time, but this effect will reduce gradually in the long time. Second, rural tourism is the granger reason to agricultural food marketing and there exist a long-term equilibrium relationship between them. From the VAR model, we can get that rural tourism will promote agricultural food marketing growth. LnRT at lag 1 period increased 1% can drive LnFPI growth by 0.48%; LnRT at lag 2 period increased 1% can drive LnFPI growth by 0.2%, so the effect of rural tourism on agricultural food marketing is obvious.
Windows Volatile Memory Forensics Based on Correlation Analysis
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Xiaolu Zhang
2014-03-01
Full Text Available In this paper, we present an integrated memory forensic solution for multiple Windows memory images. By calculation, the method can find out the correlation degree among the processes of volatile memory images and the hidden clues behind the events of computers, which is usually difficult to be obtained and easily ignored by analyzing one single memory image and forensic investigators. In order to test the validity, we performed an experiment based on two hosts' memory image which contains criminal incidents. According to the experimental result, we find that the event chains reconstructed by our method are similar to the actual actions in the criminal scene. Investigators can review the digital crime scenario which is contained in the data set by analyzing the experimental results. This paper is aimed at finding the valid actions with illegal attempt and making the memory analysis not to be utterly dependent on the operating system and relevant experts.
Pulsar timing analysis in the presence of correlated noise
Coles, W; Champion, D J; Manchester, R N; Verbiest, J P W
2011-01-01
Pulsar timing observations are usually analysed with least-square-fitting procedures under the assumption that the timing residuals are uncorrelated (statistically "white"). Pulsar observers are well aware that this assumption often breaks down and causes severe errors in estimating the parameters of the timing model and their uncertainties. Ad hoc methods for minimizing these errors have been developed, but we show that they are far from optimal. Compensation for temporal correlation can be done optimally if the covariance matrix of the residuals is known using a linear transformation that whitens both the residuals and the timing model. We adopt a transformation based on the Cholesky decomposition of the covariance matrix, but the transformation is not unique. We show how to estimate the covariance matrix with sufficient accuracy to optimize the pulsar timing analysis. We also show how to apply this procedure to estimate the spectrum of any time series with a steep red power-law spectrum, including those wi...
Correlation network analysis applied to complex biofilm communities.
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Ana E Duran-Pinedo
Full Text Available The complexity of the human microbiome makes it difficult to reveal organizational principles of the community and even more challenging to generate testable hypotheses. It has been suggested that in the gut microbiome species such as Bacteroides thetaiotaomicron are keystone in maintaining the stability and functional adaptability of the microbial community. In this study, we investigate the interspecies associations in a complex microbial biofilm applying systems biology principles. Using correlation network analysis we identified bacterial modules that represent important microbial associations within the oral community. We used dental plaque as a model community because of its high diversity and the well known species-species interactions that are common in the oral biofilm. We analyzed samples from healthy individuals as well as from patients with periodontitis, a polymicrobial disease. Using results obtained by checkerboard hybridization on cultivable bacteria we identified modules that correlated well with microbial complexes previously described. Furthermore, we extended our analysis using the Human Oral Microbe Identification Microarray (HOMIM, which includes a large number of bacterial species, among them uncultivated organisms present in the mouth. Two distinct microbial communities appeared in healthy individuals while there was one major type in disease. Bacterial modules in all communities did not overlap, indicating that bacteria were able to effectively re-associate with new partners depending on the environmental conditions. We then identified hubs that could act as keystone species in the bacterial modules. Based on those results we then cultured a not-yet-cultivated microorganism, Tannerella sp. OT286 (clone BU063. After two rounds of enrichment by a selected helper (Prevotella oris OT311 we obtained colonies of Tannerella sp. OT286 growing on blood agar plates. This system-level approach would open the possibility of
Digital Image Correlation: Metrological Characterization in Mechanical Analysis
Petrella, Orsola; Signore, Davide; Caramuta, Pietro; Toscano, Cinzia; Ferraiuolo, Michele
2017-04-01
The Digital Image Correlation (DIC) is a newly developed optical technique that is spreading in all engineering sectors because it allows the non-destructive estimation of the entire surface deformation without any contact with the component under analysis. These characteristics make the DIC very appealing in all the cases the global deformation state is to be known without using strain gages, which are the most used measuring device. The DIC is applicable to any material subjected to distortion caused by either thermal or mechanical load, allowing to obtain high-definition mapping of displacements and deformations. That is why in the civil and the transportation industry, DIC is very useful for studying the behavior of metallic materials as well as of composite materials. DIC is also used in the medical field for the characterization of the local strain field of the vascular tissues surface subjected to uniaxial tensile loading. DIC can be carried out in the two dimension mode (2D DIC) if a single camera is used or in a three dimension mode (3D DIC) if two cameras are involved. Each point of the test surface framed by the cameras can be associated with a specific pixel of the image and the coordinates of each point are calculated knowing the relative distance between the two cameras together with their orientation. In both arrangements, when a component is subjected to a load, several images related to different deformation states can be are acquired through the cameras. A specific software analyzes the images via the mutual correlation between the reference image (obtained without any applied load) and those acquired during the deformation giving the relative displacements. In this paper, a Metrological Characterization of the Digital Image Correlation is performed on aluminum and composite targets both in static and dynamic loading conditions by comparison between DIC and strain gauges measures. In the static test, interesting results have been obtained thanks
Interactive Correlation Analysis and Visualization of Climate Data
Energy Technology Data Exchange (ETDEWEB)
Ma, Kwan-Liu [Univ. of California, Davis, CA (United States)
2016-09-21
The relationship between our ability to analyze and extract insights from visualization of climate model output and the capability of the available resources to make those visualizations has reached a crisis point. The large volume of data currently produced by climate models is overwhelming the current, decades-old visualization workflow. The traditional methods for visualizing climate output also have not kept pace with changes in the types of grids used, the number of variables involved, and the number of different simulations performed with a climate model or the feature-richness of high-resolution simulations. This project has developed new and faster methods for visualization in order to get the most knowledge out of the new generation of high-resolution climate models. While traditional climate images will continue to be useful, there is need for new approaches to visualization and analysis of climate data if we are to gain all the insights available in ultra-large data sets produced by high-resolution model output and ensemble integrations of climate models such as those produced for the Coupled Model Intercomparison Project. Towards that end, we have developed new visualization techniques for performing correlation analysis. We have also introduced highly scalable, parallel rendering methods for visualizing large-scale 3D data. This project was done jointly with climate scientists and visualization researchers at Argonne National Laboratory and NCAR.
Correlation between two methods of florbetapir PET quantitative analysis.
Breault, Christopher; Piper, Jonathan; Joshi, Abhinay D; Pirozzi, Sara D; Nelson, Aaron S; Lu, Ming; Pontecorvo, Michael J; Mintun, Mark A; Devous, Michael D
2017-01-01
This study evaluated performance of a commercially available standardized software program for calculation of florbetapir PET standard uptake value ratios (SUVr) in comparison with an established research method. Florbetapir PET images for 183 subjects clinically diagnosed as cognitively normal (CN), mild cognitive impairment (MCI) or probable Alzheimer's disease (AD) (45 AD, 60 MCI, and 78 CN) were evaluated using two software processing algorithms. The research method uses a single florbetapir PET template generated by averaging both amyloid positive and amyloid negative registered brains together. The commercial software simultaneously optimizes the registration between the florbetapir PET images and three templates: amyloid negative, amyloid positive, and an average. Cortical average SUVr values were calculated across six predefined anatomic regions with respect to the whole cerebellum reference region. SUVr values were well correlated between the two methods (r2 = 0.98). The relationship between the methods computed from the regression analysis is: Commercial method SUVr = (0.9757*Research SUVr) + 0.0299. A previously defined cutoff SUVr of 1.1 for distinguishing amyloid positivity by the research method corresponded to 1.1 (95% CI = 1.098, 1.11) for the commercial method. This study suggests that the commercial method is comparable to the published research method of SUVr analysis for florbetapir PET images, thus facilitating the potential use of standardized quantitative approaches to PET amyloid imaging.
Multifractal Detrended Cross-Correlation Analysis of agricultural futures markets
Energy Technology Data Exchange (ETDEWEB)
He Lingyun, E-mail: lyhe@amss.ac.cn [Center for Futures and Financial Derivatives, College of Economics and Management, China Agricultural University, Beijing 100083 (China); Chen Shupeng [Center for Futures and Financial Derivatives, College of Economics and Management, China Agricultural University, Beijing 100083 (China)
2011-06-15
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 and greater than the latter 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 and greater than the averaged GHE when q > 0.
Efficient techniques for genotype-phenotype correlational analysis.
Saha, Subrata; Rajasekaran, Sanguthevar; Bi, Jinbo; Pathak, Sudipta
2013-04-04
Single Nucleotide Polymorphisms (SNPs) are sequence variations found in individuals at some specific points in the genomic sequence. As SNPs are highly conserved throughout evolution and within a population, the map of SNPs serves as an excellent genotypic marker. Conventional SNPs analysis mechanisms suffer from large run times, inefficient memory usage, and frequent overestimation. In this paper, we propose efficient, scalable, and reliable algorithms to select a small subset of SNPs from a large set of SNPs which can together be employed to perform phenotypic classification. Our algorithms exploit the techniques of gene selection and random projections to identify a meaningful subset of SNPs. To the best of our knowledge, these techniques have not been employed before in the context of genotype-phenotype correlations. Random projections are used to project the input data into a lower dimensional space (closely preserving distances). Gene selection is then applied on the projected data to identify a subset of the most relevant SNPs. We have compared the performance of our algorithms with one of the currently known best algorithms called Multifactor Dimensionality Reduction (MDR), and Principal Component Analysis (PCA) technique. Experimental results demonstrate that our algorithms are superior in terms of accuracy as well as run time. In our proposed techniques, random projection is used to map data from a high dimensional space to a lower dimensional space, and thus overcomes the curse of dimensionality problem. From this space of reduced dimension, we select the best subset of attributes. It is a unique mechanism in the domain of SNPs analysis, and to the best of our knowledge it is not employed before. As revealed by our experimental results, our proposed techniques offer the potential of high accuracies while keeping the run times low.
Canonical correlation analysis for gene-based pleiotropy discovery.
Directory of Open Access Journals (Sweden)
Jose A Seoane
2014-10-01
Full Text Available Genome-wide association studies have identified a wealth of genetic variants involved in complex traits and multifactorial diseases. There is now considerable interest in testing variants for association with multiple phenotypes (pleiotropy and for testing multiple variants for association with a single phenotype (gene-based association tests. Such approaches can increase statistical power by combining evidence for association over multiple phenotypes or genetic variants respectively. Canonical Correlation Analysis (CCA measures the correlation between two sets of multidimensional variables, and thus offers the potential to combine these two approaches. To apply CCA, we must restrict the number of attributes relative to the number of samples. Hence we consider modules of genetic variation that can comprise a gene, a pathway or another biologically relevant grouping, and/or a set of phenotypes. In order to do this, we use an attribute selection strategy based on a binary genetic algorithm. Applied to a UK-based prospective cohort study of 4286 women (the British Women's Heart and Health Study, we find improved statistical power in the detection of previously reported genetic associations, and identify a number of novel pleiotropic associations between genetic variants and phenotypes. New discoveries include gene-based association of NSF with triglyceride levels and several genes (ACSM3, ERI2, IL18RAP, IL23RAP and NRG1 with left ventricular hypertrophy phenotypes. In multiple-phenotype analyses we find association of NRG1 with left ventricular hypertrophy phenotypes, fibrinogen and urea and pleiotropic relationships of F7 and F10 with Factor VII, Factor IX and cholesterol levels.
Correlation analysis of electromyogram signals for multiuser myoelectric interfaces.
Khushaba, Rami N
2014-07-01
An inability to adapt myoelectric interfaces to a novel user's unique style of hand motion, or even to adapt to the motion style of an opposite limb upon which the interface is trained, are important factors inhibiting the practical application of myoelectric interfaces. This is mainly attributed to the individual differences in the exhibited electromyogram (EMG) signals generated by the muscles of different limbs. We propose in this paper a multiuser myoelectric interface which easily adapts to novel users and maintains good movement recognition performance. The main contribution is a framework for implementing style-independent feature transformation by using canonical correlation analysis (CCA) in which different users' data is projected onto a unified-style space. The proposed idea is summarized into three steps: 1) train a myoelectric pattern classifier on the set of style-independent features extracted from multiple users using the proposed CCA-based mapping; 2) create a new set of features describing the movements of a novel user during a quick calibration session; and 3) project the novel user's features onto a lower dimensional unified-style space with features maximally correlated with training data and classify accordingly. The proposed method has been validated on a set of eight intact-limbed subjects, left-and-right handed, performing ten classes of bilateral synchronous fingers movements with four electrodes on each forearm. The method was able to overcome individual differences through the style-independent framework with accuracies of > 83% across multiple users. Testing was also performed on a set of ten intact-limbed and six below-elbow amputee subjects as they performed finger and thumb movements. The proposed framework allowed us to train the classifier on a normal subject's data while subsequently testing it on an amputee's data after calibration with a performance of > 82% on average across all amputees.
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.
Asymmetric correlation matrices: an analysis of financial data
Livan, G.; Rebecchi, L.
2012-06-01
We analyse the spectral properties of correlation matrices between distinct statistical systems. Such matrices are intrinsically non-symmetric, and lend themselves to extend the spectral analyses usually performed on standard Pearson correlation matrices to the realm of complex eigenvalues. We employ some recent random matrix theory results on the average eigenvalue density of this type of matrix to distinguish between noise and non-trivial correlation structures, and we focus on financial data as a case study. Namely, we employ daily prices of stocks belonging to the American and British stock exchanges, and look for the emergence of correlations between two such markets in the eigenvalue spectrum of their non-symmetric correlation matrix. We find several non trivial results when considering time-lagged correlations over short lags, and we corroborate our findings by additionally studying the asymmetric correlation matrix of the principal components of our datasets.
Liu, An-Nuo; Wang, Lu-Lu; Li, Hui-Ping; Gong, Juan; Liu, Xiao-Hong
2016-11-22
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.
Applications of temporal kernel canonical correlation analysis in adherence studies.
John, Majnu; Lencz, Todd; Ferbinteanu, Janina; Gallego, Juan A; Robinson, Delbert G
2015-08-20
Adherence to medication is often measured as a continuous outcome but analyzed as a dichotomous outcome due to lack of appropriate tools. In this paper, we illustrate the use of the temporal kernel canonical correlation analysis (tkCCA) as a method to analyze adherence measurements and symptom levels on a continuous scale. The tkCCA is a novel method developed for studying the relationship between neural signals and hemodynamic response detected by functional MRI during spontaneous activity. Although the tkCCA is a powerful tool, it has not been utilized outside the application that it was originally developed for. In this paper, we simulate time series of symptoms and adherence levels for patients with a hypothetical brain disorder and show how the tkCCA can be used to understand the relationship between them. We also examine, via simulations, the behavior of the tkCCA under various missing value mechanisms and imputation methods. Finally, we apply the tkCCA to a real data example of psychotic symptoms and adherence levels obtained from a study based on subjects with a first episode of schizophrenia, schizophreniform or schizoaffective disorder. © The Author(s) 2015.
Analysis of Consistency of Printing Blankets using Correlation Technique
Directory of Open Access Journals (Sweden)
Lalitha Jayaraman
2010-01-01
Full Text Available This paper presents the application of an analytical tool to quantify material consistency of offset printing blankets. Printing blankets are essentially viscoelastic rubber composites of several laminas. High levels of material consistency are expected from rubber blankets for quality print and for quick recovery from smash encountered during the printing process. The present study aims at determining objectively the consistency of printing blankets at three specific torque levels of tension under two distinct stages; 1. under normal printing conditions and 2. on recovery after smash. The experiment devised exhibits a variation in tone reproduction properties of each blanket signifying the levels of inconsistency also in thicknessdirection. Correlation technique was employed on ink density variations obtained from the blanket on paper. Both blankets exhibited good consistency over three torque levels under normal printing conditions. However on smash the recovery of blanket and its consistency was a function of manufacturing and torque levels. This study attempts to provide a new metrics for failure analysis of offset printing blankets. It also underscores the need for optimizing the torque for blankets from different manufacturers.
HRAS mutation analysis in Costello syndrome: genotype and phenotype correlation.
Gripp, Karen W; Lin, Angela E; Stabley, Deborah L; Nicholson, Linda; Scott, Charles I; Doyle, Daniel; Aoki, Yoko; Matsubara, Yoichi; Zackai, Elaine H; Lapunzina, Pablo; Gonzalez-Meneses, Antonio; Holbrook, Jennifer; Agresta, Cynthia A; Gonzalez, Iris L; Sol-Church, Katia
2006-01-01
Costello syndrome is a rare condition comprising mental retardation, distinctive facial appearance, cardiovascular abnormalities (typically pulmonic stenosis, hypertrophic cardiomyopathy, and/or atrial tachycardia), tumor predisposition, and skin and musculoskeletal abnormalities. Recently mutations in HRAS were identified in 12 Japanese and Italian patients with clinical information available on 7 of the Japanese patients. To expand the molecular delineation of Costello syndrome, we performed mutation analysis in 34 North American and 6 European (total 40) patients with Costello syndrome, and detected missense mutations in HRAS in 33 (82.5%) patients. All mutations affected either codon 12 or 13 of the protein product, with G12S occurring in 30 (90.9%) patients of the mutation-positive cases. In two patients, we found a mutation resulting in an alanine substitution in position 12 (G12A), and in one patient, we detected a novel mutation (G13C). Five different HRAS mutations have now been reported in Costello syndrome, however genotype-phenotype correlation remains incomplete.
Analysis of Consistency of Printing Blankets using Correlation Technique
Directory of Open Access Journals (Sweden)
Balaraman Kumar
2010-06-01
Full Text Available This paper presents the application of an analytical tool to quantify material consistency of offset printing blankets. Printing blankets are essentially viscoelastic rubber composites of several laminas. High levels of material consistency are expected from rubber blankets for quality print and for quick recovery from smash encountered during the printing process. The present study aims at determining objectively the consistency of printing blankets at three specific torque levels of tension under two distinct stages; 1. under normal printing conditions and 2. on recovery after smash. The experiment devised exhibits a variation in tone reproduction properties of each blanket signifying the levels of inconsistency also in thickness direction. Correlation technique was employed on ink density variations obtained from the blanket on paper. Both blankets exhibited good consistency over three torque levels under normal printing conditions. However on smash the recovery of blanket and its consistency was a function of manufacturing and torque levels. This study attempts to provide a new metrics for failure analysis of offset printing blankets. It also underscores the need for optimising the torque for blankets from different manufacturers.
Correlation Analysis of Multi-Wavelength Luminosity of Fermi Blazars
Indian Academy of Sciences (India)
Xiongwei Bi; Wanquan He; Jiajin Tian; Zhimei Ding; Shuping Ge
2014-09-01
We have studied the correlations between luminosities (R, O, X, ) in radio, optical, X-ray and -ray wave bands for Fermi blazars, and found that there are significant correlations between R and , X and and O and for blazars, BL Lacs and FSRQs, but no correlation between and O for BL Lacs. These results suggest that for Fermi blazars, the high energy -ray emission can be related with radio, X-ray and optical emissions.
Image patch analysis of sunspots and active regions. I. Intrinsic dimension and correlation analysis
Moon, Kevin R; Delouille, Veronique; De Visscher, Ruben; Watson, Fraser; Hero, Alfred O
2015-01-01
Complexity of an active region is related to its flare-productivity. Mount Wilson or McIntosh sunspot classifications measure such complexity but in a categorical way, and may therefore not use all the information present in the observations. Moreover, such categorical schemes hinder a systematic study of an active region's evolution for example. We propose fine-scale quantitative descriptors for an active region's complexity and relate them to the Mount Wilson classification. We analyze the local correlation structure within continuum and magnetogram data, as well as the cross-correlation between continuum and magnetogram data. We compute the intrinsic dimension, partial correlation, and canonical correlation analysis (CCA) of image patches of continuum and magnetogram active region images taken from the SOHO-MDI instrument. We use masks of sunspots derived from continuum as well as larger masks of magnetic active regions derived from the magnetogram to analyze separately the core part of an active region fr...
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
Tang, You-Fu; Liu, Shu-Lin; Jiang, Rui-Hong; Liu, Ying-Hui
2013-03-01
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.
Nimon, Kim; Henson, Robin K.; Gates, Michael S.
2010-01-01
In the face of multicollinearity, researchers face challenges interpreting canonical correlation analysis (CCA) results. Although standardized function and structure coefficients provide insight into the canonical variates produced, they fall short when researchers want to fully report canonical effects. This article revisits the interpretation of…
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.
Analysis of correlation coefficient filtering in elasticity imaging.
Huang, Sheng-Wen; Rubin, Jonathan M; Xie, Hua; Witte, Russell S; Jia, Congxian; Olafsson, Ragnar; O'Donnell, Matthew
2008-11-01
Correlation-based speckle tracking methods are commonly used in elasticity imaging to estimate displacements. In the presence of local strain, a larger window size results in larger displacement error. To reduce tracking error, we proposed a short correlation window followed by a correlation coefficient filter. Although simulation and experimental results demonstrated the efficacy of the method, it was not clear why correlation coefficient filtering reduces tracking error since tracking error increases if normalization before filtering is not applied. In this paper, we analyzed tracking errors by estimating phase variances of the cross-correlation function and the correlation coefficient at the true time lag based on statistical properties of these functions' real and imaginary parts. The role of normalization is clarified by identifying the effect of the cross-correlation function's amplitude fluctuation on the function's imaginary part. Furthermore, we present analytic forms for predicting axial displacement error as a function of strain, system parameters (signal-to-noise ratio, center frequency, and signal and noise bandwidths), and tracking parameters (window and filter sizes) for cases with and without normalization before filtering. Simulation results correspond to theory well for both noise-free cases and general cases with an empirical correction term included for strains up to 4%.
Random matrix theory analysis of cross correlations in financial markets.
Utsugi, Akihiko; Ino, Kazusumi; Oshikawa, Masaki
2004-08-01
We confirm universal behaviors such as eigenvalue distribution and spacings predicted by random matrix theory (RMT) for the cross correlation matrix of the daily stock prices of Tokyo Stock Exchange from 1993 to 2001, which have been reported for New York Stock Exchange in previous studies. It is shown that the random part of the eigenvalue distribution of the cross correlation matrix is stable even when deterministic correlations are present. Some deviations in the small eigenvalue statistics outside the bounds of the universality class of RMT are not completely explained with the deterministic correlations as proposed in previous studies. We study the effect of randomness on deterministic correlations and find that randomness causes a repulsion between deterministic eigenvalues and the random eigenvalues. This is interpreted as a reminiscent of "level repulsion" in RMT and explains some deviations from the previous studies observed in the market data. We also study correlated groups of issues in these markets and propose a refined method to identify correlated groups based on RMT. Some characteristic differences between properties of Tokyo Stock Exchange and New York Stock Exchange are found.
An analysis of cross-correlations in an emerging market
Wilcox, Diane; Gebbie, Tim
2007-03-01
We apply random matrix theory to compare correlation matrix estimators C obtained from emerging market data. The correlation matrices are constructed from 10 years of daily data for stocks listed on the Johannesburg stock exchange (JSE) from January 1993 to December 2002. We test the spectral properties of C against random matrix predictions and find some agreement between the distributions of eigenvalues, nearest neighbour spacings, distributions of eigenvector components and the inverse participation ratios for eigenvectors. We show that interpolating both missing data and illiquid trading days with a zero-order hold increases agreement with RMT predictions. For the more realistic estimation of correlations in an emerging market, we suggest a pairwise measured-data correlation matrix. For the data set used, this approach suggests greater temporal stability for the leading eigenvectors. An interpretation of eigenvectors in terms of trading strategies is given, as opposed to classification by economic sectors.
Correlation Analysis of some Growth, Yield, Yield Components and ...
African Journals Online (AJOL)
Keywords: Correlation, Wheat; growth, yield, yield components, grain quality. INTRODUCTION. Wheat ... macaroni, biscuits, cookies, cakes, pasta, noodles and couscous; beer, many .... and 6 WAS which ensured weed free plots. Fertilizer was ...
Asymptotic distributions in the projection pursuit based canonical correlation analysis
Institute of Scientific and Technical Information of China (English)
无
2010-01-01
In this paper, associations between two sets of random variables based on the projection pursuit (PP) method are studied. The asymptotic normal distributions of estimators of the PP based canonical correlations and weighting vectors are derived.
Correlation Function Analysis of Fiber Networks: Implications for Thermal Conductivity
Martinez-Garcia, Jorge; Braginsky, Leonid; Shklover, Valery; Lawson, John W.
2011-01-01
The heat transport in highly porous fiber structures is investigated. The fibers are supposed to be thin, but long, so that the number of the inter-fiber connections along each fiber is large. We show that the effective conductivity of such structures can be found from the correlation length of the two-point correlation function of the local conductivities. Estimation of the parameters, determining the conductivity, from the 2D images of the structures is analyzed.
Analysis of transverse momentum correlations in hadronic Z decays
Barate, R; Décamp, D; Ghez, P; Goy, C; Lees, J P; Lucotte, A; Merle, E; Minard, M N; Nief, J Y; Perrodo, P; Pietrzyk, B; Alemany, R; Casado, M P; Chmeissani, M; Crespo, J M; Delfino, M C; Fernández, E; Fernández-Bosman, M; Garrido, L; Graugès-Pous, E; Juste, A; Martínez, M; Merino, G; Miquel, R; Mir, L M; Pacheco, A; Park, I C; Pascual, A; Riu, I; Sánchez, F; Colaleo, A; Creanza, D; De Palma, M; Gelao, G; Iaselli, Giuseppe; Maggi, G; Maggi, M; Nuzzo, S; Ranieri, A; Raso, G; Ruggieri, F; Selvaggi, G; Silvestris, L; Tempesta, P; Tricomi, A; Zito, G; Huang, X; Lin, J; Ouyang, Q; Wang, T; Xie, Y; Xu, R; Xue, S; Zhang, J; Zhang, L; Zhao, W; Abbaneo, D; Becker, U; Boix, G; Cattaneo, M; Cerutti, F; Ciulli, V; Dissertori, G; Drevermann, H; Forty, Roger W; Frank, M; Hagelberg, R; Halley, A W; Hansen, J B; Harvey, J; Janot, P; Jost, B; Lehraus, Ivan; Leroy, O; Mato, P; Minten, Adolf G; Moneta, L; Moutoussi, A; Ranjard, F; Rolandi, Luigi; Rousseau, D; Schlatter, W D; Schmitt, M; Schneider, O; Tejessy, W; Teubert, F; Tomalin, I R; Tournefier, E; Vreeswijk, M; Wachsmuth, H W; Ajaltouni, Ziad J; Badaud, F; Chazelle, G; Deschamps, O; Dessagne, S; Falvard, A; Ferdi, C; Gay, P; Guicheney, C; Henrard, P; Jousset, J; Michel, B; Monteil, S; Montret, J C; Pallin, D; Perret, P; Podlyski, F; Hansen, J D; Hansen, J R; Hansen, P H; Nilsson, B S; Rensch, B; Wäänänen, A; Daskalakis, G; Kyriakis, A; Markou, C; Simopoulou, Errietta; Siotis, I; Vayaki, Anna; Blondel, A; Bonneaud, G R; Brient, J C; Machefert, F P; Rougé, A; Rumpf, M; Swynghedauw, M; Tanaka, R; Valassi, Andrea; Verderi, M; Videau, H L; Focardi, E; Parrini, G; Zachariadou, K; Cavanaugh, R J; Corden, M; Georgiopoulos, C H; Hühn, T; Jaffe, D E; Antonelli, A; Bencivenni, G; Bologna, G; Bossi, F; Campana, P; Capon, G; Chiarella, V; Laurelli, P; Mannocchi, G; Murtas, F; Murtas, G P; Passalacqua, L; Pepé-Altarelli, M; Chalmers, M; Curtis, L; Lynch, J G; Negus, P; O'Shea, V; Raine, C; Scarr, J M; Teixeira-Dias, P; Thompson, A S; Thomson, E; Ward, J J; Buchmüller, O L; Dhamotharan, S; Geweniger, C; Hanke, P; Hansper, G; Hepp, V; Kluge, E E; Putzer, A; Sommer, J; Tittel, K; Werner, S; Wunsch, M; Beuselinck, R; Binnie, David M; Cameron, W; Dornan, Peter J; Girone, M; Goodsir, S M; Marinelli, N; Martin, E B; Nash, J; Sedgbeer, J K; Spagnolo, P; Williams, M D; Ghete, V M; Girtler, P; Kneringer, E; Kuhn, D; Rudolph, G; Betteridge, A P; Bowdery, C K; Buck, P G; Colrain, P; Crawford, G; Ellis, G; Finch, A J; Foster, F; Hughes, G; Jones, R W L; Robertson, N A; Williams, M; Van Gemmeren, P; Giehl, I; Hoffmann, C; Jakobs, K; Kleinknecht, K; Quast, G; Renk, B; Rohne, E; Sander, H G; Zeitnitz, C; Aubert, Jean-Jacques; Benchouk, C; Bonissent, A; Carr, J; Coyle, P; Etienne, F; Ealet, A; Motsch, F; Payre, P; Talby, M; Thulasidas, M; Aleppo, M; Antonelli, M; Ragusa, F; Berlich, R; Büscher, V; Dietl, H; Ganis, G; Hüttmann, K; Lütjens, G; Mannert, C; Männer, W; Moser, H G; Schael, S; Settles, Ronald; Seywerd, H C J; Stenzel, H; Wiedenmann, W; Wolf, G; Azzurri, P; Boucrot, J; Callot, O; Chen, S; Cordier, A; Davier, M; Duflot, L; Grivaz, J F; Heusse, P; Jacholkowska, A; Kim, D W; Le Diberder, F R; Lefrançois, J; Lutz, A M; Schune, M H; Veillet, J J; Videau, I; Zerwas, D; Bagliesi, G; Bettarini, S; Boccali, T; Bozzi, C; Calderini, G; Dell'Orso, R; Ferrante, I; Foà, L; Giassi, A; Gregorio, A; Ligabue, F; Lusiani, A; Marrocchesi, P S; Messineo, A; Palla, Fabrizio; Rizzo, G; Sanguinetti, G; Sciabà, A; Sguazzoni, G; Tenchini, Roberto; Vannini, C; Venturi, A; Verdini, P G; Blair, G A; Chambers, J T; Cowan, G D; Green, M G; Medcalf, T; Strong, J A; Von Wimmersperg-Töller, J H; Botterill, David R; Clifft, R W; Edgecock, T R; Norton, P R; Thompson, J C; Wright, A E; Bloch-Devaux, B; Colas, P; Emery, S; Kozanecki, Witold; Lançon, E; Lemaire, M C; Locci, E; Pérez, P; Rander, J; Renardy, J F; Roussarie, A; Schuller, J P; Schwindling, J; Trabelsi, A; Vallage, B; Black, S N; Dann, J H; Johnson, R P; Kim, H Y; Konstantinidis, N P; Litke, A M; McNeil, M A; Taylor, G; Booth, C N; Cartwright, S L; Combley, F; Kelly, M S; Lehto, M H; Thompson, L F; Affholderbach, K; Böhrer, A; Brandt, S; Grupen, Claus; Prange, G; Saraiva, P; Smolik, L; Stephan, F; Giannini, G; Gobbo, B; Rothberg, J E; Wasserbaech, S R; Armstrong, S R; Charles, E; Elmer, P; Ferguson, D P S; Gao, Y; González, S; Greening, T C; Hayes, O J; Hu, H; Jin, S; McNamara, P A; Nachtman, J M; Nielsen, J; Orejudos, W; Pan, Y B; Saadi, Y; Scott, I J; Walsh, J; Wu Sau Lan; Wu, X; Zobernig, G
1999-01-01
In a recent paper, evidence was presented for a significant,positive correlation between the total transverse momenta of particleson opposite hemispheres of hadronic events. A new, model independentanalysis of the data has been made. Two components can be distinguishedin the correlation, and quantitative estimates of each are given.The results form a significant test of Monte Carlo models and some of the physics behind them.
Statistical Mechanical Analysis of Compressed Sensing Utilizing Correlated Compression Matrix
Takeda, Koujin
2010-01-01
We investigate a reconstruction limit of compressed sensing for a reconstruction scheme based on the L1-norm minimization utilizing a correlated compression matrix with a statistical mechanics method. We focus on the compression matrix modeled as the Kronecker-type random matrix studied in research on multi-input multi-output wireless communication systems. We found that strong one-dimensional correlations between expansion bases of original information slightly degrade reconstruction performance.
Analysis of experimental data on correlations between cumulative particles
Energy Technology Data Exchange (ETDEWEB)
Vlasov, A.V.; Doroshkevich, E.A.; Leksin, G.A. [Institute of Theoretical and Experimental Physics, Moscow (Russian Federation)] [and others
1995-04-01
Experimental data on correlations between cumulative particles are analyzed. A space-time and energy-transfer pattern of hadron-nucleus interaction based on both correlation data and data on the inclusive spectra of cumulative particles is considered. A new variable that is convenient for describing the production of cumulative particles is proposed using the concept of symmetry between the one-particle and multiparticle distributions. 32 refs., 9 figs., 1 tab.
Two-Dimensional Correlation Method for Polymer Analysis
Energy Technology Data Exchange (ETDEWEB)
Herman, Matthew Joseph [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2015-06-08
Since its introduction by Noda in 1986 two-dimension correlation spectroscopy has been offering polymer scientists an opportunity to look more deeply into collected spectroscopic data. When the spectra are recorded in response to an external perturbation, it is possible to correlate the spectra and expand the information over a separate spectra axis allow for enhancement of spectral resolution, the ability to determine synchronous change, and a unique way to organize observed changes in the spectra into sequential order following a set of three simple rules. By organizing the 2D spectra into synchronous change plots and asynchronous change plots it is possible to correlate change between spectral regions and develop their temporal relationships to one another. With the introduction of moving-window correlation-spectroscopy by Thomas and Richardson in 2000, a method of binning and processing data, it became possible to directly correlate relationships generated in the spectra from the change in the perturbation variable. This method takes advantage of the added resolution of two-dimension spectroscopy and has been applied to study very week transitions found in polymer materials. Appling both of these techniques we are beginning to develop an understanding of how polymers decay under radiolytic aging, to develop a stronger understanding of changes in mechanical properties and the service capabilities of materials.
A Longitudinal Analysis of Adolescent Smoking and Its Correlates.
Eckhardt, Laura; And Others
1994-01-01
This study examined cross-sectional correlates of smoking during early and late adolescence to compare patterns of prediction of smoking at both stages. Intention to smoke was the strongest predictor of smoking during both stages, particularly in late adolescence, as well as being the strongest predictor of changes in smoking. (SM)
Analysis of short-distance current correlators using OPE
Tomii, M; Fahy, B; Fukaya, H; Hashimoto, S; Noaki, J
2015-01-01
We investigate the correlators of flavor non-singlet bilinear operators calculated on the lattice at short distances. In the continuum theory, non-perturbative effects are encoded in the form of the operator product expansion (OPE). We test the prediction of OPE by comparing lattice results with those in the continuum theory. We also determine the renormalization factors of quark currents.
Analysis of the correlation dimension for inertial particles
Energy Technology Data Exchange (ETDEWEB)
Gustavsson, Kristian [Department of Physics, University of Tor Vergata, 00133 Rome (Italy); Department of Physics, Göteborg University, 41296 Gothenburg (Sweden); Mehlig, Bernhard [Department of Physics, Göteborg University, 41296 Gothenburg (Sweden); Wilkinson, Michael [Department of Mathematics and Statistics, The Open University, Walton Hall, Milton Keynes MK7 6AA (United Kingdom)
2015-07-15
We obtain an implicit equation for the correlation dimension which describes clustering of inertial particles in a complex flow onto a fractal measure. Our general equation involves a propagator of a nonlinear stochastic process in which the velocity gradient of the fluid appears as additive noise. When the long-time limit of the propagator is considered our equation reduces to an existing large-deviation formalism from which it is difficult to extract concrete results. In the short-time limit, however, our equation reduces to a solvability condition on a partial differential equation. In the case where the inertial particles are much denser than the fluid, we show how this approach leads to a perturbative expansion of the correlation dimension, for which the coefficients can be obtained exactly and in principle to any order. We derive the perturbation series for the correlation dimension of inertial particles suspended in three-dimensional spatially smooth random flows with white-noise time correlations, obtaining the first 33 non-zero coefficients exactly.
Correlational Analysis of Servant Leadership and School Climate
Black, Glenda Lee
2010-01-01
The purpose of this mixed-method research study was to determine the extent that servant leadership was correlated with perceptions of school climate to identify whether there was a relationship between principals' and teachers' perceived practice of servant leadership and of school climate. The study employed a mixed-method approach by first…
Image patch analysis of sunspots and active regions. I. Intrinsic dimension and correlation analysis
Moon, Kevin R.; Li, Jimmy J.; Delouille, Véronique; De Visscher, Ruben; Watson, Fraser; Hero, Alfred O.
2016-01-01
Context. The flare productivity of an active region is observed to be related to its spatial complexity. Mount Wilson or McIntosh sunspot classifications measure such complexity but in a categorical way, and may therefore not use all the information present in the observations. Moreover, such categorical schemes hinder a systematic study of an active region's evolution for example. Aims: We propose fine-scale quantitative descriptors for an active region's complexity and relate them to the Mount Wilson classification. We analyze the local correlation structure within continuum and magnetogram data, as well as the cross-correlation between continuum and magnetogram data. Methods: We compute the intrinsic dimension, partial correlation, and canonical correlation analysis (CCA) of image patches of continuum and magnetogram active region images taken from the SOHO-MDI instrument. We use masks of sunspots derived from continuum as well as larger masks of magnetic active regions derived from magnetogram to analyze separately the core part of an active region from its surrounding part. Results: We find relationships between the complexity of an active region as measured by its Mount Wilson classification and the intrinsic dimension of its image patches. Partial correlation patterns exhibit approximately a third-order Markov structure. CCA reveals different patterns of correlation between continuum and magnetogram within the sunspots and in the region surrounding the sunspots. Conclusions: Intrinsic dimension has the potential to distinguish simple from complex active regions. These results also pave the way for patch-based dictionary learning with a view toward automatic clustering of active regions.
Penetration Resistance of Armor Ceramics: Dimensional Analysis and Property Correlations
2015-08-01
rocksalt [34]). Amorphization in B4C is a stress-induced change from trigonal (i.e., rhombohedral) crystal structure to a non - crystalline solid ...Correlations by JD Clayton A reprint from the International Journal of Impact Engineering. 2015;85:124–131 Approved for...by JD Clayton Weapons and Materials Research Directorate, ARL A reprint from the International Journal of Impact Engineering. 2015;85:124
Dynamics of market correlations: Taxonomy and portfolio analysis
Onnela, J.-P.; Chakraborti, A.; Kaski, K.; Kertész, J.; Kanto, A.
2003-11-01
The time dependence of the recently introduced minimum spanning tree description of correlations between stocks, called the “asset tree” has been studied in order to reflect the financial market taxonomy. The nodes of the tree are identified with stocks and the distance between them is a unique function of the corresponding element of the correlation matrix. By using the concept of a central vertex, chosen as the most strongly connected node of the tree, an important characteristic is defined by the mean occupation layer. During crashes, due to the strong global correlation in the market, the tree shrinks topologically, and this is shown by a low value of the mean occupation layer. The tree seems to have a scale-free structure where the scaling exponent of the degree distribution is different for “business as usual” and “crash” periods. The basic structure of the tree topology is very robust with respect to time. We also point out that the diversification aspect of portfolio optimization results in the fact that the assets of the classic Markowitz portfolio are always located on the outer leaves of the tree. Technical aspects such as the window size dependence of the investigated quantities are also discussed.
Correlation analysis on alpha attenuation and nasal skin temperature
Nozawa, Akio; Tacano, Munecazu
2009-01-01
Some serious accidents caused by declines in arousal level, such as traffic accidents and mechanical control mistakes, have become issues of social concern. The physiological index obtained by human body measurement is expected to offer a leading tool for evaluating arousal level as an objective indicator. In this study, declines in temporal arousal levels were evaluated by nasal skin temperature. As arousal level declines, sympathetic nervous activity is decreased and blood flow in peripheral vessels is increased. Since peripheral vessels exist just under the skin on the fingers and nose, the psychophysiological state can be judged from the displacement of skin temperature caused by changing blood flow volume. Declining arousal level is expected to be observable as a temperature rise in peripheral parts of the body. The objective of this experiment was to obtain assessment criteria for judging declines in arousal level by nasal skin temperature using the alpha attenuation coefficient (AAC) of electroencephalography (EEG) as a reference benchmark. Furthermore, a psychophysical index of sleepiness was also measured using a visual analogue scale (VAS). Correlations between nasal skin temperature index and EEG index were analyzed. AAC and maximum displacement of nasal skin temperature displayed a clear negative correlation, with a correlation coefficient of -0.55.
Dynamics of market correlations: taxonomy and portfolio analysis.
Onnela, J-P; Chakraborti, A; Kaski, K; Kertész, J; Kanto, A
2003-11-01
The time dependence of the recently introduced minimum spanning tree description of correlations between stocks, called the "asset tree" has been studied in order to reflect the financial market taxonomy. The nodes of the tree are identified with stocks and the distance between them is a unique function of the corresponding element of the correlation matrix. By using the concept of a central vertex, chosen as the most strongly connected node of the tree, an important characteristic is defined by the mean occupation layer. During crashes, due to the strong global correlation in the market, the tree shrinks topologically, and this is shown by a low value of the mean occupation layer. The tree seems to have a scale-free structure where the scaling exponent of the degree distribution is different for "business as usual" and "crash" periods. The basic structure of the tree topology is very robust with respect to time. We also point out that the diversification aspect of portfolio optimization results in the fact that the assets of the classic Markowitz portfolio are always located on the outer leaves of the tree. Technical aspects such as the window size dependence of the investigated quantities are also discussed.
Correlation analysis of PCB and comparison of test-analysis model reduction methods
Institute of Scientific and Technical Information of China (English)
Xu Fei; Li Chuanri; Jiang Tongmin; Rong Shuanglong
2014-01-01
The validity of correlation analysis between finite element model (FEM) and modal test data is strongly affected by three factors, i.e., quality of excitation and measurement points in modal test, FEM reduction methods, and correlation check techniques. A new criterion based on modified mode participation (MMP) for choosing the best excitation point is presented. Comparison between this new criterion and mode participation (MP) criterion is made by using Case 1 with a simple printed circuit board (PCB). The result indicates that this new criterion produces better results. In Case 2, 35 measure-ment points are selected to perform modal test and correlation analysis while 9 selected in Case 3. System equivalent reduction expansion process (SEREP), modal assurance criteria (MAC), coordinate modal assurance criteria (CoMAC), pseudo orthogonality check (POC) and coordinate orthogonality check (CORTHOG) are used to show the error introduced by modal test in Cases 2 and 3. Case 2 shows that additional errors which cannot be identified by using CoMAC can be found by using CORTHOG. In both Cases 2 and 3, Guyan reduction, improved reduced system (IRS) method, SEREP and Hybrid reduction are compared for accuracy and robustness. The results suggest that the quality of the reduction process is problem dependent. However, the IRS method is an improvement over the Guyan reduction, and the Hybrid reduction is an improvement over the SEREP reduction.
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.
Correlation analysis of PCB and comparison of test-analysis model reduction methods
Directory of Open Access Journals (Sweden)
Xu Fei
2014-08-01
Full Text Available The validity of correlation analysis between finite element model (FEM and modal test data is strongly affected by three factors, i.e., quality of excitation and measurement points in modal test, FEM reduction methods, and correlation check techniques. A new criterion based on modified mode participation (MMP for choosing the best excitation point is presented. Comparison between this new criterion and mode participation (MP criterion is made by using Case 1 with a simple printed circuit board (PCB. The result indicates that this new criterion produces better results. In Case 2, 35 measurement points are selected to perform modal test and correlation analysis while 9 selected in Case 3. System equivalent reduction expansion process (SEREP, modal assurance criteria (MAC, coordinate modal assurance criteria (CoMAC, pseudo orthogonality check (POC and coordinate orthogonality check (CORTHOG are used to show the error introduced by modal test in Cases 2 and 3. Case 2 shows that additional errors which cannot be identified by using CoMAC can be found by using CORTHOG. In both Cases 2 and 3, Guyan reduction, improved reduced system (IRS method, SEREP and Hybrid reduction are compared for accuracy and robustness. The results suggest that the quality of the reduction process is problem dependent. However, the IRS method is an improvement over the Guyan reduction, and the Hybrid reduction is an improvement over the SEREP reduction.
Statistical analysis of highly correlated systems in biology and physics
Martin, Hector Garcia
In this dissertation, I present my work on the statistical study of highly correlated systems in three fields of science: ecology, microbial ecology and physics. I propose an explanation for how the highly correlated distribution of species individuals, and an abundance distribution commonly observed in ecological systems, give rise to a power law dependence between a given area and the number of unique species it harbors. This is one of the oldest known ecological patterns: the power-law Species Area Rule. As a natural extension of my studies in ecology, I have undertaken both theoretical research and field work in the developing field of microbial ecology. In particular, I participated in a multidisciplinary study of the impact of microbes on the formation of macroscopic calcium carbonate terraces at Yellowstone National Park Hot Springs. I have used ecological techniques to characterize the biodiversity of our study site and developed a new bootstrap method for extracting abundance information from clone libraries. This has singled out the most abundant microorganisms and paved the way for future studies of the possible non-passive role of microorganisms in carbonate precipitation. The third part of my thesis uses statistical techniques to explore the correlations in rotating Bose-Einstein condensates. I have used finite difference techniques to solve the Gross-Pitaevskii equation in order to obtain the structure of a vortex in a lattice. Surprisingly, I have found that, in order to understand this structure, it is necessary to add a correction to the Gross-Pitaevskii equation which introduces a dependence on the particle scattering length. I have also used Path Integral Monte Carlo techniques to explore the limit of rapid rotations, where the Gross-Pitaevskii equation is no longer valid. Interestingly, the Gross-Pitaevskii equation seems to be valid for much higher densities than expected if properly renormalized. I show that, in accord with the prediction of
The Asian crisis contagion: A dynamic correlation approach analysis
Directory of Open Access Journals (Sweden)
Essaadi Essahbi
2009-01-01
Full Text Available In this paper we are testing for contagion caused by the Thai baht collapse of July 1997. In line with earlier work, shift-contagion is defined as a structural change within the international propagation mechanisms of financial shocks. We adopt Bai and Perron's (1998 structural break approach in order to detect the endogenous break points of the pair-wise time-varying correlations between Thailand and seven Asian stock market returns. Our approach enables us to solve the misspecification problem of the crisis window. Our results illustrate the existence of shift-contagion in the Asian crisis caused by the crisis in Thailand.
Almost Periodically Correlated Time Series in Business Fluctuations Analysis
Lenart, Lukasz
2012-01-01
We propose a non-standard subsampling procedure to make formal statistical inference about the business cycle, one of the most important unobserved feature characterising fluctuations of economic growth. We show that some characteristics of business cycle can be modelled in a non-parametric way by discrete spectrum of the Almost Periodically Correlated (APC) time series. On the basis of estimated characteristics of this spectrum business cycle is extracted by filtering. As an illustration we characterise the man properties of business cycles in industrial production index for Polish economy.
Family dynamics and self-injury behaviors: a correlation analysis.
Halstead, Ruth Ogden; Pavkov, Thomas W; Hecker, Lorna L; Seliner, Michelle M
2014-04-01
This study tested the relationship between family dynamics and self-injury. A total of 189 participants responded to a web-based survey collecting information related to previous self-injury behaviors and family dynamics. Participants were over 18 years old who had used self-injury (intentionally harming themselves physically to relieve painful emotions without suicidal intent), but who had not used self-injury for over a year. Results indicated that healthy family dynamics were negatively correlated and associated with higher scores of self-injury behaviors. This study offers some evidence that family dynamics influence self-injury behaviors. The implications for family therapy are discussed.
Cochlear otosclerosis (otospongiosis): CT analysis with audiometric correlation
Energy Technology Data Exchange (ETDEWEB)
Swartz, J.D.; Mandell, D.W.; Berman, S.E.; Wolfson, R.J.; Marlowe, F.I.; Popky, G.L.
1985-04-01
Ninety patients who had suspected or confirmed fenestral or cochlear otosclerosis underwent CT examination. Foci of demineralization in the otic capsule were discovered in 20 ears (12 patients). Audiometric studies of the 12 patients revealed sensorineural hearing loss (SNHL) with distinct correlation of CT findings with progressivity and with involvement of the frequency level subtended by the specific area of the cochlea involved. Foci of abnormal increased density, presumably representing the healed phase of this disorder, were found less frequently than expected. There was a predilection for the basilar turn. All patients had static SNHL in the higher frequencies. The healed phase of this disorder is probably not consistently diagnosable with CT.
Analysis of size correlations for microdroplets produced by ultrasonic atomization.
Dalmoro, Annalisa; Barba, Anna Angela; d'Amore, Matteo
2013-01-01
Microencapsulation techniques are widely applied in the field of pharmaceutical production to control drugs release in time and in physiological environments. Ultrasonic-assisted atomization is a new technique to produce microencapsulated systems by a mechanical approach. Interest in this technique is due to the advantages evidenceable (low level of mechanical stress in materials, reduced energy request, reduced apparatuses size) when comparing it to more conventional techniques. In this paper, the groundwork of atomization is introduced, the role of relevant parameters in ultrasonic atomization mechanism is discussed, and correlations to predict droplets size starting from process parameters and material properties are presented and tested.
Analysis of Size Correlations for Microdroplets Produced by Ultrasonic Atomization
Directory of Open Access Journals (Sweden)
Annalisa Dalmoro
2013-01-01
Full Text Available Microencapsulation techniques are widely applied in the field of pharmaceutical production to control drugs release in time and in physiological environments. Ultrasonic-assisted atomization is a new technique to produce microencapsulated systems by a mechanical approach. Interest in this technique is due to the advantages evidenceable (low level of mechanical stress in materials, reduced energy request, reduced apparatuses size when comparing it to more conventional techniques. In this paper, the groundwork of atomization is introduced, the role of relevant parameters in ultrasonic atomization mechanism is discussed, and correlations to predict droplets size starting from process parameters and material properties are presented and tested.
Maximum-likelihood analysis of the COBE angular correlation function
Seljak, Uros; Bertschinger, Edmund
1993-01-01
We have used maximum-likelihood estimation to determine the quadrupole amplitude Q(sub rms-PS) and the spectral index n of the density fluctuation power spectrum at recombination from the COBE DMR data. We find a strong correlation between the two parameters of the form Q(sub rms-PS) = (15.7 +/- 2.6) exp (0.46(1 - n)) microK for fixed n. Our result is slightly smaller than and has a smaller statistical uncertainty than the 1992 estimate of Smoot et al.
Correlator data analysis for the array feed compensation system
Iijima, B.; Fort, D.; Vilnrotter, V.
1994-05-01
The real-time array feed compensation system is currently being evaluated at DSS 13. This system recovers signal-to-noise ratio (SNR) loss due to mechanical antenna deformations by using an array of seven Ka-band (33.7-GHz) horns to collect the defocused signal fields. The received signals are downconverted and digitized, in-phase and quadrature samples are generated, and combining weights are applied before the samples are recombined. It is shown that when optimum combining weights are employed, the SNR of the combined signal approaches the sum of the channel SNR's. The optimum combining weights are estimated directly from the signals in each channel by the Real-Time Block 2 (RTB2) correlator; since it was designed for very-long-baseline interferometer (VLBI) applications, it can process broadband signals as well as tones to extract the required weight estimates. The estimation algorithms for the optimum combining weights are described for tones and broadband sources. Data recorded in correlator output files can also be used off-line to estimate combiner performance by estimating the SNR in each channel, which was done for data taken during a Jupiter track at DSS 13.
The effects of common risk factors on stock returns: A detrended cross-correlation analysis
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.
Directory of Open Access Journals (Sweden)
Dror Y Kenett
Full Text Available 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.
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.
FUNCTIONAL ANALYSIS AND GENOTYPE-PHENOTYPE CORRELATIONS IN WILSON DISEASE
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Elena Scvortova
2013-10-01
Full Text Available Abstract: Knowledge of how mutations other than p.H1069Q translate into the basic defect in Wilson disease (WD is scarce due to the low incidence of homozygous index cases. A total of 12 homozygous mutations of ATP7B, were examined for their functional activity. Transfected Chinese hamster ovary cells (CHO-K1 exposed to elevated copper levels was used as a model for predicting the severity of different WD mutations. The results of this research have direct implications for WD diagnosis. Our data strongly confirms that phenotypic presentation of the patients is related to the ATP7B mutation, providing evidence for genotype - phenotype correlations and can explain in part the variable clinical features observed in patients with WD. The results we have provided help to highlight the information still needed for understanding the function and malfunction of ATP7B and its role in the disease.
New Insights into Time Series Analysis II - No Correlated Observations
Lopes, C E Ferreira
2016-01-01
Statistical parameters are used in finance, weather, industrial, science, among other vast number of different fields to draw conclusions. They are also used to identify variability patterns on photometric data in order to select non-stochastic variations, indicative of astrophysical effects. New more efficient selection methods are mandatory to analyses the huge amount of astronomical data. Our aims are to improve the current methods used to select non-stochastic variations on non-correlated data. A new approach including a modified Strateva function are used to select non-stochastic variations. Monte-Carlo simulation and public time-domain data are used to estimate its accuracy and performance. We introduce 15 modified statistical parameters covering different features of statistical distribution, like; average, dispersion, and shape parameters. Many of dispersion and shape parameters are unbound parameters, i.e. equations which do not require the calculation of the average. Unbound parameters are computed ...
CORRELATION ANALYSIS OF THE AUDIT COMMITTEE AND STRUCTURAL INDICATORS
Directory of Open Access Journals (Sweden)
FÜLÖP MELINDA TIMEA
2014-02-01
Full Text Available The main role of corporate governance is to restore market confidence and in this process plays an important role the audit committee. The purpose of this case study is to analyze the correlations between the Audit Committee and structural indicators. Considering the achievement of the objectives proposed in this research, our research is based on a deductive approach from general aspects to particular aspects that combines quantitative and qualitative studies. Theoretical knowledge is used for a better understanding of a phenomenon and not for making assumptions. Thus, in order to achieve our study, we selected 25 companies listed on Berlin Stock Exchange. Following this study, we concluded that the role of the audit committee is crucial.
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.
CORRELATIVE ANALYSIS OF COSMIC RAY INTENSITY AND SOLAR ACTIVITY PARAMETERS
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M. ROY
2014-02-01
Full Text Available Incoming cosmic ray shows significant intensity modulation in association with different solar geo parameters during their passage through heliosphere. Cosmic ray intensity is found anticorrelated with solar activity parameters. Using pressure corrected data of Mcmurdo neutron monitor, modulation of cosmic ray is analyzed covering solar cycles 21, 22, 23 and 24 (from 1976 to 2013. Negative and high correlations are obtained with some time lag for most of the solar parameters. Difference in shapes of hysteresis curves CRI~SSN, CRI~SRF. CRI~CI and CRI~FI for odd and even cycles pointed out that different mechanisms convection and diffusion are the dominating factors to drift cosmic ray particles.
Cross Correlation Analysis of Multi-Channel Near Infrared Spectroscopy
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Raul Fernandez Rojas
2016-02-01
Full Text Available In this paper we present the use of a signal proces sing technique to find dominant channels in near infrared spectroscopy (NIRS. Cross correlatio n is computed to compare measuring channels and identify delays among the channels. In addition, visual inspection was used to detect potential dominant channels. The results sho wed that the visual analysis exposed pain- related activations in the primary somatosensory co rtex (S1 after stimulation which is consistent with similar studies and the cross corre lation analysis found dominant channels on both cerebral hemispheres. The analysis also showed a relationship between dominant channels and neighbouring channels. Therefore, our results p resent a new method to detect dominant regions in the cerebral cortex using near-infrared spectroscopy. These results have also implications in the reduction of number of channels by eliminating irrelevant channels for the experiment
Correlation of the CT analysis and audiometry in otosclerosis
Energy Technology Data Exchange (ETDEWEB)
Kiyomizu, Kensuke; Tono, Tetsuya; Yang, Dewen; Haruta, Atsushi; Kodama, Takao; Kato, Eiji; Komune, Shizuo [Miyazaki Medical Coll., Kiyotake (Japan)
1998-11-01
Thirty-three patients (62 ears) with surgically confirmed otosclerosis underwent a preoperative CT examination in order to determine the presence of any correlation between the audiometric and CT findings. Based on the CT findings, the ears were classified into five groups as follows: group A; 25 ears (40.3%) with normal CT findings, group B1; 15 ears (24.2%) with demineralization in the region of the fissula antefenestram, group B2; 12 ears (19.4%) with demineralization around the anterior to the oval window, group B3; 4 ears (6.5%) with demineralization surrounding the cochlea, and group C; 6 ears (9.7%) with thick anterior and posterior plaques. The expansion of demineralization led to an increase in average bone conduction hearing level: group A ; 27.1 dB, group B1; 30.6 dB, group B2; 34.6 dB, group B3; 36.7 dB, and group C; 30.3 dB. This increase is most likely due to progressive labyrinthine otosclerosis. Group C in the average air-bone gap was greater (37.5 dB) than that in the patients with demineralization, group B1 (21.6 dB), group B2 (28.2 dB), group B3 (26.7 dB), the Carhart effect of group C was smaller than that of any other groups, thus suggesting the mode of otosclerosis progression in group C to be different from that in patients with demineralization. The results of the present study indicate that the preoperative CT findings of otosclerosis correlate with the audiometry findings, thus proving the usefulness of CT in diagnosing otosclerosis. (author)
Midkine expression in 52 human meningiomas A correlation analysis
Institute of Scientific and Technical Information of China (English)
Xinjun Li; Xiangguo Xia
2008-01-01
BACKGROUND: Several studies have shown that midkine directly participates in tumor cell growth and invasion, as well as the regulation of angiogenesis.OBJECTIVE: To investigate midkine expression in meningioma tissue in relation to angiogenesis, invasion, peritumoral edema, and clinicopathology.DESIGN, TIME AND SETTING: The present clinical, case-controlled, neuropathological study was performed at the Laboratory of Molecular Organism, People's Hospital of Deyang City between May 2007 and April 2008.MATERIALS: Fifty-two meningioma tissues were classified by WHO tumor classification of the central nervous system, comprising 40 grade Ⅰ meningioma, five grade Ⅱ meningioma, and seven grade Ⅲ meningioma. Ten normal, human cerebral maters were selected from cerebral trauma patients.METHODS: Midkine protein expression and mean microvessel density were detected using immunohistochemical techniques. Simultaneously, all data were statistically analyzed.MAIN OUTCOME MEASURES: Midkine expression and microvessel density in meningiomas and normal cerebral maters.RESULTS: The positive midkine expression rate was 64% in the meningioma tissues. However, midkine expression was not detected in normal cerebral mater tissue. The mean microvessel density was 82.0±22.7 in the meningiomas, and 25.8±6.2 in the normal cerebral mater tissues. There was significant difference in midkine expression and mean microvessel density between meningioma tissues and human cerebral maters (P 0.05). However, it closely correlated with patient clinical condition, pathological grade, invasion, and peritumoral edema (r =0.378 5, 0.741 2, 0.651 8, 0.614 2, P < 0.05).CONCLUSION: Midkinc protein was overexpressed in meningiomas and correlated to tumor angiogenesis, invasion, peritumoral edema, and clinicopathology.
NDVI and Panchromatic Image Correlation Using Texture Analysis
2010-03-01
18 Equation 4. Equations of the eight GLCM texture features (After Shi, 2003)....................21 Equation 5...analysis and image classification like the Grey Level Co-occurrence Matrix ( GLCM ) by Haralick, 1973. First-order and second-order texture measures on... GLCM consist of Standard Deviation, Range, Minimum, Maximum and Mean. The second order of texture measures includes Angular Second Moment, Contrast
Pinto da Costa, Joaquim
2015-01-01
This book examines in detail the correlation, more precisely the weighted correlation, and applications involving rankings. A general application is the evaluation of methods to predict rankings. Others involve rankings representing human preferences to infer user preferences; the use of weighted correlation with microarray data and those in the domain of time series. In this book we present new weighted correlation coefficients and new methods of weighted principal component analysis. We also introduce new methods of dimension reduction and clustering for time series data, and describe some theoretical results on the weighted correlation coefficients in separate sections.
Spatio-Chromatic Adaptation via Higher-Order Canonical Correlation Analysis of Natural Images
Gutmann, Michael U.; Valero Laparra; Aapo Hyvärinen; Jesús Malo
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...
Correlates of formal operational reasoning: A neo-piagetian analysis
Niaz, Mansoor
Most Piagetian formal operational reasoning tasks show horizontal decalage; that is, subjects pass certain tasks and fail others that have the same logical structure. The study reported here analyzes the importance of individual difference variables, as postulated by the neo-Piagetian theory of Pascual-Leone, in explaining subject performance in formal reasoning. A sample of 72 freshman students were administered a test of formal reasoning having 20 items of different types of reasoning, and the tests of the individual difference variables. Results obtained from multiple regression analyses show that Pascual-Leone's structural M-capacity (Ms) is the most consistent predictor of success in the different formal reasoning tasks, followed by Witkin's cognitive style, and to a much lesser degree Raven's progressive matrices, and Pascual-Leone's functional M-capacity (Mf). It was found that in the total score on the 20 items of formal reasoning, Ms accounted for 23.3% of the variance (R = 0.483, F = 6.39, p = 0.014) and Witkin's Group Embedded Figures Test, increased the multiple R significantly (F = 7.77, p = 0.007) and accounted for 7.6% of the variance. Mf and the Raven test did not make a significant contribution to the regression equation. Correlation coefficients among most of the items having the same reasoning pattern but different content are generally low but statistically significant (p < 0.01). Intercorrelations among items having the same formal reasoning pattern and content are fairly high (p < 0.001). These results emphasize the importance of individual difference variables: information-processing capacity (Pascual-Leone) and oversensitivity to potentially misleading information (Witkin). It is suggested that in order to understand student performance in formal reasoning tasks, we should expect horizontal decalages as a rule and not the exception, as Piaget had postulated. Educational implications are drawn.
Correlation analysis on partition of rare earth in ion-exchangeable phase from weathered crust ores
Institute of Scientific and Technical Information of China (English)
CHI Ru-an; DAI Zu-xu; XU Zhi-gao; WU Yuan-xin; WANG Cun-wen
2006-01-01
The rare earth(RE) in weathered crust ores mainly exists as ion-exchangeable phase, approximately 80%. The correlation analysis on partition of 376 samples in ion-exchangeable phase from weathered crust ores was conducted. The results show that partition both among heavy RE elements and light RE elements with high partition appears positive correlation, but partition sums between the heavy RE elements and the light RE elements appear close negative correlation obviously. Clear negative correlations exist between the light RE elements (except Ce) and yttrium(Y). Matrix of correlation analysis on this partition can be divided into three zones. The correlated coefficient variation from negative to positive in zones B and C occurs at Gd, so does that in zones B and A (except Ce, Eu, and Sm), suggesting that RE elements can be divided into two groups with Gd as border. This phenomenon is called Gadolinium-broken effect.
Vortex metrology using Fourier analysis techniques: vortex networks correlation fringes.
Angel-Toro, Luciano; Sierra-Sosa, Daniel; Tebaldi, Myrian; Bolognini, Néstor
2012-10-20
In this work, we introduce an alternative method of analysis in vortex metrology based on the application of the Fourier optics techniques. The first part of the procedure is conducted as is usual in vortex metrology for uniform in-plane displacement determination. On the basis of two recorded intensity speckled distributions, corresponding to two states of a diffuser coherently illuminated, we numerically generate an analytical signal from each recorded intensity pattern by using a version of the Riesz integral transform. Then, from each analytical signal, a two-dimensional pseudophase map is generated in which the vortices are located and characterized in terms of their topological charges and their core's structural properties. The second part of the procedure allows obtaining Young's interference fringes when Fourier transforming the light passing through a diffracting mask with multiple apertures at the locations of the homologous vortices. In fact, we use the Fourier transform as a mathematical operation to compute the far-field diffraction intensity pattern corresponding to the multiaperture set. Each aperture from the set is associated with a rectangular hole that coincides both in shape and size with a pixel from recorded images. We show that the fringe analysis can be conducted as in speckle photography in an extended range of displacement measurements. Effects related with speckled decorrelation are also considered. Our experimental results agree with those of speckle photography in the range in which both techniques are applicable.
Genome-scale cluster analysis of replicated microarrays using shrinkage correlation coefficient.
Yao, Jianchao; Chang, Chunqi; Salmi, Mari L; Hung, Yeung Sam; Loraine, Ann; Roux, Stanley J
2008-06-18
Currently, clustering with some form of correlation coefficient as the gene similarity metric has become a popular method for profiling genomic data. The Pearson correlation coefficient and the standard deviation (SD)-weighted correlation coefficient are the two most widely-used correlations as the similarity metrics in clustering microarray data. However, these two correlations are not optimal for analyzing replicated microarray data generated by most laboratories. An effective correlation coefficient is needed to provide statistically sufficient analysis of replicated microarray data. In this study, we describe a novel correlation coefficient, shrinkage correlation coefficient (SCC), that fully exploits the similarity between the replicated microarray experimental samples. The methodology considers both the number of replicates and the variance within each experimental group in clustering expression data, and provides a robust statistical estimation of the error of replicated microarray data. The value of SCC is revealed by its comparison with two other correlation coefficients that are currently the most widely-used (Pearson correlation coefficient and SD-weighted correlation coefficient) using statistical measures on both synthetic expression data as well as real gene expression data from Saccharomyces cerevisiae. Two leading clustering methods, hierarchical and k-means clustering were applied for the comparison. The comparison indicated that using SCC achieves better clustering performance. Applying SCC-based hierarchical clustering to the replicated microarray data obtained from germinating spores of the fern Ceratopteris richardii, we discovered two clusters of genes with shared expression patterns during spore germination. Functional analysis suggested that some of the genetic mechanisms that control germination in such diverse plant lineages as mosses and angiosperms are also conserved among ferns. This study shows that SCC is an alternative to the Pearson
Genome-scale cluster analysis of replicated microarrays using shrinkage correlation coefficient
Directory of Open Access Journals (Sweden)
Loraine Ann
2008-06-01
Full Text Available Abstract Background Currently, clustering with some form of correlation coefficient as the gene similarity metric has become a popular method for profiling genomic data. The Pearson correlation coefficient and the standard deviation (SD-weighted correlation coefficient are the two most widely-used correlations as the similarity metrics in clustering microarray data. However, these two correlations are not optimal for analyzing replicated microarray data generated by most laboratories. An effective correlation coefficient is needed to provide statistically sufficient analysis of replicated microarray data. Results In this study, we describe a novel correlation coefficient, shrinkage correlation coefficient (SCC, that fully exploits the similarity between the replicated microarray experimental samples. The methodology considers both the number of replicates and the variance within each experimental group in clustering expression data, and provides a robust statistical estimation of the error of replicated microarray data. The value of SCC is revealed by its comparison with two other correlation coefficients that are currently the most widely-used (Pearson correlation coefficient and SD-weighted correlation coefficient using statistical measures on both synthetic expression data as well as real gene expression data from Saccharomyces cerevisiae. Two leading clustering methods, hierarchical and k-means clustering were applied for the comparison. The comparison indicated that using SCC achieves better clustering performance. Applying SCC-based hierarchical clustering to the replicated microarray data obtained from germinating spores of the fern Ceratopteris richardii, we discovered two clusters of genes with shared expression patterns during spore germination. Functional analysis suggested that some of the genetic mechanisms that control germination in such diverse plant lineages as mosses and angiosperms are also conserved among ferns. Conclusion
Bikondoa, Oier
2017-04-01
Multi-time correlation functions are especially well suited to study non-equilibrium processes. In particular, two-time correlation functions are widely used in X-ray photon correlation experiments on systems out of equilibrium. One-time correlations are often extracted from two-time correlation functions at different sample ages. However, this way of analysing two-time correlation functions is not unique. Here, two methods to analyse two-time correlation functions are scrutinized, and three illustrative examples are used to discuss the implications for the evaluation of the correlation times and functional shape of the correlations.
L2 Reading Comprehension and Its Correlates: A Meta-Analysis
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…
Effects of Correlated Errors on the Analysis of Space Geodetic Data
Romero-Wolf, Andres; Jacobs, C. S.
2011-01-01
As thermal errors are reduced instrumental and troposphere correlated errors will increasingly become more important. Work in progress shows that troposphere covariance error models improve data analysis results. We expect to see stronger effects with higher data rates. Temperature modeling of delay errors may further reduce temporal correlations in the data.
L2 Reading Comprehension and Its Correlates: A Meta-Analysis
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…
Lentjes, M.; Dickmann, K.; Meijer, J.
2007-01-01
Linear correlation analysis may be used as a technique for the identification of samples with a very similar chemical composition by laser induced breakdown spectroscopy. The spectrum of the “unknown” sample is correlated with a library of reference spectra. The probability of identification by
Dissection of genomic correlation matrices of US Holsteins using multivariate factor analysis
Aim of the study was to compare correlation matrices between direct genomic predictions for 31 production, fitness and conformation traits both at genomic and chromosomal level in US Holstein bulls. Multivariate factor analysis was used to quantify basic features of correlation matrices. Factor extr...
Correlation between videogame mechanics and executive functions through EEG analysis.
Mondéjar, Tania; Hervás, Ramón; Johnson, Esperanza; Gutierrez, Carlos; Latorre, José Miguel
2016-10-01
This paper addresses a different point of view of videogames, specifically serious games for health. This paper contributes to that area with a multidisciplinary perspective focus on neurosciences and computation. The experiment population has been pre-adolescents between the ages of 8 and 12 without any cognitive issues. The experiment consisted in users playing videogames as well as performing traditional psychological assessments; during these tasks the frontal brain activity was evaluated. The main goal was to analyse how the frontal lobe of the brain (executive function) works in terms of prominent cognitive skills during five types of game mechanics widely used in commercial videogames. The analysis was made by collecting brain signals during the two phases of the experiment, where the signals were analysed with an electroencephalogram neuroheadset. The validated hypotheses were whether videogames can develop executive functioning and if it was possible to identify which kind of cognitive skills are developed during each kind of typical videogame mechanic. The results contribute to the design of serious games for health purposes on a conceptual level, particularly in support of the diagnosis and treatment of cognitive-related pathologies.
Serum adiponectin levels are inversely correlated with leukemia: A meta-analysis
Directory of Open Access Journals (Sweden)
Jun-Jie Ma
2016-01-01
Conclusion: Our meta-analysis suggested that serum ADPN levels may be inversely correlated with leukemia, and ADPN levels can be used as an effective biologic marker in early diagnosis and therapeutic monitoring of leukemia.
Climate Prediction Center(CPC)Ensemble Canonical Correlation Analysis Forecast of Temperature
National Oceanic and Atmospheric Administration, Department of Commerce — The Ensemble Canonical Correlation Analysis (ECCA) temperature forecast is a 90-day (seasonal) outlook of US surface temperature anomalies. The ECCA uses Canonical...
National Oceanic and Atmospheric Administration, Department of Commerce — The Ensemble Canonical Correlation Analysis (ECCA) precipitation forecast is a 90-day (seasonal) outlook of US surface precipitation anomalies. The ECCA uses...
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 can
Time-correlated neutron analysis of a multiplying HEU source
Energy Technology Data Exchange (ETDEWEB)
Miller, E.C., E-mail: Eric.Miller@jhuapl.edu [Johns Hopkins University Applied Physics Laboratory, Laurel, MD (United States); Kalter, J.M.; Lavelle, C.M. [Johns Hopkins University Applied Physics Laboratory, Laurel, MD (United States); Watson, S.M.; Kinlaw, M.T.; Chichester, D.L. [Idaho National Laboratory, Idaho Falls, ID (United States); Noonan, W.A. [Johns Hopkins University Applied Physics Laboratory, Laurel, MD (United States)
2015-06-01
The ability to quickly identify and characterize special nuclear material remains a national security challenge. In counter-proliferation applications, identifying the neutron multiplication of a sample can be a good indication of the level of threat. Currently neutron multiplicity measurements are performed with moderated {sup 3}He proportional counters. These systems rely on the detection of thermalized neutrons, a process which obscures both energy and time information from the source. Fast neutron detectors, such as liquid scintillators, have the ability to detect events on nanosecond time scales, providing more information on the temporal structure of the arriving signal, and provide an alternative method for extracting information from the source. To explore this possibility, a series of measurements were performed on the Idaho National Laboratory's MARVEL assembly, a configurable HEU source. The source assembly was measured in a variety of different HEU configurations and with different reflectors, covering a range of neutron multiplications from 2 to 8. The data was collected with liquid scintillator detectors and digitized for offline analysis. A gap based approach for identifying the bursts of detected neutrons associated with the same fission chain was used. Using this approach, we are able to study various statistical properties of individual fission chains. One of these properties is the distribution of neutron arrival times within a given burst. We have observed two interesting empirical trends. First, this distribution exhibits a weak, but definite, dependence on source multiplication. Second, there are distinctive differences in the distribution depending on the presence and type of reflector. Both of these phenomena might prove to be useful when assessing an unknown source. The physical origins of these phenomena can be illuminated with help of MCNPX-PoliMi simulations.
Non-linear canonical correlation for joint analysis of MEG signals from two subjects
Directory of Open Access Journals (Sweden)
Cristina eCampi
2013-06-01
Full Text Available We consider the problem of analysing magnetoencephalography (MEG data measured from two persons undergoing the same experiment, and we propose a method that searches for sources with maximally correlated energies. Our method is based on canonical correlation analysis (CCA, which provides linear transformations, one for each subject, such that the correlation between the transformed MEG signals is maximized. Here, we present a nonlinear version of CCA which measures the correlation of energies. Furthermore, we introduce a delay parameter in the modelto analyse, e.g., leader-follower changes in experiments where the two subjects are engaged in social interaction.
The cross-correlation analysis in Z source GX 349+2
Ding, G. Q.; Zhang, W.Y.; Wang, Y. N.; Li, Z. B.; Qu, J. L.; Huang, C. P.
2015-01-01
Using all the observations from Rossi X-ray Timing Explorer for Z source GX 349+2, we systematically carry out cross-correlation analysis between its soft and hard X-ray light curves. During the observations from January 9 to January 29, 1998, GX 349+2 traced out the most extensive Z track on its hardness-intensity diagram, making a comprehensive study of cross-correlation on the track. The positive correlations and positively correlated time lags are detected throughout the Z track. Outside ...
Spatio-chromatic adaptation via higher-order canonical correlation analysis of natural images.
Directory of Open Access Journals (Sweden)
Michael U Gutmann
Full Text Available 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.
Spatio-chromatic adaptation via higher-order canonical correlation analysis of natural images.
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.
Correlation analysis-based image segmentation approach for automatic agriculture vehicle
Institute of Scientific and Technical Information of China (English)
无
2005-01-01
It is important to segment image correctly to extract guidance information for automatic agriculture vehicle. If we can make the computer know where the crops are, we can extract the guidance line easily. Images were divided into some rectangle small windows, then a pair of 1-D arrays was constructed in each small windows. The correlation coefficients of every small window constructed the features to segment images. The results showed that correlation analysis is a potential approach for processing complex farmland for guidance system, and more correlation analysis methods must be researched.
Auto-correlation analysis of wave heights in the Bay of Bengal
Indian Academy of Sciences (India)
Abhijit Sarkar; Jignesh Kshatriya; K Satheesan
2006-04-01
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 exponential fall of auto-correlation in the ﬁrst few hours with a decorrelation time scale of about six hours.A similar ﬁgure was found earlier for ocean surface winds.The nature of variation of auto-correlation with time lags was also found to be similar for winds and wave heights.
Detrended cross-correlation analysis on RMB exchange rate and Hang Seng China Enterprises Index
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.
The Canonical Correlation Analysis on Semen Quality and Serum Heavy Metals in Chinese Young Men
Institute of Scientific and Technical Information of China (English)
Jun-qing WU; Jiang ZHU; Zhan-hai FU; Yin-mei DU; Cui-ling LIANG; Er-sheng GAO; Jian-guo TAO; Qiu-ying YANG; Xiao XU; Wen-juan CAI; Jian GUO; Feng TANG
2003-01-01
Objective To explore the correlation between serum heavy metal and semen quality in normal Chinese young menMethods This study was designed as a multi-center cross-sectional investigation. The subjects consisted of 562 male vomunteers who had undergone premarital physical examination in maternal and children health centers in 7 provinces in China.Results Results from Spearman rank correlation analysis (partial variable: region) show that serum lead and cadmium are negatively related to percentage of morphological normal sperm, but canonical correlation between semen quality and serum heavy metal are not significant. Canonical correlation analysis among the subjects from Guizhou shows cadmium is harmful to sperm morphology. In Henan, furthermore, results show lead and cadmium could negatively affect sperm viability and morphology.Conclusion Among all study subjects, canonical correlation between semen quality and serum heavy metal were not significant; however, results in some region showed serum cadmium and lead might be harmful to sperm quality.
Spectral and network methods in the analysis of correlation matrices of stock returns
Heimo, T; Onnela, J P; Saramäki, J; Heimo, Tapio; Kaski, Kimmo; Onnela, Jukka-Pekka; Saramaki, Jari
2007-01-01
Correlation matrices inferred from stock return time series contain information on the behaviour of the market, especially on clusters of highly correlating stocks. Here we study a subset of New York Stock Exchange (NYSE) traded stocks and compare three different methods of analysis: i) spectral analysis, i.e. investigation of the eigenvalue-eigenvector pairs of the correlation matrix, ii) asset trees, obtained by constructing the maximal spanning tree of the correlation matrix, and iii) asset graphs, which are networks in which the strongest correlations are depicted as edges. We illustrate and discuss the localisation of the most significant modes of fluctuation, i.e. eigenvectors corresponding to the largest eigenvalues, on the asset trees and graphs.
Irregular Liesegang-type patterns in gas phase revisited. II. Statistical correlation analysis
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.
Kilger, Robert; Stuke, Maik
2016-01-01
In this work we performed a detailed analysis on the calculation of 43 critical experiments from 6 experimental series all describing plutonium nitrate in aqueous solution contained in metal spheres. The underlying experimental data is taken from the handbook of the International Criticality Safety Benchmark Evaluation Project (ICSBEP) Working Group. We present our modeling assumptions which were derived from the interpretation of the experimental data and discuss the resulting sensitivity analysis. Although the experiments share some components, the derived correlation coefficients are for many cases statistically not significant. Comparing our findings for the correlation coefficients with available data from the DICE Database we find an agreement for the correlation coefficients due to nuclear data. We also compare our results for the correlation coefficients due to experimental uncertainty. Our findings indicate that for the reliable Determination of correlation coefficients a detailed study of the underl...
Because the Light is Better Here: Correlation-Time Analysis by NMR Spectroscopy.
Smith, Albert A; Ernst, Matthias; Meier, Beat H
2017-08-30
Relaxation data in NMR spectra are often used for dynamics analysis, by modeling motion in the sample with a correlation function consisting of one or more decaying exponential terms, each described by an order parameter, and a correlation time. This method has its origins in the Lipari-Szabo model-free approach, which originally considered overall tumbling plus one internal motion and was later expanded to several internal motions. Considering several of these cases in the solid state it is found that if the real motion is more complex than the assumed model, model fitting is biased towards correlation times where the relaxation data are most sensitive. This leads to unexpected distortions in the resulting dynamics description. Therefore dynamics detectors should be used, which characterize different ranges of correlation times and can help in the analysis of protein motion without assuming a specific model of the correlation function. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.
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.
A NEW SYSTEM DYNAMIC EXTREMUM SELF-SEARCHING METHOD BASED ON CORRELATION ANALYSIS
Institute of Scientific and Technical Information of China (English)
李嘉; 刘文江; 胡军; 袁廷奇
2003-01-01
Objective To propose a new dynamic extremum self-searching method, which can be used in industrial processes extremum optimum control systems, to overcome the disadvantages of traditional method. Methods This algorithm is based on correlation analysis. A pseudo-random binary signal m-sequence u(t) is added as probe signal in system input, construct cross-correlation function between system input and output, the next step hunting direction is judged by the differential sign. Results Compared with traditional algorithm such as step forward hunting method, the iterative efficient, hunting precision and anti-interference ability of the correlation analysis method is obvious over the traditional algorithm. The computer simulation experimental given illustrate these viewpoints. Conclusion The correlation analysis method can settle the optimum state point of device operating process. It has the advantage of easy condition , simple calculate process.
Kim, Dahan; Curthoys, Nikki M; Parent, Matthew T; Hess, Samuel T
2013-09-01
Multi-colour localization microscopy has enabled sub-diffraction studies of colocalization between multiple biological species and quantification of their correlation at length scales previously inaccessible with conventional fluorescence microscopy. However, bleed-through, or misidentification of probe species, creates false colocalization and artificially increases certain types of correlation between two imaged species, affecting the reliability of information provided by colocalization and quantified correlation. Despite the potential risk of these artefacts of bleed-through, neither the effect of bleed-through on correlation nor methods of its correction in correlation analyses has been systematically studied at typical rates of bleed-through reported to affect multi-colour imaging. Here, we present a reliable method of bleed-through correction applicable to image rendering and correlation analysis of multi-colour localization microscopy. Application of our bleed-through correction shows our method accurately corrects the artificial increase in both types of correlations studied (Pearson coefficient and pair correlation), at all rates of bleed-through tested, in all types of correlations examined. In particular, anti-correlation could not be quantified without our bleed-through correction, even at rates of bleed-through as low as 2%. Demonstrated with dichroic-based multi-colour FPALM here, our presented method of bleed-through correction can be applied to all types of localization microscopy (PALM, STORM, dSTORM, GSDIM, etc.), including both simultaneous and sequential multi-colour modalities, provided the rate of bleed-through can be reliably determined.
Han, Fang; Liu, Han
2016-01-01
Correlation matrix plays a key role in many multivariate methods (e.g., graphical model estimation and factor analysis). The current state-of-the-art in estimating large correlation matrices focuses on the use of Pearson’s sample correlation matrix. Although Pearson’s sample correlation matrix enjoys various good properties under Gaussian models, its not an effective estimator when facing heavy-tail distributions with possible outliers. As a robust alternative, Han and Liu (2013b) advocated the use of a transformed version of the Kendall’s tau sample correlation matrix in estimating high dimensional latent generalized correlation matrix under the transelliptical distribution family (or elliptical copula). The transelliptical family assumes that after unspecified marginal monotone transformations, the data follow an elliptical distribution. In this paper, we study the theoretical properties of the Kendall’s tau sample correlation matrix and its transformed version proposed in Han and Liu (2013b) for estimating the population Kendall’s tau correlation matrix and the latent Pearson’s correlation matrix under both spectral and restricted spectral norms. With regard to the spectral norm, we highlight the role of “effective rank” in quantifying the rate of convergence. With regard to the restricted spectral norm, we for the first time present a “sign subgaussian condition” which is sufficient to guarantee that the rank-based correlation matrix estimator attains the optimal rate of convergence. In both cases, we do not need any moment condition.
Han, Fang; Liu, Han
2017-02-01
Correlation matrix plays a key role in many multivariate methods (e.g., graphical model estimation and factor analysis). The current state-of-the-art in estimating large correlation matrices focuses on the use of Pearson's sample correlation matrix. Although Pearson's sample correlation matrix enjoys various good properties under Gaussian models, its not an effective estimator when facing heavy-tail distributions with possible outliers. As a robust alternative, Han and Liu (2013b) advocated the use of a transformed version of the Kendall's tau sample correlation matrix in estimating high dimensional latent generalized correlation matrix under the transelliptical distribution family (or elliptical copula). The transelliptical family assumes that after unspecified marginal monotone transformations, the data follow an elliptical distribution. In this paper, we study the theoretical properties of the Kendall's tau sample correlation matrix and its transformed version proposed in Han and Liu (2013b) for estimating the population Kendall's tau correlation matrix and the latent Pearson's correlation matrix under both spectral and restricted spectral norms. With regard to the spectral norm, we highlight the role of "effective rank" in quantifying the rate of convergence. With regard to the restricted spectral norm, we for the first time present a "sign subgaussian condition" which is sufficient to guarantee that the rank-based correlation matrix estimator attains the optimal rate of convergence. In both cases, we do not need any moment condition.
Li, Yanbin; Mulani, Sameer B.; Kapania, Rakesh K.; Fei, Qingguo; Wu, Shaoqing
2017-07-01
An algorithm that integrates Karhunen-Loeve expansion (KLE) and the finite element method (FEM) is proposed to perform non-stationary random vibration analysis of structures under excitations, represented by multiple random processes that are correlated in both time and spatial domains. In KLE, the auto-covariance functions of random excitations are discretized using orthogonal basis functions. The KLE for multiple correlated random excitations relies on expansions in terms of correlated sets of random variables reflecting the cross-covariance of the random processes. During the response calculations, the eigenfunctions of KLE used to represent excitations are applied as forcing functions to the structure. The proposed algorithm is applied to a 2DOF system, a 2D cantilever beam and a 3D aircraft wing under both stationary and non-stationary correlated random excitations. Two methods are adopted to obtain the structural responses: a) the modal method and b) the direct method. Both the methods provide the statistics of the dynamic response with sufficient accuracy. The structural responses under the same type of correlated random excitations are bounded by the response obtained by perfectly correlated and uncorrelated random excitations. The structural response increases with a decrease in the correlation length and with an increase in the correlation magnitude. The proposed methodology can be applied for the analysis of any complex structure under any type of random excitation.
An analysis of the intrinsic cross-correlations between API and meteorological elements using DPCCA
Shen, Chen-hua; Li, Cao-ling
2016-03-01
In order to reveal the intrinsic cross-correlations between air pollution index (API) records and synchronously meteorological elements data, the detrended partial cross-correlation (DPCC) coefficients are analyzed using a detrended partial cross-correlation analysis (DPCCA). DPCC coefficients for different spatial locations and seasons are calculated and compared. The results show that DPCCA can uncover intrinsic cross-correlations between API and meteorological elements, and most of their interactional mechanisms can be explained. DPCC coefficients are either positive or negative, and vary with spatial locations and seasons, with consistently interactional mechanisms. More remarkable, we find that detrended cross-correlation analysis can present the cross-correlations between the fluctuations in two nonstationary time series, but this cross-correlation does not always fully reflect the interactional mechanism for the original time series. Despite this, DPCCA is recommended as a comparatively reliable method for revealing intrinsic cross-correlations between API and meteorological elements, and it can also be useful for our understanding of their interactional mechanisms.
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.
Detrended fluctuation analysis made flexible to detect range of cross-correlated fluctuations
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.
PCAN: Probabilistic correlation analysis of two non-normal data sets.
Zoh, Roger S; Mallick, Bani; Ivanov, Ivan; Baladandayuthapani, Veera; Manyam, Ganiraju; Chapkin, Robert S; Lampe, Johanna W; Carroll, Raymond J
2016-12-01
Most cancer research now involves one or more assays profiling various biological molecules, e.g., messenger RNA and micro RNA, in samples collected on the same individuals. The main interest with these genomic data sets lies in the identification of a subset of features that are active in explaining the dependence between platforms. To quantify the strength of the dependency between two variables, correlation is often preferred. However, expression data obtained from next-generation sequencing platforms are integer with very low counts for some important features. In this case, the sample Pearson correlation is not a valid estimate of the true correlation matrix, because the sample correlation estimate between two features/variables with low counts will often be close to zero, even when the natural parameters of the Poisson distribution are, in actuality, highly correlated. We propose a model-based approach to correlation estimation between two non-normal data sets, via a method we call Probabilistic Correlations ANalysis, or PCAN. PCAN takes into consideration the distributional assumption about both data sets and suggests that correlations estimated at the model natural parameter level are more appropriate than correlations estimated directly on the observed data. We demonstrate through a simulation study that PCAN outperforms other standard approaches in estimating the true correlation between the natural parameters. We then apply PCAN to the joint analysis of a microRNA (miRNA) and a messenger RNA (mRNA) expression data set from a squamous cell lung cancer study, finding a large number of negative correlation pairs when compared to the standard approaches.
Pal, Mayukha; Kiran, V. Satya; Rao, P. Madhusudana; Manimaran, P.
2016-08-01
We characterized the multifractal nature and power law cross-correlation between any pair of genome sequence through an integrative approach combining 2D multifractal detrended cross-correlation analysis and chaos game representation. In this paper, we have analyzed genomes of some prokaryotes and calculated fractal spectra h(q) and f(α) . From our analysis, we observed existence of multifractal nature and power law cross-correlation behavior between any pair of genome sequences. Cluster analysis was performed on the calculated scaling exponents to identify the class affiliation and the same is represented as a dendrogram. We suggest this approach may find applications in next generation sequence analysis, big data analytics etc.
Kirwan, Gemma M; Fernandez, David I; Niere, Julie O; Adams, Michael J
2012-10-01
Generalized two-dimensional (Gen2D) correlation analysis and hybrid correlation analysis have been applied to a series of dynamic (31)P nuclear magnetic resonance (NMR) spectra to monitor the in vivo metabolic changes of the plant pathogen Phytophthora palmivora in the presence and absence of phosphonate over an 18-h period. Results indicate that phosphonate exposure causes cleavage in organism polyphosphate chains as well as an increase in total sugar phosphates. In the presence of phosphonate, the NMR resonances attributed to terminal polyphosphate phosphorus reduced at a lower rate than those of middle polyphosphate phosphorus, indicating a change in average chain length and suggesting cleavage in the middle of the chain as well as at the ends. The correlation analysis techniques serve to identify and confirm spectral regions undergoing major change in the time-series data and facilitate the analysis of these dynamic changes.
Robustness analysis of bimodal networks in the whole range of degree correlation
Mizutaka, Shogo; Tanizawa, Toshihiro
2016-08-01
We present an exact analysis of the physical properties of bimodal networks specified by the two peak degree distribution fully incorporating the degree-degree correlation between node connections. The structure of the correlated bimodal network is uniquely determined by the Pearson coefficient of the degree correlation, keeping its degree distribution fixed. The percolation threshold and the giant component fraction of the correlated bimodal network are analytically calculated in the whole range of the Pearson coefficient from -1 to 1 against two major types of node removal, which are the random failure and the degree-based targeted attack. The Pearson coefficient for next-nearest-neighbor pairs is also calculated, which always takes a positive value even when the correlation between nearest-neighbor pairs is negative. From the results, it is confirmed that the percolation threshold is a monotonically decreasing function of the Pearson coefficient for the degrees of nearest-neighbor pairs increasing from -1 and 1 regardless of the types of node removal. In contrast, the node fraction of the giant component for bimodal networks with positive degree correlation rapidly decreases in the early stage of random failure, while that for bimodal networks with negative degree correlation remains relatively large until the removed node fraction reaches the threshold. In this sense, bimodal networks with negative degree correlation are more robust against random failure than those with positive degree correlation.
A correlation for calculating HHV from proximate analysis of solid fuels
Energy Technology Data Exchange (ETDEWEB)
Jigisha Parikh; S.A. Channiwala; G.K. Ghosal [Sarvajanik College of Engineering and Technology, Surat (India). Chemical Engineering Department
2005-03-01
Higher heating value (HHV) and composition of biomass, coal and other solid fuels, are important properties which define the energy content and determine the clean and efficient use of these fuels. There exists a variety of correlations for predicting HHV from ultimate analysis of fuels. However, the ultimate analysis requires very expensive equipments and highly trained analysts. The proximate analysis on the other hand only requires standard laboratory equipments and can be run by any competent scientist or engineer. A few number of correlations of HHV with proximate analysis have appeared in the solid fuel literature in the past but were focused on one fuel or dependent on the country of origin. This work introduces a general correlation, based on proximate analysis of solid fuels, to calculate HHV, using 450 data points and validated further for additional 100 data points. The entire spectrum of solid carbonaceous materials like coals, lignite, all types of biomass material, and char to residue-derived fuels have been considered in derivation of present correlation which is given as below: HHV = 0.3536FC + 0.1559VM - 0.0078ASH (MJ/kg) (where FC 1.0-91.5% fixed carbon, VM 0.92-90.6% volatile matter and Ash 0.12-77.7% ash content in wt% on a dry basis). The average absolute error of this correlation is 3.74% and bias error is 0.12% with respect to the measured value of HHV, which is much less than that of previous correlations of the similar kind. The major advantage of this correlation is its capability to compute HHV of any fuel simply from its proximate analysis and thereby provides a useful tool for modeling of combustion, gasification and pyrolysis processes. It can also be used in examining old/new data for probable errors when results lie much outside the predicted results. 25 refs., 8 figs., 3 tabs.
Energy Technology Data Exchange (ETDEWEB)
Munoz-Diosdado, A [Department of Mathematics, Unidad Profesional Interdisciplinaria de Biotecnologia, Instituto Politecnico Nacional, Av. Acueducto s/n, 07340, Mexico City (Mexico)
2005-01-01
We analyzed databases with gait time series of adults and persons with Parkinson, Huntington and amyotrophic lateral sclerosis (ALS) diseases. We obtained the staircase graphs of accumulated events that can be bounded by a straight line whose slope can be used to distinguish between gait time series from healthy and ill persons. The global Hurst exponent of these series do not show tendencies, we intend that this is because some gait time series have monofractal behavior and others have multifractal behavior so they cannot be characterized with a single Hurst exponent. We calculated the multifractal spectra, obtained the spectra width and found that the spectra of the healthy young persons are almost monofractal. The spectra of ill persons are wider than the spectra of healthy persons. In opposition to the interbeat time series where the pathology implies loss of multifractality, in the gait time series the multifractal behavior emerges with the pathology. Data were collected from healthy and ill subjects as they walked in a roughly circular path and they have sensors in both feet, so we have one time series for the left foot and other for the right foot. First, we analyzed these time series separately, and then we compared both results, with direct comparison and with a cross correlation analysis. We tried to find differences in both time series that can be used as indicators of equilibrium problems.
Spectroscopic correlation analysis of NMR-based metabonomics in exercise science.
Kirwan, Gemma M; Coffey, Vernon G; Niere, Julie O; Hawley, John A; Adams, Michael J
2009-10-12
Spectroscopic studies of complex clinical fluids have led to the application of a more holistic approach to their chemical analysis becoming more popular and widely employed. The efficient and effective interpretation of multidimensional spectroscopic data relies on many chemometric techniques and one such group of tools is represented by so-called correlation analysis methods. Typical of these techniques are two-dimensional correlation analysis and statistical total correlation spectroscopy (STOCSY). Whilst the former has largely been applied to optical spectroscopic analysis, STOCSY was developed and has been applied almost exclusively to NMR metabonomic studies. Using a (1)H NMR study of human blood plasma, from subjects recovering from exhaustive exercise trials, the basic concepts and applications of these techniques are examined. Typical information from their application to NMR-based metabonomics is presented and their value in aiding interpretation of NMR data obtained from biological systems is illustrated. Major energy metabolites are identified in the NMR spectra and the dynamics of their appearance and removal from plasma during exercise recovery are illustrated and discussed. The complementary nature of two-dimensional correlation analysis and statistical total correlation spectroscopy are highlighted.
Figueira, P; Adibekyan, V Zh; Oshagh, M; Santos, N C
2016-01-01
We apply the Bayesian framework to assess the presence of a correlation between two quantities. To do so, we estimate the probability distribution of the parameter of interest, $\\rho$, characterizing the strength of the correlation. We provide an implementation of these ideas and concepts using python programming language and the pyMC module in a very short ($\\sim$130 lines of code, heavily commented) and user-friendly program. We used this tool to assess the presence and properties of the correlation between planetary surface gravity and stellar activity level as measured by the log($R'_{\\mathrm{HK}}$) indicator. The results of the Bayesian analysis are qualitatively similar to those obtained via p-value analysis, and support the presence of a correlation in the data. The results are more robust in their derivation and more informative, revealing interesting features such as asymmetric posterior distributions or markedly different credible intervals, and allowing for a deeper exploration. We encourage the re...
Kern, Christoph; Kortüm, Karsten; Müller, Michael; Raabe, Florian; Mayer, Wolfgang Johann; Priglinger, Siegfried; Kreutzer, Thomas Christian
2016-01-01
Purpose Our aim was to correlate the overall patient volume and the incidence of several ophthalmological diseases in our emergency department with weather data. Patients and methods For data analysis, we used our clinical data warehouse and weather data. We investigated the weekly overall patient volume and the average weekly incidence of all encoded diagnoses of “conjunctivitis”, “foreign body”, “acute iridocyclitis”, and “corneal abrasion”. A Spearman’s correlation was performed to link these data with the weekly average sunshine duration, temperature, and wind speed. Results We noticed increased patient volume in correlation with increasing sunshine duration and higher temperature. Moreover, we found a positive correlation between the weekly incidences of conjunctivitis and of foreign body and weather data. Conclusion The results of this data analysis reveal the possible influence of external conditions on the health of a population and can be used for weather-dependent resource allocation. PMID:27601872
Correlation structure analysis for distributed video compression over wireless video sensor networks
He, Zhihai; Chen, Xi
2006-01-01
From the information-theoretic perspective, as stated by the Wyner-Ziv theorem, the distributed source encoder doesn't need any knowledge about its side information in achieving the R-D performance limit. However, from the system design and performance analysis perspective, correlation modeling plays an important role in analysis, control, and optimization of the R-D behavior of the Wyner-Ziv video coding In this work, we observe that videos captured from a wireless video sensor network (WVSN) are uniquely correlated under the multi-view geometry. We propose to utilize this computer vision principal, as well as other existing information, which is already available or can be easily obtained from the encoder, to estimate the source correlation structure. The source correlation determines the R-D behavior of the Wyner-Ziv encoder, and provide useful information for rate control and performance optimization of the Wyner-Ziv encoder.
Error analysis in cross-correlation of sky maps: application to the ISW detection
Cabre, A; Manera, E G M; Cabre, Anna; Fosalba, Pablo; Manera, Enrique Gaztanaga & Marc
2007-01-01
Constraining cosmological parameters from measurements of the Integrated Sachs-Wolfe effect requires developing robust and accurate methods for computing statistical errors in the cross-correlation between maps. This paper presents a detailed comparison of such error estimation applied to the case of cross-correlation of Cosmic Microwave Background (CMB) and large-scale structure data. We compare theoretical models for error estimation with montecarlo simulations where both the galaxy and the CMB maps vary around a fiducial auto-correlation and cross-correlation model which agrees well with the current concordance LCDM cosmology. Our analysis compares estimators both in harmonic and configuration (or real) space, quantifies the accuracy of the error analysis and discuss the impact of partial sky survey area and the choice of input fiducial model on dark-energy constraints. We show that purely analytic approaches yield accurate errors even in surveys that cover only 10% of the sky and that parameter constraint...
Comparative analysis of zero aliasing logarithmic mapped optimal trade-off correlation filter
Tehsin, Sara; Rehman, Saad; Bilal, Ahmed; Chaudry, Qaiser; Saeed, Omer; Abbas, Muhammad; Young, Rupert
2017-05-01
Correlation filters are a well established means for target recognition tasks. However, the unintentional effect of circular correlation has a negative influence on the performance of correlation filters as they are implemented in frequency domain. The effects of aliasing are minimized by introducing zero aliasing constraints in the template and test image. In this paper, the comparative analysis of logarithmic zero aliasing optimal trade off correlation filters has been carried out for different types of target distortions. The zero aliasing Maximum Average Correlation Height (MACH) filter has been identified as the best choice based on our research for achieving enhanced results in the presence of any type of variance which are discussed in results section. The reformulation of the MACH expressions with zero aliasing has been made to demonstrate the achievable enhancement to the logarithmic MACH filter in target detection applications.
Robustness analysis of bimodal networks in the whole range of degree correlation
Mizutaka, Shogo
2016-01-01
We present exact analysis of the physical properties of bimodal networks specified by the two peak degree distribution fully incorporating the degree-degree correlation between node connection. The structure of the correlated bimodal network is uniquely determined by the Pearson coefficient of the degree correlation, keeping its degree distribution fixed. The percolation threshold and the giant component fraction of the correlated bimodal network are analytically calculated in the whole range of the Pearson coefficient from $-1$ to $1$ against two major types of node removal, which are the random failure and the degree-based targeted attack. The Pearson coefficient for next-nearest-neighbor pairs is also calculated, which always takes a positive value even when the correlation between nearest-neighbor pairs is negative. From the results, it is confirmed that the percolation threshold is a monotonically decreasing function of the Pearson coefficient for the degrees of nearest-neighbor pairs increasing from $-1...
The use of variable-step delta modulation in digital filtering and correlation analysis
Pogribnoi, V. A.
1985-11-01
General expressions are obtained for convolutions and correlation functions using variable-quantization-step DM in conjunction with PCM, making it possible to realize low-cost processor circuits. Algorithms for the operation of processors for digital filtering and correlation analysis on the basis of this type of modulation are proposed. In addition, they are compared with algorithms for the operation of processors with linear PCM, DM, and delta-sigma modulation.
Cross-correlation analysis of the AE index and the interplanetary magnetic field Bz component.
Meng, C.-I.; Tsurutani, B.; Kawasaki, K.; Akasofu, S.-I.
1973-01-01
A cross-correlation study between magnetospheric activity (the AE index) and the southward-directed component of the interplanetary magnetic field (IMF) is made for a total of 792 hours (33 days) with a time resolution of about 5.5 min. The peak correlation tends to occur when the interplanetary data are shifted approximately 40 min later with respect to the AE index data. Cross-correlation analysis is conducted on some idealized wave forms to illustrate that this delay between southward turning of the IMF and the AE index should not be interpreted as being the duration of the growth phase.
Gas monitoring data anomaly identification based on spatio-temporal correlativity analysis
Institute of Scientific and Technical Information of China (English)
Shi-song ZHU; Yun-jia WANG; Lian-jiang WEI
2013-01-01
Based on spatio-temporal correlativity analysis method,the automatic identification techniques for data anomaly monitoring of coal mining working face gas are presented.The asynchronous correlative characteristics of gas migration in working face airflow direction are qualitatively analyzed.The calculation method of asynchronous correlation delay step and the prediction and inversion formulas of gas concentration changing with time and space after gas emission in the air return roadway are provided.By calculating one hundred and fifty groups of gas sensors data series from a coal mine which have the theoretical correlativity,the correlative coefficient values range of eight kinds of data anomaly is obtained.Then the gas monitoring data anomaly identification algorithm based on spatio-temporal correlativity analysis is accordingly presented.In order to improve the efficiency of analysis,the gas sensors code rules which can express the spatial topological relations are suggested.The experiments indicate that methods presented in this article can effectively compensate the defects of methods based on a single gas sensor monitoring data.
Correlation analysis of gamma dose rate from natural radiation in the test field
Directory of Open Access Journals (Sweden)
Avdic Senada
2016-01-01
Full Text Available This paper deals with correlation analysis of gamma dose rate measured in the test field with the five distinctive soil samples from a few minefields in Federation of Bosnia and Herzegovina. The measurements of ambient dose equivalent rate, due to radionuclides present in each of the soil samples, were performed by the RADIAGEMTM 2000 portable survey meter, placed on the ground and 1m above the ground. The gamma spectrometric analysis of the same soil samples was carried out by GAMMA-RAD5 spectrometer. This study showed that there is a high correlation between the absorbed dose rate evaluated from soil radioactivity and the corresponding results obtained by the survey meter placed on the ground. Correlation analysis indicated that the survey meter, due to its narrow energy range, is not suitable for the examination of cosmic radiation contribution.
Institute of Scientific and Technical Information of China (English)
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.
Correlation analysis and causality test between Ludong-Huanghai block and South Japan
Institute of Scientific and Technical Information of China (English)
ZHENG Jian-chang; JIANG Hai-kun
2007-01-01
In this paper, we make a comparative analysis and correlation test for the seismic activities in the South Japan and the Ludong-Huanghai block (a secondary tectonic unit in the North China) and approach the relationship between the energy release processes of these two areas by using co-integration analysis and Granger causality test for the time series of random variables. The results show that the seismic activities in these two areas are correlative and synchronous to a certain extent, and their release series of cumulative strain energy are contemporaneously correlative. Both energy series are first-order difference stationary processes and there is secular and steady co-integration between them. We make a positive analysis on the first-order difference energy series through Granger causality test based on vector error correction (VEC) model and find there is unilateral Granger causality and prominent co-integration between the two energy release processes.
Ma, Chuang; Wang, Xiangfeng
2012-09-01
One of the computational challenges in plant systems biology is to accurately infer transcriptional regulation relationships based on correlation analyses of gene expression patterns. Despite several correlation methods that are applied in biology to analyze microarray data, concerns regarding the compatibility of these methods with the gene expression data profiled by high-throughput RNA transcriptome sequencing (RNA-Seq) technology have been raised. These concerns are mainly due to the fact that the distribution of read counts in RNA-Seq experiments is different from that of fluorescence intensities in microarray experiments. Therefore, a comprehensive evaluation of the existing correlation methods and, if necessary, introduction of novel methods into biology is appropriate. In this study, we compared four existing correlation methods used in microarray analysis and one novel method called the Gini correlation coefficient on previously published microarray-based and sequencing-based gene expression data in Arabidopsis (Arabidopsis thaliana) and maize (Zea mays). The comparisons were performed on more than 11,000 regulatory relationships in Arabidopsis, including 8,929 pairs of transcription factors and target genes. Our analyses pinpointed the strengths and weaknesses of each method and indicated that the Gini correlation can compensate for the shortcomings of the Pearson correlation, the Spearman correlation, the Kendall correlation, and the Tukey's biweight correlation. The Gini correlation method, with the other four evaluated methods in this study, was implemented as an R package named rsgcc that can be utilized as an alternative option for biologists to perform clustering analyses of gene expression patterns or transcriptional network analyses.
Ma, Chuang; Wang, Xiangfeng
2012-01-01
One of the computational challenges in plant systems biology is to accurately infer transcriptional regulation relationships based on correlation analyses of gene expression patterns. Despite several correlation methods that are applied in biology to analyze microarray data, concerns regarding the compatibility of these methods with the gene expression data profiled by high-throughput RNA transcriptome sequencing (RNA-Seq) technology have been raised. These concerns are mainly due to the fact that the distribution of read counts in RNA-Seq experiments is different from that of fluorescence intensities in microarray experiments. Therefore, a comprehensive evaluation of the existing correlation methods and, if necessary, introduction of novel methods into biology is appropriate. In this study, we compared four existing correlation methods used in microarray analysis and one novel method called the Gini correlation coefficient on previously published microarray-based and sequencing-based gene expression data in Arabidopsis (Arabidopsis thaliana) and maize (Zea mays). The comparisons were performed on more than 11,000 regulatory relationships in Arabidopsis, including 8,929 pairs of transcription factors and target genes. Our analyses pinpointed the strengths and weaknesses of each method and indicated that the Gini correlation can compensate for the shortcomings of the Pearson correlation, the Spearman correlation, the Kendall correlation, and the Tukey’s biweight correlation. The Gini correlation method, with the other four evaluated methods in this study, was implemented as an R package named rsgcc that can be utilized as an alternative option for biologists to perform clustering analyses of gene expression patterns or transcriptional network analyses. PMID:22797655
Estimation of the biserial correlation and its sampling variance for use in meta-analysis.
Jacobs, Perke; Viechtbauer, Wolfgang
2017-06-01
Meta-analyses are often used to synthesize the findings of studies examining the correlational relationship between two continuous variables. When only dichotomous measurements are available for one of the two variables, the biserial correlation coefficient can be used to estimate the product-moment correlation between the two underlying continuous variables. Unlike the point-biserial correlation coefficient, biserial correlation coefficients can therefore be integrated with product-moment correlation coefficients in the same meta-analysis. The present article describes the estimation of the biserial correlation coefficient for meta-analytic purposes and reports simulation results comparing different methods for estimating the coefficient's sampling variance. The findings indicate that commonly employed methods yield inconsistent estimates of the sampling variance across a broad range of research situations. In contrast, consistent estimates can be obtained using two methods that appear to be unknown in the meta-analytic literature. A variance-stabilizing transformation for the biserial correlation coefficient is described that allows for the construction of confidence intervals for individual coefficients with close to nominal coverage probabilities in most of the examined conditions. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.
Krafty, Robert T; Hall, Martica
2013-03-01
Although many studies collect biomedical time series signals from multiple subjects, there is a dearth of models and methods for assessing the association between frequency domain properties of time series and other study outcomes. This article introduces the random Cramér representation as a joint model for collections of time series and static outcomes where power spectra are random functions that are correlated with the outcomes. A canonical correlation analysis between cepstral coefficients and static outcomes is developed to provide a flexible yet interpretable measure of association. Estimates of the canonical correlations and weight functions are obtained from a canonical correlation analysis between the static outcomes and maximum Whittle likelihood estimates of truncated cepstral coefficients. The proposed methodology is used to analyze the association between the spectrum of heart rate variability and measures of sleep duration and fragmentation in a study of older adults who serve as the primary caregiver for their ill spouse.
The Value of HRV Analysis and Multiple Correlations for Study of Child Virus Myocarditis
Institute of Scientific and Technical Information of China (English)
宋安齐; 牛小麟; 杜颖; 郭润梅
2004-01-01
Objectives To evaluate the value of HRV analysis and multiple correlations for study of child virus myocarditis. Methods HRV analysis was performed on 41 myocarditis and 40 normal children. The HRV changes in waking and sleeping time were observed as well. Multiple correlation and regression were carried out with the depth of STT depression as dependent variable and all HRV time and frequency domain indexes including those in waking and sleeping time as independent variables.Results HRV abnormality was found in virus myocarditis children .Their HRV indexes were decreased no matter waking time or sleeping time and the differences between waking and sleeping time were much less than those in the controls. In multiple correlation and regression analysis, the ST depression correlated with VLF, LFN, LF. Conclusions HRV abnormalities existed in children with virus myocarditis which indicates the sympathetic tense were increased ermanently. The ST depression correlates with VLF,LFN, LF. HRV analysis is helpful with the study and its diagnosis of utonomic function in children with virus myocarditis.
Analysis of DNA sequences by an optical time-integrating correlator.
Brousseau, N; Brousseau, R; Salt, J W; Gutz, L; Tucker, M D
1992-08-10
The analysis of the molecular structure called DNA is of particular interest for the understanding of the basic processes governing life. Correlation techniques implemented on digital computers are currently used to do this analysis, but the process is so slow that the mapping and sequencing of the entire human genome requires a computational breakthrough. This paper presents a new method of performing the analysis of DNA sequences with an optical time-integrating correlator. The method is characterized by short processing times that make the analysis of the entire human genome a tractable enterprise. A processing strategy and the resultant processing times are presented. Experimental proofs of concept for the two types of analysis specified by the strategy are also included.
DEFF Research Database (Denmark)
Barndorff-Nielsen, Ole Eiler; Shephard, N.
2004-01-01
This paper analyses multivariate high frequency financial data using realized covariation. We provide a new asymptotic distribution theory for standard methods such as regression, correlation analysis, and covariance. It will be based on a fixed interval of time (e.g., a day or week), allowing...... the number of high frequency returns during this period to go to infinity. Our analysis allows us to study how high frequency correlations, regressions, and covariances change through time. In particular we provide confidence intervals for each of these quantities....
Generalized Correlation Coefficient for Non-Parametric Analysis of Microarray Time-Course Data.
Tan, Qihua; Thomassen, Mads; Burton, Mark; Mose, Kristian Fredløv; Andersen, Klaus Ejner; Hjelmborg, Jacob; Kruse, Torben
2017-06-06
Modeling complex time-course patterns is a challenging issue in microarray study due to complex gene expression patterns in response to the time-course experiment. We introduce the generalized correlation coefficient and propose a combinatory approach for detecting, testing and clustering the heterogeneous time-course gene expression patterns. Application of the method identified nonlinear time-course patterns in high agreement with parametric analysis. We conclude that the non-parametric nature in the generalized correlation analysis could be an useful and efficient tool for analyzing microarray time-course data and for exploring the complex relationships in the omics data for studying their association with disease and health.
Generalized Correlation Coefficient for Non-Parametric Analysis of Microarray Time-Course Data
DEFF Research Database (Denmark)
Tan, Qihua; Thomassen, Mads; Burton, Mark
2017-01-01
Modeling complex time-course patterns is a challenging issue in microarray study due to complex gene expression patterns in response to the time-course experiment. We introduce the generalized correlation coefficient and propose a combinatory approach for detecting, testing and clustering...... the heterogeneous time-course gene expression patterns. Application of the method identified nonlinear time-course patterns in high agreement with parametric analysis. We conclude that the non-parametric nature in the generalized correlation analysis could be an useful and efficient tool for analyzing microarray...... time-course data and for exploring the complex relationships in the omics data for studying their association with disease and health....
Generalized Correlation Coefficient for Non-Parametric Analysis of Microarray Time-Course Data
DEFF Research Database (Denmark)
Tan, Qihua; Thomassen, Mads; Burton, Mark
2017-01-01
Modeling complex time-course patterns is a challenging issue in microarray study due to complex gene expression patterns in response to the time-course experiment. We introduce the generalized correlation coefficient and propose a combinatory approach for detecting, testing and clustering...... the heterogeneous time-course gene expression patterns. Application of the method identified nonlinear time-course patterns in high agreement with parametric analysis. We conclude that the non-parametric nature in the generalized correlation analysis could be an useful and efficient tool for analyzing microarray...
Institute of Scientific and Technical Information of China (English)
Thinh Hong Phi; Ludmila Aleksandrovna Strokova
2013-01-01
Multifactorial correlation analysis is a new method used to predict the land subsidence caused by groundwater exploitation. This article introduces and applies the method to establish the function of the surface settlement rate (Vs) and the function of the time-dependent surface settlement (St) caused by groundwater exploitation, based on data acquired at three land subsidence monitoring stations in the Hanoi area of Vietnam. Comparison with actual monitoring data indicates that the prediction results are relatively close to the monitoring data. From this, we conclude that multifactorial correlation analysis is a reliable method and can be used to predict future land subsidence caused by groundwater exploitation in Hanoi.
Lee, Y H; Bae, S-C
2016-12-01
This study aimed to evaluate the relationship between the circulating serum leptin level and rheumatoid arthritis (RA) and to establish a correlation between serum leptin levels and RA activity. We searched the PUBMED, EMBASE, and Cochrane databases. A meta-analysis was performed, comparing the serum/plasma leptin levels in patients with RA and healthy controls. Correlation coefficients between serum leptin level and either disease activity score 28 (DAS28) or C‑reactive protein (CRP) in RA patients were also examined. Thirteen studies with a total of 648 RA patients and 426 controls were included in this meta-analysis. Circulating leptin level was significantly higher in the RA group than in the control group (SMD = 1.056, 95 % CI = 0.647-1.465, p = 4.2 × 10(-7)). In addition, stratification by ethnicity showed a significantly elevated leptin level in the RA group in Caucasian, Turkish, and Arab populations (SMD = 0.813, 95 % CI = 0.137-1.490, p = 0.018, SMD = 0.981, 95 % CI = 0.307-1.655, p = 0.004, and SMD = 1.469, 95 % CI = 0.443-2.495, p = 0.005 respectively). A meta-analysis of correlation coefficients showed a small but significantly positive correlation between the circulating leptin level and either DAS28 (correlation coefficient = 0.275, 95 % CI = 0.076-0.452, p = 0.007) or CRP (correlation coefficient = 0.274, 95 % CI = 0.068-0.458, p = 0.010). Our meta-analysis demonstrated that the circulating leptin level is significantly higher in patients with RA and that a small but significantly positive correlation exists between leptin levels and RA activity.
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
Development of two-phase pipeline hydraulic analysis model based on Beggs-Brill correlation
Waluyo, Joko; Hermawan, Achilleus; Indarto
2016-06-01
The hydraulic analysis is an important stage in a reliable pipeline design. In the implementation, fluid distribution from a source to the sinks often occurs on parallel pipeline networks. The solution to the problem is complicated because of the iterative technique requirement. Regarding its solution effectiveness, there is a need for analysis related to the model and the solution method. This study aims to investigate pipeline hydraulic analysis on distributing of two-phase fluids flow. The model uses Beggs-Brill correlation to converse mass flow rates into pressure drops. In the solution technique, the Newton-Raphson iterative method is utilized. The iterative technique is solved using a computer program. The study is carried out using a certain pipeline network. The model is validated by comparing between Beggs-Brill towards Mukherjee-Brill correlation. The result reveals that the computer program enables solving of iterative calculation on the parallel pipeline hydraulic analysis. Convergence iteration is achieved by 50 iterations. The main results of the model are mass flow rate and pressure drop. The mass flow rate is obtained in the deviation up to 2.06%, between Beggs-Brill and Mukherjee-Brill correlation. On the other hand, the pressure gradient deviation is achieved on a higher deviation due to the different approach of the two correlations. The model can be further developed in the hydraulic pipeline analysis for two-phase flow.
Asymmetric multiscale detrended cross-correlation analysis of financial time series.
Yin, Yi; Shang, Pengjian
2014-09-01
We propose the asymmetric multiscale detrended cross-correlation analysis (MS-ADCCA) method and apply MS-ADCCA method to explore the existence of asymmetric cross-correlation for daily price returns in US and Chinese stock markets and to assess the properties of these asymmetric cross-correlations. The results all show the existences of asymmetric cross-correlations, while small asymmetries at small scales and larger asymmetries at larger scales are also displayed. There is a strong similarity between S&P500 and DJI, and we reveal that the asymmetries depend more on the cross-correlations of S&P500 vs. DJI, S&P500 vs. NQCI, DJI vs. NQCI, and ShangZheng vs. ShenCheng when the market is falling than rising, respectively. By comparing the spectra of S&P500 vs. NQCI and DJI vs. NQCI with uptrends and downtrends, we detect some new characteristics which lead to some new conclusions. Likewise, some new conclusions also can be drawn by the new characteristics displayed through the comparison between the spectra of ShangZheng vs. HSI and ShenCheng vs. HSI. Obviously, we conclude that although the overall spectra are similar and one market has the same effect when it is rising and falling in the study of asymmetric cross-correlations between it and different markets, the cross-correlations and asymmetries on the trends of the different markets are all different. MS-ADCCA method can detect the differences on the asymmetric cross-correlations by different trends of markets. Moreover, the uniqueness of cross-correlation between NQCI and HSI can be detected in the study of the asymmetric cross-correlations, which confirms that HSI is unique in the Chinese stock markets and NQCI is unique in the US stock markets further.
THE USE OF CORRELATION ANALYSIS IN AIC SUGAR INDUSTRY (PART 2 – CROSSCORRELATE
Directory of Open Access Journals (Sweden)
Zhmurko D. Y.
2016-02-01
Full Text Available This article is devoted to the practical application of economic-mathematical methods (based on correlation analysis to control the economic parameters of the integrated production systems sugar subcomplex (IPS SS AIC oriented to meet the needs in the sugar production of the population not only of individuals, but also of the regions and the country as a whole. This article discusses and solves the following tasks: autocorrelation and partial autocorrelation functions, cross-correlation function (correlation matrix study of deciduous macroeconomics series, with appropriate verification (test Durbin - Watson. The study used Statistica, MS Excel and Xlstat add-in. The work describes experiments with various kinds of nonstationary time series of the agricultural sector and food industry sugar subcomplex, as well as the test results on the difficulty of communication between them. We have identified industry-high cycles. The article presents results of numerical experiments autocorrelation of the time series of sugar production, acreage, gross harvest and yield of sugar beet and sugar cane, by country. Systematically, we describe ideas and methods underlying the correlation analysis. We have given the evaluation of the results of correlation analysis on each type. Further, it can be assumed that the proposed techniques will greatly affect a key points when making recommendations for new models of production of sugar products, market-oriented – this will minimize the time and cost of the finished product that will make a more stable position in the sector for this integrated production system in relation to its competition
Davies, David L.; Smith, Peter H.; Liutermoza, John F.
1980-06-01
Profile analysis and piecewise correlation techniques for measuring internal machine part clearances by digital processing of industrial radiographs are described in this paper. These methods were developed at the Image and Pattern Analysis Laboratory of Pratt & Whitney Aircraft Group. Profile analysis requires mathematical modeling of the expected optical density of a radiograph as a function of machine part position. Part separations are estimated on the basis of individual image scan lines. A final part separation estimate is produced by fitting a polynominal to the individual estimates and correcting for imaging and processing degradations which are simulated using a mathematical model. Piecewise correlation involves an application of image registration where radiographs are correlated in a piecewise fashion to allow inference of the relative motion of machine parts in a time varying series of images. Each image is divided into segments which are dominated by a small number of features. Segments from one image are cross-correlated with subsequent images to identify machine part motion in image space. Correlation peak magnitude is used in assessing the confidence that a particular motion has occurred between images. The rigid feature motion of machine parts requires image registration by discon-tinuous parts. This method differs from the continuous deformations one encounters in perspective projective transformations characteristic of remote sensing applications.
Constructing ecological interaction networks by correlation analysis: hints from community sampling
Directory of Open Access Journals (Sweden)
WenJun Zhang
2011-09-01
Full Text Available A set of methodology for constructing ecological interaction networks by correlation analysis of community sampling data was presented in this study. Nearly 30 data sets at different levels of taxa for different sampling seasons and locations were used to construct networks and find network properties. I defined the network constructed by Pearson linear correlation is the linear network, and the network constructed by quasi-linear correlation measure (e.g., Spearman correlation is the quasi-linear network. Two taxa with statistically significant linear or quasi-linear correlation are determined to interact. The quasi-linear network is more general than linear network.The results reveled that correlation distributions of Pearson linear correlation and partial linear correlation constructed networks are unimodal functions and most of them are short-head (mostly negative correlations and long-tailed (mostly positive correlations. Spearman correlation distributions are either long-head and short-tailed unimodal functions or monotonically increasing functions. It was found that both mean partial linear correlation and mean Pearson linear correlation were approximately 0. The proportion of positive (partial linear correlations declined significantly with the increase in taxa. The mean (partial linear correlation declined significantly with the increase of taxa. More than 90% of network interactions are positive interactions. The average connectance was 9.8% (9.3% for (partial linear correlation constructed network. The parameter λ in power low distribution (L(x=x-λ increased as the decline of taxon level (from functional group to species for the partial linear correlation constructed network. λ is in average 0.8 to 0.9. The number of (positive interactions increased with the number of taxa for both linear and partial linear correlations constructed networks. The addition of a taxon would result in an increase of 0.4 (0.3 interactions (positive
Li, Min
2014-07-01
In this paper, the performance of beamforming (BF) for a dual-hop amplify-and-forward (AF) relay network, where the source and destination are each equipped with multiple antennas, is investigated. It is assumed that the source-relay and relay-destination channels experience mixed fading distributions, namely, correlated Nakagami-m/Rician and correlated Rician/Nakagami-m, respectively. By considering fixed-gain relaying, analytical expressions for outage probability (OP) and average symbol error rate (ASER) are derived in closed-form. Numerical results are presented to demonstrate the efficacy of our performance analysis, also illustrate the impact of channel correlation, fading severity, Rician factor and antenna configuration on the performance of the system. It is shown that the correlated Nakagami-m/Rician fading channel can achieve better performance than the correlated Rician/Nakagami-m fading channel with the increase of fading severity parameter, and the correlated Rician/Nakagami-m fading channel may outperform the correlated Nakagami-m/Rician fading channel by enlarging the Rician factor.
Li, Xing; Qiu, Tian; Chen, Guang; Zhong, Li-Xin; Wu, Xiao-Run
2017-04-01
Partial correlation analysis is employed to study the market impact on the Chinese stock market from both the native and external markets. Whereas the native market index is observed to have a great impact on the market correlations for both the Shanghai and Shenzhen stock markets, some external stock indices of the United States, European and Asian stock markets show a slight influence on the Chinese market. The individual stock can be affected by different economic sectors, but the dominant influence is from the sector the stock itself belongs to or closely related to, and the finance and insurance sector shows a weaker correlation with other economic sectors. Moreover, the market structure similarity exhibits a negative correlation with the price return in most time, and the structure similarity decays with the time interval.
The Measurement and Analysis Risk Factors Dependence Correlation in Software Project
Jianjie, Ding; Hong, Hou; Kegang, Hao; Xiaoqun, Guo
The complexity of software process leads to that there are all kinds of fuzzy correlations among different process management risk factors, such as dependence correlation among software risk factors. It’s difficult to analyze risk data directly by mathematic tools because that risk data is uncertain and rough. Based on the rough set theory and the data in risk management library, the risk factors dependence correlation analysis system(RFDCAS) is established, and the dependence coefficient and its calculate formula on the base of equivalence class is suggested. The RFDCAS unveils the dependence correlation among risk factors contribute to risk management, and can help discover the problems in the software process improvement management.
Vitanov, N K; Vitanov, Nikolay K.; Yankulova, Elka D.
2006-01-01
Time series of heartbeat activity of humans can exhibit long-range correlations. In this paper we show that such kind of correlations can exist for the heartbeat activity of much simpler species like Drosophila melanogaster. By means of the method of multifractal detrended fluctuation analysis (MFDFA) we calculate fractal spectra $f(\\alpha)$ and $h(q)$ and investigate the correlation properties of heartbeat activity of Drosophila with genetic hearth defects for three consequent generations of species. We observe that opposite to the case of humans the time series of the heartbeat activity of healtly Drosophila do not have scaling properties. Time series from flies with genetic defects can be long-range correllated and can have multifractal properties. The fractal heartbeat dynamics of Drosophila is transferred from generation to generation.
Diagrammatic analysis of correlations in polymer fluids: Cluster diagrams via Edwards’ field theory
Morse, David C.
2006-10-01
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
A new method for correlation analysis of compositional (environmental) data - a worked example.
Reimann, C; Filzmoser, P; Hron, K; Kynčlová, P; Garrett, R G
2017-12-31
Most data in environmental sciences and geochemistry are compositional. Already the unit used to report the data (e.g., μg/l, mg/kg, wt%) implies that the analytical results for each element are not free to vary independently of the other measured variables. This is often neglected in statistical analysis, where a simple log-transformation of the single variables is insufficient to put the data into an acceptable geometry. This is also important for bivariate data analysis and for correlation analysis, for which the data need to be appropriately log-ratio transformed. A new approach based on the isometric log-ratio (ilr) transformation, leading to so-called symmetric coordinates, is presented here. Summarizing the correlations in a heat-map gives a powerful tool for bivariate data analysis. Here an application of the new method using a data set from a regional geochemical mapping project based on soil O and C horizon samples is demonstrated. Differences to 'classical' correlation analysis based on log-transformed data are highlighted. The fact that some expected strong positive correlations appear and remain unchanged even following a log-ratio transformation has probably led to the misconception that the special nature of compositional data can be ignored when working with trace elements. The example dataset is employed to demonstrate that using 'classical' correlation analysis and plotting XY diagrams, scatterplots, based on the original or simply log-transformed data can easily lead to severe misinterpretations of the relationships between elements. Copyright © 2017 Elsevier B.V. All rights reserved.
Cross-correlation analysis of stock markets using EMD and EEMD
Xu, Mengjia; Shang, Pengjian; Lin, Aijing
2016-01-01
Empirical mode decomposition (EMD) is a data-driven signal analysis method for nonlinear and nonstationary data. Since it is intuitive, direct, posterior and adaptive, EMD is widely applied to various fields of study. In this paper, EMD and ensemble empirical mode decomposition (EEMD), a modified method of EMD, are applied to financial time series. Through analyzing the intrinsic mode functions (IMFs) of EMD and EEMD, we find EEMD method performs better on the orthogonality of IMFs than EMD. With clustering the ordered frequencies of IMFs, the IMFs obtained from EEMD method are grouped into high-, medium-, and low-frequency components, representing the short-, medium-, and long-term volatilities of the index sequences, respectively. With the cross-correlation analysis of DCCA cross-correlation coefficient, our findings allow us to gain further and detailed insight into the cross-correlations of stock markets.
Vilanova, Mar; Genisheva, Zlatina Asenova; Masa, Antón; Oliveira, J. M.
2009-01-01
In this work, sensory analysis of was used to evaluate the wine aroma character with different aroma attributes according to Norm ISO 11035.1 In parallel wine volatiles were identified and quantified by gas chromatography according the methodology proposed by Oliveira et al. (2006).2 The objective of this work was to study the correlation between instrumental analysis and sensory perception of wine constituents. Thirty-five Albariño white young wines from 2006 vintage were e...
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.
Gene differential coexpression analysis based on biweight correlation and maximum clique.
Zheng, Chun-Hou; Yuan, Lin; Sha, Wen; Sun, Zhan-Li
2014-01-01
Differential coexpression analysis usually requires the definition of 'distance' or 'similarity' between measured datasets. Until now, the most common choice is Pearson correlation coefficient. However, Pearson correlation coefficient is sensitive to outliers. Biweight midcorrelation is considered to be a good alternative to Pearson correlation since it is more robust to outliers. In this paper, we introduce to use Biweight Midcorrelation to measure 'similarity' between gene expression profiles, and provide a new approach for gene differential coexpression analysis. Firstly, we calculate the biweight midcorrelation coefficients between all gene pairs. Then, we filter out non-informative correlation pairs using the 'half-thresholding' strategy and calculate the differential coexpression value of gene, The experimental results on simulated data show that the new approach performed better than three previously published differential coexpression analysis (DCEA) methods. Moreover, we use the maximum clique analysis to gene subset included genes identified by our approach and previously reported T2D-related genes, many additional discoveries can be found through our method.
Demetrashvili, Nino; Van den Heuvel, Edwin R.
This work is motivated by a meta-analysis case study on antipsychotic medications. The Michaelis-Menten curve is employed to model the nonlinear relationship between the dose and D2 receptor occupancy across multiple studies. An intraclass correlation coefficient (ICC) is used to quantify the
A Systematic Review and Meta-Analysis of the Cognitive Correlates of Bilingualism
Adesope, Olusola O.; Lavin, Tracy; Thompson, Terri; Ungerleider, Charles
2010-01-01
A number of studies have documented the cognitive outcomes associated with bilingualism. To gain a clear understanding of the extent and diversity of these cognitive outcomes, the authors conducted a meta-analysis of studies that examined the cognitive correlates of bilingualism. Data from 63 studies (involving 6,022 participants) were extracted…
A method of correlation between the Thin Film Micro-Oxidation (TFMO) test with isothermal thermogravimetric analysis is reported utilizing a soybean oil system. Utilizing a kinetic model, pseudo-rate constants and “activation energy” can be calculated from weight loss data. This model accounts for o...
Creativity and Brain-Functioning in Product Development Engineers: A Canonical Correlation Analysis
Travis, Frederick; Lagrosen, Yvonne
2014-01-01
This study used canonical correlation analysis to explore the relation among scores on the Torrance test of figural and verbal creativity and demographic, psychological and physiological measures in Swedish product-development engineers. The first canonical variate included figural and verbal flexibility and originality as dependent measures and…
Development of a new proximate analysis based correlation to predict calorific value of coal
Energy Technology Data Exchange (ETDEWEB)
A.K. Majumder; Rachana Jain; P. Banerjee; J.P. Barnwal [Advanced Materials and Processes Research Institute (CSIR), Bhopal (India). Department of Mineral Engineering
2008-10-15
The experimental determination of higher heating value (HHV) of solid fuels is a cost intensive process, as it requires special instrumentation and highly trained analyst to operate it, where as proximate analysis data can be obtained relatively easily using an ordinary muffle furnace. Therefore, to simplify the task and to reduce the cost of analysis many correlations were developed for determining HHV from proximate analysis of solid fuels. An attempt has been made in this paper to evaluate the applicability of these correlations with a special focus on Indian coals. It has been observed that the developed correlations are either complex in nature or by-pass the effect of important variables like moisture and ash contents of coals. An effort has, therefore, been made to develop a simple correlation based on proximate analysis data for predicting HHV of coal (as-received basis). The model presented here is developed using analyses of 250 coal samples and its significance lies in involvement of all the major variables affecting the HHV. The developed model appears to be better than the existing models. 10 refs., 4 figs., 2 tabs.
Demetrashvili, Nino; Van den Heuvel, Edwin R.
2015-01-01
This work is motivated by a meta-analysis case study on antipsychotic medications. The Michaelis-Menten curve is employed to model the nonlinear relationship between the dose and D2 receptor occupancy across multiple studies. An intraclass correlation coefficient (ICC) is used to quantify the hetero
Denial-of-service attack detection based on multivariate correlation analysis
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 s
Generalized canonical correlation analysis of matrices with missing rows : A simulation study
van de Velden, Michel; Bijmolt, Tammo H. A.
2006-01-01
A method is presented for generalized canonical correlation analysis of two or more matrices with missing rows. The method is a combination of Carroll's (1968) method and the missing data approach of the OVERALS technique (Van der Burg, 1988). In a simulation study we assess the performance of the m
Yin, Yi; Shang, Pengjian
2015-04-01
In this paper, we propose multiscale detrended cross-correlation analysis (MSDCCA) to detect the long-range power-law cross-correlation of considered signals in the presence of nonstationarity. For improving the performance and getting better robustness, we further introduce the empirical mode decomposition (EMD) to eliminate the noise effects and propose MSDCCA method combined with EMD, which is called MS-EDXA method, then systematically investigate the multiscale cross-correlation structure of the real traffic signals. We apply the MSDCCA and MS-EDXA methods to study the cross-correlations in three situations: velocity and volume on one lane, velocities on the present and the next moment and velocities on the adjacent lanes, and further compare their spectrums respectively. When the difference between the spectrums of MSDCCA and MS-EDXA becomes unobvious, there is a crossover which denotes the turning point of difference. The crossover results from the competition between the noise effects in the original signals and the intrinsic fluctuation of traffic signals and divides the plot of spectrums into two regions. In all the three case, MS-EDXA method makes the average of local scaling exponents increased and the standard deviation decreased and provides a relative stable persistent scaling cross-correlated behavior which gets the analysis more precise and more robust and improves the performance after noises being removed. Applying MS-EDXA method avoids the inaccurate characteristics of multiscale cross-correlation structure at the short scale including the spectrum minimum, the range for the spectrum fluctuation and general trend, which are caused by the noise in the original signals. We get the conclusions that the traffic velocity and volume are long-range cross-correlated, which is accordant to their actual evolution, while velocities on the present and the next moment and velocities on adjacent lanes reflect the strong cross-correlations both in temporal and
Tutorial on Biostatistics: Linear Regression Analysis of Continuous Correlated Eye Data.
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.
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.
Burth, Sina; Kieslich, Pascal J.; Jungk, Christine; Sahm, Felix; Kickingereder, Philipp; Kiening, Karl; Unterberg, Andreas; Wick, Wolfgang; Schlemmer, Heinz-Peter; Bendszus, Martin; Radbruch, Alexander
2016-01-01
Objective Several studies have analyzed a correlation between the apparent diffusion coefficient (ADC) derived from diffusion-weighted MRI and the tumor cellularity of corresponding histopathological specimens in brain tumors with inconclusive findings. Here, we compared a large dataset of ADC and cellularity values of stereotactic biopsies of glioblastoma patients using a new postprocessing approach including trajectory analysis and automatic nuclei counting. Materials and Methods Thirty-seven patients with newly diagnosed glioblastomas were enrolled in this study. ADC maps were acquired preoperatively at 3T and coregistered to the intraoperative MRI that contained the coordinates of the biopsy trajectory. 561 biopsy specimens were obtained; corresponding cellularity was calculated by semi-automatic nuclei counting and correlated to the respective preoperative ADC values along the stereotactic biopsy trajectory which included areas of T1-contrast-enhancement and necrosis. Results There was a weak to moderate inverse correlation between ADC and cellularity in glioblastomas that varied depending on the approach towards statistical analysis: for mean values per patient, Spearman’s ρ = -0.48 (p = 0.002), for all trajectory values in one joint analysis Spearman’s ρ = -0.32 (p < 0.001). The inverse correlation was additionally verified by a linear mixed model. Conclusions Our data confirms a previously reported inverse correlation between ADC and tumor cellularity. However, the correlation in the current article is weaker than the pooled correlation of comparable previous studies. Hence, besides cell density, other factors, such as necrosis and edema might influence ADC values in glioblastomas. PMID:27467557
Someswara Rao, Chinta; Viswanadha Raju, S
2016-03-01
In this paper, we consider correlation coefficient, rank correlation coefficient and cosine similarity measures for evaluating similarity between Homo sapiens and monkeys. We used DNA chromosomes of genome wide genes to determine the correlation between the chromosomal content and evolutionary relationship. The similarity among the H. sapiens and monkeys is measured for a total of 210 chromosomes related to 10 species. The similarity measures of these different species show the relationship between the H. sapiens and monkey. This similarity will be helpful at theft identification, maternity identification, disease identification, etc.
The cross-correlation analysis of multi property of stock markets based on MM-DFA
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.
Reliability sensitivity-based correlation coefficient calculation in structural reliability analysis
Yang, Zhou; Zhang, Yimin; Zhang, Xufang; Huang, Xianzhen
2012-05-01
The correlation coefficients of random variables of mechanical structures are generally chosen with experience or even ignored, which cannot actually reflect the effects of parameter uncertainties on reliability. To discuss the selection problem of the correlation coefficients from the reliability-based sensitivity point of view, the theory principle of the problem is established based on the results of the reliability sensitivity, and the criterion of correlation among random variables is shown. The values of the correlation coefficients are obtained according to the proposed principle and the reliability sensitivity problem is discussed. Numerical studies have shown the following results: (1) If the sensitivity value of correlation coefficient ρ is less than (at what magnitude 0.000 01), then the correlation could be ignored, which could simplify the procedure without introducing additional error. (2) However, as the difference between ρ s, that is the most sensitive to the reliability, and ρ R , that is with the smallest reliability, is less than 0.001, ρ s is suggested to model the dependency of random variables. This could ensure the robust quality of system without the loss of safety requirement. (3) In the case of | E abs|>0.001 and also | E rel|>0.001, ρ R should be employed to quantify the correlation among random variables in order to ensure the accuracy of reliability analysis. Application of the proposed approach could provide a practical routine for mechanical design and manufactory to study the reliability and reliability-based sensitivity of basic design variables in mechanical reliability analysis and design.
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.
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 ADCmin, mean ADC or ADCmean and ADC maximum or ADCmax Some studies have suggested that ADCmin 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 ADCmin 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 ADCmin were included. Overall, 12 publications with 317 patients were identified. Spearman's correlation coefficient was used to analyze associations between ADCmin 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 ADCmean and, therefore, ADCmin does not represent a better means to reflect cellularity. Copyright© 2017, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.
Analysis on Homocysteine's Risk to Atherosclerosis and Its Correlations with Serum Lipids
Institute of Scientific and Technical Information of China (English)
李河; 郭兰; 肖敏; 陈铁峰; 吴书林; 余细勇; 石美铃; 董太明; 刘小清; 黄平; 李义和
2004-01-01
Objectives To explore the homocysteine's risk to atherosclerosis and its correlations with serum lipids TG,TG and HDL-C. Methods With a cross sectional study, 490 subjects (aged 41-86 yrs, male 420 and female 70) were surveyed in 1999 in Guangdong Province, China. The main research variables were homocysteine (Hcy) and the serum lipids total cholesterol (TC), triglyceride (TG),high-density lipoprotein cholesterol(HDL-C). Results Hcy was a possible risk factor resulting in atherosclerosis (OR=l.15, 0.05 ＜P ＜0.10, n=108) with Logistic regression analysis. There is no correlation or much lower degree correlation between Hey and the serum lipids group of TC, TG, HDL-C. The canonical correlation coefficient between V1 and W1 was R1,Can =0.12(0.05＜P＜0.10, n=490, V1=Hcy, W1= - 0.9446 * TC + 0.1588 * TG + 0.6009 * HDL-C). Conclusions It is possible that Hcy is a risk factor to atherosclerosis and is independent of serum lipids group or has much lower correlation with it. It is necessary to do more research to explore the risk degree of Hcy inducing atherosclerosis and whether are there are bigger correlations or higher independence between Hcy and other risk factors during the progress of atherosclerosis.
Directory of Open Access Journals (Sweden)
Juho Rousu
2013-04-01
Full Text Available Biomarker discovery aims to find small subsets of relevant variables in 'omics data that correlate with the clinical syndromes of interest. Despite the fact that clinical phenotypes are usually characterized by a complex set of clinical parameters, current computational approaches assume univariate targets, e.g. diagnostic classes, against which associations are sought for. We propose an approach based on asymmetrical sparse canonical correlation analysis (SCCA that finds multivariate correlations between the 'omics measurements and the complex clinical phenotypes. We correlated plasma proteomics data to multivariate overlapping complex clinical phenotypes from tuberculosis and malaria datasets. We discovered relevant 'omic biomarkers that have a high correlation to profiles of clinical measurements and are remarkably sparse, containing 1.5-3% of all 'omic variables. We show that using clinical view projections we obtain remarkable improvements in diagnostic class prediction, up to 11% in tuberculosis and up to 5% in malaria. Our approach finds proteomic-biomarkers that correlate with complex combinations of clinical-biomarkers. Using the clinical-biomarkers improves the accuracy of diagnostic class prediction while not requiring the measurement plasma proteomic profiles of each subject. Our approach makes it feasible to use omics' data to build accurate diagnostic algorithms that can be deployed to community health centres lacking the expensive 'omics measurement capabilities.
Space-time correlation analysis of traffic flow on road network
Su, Fei; Dong, Honghui; Jia, Limin; Tian, Zhao; Sun, Xuan
2017-02-01
Space-time correlation analysis has become a basic and critical work in the research on road traffic congestion. It plays an important role in improving traffic management quality. The aim of this research is to examine the space-time correlation of road networks to determine likely requirements for building a suitable space-time traffic model. In this paper, it is carried out using traffic flow data collected on Beijing’s road network. In the framework, the space-time autocorrelation function (ST-ACF) is introduced as global measure, and cross-correlation function (CCF) as local measure to reveal the change mechanism of space-time correlation. Through the use of both measures, the correlation is found to be dynamic and heterogeneous in space and time. The finding of seasonal pattern present in space-time correlation provides a theoretical assumption for traffic forecasting. Besides, combined with Simpson’s rule, the CCF is also applied to finding the critical sections in the road network, and the experiments prove that it is feasible in computability, rationality and practicality.
Detrended fluctuation analysis made flexible to detect range of cross-correlated fluctuations
Kwapien, Jaroslaw; Drozdz, Stanislaw
2015-01-01
The detrended cross-correlation coefficient $\\rho_{\\rm DCCA}$ has recently been proposed to quantify the strength of cross-correlations on different temporal scales in bivariate, non-stationary time series. It is based on the detrended cross-correlation and detrended fluctuation analyses (DCCA and DFA, respectively) and can be viewed as an analogue of the Pearson coefficient in the case of the fluctuation analysis. The coefficient $\\rho_{\\rm DCCA}$ works well in many practical situations but by construction its applicability is limited to detection of whether two signals are generally cross-correlated, without 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 $\\rho_{\\rm DCCA}$ that exploits the multifractal versions of DFA and DCCA: MFDFA and MFCCA, respectively. The resulting new coefficient $\\rho_q$ not only is able to quantify the strength of correlations, but ...
Liu, Yao; Wang, Xiufeng; Lin, Jing; Zhao, Wei
2016-11-01
Motor current is an emerging and popular signal which can be used to detect machining chatter with its multiple advantages. To achieve accurate and reliable chatter detection using motor current, it is important to make clear the quantitative relationship between motor current and chatter vibration, which has not yet been studied clearly. In this study, complex continuous wavelet coherence, including cross wavelet transform and wavelet coherence, is applied to the correlation analysis of motor current and chatter vibration in grinding. Experimental results show that complex continuous wavelet coherence performs very well in demonstrating and quantifying the intense correlation between these two signals in frequency, amplitude and phase. When chatter occurs, clear correlations in frequency and amplitude in the chatter frequency band appear and the phase difference of current signal to vibration signal turns from random to stable. The phase lead of the most correlated chatter frequency is the largest. With the further development of chatter, the correlation grows up in intensity and expands to higher order chatter frequency band. The analyzing results confirm that there is a consistent correlation between motor current and vibration signals in the grinding chatter process. However, to achieve accurate and reliable chatter detection using motor current, the frequency response bandwidth of current loop of the feed drive system must be wide enough to response chatter effectively.
Directory of Open Access Journals (Sweden)
John C. Klock
2016-01-01
Full Text Available Objectives. This study presents correlations between cross-sectional anatomy of human female breasts and Quantitative Transmission (QT Ultrasound, does discriminate classifier analysis to validate the speed of sound correlations, and does a visual grading analysis comparing QT Ultrasound with mammography. Materials and Methods. Human cadaver breasts were imaged using QT Ultrasound, sectioned, and photographed. Biopsies confirmed microanatomy and areas were correlated with QT Ultrasound images. Measurements were taken in live subjects from QT Ultrasound images and values of speed of sound for each identified anatomical structure were plotted. Finally, a visual grading analysis was performed on images to determine whether radiologists’ confidence in identifying breast structures with mammography (XRM is comparable to QT Ultrasound. Results. QT Ultrasound identified all major anatomical features of the breast, and speed of sound calculations showed specific values for different breast tissues. Using linear discriminant analysis overall accuracy is 91.4%. Using visual grading analysis readers scored the image quality on QT Ultrasound as better than on XRM in 69%–90% of breasts for specific tissues. Conclusions. QT Ultrasound provides accurate anatomic information and high tissue specificity using speed of sound information. Quantitative Transmission Ultrasound can distinguish different types of breast tissue with high resolution and accuracy.
Iuanow, Elaine; Malik, Bilal; Obuchowski, Nancy A.; Wiskin, James
2016-01-01
Objectives. This study presents correlations between cross-sectional anatomy of human female breasts and Quantitative Transmission (QT) Ultrasound, does discriminate classifier analysis to validate the speed of sound correlations, and does a visual grading analysis comparing QT Ultrasound with mammography. Materials and Methods. Human cadaver breasts were imaged using QT Ultrasound, sectioned, and photographed. Biopsies confirmed microanatomy and areas were correlated with QT Ultrasound images. Measurements were taken in live subjects from QT Ultrasound images and values of speed of sound for each identified anatomical structure were plotted. Finally, a visual grading analysis was performed on images to determine whether radiologists' confidence in identifying breast structures with mammography (XRM) is comparable to QT Ultrasound. Results. QT Ultrasound identified all major anatomical features of the breast, and speed of sound calculations showed specific values for different breast tissues. Using linear discriminant analysis overall accuracy is 91.4%. Using visual grading analysis readers scored the image quality on QT Ultrasound as better than on XRM in 69%–90% of breasts for specific tissues. Conclusions. QT Ultrasound provides accurate anatomic information and high tissue specificity using speed of sound information. Quantitative Transmission Ultrasound can distinguish different types of breast tissue with high resolution and accuracy.
Directory of Open Access Journals (Sweden)
Yang Xu
2016-02-01
Full Text Available Many complex traits are highly correlated rather than independent. By taking the correlation structure of multiple traits into account, joint association analyses can achieve both higher statistical power and more accurate estimation. To develop a statistical approach to joint association analysis that includes allele detection and genetic effect estimation, we combined multivariate partial least squares regression with variable selection strategies and selected the optimal model using the Bayesian Information Criterion (BIC. We then performed extensive simulations under varying heritabilities and sample sizes to compare the performance achieved using our method with those obtained by single-trait multilocus methods. Joint association analysis has measurable advantages over single-trait methods, as it exhibits superior gene detection power, especially for pleiotropic genes. Sample size, heritability, polymorphic information content (PIC, and magnitude of gene effects influence the statistical power, accuracy and precision of effect estimation by the joint association analysis.
Institute of Scientific and Technical Information of China (English)
Yang Xu; Wenming Hu; Zefeng Yang; Chenwu Xu
2016-01-01
Many complex traits are highly correlated rather than independent. By taking the correlation structure of multiple traits into account, joint association analyses can achieve both higher statistical power and more accurate estimation. To develop a statistical approach to joint association analysis that includes allele detection and genetic effect estimation, we combined multivariate partial least squares regression with variable selection strategies and selected the optimal model using the Bayesian Information Criterion(BIC). We then performed extensive simulations under varying heritabilities and sample sizes to compare the performance achieved using our method with those obtained by single-trait multilocus methods. Joint association analysis has measurable advantages over single-trait methods, as it exhibits superior gene detection power, especially for pleiotropic genes. Sample size, heritability,polymorphic information content(PIC), and magnitude of gene effects influence the statistical power, accuracy and precision of effect estimation by the joint association analysis.
Institute of Scientific and Technical Information of China (English)
Yang Xu; Wenming Hu; Zefeng Yang; Chenwu Xu
2016-01-01
Many complex traits are highly correlated rather than independent. By taking the correlation structure of multiple traits into account, joint association analyses can achieve both higher statistical power and more accurate estimation. To develop a statistical approach to joint association analysis that includes allele detection and genetic effect estimation, we combined multivariate partial least squares regression with variable selection strategies and selected the optimal model using the Bayesian Information Criterion (BIC). We then performed extensive simulations under varying heritabilities and sample sizes to compare the performance achieved using our method with those obtained by single-trait multilocus methods. Joint association analysis has measurable advantages over single-trait methods, as it exhibits superior gene detection power, especially for pleiotropic genes. Sample size, heritability, polymorphic information content (PIC), and magnitude of gene effects influence the statistical power, accuracy and precision of effect estimation by the joint association analysis.
Figueira, P; Faria, J P; Adibekyan, V Zh; Oshagh, M; Santos, N C
2016-11-01
We apply the Bayesian framework to assess the presence of a correlation between two quantities. To do so, we estimate the probability distribution of the parameter of interest, ρ, characterizing the strength of the correlation. We provide an implementation of these ideas and concepts using python programming language and the pyMC module in a very short (∼ 130 lines of code, heavily commented) and user-friendly program. We used this tool to assess the presence and properties of the correlation between planetary surface gravity and stellar activity level as measured by the log([Formula: see text]) indicator. The results of the Bayesian analysis are qualitatively similar to those obtained via p-value analysis, and support the presence of a correlation in the data. The results are more robust in their derivation and more informative, revealing interesting features such as asymmetric posterior distributions or markedly different credible intervals, and allowing for a deeper exploration. We encourage the reader interested in this kind of problem to apply our code to his/her own scientific problems. The full understanding of what the Bayesian framework is can only be gained through the insight that comes by handling priors, assessing the convergence of Monte Carlo runs, and a multitude of other practical problems. We hope to contribute so that Bayesian analysis becomes a tool in the toolkit of researchers, and they understand by experience its advantages and limitations.
On the equivalence of the RTI and SVM approaches to time correlated analysis
Croft, S.; Favalli, A.; Henzlova, D.; Santi, P. A.
2015-02-01
Recently two papers on how to perform passive neutron auto-correlation analysis on time gated histograms formed from pulse train data, generically called time correlation analysis (TCA), have appeared in this journal Dubi et al. Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment (673) (2012) 111; Croft et al. Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment (691) (2012) 152. For those of us working in international nuclear safeguards these treatments are of particular interest because passive neutron multiplicity counting is a widely deployed technique for the quantification of plutonium. The purpose of this letter is to show that the skewness-variance-mean (SVM) approach developed in Dubi et al. (Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment (673) (2012) 111) is equivalent in terms of assay capability to the random trigger interval (RTI) analysis laid out in Croft et al. Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment (691) (2012) 152. Mathematically we could also use other numerical ways to extract the time correlated information from the histogram data including, for example, what we might call the mean, mean square, and mean cube approach. The important feature however, from the perspective of real world applications, is that the correlated information extracted is the same, and subsequently gets interpreted in the same way based on the same underlying physics model.
Figueira, P.; Faria, J. P.; Adibekyan, V. Zh.; Oshagh, M.; Santos, N. C.
2016-11-01
We apply the Bayesian framework to assess the presence of a correlation between two quantities. To do so, we estimate the probability distribution of the parameter of interest, ρ, characterizing the strength of the correlation. We provide an implementation of these ideas and concepts using python programming language and the pyMC module in a very short (˜ 130 lines of code, heavily commented) and user-friendly program. We used this tool to assess the presence and properties of the correlation between planetary surface gravity and stellar activity level as measured by the log(R^' }_{ {HK}}) indicator. The results of the Bayesian analysis are qualitatively similar to those obtained via p-value analysis, and support the presence of a correlation in the data. The results are more robust in their derivation and more informative, revealing interesting features such as asymmetric posterior distributions or markedly different credible intervals, and allowing for a deeper exploration. We encourage the reader interested in this kind of problem to apply our code to his/her own scientific problems. The full understanding of what the Bayesian framework is can only be gained through the insight that comes by handling priors, assessing the convergence of Monte Carlo runs, and a multitude of other practical problems. We hope to contribute so that Bayesian analysis becomes a tool in the toolkit of researchers, and they understand by experience its advantages and limitations.
On the equivalence of the RTI and SVM approaches to time correlated analysis
Energy Technology Data Exchange (ETDEWEB)
Croft, S., E-mail: crofts@ornl.gov [Safeguards and Security Technology (SST), Global Nuclear Security Technology Division, PO Box 2008, Bldg 5700, MS-6166, Oak Ridge, TN 37831-6166 (United States); Favalli, A.; Henzlova, D.; Santi, P.A. [Safeguards Science and Technology Group (NEN-1), Nuclear Engineering and Nonproliferation Division, MS-E540, Los Alamos, NM 87545 (United States)
2015-02-11
Recently two papers on how to perform passive neutron auto-correlation analysis on time gated histograms formed from pulse train data, generically called time correlation analysis (TCA), have appeared in this journal Dubi et al. Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment (673) (2012) 111; Croft et al. Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment (691) (2012) 152. For those of us working in international nuclear safeguards these treatments are of particular interest because passive neutron multiplicity counting is a widely deployed technique for the quantification of plutonium. The purpose of this letter is to show that the skewness-variance-mean (SVM) approach developed in Dubi et al. (Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment (673) (2012) 111) is equivalent in terms of assay capability to the random trigger interval (RTI) analysis laid out in Croft et al. Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment (691) (2012) 152. Mathematically we could also use other numerical ways to extract the time correlated information from the histogram data including, for example, what we might call the mean, mean square, and mean cube approach. The important feature however, from the perspective of real world applications, is that the correlated information extracted is the same, and subsequently gets interpreted in the same way based on the same underlying physics model.
Iwata, Takuya; Umeno, Ken
2016-09-01
We can observe the changes of Total Electron Content, TEC, in ionosphere by analyzing the data from Global Navigation Satellite Systems (GNSS) satellites. Up to now, preseismic TEC anomalies have been reported in several papers. However, they are not so clear as coseismic TEC anomalies, and their analysis methods have some problems for practical earthquake prediction. One factor making it difficult to detect TEC anomalies is large noises in TEC data. Nonnegligible TEC disturbances are caused by many natural mechanisms. To overcome this difficulty, we propose correlation analyses between one GNSS station and GNSS stations surrounding it. First, we model TEC time series over a few hours using polynomial functions of time. Second, we calculate prediction errors as the departure of the TEC time series from the models over time scale of a few minutes and define it as the TEC anomaly. Third, we calculate the correlation between anomaly of one GNSS station and those at the surrounding stations. Although such a correlation method has long been used for radio communications, in particular for spread spectrum communications and very long baseline interferometry to increase signal-to-noise ratio, it has not been widely applied for TEC analysis. As a result of our method, we demonstrate that the correlation analysis can detect preseismic anomalies about 1 h before the 2011 Tohoku-Oki earthquake on 11 March (Mw 9.0), 20 min before the foreshock on 9 March and 40 min before the aftershock on 7 April (Mw 7.3).
Directory of Open Access Journals (Sweden)
Zwinderman Aeilko H
2009-09-01
Full Text Available Abstract Background We generalized penalized canonical correlation analysis for analyzing microarray gene-expression measurements for checking completeness of known metabolic pathways and identifying candidate genes for incorporation in the pathway. We used Wold's method for calculation of the canonical variates, and we applied ridge penalization to the regression of pathway genes on canonical variates of the non-pathway genes, and the elastic net to the regression of non-pathway genes on the canonical variates of the pathway genes. Results We performed a small simulation to illustrate the model's capability to identify new candidate genes to incorporate in the pathway: in our simulations it appeared that a gene was correctly identified if the correlation with the pathway genes was 0.3 or more. We applied the methods to a gene-expression microarray data set of 12, 209 genes measured in 45 patients with glioblastoma, and we considered genes to incorporate in the glioma-pathway: we identified more than 25 genes that correlated > 0.9 with canonical variates of the pathway genes. Conclusion We concluded that penalized canonical correlation analysis is a powerful tool to identify candidate genes in pathway analysis.
Effects of Tropospheric Spatio-Temporal Correlated Noise on the Analysis of Space Geodetic Data
Romero-Wolf, A.; Jacobs, C. S.; Ratcliff, J. T.
2012-01-01
The standard VLBI analysis models the distribution of measurement noise as Gaussian. Because the price of recording bits is steadily decreasing, thermal errors will soon no longer dominate. As a result, it is expected that troposphere and instrumentation/clock errors will increasingly become more dominant. Given that both of these errors have correlated spectra, properly modeling the error distributions will become increasingly relevant for optimal analysis. We discuss the advantages of modeling the correlations between tropospheric delays using a Kolmogorov spectrum and the frozen flow assumption pioneered by Treuhaft and Lanyi. We then apply these correlated noise spectra to the weighting of VLBI data analysis for two case studies: X/Ka-band global astrometry and Earth orientation. In both cases we see improved results when the analyses are weighted with correlated noise models vs. the standard uncorrelated models. The X/Ka astrometric scatter improved by approx.10% and the systematic Delta delta vs. delta slope decreased by approx. 50%. The TEMPO Earth orientation results improved by 17% in baseline transverse and 27% in baseline vertical.
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. PMID:28255331
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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.
Ma, Qianli D Y; Bernaola-Galván, Pedro; Yoneyama, Mitsuru; Ivanov, Plamen Ch
2010-01-01
We investigate how extreme loss of data affects the scaling behavior of long-range power-law correlated and anti-correlated signals applying the DFA method. We introduce a segmentation approach to generate surrogate signals by randomly removing data segments from stationary signals with different types of correlations. These surrogate signals are characterized by: (i) the DFA scaling exponent $\\alpha$ of the original correlated signal, (ii) the percentage $p$ of the data removed, (iii) the average length $\\mu$ of the removed (or remaining) data segments, and (iv) the functional form of the distribution of the length of the removed (or remaining) data segments. We find that the {\\it global} scaling exponent of positively correlated signals remains practically unchanged even for extreme data loss of up to 90%. In contrast, the global scaling of anti-correlated signals changes to uncorrelated behavior even when a very small fraction of the data is lost. These observations are confirmed on the examples of human g...
Institute of Scientific and Technical Information of China (English)
无
2000-01-01
The methods of deformation analysis and modeling at single point are realized easily now,but available approaches do not make full use of the information from monitoring points and can not reveal integrated deformation regularity of a deformable body.This paper presents a fuzzy clusetering method to analyze the correlative relations of multiple points in space,and then the spatial model for a practical dangerous rockmass in the area of Three Gorges,Yangtze River is established,in which the correlation of six points in space is analyzed by geological investigation and fuzzy set theory.
Scalable multi-correlative statistics and principal component analysis with Titan.
Energy Technology Data Exchange (ETDEWEB)
Thompson, David C.; Bennett, Janine C.; Roe, Diana C.; Pebay, Philippe Pierre
2009-02-01
This report summarizes existing statistical engines in VTK/Titan and presents the recently parallelized multi-correlative and principal component analysis engines. It is a sequel to [PT08] which studied the parallel descriptive and correlative engines. The ease of use of these parallel engines is illustrated by the means of C++ code snippets. Furthermore, this report justifies the design of these engines with parallel scalability in mind; then, this theoretical property is verified with test runs that demonstrate optimal parallel speed-up with up to 200 processors.
DEFF Research Database (Denmark)
Sliusarenko, Tamara; Clemmensen, Line Katrine Harder
At the Technical University of Denmark (DTU) course evaluations are performed by the students on a questionnaire. On one form the students are asked specific questions regarding the course. On a second form they are asked specific questions about the teacher. We propose to apply canonical...... correlation analysis (CCA) to investigate the association between how students evaluate the course and how students evaluate the teacher and to reveal the structure of this association. Student’s evaluation data is characterized by high correlation between the variables (questions) and insufficient sample...
DEFF Research Database (Denmark)
Thorson, James T.; Scheuerell, Mark D.; Shelton, Andrew O.;
2015-01-01
1. Predicting and explaining the distribution and density of species is one of the oldest concerns in ecology. Species distributions can be estimated using geostatistical methods, which estimate a latent spatial variable explaining observed variation in densities, but geostatistical methods may...... be imprecise for species with low densities or few observations. Additionally, simple geostatistical methods fail to account for correlations in distribution among species and generally estimate such cross-correlations as a post hoc exercise. 2. We therefore present spatial factor analysis (SFA), a spatial...
Generalised 2D-correlation NMR analysis of a wine fermentation.
Kirwan, Gemma M; Clark, Shona; Barnett, Neil W; Niere, Julie O; Adams, Michael J
2008-11-23
A wine fermentation has been monitored on a daily basis by (1)H NMR spectroscopy. Following data pre-processing that includes synthesis of the spectra to ensure all peaks are of constant half-width, the series of spectra were examined using generalised two-dimensional correlation techniques. Synchronous and asynchronous data maps have been generated and employed to interpret the changes in the fermentation process as a function of time. The results illustrate the potential of high resolution NMR with multivariate data analysis as a tool for process monitoring and the manner in which two-dimensional correlation mapping can aid in data interpretation.
Financial Support for Rural Cooperative Economy in China Based on Grey Correlation Analysis
Institute of Scientific and Technical Information of China (English)
Fuchang; XU; Chuandong; WANG
2015-01-01
This paper firstly analyzed current situations of financial support for rural cooperative economy in China and tested the correlation between rural finance and rural cooperative economy using the grey correlation analysis method. Results indicate that there is a close relationship between amount,structure and efficiency of rural finance and development of rural cooperative economy. The amount of rural finance has the largest promotion function to development of rural cooperative economy,the next is rural finance structure,and the least is efficiency of rural finance. Based on research conclusions,it came up with pertinent policy recommendations.
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.
Characteristic analysis on UAV-MIMO channel based on normalized correlation matrix.
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.
A deterministic equivalent for the capacity analysis of correlated multi-user MIMO channels
Couillet, Romain; Silverstein, Jack W
2009-01-01
This paper provides the analysis of capacity expressions in multi-user and multi-cell systems when the transmitters and receivers have a large number of correlated antennas. Our main contribution mathematically translates into a deterministic equivalent of the Shannon transform of a class of large dimensional random matrices. This class of large matrices is used in this contribution to model (i) multi-antenna multiple access (MAC) and broadcast channels (BC) with transmit and receive channel correlation, (ii) multiple-input multiple-output (MIMO) communications with inter-cell interference and channel correlation both at the base stations and at the receiver. These models extend the classical results on multi-user MIMO capacities in independent and identically distributed (i.i.d.) Gaussian channels to the more realistic Gaussian channels with separable variance profile. On an information theoretical viewpoint, this article provides: in scenario (i), an asymptotic description of the MAC and BC rate regions as ...
Nonlinear Analysis on Cross-Correlation of Financial Time Series by Continuum Percolation System
Niu, Hongli; Wang, Jun
We establish a financial price process by continuum percolation system, in which we attribute price fluctuations to the investors’ attitudes towards the financial market, and consider the clusters in continuum percolation as the investors share the same investment opinion. We investigate the cross-correlations in two return time series, and analyze the multifractal behaviors in this relationship. Further, we study the corresponding behaviors for the real stock indexes of SSE and HSI as well as the liquid stocks pair of SPD and PAB by comparison. To quantify the multifractality in cross-correlation relationship, we employ multifractal detrended cross-correlation analysis method to perform an empirical research for the simulation data and the real markets data.
Correlation analysis of couple optical paths for microstereovision with stereo light microscope
Institute of Scientific and Technical Information of China (English)
WANG Yuezong; LI Desheng; YU Yaping
2007-01-01
A micro stereovision system with a stereo light microscope (SLM) has been applied in micromanipulation systems.There is a coupling connection between two optical paths of a stereo light microscope.The coupling intension corresponds with two factors:the structure of an SLM and the position of an object point in the view of an SLM.In this paper,a correlation function is proposed to describe the coupling intension between the couple optical paths of an SLM.The quantified results are applied to the error analysis of the imaging model.Experiments show that the correlation of the optical paths of a common main objective of stereo light microscope (CMO-SLM) is little more than that of a G-SLM,and the error must be considered when a pinhole imaging model is used to analyze its correlation.
Correlation analysis of chaotic trajectories from Chua's system
Energy Technology Data Exchange (ETDEWEB)
Alvarez-Ramirez, Jose [Division de Ciencias Basicas e Ingenieria, Universidad Autonoma Metropolitana-Iatapalapa, Apartado Postal 55-534, Mexico, D.F. 09340 (Mexico)], E-mail: jjar@xanum.uam.mx; Rodriguez, Eduardo; Echeverria, Juan Carlos; Puebla, Hector [Division de Ciencias Basicas e Ingenieria, Universidad Autonoma Metropolitana-Iatapalapa, Apartado Postal 55-534, Mexico, D.F. 09340 (Mexico)
2008-06-15
Chaotic systems exhibit an erratic behavior reflected by a strong divergence of trajectories with arbitrarily close initial condition. In this way, similar to trajectories from pseudorandom number generators, chaotic trajectories can be seen as noise with some degree of correlation. This work focuses on the study of some correlation properties (i.e., scaling) of chaotic trajectories from the Chua's system. This is done by using detrended fluctuation analysis, which is a method designed for the detection of correlations in stochastic time series. It is found that, in general, Chua's trajectories behave as a Brownian motion for small time scales, while they can display a white noise-like behavior or be dominated by harmonic oscillations for large time scales.
Directory of Open Access Journals (Sweden)
Skraparlis D
2009-01-01
Full Text Available Abstract The study of relaying systems has found renewed interest in the context of cooperative diversity for communication channels suffering from fading. This paper provides analytical expressions for the end-to-end SNR and outage probability of cooperative diversity in correlated lognormal channels, typically found in indoor and specific outdoor environments. The system under consideration utilizes decode-and-forward relaying and Selection Combining or Maximum Ratio Combining at the destination node. The provided expressions are used to evaluate the gains of cooperative diversity compared to noncooperation in correlated lognormal channels, taking into account the spectral and energy efficiency of the protocols and the half-duplex or full-duplex capability of the relay. Our analysis demonstrates that correlation and lognormal variances play a significant role on the performance gain of cooperative diversity against noncooperation.
Combining individual participant and aggregated data in a meta-analysis with correlational studies.
Pigott, Terri; Williams, Ryan; Polanin, Joshua
2012-12-01
This paper presents methods for combining individual participant data (IPD) with aggregated study level data (AD) in a meta-analysis of correlational studies. Although medical researchers have employed IPD in a wide range of studies, only a single example exists in the social sciences. New policies at the National Science Foundation requiring grantees to submit data archiving plans may increase social scientists' access to individual level data that could be combined with traditional meta-analysis. The methods presented here extend prior work on IPD to meta-analyses using correlational studies. The examples presented illustrate the synthesis of publicly available national datasets in education with aggregated study data from a meta-analysis examining the correlation of socioeconomic status measures and academic achievement. The major benefit of the inclusion of the individual level is that both within-study and between-study interactions among moderators of effect size can be estimated. Given the potential growth in data archives in the social sciences, we should see a corresponding increase in the ability to synthesize IPD and AD in a single meta-analysis, leading to a more complete understanding of how within-study and between-study moderators relate to effect size. Copyright © 2012 John Wiley & Sons, Ltd.
Gomes, Manuel; Hatfield, Laura; Normand, Sharon-Lise
2016-09-20
Meta-analysis of individual participant data (IPD) is increasingly utilised to improve the estimation of treatment effects, particularly among different participant subgroups. An important concern in IPD meta-analysis relates to partially or completely missing outcomes for some studies, a problem exacerbated when interest is on multiple discrete and continuous outcomes. When leveraging information from incomplete correlated outcomes across studies, the fully observed outcomes may provide important information about the incompleteness of the other outcomes. In this paper, we compare two models for handling incomplete continuous and binary outcomes in IPD meta-analysis: a joint hierarchical model and a sequence of full conditional mixed models. We illustrate how these approaches incorporate the correlation across the multiple outcomes and the between-study heterogeneity when addressing the missing data. Simulations characterise the performance of the methods across a range of scenarios which differ according to the proportion and type of missingness, strength of correlation between outcomes and the number of studies. The joint model provided confidence interval coverage consistently closer to nominal levels and lower mean squared error compared with the fully conditional approach across the scenarios considered. Methods are illustrated in a meta-analysis of randomised controlled trials comparing the effectiveness of implantable cardioverter-defibrillator devices alone to implantable cardioverter-defibrillator combined with cardiac resynchronisation therapy for treating patients with chronic heart failure. © 2016 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.
Iterative cross-correlation analysis of resting state functional magnetic resonance imaging data.
Directory of Open Access Journals (Sweden)
Liqin Yang
Full Text Available Seed-based cross-correlation analysis (sCCA and independent component analysis have been widely employed to extract functional networks from the resting state functional magnetic resonance imaging data. However, the results of sCCA, in terms of both connectivity strength and network topology, can be sensitive to seed selection variations. ICA avoids the potential problems due to seed selection, but choosing which component(s to represent the network of interest could be subjective and problematic. In this study, we proposed a seed-based iterative cross-correlation analysis (siCCA method for resting state brain network analysis. The method was applied to extract default mode network (DMN and stable task control network (STCN in two independent datasets acquired from normal adults. Compared with the networks obtained by traditional sCCA and ICA, the resting state networks produced by siCCA were found to be highly stable and independent on seed selection. siCCA was used to analyze DMN in first-episode major depressive disorder (MDD patients. It was found that, in the MDD patients, the volume of DMN negatively correlated with the patients' social disability screening schedule scores.
Directory of Open Access Journals (Sweden)
Jin Shuxins
2016-01-01
Full Text Available Different highway safety life protection engineering decision-making have important meaning. The achieving goals and optimal highway safety life protection engineering scheme can not only improve the function of the highway facilities and service level, still can reduce the traffic accident, which caused by the imperfect highway facilities. Different highway safety life protection engineering decision-making is a multiple targets, multi-layers and multi-schemes system evaluation problem. With regard to lack of concrete data on multiple targets, multi-layers and multi-schemes system evaluation problem, make analytical hierarchy process combined with the entropy value analysis into the grey relational comprehensive evaluation method, and then get entropy-hierarchical grey correlation analysis method. This method is a qualitative and quantitative decision method, which combine comparison principle of analytic hierarchy process (AHP and the entropy principle of entropy value analysis method to determine the relative weight of various indexes between factors layer-by-layer. Then using grey relational analysis by low-layer to high-layer step by step in the possible scheme and referenced scheme. Finally, calculating the comprehensive correlation degree between the possible scheme and referenced scheme, the best plan which has maximum grey correlation degree can be selected.
Sequential Dictionary Learning From Correlated Data: Application to fMRI Data Analysis.
Seghouane, Abd-Krim; Iqbal, Asif
2017-03-22
Sequential dictionary learning via the K-SVD algorithm has been revealed as a successful alternative to conventional data driven methods such as independent component analysis (ICA) for functional magnetic resonance imaging (fMRI) data analysis. fMRI datasets are however structured data matrices with notions of spatio-temporal correlation and temporal smoothness. This prior information has not been included in the K-SVD algorithm when applied to fMRI data analysis. In this paper we propose three variants of the K-SVD algorithm dedicated to fMRI data analysis by accounting for this prior information. The proposed algorithms differ from the K-SVD in their sparse coding and dictionary update stages. The first two algorithms account for the known correlation structure in the fMRI data by using the squared Q, R-norm instead of the Frobenius norm for matrix approximation. The third and last algorithm account for both the known correlation structure in the fMRI data and the temporal smoothness. The temporal smoothness is incorporated in the dictionary update stage via regularization of the dictionary atoms obtained with penalization. The performance of the proposed dictionary learning algorithms are illustrated through simulations and applications on real fMRI data.
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.
Correlates of Unwanted Births in Bangladesh: A Study through Path Analysis
Singh, Brijesh P.
2016-01-01
Background 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. Methods 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. Results 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. Conclusion 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
Shi, Lizheng; Liu, Jinan; Fonseca, Vivian; Walker, Philip; Kalsekar, Anupama; Pawaskar, Manjiri
2010-09-13
It is vital to understand the associations between the medication event monitoring systems (MEMS) and self-reported questionnaires (SRQs) because both are often used to measure medication adherence and can produce different results. In addition, the economic implication of using alternative measures is important as the cost of electronic monitoring devices is not covered by insurance, while self-reports are the most practical and cost-effective method in the clinical settings. This meta-analysis examined the correlations of two measurements of medication adherence: MEMS and SRQs. The literature search (1980-2009) used PubMed, OVID MEDLINE, PsycINFO (EBSCO), CINAHL (EBSCO), OVID HealthStar, EMBASE (Elsevier), and Cochrane Databases. Studies were included if the correlation coefficients [Pearson (rp) or Spearman (rs)] between adherences measured by both MEMS and SRQs were available or could be calculated from other statistics in the articles. Data were independently abstracted in duplicate with standardized protocol and abstraction form including 1) first author's name; 2) year of publication; 3) disease status of participants; 4) sample size; 5) mean age (year); 6) duration of trials (month); 7) SRQ names if available; 8) adherence (%) measured by MEMS; 9) adherence (%) measured by SRQ; 10) correlation coefficient and relative information, including p-value, 95% confidence interval (CI). A meta-analysis was conducted to pool the correlation coefficients using random-effect model. Eleven studies (N = 1,684 patients) met the inclusion criteria. The mean of adherence measured by MEMS was 74.9% (range 53.4%-92.9%), versus 84.0% by SRQ (range 68.35%-95%). The correlation between adherence measured by MEMS and SRQs ranged from 0.24 to 0.87. The pooled correlation coefficient for 11 studies was 0.45 (p = 0.001, 95% confidence interval [95% CI]: 0.34-0.56). The subgroup meta-analysis on the seven studies reporting rp and four studies reporting rs reported the pooled
Correlating the EMC analysis and testing methods for space systems in MIL-STD-1541A
Perez, Reinaldo J.
1990-01-01
A study was conducted to improve the correlation between the electromagnetic compatibility (EMC) analysis models stated in MIL-STD-1541A and the suggested testing methods used for space systems. The test and analysis methods outlined in MIL-STD-1541A are described, and a comparative assessment of testing and analysis techniques as they relate to several EMC areas is presented. Suggestions on present analysis and test methods are introduced to harmonize and bring the analysis and testing tools in MIL-STD-1541A into closer agreement. It is suggested that test procedures in MIL-STD-1541A must be improved by providing alternatives to the present use of shielded enclosures as the primary site for such tests. In addition, the alternate use of anechoic chambers and open field test sites must be considered.
Correlative and multivariate analysis of increased radon concentration in underground laboratory.
Maletić, Dimitrije M; Udovičić, Vladimir I; Banjanac, Radomir M; Joković, Dejan R; Dragić, Aleksandar L; Veselinović, Nikola B; Filipović, Jelena
2014-11-01
The results of analysis using correlative and multivariate methods, as developed for data analysis in high-energy physics and implemented in the Toolkit for Multivariate Analysis software package, of the relations of the variation of increased radon concentration with climate variables in shallow underground laboratory is presented. Multivariate regression analysis identified a number of multivariate methods which can give a good evaluation of increased radon concentrations based on climate variables. The use of the multivariate regression methods will enable the investigation of the relations of specific climate variable with increased radon concentrations by analysis of regression methods resulting in 'mapped' underlying functional behaviour of radon concentrations depending on a wide spectrum of climate variables. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
Directory of Open Access Journals (Sweden)
Reddivenkatagari Subbarama Krishna Reddy
2013-06-01
Full Text Available One hundred germplasm lines of okra (Abelmoschus esculentus (L. Moench were evaluated in a randomized block design with two replications at the Vegetable Research Station, Rajendranagar, Hyderabad, Andhra Pradesh, India, during kharif, 2008. Correlation and path coefficient analysis were carried out to study the character association and contribution, respectively, for thirteen quantitative characters, namely plant height (cm, number of branches per plant, internodal length(cm, days to 50% flowering, first flowering node, first fruiting node, fruit length (cm, fruit width (cm, fruit weight (g, total number of fruits per plant, number of marketable fruits per plant, total yield per plant (g and marketable yield per plant (g for the identification of appropriate selection indices. Phenotypic and genotypic correlation coefficient analysis revealed that plant height, fruit length, fruit width, fruit weight, total number of fruits per plant, number of marketable fruits per plant and total yield per plant had significant positive correlation, while number of branches per plant, internodal length, days to 50% flowering, first flowering node and first fruiting node had significant negative correlation with marketable yield per plant.Genotypic path coefficient analysis revealed that fruit weight, total number of fruits per plant and number of marketable fruits per plant had positively high direct effect on marketable pod yield per plant. Correlation and path coefficient analyses revealed that fruit weight, total number of fruits per plant and number of marketable fruits per plant not only had positively significant association with marketable pod yield per plant, but also had positively high direct effect on marketable pod yield per plant and are regarded as the main determinants of marketable pod yield per plant. The improvement in marketable pod yield per plant will be efficient, if the selection is based on fruit weight, total number of fruits per
Meta-analysis of the correlation between selenium and incidence of hepatocellular carcinoma.
Zhang, Ziwei; Bi, Mingyu; Liu, Qi; Yang, Jie; Xu, Shiwen
2016-11-22
Hepatocellular carcinoma (HCC) is the most common cancer type. There is a correlation between selenium (Se) deficiency and the incidence of HCC. To clarify the effects of Se level on the risk of HCC patients, a meta-analysis was performed. A total of 9 articles published between 1994 and 2016 worldwide were selected through searching PubMed, EMBASE, web of science, Cochrane Library, Springer Link, Chinese National Knowledge Infrastructure (CNKI), and Chinese Biology Medicine (CBM), and the information were analyzed using a meta-analysis method. Heterogeneity was assessed by using the I2 index. Publication bias was evaluated by Begg's Test analysis. Pooled analysis indicated that patients with HCC had lower Se levels than the healthy controls [standardized mean difference (SMD)= -1.08, 95% confidence intercal (CI) = (-0.136, -0.08), P < 0.001]. Further subgroup analysis showed this effect to be independent of the study design, race or sample collection. In conclusion, this meta-analysis suggested an inverse correlation between Se level and the risk of HCC in humans patients.
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Priyanka Saxena
2013-01-01
Full Text Available Introduction. Liver disease patients have complex hemostatic defects leading to a delicate, unstable balance between bleeding and thrombosis. Conventional tests such as PT and APTT are unable to depict these defects completely. Aims. This study aimed at analyzing the abnormal effects of liver disease on sonoclot signature by using sonoclot analyzer (which depicts the entire hemostatic pathway and assessing the correlations between sonoclot variables and conventional coagulation tests. Material and Methods. Clinical and laboratory data from fifty inpatients of four subgroups of liver disease, including decompensated cirrhosis, chronic hepatitis, cirrhosis with HCC and acute-on-chronic liver failure were analyzed. All patients and controls were subjected to sonoclot analysis and correlated with routine coagulation parameters including platelet count, PT, APTT, fibrinogen, and D-dimer. Results. The sonoclot signatures demonstrated statistically significant abnormalities in patients with liver disease as compared to healthy controls. PT and APTT correlated positively with SONACT (P<0.008 and <0.0015, resp. while platelet count and fibrinogen levels depicted significant positive and negative correlations with clot rate and SONACT respectively. Conclusion. Sonoclot analysis may prove to be an efficient tool to assess coagulopathies in liver disease patients. Clot rate could emerge as a potential predictor of hypercoagulability in these patients.
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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
Edjabou, Maklawe Essonanawe; Martín-Fernández, Josep Antoni; Scheutz, Charlotte; Astrup, Thomas Fruergaard
2017-09-04
Data for fractional solid waste composition provide relative magnitudes of individual waste fractions, the percentages of which always sum to 100, thereby connecting them intrinsically. Due to this sum constraint, waste composition data represent closed data, and their interpretation and analysis require statistical methods, other than classical statistics that are suitable only for non-constrained data such as absolute values. However, the closed characteristics of waste composition data are often ignored when analysed. The results of this study showed, for example, that unavoidable animal-derived food waste amounted to 2.21±3.12% with a confidence interval of (-4.03; 8.45), which highlights the problem of the biased negative proportions. A Pearson's correlation test, applied to waste fraction generation (kg mass), indicated a positive correlation between avoidable vegetable food waste and plastic packaging. However, correlation tests applied to waste fraction compositions (percentage values) showed a negative association in this regard, thus demonstrating that statistical analyses applied to compositional waste fraction data, without addressing the closed characteristics of these data, have the potential to generate spurious or misleading results. Therefore, ¨compositional data should be transformed adequately prior to any statistical analysis, such as computing mean, standard deviation and correlation coefficients. Copyright © 2017 Elsevier Ltd. All rights reserved.
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.
Analysis of field-scale spatial correlations and variations of soil nutrients using geostatistics.
Liu, Ruimin; Xu, Fei; Yu, Wenwen; Shi, Jianhan; Zhang, Peipei; Shen, Zhenyao
2016-02-01
Spatial correlations and soil nutrient variations are important for soil nutrient management. They help to reduce the negative impacts of agricultural nonpoint source pollution. Based on the sampled available nitrogen (AN), available phosphorus (AP), and available potassium (AK), soil nutrient data from 2010, the spatial correlation, was analyzed, and the probabilities of the nutrient's abundance or deficiency were discussed. This paper presents a statistical approach to spatial analysis, the spatial correlation analysis (SCA), which was originally developed for describing heterogeneity in the presence of correlated variation and based on ordinary kriging (OK) results. Indicator kriging (IK) was used to assess the susceptibility of excess of soil nutrients based on crop needs. The kriged results showed there was a distinct spatial variability in the concentration of all three soil nutrients. High concentrations of these three soil nutrients were found near Anzhou. As the distance from the center of town increased, the concentration of the soil nutrients gradually decreased. Spatially, the relationship between AN and AP was negative, and the relationship between AP and AK was not clear. The IK results showed that there were few areas with a risk of AN and AP overabundance. However, almost the entire study region was at risk of AK overabundance. Based on the soil nutrient distribution results, it is clear that the spatial variability of the soil nutrients differed throughout the study region. This spatial soil nutrient variability might be caused by different fertilizer types and different fertilizing practices.
Correlations and path analysis in components of fiber yield in cultivars of upland cotton
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Laíse Ferreira de Araújo
2012-01-01
Full Text Available This study evaluated the relative contribution of agronomic and technological components on the fiber yield in upland cotton cultivars. The experiment was carried out with 11 upland cotton cultivars in a completely randomized blocks design with three replications. Initially, we performed analysis of variance, with the F test at 5% probability for the effect of cultivar as fixed effects as well as block and environment effects as random. Then the values were ordered according to cluster test Scott-Knott, at 5% probability level. The significance of the null hypothesis that all possible canonical correlations are null was evaluated using the chi-square test. The correlations were estimated through the path analysis. By examining the canonical correlations there was dependence between the two groups of variables and therefore it is possible to promote changes in certain characteristics through the selection of others correlated. Plants of upland cotton with higher fiber yield were influenced by the decrease in average weight of the cotton boll. When there is a reduced fiber yield, there is also an increase in uniformity and strength thereof. The fiber resistance had negative indirect effects on the fiber uniformity and length.
A Novel Approach for Nonstationary Time Series Analysis with Time-Invariant Correlation Coefficient
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Chengrui Liu
2014-01-01
Full Text Available We will concentrate on the modeling and analysis of a class of nonstationary time series, called correlation coefficient stationary series, which commonly exists in practical engineering. First, the concept and scope of correlation coefficient stationary series are discussed to get a better understanding. Second, a theorem is proposed to determine standard deviation function for correlation coefficient stationary series. Third, we propose a moving multiple-point average method to determine the function forms for mean and standard deviation, which can help to improve the analysis precision, especially in the context of limited sample size. Fourth, the conditional likelihood approach is utilized to estimate the model parameters. In addition, we discuss the correlation coefficient stationarity test method, which can contribute to the verification of modeling validity. Monte Carlo simulation study illustrates the authentication of the theorem and the validity of the established method. Empirical study shows that the approach can satisfactorily explain the nonstationary behavior of many practical data sets, including stock returns, maximum power load, China money supply, and foreign currency exchange rate. The effectiveness of these processes is addressed by forecasting performance.
Statistical analysis of data from dilution assays with censored correlated counts.
Quiroz, Jorge; Wilson, Jeffrey R; Roychoudhury, Satrajit
2012-01-01
Frequently, count data obtained from dilution assays are subject to an upper detection limit, and as such, data obtained from these assays are usually censored. Also, counts from the same subject at different dilution levels are correlated. Ignoring the censoring and the correlation may provide unreliable and misleading results. Therefore, any meaningful data modeling requires that the censoring and the correlation be simultaneously addressed. Such comprehensive approaches of modeling censoring and correlation are not widely used in the analysis of dilution assays data. Traditionally, these data are analyzed using a general linear model on a logarithmic-transformed average count per subject. However, this traditional approach ignores the between-subject variability and risks, providing inconsistent results and unreliable conclusions. In this paper, we propose the use of a censored negative binomial model with normal random effects to analyze such data. This model addresses, in addition to the censoring and the correlation, any overdispersion that may be present in count data. The model is shown to be widely accessible through the use of several modern statistical software. Copyright © 2012 John Wiley & Sons, Ltd.
Michalopoulos, Ioannis; Pavlopoulos, Georgios A; Malatras, Apostolos; Karelas, Alexandros; Kostadima, Myrto-Areti; Schneider, Reinhard; Kossida, Sophia
2012-06-06
Bioinformatics and high-throughput technologies such as microarray studies allow the measure of the expression levels of large numbers of genes simultaneously, thus helping us to understand the molecular mechanisms of various biological processes in a cell. We calculate the Pearson Correlation Coefficient (r-value) between probe set signal values from Affymetrix Human Genome Microarray samples and cluster the human genes according to the r-value correlation matrix using the Neighbour Joining (NJ) clustering method. A hyper-geometric distribution is applied on the text annotations of the probe sets to quantify the term overrepresentations. The aim of the tool is the identification of closely correlated genes for a given gene of interest and/or the prediction of its biological function, which is based on the annotations of the respective gene cluster. Human Gene Correlation Analysis (HGCA) is a tool to classify human genes according to their coexpression levels and to identify overrepresented annotation terms in correlated gene groups. It is available at: http://biobank-informatics.bioacademy.gr/coexpression/.
Analysis of two-orbital correlations in wave functions restricted to electron-pair states
Boguslawski, Katharina; Tecmer, Paweł; Legeza, Örs
2016-10-01
Wave functions constructed from electron-pair states can accurately model strong electron correlation effects and are promising approaches especially for larger many-body systems. In this article, we analyze the nature and the type of electron correlation effects that can be captured by wave functions restricted to electron-pair states. We focus on the pair-coupled-cluster doubles (pCCD) ansatz also called the antisymmetric product of the 1-reference orbital geminal (AP1roG) method, combined with an orbital optimization protocol presented in Boguslawski et al. [Phys. Rev. B 89, 201106(R) (2014)], 10.1103/PhysRevB.89.201106, whose performance is assessed against electronic structures obtained form density-matrix renormalization-group reference data. Our numerical analysis covers model systems for strong correlation: the one-dimensional Hubbard model with a periodic boundary condition as well as metallic and molecular hydrogen rings. Specifically, the accuracy of pCCD/AP1roG is benchmarked using the single-orbital entropy, the orbital-pair mutual information, as well as the eigenvalue spectrum of the one-orbital and two-orbital reduced density matrices. Our study indicates that contributions from singly occupied states become important in the strong correlation regime which highlights the limitations of the pCCD/AP1roG method. Furthermore, we examine the effect of orbital rotations within the pCCD/AP1roG model on correlations between orbital pairs.
Kujala, Jan; Sudre, Gustavo; Vartiainen, Johanna; Liljeström, Mia; Mitchell, Tom; Salmelin, Riitta
2014-05-15
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. Copyright © 2014 Elsevier Inc. All rights reserved.
Cross-correlation analysis of noise radar signals propagating through lossy dispersive media
Smith, Sonny; Narayanan, Ram M.
2011-06-01
Correlation detection is an essential ingredient in noise radar. Such detection is achieved via coherent signal processing, which, conceivably, gives the best enhancement in the signal-to-noise ratio. Over the years, much research and progress has been made on the use of noise radar systems as means for effective through-wall detection. Information about a particular target's range and/or velocity are often acquired by comparing and analyzing both transmit and received waveforms. One of the widely used techniques employed to measure the degree of similarity between the two signals is correlation. The aforementioned methodology determines to what extent two waveforms match by multiplying and shifting one signal with respect to a time-lagged version of the second signal. This feature of correlation is very applicable to radar signals since a received signal from a target is delayed on the path of return to the receiving antenna. Transmission and reflection impairments will distort the propagating signals and degrade the correlation. Thus, it is essential that we try to study the effects that such degradations can have on the signals that will be used in the correlation process. This paper presents some concepts of a noise radar system, simulation studies, and an analysis of the results ascertained.
Kotze, Helen L; Armitage, Emily G; Sharkey, Kieran J; Allwood, James W; Dunn, Warwick B; Williams, Kaye J; Goodacre, Royston
2013-10-23
Metabolomics has become increasingly popular in the study of disease phenotypes and molecular pathophysiology. One branch of metabolomics that encompasses the high-throughput screening of cellular metabolism is metabolic profiling. In the present study, the metabolic profiles of different tumour cells from colorectal carcinoma and breast adenocarcinoma were exposed to hypoxic and normoxic conditions and these have been compared to reveal the potential metabolic effects of hypoxia on the biochemistry of the tumour cells; this may contribute to their survival in oxygen compromised environments. In an attempt to analyse the complex interactions between metabolites beyond routine univariate and multivariate data analysis methods, correlation analysis has been integrated with a human metabolic reconstruction to reveal connections between pathways that are associated with normoxic or hypoxic oxygen environments. Correlation analysis has revealed statistically significant connections between metabolites, where differences in correlations between cells exposed to different oxygen levels have been highlighted as markers of hypoxic metabolism in cancer. Network mapping onto reconstructed human metabolic models is a novel addition to correlation analysis. Correlated metabolites have been mapped onto the Edinburgh human metabolic network (EHMN) with the aim of interlinking metabolites found to be regulated in a similar fashion in response to oxygen. This revealed novel pathways within the metabolic network that may be key to tumour cell survival at low oxygen. Results show that the metabolic responses to lowering oxygen availability can be conserved or specific to a particular cell line. Network-based correlation analysis identified conserved metabolites including malate, pyruvate, 2-oxoglutarate, glutamate and fructose-6-phosphate. In this way, this method has revealed metabolites not previously linked, or less well recognised, with respect to hypoxia before. Lactate
Dynamical Analysis of Stock Market Instability by Cross-correlation Matrix
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.
X-Ray Cross-Correlation Analysis of Disordered Ensembles of Particles: Potentials and Limitations
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R. P. Kurta
2013-01-01
Full Text Available Angular X-ray cross-correlation analysis (XCCA is an approach to study the structure of disordered systems using the results of X-ray scattering experiments. In this paper we summarize recent theoretical developments related to the Fourier analysis of the cross-correlation functions. Results of our simulations demonstrate the application of XCCA to two- and three-dimensional (2D and 3D disordered ensembles of particles. We show that the structure of a single particle can be recovered using X-ray data collected from a 2D disordered system of identical particles. We also demonstrate that valuable structural information about the local structure of 3D systems, inaccessible from a standard small-angle X-ray scattering experiment, can be resolved using XCCA.
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Piepel, Gregory F.
2013-08-01
This article discusses the paper "Experimental Design for Engineering Dimensional Analysis" by Albrecht et al. (2013, Technometrics). That paper provides and overview of engineering dimensional analysis (DA) for use in developing DA models. The paper proposes methods for generating model-robust experimental designs to supporting fitting DA models. The specific approach is to develop a design that maximizes the efficiency of a specified empirical model (EM) in the original independent variables, subject to a minimum efficiency for a DA model expressed in terms of dimensionless groups (DGs). This discussion article raises several issues and makes recommendations regarding the proposed approach. Also, the concept of spurious correlation is raised and discussed. Spurious correlation results from the response DG being calculated using several independent variables that are also used to calculate predictor DGs in the DA model.
Restoration of recto-verso colour documents using correlated component analysis
Tonazzini, Anna; Bedini, Luigi
2013-12-01
In this article, we consider the problem of removing see-through interferences from pairs of recto-verso documents acquired either in grayscale or RGB modality. The see-through effect is a typical degradation of historical and archival documents or manuscripts, and is caused by transparency or seeping of ink from the reverse side of the page. We formulate the problem as one of separating two individual texts, overlapped in the recto and verso maps of the colour channels through a linear convolutional mixing operator, where the mixing coefficients are unknown, while the blur kernels are assumed known a priori or estimated off-line. We exploit statistical techniques of blind source separation to estimate both the unknown model parameters and the ideal, uncorrupted images of the two document sides. We show that recently proposed correlated component analysis techniques overcome the already satisfactory performance of independent component analysis techniques and colour decorrelation, when the two texts are even sensibly correlated.
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Ali Gohary
2014-10-01
Full Text Available This study examines the relationship between Big Five personality traits with shopping motivation variables consisting of compulsive and impulsive buying, hedonic and utilitarian shopping values. Two hundred forty seven college students were recruited to participate in this research. Bivariate correlation demonstrates an overlap between personality traits; consequently, canonical correlation was performed to prevent this phenomenon. The results of multiple regression analysis suggested conscientiousness, neuroticism and openness as predictors of compulsive buying, impulsive buying and utilitarian shopping values. In addition, the results showed significant differences between males and females on conscientiousness, neuroticism, openness, compulsive buying and hedonic shopping value. Besides, using hierarchical regression analysis, we examined sex as moderator between Big Five personality traits and shopping variables, but we didn’t find sufficient evidence to prove it.
Time Series Analysis on Stock Market for Text Mining Correlation of Economy News
Seker, Sadi Evren; MERT, Cihan; Al-Naami, Khaled; Ozalp, Nuri; Ayan, Ugur
2014-01-01
This paper proposes an information retrieval method for the economy news. The effect of economy news, are researched in the word level and stock market values are considered as the ground proof. The correlation between stock market prices and economy news is an already addressed problem for most of the countries. The most well-known approach is applying the text mining approaches to the news and some time series analysis techniques over stock market closing values in order to apply classifica...
Detecting long-range correlation with detrended fluctuation analysis: Application to BWR stability
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Espinosa-Paredes, Gilberto [Departamento de Ingenieria de Procesos e Hidraulica, Universidad Autonoma Metropolitana-Iztapalapa, Apartado Postal 55-534, Mexico, DF 09340 (Mexico)]. E-mail: gepe@xanum.uam.mx; Alvarez-Ramirez, Jose [Departamento de Ingenieria de Procesos e Hidraulica, Universidad Autonoma Metropolitana-Iztapalapa, Apartado Postal 55-534, Mexico, DF 09340 (Mexico); Vazquez, Alejandro [Departamento de Ingenieria de Procesos e Hidraulica, Universidad Autonoma Metropolitana-Iztapalapa, Apartado Postal 55-534, Mexico, DF 09340 (Mexico)
2006-11-15
The aim of this paper is to explore the application of detrended fluctuation analysis (DFA) to study boiling water reactor stability. DFA is a scaling method commonly used for detecting long-range correlations in non-stationary time series. This method is based on the random walk theory and was applied to neutronic power signal of Forsmark stability benchmark. Our results shows that the scaling properties breakdown during unstable oscillations.
Getting full control of canonical correlation analysis with the AutoBiplot.CCA function
Alves, M. Rui
2016-06-01
Function AutoBiplot.CCA was built in R language. Given two multivariate data sets, this function carries out a conventional canonical correlation analysis, followed by the automatic production of predictive biplots based on the accuracy of readings as assessed by a mean standard predictive error and a user defined tolerance value. As the user's intervention is mainly restricted to the choice of the magnitude of the t.axis value, common misinterpretations, overestimations and adjustments between outputs and personal beliefs are avoided.
Inter-subject correlation in fMRI: method validation against stimulus-model based analysis.
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Juha Pajula
Full Text Available Within functional magnetic resonance imaging (fMRI, the use of the traditional general linear model (GLM based analysis methods is often restricted to strictly controlled research setups requiring a parametric activation model. Instead, Inter-Subject Correlation (ISC method is based on voxel-wise correlation between the time series of the subjects, which makes it completely non-parametric and thus suitable for naturalistic stimulus paradigms such as movie watching. In this study, we compared an ISC based analysis results with those of a GLM based in five distinct controlled research setups. We used International Consortium for Brain Mapping functional reference battery (FRB fMRI data available from the Laboratory of Neuro Imaging image data archive. The selected data included measurements from 37 right-handed subjects, who all had performed the same five tasks from FRB. The GLM was expected to locate activations accurately in FRB data and thus provide good grounds for investigating relationship between ISC and stimulus induced fMRI activation. The statistical maps of ISC and GLM were compared with two measures. The first measure was the Pearson's correlation between the non-thresholded ISC test-statistics and absolute values of the GLM Z-statistics. The average correlation value over five tasks was 0.74. The second was the Dice index between the activation regions of the methods. The average Dice value over the tasks and three threshold levels was 0.73. The results of this study indicated how the data driven ISC analysis found the same foci as the model-based GLM analysis. The agreement of the results is highly interesting, because ISC is applicable in situations where GLM is not suitable, for example, when analyzing data from a naturalistic stimuli experiment.
Correlation between PON1 gene polymorphisms and breast cancer risk: a Meta-analysis
Wen, Yayuan; Huang, Zemin; Zhang, Xiaohua; Gao, Bo; He, Yujun
2015-01-01
Objective: A number of studies have investigated the relationship between the PON1 gene polymorphisms and breast cancer risk, but the conclusions are not consistent. In this paper, a meta-analysis was conducted to explore the possible reasons for these inconsistencies, expecting to further clarify the correlation between PON1 gene polymorphisms and breast cancer risk. Methods: After searches in the database such as MEDLINE, EBSCO, ProQuest, Google Scholar, High-Wire, SID (Scientific Informati...
A correlation for calculating elemental composition from proximate analysis of biomass materials
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Jigisha Parikh; S.A. Channiwala; G.K. Ghosal [Sarvajanik College of Engineering and Technology, Surat (India). Chemical Engineering Department
2007-08-15
Elemental composition of biomass is an important property, which defines the energy content and determines the clean and efficient use of the biomass materials. However, the ultimate analysis requires very expensive equipments and highly trained analysts. The proximate analysis on the other hand only requires standard laboratory equipments and can be run by any competent scientist or engineer. This work introduces a general correlation, based on proximate analysis of biomass materials, to calculate elemental composition, derived using 200 data points and validated further for additional 50 data points. The entire spectrum of solid lignocellulosic materials have been considered in the derivation of the present correlation, which is given as: C = 0.637FC + 0.455VM, H = 0.052FC + 0.062VM, O = 0.304FC + 0.476VM, where FC - 4.7-38.4% fixed carbon, VM - 57.2-90.6% volatile matter, C - 36.2-53.1% carbon, H - 4.36-8.3% hydrogen and O - 31.37-49.5% oxygen in wt% on a dry basis. The average absolute error of these correlations are 3.21%, 4.79%, 3.4% and bias error of 0.21%, -0.15% and 0.49% with respect to measured values C, H and O, respectively. The major advantage of these correlations is their capability to compute elemental components of biomass materials from the simple proximate analysis and thereby provides a useful tool for the modeling of combustion, gasification and pyrolysis processes. 32 refs., 6 figs., 2 tabs.
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Hong-xia DONG
2015-04-01
Full Text Available Objective To explore the relationship between Helicobacter pylori (Hp infection and colorectal cancer in different continents or economic conditions. Methods Published case-control studies dealing with the correlation of colorectal cancer with Hp infection were retrieved from PubMed, EMBASE, High Wire Press, Ovid, Medline and EBSCO. Meta-analysis was performed by using RevMan 5.3 software. We selected the OR and 95% CI as indicators of the analysis according to different continents (Asia, Europe, and America and economic conditions (developed countries and developing countries. Results A total of 23 studies dealing with the correlation of colorectal cancer with Hp infection were included in the present meta-analysis, and there was a total sample of 182,561 patients, including 88,378 cases in Hp positive group and 94,183 cases in Hp negative group. The results of meta-analysis showed the OR was 1.42 (95%CI 1.38-1.46. Geographically, the correlation was low in Asian countries (OR=1.29, 95%CI 1.13-1.48, and was highest in American countries (OR=1.44, 95%CI 1.39-1.48. According to the economic conditions, the correlation was low in developing countries (OR=1.17, 95%CI 1.01-1.37, and was higher in developed countries (OR=1.43, 95%CI 1.39-1.47. Conclusions Hp infection is a risk factor for colorectal cancer. It seems that there is a close relation ship between its incidence and geography, and also economic condition. DOI: 10.11855/j.issn.0577-7402.2015.03.13
Optical injection induced polarization mode switching and correlation analysis on a VCSEL
Damodarakurup, Sajeev; Vudayagiri, Ashok
2015-01-01
Vertical cavity Surface Emitting Laser (VCSEL) diodes emit light in two polarization modes. The amount of optical feedback is found to influence the intensities of the emitted modes. We investigate the effect of the amount of total output polarization feedback and polarization selective feedback on the intensities of the two emitted polarization modes. A 40 micro seconds resolution time series correlation analysis is done for different feedback conditions and investigate the power spectral continuity and onset of chaos on two polarization modes
Institute of Scientific and Technical Information of China (English)
Marketa; Hermanova; Petr; Karasek; Jiri; Tomasek; Jiri; Lenz; Jiri; Jarkovsky; Petr; Dite
2010-01-01
AIM:To perform a comparative analysis of clinicopathological correlations of cyclooxygenase2 (COX2) expression in pancreatic cancer, examined by monoclonal and polyclonal antibodies.METHODS: The COX2 expression in 85 resection specimens of pancreatic ductal adenocarcinoma was immunohistochemically examined using both monoclonal and polyclonal antibodies. The final immunoscores were obtained by multiplying the percentage of positive cells with the numeric score reflecting the staining intensity.COX2 expressi...
Forkapic, S; Maletić, D; Vasin, J; Bikit, K; Mrdja, D; Bikit, I; Udovičić, V; Banjanac, R
2017-01-01
The most dominant source of indoor radon is the underlying soil, so the enhanced levels of radon are usually expected in mountain regions and geology units with high radium and uranium content in surface soils. Laboratory for radioactivity and dose measurement, Faculty of Sciences, University of Novi Sad has rich databases of natural radionuclides concentrations in Vojvodina soil and also of indoor radon concentrations for the region of Vojvodina, Northern Province of Serbia. In this paper we present the results of correlative and multivariate analysis of these results and soil characteristics in order to estimate the geogenic radon potential. The correlative and multivariate analysis were done using Toolkit for Multivariate Analysis software package TMVA package, within ROOT analysis framework, which uses several comparable multivariate methods for our analysis. The evaluation ranking results based on the best signal efficiency and purity, show that the Boosted Decision Trees (BDT) and Multi Layer Preceptor (MLP), based on Artificial Neural Network (ANN), are multivariate methods which give the best results in the analysis. The BDTG multivariate method shows that variables with the highest importance are radio-nuclides activity on 30 cm depth. Moreover, the multivariate regression methods give a good approximation of indoor radon activity using full set of input variables. On several locations in the city of Novi Sad the results of indoor radon concentrations, radon emanation from soil, gamma spectrometry measurements of underlying soil and geology characteristics of soil were analyzed in detail in order to verify previously obtained correlations for Vojvodina soil. Copyright Â© 2016 Elsevier Ltd. All rights reserved.
Cao, Guangxi; He, Cuiting; Xu, Wei
2016-03-01
This study investigates the correlation between weather and agricultural futures markets on the basis of detrended cross-correlation analysis (DCCA) cross-correlation coefficients and q-dependent cross-correlation coefficients. In addition, detrended fluctuation analysis (DFA) is used to measure extreme weather and thus analyze further the effect of this condition on agricultural futures markets. Cross-correlation exists between weather and agricultural futures markets on certain time scales. There are some correlations between temperature and soybean return associated with medium amplitudes. Under extreme weather conditions, weather exerts different influences on different agricultural products; for instance, soybean return is greatly influenced by temperature, and weather variables exhibit no effect on corn return. Based on the detrending moving-average cross-correlation analysis (DMCA) coefficient and DFA regression results are similar to that of DCCA coefficient.
Tam, Roger C; Traboulsee, Anthony; Riddehough, Andrew; Li, David K B
2012-01-01
The change in T 1-hypointense lesion ("black hole") volume is an important marker of pathological progression in multiple sclerosis (MS). Black hole boundaries often have low contrast and are difficult to determine accurately and most (semi-)automated segmentation methods first compute the T 2-hyperintense lesions, which are a superset of the black holes and are typically more distinct, to form a search space for the T 1w lesions. Two main potential sources of measurement noise in longitudinal black hole volume computation are partial volume and variability in the T 2w lesion segmentation. A paired analysis approach is proposed herein that uses registration to equalize partial volume and lesion mask processing to combine T 2w lesion segmentations across time. The scans of 247 MS patients are used to compare a selected black hole computation method with an enhanced version incorporating paired analysis, using rank correlation to a clinical variable (MS functional composite) as the primary outcome measure. The comparison is done at nine different levels of intensity as a previous study suggests that darker black holes may yield stronger correlations. The results demonstrate that paired analysis can strongly improve longitudinal correlation (from -0.148 to -0.303 in this sample) and may produce segmentations that are more sensitive to clinically relevant changes.
Correlation of Descriptive Analysis and Instrumental Puncture Testing of Watermelon Cultivars.
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.
Correlation of coal basins in north Japan by frequency analysis of well logging data
Energy Technology Data Exchange (ETDEWEB)
Hiroshi Oda [National Institute of Advanced Industrial Science and Technology (AIST), Ibaraki (Japan). Institute for Geo-Resources and Environment
2005-07-01
Some recent developments in the use of well logs to recognize the earth's orbital cycles within the Milankovitch band are described. Milankovitch orbital cycles are revealed by time series analysis of conventional well logs. Time series analysis reveals cyclic events whilst episodic events are not revealed. Cyclostratigraphy, therefore represents a method to recognize the results in the sedimentary record of orbital climate forcing sedimentary processes which may be further used as a near synchronous correlation tool across sedimentary basins. By contrast, Exxon's third order depositional sequences are not necessarily periodic and although they are considered to represent the results of rhythmicity in sea levels in the range of the half a million to upwards of 5 million years, their use could make correlation problematic and non-synchronous. The spectral analysis of the gamma ray log over the Miocene section of the MITI Sanriku-Oki borehole offshore Hachinohe City, northeast Japan reveals well defined Milankovitch cycles in the log response of the sedimentary succession. Two spectral attributes can be generated from the power spectrum (a spectral change attribute called PEFA in this work and a spectral trend attribute -INPEFA) and used to generate near synchronous basin wide correlation. These observations and further work may represent powerful tools for prospect generation activity as the curves derived better relate geophysical well logs recorded in depth to the seismic record.
Directory of Open Access Journals (Sweden)
Mehdi Soltani Hoveize
2016-09-01
Full Text Available The efficiency of a breeding program depends mainly on the direction of the correlation between yield and its components and the relative importance of each component involved in contributing to seed yield. This study was conducted to analysis the correlation among seed yield and some important traits in seventhin spring canola (Brassica napus L. cultivars at the farm in safi abad, from 2014 to 2015. A randomized complete block design with four replications was used. Results analysis of variance showed that highly significant differences were detected among cultivars for all studied traits. The correlation coefficients among the seed yield and 1000-seed weight, number of seed per pod, duration of flowering, and days to physiological maturity were positive and significant (0.61**, 0.72**, 0.66** and 0.65**, respectively. According to stepwise regression seed yield trait is cosidered by dependent variable and other traits by independent variables. Model determination coefficient is R2=0.897. The most of determination coefficients there were for duration of flowering, number of seed per pod and days to physiological maturity (0.51, 0.54 and 0.38, respectively. Path coefficient analysis revealed that the number of seed per pod, duration of flowering and days to physiological maturity had the largest direct effects on the seed yield, its seams possible to use there traits as a selection criteria in breeding programs for improve seed yield of spring rapeseed cultivars.
Performance analysis of EGC combining over correlated Nakagami-m fading channels
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Milić Dejan
2012-01-01
Full Text Available In this paper, performance analysis of diversity technique with equal gain combining method (EGC with two branches for the detection of signals in wireless communication systems is presented. In the following analysis, it is assumed that the fading via channels is Nakagami-m correlated. The first order statistical characteristics of the system are analysed. Useful formulae for the probability density function (pdf and cumulative distribution function (CDF of EGC output SIR are derived, and the effects of the fading severity on the output signal are observed.
Energy Technology Data Exchange (ETDEWEB)
Camus, E. (Hahn-Meitner-Institut Berlin GmbH (Germany)); Abromeit, C. (Hahn-Meitner-Institut Berlin GmbH (Germany))
1994-05-01
A statistical analysis of atom probe data is developed for evaluating the evolution of local composition fluctuations in concentrated alloys. The model allows the calculation of theoretical correlation and contingency coefficients for a presumed alloy microstructure taking into account the instrumental parameters, i.e. aperture size, block size and detector efficiency. A comparison of theoretical coefficients with those obtained from measured concentration profiles gives access to physically relevant parameters. The analysis is applied to the diffusion-controlled dissolution of spherical precipitates in the technical alloy Nimonic PE16 under ion irradiation. (orig.)
Roine, J.; Tenho, M.; Murtomaa, M.; Lehto, V.-P.; Kansanaho, R.
2007-10-01
The present research experiments the applicability of x-ray texture analysis in investigating the properties of paper coatings. The preferred orientations of kaolin, talc, ground calcium carbonate, and precipitated calcium carbonate particles used in four different paper coatings were determined qualitatively based on the measured crystal orientation data. The extent of the orientation, namely, the degree of the texture of each pigment, was characterized quantitatively using a single parameter. As a result, the effect of paper calendering is clearly seen as an increase on the degree of texture of the coating pigments. The effect of calendering on the preferred orientation of kaolin was also evident in an independent energy dispersive spectrometer analysis on micrometer scale and an electron spectroscopy for chemical analysis on nanometer scale. Thus, the present work proves x-ray texture analysis to be a potential research tool for characterizing the properties of paper coating layers.
CALA:A Web Analysis Algorithm Combined with Content Correlation Analysis Method
Institute of Scientific and Technical Information of China (English)
ZHANG Ling(张岭); MA FanYuan(马范援); YE YunMing(叶允明); CHEN JianGuo(陈建国)
2003-01-01
Web hyperlink structure analysis algorithm plays a significant role in improving the precision of Web information retrieval. Current link algorithms employ iteration function to compute the Web resource weight. The major drawback of this approach is that every Web document has a fixed rank which is independent of Web queries. This paper proposes an improved algorithm that ranks the quality and the relevance of a page according to users' query dynamically.The experiments show that the current link analysis algorithm is improved.
Directory of Open Access Journals (Sweden)
Hladni Nada
2015-01-01
Full Text Available The most important criteria for introducing new confectionary hybrids into the production is high protein yield. Path coefficient analysis was used to obtain information on direct and indirect effects of studied traits (seed oil content, kernel oil content, seed yield, kernel protein content, mass of 1000 seeds, kernel ratio and hull ratio on protein yield. The research was conducted during three vegetation seasons, on 22 experimental confectionary sunflower hybrids created in the breeding program at the Institute of Field and Vegetable Crops. Strong and very strong correlations were found among the largest number of examined traits. A weak negative interdependence was determined between kernel oil content, kernel protein content, mass of 1000 seeds, hull ratio, and protein yield using the analysis of simple correlation coefficients. Positive but weak correlation was determined between protein yield and seed oil content, and kernel ratio. Very strong positive correlation was determined between protein yield and seed yield (0.468**. The seed oil content had a very strong direct negative effect on protein yield (DE=-0.734**. The mass of 1000 seeds had a weak negative direct effect on protein yield. Kernel protein content and kernel oil content demonstrated a weak direct positive effect on protein yield. Path coefficient analysis of protein yield showed a very strong positive direct effect of kernel ratio (DE=1.340**, seed yield (DE=0.657** and hull ratio (DE=0.992*. These findings confirm the effect of seed yield, kernel ratio, and hull ratio on protein yield, and their importance as the selection criteria in confectionary sunflower breeding. [Projekat Ministarstva nauke Republike Srbije, br. 31025: Development of new varieties and production technology improvement of oil crops for different purposes
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
Study on soil water characteristics of tobacco fields based on canonical correlation analysis
Directory of Open Access Journals (Sweden)
Xiao-hou SHAO
2009-06-01
Full Text Available In order to identify the principal factors influencing soil water characteristics (SWC and evaluate SWC effectively, the multivariate-statistical canonical correlation analysis (CCA method was used to study and analyze the correlation between SWC and soil physical and chemical properties. Twenty-two soil samples were taken from 11 main tobacco-growing areas in Guizhou Province in China and the soil water characteristic curves (SWCC and basic physical and chemical properties of the soil samples were determined. The results show that: (1 The soil bulk density, soil total porosity and soil capillary porosity have significant effects on SWC of tobacco fiels. Bulk density and total porosity are positively correlated with soil water retention characteristics (SWRC, and soil capillary porosity is positively correlated with soil water supply characteristics (SWSC. (2 Soil samples from different soil layers at the same soil sampling point show similarity or consistency in SWC. Inadequate soil water supply capability and imbalance between SWRC and SWSC are problems of tobacco soil. (3 The SWC of loamy clay are generally superior to those of silty clay loam.
Lagged Poincar\\'{e} and auto-correlation analysis of Heart rate variability in diabetes
Ghatak, S K
2010-01-01
The heart rate variability (HRV) in diabetic human subjects, has been analyzed using lagged Poincar\\'{e} plot, auto-correlation and the detrended fluctuation analysis methods. The parameters $SD1$, and $SD12 (= SD1/SD2)$ for Poincar\\'{e} plot for diabetic are lower than that for non-diabetic subjects and reverse is case for $SD2$ for all lagged number (m). The slope and the curvature of the plot SD12 vs m is much reduced for diabetic subject. The scatter plot of two successive interbeat intervals points out smaller variability in diabetic heart. The detrended fluctuation exponent has a higher value for diabetic group. The auto-correlation function of the deviation of interbeat interval in diabetic group shows highly correlated pattern when compared to that of normal one. The study suggests that the curvature of $SD12$ and auto-correlation method appear to be better way to assess the alteration of regulatory system on heart dynamics in diabetic condition.
Orion MPCV Service Module Avionics Ring Pallet Testing, Correlation, and Analysis
Staab, Lucas; Akers, James; Suarez, Vicente; Jones, Trevor
2012-01-01
The NASA Orion Multi-Purpose Crew Vehicle (MPCV) is being designed to replace the Space Shuttle as the main manned spacecraft for the agency. Based on the predicted environments in the Service Module avionics ring, an isolation system was deemed necessary to protect the avionics packages carried by the spacecraft. Impact, sinusoidal, and random vibration testing were conducted on a prototype Orion Service Module avionics pallet in March 2010 at the NASA Glenn Research Center Structural Dynamics Laboratory (SDL). The pallet design utilized wire rope isolators to reduce the vibration levels seen by the avionics packages. The current pallet design utilizes the same wire rope isolators (M6-120-10) that were tested in March 2010. In an effort to save cost and schedule, the Finite Element Models of the prototype pallet tested in March 2010 were correlated. Frequency Response Function (FRF) comparisons, mode shape and frequency were all part of the correlation process. The non-linear behavior and the modeling the wire rope isolators proved to be the most difficult part of the correlation process. The correlated models of the wire rope isolators were taken from the prototype design and integrated into the current design for future frequency response analysis and component environment specification.
Study on soil water characteristics of tobacco fields based on canonical correlation analysis
Institute of Scientific and Technical Information of China (English)
Xiao-hou SHAO; Yu WANG; Li-dong BI; You-bo YUAN; Xian-kun SU; Jian-guo MO
2009-01-01
In order to identify the principal factors influencing soil water characteristics (SWC) and evaluate SWC effectively, the multivariate-statistical canonical correlation analysis (CCA) method was used to study and analyze the correlation between SWC and soil physical and chemical properties. Twenty-two soil samples were taken from 11 main tobacco-growing areas in Guizhou Province in China and the soil water characteristic curves (SWCC) and basic physical and chemical properties of the soil samples were determined. The results show that: (1) The soil bulk density, soil total porosity and soil capillary porosity have significant effects on SWC of tobacco fiels. Bulk density and total porosity are positively correlated with soil water retention characteristics (SWRC), and soil capillary porosity is positively correlated with soil water supply characteristics (SWSC). (2) Soil samples from different soil layers at the same soil sampling point show similarity or consistency in SWC. Inadequate soil water supply capability and imbalance between SWRC and SWSC are problems of tobacco soil. (3) The SWC of loamy clay are generally superior to those of silty clay loam.
Munsamy, Alvin Jeffrey; Moodley, Vanessa Racquel
2017-01-01
Background: Knowledge of the cone characteristics for the different stages of keratoconus may potentially assist practitioners in diagnosing and managing keratoconic patients. Aim: This study aims to determine if any correlation exists between the central keratometric readings and the cone characteristics for the different stages of keratoconus. Setting: A university eye clinic. Materials and Methods: In this retrospective study, a saturated sample of 190 eyes from 106 cases of previously diagnosed keratoconic patient files was analyzed. The stage of keratoconus and cone characteristics, namely, cone location, cone decentration, topographical patterns, and morphology were analyzed using an Oculus 3M corneal topographer. Results: Analysis revealed a correlation between cone decentration and stage of keratoconus (P = 0.007). The association was found to exist when central K-readings were between 45D and 52D and with an apical cone decentration of 3–4 mm. No correlations were obtained for the stage of keratoconus and the cone location; topography and morphology. Conclusion: It can be concluded that cone apices are not central in all stages. Practitioners should consider the peripheral cornea when diagnosing and managing keratoconic patients. No correlation between stage, morphology or topography was respectively revealed. PMID:28300733
Li, Jiang-Tao
2013-01-01
X-ray observations provide a key tool for exploring the properties of galactic coronae and their formation processes. In an earlier paper, we have presented a Chandra data analysis of the coronae of 53 nearby highly-inclined disc galaxies. Here we study the correlation of the X-ray measurements with other galaxy properties and compare the results with those obtained for elliptical galaxies. A good correlation is present between the coronal luminosity Lx and the SFR. But we find a better correlation between Lx and the total SN mechanical energy input rate (ESN), including the expected contribution from core collapsed (CC) and Ia SNe. The X-ray radiation efficiency (eta=Lx/ESN) has a mean value of ~0.4% with an rms of ~0.5dex. eta further correlates with MTF/M* (MTF is the baryon mass measured from the rotation velocity and the Tully-Fisher relation, M* is the stellar mass measured from the K-band luminosity) and the CC SN rate surface density (FSN, in units of SN/yr/kpc^2), which can be characterized as: eta=0...
Rahim-Taleghani, Sima; Fatemi, Alireza; Alavi Moghaddam, Mostafa; Shojaee, Majid; Abushouk, Abdelrahman Ibrahim; Forouzanfar, Mohammad Mehdi; Baratloo, Alireza
2017-03-01
This study was conducted to assess the correlation between central venous pressure (CVP) and venous blood gas (VBG) analysis parameters, to facilitate management of severe sepsis and septic shock in emergency department. This diagnostic study was conducted from January 2014 until June 2015 in three major educational medical centers, Tehran, Iran. For patients selected with diagnosis of septic shock, peripheral blood sample was taken for testing the VBG parameters and the anion gap (AG) was calculated. All the mentioned parameters were measured again after infusion of 500 cc of normal saline 0.9% in about 1 h. Totally, 93 patients with septic shock were enrolled, 63 male and 30 female. The mean age was 72.53 ± 13.03 and the mean Shock Index (SI) before fluid therapy was 0.79 ± 0.30. AG and pH showed significant negative correlations with CVP, While HCO3 showed a significant positive correlation with CVP. These relations can be affected by the treatment modalities used in shock management such as fluid therapy, mechanical ventilation and vasopressor treatment. It is likely that there is a significant statistical correlation between VBG parameters and AG with CVP, but further research is needed before implementation of the results of this study.
Motivational Basis of Personality Traits: A Meta-Analysis of Value-Personality Correlations.
Fischer, Ronald; Boer, Diana
2015-10-01
We investigated the relationships between personality traits and basic value dimensions. Furthermore, we developed novel country-level hypotheses predicting that contextual threat moderates value-personality trait relationships. We conducted a three-level v-known meta-analysis of correlations between Big Five traits and Schwartz's (1992) 10 values involving 9,935 participants from 14 countries. Variations in contextual threat (measured as resource threat, ecological threat, and restrictive social institutions) were used as country-level moderator variables. We found systematic relationships between Big Five traits and human values that varied across contexts. Overall, correlations between Openness traits and the Conservation value dimension and Agreeableness traits and the Transcendence value dimension were strongest across all samples. Correlations between values and all personality traits (except Extraversion) were weaker in contexts with greater financial, ecological, and social threats. In contrast, stronger personality-value links are typically found in contexts with low financial and ecological threats and more democratic institutions and permissive social context. These effects explained on average more than 10% of the variability in value-personality correlations. Our results provide strong support for systematic linkages between personality and broad value dimensions, but they also point out that these relations are shaped by contextual factors.
Directory of Open Access Journals (Sweden)
J. Florian Wellmann
2013-04-01
Full Text Available The quantification and analysis of uncertainties is important in all cases where maps and models of uncertain properties are the basis for further decisions. Once these uncertainties are identified, the logical next step is to determine how they can be reduced. Information theory provides a framework for the analysis of spatial uncertainties when different subregions are considered as random variables. In the work presented here, joint entropy, conditional entropy, and mutual information are applied for a detailed analysis of spatial uncertainty correlations. The aim is to determine (i which areas in a spatial analysis share information, and (ii where, and by how much, additional information would reduce uncertainties. As an illustration, a typical geological example is evaluated: the case of a subsurface layer with uncertain depth, shape and thickness. Mutual information and multivariate conditional entropies are determined based on multiple simulated model realisations. Even for this simple case, the measures not only provide a clear picture of uncertainties and their correlations but also give detailed insights into the potential reduction of uncertainties at each position, given additional information at a different location. The methods are directly applicable to other types of spatial uncertainty evaluations, especially where multiple realisations of a model simulation are analysed. In summary, the application of information theoretic measures opens up the path to a better understanding of spatial uncertainties, and their relationship to information and prior knowledge, for cases where uncertain property distributions are spatially analysed and visualised in maps and models.
Hasanzadeh, Hadi; Mokhtari-Dizaji, Manijhe; Bathaie, S Zahra; Hassan, Zuhair M
2010-06-01
Currently several therapeutic applications of ultrasound in cancer treatment are under progress which uses cavitation phenomena to deliver their effects. There are several methods to evaluate cavitation activity such as chemical dosimetry and measurement of subharmonic signals. In this study, the cavitation activity induced by the ultrasound irradiation on exposure parameters has been measured by terephthalic acid chemical dosimetry and subharmonic analysis. Experiments were performed in the near 1 MHz fields in the progressive wave mode and effect of duty cycles changes with 2 W/cm(2) intensity (I(SATA)) and acoustic intensity changes in continuous mode on both fluorescence intensity and subharmonic intensity were measured. The dependence between fluorescence intensity of terephthalic acid chemical dosimetry and subharmonic intensity analysis were analyzed by Pearson correlation (p-value subharmonic intensity and the fluorescence intensity for continuous mode is higher than for pulsing mode (p-value subharmonic intensity and the fluorescence intensity with sonication intensity (p-value subharmonic intensity at different duty cycles (R=0.997, p-value subharmonic intensity (microW/cm(2)) significantly correlated with the fluorescence intensity (count) (R=0.901; psubharmonic intensity due to subharmonic spectrum analysis. It is concluded that there is dependence between terephthalic acid chemical dosimetry and subharmonic spectrum analysis to examine the acoustic cavitation activity.
Pet Bottle Design, Correlation Analysis Of Pet Bottle Characteristics Subjective Judgment
Directory of Open Access Journals (Sweden)
Darko Avramović
2012-06-01
Full Text Available Ability to predict consumer’s reaction to particular design solution of the product is very important. Gathering andanalysis of subjective judgments of particular characteristics, based on which the aesthetic of the product is judged,is one of predicting the consumer’s reaction in the future. Knowledge gathered this manner can serve as a referencefor further studies of determining factors for aesthetic results and design quality. There are two opposed opinionsregarding prediction of aesthetic impression. One opinion is that taste of individual cannot be discussed because itis extremely variable and the possibility of meaningful analysis of aesthetic impression is rejected. Other opinionstates that there is a consistent preference of certain aesthetic characteristics despite individual and group differences.Main goal of this paper is to examine the correlation between subjective judgments of certain PET bottlecharacteristics. Analysis showed meaningful correlation between some of the PET bottle characteristics while othercharacteristics showed less correlation. It can be concluded that not all of the characteristics have the same influenceon the aesthetics and design quality of the PET bottle form. Emphasizing the characteristics relative to aesthetics ofthe product can produce better market results, taking in to account that consumer’s buy the product they consider tobe more attractive if other parameters of the product are similar.
Djupsjöbacka, Mats; Domkin, Dmitry
2005-01-01
In order to plan and control movements the central nervous system (CNS) needs to continuously keep track of the state of the musculoskeletal system. Therefore the CNS constantly uses sensory input from mechanoreceptors in muscles, joints and skin to update information about body configuration on different levels of the CNS. On the conscious level, such representations constitute proprioception. Different tests for assessment of proprioceptive acuity have been described. However, it is unclear if the proprioceptive acuity measurements in these tests correlate within subjects. By using both uni- and multivariate analysis we compared proprioceptive acuity in different variants of ipsilateral active and passive limb position-matching and ipsilateral passive limb movement velocity-discrimination in a group of healthy subjects. The analysis of the position-matching data revealed a higher acuity of matching for active movements in comparison to passive ones. The acuity of matching was negatively correlated to movement extent. There was a lack of correlation between proprioceptive acuity measurements in position-matching and velocity-discrimination.
Correlation Study and Regression Analysis of Drinking Water Quality in Kashan City, Iran
Directory of Open Access Journals (Sweden)
Mohammad Mehdi HEYDARI
2013-06-01
Full Text Available Chemical and statistical regression analysis on drinking water samples at five fields (21 sampling wells with hot and dry climate in Kashan city, central Iran was carried out. Samples were collected during October 2006 to May 2007 (25 - 30 °C. Comparing the results with drinking water quality standards issued by World Health Organization (WHO, it is found that some of the water samples are not potable. Hydrochemical facies using a Piper diagram indicate that in most parts of the city, the chemical character of water is dominated by NaCl. All samples showed sulfate and sodium ion higher and K+ and F- content lower than the permissible limit. A strongly positive correlation is observed between TDS and EC (R = 0.995 and Ca2+ and TH (R = 0.948. The results showed that regression relations have the same correlation coefficients: (I pH -TH, EC -TH (R = 0.520, (II NO3- -pH, TH-pH (R = 0.520, (III Ca2+-SO42-, TH-SO42-, Cl- -SO42- (R = 0.630. The results revealed that systematic calculations of correlation coefficients between water parameters and regression analysis provide a useful means for rapid monitoring of water quality.
Confirmatory factor analysis and job burnout correlates of the Health Professions Stress Inventory.
Akhtar, Syed; Lee, Jenny S Y
2002-02-01
Previous research in 1994 by Gupchup and Wolfgang identified four factors from Wolfgang's Health Professions Stress Inventory (1988) that were common among a sample of practicing pharmacists. The factors were labeled Professional Recognition. Patient Care Responsibilities, Job Conflicts, and Professional Uncertainty, respectively. We used confirmatory factor analysis to assess whether this factor structure was generalizable to nurses. To examine concurrent validity, we correlated the factors with Maslach and Jackson's three dimensions of job burnout, i.e., Emotional Exhaustion, Depersonalization, and Personal Accomplishment. Data were collected through a questionnaire survey of a random sample of 9,380 nurses from across 43 public hospitals in Hong Kong, from which 2,267 (24.2%) responded. Analysis indicated statistically acceptable goodness of fit indices for the four-factor solution. Except for the factor Patient Care Responsibilities. all other factors had moderate correlations between .44 and .53 with Emotional Exhaustion and Depersonalization. Correlations between the factors of Stress Inventory and Personal Accomplishment were small but significant, ranging from -.25 to .13. Areas for further improving the psychometric properties of the inventory are discussed.
Directory of Open Access Journals (Sweden)
Xun Chen
2013-01-01
Full Text Available Corticomuscular activity modeling based on multiple data sets such as electroencephalography (EEG and electromyography (EMG signals provides a useful tool for understanding human motor control systems. In this paper, we propose modeling corticomuscular activity by combining partial least squares (PLS and canonical correlation analysis (CCA. The proposed method takes advantage of both PLS and CCA to ensure that the extracted components are maximally correlated across two data sets and meanwhile can well explain the information within each data set. This complementary combination generalizes the statistical assumptions beyond both PLS and CCA methods. Simulations were performed to illustrate the performance of the proposed method. We also applied the proposed method to concurrent EEG and EMG data collected in a Parkinson’s disease (PD study. The results reveal several highly correlated temporal patterns between EEG and EMG signals and indicate meaningful corresponding spatial activation patterns. In PD subjects, enhanced connections between occipital region and other regions are noted, which is consistent with previous medical knowledge. The proposed framework is a promising technique for performing multisubject and bimodal data analysis.
Desdouits, Nathan; Nilges, Michael; Blondel, Arnaud
2015-02-01
Protein conformation has been recognized as the key feature determining biological function, as it determines the position of the essential groups specifically interacting with substrates. Hence, the shape of the cavities or grooves at the protein surface appears to drive those functions. However, only a few studies describe the geometrical evolution of protein cavities during molecular dynamics simulations (MD), usually with a crude representation. To unveil the dynamics of cavity geometry evolution, we developed an approach combining cavity detection and Principal Component Analysis (PCA). This approach was applied to four systems subjected to MD (lysozyme, sperm whale myoglobin, Dengue envelope protein and EF-CaM complex). PCA on cavities allows us to perform efficient analysis and classification of the geometry diversity explored by a cavity. Additionally, it reveals correlations between the evolutions of the cavities and structures, and can even suggest how to modify the protein conformation to induce a given cavity geometry. It also helps to perform fast and consensual clustering of conformations according to cavity geometry. Finally, using this approach, we show that both carbon monoxide (CO) location and transfer among the different xenon sites of myoglobin are correlated with few cavity evolution modes of high amplitude. This correlation illustrates the link between ligand diffusion and the dynamic network of internal cavities.
Detrended Fluctuation Analysis on Correlations of Complex Networks Under Attack and Repair Strategy
Institute of Scientific and Technical Information of China (English)
无
2006-01-01
We analyze the correlation properties of the Erdos-Rényi random graph (RG) and the Barabási-Albert scale-free network (SF) under the attack and repair strategy with detrended fluctuation analysis (DFA). The maximum degree k representing the local property of the system, shows similar scaling behaviors for random graphs and scale-free networks. The fluctuations are quite random at short time scales but display strong anticorrelation at longer time scales under the same system size N and different repair probability pre. The average degree , revealing the statistical property of the system, exhibits completely different scaling behaviors for random graphs and scale-free networks. Random graphs display long-range power-law correlations. Scale-free networks are uncorrelated at short time scales; while anticorrelated at longer time scales and the anticorrelation becoming stronger with the increase of pre.
Detecting Distributed Network Traffic Anomaly with Network-Wide Correlation Analysis
Zonglin, Li; Guangmin, Hu; Xingmiao, Yao; Dan, Yang
2008-12-01
Distributed network traffic anomaly refers to a traffic abnormal behavior involving many links of a network and caused by the same source (e.g., DDoS attack, worm propagation). The anomaly transiting in a single link might be unnoticeable and hard to detect, while the anomalous aggregation from many links can be prevailing, and does more harm to the networks. Aiming at the similar features of distributed traffic anomaly on many links, this paper proposes a network-wide detection method by performing anomalous correlation analysis of traffic signals' instantaneous parameters. In our method, traffic signals' instantaneous parameters are firstly computed, and their network-wide anomalous space is then extracted via traffic prediction. Finally, an anomaly is detected by a global correlation coefficient of anomalous space. Our evaluation using Abilene traffic traces demonstrates the excellent performance of this approach for distributed traffic anomaly detection.
Directory of Open Access Journals (Sweden)
S.M. Badwai
2013-01-01
Full Text Available the key point of super resolution process is the accurate measuring of sub-pixel shift. Any tiny error in measuring such shift leads to an incorrect image focusing. In this paper, methodology of measuring sub-pixel shift using Phase correlation (PC are evaluated using different window functions, then modified version of (PC method using high pass filter (HPF is introduced . Comprehensive analysis and assessment of (PC methods shows that different natural features yield different shift measurements. It is concluded that there is no universal window function for measuring shift; it mainly depends on the features in the satellite images. Even the question of which window is optimal of particular feature is generally remains open. This paper presents the design of a method for obtaining high accuracy sub pixel shift phase correlation using (HPF.The proposed method makes the change in the different locations that lack of edges easy.
Directory of Open Access Journals (Sweden)
Charlene C Lew
2006-03-01
Full Text Available This study investigated the relationships between the scales of the Adult Career Concerns Inventory (ACCI and those of the Career Attitudes and Strategies Inventory (CASI. The scores of 202 South African adults for the two inventories were subjected to a canonical correlation analysis. Two canonical variates made statistically significant contributions to the explanation of the relationships between the two sets of variables. Inspection of the correlations of the original variables with the first canonical variate suggested that a high level of career concerns in general, as measured by the ACCI, is associated with high levels of career worries, more geographical barriers, a low risk-taking style and a non-dominant interpersonal style, as measured by the CASI. The second canonical variate suggested that concerns with career exploration and advancement of one’s career is associated with low job satisfaction, low family commitment, high work involvement, and a dominant style at work.
Analysis of correlation functions in Toda theory and AGT-W relation for SU(3) quiver
Kanno, Shoichi; Shiba, Shotaro
2010-01-01
We give some evidences of the AGT-W 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 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 SU(3)xSU(2) case and we comment on some technical issues which need clarification before establishing the relation.
Blind Identification of SIMO Wiener Systems Based on Kernel Canonical Correlation Analysis
Van Vaerenbergh, Steven; Via, Javier; Santamaria, Ignacio
2013-05-01
We consider the problem of blind identification and equalization of single-input multiple-output (SIMO) nonlinear channels. Specifically, the nonlinear model consists of multiple single-channel Wiener systems that are excited by a common input signal. The proposed approach is based on a well-known blind identification technique for linear SIMO systems. By transforming the output signals into a reproducing kernel Hilbert space (RKHS), a linear identification problem is obtained, which we propose to solve through an iterative procedure that alternates between canonical correlation analysis (CCA) to estimate the linear parts, and kernel canonical correlation (KCCA) to estimate the memoryless nonlinearities. The proposed algorithm is able to operate on systems with as few as two output channels, on relatively small data sets and on colored signals. Simulations are included to demonstrate the effectiveness of the proposed technique.
Analysis of Inter-Domain Traffic Correlations: Random Matrix Theory Approach
Rojkova, Viktoria
2007-01-01
The traffic behavior of University of Louisville network with the interconnected backbone routers and the number of Virtual Local Area Network (VLAN) subnets is investigated using the Random Matrix Theory (RMT) approach. We employ the system of equal interval time series of traffic counts at all router to router and router to subnet connections as a representation of the inter-VLAN traffic. The cross-correlation matrix C of the traffic rate changes between different traffic time series is calculated and tested against null-hypothesis of random interactions. The majority of the eigenvalues \\lambda_{i} of matrix C fall within the bounds predicted by the RMT for the eigenvalues of random correlation matrices. The distribution of eigenvalues and eigenvectors outside of the RMT bounds displays prominent and systematic deviations from the RMT predictions. Moreover, these deviations are stable in time. The method we use provides a unique possibility to accomplish three concurrent tasks of traffic analysis. The metho...
Automatic Contrast Enhancement of Brain MR Images Using Hierarchical Correlation Histogram Analysis.
Chen, Chiao-Min; Chen, Chih-Cheng; Wu, Ming-Chi; Horng, Gwoboa; Wu, Hsien-Chu; Hsueh, Shih-Hua; Ho, His-Yun
Parkinson's disease is a progressive neurodegenerative disorder that has a higher probability of occurrence in middle-aged and older adults than in the young. With the use of a computer-aided diagnosis (CAD) system, abnormal cell regions can be identified, and this identification can help medical personnel to evaluate the chance of disease. This study proposes a hierarchical correlation histogram analysis based on the grayscale distribution degree of pixel intensity by constructing a correlation histogram, that can improves the adaptive contrast enhancement for specific objects. The proposed method produces significant results during contrast enhancement preprocessing and facilitates subsequent CAD processes, thereby reducing recognition time and improving accuracy. The experimental results show that the proposed method is superior to existing methods by using two estimation image quantitative methods of PSNR and average gradient values. Furthermore, the edge information pertaining to specific cells can effectively increase the accuracy of the results.
Detecting Distributed Network Traffic Anomaly with Network-Wide Correlation Analysis
Directory of Open Access Journals (Sweden)
Yang Dan
2008-12-01
Full Text Available Distributed network traffic anomaly refers to a traffic abnormal behavior involving many links of a network and caused by the same source (e.g., DDoS attack, worm propagation. The anomaly transiting in a single link might be unnoticeable and hard to detect, while the anomalous aggregation from many links can be prevailing, and does more harm to the networks. Aiming at the similar features of distributed traffic anomaly on many links, this paper proposes a network-wide detection method by performing anomalous correlation analysis of traffic signals' instantaneous parameters. In our method, traffic signals' instantaneous parameters are firstly computed, and their network-wide anomalous space is then extracted via traffic prediction. Finally, an anomaly is detected by a global correlation coefficient of anomalous space. Our evaluation using Abilene traffic traces demonstrates the excellent performance of this approach for distributed traffic anomaly detection.
Peri-event cross-correlation over time for analysis of interactions in neuronal firing.
Paiva, António R C; Park, Il; Sanchez, Justin C; Príncipe, José C
2008-01-01
Several methods have been described in the literature to verify the presence of couplings between neurons in the brain. In this paper we introduce the peri-event cross-correlation over time (PECCOT) to describe the interaction among the two neurons as a function of the event onset. Instead of averaging over time, the PECCOT averages the cross-correlation over instances of the event. As a consequence, the PECCOT is able to characterize with high temporal resolution the interactions over time among neurons. To illustrate the method, the PECCOT is applied to a simulated dataset and for analysis of synchrony in recordings of a rat performing a go/no go behavioral lever press task. We verify the presence of synchrony before the lever press time and its suppression afterwards.
Structure and evolution of a European Parliament via a network and correlation analysis
Puccio, Elena; Piilo, Jyrki; Tumminello, Michele
2016-01-01
We present a study of the network of relationships among elected members of the Finnish parliament, based on a quantitative analysis of initiative co-signatures, and its evolution over 16 years. To understand the structure of the parliament, we constructed a statistically validated network of members, based on the similarity between the patterns of initiatives they signed. We looked for communities within the network and characterized them in terms of members' attributes, such as electoral district and party. To gain insight on the nested structure of communities, we constructed a hierarchical tree of members from the correlation matrix. Afterwards, we studied parliament dynamics yearly, with a focus on correlations within and between parties, by also distinguishing between government and opposition. Finally, we investigated the role played by specific individuals, at a local level. In particular, whether they act as proponents who gather consensus, or as signers. Our results provide a quantitative background...
Ding, Zhenyang; Yao, X Steve; Liu, Tiegen; Du, Yang; Liu, Kun; Han, Qun; Meng, Zhuo; Chen, Hongxin
2012-12-17
We present a novel method to achieve a space-resolved long- range vibration detection system based on the correlation analysis of the optical frequency-domain reflectometry (OFDR) signals. By performing two separate measurements of the vibrated and non-vibrated states on a test fiber, the vibration frequency and position of a vibration event can be obtained by analyzing the cross-correlation between beat signals of the vibrated and non-vibrated states in a spatial domain, where the beat signals are generated from interferences between local Rayleigh backscattering signals of the test fiber and local light oscillator. Using the proposed technique, we constructed a standard single-mode fiber based vibration sensor that can have a dynamic range of 12 km and a measurable vibration frequency up to 2 kHz with a spatial resolution of 5 m. Moreover, preliminarily investigation results of two vibration events located at different positions along the test fiber are also reported.
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Fabrizio Giannandrea
2009-02-01
Full Text Available The underlying reasons for the increasing occurrence of male reproductive diseases (MRD such as hypospadias, cryptorchidism, and testicular cancer (TC over the last decades are still unknown. It has been hypothesized that the risk of MRD is determined in utero and that pregnancy dietary intake could also affect MRD risk in the offspring. Various studies in animals reported that cocoa and theobromine, the main stimulant of cocoa, exert toxic effects on the testis, inducing testicular atrophy and impaired sperm quality. A correlation analysis was conducted to examine the possible role of cocoa consumption on the occurrence of selected MRD during the prenatal and early life period of cases. The incidence rates between 1998-2002 of TC in 18 countries obtained from Cancer Incidence in Five Continents were correlated with the average per-capita consumption of cocoa (kg/capita/year (FAOSTAT-Database in these countries from 1965 to 1980, i.e. the period corresponding to the early life of TC cases. In order to test the above correlation in the case of hypospadias, the mean prevalence at birth in 20 countries (1999-2003 with average per-capita consumption of cocoa in these countries in the same period corresponding to pregnancy were used. The consumption of cocoa in the period 1965–80, was most closely correlated with the incidence of TC in young adults (r=0.859; p<0.001. An analogous significant correlation was also observed between early cocoa consumption and the prevalence rates of hypospadias in the period 1999-2003 (r=0.760; p<0.001. Although the ecological approach used in this study cannot provide an answer on the causal relationship between consumption of cocoa in early life and TC and hypospadias, the results are suggestive and indicate the need of further analytic studies to investigate the role of individual exposure to cocoa, particularly during the prenatal and in early life of the patients.
Sudhir, G; Acharya, Shankar; K L, Kalra; Chahal, Rupinder
2016-03-01
Study Design Cross-sectional study. Objective Sacropelvic parameters in various spine and hip disorders have been published in various studies. We aimed to study the normal sacropelvic parameters and curvatures of the spine and their correlation in asymptomatic Indian adults in relation to variations in sex and age. Methods The study included 101 asymptomatic adults (50 men and 51 women with an average age of 47.16 and 48.59 years, respectively). For each subject, the thoracic kyphosis (TK), lumbar lordosis (LL), pelvic incidence (PI), pelvic tilt (PT), and sacral slope (SS) were measured from standing lateral radiographs. After stratification of the group by sex and age with a cutoff of 50 years, descriptive, correlation, and regression analysis were performed using SPSS software. Results The average PI, SS, PT, LL, and TK values were 55.48 (±5.31), 35.99 (±7.53), 17.97 (±7.16), 48.84 (±9.82), and 32.55 (±10.92), respectively. No statistically significant difference was observed in these values with regards to sex and age 50 years but the pelvic incidence was found to be higher in women. A positive correlation between the PI and SS and a negative correlation between the SS and PT was observed. A positive correlation between the TK and LL was found in subjects > 50 years. Simple and multiple regression analyses were also performed for different groups. Conclusion The current study is the first of asymptomatic Indian adults and provides invaluable information to the clinicians about the normal range of sacropelvic and spinopelvic parameters, which is useful to plan spinal deformity corrections and to evaluate pathologic conditions associated with abnormal angular values.
Stratigraphic Division and Correlation of the Nihewan Beds by Multivariate Statistical Analysis
Institute of Scientific and Technical Information of China (English)
岳军; 蒋明媚
1992-01-01
Described in paper is the principle of optimal partitioning method for stratigraphic division and correlation.The Nihewan Beds are taken for example to show how to apply this approach in stratigraphic division and correlation.The semiquantitative spectral analysis data on aggregate trace elements in 324 samples taken from the nine sections in the Nihewan Basin are treated with multivariate statistical method for stratigraphic division and correlation.First ,the data from all the sections are respectively calculated by the optimal partitioning method to establish the stratigraphic boundaries.The optimal partitioning method has proved itself to be applicable to stratigraphic division and correlation. In our practice the Nihewan Beds are divided into five zones (I-V).Zone I includes subzones Ia and Ib,Zones Ia,Ib,II and III are considered to be corresponding to the Pliocene(N2),the early Early Pleistocene,the late Early Pleistocene,and the Middle Pleistocene,respectively .Zones IV and V are probably Late Pleistocene in age.This indicated that sediments deposited con-temporaneous in the sections of the same basin are similar in geochemical characteristics,although dif-ferent in geographical location.However,the sediments also show some variations ,with a transitional relationship from one section to another .For example ,in Zone II,the sediments of the Xiaodukou section show not only the characteristics of the Nangou-Hongya and Hutouliang sections,but also those of the Xiashagou,Shixiaxi,Shixiadong and Wulitai sections.It can be seen from the above that the zones can be characteristically correlated with one another.In addition the feasibility of the optimal partitioning method is also described in the present paper.
Study on insomnia and sleep quality in adolescents and their correlation analysis
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Xian LUO
2017-09-01
Full Text Available Objective To investigate the correlation between insomnia and sleep quality in adolescents. Methods According to Insomnia Severity Index (ISI Chinese Version, 3342 students technician training in school were divided into non insomnia group (N = 2345 and insomnia group (N = 997. Sleep and emotional state were assessed by ISI Chinese Version, Pittsburgh Sleep Quality Index (PSQI, Epworth Sleepiness Scale (ESS, Self?Rating Anxiety Scale (SAS and Beck Depression Inventory (BDI. The social demographic data were collected simultaneously. Results The number of insomnia, daytime sleepiness, anxiety and depression in the population was 997 (29.83%, 568 (17.00%, 243 (7.27% and 1287 (38.51%, respectively. The comparison of social demographic data between 2 groups showed that the proportion of female (P = 0.000, poor physical condition (P = 0.000, non?only child (P = 0.006, high learning pressure (P = 0.000 and smoking (P = 0.027 in insomnia group were significantly higher than those in non insomnia group. The total scores of ISI Chinese Version (P = 0.000, ESS (P = 0.000, SAS (P = 0.000 and BDI (P = 0.000 in insomnia group were significantly higher than those in non insomnia group. Pearson correlation analysis showed that ISI Chinese Version and PSQI scores were positively correlated with ESS score (r = 0.361, P = 0.000; r = 0.064, P = 0.000, SAS score (r = 0.326, P = 0.000; r = 0.069, P = 0.000 and BDI score (r = 0.529, P = 0.000; r = 0.067, P = 0.000, and ISI Chinese Version had higher correlation (r = 0.300-0.600 with the above scores than PSQI (r < 0.100. Further partial correlation analysis showed that ISI Chinese Version score was negatively correlated with PSQI score (r = - 0.056, P = 0.001. Conclusions Higher proportion of female, worse physical condition, more non?only child, greater learning pressure and higher smoking rate were observed in insomnia group. Daytime sleepiness, anxiety and depression in insomnia group were more serious than those
Zhao, Zhihua; Zheng, Zhiqin; Roux, Clément; Delmas, Céline; Marty, Jean-Daniel; Kahn, Myrtil L; Mingotaud, Christophe
2016-08-22
Analysis of nanoparticle size through a simple 2D plot is proposed in order to extract the correlation between length and width in a collection or a mixture of anisotropic particles. Compared to the usual statistics on the length associated with a second and independent statistical analysis of the width, this simple plot easily points out the various types of nanoparticles and their (an)isotropy. For each class of nano-objects, the relationship between width and length (i.e., the strong or weak correlations between these two parameters) may suggest information concerning the nucleation/growth processes. It allows one to follow the effect on the shape and size distribution of physical or chemical processes such as simple ripening. Various electron microscopy pictures from the literature or from the authors' own syntheses are used as examples to demonstrate the efficiency and simplicity of the proposed 2D plot combined with a multivariate analysis.
A LFP-tree based method for association rules mining in telecommunication alarm correlation analysis
Institute of Scientific and Technical Information of China (English)
无
2007-01-01
The mining of association rules is one of the primary methods used in telecommunication alarm correlation analysis,of which the alarm databases are very large.The efficiency of the algorithms plays an important role in tackling with large datasets. The classical frequent pattern growth(FP-growth) algorithm can produce a large number of conditional pattern trees which made it difficult to mine association rules in are telecommunication environment.In this paper,an algorithm based on layered frequent pattern tree(LFP-tree) is proposed for mining frequent patterns. Efficiency of this alagorithm is achieved with following techniques:1) All the frequent patterns are condensed into a layered structure,which can save memory time but also be very useful for updating the alarm databases.2) Each alarm item can be viewed as a triple,in which t is a Boolean vaviable that shows the item frequent or not.3) Deleting infrequent items with dynamic pruning can avoid produce conditional pattern sets. Simulation and analysis of algorithm show that it is a valid method with better time and space efficiency,which is adapted to mine association rules in telecommunication alarm correlation analysis.
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Da-Hang Zhao
2014-01-01
Full Text Available We conducted a meta-analysis to comprehensively evaluate the correlations of ezrin expression with pathological characteristics and the prognosis of osteosarcoma. The MEDLINE (1966–2013, the Cochrane Library Database, EMBASE, CINAHL, Web of Science (1945–2013, and the Chinese Biomedical Database were searched without language restrictions. Meta-analyses conducted using STATA software were calculated. Ten studies met the inclusion criteria, including 459 patients with osteosarcoma. Meta-analysis results illustrated that ezrin expression may be closely associated with the recurrence of osteosarcoma or metastasis in osteosarcoma. Our findings also demonstrated that patients with grade III-IV osteosarcoma showed a higher frequency of ezrin expression than those with histological grade I-II osteosarcoma. Furthermore, we found that patients with positive expression of ezrin exhibited a shorter overall survival than those with negative ezrin expression. The results also indicated that positive ezrin expression was strongly correlated with poorer metastasis-free survival. Nevertheless, no significant relationships were observed between ezrin expression and clinical variables (age and gender. In the current meta-analysis, our results illustrated significant relationships of ezrin expression with pathological characteristics and prognosis of osteosarcoma. Thus, ezrin expression could be a promising marker in predicting the clinical outcome of patients with osteosarcoma.
Correlation between PON1 gene polymorphisms and breast cancer risk: a Meta-analysis.
Wen, Yayuan; Huang, Zemin; Zhang, Xiaohua; Gao, Bo; He, Yujun
2015-01-01
A number of studies have investigated the relationship between the PON1 gene polymorphisms and breast cancer risk, but the conclusions are not consistent. In this paper, a meta-analysis was conducted to explore the possible reasons for these inconsistencies, expecting to further clarify the correlation between PON1 gene polymorphisms and breast cancer risk. After searches in the database such as MEDLINE, EBSCO, ProQuest, Google Scholar, High-Wire, SID (Scientific Information Database) and PubMed, 7 literatures were collected. RevMan 5.2 software was used to perform the meta-analysis. Random-effects or fixed-effects model was used to analyze the odds ratio (OR) and 95% confidence intervals. The analysis of L55M single nucleotide polymorphisms (SNPs) showed that M allele frequency was positively correlated with the incidence risk of breast cancer (OR=1.34, 95% CI: 1.03-1.74). While we did not found Q192R polymorphism associated with the risk of breast cancer (OR=1.0, 95% CI: 0.71-1.42). For PON1 gene, the frequencies of M allele were associated with the incidence risk of breast cancer.
Gligor, M.; Ausloos, M.
2007-05-01
The statistical distances between countries, calculated for various moving average time windows, are mapped into the ultrametric subdominant space as in classical Minimal Spanning Tree methods. The Moving Average Minimal Length Path (MAMLP) algorithm allows a decoupling of fluctuations with respect to the mass center of the system from the movement of the mass center itself. A Hamiltonian representation given by a factor graph is used and plays the role of cost function. The present analysis pertains to 11 macroeconomic (ME) indicators, namely the GDP (x1), Final Consumption Expenditure (x2), Gross Capital Formation (x3), Net Exports (x4), Consumer Price Index (y1), Rates of Interest of the Central Banks (y2), Labour Force (z1), Unemployment (z2), GDP/hour worked (z3), GDP/capita (w1) and Gini coefficient (w2). The target group of countries is composed of 15 EU countries, data taken between 1995 and 2004. By two different methods (the Bipartite Factor Graph Analysis and the Correlation Matrix Eigensystem Analysis) it is found that the strongly correlated countries with respect to the macroeconomic indicators fluctuations can be partitioned into stable clusters.
Сomparative analysis of wind correlation lidar sounding range in UV, visible band and near IR bands
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S. E. Ivanov
2014-01-01
Full Text Available The paper presents a comparative analysis of the sounding range of wind correlation lidar in ultraviolet, visible, and near infrared spectral bands. It shows that a visible spectral band is the most advanced one to provide a maximum sounding range of wind correlation lidar in earth atmosphere. If there are specific requirements for wind correlation lidar, for example, a requirement is that a wind correlation lidar should operate at the eye-safe laser sounding wavelength then the efficient work of wind correlation lidar may be maintained in ultraviolet and near infrared spectral bands with the sounding range reduced a little bit.
Sviridov, Alexander P; Chernomordik, Victor; Hassan, Moinuddin; Boccara, Albert C; Russo, Angelo; Smith, Paul; Gandjbakhche, Amir
2005-01-01
The skin of athymic nude mice is irradiated with a single dose of x-ray irradiation that initiated fibrosis. Digital photographs of the irradiated mice are taken by illuminating the mouse skin with linearly polarized probe light of 650 nm. The specific pattern of the surface distribution of the degree of polarization enables the detection of initial skin fibrosis structures that were not visually apparent. Data processing of the raw spatial distributions of the degree of polarization based on Fourier filtering of the high-frequency noise improves subjective perception of the revealed structure in the images. In addition, Pearson correlation analysis provides information about skin structural size and directionality.
DEFF Research Database (Denmark)
Kinnebrock, Silja; Podolskij, Mark
This paper introduces a new estimator to measure the ex-post covariation between high-frequency financial time series under market microstructure noise. We provide an asymptotic limit theory (including feasible central limit theorems) for standard methods such as regression, correlation analysis...... and covariance, for which we obtain the optimal rate of convergence. We demonstrate some positive semidefinite estimators of the covariation and construct a positive semidefinite estimator of the conditional covariance matrix in the central limit theorem. Furthermore, we indicate how the assumptions on the noise...
DEFF Research Database (Denmark)
Kinnebrock, Silja; Podolskij, Mark
and covariance, for which we obtain the optimal rate of convergence. We demonstrate some positive semidefinite estimators of the covariation and construct a positive semidefinite estimator of the conditional covariance matrix in the central limit theorem. Furthermore, we indicate how the assumptions on the noise......This paper introduces a new estimator to measure the ex-post covariation between high-frequency financial time series under market microstructure noise. We provide an asymptotic limit theory (including feasible central limit theorems) for standard methods such as regression, correlation analysis...
Determination of Material for Shaft Design Using on Grey Correlation Analysis and TOPSIS Method
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B. Siva Kumar
2015-10-01
Full Text Available Machines, automobiles, aircrafts and many other applications have shaft as major mechanical component which must have a proper design, in-order to have the efficient transmission of power from one element to another. For the design of shaft an appropriate range of evaluation, general product form and processing methods for material must be made. The selection of material should be done by using multiple attribute decision methods (MADM. In this paper, Grey Correlation Analysis and TOPSIS Method is proposed in order to decide a suitable material by considering different attributes and graphical representations are made for different attributes verse materials and vice versa.
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Todić Jelena
2011-01-01
Full Text Available Background/Aim. Complex etiology and symptomatology of craniomandibular dysfunction make the diagnosing and therapy of this disorder more difficult. The aim of this work was to assess the value of clinical and instrumental functional analyses in diagnosing of this type of disorders. Methods. In this study 200 subjects were examined, 15 with temporomandibular joint disorder. They were subjected to clinical functional analysis (Fricton-Shiffman and instrumental functional analysis by using the method of gothic arch. The parameters of the gothic arch records were analyzed and subsequently compared among the subjects of the observed groups. Results. In the examined group of the population 7.5% of them were with craniomandibular dysfunction. The most frequent symptoms were sound in temporomandibular joint, painful sensitivity of the muscles on palpation and lateral turning of the lower jaw while opening the mouth. By analyzing the gothic arch records and comparing the obtained values between the observed groups it was assessed that: lateral and protrusion movements, lateral amplitude and the size of gothic arch were much bigger in the healthy subjects, and latero-lateral asymmetry was larger in the sick subjects. Latero-lateral dislocation of apex was recorded only in the sick subjects with average values of 0.22 ± 0.130 mm. The correlation between the values of Fricton-Shiffman craniomandibular index and the parameters of the gothic arch records and latero-lateral amplitude and dislocation of apex records were established by correlative statistical analysis. Conclusion. Functional analysis of orofacial system and instrumental analysis of lower jaw movements (gothic arch method can be recommended as precise and simple methods in diagnosing craniomandibular dysfunctions.
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.)
Böer, Tania Maria; Procópio, José Valdilânio Virgulino; Nascimento, Ticiano Gomes do; Macêdo, Rui Oliveira
2013-01-25
In recent years, thermal analysis has assumed major role in the pharmaceutical industry because it can be used to evaluate the stability both in the control of raw materials and the finished product, having employment potential in the development and characterization of new products and assessment processes. Tacrolimus (TCR) is a macrolide lactone with potent immunosuppressive activity. The purpose of this study was to characterize tacrolimus raw material using Thermal analysis and Pyrolysis coupled to Gas chromatography-Mass spectrometry (Pyr-GC-MS). It was analyzed four samples of tacrolimus named TCR A, B, C and D. Thermal analysis experiments was performed in Shimadzu equipment, under nitrogen and synthetic air atmosphere in different heating rate. Pyrolysis analysis was conducted in isothermal conditions of 300°C and 400°C coupled to GC-MS, in which the mass spectrometer was operated in scan mode to detect ions in the range of mass of m/z 25-900. The thermal studies by DSC, DTA and DSC-Photovisual showed desolvation process for all tacrolimus raw materials and TG-dynamical demonstrated two pseudo-polymorphic forms (monohydrate and sesquihydrate) of tacrolimus. It was observed good correlation between the stoichiometric mass losses of the TG-dynamical and identification of product ion in Pyr-GC/MS technique. It was possible to correlate the five pyrolytic product ions with the Ozawa kinetic analysis from the thermal decomposition of TG-dynamical. The thermal studies (DSC, DSC-Photovisual, DTA and TG-dynamical) were applied in the thermal characterization of the raw materials of tacrolimus which showed pseudo-polymorphic forms, which must be monitored by pharmaceutical industry, avoiding future problems in pharmaceutical process, chemical stability and bioavailability of the tacrolimus product.
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C. Stefanovic
2013-12-01
Full Text Available A very efficient technique that reduces fading and channel interference influence is selection diversity based on the signal to interference ratio (SIR. In this pa¬per, system performances of selection combiner (SC over correlated Nakagami-m channels with constant correlation model are analyzed. Closed-form expressions are obtained for the output SIR probability density function (PDF and cumulative distribution function (CDF which is main contribution of this paper. Outage probability and the average error probability for coherent, noncoherent modulation are derived. Numerical results presented in this paper point out the effects of fading severity and cor¬relation on the system performances. The main contribu¬tion of this analysis for multibranch signal combiner is that it has been done for general case of correlated co-channel interference (CCI.
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Felix Tobias Kurz
2016-12-01
Full Text Available In biological tissue, an accumulation of similarly shaped objects with a susceptibility difference to the surrounding tissue generates a local distortion of the external magnetic field in magnetic resonance imaging. It induces stochastic field fluctuations that characteristically influence proton spin diffusion in the vicinity of these magnetic perturbers. The magnetic field correlation that is associated with such local magnetic field inhomogeneities can be expressed in the form of a dynamic frequency autocorrelation function that is related to the time evolution of the measured magnetization. Here, an eigenfunction expansion for two simple magnetic perturber shapes, that of spheres and cylinders, is considered for restricted spin diffusion in a simple model geometry. Then, the concept of generalized moment analysis, an approximation technique that is applied in the study of (non-reactive processes that involve Brownian motion, allows to provide analytical expressions for the correlation function for different exponential decay forms. Results for the biexponential decay for both spherical and cylindrical magnetized objects are derived and compared with the frequently used (less accurate monoexponential decay forms. They are in asymptotic agreement with the numerically exact value of the correlation function for long and short times.
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Chengjing Nie
Full Text Available BACKGROUND: In the past decade, bacillary dysentery was still a big public health problem in China, especially in Guangxi Province, where thousands of severe diarrhea cases occur every year. METHODS: Reported bacillary dysentery cases in Guangxi Province were obtained from local Centers for Diseases Prevention and Control. The 14 socio-economic indexes were selected as potential explanatory variables for the study. The spatial correlation analysis was used to explore the associations between the selected factors and bacillary dysentery incidence at county level, which was based on the software of ArcGIS10.2 and GeoDA 0.9.5i. RESULTS: The proportion of primary industry, the proportion of younger than 5-year-old children in total population, the number of hospitals per thousand persons and the rates of bacillary dysentery incidence show statistically significant positive correlation. But the proportion of secondary industry, per capital GDP, per capital government revenue, rural population proportion, popularization rate of tap water in rural area, access rate to the sanitation toilets in rural, number of beds in hospitals per thousand persons, medical and technical personnel per thousand persons and the rate of bacillary dysentery incidence show statistically significant negative correlation. The socio-economic factors can be divided into four aspects, including economic development, health development, medical development and human own condition. The four aspects were not isolated from each other, but interacted with each other.
A meta-analysis of genetic correlations between plant resistances to multiple enemies.
Leimu, Roosa; Koricheva, Julia
2006-07-01
Genetic correlations between plant resistances to multiple natural enemies are important because they have the potential to determine the mode of selection that natural enemies impose on a host plant, the structure of herbivore and pathogen communities, and the success of plant breeding for resistance to multiple diseases and pests. We conducted a meta-analysis of 29 published studies of 16 different plant species reporting a total of 467 genetic correlations between resistances to multiple herbivores or pathogens. In general, genetic associations between resistances to multiple natural enemies tended to be positive regardless of the breeding design, type of attacker, and type of host plant. Positive genetic correlations between resistances were stronger when both attackers were pathogens or generalist herbivores and when resistance to different enemies was tested independently, suggesting that generalists may be affected by the same plant resistance traits and that interactions among natural enemies are common. Although the mean associations between resistances were positive, indicating the prevalence of diffuse selection and generalized defenses against multiple enemies, the large variation in both the strength and the direction of the associations suggests a continuum between pairwise and diffuse selection.
Correlation analysis between pulmonary function test parameters and CT image parameters of emphysema
Liu, Cheng-Pei; Li, Chia-Chen; Yu, Chong-Jen; Chang, Yeun-Chung; Wang, Cheng-Yi; Yu, Wen-Kuang; Chen, Chung-Ming
2016-03-01
Conventionally, diagnosis and severity classification of Chronic Obstructive Pulmonary Disease (COPD) are usually based on the pulmonary function tests (PFTs). To reduce the need of PFT for the diagnosis of COPD, this paper proposes a correlation model between the lung CT images and the crucial index of the PFT, FEV1/FVC, a severity index of COPD distinguishing a normal subject from a COPD patient. A new lung CT image index, Mirage Index (MI), has been developed to describe the severity of COPD primarily with emphysema disease. Unlike conventional Pixel Index (PI) which takes into account all voxels with HU values less than -950, the proposed approach modeled these voxels by different sizes of bullae balls and defines MI as a weighted sum of the percentages of the bullae balls of different size classes and locations in a lung. For evaluation of the efficacy of the proposed model, 45 emphysema subjects of different severity were involved in this study. In comparison with the conventional index, PI, the correlation between MI and FEV1/FVC is -0.75+/-0.08, which substantially outperforms the correlation between PI and FEV1/FVC, i.e., -0.63+/-0.11. Moreover, we have shown that the emphysematous lesion areas constituted by small bullae balls are basically irrelevant to FEV1/FVC. The statistical analysis and special case study results show that MI can offer better assessment in different analyses.
Speckle-correlation analysis of the dynamic scatterers in temperature-governed gelation
Zimnyakov, D. A.; Isaeva, A. A.; Isaeva, E. A.; Ushakova, O. V.
2016-04-01
This study focuses on the analysis of the temperature-dependent dynamics of scatterers in aqueous solutions of gelatin with added scattering centers (submicron particles of titanium dioxide), whose characterized by high scattering efficiency, during the process of gelation. The technique of full field speckle-correlometry with a localized source of probing radiation and the spatial filtering of the speckle-modulated images of the medium surface was applied to investigate systems with different values of the volume fraction of scatterers. It was shown that the Arrhenius equations with significantly different values of the activation energy can describe the temperature dependencies of the correlation time of speckle intensity fluctuations for temperature ranges above and below the gelation characteristic temperature. Note that the correlation time of speckle intensity fluctuations is determined by the mobility of the scattering centers in the medium. This suggests the existence of transition between two different regimes of spatially limited diffusion of scattering centers in the probed medium under the condition of "sol-gel" transition. The estimated values of activation energy of spatially limited scatter diffusion in the studied systems at low temperatures correlate with the published values of the gelation activation energy for gelatin aqueous solutions.
Oh, Jung Hue; Park, Ki Bum
2016-01-01
Background Thoracic epidural anesthesia is frequently used to maintain intraoperative and postoperative analgesia. Frequently, 3 ml of local anesthetic is used as a test dose, or for intermittent epidural injection. We assessed the extent of the spread of 3 ml of contrast medium in the thoracic epidural space and attempted to identify any correlating factors affecting the epidurography. Methods A total of 70 patients were enrolled in the study, and thoracic epidural catheterizations were performed under fluoroscopic guidance. Using 3 ml of contrast medium, epidurography was evaluated to confirm the number of spinal segments covered by the contrast medium. Correlation analysis was performed between patient characteristics (sex, age, body mass index, weight, height, and location of catheter tip) and the extent of the contrast spread. Results The mean number of vertebral segments evaluated by contrast medium was 7.9 ± 2.2 using 3 ml of contrast medium. The contrast spread in the cranial direction showed more extensive distribution than that in the caudal direction, with statistical significance (P spread, and patient height showed a weak negative correlation with the distribution of contrast medium.
Wang, Liang; Wu, Zheyang; Yang, Chun; Zheng, Jie; Bach, Richard; Muccigrosso, David; Billiar, Kristen; Maehara, Akiko; Mintz, Gary S; Tang, Dalin
2015-01-01
Atherosclerotic plaque progression is believed to be associated with mechanical stress conditions. Patient follow-up in vivo intravascular ultrasound coronary plaque data were acquired to construct fluid-structure interaction (FSI) models with cyclic bending to obtain flow wall shear stress (WSS), plaque wall stress (PWS) and strain (PWSn) data and investigate correlations between plaque progression measured by wall thickness increase (WTI), cap thickness increase (CTI), lipid depth increase (LDI) and risk factors including wall thickness (WT), WSS, PWS, and PWSn. Quarter average values (n = 178-1016) of morphological and mechanical factors from all slices were obtained for analysis. A predictive method was introduced to assess prediction accuracy of risk factors and identify the optimal predictor(s) for plaque progression. A combination of WT and PWS was identified as the best predictor for plaque progression measured by WTI. Plaque WT had best overall correlation with WTI (r = -0.7363, p WTI: (r = -0.3208, p < 1E-10); cap thickness: (r = 0.4541, p < 1E-10); CTI: (r = -0.1719, p = 0.0190); LD: (r = -0.2206, p < 1E-10); LDI: r = 0.1775, p < 0.0001). WSS had mixed correlation results.
Kurz, Felix; Kampf, Thomas; Buschle, Lukas; Schlemmer, Heinz-Peter; Bendszus, Martin; Heiland, Sabine; Ziener, Christian
2016-12-01
In biological tissue, an accumulation of similarly shaped objects with a susceptibility difference to the surrounding tissue generates a local distortion of the external magnetic field in magnetic resonance imaging. It induces stochastic field fluctuations that characteristically influence proton spin diffusion in the vicinity of these magnetic perturbers. The magnetic field correlation that is associated with such local magnetic field inhomogeneities can be expressed in the form of a dynamic frequency autocorrelation function that is related to the time evolution of the measured magnetization. Here, an eigenfunction expansion for two simple magnetic perturber shapes, that of spheres and cylinders, is considered for restricted spin diffusion in a simple model geometry. Then, the concept of generalized moment analysis, an approximation technique that is applied in the study of (non-)reactive processes that involve Brownian motion, allows to provide analytical expressions for the correlation function for different exponential decay forms. Results for the biexponential decay for both spherical and cylindrical magnetized objects are derived and compared with the frequently used (less accurate) monoexponential decay forms. They are in asymptotic agreement with the numerically exact value of the correlation function for long and short times.
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Rosana Gonçalves Pires Matias
2014-12-01
Full Text Available This study aimed to determine the number of measurements necessary to evaluate physical and chemical characteristics of peach fruits, study the relationships between them and their direct and indirect effects on the content of ascorbic acid and total carotenoids. The characteristics skin and pulp color, fruit weight, suture, equatorial and polar diameters, firmness, soluble solids (SS, titratable acidity (TA, SS/TA ratio, ascorbic acid and total carotenoids were evaluated in 39 cultivars of peach and 3 cultivars of nectarine from the orchard of the Universidade Federal de Viçosa. The repeatability coefficient was estimated by ANOVA and CPCOR. Phenotypic correlation coefficients (rf were estimated and, after the multicollinearity diagnostics, they were unfolded to direct and indirect effects of the explanatory variables on the response variable using path analysis. There was agreement on the magnitude of repeatability coefficients obtained by the two methods; however, they varied among the 14 characteristics. The highest correlations were found between FW, SD, ED and PD. Seven fruits are sufficient to evaluate the physical and chemical characteristics of peach with a correlation coefficient of 90%. The characteristics considered in the path diagrams (b* skin, hº skin, b* pulp, hº pulp, ED, PD, FIR, SS, SS/AT and TC are not the main determinants of the ascorbic acid. The yellow hue of the pulp (hº pulp has the potential to be used in indirect selection for total carotenoids.
Aliya, F; Begum, H; Reddy, M T; Sivaraj, N; Pandravada, S R; Narshimulu, G
2014-05-01
Fifty genotypes of spine gourd (Momordica dioica Roxb.) were evaluated in a randomized block design with two replications at the Vegetable Research Station, Rajendranagar, Hyderabad, Andhra Pradesh, India during kharif, 2012. Correlation and path coefficient analysis were carried out to study the character association and contribution, respectively for twelve quantitative characters namely vine length (m), number of stems per plant, days to first female flower appearance, first female flowering node, days to first fruit harvest, days to last fruit harvest, fruiting period (days), fruit length (cm), fruit width (cm), fruit weight (g), number of fruits per plant and fruit yield per plant (kg) for identification of the potential selection indices. Correlation and path coefficient analyses revealed that fruiting period and number of fruits per plant not only had positively significant correlation with fruit yield but also had positively high direct effect on it and are regarded as the main determinants of fruit yield. Days to first fruit harvest had positively moderate direct effect on fruit yield and its association was negatively significant, days to last fruit harvest had negatively high direct effect on fruit yield and its association was significant positively, hence restricted simultaneous selection can be made for days to first fruit harvest and days to last fruit harvest. The improvement in fruit yield can be effective if selection is based on days to first fruit harvest, days to last fruit harvest, fruiting period and number of fruits per plant.
Indian Academy of Sciences (India)
K M Dilsha; Seema Kothari
2009-03-01
The oxidation of a number of monosubstituted aryl methyl, alkyl phenyl, dialkyl, and diphenyl sulfides by butyltriphenylphosphonium dichromate (BTPPD), to the corresponding sulfoxides, is first order with respect to BTPPD and is second order with respect to sulfide. The reaction is catalysed by hydrogen ions and the dependence is of second order. The oxidation of meta- and para-substituted aryl methyl sulfides correlated best in terms of Hammett equation, the reactions exhibited negative polar reaction constant. The ortho-substituted compounds correlated best in terms of Charton’s triparametric equation with negative polar constant and a small degree of steric hindrance. The oxidation of alkyl phenyl sulfides exhibited a good correlation in terms of Pavelich-Taft equation confirming that the electron-donating power of the alkyl group increases the rate, however, the reactivity is not markedly controlled by the bulkiness of the alkyl group. The rates of oxidation of sulfides were determined in nineteen organic solvents. An analysis of the solvent effect by multi-parametric equations indicated the relatively greater importance of the cation-solvating power of the solvents. A mechanism involving a single-step electrophilic oxygen transfer from BTPPD to the sulfide leading to polar transition state has been proposed.
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Pei-Feng Lin
Full Text Available The heart begins to beat before the brain is formed. Whether conventional hierarchical central commands sent by the brain to the heart alone explain all the interplay between these two organs should be reconsidered. Here, we demonstrate correlations between the signal complexity of brain and cardiac activity. Eighty-seven geriatric outpatients with healthy hearts and varied cognitive abilities each provided a 24-hour electrocardiography (ECG and a 19-channel eye-closed routine electroencephalography (EEG. Multiscale entropy (MSE analysis was applied to three epochs (resting-awake state, photic stimulation of fast frequencies (fast-PS, and photic stimulation of slow frequencies (slow-PS of EEG in the 1-58 Hz frequency range, and three RR interval (RRI time series (awake-state, sleep and that concomitant with the EEG for each subject. The low-to-high frequency power (LF/HF ratio of RRI was calculated to represent sympatho-vagal balance. With statistics after Bonferroni corrections, we found that: (a the summed MSE value on coarse scales of the awake RRI (scales 11-20, RRI-MSE-coarse were inversely correlated with the summed MSE value on coarse scales of the resting-awake EEG (scales 6-20, EEG-MSE-coarse at Fp2, C4, T6 and T4; (b the awake RRI-MSE-coarse was inversely correlated with the fast-PS EEG-MSE-coarse at O1, O2 and C4; (c the sleep RRI-MSE-coarse was inversely correlated with the slow-PS EEG-MSE-coarse at Fp2; (d the RRI-MSE-coarse and LF/HF ratio of the awake RRI were correlated positively to each other; (e the EEG-MSE-coarse at F8 was proportional to the cognitive test score; (f the results conform to the cholinergic hypothesis which states that cognitive impairment causes reduction in vagal cardiac modulation; (g fast-PS significantly lowered the EEG-MSE-coarse globally. Whether these heart-brain correlations could be fully explained by the central autonomic network is unknown and needs further exploration.
Kays, Ibrahim; Cvetkovska, Vedrana; Chen, Brian E
2014-01-01
We describe a protocol to image the complex axonal branching structure of identified mechanosensory neurons in Drosophila, combined with a behavioral assay to evaluate the functional output of the neuron. The stimulation of identified mechanosensory neurons in live animals produces a stereotyped grooming reflex. The mechanosensory axonal arbor within the CNS is subsequently labeled with a lipophilic fluorescent dye and imaged by fluorescence microscopy. The behavioral output can therefore be correlated to the axonal morphology of the stimulated neuron in the same animal. Combining this protocol with genetic analysis provides a powerful tool for identifying the roles of molecules involved in different aspects of hard-wired neural circuit formation underlying an innate behavior. From behavioral analysis to axonal imaging, the protocol takes 4 d.
SVD-based anatomy of gene expressions for correlation analysis in Arabidopsis thaliana.
Fukushima, Atsushi; Wada, Masayoshi; Kanaya, Shigehiko; Arita, Masanori
2008-12-01
Gene co-expression analysis has been widely used in recent years for predicting unknown gene function and its regulatory mechanisms. The predictive accuracy depends on the quality and the diversity of data set used. In this report, we applied singular value decomposition (SVD) to array experiments in public databases to find that co-expression linkage could be estimated by a much smaller number of array data. Correlations of co-expressed gene were assessed using two regulatory mechanisms (feedback loop of the fundamental circadian clock and a global transcription factor Myb28), as well as metabolic pathways in the AraCyc database. Our conclusion is that a smaller number of informative arrays across tissues can suffice to reproduce comparable results with a state-of-the-art co-expression software tool. In our SVD analysis on Arabidopsis data set, array experiments that contributed most as the principal components included stamen development, germinating seed and stress responses on leaf.
AUTHOR|(INSPIRE)INSPIRE-00361630
Heavy-ion collisions at ultra-relativistic energies give a unique possibility to create and to analyse the Quark-Gluon Plasma predicted by the theory of Quantum Chromodynamics. The research on the properties of such state of matter is crucial for understanding the features of the strongly interacting system. Experimental results reveal the collective behaviour of matter created in the heavy-ion collisions at ultra-relativistic energies. The existence of this effect can be verified by the measurement of the transverse mass dependence of the source size extracted using different particle species. Such characteristics can be determined using the analysis technique called femtoscopy. This method is based on the correlations of particles with small relative momenta which originate from the effects of Quantum Statistics as well as the strong and Coulomb Final State Interactions. A recent analysis of the particle production at the highest available collision energies of heavy-ion collisions reveals the puzzling res...
Timashev, Serge F; Polyakov, Yuriy S; Demin, Sergey A; Kaplan, Alexander Ya
2011-01-01
We apply flicker-noise spectroscopy (FNS), a time series analysis method operating on structure functions and power spectrum estimates, to study the clinical electroencephalogram (EEG) signals recorded in children/adolescents (11 to 14 years of age) with diagnosed schizophrenia-spectrum symptoms at the National Center for Psychiatric Health (NCPH) of the Russian Academy of Medical Sciences. The EEG signals for these subjects were compared with the signals for a control sample of chronically depressed children/adolescents. The purpose of the study is to look for diagnostic signs of subjects' susceptibility to schizophrenia in the FNS parameters for specific electrodes and cross-correlations between the signals simultaneously measured at different points on the scalp. Our analysis of EEG signals from scalp-mounted electrodes at locations F3 and F4, which are symmetrically positioned in the left and right frontal areas of cerebral cortex, respectively, demonstrates an essential role of frequency-phase synchroniz...
An estimation method of the fault wind turbine power generation loss based on correlation analysis
Zhang, Tao; Zhu, Shourang; Wang, Wei
2017-01-01
A method for estimating the power generation loss of a fault wind turbine is proposed in this paper. In this method, the wind speed is estimated and the estimated value of the loss of power generation is given by combining the actual output power characteristic curve of the wind turbine. In the wind speed estimation, the correlation analysis is used, and the normal operation of the wind speed of the fault wind turbine is selected, and the regression analysis method is used to obtain the estimated value of the wind speed. Based on the estimation method, this paper presents an implementation of the method in the monitoring system of the wind turbine, and verifies the effectiveness of the proposed method.
Interconnectivity among Assessments from Rating Agencies: Using Cluster and Correlation Analysis
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Jaroslav Krejčíř
2014-09-01
Full Text Available The aim of this paper is to determine whether there is a dependency among leading rating agencies assessments. Rating agencies are important part of global economy. Great attention has been paid to activities of rating agencies since 2007, when there was a financial crisis. One of the main causes of this crisis was identified credit rating agencies. This paper is focused on an existence of mutual interconnectivity among assessments from three leading rating agencies. The method used for this determines is based on cluster analysis and subsequently correlation analysis and the test of independence. Credit rating assessments of Greece and Spain were chosen to the determination of this mutual interconnectivity due to the fact that these countries are most talked euroarea countries. The significant dependence of the assessment from different rating agencies has been demonstrated.
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Licheng Zhang
Full Text Available Calcaneal quantitative ultrasound (QUS, which is used in the evaluation of osteoporosis, is believed to be intimately associated with the characteristics of the proximal femur. However, the specific associations of calcaneal QUS with characteristics of the hip sub-regions remain unclear.A cross-sectional assessment of 53 osteoporotic patients was performed for the skeletal status of the heel and hip.We prospectively enrolled 53 female osteoporotic patients with femoral fractures. Calcaneal QUS, dual energy X-ray absorptiometry (DXA, and hip structural analysis (HSA were performed for each patient. Femoral heads were obtained during the surgery, and principal compressive trabeculae (PCT were extracted by a three-dimensional printing technique-assisted method. Pearson's correlation between QUS measurement with DXA, HSA-derived parameters and Young's modulus were calculated in order to evaluate the specific association of QUS with the parameters for the hip sub-regions, including the femoral neck, trochanteric and Ward's areas, and the femoral shaft, respectively.Significant correlations were found between estimated BMD (Est.BMD and BMD of different sub-regions of proximal femur. However, the correlation coefficient of trochanteric area (r = 0.356, p = 0.009 was higher than that of the neck area (r = 0.297, p = 0.031 and total proximal femur (r = 0.291, p = 0.034. Furthermore, the quantitative ultrasound index (QUI was significantly correlated with the HSA-derived parameters of the trochanteric area (r value: 0.315-0.356, all p<0.05 as well as with the Young's modulus of PCT from the femoral head (r = 0.589, p<0.001.The calcaneal bone had an intimate association with the trochanteric cancellous bone. To a certain extent, the parameters of the calcaneal QUS can reflect the characteristics of the trochanteric area of the proximal hip, although not specifically reflective of those of the femoral neck or shaft.
Energy Technology Data Exchange (ETDEWEB)
Hsu, P. J.; Lai, S. K., E-mail: sklai@coll.phy.ncu.edu.tw [Complex Liquids Laboratory, Department of Physics, National Central University, Chungli 320 Taiwan (China); Molecular Science and Technology Program, Taiwan International Graduate Program, Academia Sinica, Taipei 115, Taiwan (China); Cheong, S. A. [Division of Physics and Applied Physics, School of Physical and Mathematical Sciences, Nanyang Technological University, 21 Nanyang Link, Singapore 637371 (Singapore)
2014-05-28
Folded conformations of proteins in thermodynamically stable states have long lifetimes. Before it folds into a stable conformation, or after unfolding from a stable conformation, the protein will generally stray from one random conformation to another leading thus to rapid fluctuations. Brief structural changes therefore occur before folding and unfolding events. These short-lived movements are easily overlooked in studies of folding/unfolding for they represent momentary excursions of the protein to explore conformations in the neighborhood of the stable conformation. The present study looks for precursory signatures of protein folding/unfolding within these rapid fluctuations through a combination of three techniques: (1) ultrafast shape recognition, (2) time series segmentation, and (3) time series correlation analysis. The first procedure measures the differences between statistical distance distributions of atoms in different conformations by calculating shape similarity indices from molecular dynamics simulation trajectories. The second procedure is used to discover the times at which the protein makes transitions from one conformation to another. Finally, we employ the third technique to exploit spatial fingerprints of the stable conformations; this procedure is to map out the sequences of changes preceding the actual folding and unfolding events, since strongly correlated atoms in different conformations are different due to bond and steric constraints. The aforementioned high-frequency fluctuations are therefore characterized by distinct correlational and structural changes that are associated with rate-limiting precursors that translate into brief segments. Guided by these technical procedures, we choose a model system, a fragment of the protein transthyretin, for identifying in this system not only the precursory signatures of transitions associated with α helix and β hairpin, but also the important role played by weaker correlations in such protein
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Chaumongkol, Y.
2001-11-01
Full Text Available A study of correlation, path coefficient analysis and heritablity for some agronomic characters of oil palm was investigated during February 1998 to January 2002. The oil palm population used in this experiment was derived from F1 tenera hybrids which were collected from various oil palm plantations in Southern Thailand. One good performance bunch (i.e., big bunch, thin shell was selected from each plantation and four to six seeds per selected bunch were used for cultivation. One thousand thirty eight plants were grown at Klong Hoi Khong Research Station, Faculty of Natural Resources, Prince of Songkla University, Songkhla, in 1989. Forty five palms consisted of Dura, Tenera and Pisifera types with 18, 18 and 9 plants respectively, were selected by randomization and tagged for investigation. The oil palm bunch yield and yield component characters were observed from individual palm for 4 years (February 1998 to January 2002. The bunch composition characters were analysed from a single bunch of each palm, sampled between June to October 1999. The results showed that in F2 plants of oil palm, the correlation and the path coefficient between characters relating to oil yield and %oil/bunch varied according to oil palm types (Dura, Tenera and Pisifera. In Dura and Tenera palms, the characters which gave highly positive correlation with a large direct and indirect positive effects on oil yield and %oil/bunch were total bunch weight, %oil/bunch, %fruit/bunch and %oil/fruit. In case of Pisifera palms, the characters which gave highly positive correlation with a large direct and indirect positive effects on oil yield and %oil/bunch were total bunch weight, number of bunches, single bunch weight, %oil/bunch and %fruit/bunch. However, from all investigated characters in F2 plants, only %mesocarp/fruit, %oil/fruit and %fruit/bunch showed the high values of broad sense heritabilities.
Multi-channel analysis of passive surface waves based on cross-correlations
Cheng, F.; Xia, J.; Xu, Z.; Hu, Y.
2015-12-01
Traditional active seismic survey can no longer be properly applied in highly populated urban areas due to restrictions in modern civilian life styles. Passive seismic methods, however, have gained much more attention from the engineering geophysics community because of their environmental friendly and deeper investigation depth. Due to extracting signal from noise has never been as comfortable as that in active seismic survey, how to make it more efficiently and accurately has been emphasized. We propose a multi-channel analysis of passive surface waves (MAPW) based on long noise sequences cross-correlations to meet the demand for increasing investigation depth by acquiring surface-wave data at a relative low-frequency range (1 Hz ≤ f ≤ 10 Hz) in urban areas. We utilize seismic interferometry to produce common virtual source gathers from one-hour-long noise records and do dispersion measurements by using the classic passive multi-channel analysis of surface waves (PMASW). We used synthetic tests to demonstrate the advantages of MAPW for various noise distributions. Results show that our method has the superiority of maximizing the analysis accuracy. Finally, we used two field data applications to demonstrate the advantages of our MAPW over the classic PMASW on isolating azimuth of the predominant noise sources and the effectivity of combined survey of active multi-channel analysis of surface waves (MASW) and MAPW. We suggest, for the field operation using MAPW, that a parallel receiver line which is close to a main road or river, if any, with one or two hours noise observation will be an effective means for an unbiased dispersion image. Keywords: passive seismic method, MAPW, MASW, cross-correlation, directional noise source, spatial-aliasing effects, inversion
Finite Element Analysis and Test Correlation of a 10-Meter Inflation-Deployed Solar Sail
Sleight, David W.; Michii, Yuki; Lichodziejewski, David; Derbes, Billy; Mann. Troy O.; Slade, Kara N.; Wang, John T.
2005-01-01
Under the direction of the NASA In-Space Propulsion Technology Office, the team of L Garde, NASA Jet Propulsion Laboratory, Ball Aerospace, and NASA Langley Research Center has been developing a scalable solar sail configuration to address NASA's future space propulsion needs. Prior to a flight experiment of a full-scale solar sail, a comprehensive phased test plan is currently being implemented to advance the technology readiness level of the solar sail design. These tests consist of solar sail component, subsystem, and sub-scale system ground tests that simulate the vacuum and thermal conditions of the space environment. Recently, two solar sail test articles, a 7.4-m beam assembly subsystem test article and a 10-m four-quadrant solar sail system test article, were tested in vacuum conditions with a gravity-offload system to mitigate the effects of gravity. This paper presents the structural analyses simulating the ground tests and the correlation of the analyses with the test results. For programmatic risk reduction, a two-prong analysis approach was undertaken in which two separate teams independently developed computational models of the solar sail test articles using the finite element analysis software packages: NEiNastran and ABAQUS. This paper compares the pre-test and post-test analysis predictions from both software packages with the test data including load-deflection curves from static load tests, and vibration frequencies and mode shapes from vibration tests. The analysis predictions were in reasonable agreement with the test data. Factors that precluded better correlation of the analyses and the tests were uncertainties in the material properties, test conditions, and modeling assumptions used in the analyses.
New insights into time series analysis. II - Non-correlated observations
Ferreira Lopes, C. E.; Cross, N. J. G.
2017-08-01
to improve the effectiveness of both correlated and non-correlated indices. Conclusions: The selection of non-stochastic variations is improved by non-correlated indices. The even-averages provide a better estimation of mean and median for almost all statistical distributions analyzed. The correlated variability indices, which are proposed in the first paper of this series, are also improved if the even-mean is used. The even-parameters will also be useful for classifying light curves in the last step of this project. We consider that the first step of this project, where we set new techniques and methods that provide a huge improvement on the efficiency of selection of variable stars, is now complete. Many of these techniques may be useful for a large number of fields. Next, we will commence a new step of this project regarding the analysis of period search methods.
Timashev, Serge F.; Panischev, Oleg Yu.; Polyakov, Yuriy S.; Demin, Sergey A.; Kaplan, Alexander Ya.
2012-02-01
We apply flicker-noise spectroscopy (FNS), a time series analysis method operating on structure functions and power spectrum estimates, to study the clinical electroencephalogram (EEG) signals recorded in children/adolescents (11 to 14 years of age) with diagnosed schizophrenia-spectrum symptoms at the National Center for Psychiatric Health (NCPH) of the Russian Academy of Medical Sciences. The EEG signals for these subjects were compared with the signals for a control sample of chronically depressed children/adolescents. The purpose of the study is to look for diagnostic signs of subjects' susceptibility to schizophrenia in the FNS parameters for specific electrodes and cross-correlations between the signals simultaneously measured at different points on the scalp. Our analysis of EEG signals from scalp-mounted electrodes at locations F3 and F4, which are symmetrically positioned in the left and right frontal areas of cerebral cortex, respectively, demonstrates an essential role of frequency-phase synchronization, a phenomenon representing specific correlations between the characteristic frequencies and phases of excitations in the brain. We introduce quantitative measures of frequency-phase synchronization and systematize the values of FNS parameters for the EEG data. The comparison of our results with the medical diagnoses for 84 subjects performed at NCPH makes it possible to group the EEG signals into 4 categories corresponding to different risk levels of subjects' susceptibility to schizophrenia. We suggest that the introduced quantitative characteristics and classification of cross-correlations may be used for the diagnosis of schizophrenia at the early stages of its development.
DiBartola, Alex C; Everhart, Joshua S; Magnussen, Robert A; Carey, James L; Brophy, Robert H; Schmitt, Laura C; Flanigan, David C
2016-06-01
Compare histological outcomes after microfracture (MF), autologous chondrocyte implantation (ACI), and osteochondral autograft transfer (OATS). Literature review using PubMed MEDLINE, SCOPUS, Cumulative Index for Nursing and Allied Health Literature (CINAHL), and Cochrane Collaboration Library. Inclusion criteria limited to English language studies International Cartilage Repair Society (ICRS) grading criteria for cartilage analysis after ACI (autologous chondrocyte implantation), MF (microfracture), or OATS (osteochondral autografting) repair techniques. Thirty-three studies investigating 1511 patients were identified. Thirty evaluated ACI or one of its subtypes, six evaluated MF, and seven evaluated OATS. There was no evidence of publication bias (Begg's p=0.48). No statistically significant correlation was found between percent change in clinical outcome and percent biopsies showing ICRS Excellent scores (R(2)=0.05, p=0.38). Percent change in clinical outcome and percent of biopsies showing only hyaline cartilage were significantly associated (R(2)=0.24, p=0.024). Mean lesion size and histological outcome were not correlated based either on percent ICRS Excellent (R(2)=0.03, p=0.50) or percent hyaline cartilage only (R(2)=0.01, p=0.67). Most common lesion location and histological outcome were not correlated based either on percent ICRS Excellent (R(2)=0.03, p=0.50) or percent hyaline cartilage only (R(2)=0.01, p=0.67). Microfracture has poorer histologic outcomes than other cartilage repair techniques. OATS repairs primarily are comprised of hyaline cartilage, followed closely by cell-based techniques, but no significant difference was found cartilage quality using ICRS grading criteria among OATS, ACI-C, MACI, and ACI-P. IV, meta-analysis. Copyright © 2016 Elsevier B.V. All rights reserved.
Correlating transcriptional networks to breast cancer survival: a large-scale coexpression analysis.
Clarke, Colin; Madden, Stephen F; Doolan, Padraig; Aherne, Sinead T; Joyce, Helena; O'Driscoll, Lorraine; Gallagher, William M; Hennessy, Bryan T; Moriarty, Michael; Crown, John; Kennedy, Susan; Clynes, Martin
2013-10-01
Weighted gene coexpression network analysis (WGCNA) is a powerful 'guilt-by-association'-based method to extract coexpressed groups of genes from large heterogeneous messenger RNA expression data sets. We have utilized WGCNA to identify 11 coregulated gene clusters across 2342 breast cancer samples from 13 microarray-based gene expression studies. A number of these transcriptional modules were found to be correlated to clinicopathological variables (e.g. tumor grade), survival endpoints for breast cancer as a whole (disease-free survival, distant disease-free survival and overall survival) and also its molecular subtypes (luminal A, luminal B, HER2+ and basal-like). Examples of findings arising from this work include the identification of a cluster of proliferation-related genes that when upregulated correlated to increased tumor grade and were associated with poor survival in general. The prognostic potential of novel genes, for example, ubiquitin-conjugating enzyme E2S (UBE2S) within this group was confirmed in an independent data set. In addition, gene clusters were also associated with survival for breast cancer molecular subtypes including a cluster of genes that was found to correlate with prognosis exclusively for basal-like breast cancer. The upregulation of several single genes within this coexpression cluster, for example, the potassium channel, subfamily K, member 5 (KCNK5) was associated with poor outcome for the basal-like molecular subtype. We have developed an online database to allow user-friendly access to the coexpression patterns and the survival analysis outputs uncovered in this study (available at http://glados.ucd.ie/Coexpression/).
Suppression of pulmonary vasculature in lung perfusion MRI using correlation analysis
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Risse, Frank; Semmler, Wolfhard [Deutsches Krebsforschungszentrum, Department of Medical Physics in Radiology, Heidelberg (Germany); Kuder, Tristan A. [Deutsches Krebsforschungszentrum, Department of Medical Physics in Radiology, Heidelberg (Germany); Deutsches Krebsforschungszentrum, Department of Radiology, Heidelberg (Germany); Kauczor, Hans-Ulrich [University of Heidelberg, Department of Diagnostic Radiology, Heidelberg (Germany); Fink, Christian [University Medical Center Mannheim, Medical Faculty Mannheim - University of Heidelberg, Department of Clinical Radiology and Nuclear Medicine, Mannheim (Germany); Universitaetsmedizin Mannheim, Institut fuer Klinische Radiologie und Nuklearmedizin, Mannheim (Germany)
2009-11-15
The purpose of the study was to evaluate the feasibility of suppressing the pulmonary vasculature in lung perfusion MRI using cross-correlation analysis (CCA). Perfusion magnetic resonance imaging (MRI) (3D FLASH, TR/TE/flip angle: 0.8 ms/2.1 ms/40 ) of the lungs was performed in seven healthy volunteers at 1.5 Tesla after injection of Gd-DTPA. CCA was performed pixel-wise in lung segmentations using the signal time-course of the main pulmonary artery and left atrium as references. Pixels with high correlation coefficients were considered as arterial or venous and excluded from further analysis. Quantitative perfusion parameters [pulmonary blood flow (PBF) and volume (PBV)] were calculated for manual lung segmentations separately, with the entire left and right lung with all intrapulmonary vessels (IPV) included, excluded manually or excluded using CCA. The application of CCA allowed reliable suppression of hilar and large IPVs. Using vascular suppression by CCA, perfusion parameters were significantly reduced (p {<=} 0.001). The reduction was 8% for PBF and 13% for PBV compared with manual exclusion and 15% for PBF and 25% for PBV when all vessel structures were included. The application of CCA improves the visualisation and quantification of lung perfusion in MRI. Overestimation of perfusion parameters caused by pulmonary vessels is significantly reduced. (orig.)
Correlative Spectral Analysis of Gamma-Ray Bursts using Swift-BAT and GLAST-GBM
Stamatikos, Michael; Band, David L
2008-01-01
We discuss the preliminary results of spectral analysis simulations involving anticipated correlated multi-wavelength observations of gamma-ray bursts (GRBs) using Swift's Burst Alert Telescope (BAT) and the Gamma-Ray Large Area Space Telescope's (GLAST) Burst Monitor (GLAST-GBM), resulting in joint spectral fits, including characteristic photon energy (Epeak) values, for a conservative annual estimate of ~30 GRBs. The addition of BAT's spectral response will (i) complement in-orbit calibration efforts of GBM's detector response matrices, (ii) augment GLAST's low energy sensitivity by increasing the ~20-100 keV effective area, (iii) facilitate ground-based follow-up efforts of GLAST GRBs by increasing GBM's source localization precision, and (iv) help identify a subset of non-triggered GRBs discovered via off-line GBM data analysis. Such multi-wavelength correlative analyses, which have been demonstrated by successful joint-spectral fits of Swift-BAT GRBs with other higher energy detectors such as Konus-WIND ...
Baseline distribution and correlation analysis of hsCRP in an insurance applicant population.
Krause, Kenneth J; Williams, David S; White, Nancy
2008-01-01
Many clinical studies have shown that baseline levels of high sensitivity C-reactive protein (hsCRP) in apparently healthy men and women are highly predictive of future risk of heart attack, stroke, sudden cardiac death, and the development of peripheral arterial disease. This paper presents an analysis of the baseline characteristics of our prospective study cohort. The intent of our prospective study is to determine whether hsCRP can be used to better classify risk for life insurance applicants already at risk for cardiovascular events, as well as those who are not. The possibility that low levels of hsCRP levels in otherwise healthy applicants might be associated with more favorable cardiovascular risk could allow this test to be used to more precisely stratify risk in the standard-or-better underwriting classifications. In this preliminary analysis, high sensitivity CRP appears to be weakly correlated with BMI, and perhaps triglyceride level in this cohort of insurance applicants. Somewhat surprisingly, in contrast to many published reports, hsCRP was not found to be correlated with other lipid measures (TC, HDL, LDL), dysmetabolic markers or smoking classification during the underwriting process. We plan to analyze mortality results as they evolve in the future.
Joint Analysis Method for Major Genes Controlling Multiple Correlated Quantitative Traits
Institute of Scientific and Technical Information of China (English)
无
2006-01-01
Based on the major gene and polygene mixed inheritance model for multiple correlated quantitative traits, the authors proposed a new joint segregation analysis method of major gene controlling multiple correlated quantitative traits, which include major gene detection and its effect and variation estimation. The effect and variation of major gene are estimated by the maximum likelihood method implemented via expectation-maximization (EM) algorithm. Major gene is tested with the likelihood ratio (LR) test statistic. Extensive simulation studies showed that joint analysis not only increases the statistical power of major gene detection but also improves the precision and accuracy of major gene effect estimates. An example of the plant height and the number of tiller of F2 population in rice cross Duonieai × Zhonghua 11 was used in the illustration. The results indicated that the genetic difference of these two traits in this cross refers to only one pleiotropic major gene. The additive effect and dominance effect of the major gene are estimated as -21.3 and 40.6 cm on plant height, and 22.7 and -25.3 on number of tiller, respectively. The major gene shows overdominance for plant height and close to complete dominance for number of tillers.
Patel, Prianka V; Gianoulis, Tara A; Bjornson, Robert D; Yip, Kevin Y; Engelman, Donald M; Gerstein, Mark B
2010-07-01
Recent metagenomics studies have begun to sample the genomic diversity among disparate habitats and relate this variation to features of the environment. Membrane proteins are an intuitive, but thus far overlooked, choice in this type of analysis as they directly interact with the environment, receiving signals from the outside and transporting nutrients. Using global ocean sampling (GOS) data, we found nearly approximately 900,000 membrane proteins in large-scale metagenomic sequence, approximately a fifth of which are completely novel, suggesting a large space of hitherto unexplored protein diversity. Using GPS coordinates for the GOS sites, we extracted additional environmental features via interpolation from the World Ocean Database, the National Center for Ecological Analysis and Synthesis, and empirical models of dust occurrence. This allowed us to study membrane protein variation in terms of natural features, such as phosphate and nitrate concentrations, and also in terms of human impacts, such as pollution and climate change. We show that there is widespread variation in membrane protein content across marine sites, which is correlated with changes in both oceanographic variables and human factors. Furthermore, using these data, we developed an approach, protein families and environment features network (PEN), to quantify and visualize the correlations. PEN identifies small groups of covarying environmental features and membrane protein families, which we call "bimodules." Using this approach, we find that the affinity of phosphate transporters is related to the concentration of phosphate and that the occurrence of iron transporters is connected to the amount of shipping, pollution, and iron-containing dust.
Three dimensional passive underwater target motion analysis using correlated data fusion
Institute of Scientific and Technical Information of China (English)
HU Youfeng; JIAO Bingli
2004-01-01
In this paper a new method of passive underwater TMA (target motion analysis) using data fusion is presented. The findings of this research are based on an understanding that there is a powerful sonar system that consists of many types of sonar but with one own-ship, and that different target parameter measurements can be obtained simultaneously. For the analysis 3 data measurements, passive bearing, elevation and multipath time-delay, are used, which are divided into two groups: a group with estimates of two preliminary target parameter obtained by dealing with each group measurement independently, and a group where correlated estimates are sent to a fusion center where the correlation between two data groups are considered so that the passive underwater TMA is realized. Simulation results show that curves of parameter estimation errors obtained by using the data fusion have fast convergence and the estimation accuracy is noticeably improved. The TMA algorithm presented is verified and is of practical significance because it is easy to be realized in one ship.
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.
Correlation between periodontal disease and oral cancer risk: A meta-analysis.
Ye, Lili; Jiang, Yinhua; Liu, Weidong; Tao, HaiBiao
2016-12-01
The purpose of this study is to investigate the correlation between periodontal disease and oral cancer risk by meta-analysis. We searched the electronic databases of PubMed and Wanfang to include the articles related to periodontal disease and oral cancer risk. The association between periodontal disease and oral cancer risk was assessed by odds ratio (OR) and its corresponding 95% confidence interval (95% CI). The publication bias was evaluated by Begg's funnel plot and Egger's line regression test. All the data analysis was done by STATA12.0 software (Stata Corporation, College Station, TX, USA). Eleven case-control studies were included in our present meta-analysis. We found significant statistical heterogeneity was existed in our present meta-analysis (I2 = 99.8%, P periodontal disease and oral cancer risk was found with OR = 3.21 and the 95% CI = 2.25-4.16 (P periodontal disease can increase the oral cancer risk by nearly 2-fold.
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Qian Hong
2008-05-01
Full Text Available Abstract Background: Several approaches, including metabolic control analysis (MCA, flux balance analysis (FBA, correlation metric construction (CMC, and biochemical circuit theory (BCT, have been developed for the quantitative analysis of complex biochemical networks. Here, we present a comprehensive theory of linear analysis for nonequilibrium steady-state (NESS biochemical reaction networks that unites these disparate approaches in a common mathematical framework and thermodynamic basis. Results: In this theory a number of relationships between key matrices are introduced: the matrix A obtained in the standard, linear-dynamic-stability analysis of the steady-state can be decomposed as A = SRT where R and S are directly related to the elasticity-coefficient matrix for the fluxes and chemical potentials in MCA, respectively; the control-coefficients for the fluxes and chemical potentials can be written in terms of RT BS and ST BS respectively where matrix B is the inverse of A; the matrix S is precisely the stoichiometric matrix in FBA; and the matrix eAt plays a central role in CMC. Conclusion: One key finding that emerges from this analysis is that the well-known summation theorems in MCA take different forms depending on whether metabolic steady-state is maintained by flux injection or concentration clamping. We demonstrate that if rate-limiting steps exist in a biochemical pathway, they are the steps with smallest biochemical conductances and largest flux control-coefficients. We hypothesize that biochemical networks for cellular signaling have a different strategy for minimizing energy waste and being efficient than do biochemical networks for biosynthesis. We also discuss the intimate relationship between MCA and biochemical systems analysis (BSA.
Liu, Shun-Zhi; Yan, Hong; Xu, Peng; Li, Jian-Ping; Zhuang, Gui-Hua; Zhu, Bo-Feng; Lu, She-Min
2009-12-01
The objective of this paper is to investigate the correlation between serum macro-element and trace element contents and bone mineral density (BMD) as well as the occurrence of osteoporosis. After the epidemiological investigation of 290 postmenopausal women from ages 45 to 65 in the Xi'an urban area, their blood was collected and serum concentrations of macro-elements, calcium, phosphonium, potassium, sodium, magnesium, and trace elements, zinc, iron, copper, and selenium were determined using atomic absorption spectrometry. Their BMD was measured by QDR-2000 dual-energy X-ray absorptiometry (DEXA). The correlation analysis between BMD and serum element contents was done with the software of SPSS 13.0. The correlation analysis of serum elements of postmenopausal women showed that there was a significant correlation between serum calcium and the other elements, and also a significant correlation between serum phosphonium and the others except serum potassium. The serum potassium content had a significant correlation with serum calcium, sodium and iron, but sodium content showed a significant correlation with the others except iron and selenium. In addition, copper had a significant correlation with the others except potassium and selenium. In correlation analysis between BMD and the elements contents, only did the potassium content show a significant positive correlation with BMD of lumbar vertebra and proximal femora. The comparison results between osteoporosis group, osteopenia group, and healthy group showed that there was no significant difference in the element contents between the groups, but there existed a tendency that potassium content increased with the rise of BMD. There exist significant correlations between the contents of serum elements such as calcium, phosphonium, sodium, potassium, magnesium, zinc, iron, copper, and selenium, but no significant differences in these elements contents between the osteoporosis group, osteopenia group, and healthy
Post analysis simulated correlation of the El-Ganzouri airway difficulty score with difficult airway
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Ruggero M. Corso
2016-06-01
Full Text Available ABSTRACT BACKGROUND: Difficult airway (DA occurs frequently (5-15% in clinical practice. The El-Ganzouri Risk Index (EGRI has a high sensitivity for predicting a difficult intubation (DI. However difficult mask ventilation (DMV was never included in the EGRI. Since DMV was not included in the EGRI assessment, and obstructive sleep apnea (OSA is also correlated with DMV, a study correlating the prediction of DA and OSA (identified by STOP-Bang questionnaire, SB seemed important. METHODS: We accessed a database previously collected for a post analysis simulation of the airway difficulty predictivity of the EGRI, associated with normal and difficult airway, particularly DMV. As secondary aim, we measured the correlation between the SB prediction system and DA, compared to the EGRI. RESULTS: A total of 2747 patients were included in the study. The proportion of patients with DI was 14.7% (95% CI 13.4-16 and the proportion of patients with DMV was 3.42% (95% CI 2.7-4.1. The incidence of DMV combined with DI was (2.3%. The optimal cutoff value of EGRI was 3. EGRI registered also an higher ability to predict DMV (AUC = 0.76 (95% CI 0.71-0.81. Adding the SB variables in the logistic model, the AUC increases with the inclusion of "observed apnea" variable (0.83 vs. 0.81, p = 0.03. The area under the ROC curve for the patients with DI and DMV was 0.77 (95% CI 0.72-0.83. CONCLUSIONS: This study confirms that the incidence of DA is not negligible and suggests the use of the EGRI as simple bedside predictive score to improve patient safety.
Filipović Grčić, Petar; Matijaca, Meri; Bilić, Ivica; Džamonja, Gordan; Lušić, Ivo; Čaljkušić, Krešimir; Čapkun, Vesna
2013-12-01
Walking limitation assessment in multiple sclerosis patients (MSPs) is a demanding task, especially in the clinical setting. The aim of this study is to correlate the visual analogue scale (VAS), a simple method for measuring subjective experience, with measures of walking ability used in clinical research of MS. The study included 82 ambulatory MSPs who have resided in the local community. The applied measures of walking ability were the following: the single-item and patient-rated Walking Ability Visual Analogue Scale (WA-VAS), the Expanded Disability Status Scale (EDSS), the 25-foot walk test (25FWT), the Six Spot Step Test (SSST), the 2 min timed walk (2 min TW), the Multiple Sclerosis Walking Scale-12 (MSWS-12), and step activity monitor accelerometer (SAM) during 7 day period. The SAM analysis included the average daily step count, the average steps/min of the highest 1 min of a day, and the average steps/min of the highest continuous 60 min of a day. The WA-VAS scores significantly and strongly correlated with EDSS (ρ = 0.679, P < 0.001), 25FWT (ρ = 0.606, P < 0.001), SSST (ρ = 0.729, P < 0.001), 2 min TW (ρ = -0.643, P < 0.001), MSWS-12 (ρ = 0.746, P < 0.001), average daily step count (ρ = -0.507, P < 0.001), average steps/min of the highest 1 min of a day (ρ = -0.544, P < 0.001), and average steps/min of the highest continuous 60 min of a day (ρ = -0.473, P < 0.001). Correlations between WA-VAS and measures of walking ability used in clinical research of MS were satisfactory. The results obtained in this research indicate that the WA-VAS could be an instrument for simple measurement of walking limitations in MSPs in the clinical setting.
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Zhichen Yu
2017-02-01
Full Text Available With the continuous progress of human production and life, air quality has become the focus of attention. In this paper, Beijing, Tianjin, Hebei, Shanxi, Shandong and Henan provinces were taken as the study area, where there are 58 air quality monitoring stations from which daily and monthly data are obtained. Firstly, the temporal characteristics of the air quality index (AQI are explored. Then, the spatial distribution of the AQI is mapped by the inverse distance weighted (IDW method, the ordinary kriging (OK method and the Bayesian maximum entropy (BME method. Additionally, cross-validation is utilized to evaluate the mapping results of these methods with two indexes: mean absolute error and root mean square interpolation error. Furthermore, the correlation analysis of meteorological factors, including precipitation anomaly percentage, precipitation, mean wind speed, average temperature, average water vapor pressure and average relative humidity, potentially affecting the AQI was carried out on both daily and monthly scales. In the study area and period, AQI shows a clear periodicity, although overall, it has a downward trend. The peak of AQI appeared in November, December and January. BME interpolation has a higher accuracy than OK. IDW has the maximum error. Overall, the AQI of winter (November, spring (February is much worse than summer (May and autumn (August. Additionally, the air quality has improved during the study period. The most polluted areas of air quality are concentrated in Beijing, the southern part of Tianjin, the central-southern part of Hebei, the central-northern part of Henan and the western part of Shandong. The average wind speed and average relative humidity have real correlation with AQI. The effect of meteorological factors such as wind, precipitation and humidity on AQI is putative to have temporal lag to different extents. AQI of cities with poor air quality will fluctuate greater than that of others when weather
He, Bin; Liu, Rong; Yang, Renjie; Xu, Kexin
2010-02-01
Adulteration of milk and dairy products has brought serious threats to human health as well as enormous economic losses to the food industry. Considering the diversity of adulterants possibly mixed in milk, such as melamine, urea, tetracycline, sugar/salt and so forth, a rapid, widely available, high-throughput, cost-effective method is needed for detecting each of the components in milk at once. In this paper, a method using Fourier Transform Infrared spectroscopy (FTIR) combined with two-dimensional (2D) correlation spectroscopy is established for the discriminative analysis of adulteration in milk. Firstly, the characteristic peaks of the raw milk are found in the 4000-400 cm-1 region by its original spectra. Secondly, the adulterant samples are respectively detected with the same method to establish a spectral database for subsequent comparison. Then, 2D correlation spectra of the samples are obtained which have high time resolution and can provide information about concentration-dependent intensity changes not readily accessible from one-dimensional spectra. And the characteristic peaks in the synchronous 2D correlation spectra of the suspected samples are compared with those of raw milk. The differences among their synchronous spectra imply that the suspected milk sample must contain some kinds of adulterants. Melamine, urea, tetracycline and glucose adulterants in milk are identified respectively. This nondestructive method can be used for a correct discrimination on whether the milk and dairy products are adulterated with deleterious substances and it provides a new simple and cost-effective alternative to test the components of milk.
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Santi, Peter Angelo [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Cutler, Theresa Elizabeth [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Favalli, Andrea [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Koehler, Katrina Elizabeth [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Henzl, Vladimir [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Henzlova, Daniela [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Parker, Robert Francis [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Croft, Stephen [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
2015-12-01
In order to improve the accuracy and capabilities of neutron multiplicity counting, additional quantifiable information is needed in order to address the assumptions that are present in the point model. Extracting and utilizing higher order moments (Quads and Pents) from the neutron pulse train represents the most direct way of extracting additional information from the measurement data to allow for an improved determination of the physical properties of the item of interest. The extraction of higher order moments from a neutron pulse train required the development of advanced dead time correction algorithms which could correct for dead time effects in all of the measurement moments in a self-consistent manner. In addition, advanced analysis algorithms have been developed to address specific assumptions that are made within the current analysis model, namely that all neutrons are created at a single point within the item of interest, and that all neutrons that are produced within an item are created with the same energy distribution. This report will discuss the current status of implementation and initial testing of the advanced dead time correction and analysis algorithms that have been developed in an attempt to utilize higher order moments to improve the capabilities of correlated neutron measurement techniques.
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Syed Zaki Hassan Kazmi
Full Text Available The dynamical fluctuations in the rhythms of biological systems provide valuable information about the underlying functioning of these systems. During the past few decades analysis of cardiac function based on the heart rate variability (HRV; variation in R wave to R wave intervals has attracted great attention, resulting in more than 17000-publications (PubMed list. However, it is still controversial about the underling mechanisms of HRV. In this study, we performed both linear (time domain and frequency domain and nonlinear analysis of HRV data acquired from humans and animals to identify the relationship between HRV and heart rate (HR. The HRV data consists of the following groups: (a human normal sinus rhythm (n = 72; (b human congestive heart failure (n = 44; (c rabbit sinoatrial node cells (SANC; n = 67; (d conscious rat (n = 11. In both human and animal data at variant pathological conditions, both linear and nonlinear analysis techniques showed an inverse correlation between HRV and HR, supporting the concept that HRV is dependent on HR, and therefore, HRV cannot be used in an ordinary manner to analyse autonomic nerve activity of a heart.
Jiang, Sen; Gao, Hua; Luo, Qin; Wang, Pengfei; Yang, Xinling
2017-08-01
The correlation between immunity and Parkinson's disease was presented in many papers, which also discussed lymphocyte and natural killer cell. But these studies have yielded inconsistent results. To systematically review the relationship between the lymphocyte subsets/natural killer cell and the risk of Parkinson's disease, we electronically searched the SpringerLink, Web of Science, Ebsco-medline with full text, Pubmed, Elsevier-ScienceDirect, Ovid-lww-oup, Wanfang Data for case-control trials on comparing the number of peripheral blood lymphocyte subsets and natural killer cell in Parkinson's patients and healthy controls. According to the Cochrane methods, the reviewers selected literature, extracted data, and assessed the quality. Then, a meta-analysis was performed using RevMan 5.2. Finally, 21 case-control trials including 943 cases of Parkinson's disease were fit into our data analysis. Meta-analysis showed that the decreased numbers of CD3+, CD4+ lymphocyte subsets and the increased number of natural killer cell were found in Parkinson's disease patients. In the intermediate and late stage of PD, CD8+ lymphocyte subsets had a significant decrement. However, the number of B lymphocyte subsets had no significant association with Parkinson's disease. The lymphocyte subsets and NK cell may be associated with the risk of Parkinson's disease.
Retrospective North American CFL Experience Curve Analysis and Correlation to Deployment Programs
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Smith, Sarah J. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Wei, Max [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Sohn, Michael D. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
2015-07-01
Retrospective experience curves are a useful tool for understanding historic technology development, and can contribute to investment program analysis and future cost estimation efforts. This work documents our development of an analysis approach for deriving retrospective experience curves with a variable learning rate, and its application to develop an experience curve for compact fluorescent lamps for the global and North American markets over the years 1990-2007. Uncertainties and assumptions involved in interpreting data for our experience curve development are discussed, including the processing and transformation of empirical data, the selection of system boundaries, and the identification of historical changes in the learning rate over the course of 15 years. In the results that follow, we find that that the learning rate has changed at least once from 1990-2007. We also explore if, and to what degree, public deployment programs may have contributed to an increased technology learning rate in North America. We observe correlations between the changes in the learning rate and the initiation of new policies, abrupt technological advances, including improvements to ballast technology, and economic and political events such as trade tariffs and electricity prices. Finally, we discuss how the findings of this work (1) support the use of segmented experience curves for retrospective and prospective analysis and (2) may imply that investments in technological research and development have contributed to a change in market adoption and penetration.
Han, Rui-Qi; Xie, Wen-Jie; Xiong, Xiong; Zhang, Wei; Zhou, Wei-Xing
The correlation structure of a stock market contains important financial contents, which may change remarkably due to the occurrence of financial crisis. We perform a comparative analysis of the Chinese stock market around the occurrence of the 2008 crisis based on the random matrix analysis of high-frequency stock returns of 1228 Chinese stocks. Both raw correlation matrix and partial correlation matrix with respect to the market index in two time periods of one year are investigated. We find that the Chinese stocks have stronger average correlation and partial correlation in 2008 than in 2007 and the average partial correlation is significantly weaker than the average correlation in each period. Accordingly, the largest eigenvalue of the correlation matrix is remarkably greater than that of the partial correlation matrix in each period. Moreover, each largest eigenvalue and its eigenvector reflect an evident market effect, while other deviating eigenvalues do not. We find no evidence that deviating eigenvalues contain industrial sectorial information. Surprisingly, the eigenvectors of the second largest eigenvalues in 2007 and of the third largest eigenvalues in 2008 are able to distinguish the stocks from the two exchanges. We also find that the component magnitudes of the some largest eigenvectors are proportional to the stocks’ capitalizations.
Analysis of Input and Output of China’s Agriculture Based on Canonical Correlation
Institute of Scientific and Technical Information of China (English)
2011-01-01
I select effective irrigated area, consumption of agricultural chemical fertilizer, electricity consumed in rural areas, and total power of agricultural machinery as input variables of China’s agriculture; I select grain, bean, tobacco, oil-bearing crop and fruit as output variables of China’s agriculture. By using the data of China Statistical Yearbook in 2010, based on the analysis method of canonical correlation, I conduct research on the input and output of China’s agriculture. The results show that consumption of chemical fertilizer has the biggest impact on the agricultural output of China, followed by the input of total power of agricultural machinery; the canonical variable of agricultural output of China is mainly impacted by grain, oil-bearing crop and fruit; in terms of the selected variables, the output increase of grain, oil-bearing crop and fruit in China arises from the input increase of agricultural chemical fertilizer and machinery, and there is high-degree correlation between the two. According to the conclusions, the policy suggestions are put forward as follows: gradually decrease consumption of chemical fertilizer; increase the use of modern agricultural machinery; increase agricultural irrigation input.
Per se performance of genotypes and correlation analysis in Pumpkin (Cucurbita moschata Duch.ex Poir
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N.A.Tamil selvi, P.Jansirani, L.Pugalendhi, A.Nirmalakumari
2012-12-01
Full Text Available Evaluation of 15 pumpkin genotypes collected from various sources was carried out. Observations were recorded on thefollowing traits viz. vine length, days to first female flower appearance, node number for first female flower appearance, sexratio, days to first harvest, fruit number per vine, fruit weight, fruit equatorial diameter, fruit polar diameter, flesh thickness,seed number per fruit, seed weight per fruit and fruit yield per vine along with quality traits such as total carbohydratescontent, total carotenoids content and crude fibre content of the fruit and analysed statistically. Among the genotypes, CM6followed by CM10 and CM9 recorded the highest mean value of fruit yield. Correlation analysis revealed that fruit yield per vinewas significantly and positively correlated with fruit number per vine, flesh thickness and total carotenoids content.However negative association was observed with days to first female flower appearance, node number for first femaleflower appearance, sex ratio, days to first harvest, fruit weight, fruit equatorial diameter, fruit polar diameter and crude fibrecontent. Hence selecting pumpkin genotypes with narrow sex ratio, more number of fruits per vine, fruits with high flesh thicknessand total carotenoids content will help to improve yield per vine and quality of pumpkin fruits.
Lin, C J; Lin, S C; Huang, W; Ho, C S; Chou, Y L
1999-01-01
Physiological knock-knee (PKK) was categorized by measuring intermalleolar distance (IMD), a clinically simple method, to evaluate the prevalence and correlating factors in 305 preschool children. The prevalence in this cross-sectional study was relatively high, and it was age related (p = 0.002; 64, 44, and 34% for ages 3-4, 4-5, and 5-6 years, respectively). The following factors were correlated with PKK: use of walking chair early (p = 0.0001), independently walked late (p = 0.0005), dependently walked longer (p = 0.0001), concurrence with flatfoot (p = 0.001), and angular deformity (toe in/out, p = 0.03). Gait analysis, with spatiotemporal, kinematics, and kinetics parameters, was performed to evaluate the ambulatory significance. Preschool children with PKK have a shorter stride length (p = 0.02) and a slower walking speed (p = 0.004). Dynamic hyperextension of the knee is noted for 8 degrees during the whole gait cycle (p PKK is a variable that should be considered in the development of mature gait for preschool children.
Gould, Kevin E.; Satyanarayana, Arunkumar; Bogert, Philip B.
2016-01-01
Analysis performed in this study substantiates the need for high fidelity vehicle level progressive damage analyses (PDA) structural models for use in the verification and validation of proposed sub-scale structural models and to support required full-scale vehicle level testing. PDA results are presented that capture and correlate the responses of sub-scale 3-stringer and 7-stringer panel models and an idealized 8-ft diameter fuselage model, which provides a vehicle level environment for the 7-stringer sub-scale panel model. Two unique skin-stringer attachment assumptions are considered and correlated in the models analyzed: the TIE constraint interface versus the cohesive element (COH3D8) interface. Evaluating different interfaces allows for assessing a range of predicted damage modes, including delamination and crack propagation responses. Damage models considered in this study are the ABAQUS built-in Hashin procedure and the COmplete STress Reduction (COSTR) damage procedure implemented through a VUMAT user subroutine using the ABAQUS/Explicit code.
Investment Decision Support for Engineering Projects Based on Risk Correlation Analysis
Directory of Open Access Journals (Sweden)
Yan Liu
2012-01-01
Full Text Available Investment decisions are usually made on the basis of the subjective judgments of experts subjected to the information gap during the preliminary stages of a project. As a consequence, a series of errors in risk prediction and/or decision-making will be generated leading to out of control investment and project failure. In this paper, the variable fuzzy set theory and intelligent algorithms integrated with case-based reasoning are presented. The proposed algorithm manages the numerous fuzzy concepts and variable factors of a project and also sets up the decision-making process in accordance with past cases and experiences. Furthermore, it decreases the calculation difficulty and reduces the decision-making reaction time. Three types of risk correlations combined with different characteristics of engineering projects are summarized, and each of these correlations is expounded at the project investment decision-making stage. Quantitative and qualitative change theories of variable fuzzy sets are also addressed for investment risk warning. The approach presented in this paper enables the risk analysis in a simple and intuitive manner and realizes the integration of objective and subjective risk assessments within the decision-makers' risk expectation.
Directory of Open Access Journals (Sweden)
Stojanović Zlatan
2014-01-01
Full Text Available Introduction: Knowledge of etiopathogenesis of post-stroke depressive phenomena contributes to early diagnostics which shortens recovery to a great extent and suits the social and professional rehabilitation of patients, if followed by proper psycho/pharmacotherapy. The aim of this work is to research dependence of depressive manifestations considering the size and anatomical localization of lesion. Subjects and Methods: The research included 118 patients with stroke. Lesion localization was defined on computerized axial tomography records, whereas the area and perimeter of lesion were measured by AutoCAD 2004 software. Examinations by means of Hamilton Rating Scale for Depression were carried out by the method of random selection 11-40 days after stroke. Correlation analysis was made by simple linear/non-linear regression and Cox's hazard regression model. Results: Negative correlation was observed between the intensity of depressive manifestations and the size of cerebrovascular lesion (Spearman's r = - 0.263, P = 0.004. By means of Cox's regression model we determined 4.389 times higher risk for depression occurrence in female patients (P < 0.001, as well as higher risk due to lobus limbicus structure damages (hazard ratio eb (HR = 2.661, P = 0.019. Conclusion: Lower intensity of depressive manifestations with larger cerebrovascular lesions, we have explained by activation of reparation mechanisms with energy savings and decrease (due to neurological deficits of afferent peripheral sensations which antecedent the occurrence of emotions (James-Lange peripheral theory of emotions.
Correlation Analysis for Total Electron Content Anomalies on 11th March, 2011
Iwata, Takuya
2016-01-01
We can observe the changes of Total Electron Content, TEC, in ionosphere by analyzing the data from GNSS satellites. There are many reports about TEC anomalies after earthquakes, i.e. large earthquakes often disturb the ionosphere. Up to now, preseismic TEC anomalies have been reported in several papers. However, they are not so clear as coseismic TEC anomalies, and their analysis methods have some problems for practical earthquake prediction. One factor making it difficult to detect TEC anomalies is large noises in TEC data. Non-negligible TEC disturbances are caused by many natural mechanisms. To overcome this difficulty, we propose correlation analyses between one GNSS station and GNSS stations surrounding it. First, we model TEC time series over a few hours using polynomial functions of time. Second, we calculate prediction errors as the departure of the TEC time series from the models over time scale of a few minutes, and define it as the TEC anomaly. Third, we calculate the correlation between anomaly o...
Mesquita Júnior, E J; Vieta, A I; Taba Júnior, M; Faria, P E P
2017-01-01
Most of the decisions made in planning treatment with implants rely on the clinician's assessment of the density of the jawbone. However, we know of only a few studies that have evaluated the clinicians' subjectivity and the objective quantitative methods. Our aim was to assess whether the characteristics of the bone seen on preoperative imaging are similar to the features faced during the operation. We collected data about 32 implant procedures done during the Specialisation Course for Implant Dentistry, Universidade de Ribeirão Preto, San Paulo. First, the clinicians evaluated the panoramic radiograph and computed tomographic scans preoperatively, classified the bone density according to the Lekholm and Zarb classification, and marked their subjective evaluation on a visual analogue scale. Postoperatively the surgeons filled out a questionnaire based on their subjective perceptions obtained during the insertion of the implants. Another examiner answered the same questionnaire after looking at the patient's images but without knowing the surgeon's results. There was a good correlation between the surgeons' preoperative classification of the type of bone and their tactile perception (p=0.000), and a good correlation between the surgeon's preoperative classification of the bone and the examiner's findings (p=0.000). We conclude that imaging is an important part of preoperative planning and can predict the quality of the bone when coupled with the opinion of a trained clinician, objective analysis, and standard classification of the bone.
Yamazawa, Akira; Date, Yasuhiro; Ito, Keijiro; Kikuchi, Jun
2014-03-01
Microbial ecosystems are typified by diverse microbial interactions and competition. Consequently, the microbial networks and metabolic dynamics of bioprocesses catalyzed by these ecosystems are highly complex, and their visualization is regarded as essential to bioengineering technology and innovation. Here we describe a means of visualizing the variants in a microbial community and their metabolic profiles. The approach enables previously unidentified bacterial functions in the ecosystems to be elucidated. We investigated the anaerobic bioremediation of chlorinated ethene in a soil column experiment as a case study. Microbial community and dechlorination profiles in the ecosystem were evaluated by denaturing gradient gel electrophoresis (DGGE) fingerprinting and gas chromatography, respectively. Dechlorination profiles were obtained from changes in dechlorination by microbial community (evaluated by data mining methods). Individual microbes were then associated with their dechlorination profiles by heterogenous correlation analysis. Our correlation-based visualization approach enables deduction of the roles and functions of bacteria in the dechlorination of chlorinated ethenes. Because it estimates functions and relationships between unidentified microbes and metabolites in microbial ecosystems, this approach is proposed as a control-logic tool by which to understand complex microbial processes.
Correlation and path coefficient analysis for yield and its components in vegetable soybean
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Teerawat Sarutayophat
2012-07-01
Full Text Available The associations of yield and its components offer important information in breeding plants. A study was conductedat the experimental field of the Faculty of Agricultural Technology, King Mongkut’s Institute of Technology Ladkrabang,Bangkok on 22 genotypes of the vegetable soybean to determine the association of yield and its components. The associationwas analyzed by correlation coefficient, and further subjected by path coefficient analysis to estimate direct and indirecteffects of each character on pod yield. Positive and significant correlation were found between the plant height and numberof marketable pods/plant (0.821**, plant height and marketable pod yield (0.520*, and number of marketable pods/plant andmarketable pod yield (0.822**. Negative and significance was determined between the plant height and green pod weight(-0.620**, and number of marketable pods/plant and green pod weight (-0.588**. Direct effects of the number of marketablepods/plant and green pod weight on marketable pod yield were positive and significant with path coefficients of 1.310** and0.707**, respectively. Indirect effect of the plant height on marketable pod yield through its association with number ofmarketable pods/plant was positive and significant (1.075**. The results of this study suggested that the number of marketablepods/plant, green pod weight and plant height were important characters that should be taken into account as selectioncriteria in improving marketable pod yield of the vegetable soybean.
Correction of vibration for classical free-fall gravimeters with correlation-analysis
Wang, G.; Hu, H.; Wu, K.; Wang, L. J.
2017-03-01
In a free-fall absolute gravimeter, a laser interferometer is used to track the falling retro-reflector. To buffer the reference retro-reflector from seismic noise, a low-frequency vertical vibration isolator is traditionally used. However, an isolation device is usually complicated and expensive. A strap-down system using a seismometer to record the vibration and correct the measurement resolves the issue, but the actual recorded vibration cannot be directly used because of signal transfer delay and amplitude attenuation. Nevertheless, by quadratically fitting the trajectory of the falling retro-reflector and the motion of the reference retro-reflector, we find that their residuals are significantly correlated. Moreover, the transfer delay and the amplitude attenuation can be calculated using correlation analysis. With this capability, a vibration correction method for absolute gravimeters is proposed and demonstrated. The transfer delay and the gain attenuation are determined from data of only 25 drops, and can be used to correct subsequent measurements. The method is also applied in the T-1 absolute gravimeter. The standard deviation of the measurement results is improved by a factor of 20 after correction in a noisy environment, and improved by a factor of 5 in a quiet environment. Compared with vibration isolators, the strap-down system using this correction method is much more compact, enabling its use in field conditions or even dynamic environments not suitable for vibration isolators.
Huang, Y X
2014-01-01
In the marine environment, many fields have fluctuations over a large range of different spatial and temporal scales. These quantities can be nonlinear \\red{and} non-stationary, and often interact with each other. A good method to study the multiple scale dynamics of such time series, and their correlations, is needed. In this paper an application of an empirical mode decomposition based time dependent intrinsic correlation, \\red{of} two coastal oceanic time series, temperature and dissolved oxygen (saturation percentage) is presented. The two time series are recorded every 20 minutes \\red{for} 7 years, from 2004 to 2011. The application of the Empirical Mode Decomposition on such time series is illustrated, and the power spectra of the time series are estimated using the Hilbert transform (Hilbert spectral analysis). Power-law regimes are found with slopes of 1.33 for dissolved oxygen and 1.68 for temperature at high frequencies (between 1.2 and 12 hours) \\red{with} both close to 1.9 for lower frequencies (t...
Single-trial analysis of the neural correlates of speech quality perception
Porbadnigk, Anne K.; Treder, Matthias S.; Blankertz, Benjamin; Antons, Jan-Niklas; Schleicher, Robert; Möller, Sebastian; Curio, Gabriel; Müller, Klaus-Robert
2013-10-01
Objective. Assessing speech quality perception is a challenge typically addressed in behavioral and opinion-seeking experiments. Only recently, neuroimaging methods were introduced, which were used to study the neural processing of quality at group level. However, our electroencephalography (EEG) studies show that the neural correlates of quality perception are highly individual. Therefore, it became necessary to establish dedicated machine learning methods for decoding subject-specific effects. Approach. The effectiveness of our methods is shown by the data of an EEG study that investigates how the quality of spoken vowels is processed neurally. Participants were asked to indicate whether they had perceived a degradation of quality (signal-correlated noise) in vowels, presented in an oddball paradigm. Main results. We find that the P3 amplitude is attenuated with increasing noise. Single-trial analysis allows one to show that this is partly due to an increasing jitter of the P3 component. A novel classification approach helps to detect trials with presumably non-conscious processing at the threshold of perception. We show that this approach uncovers a non-trivial confounder between neural hits and neural misses. Significance. The combined use of EEG signals and machine learning methods results in a significant ‘neural’ gain in sensitivity (in processing quality loss) when compared to standard behavioral evaluation; averaged over 11 subjects, this amounts to a relative improvement in sensitivity of 35%.
Genotype-phenotype correlations analysis of mutations in the phenylalanine hydroxylase (PAH) gene.
Bercovich, Dani; Elimelech, Arava; Zlotogora, Joel; Korem, Sigal; Yardeni, Tal; Gal, Nurit; Goldstein, Nurit; Vilensky, Bela; Segev, Roni; Avraham, Smadar; Loewenthal, Ron; Schwartz, Gerard; Anikster, Yair
2008-01-01
The aims of our research were to define the genotype-phenotype correlations of mutations in the phenylalanine hydroxylase (PAH) gene that cause phenylketonuria (PKU) among the Israeli population. The mutation spectrum of the PAH gene in PKU patients in Israel is described, along with a discussion on genotype-phenotype correlations. By using polymerase chain reaction/denaturing high-performance liquid chromatography (PCR/dHPLC) and DNA sequencing, we screened all exons of the PAH gene in 180 unrelated patients with four different PKU phenotypes [classic PKU, moderate PKU, mild PKU, and mild hyperphenylalaninemia (MHP)]. In 63.2% of patient genotypes, the metabolic phenotype could be predicted, though evidence is also found for both phenotypic inconsistencies among subjects with more than one type of mutation in the PAH gene. Data analysis revealed that about 25% of patients could participate in the future in (6R)-L: -erythro-5, 6, 7, 8-tetrahydrobiopterin (BH4) treatment trials according to their mutation genotypes. This study enables us to construct a national database in Israel that will serve as a valuable tool for genetic counseling and a prognostic evaluation of future cases of PKU.
Structure and evolution of a European Parliament via a network and correlation analysis
Puccio, Elena; Pajala, Antti; Piilo, Jyrki; Tumminello, Michele
2016-11-01
We present a study of the network of relationships among elected members of the Finnish parliament, based on a quantitative analysis of initiative co-signatures, and its evolution over 16 years. To understand the structure of the parliament, we constructed a statistically validated network of members, based on the similarity between the patterns of initiatives they signed. We looked for communities within the network and characterized them in terms of members' attributes, such as electoral district and party. To gain insight on the nested structure of communities, we constructed a hierarchical tree of members from the correlation matrix. Afterwards, we studied parliament dynamics yearly, with a focus on correlations within and between parties, by also distinguishing between government and opposition. Finally, we investigated the role played by specific individuals, at a local level. In particular, whether they act as proponents who gather consensus, or as signers. Our results provide a quantitative background to current theories in political science. From a methodological point of view, our network approach has proven able to highlight both local and global features of a complex social system.
Word-Length Correlations and Memory in Large Texts: A Visibility Network Analysis
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Lev Guzmán-Vargas
2015-11-01
Full Text Available We study the correlation properties of word lengths in large texts from 30 ebooks in the English language from the Gutenberg Project (www.gutenberg.org using the natural visibility graph method (NVG. NVG converts a time series into a graph and then analyzes its graph properties. First, the original sequence of words is transformed into a sequence of values containing the length of each word, and then, it is integrated. Next, we apply the NVG to the integrated word-length series and construct the network. We show that the degree distribution of that network follows a power law, P ( k ∼ k - γ , with two regimes, which are characterized by the exponents γ s ≈ 1 . 7 (at short degree scales and γ l ≈ 1 . 3 (at large degree scales. This suggests that word lengths are much more strongly correlated at large distances between words than at short distances between words. That finding is also supported by the detrended fluctuation analysis (DFA and recurrence time distribution. These results provide new information about the universal characteristics of the structure of written texts beyond that given by word frequencies.
Investigation of Correlations for the Thermal-hydraulic Analysis of Liquid Metal Reactors
Energy Technology Data Exchange (ETDEWEB)
Chang, Won Pyo; Jeong, Hae Yong; Lee, Yong Bum
2007-08-15
The present investigation is aimed at reducing favorable constitutive correlations from those developed for the thermal-hydraulic analysis of Liquid Metal Reactors (LMR), for reliable safety analyses of KALIMER. It is achieved by analyzing them in a point of their accuracies. The study is particularly important because its outcomes can provide an essential knowledge on their relative errors including their conservatisms to be analyzed in the future KALIMER licensing stage. The predictions of the correlations have been compared with available experimental data on both friction factors for the wired-wrapped rod bundles in the core and the heat transfer coefficients in the system. As a result, the heat transfer coefficient inside pipe currently featured in SSC-K has been found acceptable. It, however, has shown a discrepancy of about 60 % and thus an alternative one has been proposed for improvement. Meanwhile, the friction factor model in the current SSC-K has not shown a prominent discrepancy in prediction trend but it has not backed an enough theoretical basis so that another model has been proposed. A systematic assessment for effects of those factors to the conservatism must be fully understood for the future licensing stage, and systematic calculations must be followed by designing an assessment matrix. Besides, it is essential to conduct experiments under similar conditions for constitutive parts of geometries which represent the KALIMER design.
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.
Overview of Neutron Beta Correlation Parameter Analysis from the UCNA Experiment
Sun, Xuan; UCNA Collaboration
2017-01-01
The UCNA experiment, operated at the Ultracold Neutron Facility at the Los Alamos Neutron Science Center, uses ultracold neutrons (UCN) to measure the free-neutron β-decay correlation parameter, A, between the neutron spin direction and β momentum direction. Measurements of A presently provide the most precise value of gA /gV , the ratio of the axial-vector and vector coupling constants of the nucleon weak interaction. The UCNA experiment has previously analyzed and reported on a measurement of A from a 2010 dataset. Additional datasets were also taken in 2011-2012 and 2012-2013. Improvements in energy calibrations, polarimetry, and statistics are expected to provide a more precise measurement of A from the later datasets. We provide a review of the experimental apparatus and give an updated overview on the state of the 2011-2012 and 2012-2013 dataset analysis with respect to the A measurement.
Suefusa, Kaori; Tanaka, Toshihisa
2016-08-01
Brain-computer interfacing (BCI) based on steady-state visual evoked potentials (SSVEPs) is one of the most practical BCIs because of its high recognition accuracies and little training of a user. Mixed frequency and phase coding which can implement a number of commands and achieve a high information transfer rate (ITR) has recently been gaining much attention. In order to implement mixed-coded SSVEP-BCI as a reliable interface, it is important to detect commands fast and accurately. This paper presents a novel method to recognize mixed-coded SSVEPs which achieves high performance. The method employs multiset canonical correlation analysis to obtain spatial filters which enhance SSVEP components. An experiment with a mixed-coded SSVEP-BCI was conducted to evaluate performance of the proposed method compared with the previous work. The experimental results showed that the proposed method achieved significantly higher command recognition accuracy and ITR than the state-of-the-art.
Liu, Xuan; Ramella-Roman, Jessica C; Huang, Yong; Guo, Yuan; Kang, Jin U
2013-01-01
In this study, we propose a generic speckle simulation for optical coherence tomography (OCT) signal, by convolving the point-spread function (PSF) of the OCT system with the numerically synthesized random sample field. We validate our model and use the simulation method to study the statistical properties of cross-correlation coefficients between A-scans, which have been recently applied in transverse motion analysis by our group. The results of simulation show that oversampling is essential for accurate motion tracking; exponential decay of OCT signal leads to an underestimate of motion that can be corrected; lateral heterogeneity of sample leads to an overestimate of motion for a few pixels corresponding to the structural boundary.
Minimum variance imaging based on correlation analysis of Lamb wave signals.
Hua, Jiadong; Lin, Jing; Zeng, Liang; Luo, Zhi
2016-08-01
In Lamb wave imaging, MVDR (minimum variance distortionless response) is a promising approach for the detection and monitoring of large areas with sparse transducer network. Previous studies in MVDR use signal amplitude as the input damage feature, and the imaging performance is closely related to the evaluation accuracy of the scattering characteristic. However, scattering characteristic is highly dependent on damage parameters (e.g. type, orientation and size), which are unknown beforehand. The evaluation error can degrade imaging performance severely. In this study, a more reliable damage feature, LSCC (local signal correlation coefficient), is established to replace signal amplitude. In comparison with signal amplitude, one attractive feature of LSCC is its independence of damage parameters. Therefore, LSCC model in the transducer network could be accurately evaluated, the imaging performance is improved subsequently. Both theoretical analysis and experimental investigation are given to validate the effectiveness of the LSCC-based MVDR algorithm in improving imaging performance.
Statistical anomalies in 2011-2012 Russian elections revealed by 2D correlation analysis
Kobak, Dmitry; Pshenichnikov, Maxim S
2012-01-01
Here we perform a statistical analysis of the official data from recent Russian parliamentary and presidential elections (held on December 4th, 2011 and March 4th, 2012, respectively). A number of anomalies are identified that persistently skew the results in favour of the pro-government party, United Russia (UR), and its leader Vladimir Putin. The main irregularities are: (i) remarkably high correlation between turnout and voting results; (ii) a large number of polling stations where the UR/Putin results are given by a round number of percent; (iii) constituencies showing improbably low or (iv) anomalously high dispersion of results across polling stations; (v) substantial difference between results at paper-based and electronic polling stations. These anomalies, albeit less prominent in the presidential elections, hardly conform to the assumptions of fair and free voting. The approaches proposed here can be readily extended to quantify fingerprints of electoral fraud in any other problematic elections.
Directory of Open Access Journals (Sweden)
Ignacio Santamaría
2008-04-01
Full Text Available This paper treats the identification of nonlinear systems that consist of a cascade of a linear channel and a nonlinearity, such as the well-known Wiener and Hammerstein systems. In particular, we follow a supervised identification approach that simultaneously identifies both parts of the nonlinear system. Given the correct restrictions on the identification problem, we show how kernel canonical correlation analysis (KCCA emerges as the logical solution to this problem. We then extend the proposed identification algorithm to an adaptive version allowing to deal with time-varying systems. In order to avoid overfitting problems, we discuss and compare three possible regularization techniques for both the batch and the adaptive versions of the proposed algorithm. Simulations are included to demonstrate the effectiveness of the presented algorithm.
Chen, Zhiwen
2017-01-01
Zhiwen Chen aims to develop advanced fault detection (FD) methods for the monitoring of industrial processes. With the ever increasing demands on reliability and safety in industrial processes, fault detection has become an important issue. Although the model-based fault detection theory has been well studied in the past decades, its applications are limited to large-scale industrial processes because it is difficult to build accurate models. Furthermore, motivated by the limitations of existing data-driven FD methods, novel canonical correlation analysis (CCA) and projection-based methods are proposed from the perspectives of process input and output data, less engineering effort and wide application scope. For performance evaluation of FD methods, a new index is also developed. Contents A New Index for Performance Evaluation of FD Methods CCA-based FD Method for the Monitoring of Stationary Processes Projection-based FD Method for the Monitoring of Dynamic Processes Benchmark Study and Real-Time Implementat...
Correlation dimension analysis and capillary wave turbulence in Dragon-Wash phenomena
Peng, Huai-Wu; Li, Rui-Qu; Chen, Song-Ze; Li, Cun-Biao
2008-02-01
This paper describes the evolution of surface capillary waves of deep water excited by gradually increasing the lateral external force at a single frequency. The vertical velocities of the water surface are measured by using a Polytec Laser Vibrometer with a thin layer of aluminium powder scattering on the surface to reflect the laser beam. Nonlinear interaction processes result in a stationary Fourier spectrum of the vertical surface velocities (the same as the surface elevation), i.e. Iω ~ ω-3.5. The observed spectrum can be interpreted as a wave-turbulent Kolmogorov spectrum for the case of 'narrowband pumping' for a direct cascade of energy. Correlation dimension analysis of the whole development process reveals four distinct stages during the wave structure development and identifies the wave turbulence stage.
Choi, Bo-Hun; Kwon, Il-Bum
2014-01-01
A time-division Brillouin optical correlation domain analysis system was successfully achieved using simplified laser diode (LD) modulation and pump lightwave optimization. A complicated transfer function for a precise output waveform of a LD was required for the conventional system. However, a very simple modulation function gave a power output very close to a required ideal rectangle waveform without sacrificing optical output spectrum. An electrical input waveform applied into a gate in the pump lightwave path was also optimized for eliminating a probe lightwave included in a pump lightwave and for passing consecutive pump pulses alternatively. So the stimulated Brillouin scattering gain was attained without seriously distorting FM modulation, and the targeted spatial resolution was clearly accomplished. Additionally, using high speed response of a semiconductor optical amplifier (SOA), unlike an erbium-doped fiber amplifier (EDFA), the possibility was investigated that an SOA was going to replace an EDFA and a modulator used as a gate in the same time.
Correlation dimension analysis and capillary wave turbulence in Dragon-Wash phenomena
Institute of Scientific and Technical Information of China (English)
Peng Huai-Wu; Li Rui-Qu; Chen Song-Ze; Li Cun-Biao
2008-01-01
This paper describes the evolution of surface capillary waves of deep water excited by gradually increasing the lateral external force at a single frequency.The vertical velocities of the water surface are measured by using a Polytec Laser Vibrometer with a thin layer of aluminium powder scattering on the surface to reflect the laser beam.Nonlinear interaction processes result in a stationary Fourier spectrum of the vertical surface velocities (the same as the surface elevation),i.e.Iω～ω-3.5.The observed spectrum can be interpreted as a wave-turbulent Kolmogorov spectrum for the case of 'narrowband pumping' for a direct cascade of energy.Correlation dimension analysis of the whole development process reveals four distinct stages during the wave structure development and identifies the wave turbulence stage.
Zhang, Chen-lu; Liang, Zong-suo; Guo, Hong-bo; Liu, Jing-ling; Liu, Yan; Liu, Feng-hua; Wei, Lang-zhu
2015-02-01
In this study, the growth and accumulation of active components of Salvia miltiorrhiza in twenty two experimental sites which crossing through three typical climate zones. The S. miltiorrhiza seedlings with the same genotype were planted in each site in spring, which were cultivated in fields with uniform management during their growing seasons till to harvest. The diterpene ketones (dihydrotanshinone, cryptotanshinone, tanshinone I and tanshinone II(A)) in S. miltiorrhiza root samples were determined by using high-performance liquid chromatography (HPLC) method. The biomass of root (root length, number of root branches, root width and dry weight) was also measured. The results showed that tanshinone II(A) in all samples of each site were higher than the standards required by China Pharmacopoeia. It has been found there is a relationship between root shape and climate change. The correlation analysis between active components and meteorological factors showed that the accumulation of tanshinones were effected by such meteorological factors as average relative humidity from April to October > average vapor pressure from April to October > average temperature difference day and night from April to October > annual average temperature and so on. The correlation analysis between root biomass and meteorological factors exhibited that root shape and accumulation of dry matter were affected by those factors, such as average annual aboveground (0-20 cm) temperature from April to October > annual average temperature > average vapor pressure from April to October > annual active accumulated temperature > annual average temperature > average vapor pressure from April to October. The accumulation of tanshinones and biomass was increased with the decrease of latitude. At the same time, the dry matter and diameter of root decreased if altitude rises. In addition, S. miltiorrhiza required sunlight is not sophisticated, when compared with humid and temperature. To sum up, S
Xi, Caiping; Zhang, Shuning; Xiong, Gang; Zhao, Huichang; Yang, Yonghong
2017-02-01
Many complex systems generate multifractal time series which are long-range cross-correlated. This paper introduces three multifractal cross-correlation analysis methods, such as multifractal cross-correlation analysis based on the partition function approach (MFXPF), multifractal detrended cross-correlation analysis (MFDCCA) methods based on detrended fluctuation analysis (MFXDFA) and detrended moving average analysis (MFXDMA), which only consider one moment order. We do comparative analysis of the artificial time series (binomial multiplicative cascades and Cantor sets with different probabilities) by these methods. Then we do a feasibility test of the fixed threshold target detection within sea clutter by applying the multifractal cross-correlation analysis methods to the IPIX radar sea clutter data. The results show that it is feasible to use the method of the fixed threshold based on the multifractal feature parameter Δf(α) by the MFXPF and MFXDFA-1 methods. At last, we give the main conclusions and provide a valuable reference on how to choose the multifractal algorithms, the detection parameters and the target detection methods within sea clutter in practice.
Correlation Relationship of Performance Shaping Factors (PSFs) for Human Reliability Analysis
Energy Technology Data Exchange (ETDEWEB)
Bheka, M. Khumalo; Kim, Jonghyun [KEPCO International Nuclear Graduate School, Ulsan (Korea, Republic of)
2014-10-15
between PSFs using correlation analysis and identify patterns in the PSFs using Principal Factor Analysis (PFA). The study is specifically based on Operational Performance Information Systems (OPIS) database. This study was conducted to determine causal relationships between PSFs and also find sets of PSFs (error forcing context) which contribute more to human error probabilities. These goals were achieved using correlation and principal factor analysis.
Xiang, Zhiming; Liang, Qianwen; Liang, Changhong; Zhong, Guimian
2014-12-01
Our objective is to explore the value of liver cancer contrast-enhanced ultrasound (CEUS) and MRI perfusion quantitative analysis in liver cancer and the correlation between these two analysis methods. Rabbit VX2 liver cancer model was established in this study. CEUS was applied. Sono Vue was applied in rabbits by ear vein to dynamically observe and record the blood perfusion and changes in the process of VX2 liver cancer and surrounding tissue. MRI perfusion quantitative analysis was used to analyze the mean enhancement time and change law of maximal slope increasing, which were further compared with the pathological examination results. Quantitative indicators of liver cancer CEUS and MRI perfusion quantitative analysis were compared, and the correlation between them was analyzed by correlation analysis. Rabbit VX2 liver cancer model was successfully established. CEUS showed that time-intensity curve of rabbit VX2 liver cancer showed "fast in, fast out" model while MRI perfusion quantitative analysis showed that quantitative parameter MTE of tumor tissue increased and MSI decreased: the difference was statistically significant (P 0.05). However, the quantitative parameter of them were significantly positively correlated (P liver cancer lesion and surrounding liver parenchyma, and the quantitative parameters of them are correlated. The combined application of both is of importance in early diagnosis of liver cancer.
Nonlinear Analysis and Post-Test Correlation for a Curved PRSEUS Panel
Gould, Kevin; Lovejoy, Andrew E.; Jegley, Dawn; Neal, Albert L.; Linton, Kim, A.; Bergan, Andrew C.; Bakuckas, John G., Jr.
2013-01-01
The Pultruded Rod Stitched Efficient Unitized Structure (PRSEUS) concept, developed by The Boeing Company, has been extensively studied as part of the National Aeronautics and Space Administration's (NASA s) Environmentally Responsible Aviation (ERA) Program. The PRSEUS concept provides a light-weight alternative to aluminum or traditional composite design concepts and is applicable to traditional-shaped fuselage barrels and wings, as well as advanced configurations such as a hybrid wing body or truss braced wings. Therefore, NASA, the Federal Aviation Administration (FAA) and The Boeing Company partnered in an effort to assess the performance and damage arrestments capabilities of a PRSEUS concept panel using a full-scale curved panel in the FAA Full-Scale Aircraft Structural Test Evaluation and Research (FASTER) facility. Testing was conducted in the FASTER facility by subjecting the panel to axial tension loads applied to the ends of the panel, internal pressure, and combined axial tension and internal pressure loadings. Additionally, reactive hoop loads were applied to the skin and frames of the panel along its edges. The panel successfully supported the required design loads in the pristine condition and with a severed stiffener. The panel also demonstrated that the PRSEUS concept could arrest the progression of damage including crack arrestment and crack turning. This paper presents the nonlinear post-test analysis and correlation with test results for the curved PRSEUS panel. It is shown that nonlinear analysis can accurately calculate the behavior of a PRSEUS panel under tension, pressure and combined loading conditions.
Gligor, M
2006-01-01
The statistical distances between countries, calculated for various moving average time windows, are mapped into the ultrametric subdominant space as in classical Minimal Spanning Tree methods. The Moving Average Minimal Length Path (MAMLP) algorithm allows a decoupling of fluctuations with respect to the mass center of the system from the movement of the mass center itself. A Hamiltonian representation given by a factor graph is used and plays the role of cost function. The present analysis pertains to 11 macroeconomic (ME) indicators, namely the GDP (x1), Final Consumption Expenditure (x2), Gross Capital Formation (x3), Net Exports (x4), Consumer Price Index (y1), Rates of Interest of the Central Banks (y2), Labour Force (z1), Unemployment (z2), GDP/hour worked (z3), GDP/capita (w1) and Gini coefficient (w2). The target group of countries is composed of 15 EU countries, data taken between 1995 and 2004. By two different methods (the Bipartite Factor Graph Analysis and the Correlation Matrix Eigensystem Anal...
Analysis of correlations between protein complex and protein-protein interaction and mRNA expression
Institute of Scientific and Technical Information of China (English)
CAI Lun; XUE Hong; LU Hongchao; ZHAO Yi; ZHU Xiaopeng; BU Dongbo; LING Lunjiang; CHEN Runsheng
2003-01-01
Protein-protein interaction is a physical interaction of two proteins in living cells. In budding yeast Saccharomyces cerevisiae, large-scale protein-protein interaction data have been obtained through high-throughput yeast two-hybrid systems (Y2H) and protein complex purification techniques based on mass-spectrometry. Here, we collect 11855 interactions between total 2617 proteins. Through seriate genome-wide mRNA expression data, similarity between two genes could be measured. Protein complex data can also be obtained publicly and can be translated to pair relationship that any two proteins can only exist in the same complex or not. Analysis of protein complex data, protein-protein interaction data and mRNA expression data can elucidate correlations between them. The results show that proteins that have interactions or similar expression patterns have a higher possibility to be in the same protein complex than randomized selected proteins, and proteins which have interactions and similar expression patterns are even more possible to exist in the same protein complex. The work indicates that comprehensive integration and analysis of public large-scale bioinformatical data, such as protein complex data, protein-protein interaction data and mRNA expression data, may help to uncover their relationships and common biological information underlying these data. The strategies described here may help to integrate and analyze other functional genomic and proteomic data, such as gene expression profiling, protein-localization mapping and large-scale phenotypic data, both in yeast and in other organisms.
Barufaldi, Bruno; Lau, Kristen C.; Schiabel, Homero; Maidment, D. A.
2015-03-01
Routine performance of basic test procedures and dose measurements are essential for assuring high quality of mammograms. International guidelines recommend that breast care providers ascertain that mammography systems produce a constant high quality image, using as low a radiation dose as is reasonably achievable. The main purpose of this research is to develop a framework to monitor radiation dose and image quality in a mixed breast screening and diagnostic imaging environment using an automated tracking system. This study presents a module of this framework, consisting of a computerized system to measure the image quality of the American College of Radiology mammography accreditation phantom. The methods developed combine correlation approaches, matched filters, and data mining techniques. These methods have been used to analyze radiological images of the accreditation phantom. The classification of structures of interest is based upon reports produced by four trained readers. As previously reported, human observers demonstrate great variation in their analysis due to the subjectivity of human visual inspection. The software tool was trained with three sets of 60 phantom images in order to generate decision trees using the software WEKA (Waikato Environment for Knowledge Analysis). When tested with 240 images during the classification step, the tool correctly classified 88%, 99%, and 98%, of fibers, speck groups and masses, respectively. The variation between the computer classification and human reading was comparable to the variation between human readers. This computerized system not only automates the quality control procedure in mammography, but also decreases the subjectivity in the expert evaluation of the phantom images.
Westgate, Philip M; Braun, Thomas M
2013-08-30
Generalized estimating equations (GEE) are commonly employed for the analysis of correlated data. However, the quadratic inference function (QIF) method is increasing in popularity because of its multiple theoretical advantages over GEE. We base our focus on the fact that the QIF method is more efficient than GEE when the working covariance structure for the data is misspecified. It has been shown that because of the use of an empirical weighting covariance matrix inside its estimating equations, the QIF method's realized estimation performance can potentially be inferior to GEE's when the number of independent clusters is not large. We therefore propose an alternative weighting matrix for the QIF, which asymptotically is an optimally weighted combination of the empirical covariance matrix and its model-based version, which is derived by minimizing its expected quadratic loss. Use of the proposed weighting matrix maintains the large-sample advantages the QIF approach has over GEE and, as shown via simulation, improves small-sample parameter estimation. We also illustrated the proposed method in the analysis of a longitudinal study. Copyright © 2012 John Wiley & Sons, Ltd.
VOLUME STUDY WITH HIGH DENSITY OF PARTICLES BASED ON CONTOUR AND CORRELATION IMAGE ANALYSIS
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Tatyana Yu. Nikolaeva
2014-11-01
Full Text Available The subject of study is the techniques of particle statistics evaluation, in particular, processing methods of particle images obtained by coherent illumination. This paper considers the problem of recognition and statistical accounting for individual images of small scattering particles in an arbitrary section of the volume in case of high concentrations. For automatic recognition of focused particles images, a special algorithm for statistical analysis based on contouring and thresholding was used. By means of the mathematical formalism of the scalar diffraction theory, coherent images of the particles formed by the optical system with high numerical aperture were simulated. Numerical testing of the method proposed for the cases of different concentrations and distributions of particles in the volume was performed. As a result, distributions of density and mass fraction of the particles were obtained, and the efficiency of the method in case of different concentrations of particles was evaluated. At high concentrations, the effect of coherent superposition of the particles from the adjacent planes strengthens, which makes it difficult to recognize images of particles using the algorithm considered in the paper. In this case, we propose to supplement the method with calculating the cross-correlation function of particle images from adjacent segments of the volume, and evaluating the ratio between the height of the correlation peak and the height of the function pedestal in the case of different distribution characters. The method of statistical accounting of particles considered in this paper is of practical importance in the study of volume with particles of different nature, for example, in problems of biology and oceanography. Effective work in the regime of high concentrations expands the limits of applicability of these methods for practically important cases and helps to optimize determination time of the distribution character and
Rogoza-Mateja, Wiesława; Domagala, Pawel; Kaczmarczyk, Mariusz; Mieżyńska-Kurtycz, Joanna; Ławniczak, Małgorzata; Sulżyc-Bielicka, Violetta; Bielicki, Dariusz; Karpińska-Kaczmarczyk, Katarzyna; Domagala, Wenancjusz
2017-02-01
The correlation of thymidylate synthase (TS) expression in gastric cancers with tumor histology and prognostic or predictive information remains unclear. Most studies have involved Asian populations, with few conducted in European cohorts. Moreover, all published studies analyze TS expression using semi-quantitative methods. This retrospective study evaluated the association of TS expression in tumor cells with gastric carcinoma histological type, with selected clinicopathological parameters, and with the prognosis of patients who underwent surgical treatment. TS expression was detected using immunochemistry and objectively assessed by computerized image analysis of tumor cells in 100 gastric cancers. We found that high TS expression was significantly more common in intestinal than in diffuse type of gastric cancer according to Lauren classification (P=0.0003); in type I carcinomas compared to type IV according to Goseki classification (P=0.002); and in gastric cancers in men than women (P=0.04). Low TS expression was found more often in carcinomas in the middle and lower third of the stomach than in cancers in the upper third of the stomach (P=0.009 and P=0.001, respectively). In the subgroup of 25 patients without lymph node metastases (stage I+II), high TS expression was associated with better DFS (83% for high TS expression versus 38,5% for low TS expression, P=0.03). The results (1) indicate significant correlation between the Lauren and Goseki histopathological classifications of gastric cancer and TS expression in tumor cells, (2) suggest that high TS expression may be a positive prognostic marker with regard to DFS in patients with gastric cancer without involvement of regional lymph nodes who underwent radical surgical treatment and were not treated with preoperative chemotherapy. Prognostic results need confirmation in larger cohorts.
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Stojanovic Zlatan
2014-04-01
Full Text Available Introduction: Knowledge of etiopathogenesis of post-stroke depressive phenomena contributes to early diagnostics which shortens recovery to a great extent and suits the social and professional rehabilitation of patients, if followed by proper psycho/pharmacotherapy. The aim of this work is to research dependence of depressive manifestations considering the size and anatomical localization of lesion. Subjects and Methods: The research included 118 patients with stroke. Lesion localization was defined on computerized axial tomography records, whereas the area and perimeter of lesion were measured by AutoCAD 2004 software. Examinations by means of Hamilton Rating Scale for Depression were carried out by the method of random selection 11–40 days after stroke. Correlation analysis was made by simple linear/nonlinear regression and Cox’s hazard regression model. Results: Negative correlation was observed between the intensity of depressive manifestations and the size of cerebrovascular lesion (Spearman’s r= – 0.263, P= 0.004. By means of Cox’s regression model we determined 4.389 times higher risk for depression occurrence in female patients (P< 0.001, as well as higher risk due to lobus limbicus structure damages (hazard ratio eb(HR = 2.661, P= 0.019. Conclusion: Lower intensity of depressive manifestations with larger cerebrovascular lesions, we have explained by activation of reparation mechanisms with energy savings and decrease (due to neurological deficits of afferent peripheral sensations which antecedent the occurrence of emotions (James-Lange peripheral theory of emotions.
Frankel, Adam; Armour, Nicola; Nancarrow, Derek; Krause, Lutz; Hayward, Nicholas; Lampe, Guy; Smithers, B Mark; Barbour, Andrew
2014-04-01
The incidence of esophageal adenocarcinoma (EAC) has been increasing rapidly for the past 3 decades in Western (Caucasian) populations. Curative treatment is based around esophagectomy, which has a major impact on quality of life. For those suitable for treatment with curative intent, 5-year survival is ∼30%. More accurate prognostic tools are therefore needed, and copy number aberrations (CNAs) may offer the ability to act as prospective biomarkers in this regard. We performed a genome-wide examination of CNAs in 54 samples of EAC using single-nucleotide polymorphism (SNP) arrays. Our aims were to describe frequent regions of CNA, to define driver CNAs, and to identify CNAs that correlated with survival. Regions of frequent amplification included oncogenes such as EGFR, MYC, KLF12, and ERBB2, while frequently deleted regions included tumor suppressor genes such as CDKN2A/B, PTPRD, FHIT, and SMAD4. The genomic identification of significant targets in cancer (GISTIC) algorithm identified 24 regions of gain and 28 regions of loss that were likely to contain driver changes. We discovered 61 genes in five regions that, when stratified by CNA type (gain or loss), correlated with a statistically significant difference in survival. Pathway analysis of the genes residing in both the GISTIC and prognostic regions showed they were significantly enriched for cancer-related networks. Finally, we discovered that copy-neutral loss of heterozygosity is a frequent mechanism of CNA in genes currently targetable by chemotherapy, potentially leading to under-reporting of cases suitable for such treatment. Copyright © 2014 Wiley Periodicals, Inc.
G7 country Gross Domestic Product (GDP) time correlations. A graph network analysis
Mi'skiewicz, J
2005-01-01
The correlation between G7 countries has been analysed on the basis of Gross Domestic Product using different distance functions i.e. discrete, linear correlation and distribution distance. The distance matrics is analysed by various graph methods and the percolation threshold is calculated. The globalization process understood as increas of correlation has been observed. The applications of different distance function discussed.
Frequency domain analysis of errors in cross-correlations of ambient seismic noise
Liu, Xin; Ben-Zion, Yehuda; Zigone, Dimitri
2016-12-01
We analyse random errors (variances) in cross-correlations of ambient seismic noise in the frequency domain, which differ from previous time domain methods. Extending previous theoretical results on ensemble averaged cross-spectrum, we estimate confidence interval of stacked cross-spectrum of finite amount of data at each frequency using non-overlapping windows with fixed length. The extended theory also connects amplitude and phase variances with the variance of each complex spectrum value. Analysis of synthetic stationary ambient noise is used to estimate the confidence interval of stacked cross-spectrum obtained with different length of noise data corresponding to different number of evenly spaced windows of the same duration. This method allows estimating Signal/Noise Ratio (SNR) of noise cross-correlation in the frequency domain, without specifying filter bandwidth or signal/noise windows that are needed for time domain SNR estimations. Based on synthetic ambient noise data, we also compare the probability distributions, causal part amplitude and SNR of stacked cross-spectrum function using one-bit normalization or pre-whitening with those obtained without these pre-processing steps. Natural continuous noise records contain both ambient noise and small earthquakes that are inseparable from the noise with the existing pre-processing steps. Using probability distributions of random cross-spectrum values based on the theoretical results provides an effective way to exclude such small earthquakes, and additional data segments (outliers) contaminated by signals of different statistics (e.g. rain, cultural noise), from continuous noise waveforms. This technique is applied to constrain values and uncertainties of amplitude and phase velocity of stacked noise cross-spectrum at different frequencies, using data from southern California at both regional scale (˜35 km) and dense linear array (˜20 m) across the plate-boundary faults. A block bootstrap resampling method
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Ju-Yeun Lee
Full Text Available The aims of this study were 1 To evaluate retinal nerve fiber layer (fRNFL thickness and ganglion cell layer plus inner plexiform layer (GCIPL thickness at the fovea in eyes affected with traumatic optic neuropathy (TON compared with contralateral normal eyes, 2 to further evaluate these thicknesses within 3 weeks following trauma (defined as "early TON", and 3 to investigate the relationship between these retinal layer thicknesses and visual function in TON eyes. Twenty-nine patients with unilateral TON were included. Horizontal and vertical spectral-domain optical coherence tomography (SD-OCT scans of the fovea were taken in patients with unilateral TON. The main outcome measure was thickness of the entire retina, fRNFL, and GCIPL in eight areas. Thickness of each retinal layer was compared between affected and unaffected eyes. The correlation between the thickness of each retinal layer and visual function parameters, including best corrected visual acuity, color vision, P100 latency, and P100 amplitude in visual evoked potential (VEP, mean deviation (MD and visual field index (VFI in Humphrey visual field analysis in TON eyes was analyzed. Thicknesses of the entire retina, fRNFL, and GCIPL in SD-OCT were significantly thinner (3-36% in all measurement areas of TON eyes compared to those in healthy eyes (all p<0.05. Whereas, only GCIPL in the outer nasal, superior, and inferior areas was significantly thinner (5-10% in the early TON eyes than that in the control eyes (all p<0.01. A significant correlation was detected between retinal layer thicknesses and visual function parameters including color vision, P100 latency and P100 amplitude in VEP, MD, and VFI (particularly P100 latency, MD, and VFI (r = -0.70 to 0.84. Among the retinal layers analyzed in this study, GCIPL (particularly in the superior and inferior areas was most correlated with these five visual function parameters (r = -0.70 to 0.71. Therefore, evaluation of morphological change
Correlates of physician burnout across regions and specialties: a meta-analysis
2013-01-01
Background Health care organizations globally realize the need to address physician burnout due to its close linkages with quality of care, retention and migration. The many functions of health human resources include identifying and managing burnout risk factors for health professionals, while also promoting effective coping. Our study of physician burnout aims to show: (1) which correlates are most strongly associated with emotional exhaustion (EE) and depersonalization (DP), and (2) whether the associations vary across regions and specialties. Methods Meta-analysis allowed us to examine a diverse range of correlates. Our search yielded 65 samples of physicians from various regions and specialties. Results EE was negatively associated with autonomy, positive work attitudes, and quality and safety culture. It was positively associated with workload, constraining organizational structure, incivility/conflicts/violence, low quality and safety standards, negative work attitudes, work-life conflict, and contributors to poor mental health. We found a similar but weaker pattern of associations for DP. Physicians in the Americas experienced lower EE levels than physicians in Europe when quality and safety culture and career development opportunities were both strong, and when they used problem-focused coping. The former experienced higher EE levels when work-life conflict was strong and they used ineffective coping. Physicians in Europe experienced lower EE levels than physicians in the Americas with positive work attitudes. We found a similar but weaker pattern of associations for DP. Outpatient specialties experienced higher EE levels than inpatient specialties when organization structures were constraining and contributors to poor mental health were present. The former experienced lower EE levels when autonomy was present. Inpatient specialties experienced lower EE levels than outpatient specialties with positive work attitudes. As above, we found a similar but weaker
Directory of Open Access Journals (Sweden)
Eszter Katalin Bognár
2016-06-01
Full Text Available The aim of this article is to introduce a system that is capable of collecting and analyzing different types of financial data to support traders in their decision - making. Oracle’s Big Data platform Oracle Advanced Analytics was utilized, which extends the Oracle Database with Oracle R, thus providing the opportunity to run embedded R scripts on the database server to speed up data processing. The extract, transform and load (ETL process was combined with a dictionary - based sentiment analysis module to examine cross - correlation and causality between numerical and textual financial data for a 10 week period. A notable correlation (0.42 was found between daily news sentiment scores and daily stock returns. By applying cross - correlation analysis and Granger causality testing, the results show that the news’ impact is incorporated into stock prices rapidly, having the highest correlation on the first day, while the returns’ impact on market sentiment is seen only after a few days.
Li, Liang; Yang, Shi-Long; Liu, Yu-Jie; Wsng, Yun-Wei; Zhong, Lian; Ai, Li
2014-09-01
In order to investigate the mechanism, the correlation between the odor change in Crataegi Fructus stir-fried process and 5-HMF were studied. Required samples were retrieved from Crataegi Fructus stir-fried process. Statistical quality control (SQC) was used to analyze the response values acquired by the electronic nose. At the same time, the content of 5-HMF was detected by high performance liquid chromatography (HPLC). Correlation analysis was used to analyze the relationship between the above two. Experimental results showed that SQC model established by response values of all samples could show the change law of odor in Crataegi Fructus stir-fried process and changes of 5-HMF content was dropped after the first increase. Correlation analysis showed that the odor change in Crataegi Fructus stir-fried process and 5-HMF were significantly correlated (P process.
Regina Helena Lourenço Belluzzo; Kurt Faltin Jr.; Cristina Ortolani; Adolpho Chelotti
2013-01-01
INTRODUCTION: Currently in orthodontic diagnosis, besides the lateral cephalometric analysis which evaluates the anteroposterior and vertical direction, the frontal analysis may be added, leading us to another important dimension in space: the transverse dimension. OBJECTIVE: Few longitudinal samples with the frontal radiograph were published, so this cephalometric study was designed to correlate the transversal and vertical measures by Ricketts-Faltin frontal analysis into two radiographic t...
Feasibility study of parallel optical correlation-decoding analysis of lightning
Energy Technology Data Exchange (ETDEWEB)
Descour, M.R. [Univ. of Arizona, Tucson, AZ (United States); Sweatt, W.C.; Elliott, G.R.; Yee, M.L. [Sandia National Labs, Albuquerque, NM (United States)] [and others
1996-08-01
The optical correlator described in this report is intended to serve as an attention-focusing processor. The objective is to narrowly bracket the range of a parameter value that characterizes the correlator input. The input is a waveform collected by a satellite-borne receiver. In the correlator, this waveform is simultaneously correlated with an ensemble of ionosphere impulse-response functions, each corresponding to a different total-electron-count (TEC) value. We have found that correlation is an effective method of bracketing the range of TEC values likely to be represented by the input waveform. High accuracy in a computational sense is not required of the correlator. Binarization of the impulse-response functions and the input waveforms prior to correlation results in a lower correlation-peak-to-background-fluctuation (signal-to-noise) ratio than the peak that is obtained when all waveforms retain their grayscale values. The results presented in this report were obtained by means of an acousto-optic correlator previously developed at SNL as well as by simulation. An optical-processor architecture optimized for 1D correlation of long waveforms characteristic of this application is described. Discussions of correlator components, such as optics, acousto-optic cells, digital micromirror devices, laser diodes, and VCSELs are included.
Mohamed B. El Mashade
2014-01-01
This paper addresses the problem of detecting the partially-correlated χ2 fluctuating targets with two and four degrees of freedom. It presents the performance analysis, in its exact form, of GTM-CFAR processor when the operating environment is contaminated with extraneous targets and the radar receiver post-detection integrates M pulses of exponentially correlated targets. Mathematical formulas for the detection and false alarm probabilities are derived, in the absence as well as in the pres...
Cai, Chen-Bo; Xu, Lu; Han, Qing-Juan; Wu, Hai-Long; Nie, Jin-Fang; Fu, Hai-Yan; Yu, Ru-Qin
2010-05-15
The paper focuses on solving a common and important problem of NIR quantitative analysis in multi-component systems: how to significantly reduce the size of the calibration set while not impairing the predictive precision. To cope with the problem orthogonal discrete wavelet packet transform (WPT), the least correlation design and correlation coefficient test (r-test) have been combined together. As three examples, a two-component carbon tetrachloride system with 21 calibration samples, a two-component aqueous system with 21 calibration samples, and a two-component aqueous system with 41 calibration samples have been treated with the proposed strategy, respectively. In comparison with some previous methods based on much more calibration samples, the results out of the strategy showed that the predictive ability was not obviously decreased for the first system while being clearly strengthened for the second one, and the predictive precision out of the third one was even satisfactory enough for most cases of quantitative analysis. In addition, all important factors and parameters related to our strategy are discussed in detail.
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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.
Capillary Index Score and Correlation with Outcomes in Acute Ischemic Stroke: A Meta-analysis
Jagani, Manoj; Brinjikji, Waleed; Murad, Mohammad H.; Rabinstein, Alejandro A.; Cloft, Harry J.; Kallmes, David F.
2017-01-01
Background and Purpose The capillary index score (CIS) has been recently introduced as a metric for rating the collateral circulation of ischemic stroke patients. Multiple studies in the last five years have evaluated the correlation of good CIS with clinical outcomes and suggested the use of CIS in selecting patients for endovascular treatment. We performed a meta-analysis of these studies comparing CIS with clinical outcomes. Methods We conducted a computerized search of three databases from January 2011 to November 2015 for studies related to CIS and outcomes. A CIS = 0 or 1 is considered poor (pCIS) and a CIS = 2 or 3 is considered favorable (fCIS). Using random-effect meta-analysis, we evaluated the relationship of CIS to neurological outcome (modified Rankin scale score ≤ 2), recanalization, and post-treatment hemorrhage. Meta-regression analysis of good neurological outcome was performed for adjusting baseline National Institutes of Health Stroke Scale (NIHSS) between groups. Results Six studies totaling 338 patients (212 with fCISs and 126 with pCISs) were included in the analysis. Patients with fCIS had higher likelihood of good neurological outcome [relative risk (RR) = 3.03; confidence interval (CI) = 95%, 2.05–4.47; p < 0.001] and lower risk of post-treatment hemorrhage (RR = 0.38; CI = 95%, 0.19–0.93; p = 0.04) as compared with patients in the pCIS group. When adjusting for baseline NIHSS, patients with fCIS had higher RR of good neurological outcome when compared with those with pCIS (RR = 2.94; CI = 95%, 1.23–7, p < 0.0001). Favorable CIS was not associated with higher rates of recanalization. Conclusions Observational evidence suggests that acute ischemic stroke patients with fCIS may have higher rates of good neurological outcomes compared with patients with pCIS, independent of baseline NIHSS. CIS may be used as another tool to select patients for endovascular treatment of acute ischemic stroke.
Balint-Kurti, Gabriel G; Vasyutinskii, Oleg S
2009-12-31
A general reactive collision of the type A + B --> C + D is considered where both the collision partners (A and B) or the products (C and D) may possess internal, i.e., spin, orbital or rotational, angular momenta. Compact expressions are derived using a rigorous quantum mechanical analysis for the angular momentum anisotropy of either of the products (C or D) arising from an initially polarized distribution of the reactant angular momentum. The angular momentum distribution of the product is expressed in terms of canonical spherical tensors multiplied by anisotropy-transforming coefficients c(K(i)q(k))(K)(K(r),L). These coefficients act as transformation coefficients between the angular momentum anisotropy of the reactants and that of the product. They are independent of scattering angle but depend on the details of the scattering dynamics. The relationship between the coefficients c(K(i)q(k))(K)(K(r),L) and the body-fixed scattering S matrix is given and the methodology for the quantum mechanical calculation of the anisotropy-transforming coefficients is clearly laid out. The anisotropy-transforming coefficients are amenable to direct experimental measurement in a similar manner to vector correlation and alignment parameters in photodissociation processes. A key aspect of the theory is the use of projections of both reactant and product angular momenta onto the product recoil vector direction. An important new conservation rule is revealed through the analysis, namely that if the state multipole for reactant angular momentum distribution has a projection q(k) onto the product recoil vector the state multipoles for the product angular momentum distribution all have this same projection. Expressions are also presented for the distribution of the product angular momentum when its components are evaluated relative to the space-fixed Z-axis. Notes with detailed derivations of all the formulas are available as Supporting Information.
SATB1 is Correlated with Progression and Metastasis of Breast Cancers: A Meta-Analysis
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Zhongya Pan
2016-05-01
Full Text Available Background/Aims: Several researches have evaluated the significance of SATB1 (Special AT-rich sequence binding protein 1 expression in breast cancers (BCs, but the results have been disputed, especially in the aspects of clinicopathological features and prognosis. Therefore, our study aimed to use a meta-analysis to summarize the clinical and prognostic relevance of SATB1 gene expression in BCs. Methods: A literature search of PubMed, EMBASE, Cochrane library, Chinese Wanfang and CNKI was performed to identify eligible studies. Ten studies total, comprising 5,185 patients (1,699 SATB1-positive and 3,486 SATB1-negative, were enrolled in our study, which was performed using Revman5.3 Software and Stata11.0 Software. Results: This meta-analysis showed that the expression of SATB1 was significantly higher in breast cancer than in normal tissues (OR = 12.28; 95%CI = 6.01-25.09, and was statistically related to several clinicopathological parameters, including lymph node metastasis (OR = 1.55, 95%CI = 1.01-2.39 and Tumor Node Metastasis(TNM stage (OR = 0.35, 95%CI = 0.22-0.56. However, the level of SATB1 was not statistically associated with the age (OR = 1.13, 95%CI = 0.87-1.46, tumour size (OR = 0.72, 95%CI = 0.44-1.19, estrogen receptor (OR = 0.78, 95%CI = 0.55-1.09, progesterone receptor (OR = 0.64, 95%CI = 0.32-1.29, HER2 status (OR=1.98, 95%CI = 0.74-5.30, and histological type (OR = 0.49, 95%CI = 0.22-1.11. Conclusion: High expression of SATB1 was significantly correlated with tumourigenesis and metastasis of BCs, indicating poor prognosis for patients. SATB1 could serve as a potential marker for detection and prognosis evaluation of breast cancers.
Ouyang, Juan; Zheng, Wenli; Shen, Qi; Goswami, Maitrayee; Jorgensen, Jeffrey L; Medeiros, L Jeffrey; Wang, S A
2015-01-01
Compared with the proven utility of flow cytometry immunophenotyping (FCI) analysis in the workup of myelodysplastic syndromes (MDS), immunophenotypic alterations in myeloproliferative neoplasms (MPN) have been less studied and the potential utility of FCI is not defined. Bone marrow (BM) samples of 83 Philadelphia-negative MPN patients were assessed by multicolor FCI including 27 with essential thrombocythemia (ET); 17 polycythemia vera (PV); 33 primary myelofibrosis (PMF) and 6 MPN-unclassifiable (MPN-U). The time interval from initial diagnosis of MPN to FCI analysis was 18 months (0-370). Ninety-five age-matched MDS patients with a similar BM blast count were included for comparison. Immunophenotypic alterations, either in CD34(+) cells or myelomonocytic cells, were detected in 82 of 83 (99%) MPN cases. FCI abnormalities were more frequently observed in cases with substantial myelofibrosis but not different between PMF and fibrotic stage of ET/PV. Furthermore, FCI abnormalities were more frequent in cases with ≥5% BM blasts and/or circulating blasts (P = 0.006); as well as cases with an abnormal karyotype (P = 0.036); but not associated with morphologic dysplasia or JAK2 mutation status. Comparing with MDS, FCI abnormalities were overall less pronounced in MPN cases (P = 0.001). MPNs exhibit frequent immunophenotypic alterations, more pronounced in cases with adverse histopathologic features. These findings illustrate that immunophenotypic alterations are a part of constellational findings in MPN, and correlate progressively with disease stage. The study results also suggest a role of FCI in diagnosis of MPN and monitoring disease over time and after therapy. © 2014 International Clinical Cytometry Society.
Correlating multidimensional fetal heart rate variability analysis with acid-base balance at birth.
Frasch, Martin G; Xu, Yawen; Stampalija, Tamara; Durosier, Lucien D; Herry, Christophe; Wang, Xiaogang; Casati, Daniela; Seely, Andrew Je; Alfirevic, Zarko; Gao, Xin; Ferrazzi, Enrico
2014-12-01
Fetal monitoring during labour currently fails to accurately detect acidemia. We developed a method to assess the multidimensional properties of fetal heart rate variability (fHRV) from trans-abdominal fetal electrocardiogram (fECG) during labour. We aimed to assess this novel bioinformatics approach for correlation between fHRV and neonatal pH or base excess (BE) at birth.We enrolled a prospective pilot cohort of uncomplicated singleton pregnancies at 38-42 weeks' gestation in Milan, Italy, and Liverpool, UK. Fetal monitoring was performed by standard cardiotocography. Simultaneously, with fECG (high sampling frequency) was recorded. To ensure clinician blinding, fECG information was not displayed. Data from the last 60 min preceding onset of second-stage labour were analyzed using clinically validated continuous individualized multiorgan variability analysis (CIMVA) software in 5 min overlapping windows. CIMVA allows simultaneous calculation of 101 fHRV measures across five fHRV signal analysis domains. We validated our mathematical prediction model internally with 80:20 cross-validation split, comparing results to cord pH and BE at birth.The cohort consisted of 60 women with neonatal pH values at birth ranging from 7.44 to 6.99 and BE from -0.3 to -18.7 mmol L(-1). Our model predicted pH from 30 fHRV measures (R(2) = 0.90, P birth. Further refinement and validation in larger cohorts are needed. These new measurements of fHRV might offer a new opportunity to predict fetal acid-base balance at birth.
Analysis of Correlations between Economic Growth (Rate of Real GDP and the Underground Economy
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Pripoaie Silviu
2009-06-01
Full Text Available Analysis of performance of any economy involves the measurement and correlation of threebasic elements: the rate of economic growth, the rate of inflation and unemployment rate. When the rateof growth (rate of real GDP is high, the production of goods and services is growing and thereforeincreasing the number of jobs, decrease unemployment and raise living standards. If the economy is inrecession phase, increasing fiscal pressure to ensure the necessary budgetary funds triggers complexeconomic mechanisms. Rules more strictly is that those who are not able to operate in the normaleconomy to slide towards the underground economy, and this not because he wants to tax evasion, butbecause they simply can not cope with new regulations. It is widely accepted in economic theory andpractice the idea that reliability scale macroeconomic indicators of a country is affected by size ofunderground economy and the various tests made so far on this subject, focusing either on the socialaspect or the economic or moral, or emphasizes the illegal or the edge of legality. This has led to variousstudies in this area do not provide comparable data or provide data to the contrary. Worldwide were putin place, however, some calculation methods provided that applied the same country and same period,the results are rarely consistent, sometimes even in fundamentally different.
Extending Local Canonical Correlation Analysis to Handle General Linear Contrasts for fMRI Data
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Mingwu Jin
2012-01-01
Full Text Available Local canonical correlation analysis (CCA is a multivariate method that has been proposed to more accurately determine activation patterns in fMRI data. In its conventional formulation, CCA has several drawbacks that limit its usefulness in fMRI. A major drawback is that, unlike the general linear model (GLM, a test of general linear contrasts of the temporal regressors has not been incorporated into the CCA formalism. To overcome this drawback, a novel directional test statistic was derived using the equivalence of multivariate multiple regression (MVMR and CCA. This extension will allow CCA to be used for inference of general linear contrasts in more complicated fMRI designs without reparameterization of the design matrix and without reestimating the CCA solutions for each particular contrast of interest. With the proper constraints on the spatial coefficients of CCA, this test statistic can yield a more powerful test on the inference of evoked brain regional activations from noisy fMRI data than the conventional t-test in the GLM. The quantitative results from simulated and pseudoreal data and activation maps from fMRI data were used to demonstrate the advantage of this novel test statistic.