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Sample records for rank correlation analysis

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

    OpenAIRE

    WenJun Zhang; Xin Li

    2015-01-01

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

  2. Sparse and smooth canonical correlation analysis through rank-1 matrix approximation

    Science.gov (United States)

    Aïssa-El-Bey, Abdeldjalil; Seghouane, Abd-Krim

    2017-12-01

    Canonical correlation analysis (CCA) is a well-known technique used to characterize the relationship between two sets of multidimensional variables by finding linear combinations of variables with maximal correlation. Sparse CCA and smooth or regularized CCA are two widely used variants of CCA because of the improved interpretability of the former and the better performance of the later. So far, the cross-matrix product of the two sets of multidimensional variables has been widely used for the derivation of these variants. In this paper, two new algorithms for sparse CCA and smooth CCA are proposed. These algorithms differ from the existing ones in their derivation which is based on penalized rank-1 matrix approximation and the orthogonal projectors onto the space spanned by the two sets of multidimensional variables instead of the simple cross-matrix product. The performance and effectiveness of the proposed algorithms are tested on simulated experiments. On these results, it can be observed that they outperform the state of the art sparse CCA algorithms.

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

    OpenAIRE

    Someswara Rao, Chinta; Viswanadha Raju, S.

    2016-01-01

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

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

    Science.gov (United States)

    Someswara Rao, Chinta; Viswanadha Raju, S

    2016-03-01

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

  5. Canonical correlation analysis of professional stress,social support,and professional burnout among low-rank army officers

    Directory of Open Access Journals (Sweden)

    Chuan-yun LI

    2011-12-01

    Full Text Available Objective The present study investigates the influence of professional stress and social support on professional burnout among low-rank army officers.Methods The professional stress,social support,and professional burnout scales among low-rank army officers were used as test tools.Moreover,the officers of established units(battalion,company,and platoon were chosen as test subjects.Out of the 260 scales sent,226 effective scales were received.The descriptive statistic and canonical correlation analysis models were used to analyze the influence of each variable.Results The scores of low-rank army officers in the professional stress,social support,and professional burnout scales were more than average,except on two factors,namely,interpersonal support and de-individualization.The canonical analysis identified three groups of canonical correlation factors,of which two were up to a significant level(P < 0.001.After further eliminating the social support variable,the canonical correlation analysis of professional stress and burnout showed that the canonical correlation coefficients P corresponding to 1 and 2 were 0.62 and 0.36,respectively,and were up to a very significant level(P < 0.001.Conclusion The low-rank army officers experience higher professional stress and burnout levels,showing a lower sense of accomplishment,emotional exhaustion,and more serious depersonalization.However,social support can reduce the onset and seriousness of professional burnout among these officers by lessening pressure factors,such as career development,work features,salary conditions,and other personal factors.

  6. Rank reduction of correlation matrices by majorization

    NARCIS (Netherlands)

    R. Pietersz (Raoul); P.J.F. Groenen (Patrick)

    2004-01-01

    textabstractIn this paper a novel method is developed for the problem of finding a low-rank correlation matrix nearest to a given correlation matrix. The method is based on majorization and therefore it is globally convergent. The method is computationally efficient, is straightforward to implement,

  7. Estimation of rank correlation for clustered data.

    Science.gov (United States)

    Rosner, Bernard; Glynn, Robert J

    2017-06-30

    It is well known that the sample correlation coefficient (R xy ) is the maximum likelihood estimator of the Pearson correlation (ρ xy ) for independent and identically distributed (i.i.d.) bivariate normal data. However, this is not true for ophthalmologic data where X (e.g., visual acuity) and Y (e.g., visual field) are available for each eye and there is positive intraclass correlation for both X and Y in fellow eyes. In this paper, we provide a regression-based approach for obtaining the maximum likelihood estimator of ρ xy for clustered data, which can be implemented using standard mixed effects model software. This method is also extended to allow for estimation of partial correlation by controlling both X and Y for a vector U_ of other covariates. In addition, these methods can be extended to allow for estimation of rank correlation for clustered data by (i) converting ranks of both X and Y to the probit scale, (ii) estimating the Pearson correlation between probit scores for X and Y, and (iii) using the relationship between Pearson and rank correlation for bivariate normally distributed data. The validity of the methods in finite-sized samples is supported by simulation studies. Finally, two examples from ophthalmology and analgesic abuse are used to illustrate the methods. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

  8. Efficient Rank Reduction of Correlation Matrices

    NARCIS (Netherlands)

    I. Grubisic (Igor); R. Pietersz (Raoul)

    2005-01-01

    textabstractGeometric optimisation algorithms are developed that efficiently find the nearest low-rank correlation matrix. We show, in numerical tests, that our methods compare favourably to the existing methods in the literature. The connection with the Lagrange multiplier method is established,

  9. Ranking structures and rank-rank correlations of countries: The FIFA and UEFA cases

    Science.gov (United States)

    Ausloos, Marcel; Cloots, Rudi; Gadomski, Adam; Vitanov, Nikolay K.

    2014-04-01

    Ranking of agents competing with each other in complex systems may lead to paradoxes according to the pre-chosen different measures. A discussion is presented on such rank-rank, similar or not, correlations based on the case of European countries ranked by UEFA and FIFA from different soccer competitions. The first question to be answered is whether an empirical and simple law is obtained for such (self-) organizations of complex sociological systems with such different measuring schemes. It is found that the power law form is not the best description contrary to many modern expectations. The stretched exponential is much more adequate. Moreover, it is found that the measuring rules lead to some inner structures in both cases.

  10. Error analysis of stochastic gradient descent ranking.

    Science.gov (United States)

    Chen, Hong; Tang, Yi; Li, Luoqing; Yuan, Yuan; Li, Xuelong; Tang, Yuanyan

    2013-06-01

    Ranking is always an important task in machine learning and information retrieval, e.g., collaborative filtering, recommender systems, drug discovery, etc. A kernel-based stochastic gradient descent algorithm with the least squares loss is proposed for ranking in this paper. The implementation of this algorithm is simple, and an expression of the solution is derived via a sampling operator and an integral operator. An explicit convergence rate for leaning a ranking function is given in terms of the suitable choices of the step size and the regularization parameter. The analysis technique used here is capacity independent and is novel in error analysis of ranking learning. Experimental results on real-world data have shown the effectiveness of the proposed algorithm in ranking tasks, which verifies the theoretical analysis in ranking error.

  11. Correlation of Cognitive Abilities Level, Age and Ranks in Judo

    Directory of Open Access Journals (Sweden)

    Kraček Stanislav

    2016-11-01

    Full Text Available The aim of this paper is to ascertain the correlation between selected cognitive abilities, age and performance of judokas according to ranking. The study group consisted of judokas in the age group 18 ± 2.4 years. The Stroop Color-Word Test - Victoria Version (VST was the instrument used to determine the level of cognitive abilities. The data obtained were measured by the Pearson Correlation (r correlation test. The results of the study show an associative relationship of indirect correlation (p < 0.01 between age and all of the three categories of the Stroop test. This is an indirect correlation, so the higher the age, the lower the time (better performance of the probands in the Stroop test. There was no statistically significant correlation between performance in the categories of the Stroop test and rankings. The outcomes show that the level of selected cognitive abilities depends on age, but the level of the selected cognitive abilities does not affect the ranking of the judokas.

  12. PageRank, HITS and a unified framework for link analysis

    Energy Technology Data Exchange (ETDEWEB)

    Ding, Chris; He, Xiaofeng; Husbands, Parry; Zha, Hongyuan; Simon, Horst

    2001-10-01

    Two popular webpage ranking algorithms are HITS and PageRank. HITS emphasizes mutual reinforcement between authority and hub webpages, while PageRank emphasizes hyperlink weight normalization and web surfing based on random walk models. We systematically generalize/combine these concepts into a unified framework. The ranking framework contains a large algorithm space; HITS and PageRank are two extreme ends in this space. We study several normalized ranking algorithms which are intermediate between HITS and PageRank, and obtain closed-form solutions. We show that, to first order approximation, all ranking algorithms in this framework, including PageRank and HITS, lead to same ranking which is highly correlated with ranking by indegree. These results support the notion that in web resource ranking indegree and outdegree are of fundamental importance. Rankings of webgraphs of different sizes and queries are presented to illustrate our analysis.

  13. Eliciting conditional and unconditional rank correlations from conditional probabilities

    International Nuclear Information System (INIS)

    Morales, O.; Kurowicka, D.; Roelen, A.

    2008-01-01

    Causes of uncertainties may be interrelated and may introduce dependencies. Ignoring these dependencies may lead to large errors. A number of graphical models in probability theory such as dependence trees, vines and (continuous) Bayesian belief nets [Cooke RM. Markov and entropy properties of tree and vine-dependent variables. In: Proceedings of the ASA section on Bayesian statistical science, 1997; Kurowicka D, Cooke RM. Distribution-free continuous Bayesian belief nets. In: Proceedings of mathematical methods in reliability conference, 2004; Bedford TJ, Cooke RM. Vines-a new graphical model for dependent random variables. Ann Stat 2002; 30(4):1031-68; Kurowicka D, Cooke RM. Uncertainty analysis with high dimensional dependence modelling. New York: Wiley; 2006; Hanea AM, et al. Hybrid methods for quantifying and analyzing Bayesian belief nets. In: Proceedings of the 2005 ENBIS5 conference, 2005; Shachter RD, Kenley CR. Gaussian influence diagrams. Manage Sci 1998; 35(5) .] have been developed to capture dependencies between random variables. The input for these models are various marginal distributions and dependence information, usually in the form of conditional rank correlations. Often expert elicitation is required. This paper focuses on dependence representation, and dependence elicitation. The techniques presented are illustrated with an application from aviation safety

  14. Data envelopment analysis of randomized ranks

    Directory of Open Access Journals (Sweden)

    Sant'Anna Annibal P.

    2002-01-01

    Full Text Available Probabilities and odds, derived from vectors of ranks, are here compared as measures of efficiency of decision-making units (DMUs. These measures are computed with the goal of providing preliminary information before starting a Data Envelopment Analysis (DEA or the application of any other evaluation or composition of preferences methodology. Preferences, quality and productivity evaluations are usually measured with errors or subject to influence of other random disturbances. Reducing evaluations to ranks and treating the ranks as estimates of location parameters of random variables, we are able to compute the probability of each DMU being classified as the best according to the consumption of each input and the production of each output. Employing the probabilities of being the best as efficiency measures, we stretch distances between the most efficient units. We combine these partial probabilities in a global efficiency score determined in terms of proximity to the efficiency frontier.

  15. A Comprehensive Analysis of Marketing Journal Rankings

    Science.gov (United States)

    Steward, Michelle D.; Lewis, Bruce R.

    2010-01-01

    The purpose of this study is to offer a comprehensive assessment of journal standings in Marketing from two perspectives. The discipline perspective of rankings is obtained from a collection of published journal ranking studies during the past 15 years. The studies in the published ranking stream are assessed for reliability by examining internal…

  16. RankProdIt: A web-interactive Rank Products analysis tool

    Directory of Open Access Journals (Sweden)

    Laing Emma

    2010-08-01

    Full Text Available Abstract Background The first objective of a DNA microarray experiment is typically to generate a list of genes or probes that are found to be differentially expressed or represented (in the case of comparative genomic hybridizations and/or copy number variation between two conditions or strains. Rank Products analysis comprises a robust algorithm for deriving such lists from microarray experiments that comprise small numbers of replicates, for example, less than the number required for the commonly used t-test. Currently, users wishing to apply Rank Products analysis to their own microarray data sets have been restricted to the use of command line-based software which can limit its usage within the biological community. Findings Here we have developed a web interface to existing Rank Products analysis tools allowing users to quickly process their data in an intuitive and step-wise manner to obtain the respective Rank Product or Rank Sum, probability of false prediction and p-values in a downloadable file. Conclusions The online interactive Rank Products analysis tool RankProdIt, for analysis of any data set containing measurements for multiple replicated conditions, is available at: http://strep-microarray.sbs.surrey.ac.uk/RankProducts

  17. Paired comparisons analysis: an axiomatic approach to ranking methods

    NARCIS (Netherlands)

    Gonzalez-Diaz, J.; Hendrickx, Ruud; Lohmann, E.R.M.A.

    2014-01-01

    In this paper we present an axiomatic analysis of several ranking methods for general tournaments. We find that the ranking method obtained by applying maximum likelihood to the (Zermelo-)Bradley-Terry model, the most common method in statistics and psychology, is one of the ranking methods that

  18. A study of metrics of distance and correlation between ranked lists for compositionality detection

    DEFF Research Database (Denmark)

    Lioma, Christina; Hansen, Niels Dalum

    2017-01-01

    affects the measurement of semantic similarity. We propose a new compositionality detection method that represents phrases as ranked lists of term weights. Our method approximates the semantic similarity between two ranked list representations using a range of well-known distance and correlation metrics...... of compositionality using any of the distance and correlation metrics considered....

  19. Detecting genuine multipartite correlations in terms of the rank of coefficient matrix

    International Nuclear Information System (INIS)

    Li Bo; Kwek, Leong Chuan; Fan Heng

    2012-01-01

    We propose a method to detect genuine quantum correlation for arbitrary quantum states in terms of the rank of coefficient matrices associated with the pure state. We then derive a necessary and sufficient condition for a quantum state to possess genuine correlation, namely that all corresponding coefficient matrices have rank larger than 1. We demonstrate an approach to decompose the genuine quantum correlated state with high rank coefficient matrix into the form of product states with no genuine quantum correlation for a pure state. (paper)

  20. Extreme learning machine for ranking: generalization analysis and applications.

    Science.gov (United States)

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

    2014-05-01

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

  1. Population models and simulation methods: The case of the Spearman rank correlation.

    Science.gov (United States)

    Astivia, Oscar L Olvera; Zumbo, Bruno D

    2017-11-01

    The purpose of this paper is to highlight the importance of a population model in guiding the design and interpretation of simulation studies used to investigate the Spearman rank correlation. The Spearman rank correlation has been known for over a hundred years to applied researchers and methodologists alike and is one of the most widely used non-parametric statistics. Still, certain misconceptions can be found, either explicitly or implicitly, in the published literature because a population definition for this statistic is rarely discussed within the social and behavioural sciences. By relying on copula distribution theory, a population model is presented for the Spearman rank correlation, and its properties are explored both theoretically and in a simulation study. Through the use of the Iman-Conover algorithm (which allows the user to specify the rank correlation as a population parameter), simulation studies from previously published articles are explored, and it is found that many of the conclusions purported in them regarding the nature of the Spearman correlation would change if the data-generation mechanism better matched the simulation design. More specifically, issues such as small sample bias and lack of power of the t-test and r-to-z Fisher transformation disappear when the rank correlation is calculated from data sampled where the rank correlation is the population parameter. A proof for the consistency of the sample estimate of the rank correlation is shown as well as the flexibility of the copula model to encompass results previously published in the mathematical literature. © 2017 The British Psychological Society.

  2. SibRank: Signed bipartite network analysis for neighbor-based collaborative ranking

    Science.gov (United States)

    Shams, Bita; Haratizadeh, Saman

    2016-09-01

    Collaborative ranking is an emerging field of recommender systems that utilizes users' preference data rather than rating values. Unfortunately, neighbor-based collaborative ranking has gained little attention despite its more flexibility and justifiability. This paper proposes a novel framework, called SibRank that seeks to improve the state of the art neighbor-based collaborative ranking methods. SibRank represents users' preferences as a signed bipartite network, and finds similar users, through a novel personalized ranking algorithm in signed networks.

  3. Covariate-adjusted Spearman's rank correlation with probability-scale residuals.

    Science.gov (United States)

    Liu, Qi; Li, Chun; Wanga, Valentine; Shepherd, Bryan E

    2018-06-01

    It is desirable to adjust Spearman's rank correlation for covariates, yet existing approaches have limitations. For example, the traditionally defined partial Spearman's correlation does not have a sensible population parameter, and the conditional Spearman's correlation defined with copulas cannot be easily generalized to discrete variables. We define population parameters for both partial and conditional Spearman's correlation through concordance-discordance probabilities. The definitions are natural extensions of Spearman's rank correlation in the presence of covariates and are general for any orderable random variables. We show that they can be neatly expressed using probability-scale residuals (PSRs). This connection allows us to derive simple estimators. Our partial estimator for Spearman's correlation between X and Y adjusted for Z is the correlation of PSRs from models of X on Z and of Y on Z, which is analogous to the partial Pearson's correlation derived as the correlation of observed-minus-expected residuals. Our conditional estimator is the conditional correlation of PSRs. We describe estimation and inference, and highlight the use of semiparametric cumulative probability models, which allow preservation of the rank-based nature of Spearman's correlation. We conduct simulations to evaluate the performance of our estimators and compare them with other popular measures of association, demonstrating their robustness and efficiency. We illustrate our method in two applications, a biomarker study and a large survey. © 2017, The International Biometric Society.

  4. About the use of rank transformation in sensitivity analysis of model output

    International Nuclear Information System (INIS)

    Saltelli, Andrea; Sobol', Ilya M

    1995-01-01

    Rank transformations are frequently employed in numerical experiments involving a computational model, especially in the context of sensitivity and uncertainty analyses. Response surface replacement and parameter screening are tasks which may benefit from a rank transformation. Ranks can cope with nonlinear (albeit monotonic) input-output distributions, allowing the use of linear regression techniques. Rank transformed statistics are more robust, and provide a useful solution in the presence of long tailed input and output distributions. As is known to practitioners, care must be employed when interpreting the results of such analyses, as any conclusion drawn using ranks does not translate easily to the original model. In the present note an heuristic approach is taken, to explore, by way of practical examples, the effect of a rank transformation on the outcome of a sensitivity analysis. An attempt is made to identify trends, and to correlate these effects to a model taxonomy. Employing sensitivity indices, whereby the total variance of the model output is decomposed into a sum of terms of increasing dimensionality, we show that the main effect of the rank transformation is to increase the relative weight of the first order terms (the 'main effects'), at the expense of the 'interactions' and 'higher order interactions'. As a result the influence of those parameters which influence the output mostly by way of interactions may be overlooked in an analysis based on the ranks. This difficulty increases with the dimensionality of the problem, and may lead to the failure of a rank based sensitivity analysis. We suggest that the models can be ranked, with respect to the complexity of their input-output relationship, by mean of an 'Association' index I y . I y may complement the usual model coefficient of determination R y 2 as a measure of model complexity for the purpose of uncertainty and sensitivity analysis

  5. Low-rank and sparse modeling for visual analysis

    CERN Document Server

    Fu, Yun

    2014-01-01

    This book provides a view of low-rank and sparse computing, especially approximation, recovery, representation, scaling, coding, embedding and learning among unconstrained visual data. The book includes chapters covering multiple emerging topics in this new field. It links multiple popular research fields in Human-Centered Computing, Social Media, Image Classification, Pattern Recognition, Computer Vision, Big Data, and Human-Computer Interaction. Contains an overview of the low-rank and sparse modeling techniques for visual analysis by examining both theoretical analysis and real-world applic

  6. Thalamo-Sensorimotor Functional Connectivity Correlates with World Ranking of Olympic, Elite, and High Performance Athletes

    Directory of Open Access Journals (Sweden)

    Zirui Huang

    2017-01-01

    Full Text Available Brain plasticity studies have shown functional reorganization in participants with outstanding motor expertise. Little is known about neural plasticity associated with exceptionally long motor training or of its predictive value for motor performance excellence. The present study utilised resting-state functional magnetic resonance imaging (rs-fMRI in a unique sample of world-class athletes: Olympic, elite, and internationally ranked swimmers (n=30. Their world ranking ranged from 1st to 250th: each had prepared for participation in the Olympic Games. Combining rs-fMRI graph-theoretical and seed-based functional connectivity analyses, it was discovered that the thalamus has its strongest connections with the sensorimotor network in elite swimmers with the highest world rankings (career best rank: 1–35. Strikingly, thalamo-sensorimotor functional connections were highly correlated with the swimmers’ motor performance excellence, that is, accounting for 41% of the individual variance in best world ranking. Our findings shed light on neural correlates of long-term athletic performance involving thalamo-sensorimotor functional circuits.

  7. Do Quantitative Measures of Research Productivity Correlate with Academic Rank in Oral and Maxillofacial Surgery?

    Science.gov (United States)

    Susarla, Srinivas M; Dodson, Thomas B; Lopez, Joseph; Swanson, Edward W; Calotta, Nicholas; Peacock, Zachary S

    2015-08-01

    Academic promotion is linked to research productivity. The purpose of this study was to assess the correlation between quantitative measures of academic productivity and academic rank among academic oral and maxillofacial surgeons. This was a cross-sectional study of full-time academic oral and maxillofacial surgeons in the United States. The predictor variables were categorized as demographic (gender, medical degree, research doctorate, other advanced degree) and quantitative measures of academic productivity (total number of publications, total number of citations, maximum number of citations for a single article, I-10 index [number of publications with ≥ 10 citations], and h-index [number of publications h with ≥ h citations each]). The outcome variable was current academic rank (instructor, assistant professor, associate professor, professor, or endowed professor). Descriptive, bivariate, and multiple regression statistics were computed to evaluate associations between the predictors and academic rank. Receiver-operator characteristic curves were computed to identify thresholds for academic promotion. The sample consisted of 324 academic oral and maxillofacial surgeons, of whom 11.7% were female, 40% had medical degrees, and 8% had research doctorates. The h-index was the most strongly correlated with academic rank (ρ = 0.62, p research activity.

  8. Ranking metrics in gene set enrichment analysis: do they matter?

    Science.gov (United States)

    Zyla, Joanna; Marczyk, Michal; Weiner, January; Polanska, Joanna

    2017-05-12

    There exist many methods for describing the complex relation between changes of gene expression in molecular pathways or gene ontologies under different experimental conditions. Among them, Gene Set Enrichment Analysis seems to be one of the most commonly used (over 10,000 citations). An important parameter, which could affect the final result, is the choice of a metric for the ranking of genes. Applying a default ranking metric may lead to poor results. In this work 28 benchmark data sets were used to evaluate the sensitivity and false positive rate of gene set analysis for 16 different ranking metrics including new proposals. Furthermore, the robustness of the chosen methods to sample size was tested. Using k-means clustering algorithm a group of four metrics with the highest performance in terms of overall sensitivity, overall false positive rate and computational load was established i.e. absolute value of Moderated Welch Test statistic, Minimum Significant Difference, absolute value of Signal-To-Noise ratio and Baumgartner-Weiss-Schindler test statistic. In case of false positive rate estimation, all selected ranking metrics were robust with respect to sample size. In case of sensitivity, the absolute value of Moderated Welch Test statistic and absolute value of Signal-To-Noise ratio gave stable results, while Baumgartner-Weiss-Schindler and Minimum Significant Difference showed better results for larger sample size. Finally, the Gene Set Enrichment Analysis method with all tested ranking metrics was parallelised and implemented in MATLAB, and is available at https://github.com/ZAEDPolSl/MrGSEA . Choosing a ranking metric in Gene Set Enrichment Analysis has critical impact on results of pathway enrichment analysis. The absolute value of Moderated Welch Test has the best overall sensitivity and Minimum Significant Difference has the best overall specificity of gene set analysis. When the number of non-normally distributed genes is high, using Baumgartner

  9. Are Quantitative Measures of Academic Productivity Correlated with Academic Rank in Plastic Surgery? A National Study.

    Science.gov (United States)

    Susarla, Srinivas M; Lopez, Joseph; Swanson, Edward W; Miller, Devin; O'Brien-Coon, Devin; Zins, James E; Serletti, Joseph M; Yaremchuk, Michael J; Manson, Paul N; Gordon, Chad R

    2015-09-01

    The purpose of this study was to investigate the correlation between quantitative measures of academic productivity and academic rank among full-time academic plastic surgeons. Bibliometric indices were computed for all full-time academic plastic surgeons in the United States. The primary study variable was academic rank. Bibliometric predictors included the Hirsch index, I-10 index, number of publications, number of citations, and highest number of citations for a single publication. Descriptive, bivariate, and correlation analyses were computed. Multiple comparisons testing was used to calculate adjusted associations for subgroups. For all analyses, a value of p productivity. Although academic promotion is the result of success in multiple different areas, bibliometric measures may be useful adjuncts for assessment of research productivity.

  10. Journal rankings by citation analysis in health sciences librarianship.

    Science.gov (United States)

    Fang, M L

    1989-01-01

    The purpose of this study was to identify objectively a hierarchical ranking of journals for health sciences librarians with faculty status. Such a guideline can indicate a journal's value for promotion and tenure consideration. Lists of recent research articles (1982-1986) in health sciences librarianship, and articles written by health sciences librarians, were compiled by searching Social SCISEARCH and MEDLINE. The journals publishing those articles are presented. Results show BMLA as the most prominent journal in the field. Therefore, citations from articles in BMLA from 1982 to 1986 were chosen as a sample for citation analysis. Citation analysis was employed to identify the most frequently cited journals. Some characteristics of the citations in BMLA are also discussed. The ranking of journals based on citation frequency, as a result, was identified. PMID:2655785

  11. Do Standard Bibliometric Measures Correlate with Academic Rank of Full-Time Pediatric Dentistry Faculty Members?

    Science.gov (United States)

    Susarla, Harlyn K; Dhar, Vineet; Karimbux, Nadeem Y; Tinanoff, Norman

    2017-04-01

    The aim of this cross-sectional study was to assess the relationship between quantitative measures of research productivity and academic rank for full-time pediatric dentistry faculty members in accredited U.S. and Canadian residency programs. For each pediatric dentist in the study group, academic rank and bibliometric factors derived from publicly available databases were recorded. Academic ranks were lecturer/instructor, assistant professor, associate professor, and professor. Bibliometric factors were mean total number of publications, mean total number of citations, maximum number of citations for a single work, and h-index (a measure of the impact of publications, determined by total number of publications h that had at least h citations each). The study sample was comprised of 267 pediatric dentists: 4% were lecturers/instructors, 44% were assistant professors, 30% were associate professors, and 22% were professors. The mean number of publications for the sample was 15.4±27.8. The mean number of citations was 218.4±482.0. The mean h-index was 4.9±6.6. The h-index was strongly correlated with academic rank (r=0.60, p=0.001). For this sample, an h-index of ≥3 was identified as a threshold for promotion to associate professor, and an h-index of ≥6 was identified as a threshold for promotion to professor. The h-index was strongly correlated with the academic rank of these pediatric dental faculty members, suggesting that this index may be considered a measure for promotion, along with a faculty member's quality and quantity of research, teaching, service, and clinical activities.

  12. Construction Project Success ranking through the Data Envelopment Analysis

    Directory of Open Access Journals (Sweden)

    Mazyar Zahedi-Seresht

    2014-09-01

    Full Text Available The purpose of this paper is to rank construction projects' success in a post delivery phase. To attain this objective, a data envelopment analysis (DEA approach is used. The model's output is a project success index which is calculated based on five project success criteria. These criteria which are determined by a two-round Delphi questionnaire survey are time performance, cost performance, quality, HSE, and customer satisfaction. The input factors which have effects on the output measures are Organizational Sponsorship, Project Manager Competency, Customer Organization, Project Operational Environment and Organizational Experience. The tool adopted to determine these factors is questionnaire. This model is applied for 9 projects with different importance of output and input factors and the reasonable result is achieved for ranking these projects.

  13. Improving residue-residue contact prediction via low-rank and sparse decomposition of residue correlation matrix.

    Science.gov (United States)

    Zhang, Haicang; Gao, Yujuan; Deng, Minghua; Wang, Chao; Zhu, Jianwei; Li, Shuai Cheng; Zheng, Wei-Mou; Bu, Dongbo

    2016-03-25

    Strategies for correlation analysis in protein contact prediction often encounter two challenges, namely, the indirect coupling among residues, and the background correlations mainly caused by phylogenetic biases. While various studies have been conducted on how to disentangle indirect coupling, the removal of background correlations still remains unresolved. Here, we present an approach for removing background correlations via low-rank and sparse decomposition (LRS) of a residue correlation matrix. The correlation matrix can be constructed using either local inference strategies (e.g., mutual information, or MI) or global inference strategies (e.g., direct coupling analysis, or DCA). In our approach, a correlation matrix was decomposed into two components, i.e., a low-rank component representing background correlations, and a sparse component representing true correlations. Finally the residue contacts were inferred from the sparse component of correlation matrix. We trained our LRS-based method on the PSICOV dataset, and tested it on both GREMLIN and CASP11 datasets. Our experimental results suggested that LRS significantly improves the contact prediction precision. For example, when equipped with the LRS technique, the prediction precision of MI and mfDCA increased from 0.25 to 0.67 and from 0.58 to 0.70, respectively (Top L/10 predicted contacts, sequence separation: 5 AA, dataset: GREMLIN). In addition, our LRS technique also consistently outperforms the popular denoising technique APC (average product correction), on both local (MI_LRS: 0.67 vs MI_APC: 0.34) and global measures (mfDCA_LRS: 0.70 vs mfDCA_APC: 0.67). Interestingly, we found out that when equipped with our LRS technique, local inference strategies performed in a comparable manner to that of global inference strategies, implying that the application of LRS technique narrowed down the performance gap between local and global inference strategies. Overall, our LRS technique greatly facilitates

  14. Global sensitivity analysis using low-rank tensor approximations

    International Nuclear Information System (INIS)

    Konakli, Katerina; Sudret, Bruno

    2016-01-01

    In the context of global sensitivity analysis, the Sobol' indices constitute a powerful tool for assessing the relative significance of the uncertain input parameters of a model. We herein introduce a novel approach for evaluating these indices at low computational cost, by post-processing the coefficients of polynomial meta-models belonging to the class of low-rank tensor approximations. Meta-models of this class can be particularly efficient in representing responses of high-dimensional models, because the number of unknowns in their general functional form grows only linearly with the input dimension. The proposed approach is validated in example applications, where the Sobol' indices derived from the meta-model coefficients are compared to reference indices, the latter obtained by exact analytical solutions or Monte-Carlo simulation with extremely large samples. Moreover, low-rank tensor approximations are confronted to the popular polynomial chaos expansion meta-models in case studies that involve analytical rank-one functions and finite-element models pertinent to structural mechanics and heat conduction. In the examined applications, indices based on the novel approach tend to converge faster to the reference solution with increasing size of the experimental design used to build the meta-model. - Highlights: • A new method is proposed for global sensitivity analysis of high-dimensional models. • Low-rank tensor approximations (LRA) are used as a meta-modeling technique. • Analytical formulas for the Sobol' indices in terms of LRA coefficients are derived. • The accuracy and efficiency of the approach is illustrated in application examples. • LRA-based indices are compared to indices based on polynomial chaos expansions.

  15. Video deraining and desnowing using temporal correlation and low-rank matrix completion.

    Science.gov (United States)

    Kim, Jin-Hwan; Sim, Jae-Young; Kim, Chang-Su

    2015-09-01

    A novel algorithm to remove rain or snow streaks from a video sequence using temporal correlation and low-rank matrix completion is proposed in this paper. Based on the observation that rain streaks are too small and move too fast to affect the optical flow estimation between consecutive frames, we obtain an initial rain map by subtracting temporally warped frames from a current frame. Then, we decompose the initial rain map into basis vectors based on the sparse representation, and classify those basis vectors into rain streak ones and outliers with a support vector machine. We then refine the rain map by excluding the outliers. Finally, we remove the detected rain streaks by employing a low-rank matrix completion technique. Furthermore, we extend the proposed algorithm to stereo video deraining. Experimental results demonstrate that the proposed algorithm detects and removes rain or snow streaks efficiently, outperforming conventional algorithms.

  16. A new method for comparing rankings through complex networks: Model and analysis of competitiveness of major European soccer leagues

    Science.gov (United States)

    Criado, Regino; García, Esther; Pedroche, Francisco; Romance, Miguel

    2013-12-01

    In this paper, we show a new technique to analyze families of rankings. In particular, we focus on sports rankings and, more precisely, on soccer leagues. We consider that two teams compete when they change their relative positions in consecutive rankings. This allows to define a graph by linking teams that compete. We show how to use some structural properties of this competitivity graph to measure to what extend the teams in a league compete. These structural properties are the mean degree, the mean strength, and the clustering coefficient. We give a generalization of the Kendall's correlation coefficient to more than two rankings. We also show how to make a dynamic analysis of a league and how to compare different leagues. We apply this technique to analyze the four major European soccer leagues: Bundesliga, Italian Lega, Spanish Liga, and Premier League. We compare our results with the classical analysis of sport ranking based on measures of competitive balance.

  17. Tensor Rank Preserving Discriminant Analysis for Facial Recognition.

    Science.gov (United States)

    Tao, Dapeng; Guo, Yanan; Li, Yaotang; Gao, Xinbo

    2017-10-12

    Facial recognition, one of the basic topics in computer vision and pattern recognition, has received substantial attention in recent years. However, for those traditional facial recognition algorithms, the facial images are reshaped to a long vector, thereby losing part of the original spatial constraints of each pixel. In this paper, a new tensor-based feature extraction algorithm termed tensor rank preserving discriminant analysis (TRPDA) for facial image recognition is proposed; the proposed method involves two stages: in the first stage, the low-dimensional tensor subspace of the original input tensor samples was obtained; in the second stage, discriminative locality alignment was utilized to obtain the ultimate vector feature representation for subsequent facial recognition. On the one hand, the proposed TRPDA algorithm fully utilizes the natural structure of the input samples, and it applies an optimization criterion that can directly handle the tensor spectral analysis problem, thereby decreasing the computation cost compared those traditional tensor-based feature selection algorithms. On the other hand, the proposed TRPDA algorithm extracts feature by finding a tensor subspace that preserves most of the rank order information of the intra-class input samples. Experiments on the three facial databases are performed here to determine the effectiveness of the proposed TRPDA algorithm.

  18. Ranking insurance firms using AHP and Factor Analysis

    Directory of Open Access Journals (Sweden)

    Mohammad Khodaei Valahzaghard

    2013-03-01

    Full Text Available Insurance industry includes a significant part of economy and it is important to learn more about the capabilities of different firms, which are active in this industry. In this paper, we present an empirical study to rank the insurance firms using analytical hierarchy process as well as factor analysis. The study considers four criteria including capital adequacy, quality of earning, quality of cash flow and quality of firms’ assets. The results of the implementation of factor analysis (FA have been verified using Kaiser-Meyer-Olkin (KMO=0.573 and Bartlett's Chi-Square (443.267 P-value=0.000 tests. According to the results FA, the first important factor, capital adequacy, represents 21.557% of total variance, the second factor, quality of income, represents 20.958% of total variance. In addition, the third factor, quality of cash flow, represents 19.417% of total variance and the last factor, quality of assets, represents 18.641% of total variance. The study has also used analytical hierarchy process (AHP to rank insurance firms. The results of our survey indicate that capital adequacy (0.559 is accounted as the most important factor followed by quality of income (0.235, quality of cash flow (0.144 and quality of assets (0.061. The results of AHP are consistent with the results of FA, which somewhat validates the overall study.

  19. Sex-reversed correlation between stress levels and dominance rank in a captive non-breeder flock of crows.

    Science.gov (United States)

    Ode, Minami; Asaba, Akari; Miyazawa, Eri; Mogi, Kazutaka; Kikusui, Takefumi; Izawa, Ei-Ichi

    2015-07-01

    Group living has both benefits and costs to individuals; benefits include efficient acquisition of resources, and costs include stress from social conflicts among group members. Such social challenges result in hierarchical dominance ranking among group members as a solution to avoid escalating conflict that causes different levels of basal stress between individuals at different ranks. Stress-associated glucocorticoid (corticosterone in rodents and birds; CORT) levels are known to correlate with dominance rank in diverse taxa and to covary with various social factors, such as sex and dominance maintenance styles. Although there is much evidence for sex differences in the basal levels of CORT in various species, the correlation of sex differences in basal CORT with dominance rank is poorly understood. We investigated the correlation between CORT metabolites (CM) in the droppings and social factors, including rank and sex, in a captive non-breeder group of crows. In this group, all the single males dominated all the single females, and dominance ranks were stable among single males but relatively unstable among single females. CM levels and rank were significantly correlated in a sex-reversed fashion: males at higher rank (i.e., more dominant) had higher CM, whereas females at higher rank exhibited lower CM. This is the first evidence of sex-reversed patterns of CM-rank correlation in birds. The results suggest that different mechanisms of stress-dominance relationships operate on the sexes in non-breeder crow aggregations; in males, stress is associated with the cost of aggressive displays, whereas females experience subordination stress due to males' overt aggression. Copyright © 2015 Elsevier Inc. All rights reserved.

  20. Research on the Fusion of Dependent Evidence Based on Rank Correlation Coefficient

    Directory of Open Access Journals (Sweden)

    Fengjian Shi

    2017-10-01

    Full Text Available In order to meet the higher accuracy and system reliability requirements, the information fusion for multi-sensor systems is an increasing concern. Dempster–Shafer evidence theory (D–S theory has been investigated for many applications in multi-sensor information fusion due to its flexibility in uncertainty modeling. However, classical evidence theory assumes that the evidence is independent of each other, which is often unrealistic. Ignoring the relationship between the evidence may lead to unreasonable fusion results, and even lead to wrong decisions. This assumption severely prevents D–S evidence theory from practical application and further development. In this paper, an innovative evidence fusion model to deal with dependent evidence based on rank correlation coefficient is proposed. The model first uses rank correlation coefficient to measure the dependence degree between different evidence. Then, total discount coefficient is obtained based on the dependence degree, which also considers the impact of the reliability of evidence. Finally, the discount evidence fusion model is presented. An example is illustrated to show the use and effectiveness of the proposed method.

  1. Pearson's chi-square test and rank correlation inferences for clustered data.

    Science.gov (United States)

    Shih, Joanna H; Fay, Michael P

    2017-09-01

    Pearson's chi-square test has been widely used in testing for association between two categorical responses. Spearman rank correlation and Kendall's tau are often used for measuring and testing association between two continuous or ordered categorical responses. However, the established statistical properties of these tests are only valid when each pair of responses are independent, where each sampling unit has only one pair of responses. When each sampling unit consists of a cluster of paired responses, the assumption of independent pairs is violated. In this article, we apply the within-cluster resampling technique to U-statistics to form new tests and rank-based correlation estimators for possibly tied clustered data. We develop large sample properties of the new proposed tests and estimators and evaluate their performance by simulations. The proposed methods are applied to a data set collected from a PET/CT imaging study for illustration. Published 2017. This article is a U.S. Government work and is in the public domain in the USA.

  2. Research on the Fusion of Dependent Evidence Based on Rank Correlation Coefficient.

    Science.gov (United States)

    Shi, Fengjian; Su, Xiaoyan; Qian, Hong; Yang, Ning; Han, Wenhua

    2017-10-16

    In order to meet the higher accuracy and system reliability requirements, the information fusion for multi-sensor systems is an increasing concern. Dempster-Shafer evidence theory (D-S theory) has been investigated for many applications in multi-sensor information fusion due to its flexibility in uncertainty modeling. However, classical evidence theory assumes that the evidence is independent of each other, which is often unrealistic. Ignoring the relationship between the evidence may lead to unreasonable fusion results, and even lead to wrong decisions. This assumption severely prevents D-S evidence theory from practical application and further development. In this paper, an innovative evidence fusion model to deal with dependent evidence based on rank correlation coefficient is proposed. The model first uses rank correlation coefficient to measure the dependence degree between different evidence. Then, total discount coefficient is obtained based on the dependence degree, which also considers the impact of the reliability of evidence. Finally, the discount evidence fusion model is presented. An example is illustrated to show the use and effectiveness of the proposed method.

  3. Asymptotic properties of Pearson's rank-variate correlation coefficient under contaminated Gaussian model.

    Science.gov (United States)

    Ma, Rubao; Xu, Weichao; Zhang, Yun; Ye, Zhongfu

    2014-01-01

    This paper investigates the robustness properties of Pearson's rank-variate correlation coefficient (PRVCC) in scenarios where one channel is corrupted by impulsive noise and the other is impulsive noise-free. As shown in our previous work, these scenarios that frequently encountered in radar and/or sonar, can be well emulated by a particular bivariate contaminated Gaussian model (CGM). Under this CGM, we establish the asymptotic closed forms of the expectation and variance of PRVCC by means of the well known Delta method. To gain a deeper understanding, we also compare PRVCC with two other classical correlation coefficients, i.e., Spearman's rho (SR) and Kendall's tau (KT), in terms of the root mean squared error (RMSE). Monte Carlo simulations not only verify our theoretical findings, but also reveal the advantage of PRVCC by an example of estimating the time delay in the particular impulsive noise environment.

  4. ANALYSIS, SELECTION AND RANKING OF FOREIGN MARKETS. A COMPREHENSIVE APPROACH

    Directory of Open Access Journals (Sweden)

    LIVIU NEAMŢU

    2013-12-01

    Full Text Available Choosing the appropriate markets for growth and development is essential for a company that wishes expanding businesses through international economic exchanges. But in this business case foreign markets research is not sufficient even though is an important chapter in the decision technology and an indispensable condition for achieving firm’s objectives. If in marketing on the national market this market is defined requiring no more than its prospection and segmentation, in the case of the international market outside the research process there is a need of a selection of markets and their classification. Companies that have this intention know little or nothing about the conditions offered by a new market or another. Therefore, they must go, step by step, through a complex analysis process, multilevel- type, composed of selection and ranking of markets followed by the proper research through exploration and segmentation, which can lead to choosing the most profitable markets. In this regard, within this study, we propose a multi-criteria model for selection and ranking of international development markets, allowing companies access to those markets which are in compliance with the company's development strategy.

  5. A Combined Raman Spectroscopic and Thermogravimetric Analysis Study on Oxidation of Coal with Different Ranks

    Directory of Open Access Journals (Sweden)

    Weiqing Zhang

    2015-01-01

    Full Text Available Raman spectroscopy and nonisothermal thermogravimetric analysis (TGA measurements have been reported for different rank coals (lignite, bituminous coal, and anthracite and the relationship between the measurements was examined. It was found that the Raman spectra parameters can be used to characterize structure changes in the different rank coals, such as the band area ratios based on the curve-fitted results. Higher ranked coal was found to have higher values of IGR/IAll and IG+GR/IAll but lower values of ID/I(G+GR, IDL/I(G+GR, IS+SL/I(G+GR, and I(GL+GL'/I(G+GR. The oxidation properties of the coal samples were characterized by the reactivity indexes Tig, T20%, and Tmax from TGA data which were found to correlate well with the band area ratios of IGR/IAll, IG+GR/IAll, and IS+SL/I(G+GR. Based on these correlations, the Raman band area ratios were found to correlate with the oxidation activity of coal providing additional structural information which can be used to understand the changes in the TGA measurements.

  6. A Combined Raman Spectroscopic and Thermogravimetric Analysis Study on Oxidation of Coal with Different Ranks.

    Science.gov (United States)

    Zhang, Weiqing; Jiang, Shuguang; Hardacre, Christopher; Goodrich, Peter; Wang, Kai; Shao, Hao; Wu, Zhengyan

    2015-01-01

    Raman spectroscopy and nonisothermal thermogravimetric analysis (TGA) measurements have been reported for different rank coals (lignite, bituminous coal, and anthracite) and the relationship between the measurements was examined. It was found that the Raman spectra parameters can be used to characterize structure changes in the different rank coals, such as the band area ratios based on the curve-fitted results. Higher ranked coal was found to have higher values of I GR/I All and I (G + GR)/I All but lower values of I D/I (G+GR), I DL/I (G+GR), I (S + SL)/I (G+GR), and I (GL+GL')/I (G+GR). The oxidation properties of the coal samples were characterized by the reactivity indexes T ig, T 20%, and T max from TGA data which were found to correlate well with the band area ratios of I GR/I All, I (G + GR)/I All, and I (S + SL)/I (G+GR). Based on these correlations, the Raman band area ratios were found to correlate with the oxidation activity of coal providing additional structural information which can be used to understand the changes in the TGA measurements.

  7. Spectral analysis by correlation

    International Nuclear Information System (INIS)

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

    1969-01-01

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

  8. An Improved Rank Correlation Effect Size Statistic for Single-Case Designs: Baseline Corrected Tau.

    Science.gov (United States)

    Tarlow, Kevin R

    2017-07-01

    Measuring treatment effects when an individual's pretreatment performance is improving poses a challenge for single-case experimental designs. It may be difficult to determine whether improvement is due to the treatment or due to the preexisting baseline trend. Tau- U is a popular single-case effect size statistic that purports to control for baseline trend. However, despite its strengths, Tau- U has substantial limitations: Its values are inflated and not bound between -1 and +1, it cannot be visually graphed, and its relatively weak method of trend control leads to unacceptable levels of Type I error wherein ineffective treatments appear effective. An improved effect size statistic based on rank correlation and robust regression, Baseline Corrected Tau, is proposed and field-tested with both published and simulated single-case time series. A web-based calculator for Baseline Corrected Tau is also introduced for use by single-case investigators.

  9. Multicriteria decision analysis in ranking of analytical procedures for aldrin determination in water.

    Science.gov (United States)

    Tobiszewski, Marek; Orłowski, Aleksander

    2015-03-27

    The study presents the possibility of multi-criteria decision analysis (MCDA) application when choosing analytical procedures with low environmental impact. A type of MCDA, Preference Ranking Organization Method for Enrichment Evaluations (PROMETHEE), was chosen as versatile tool that meets all the analytical chemists--decision makers requirements. Twenty five analytical procedures for aldrin determination in water samples (as an example) were selected as input alternatives to MCDA analysis. Nine different criteria describing the alternatives were chosen from different groups--metrological, economical and the most importantly--environmental impact. The weights for each criterion were obtained from questionnaires that were sent to experts, giving three different scenarios for MCDA results. The results of analysis show that PROMETHEE is very promising tool to choose the analytical procedure with respect to its greenness. The rankings for all three scenarios placed solid phase microextraction and liquid phase microextraction--based procedures high, while liquid-liquid extraction, solid phase extraction and stir bar sorptive extraction--based procedures were placed low in the ranking. The results show that although some of the experts do not intentionally choose green analytical chemistry procedures, their MCDA choice is in accordance with green chemistry principles. The PROMETHEE ranking results were compared with more widely accepted green analytical chemistry tools--NEMI and Eco-Scale. As PROMETHEE involved more different factors than NEMI, the assessment results were only weakly correlated. Oppositely, the results of Eco-Scale assessment were well-correlated as both methodologies involved similar criteria of assessment. Copyright © 2015 Elsevier B.V. All rights reserved.

  10. Optimal ranking regime analysis of TreeFlow dendrohydrological reconstructions

    Science.gov (United States)

    The Optimal Ranking Regime (ORR) method was used to identify 6-100 year time windows containing significant ranking sequences in 55 western U.S. streamflow reconstructions, and reconstructions of the level of the Great Salt Lake and San Francisco Bay salinity during 1500-2007. The method’s ability t...

  11. Use of the dry-weight-rank method of botanical analysis in the ...

    African Journals Online (AJOL)

    The dry-weight-rank method of botanical analysis was tested in the highveld of the Eastern Transvaal and was found to be an efficient and accurate means of determining the botanical composition of veld herbage. Accuracy was increased by weighting ranks on the basis of quadrat yield, and by allocation of equal ranks to ...

  12. The indicative analysis and ranking of human capital development

    Science.gov (United States)

    Inessa, Gurban; Alexandr, Tarasyev

    2017-07-01

    In this article we discuss the rationale for the importance and effectiveness of the regions ranking as a tool for regional social and economic policies aimed to control the regional socio-economic development. A methodological approach to the determination of the human capital development level in the regions of the Russian Federation is provided focused on determining the quality of human capital in each region of the Russian Federation and the causes underlying this situation. The methodological apparatus is based on the indicative qualimetric analysis method that allows to convert various benchmarks expressed in different units in a comparable type. Also it is possible to receive and differentiate a comprehensive assessment of the human capital level in each region of the Russian Federation on the basis of the proposed classification. In this article we present the structure of the indicators system that simulates the human capital level by a number of descriptive components including demographic, educational, employment, research and socio-cultural components. In our research we found that in the overwhelming majority of the Russian Federation human capital is characterized mainly by a low development level. The system shows unstable dynamics in the human capital level through the Russian Federal Districts, as well as the leaders and laggards in the rating of the Russian Federation during the period 2000-2013. Our article presents the structure of a comprehensive assessment of the human capital level by providing estimates of its components.

  13. Modified Phenomena Identification and Ranking Table (PIRT) for Uncertainty Analysis

    International Nuclear Information System (INIS)

    Gol-Mohamad, Mohammad P.; Modarres, Mohammad; Mosleh, Ali

    2006-01-01

    This paper describes a methodology of characterizing important phenomena, which is also part of a broader research by the authors called 'Modified PIRT'. The methodology provides robust process of phenomena identification and ranking process for more precise quantification of uncertainty. It is a two-step process of identifying and ranking methodology based on thermal-hydraulics (TH) importance as well as uncertainty importance. Analytical Hierarchical Process (AHP) has been used for as a formal approach for TH identification and ranking. Formal uncertainty importance technique is used to estimate the degree of credibility of the TH model(s) used to represent the important phenomena. This part uses subjective justification by evaluating available information and data from experiments, and code predictions. The proposed methodology was demonstrated by developing a PIRT for large break loss of coolant accident LBLOCA for the LOFT integral facility with highest core power (test LB-1). (authors)

  14. A stable systemic risk ranking in China's banking sector: Based on principal component analysis

    Science.gov (United States)

    Fang, Libing; Xiao, Binqing; Yu, Honghai; You, Qixing

    2018-02-01

    In this paper, we compare five popular systemic risk rankings, and apply principal component analysis (PCA) model to provide a stable systemic risk ranking for the Chinese banking sector. Our empirical results indicate that five methods suggest vastly different systemic risk rankings for the same bank, while the combined systemic risk measure based on PCA provides a reliable ranking. Furthermore, according to factor loadings of the first component, PCA combined ranking is mainly based on fundamentals instead of market price data. We clearly find that price-based rankings are not as practical a method as fundamentals-based ones. This PCA combined ranking directly shows systemic risk contributions of each bank for banking supervision purpose and reminds banks to prevent and cope with the financial crisis in advance.

  15. Rankings in education: history and critical analysis of rates

    Directory of Open Access Journals (Sweden)

    Bebenina Ekaterina

    2016-01-01

    Full Text Available The history of rankings, mechanisms of their appearing and reasons of their popularity are little scrutinized yet although they are widely spread in the modern information flow, they are widely used during the evaluation for organizations of the Ministry of Education and Science of Russia and the Russian Academy of Science as key indices.

  16. Ranking factors of an investment in cogeneration: sensitivity analysis ranking the technical and economical factors

    International Nuclear Information System (INIS)

    Sundberg, Gunnel

    2001-01-01

    A deregulation of the electricity market in Europe will result in increased competition among the power-producing companies. They will therefore carefully estimate the financial risk in an investment in new power-producing capability. One part of the risk assessment is to perform a sensitivity analysis. This paper presents a sensitivity analysis using factorial design, resulting in an assessment of the most important technical and economical factors affecting an investment in gas turbine combined cycle and a steam cycle fired by wood chips. The study is performed using a simulation model that optimises the operation of existing power plants and potential new investments to fulfil the desired heat demand. The local utility system analysed is a Swedish district heating system with 655 GWh y -1 heat demand. The conclusion is that to understand which of the technical and economical factors affect the investment, it is not sufficient to investigate the parameters of the studied plant, but also the parameters related to the competing plants. Both the individual effects of the factors and the effect of their interaction should be investigated. For the energy system studied the price of natural gas, price of wood chips and investment cost have the major influence on the profitability of the investment. (Author)

  17. Analysis model for forecasting extreme temperature using refined rank set pair

    Directory of Open Access Journals (Sweden)

    Qiao Ling-Xia

    2013-01-01

    Full Text Available In order to improve the precision of forecasting extreme temperature time series, a refined rank set pair analysis model with a refined rank transformation function is proposed to improve precision of its prediction. The measured values of the annual highest temperature of two China’s cities, Taiyuan and Shijiazhuang, in July are taken to examine the performance of a refined rank set pair model.

  18. Rankings of International Achievement Test Performance and Economic Strength: Correlation or Conjecture?

    Directory of Open Access Journals (Sweden)

    CHRISTOPHER H. TIENKEN

    2008-04-01

    Full Text Available Examining a popular political notion, this article presents results from a series of Spearman Rho calculations conducted to investigate relationships between countries’ rankings on international tests of mathematics and science and future economic competitiveness as measured by the 2006 World Economic Forum’s Growth Competitiveness Index (GCI. The study investigated the existence of relationships between international test rankings from three different time periods during the last 50 years of U.S. education policy development (i.e., 1957–1982, 1983–2000, and 2001–2006 and 2006 GCI ranks. It extends previous research on the topic by investigating how GCI rankings in the top 50 percent and bottom 50 percent relate to rankings on international tests for the countries that participated in each test. The study found that the relationship between ranks on international tests of mathematics and science and future economic strength is stronger among nations with lower-performing economies. Nations with strong economies, such as the United States, demonstrate a weaker, nonsignificant relationship.

  19. Analysis of some methods for reduced rank Gaussian process regression

    DEFF Research Database (Denmark)

    Quinonero-Candela, J.; Rasmussen, Carl Edward

    2005-01-01

    While there is strong motivation for using Gaussian Processes (GPs) due to their excellent performance in regression and classification problems, their computational complexity makes them impractical when the size of the training set exceeds a few thousand cases. This has motivated the recent...... proliferation of a number of cost-effective approximations to GPs, both for classification and for regression. In this paper we analyze one popular approximation to GPs for regression: the reduced rank approximation. While generally GPs are equivalent to infinite linear models, we show that Reduced Rank...... Gaussian Processes (RRGPs) are equivalent to finite sparse linear models. We also introduce the concept of degenerate GPs and show that they correspond to inappropriate priors. We show how to modify the RRGP to prevent it from being degenerate at test time. Training RRGPs consists both in learning...

  20. Rankings of International Achievement Test Performance and Economic Strength: Correlation or Conjecture?

    Science.gov (United States)

    Tienken, Christopher H.

    2008-01-01

    Examining a popular political notion, this article presents results from a series of Spearman Rho calculations conducted to investigate relationships between countries' rankings on international tests of mathematics and science and future economic competitiveness as measured by the 2006 World Economic Forum's Growth Competitiveness Index (GCI).…

  1. Academic Productivity of US Neurosurgery Residents as Measured by H-Index: Program Ranking with Correlation to Faculty Productivity.

    Science.gov (United States)

    Sarkiss, Christopher A; Riley, Kyle J; Hernandez, Christopher M; Oermann, Eric K; Ladner, Travis R; Bederson, Joshua B; Shrivastava, Raj K

    2017-06-01

    Engagement in research and academic productivity are crucial components in the training of a neurosurgeon. This process typically begins in residency training. In this study, we analyzed individual resident productivity as it correlated to publications across all Accreditation Council for Graduate Medical Education (ACGME)-accredited neurosurgery training programs in an attempt to identify how programs have developed and fostered a research culture and environment. We obtained a list of current neurosurgery residents in ACGME-accredited programs from the American Association of Neurological Surgeons database. An expanded PubMed and Scopus search was conducted for each resident through the present time. We tabulated all articles attributed to each resident. We then categorized the publications based on each neurosurgical subspecialty while in residency. A spreadsheet-based statistical analysis was performed. This formulated the average number of resident articles, h-indices, and most common subspecialty categories by training program. We analyzed 1352 current neurosurgery residents in 105 programs. There were a total of 10 645 publications, of which 3985 were resident first-author publications during the period of study. The most common subspecialties among all resident publications were vascular (24.9%), spine (16.9%), oncology (16.1%), pediatric (5.6%), functional (4.9%), and trauma (3.8%). The average resident published 2.9 first-author papers with average of 38.0 first-author publications by total residents at each program (range 0-241). The average h-index per resident is 2.47 ± 3.25. When comparing previously published faculty h-index program rankings against our resident h-index rankings, there is a strong correlation between the 2 datasets with a clear delineation between Top-20 productivity and that of other programs (average h-index 4.2 vs 1.7, respectively, P productivity on both the resident and faculty level (average h-index 1.6, 1.9, 3.9 for 1, 2, and

  2. Flexibility of internal and external glenohumeral rotation of junior female tennis players and its correlation with performance ranking.

    Science.gov (United States)

    Chiang, Ching-Cheng; Hsu, Chih-Chia; Chiang, Jinn-Yen; Chang, Weng-Cheng; Tsai, Jong-Chang

    2016-12-01

    [Purpose] The purpose of this study was to compare the internal and external rotation of the dominant and nondominant shoulders of adolescent female tennis players. The correlation between the shoulder rotation range of motion and the player's ranking was also analyzed. [Subjects and Methods] Twenty-one female junior tennis players who were 13 to 18 years old participated in this study. A standard goniometer was used to measure the internal and external rotation of both glenohumeral joints. The difference in internal and external rotation was calculated as the glenohumeral rotation deficit. The year-end ranking of each player was obtained from the Chinese Taipei Tennis Association. [Results] The internal rotation of the dominant shoulder was significantly smaller than that of the nondominant shoulder. Moreover, player ranking was significantly and negatively correlated with the internal rotation range of motion of both shoulders. On the other hand, the correlations of the internal and external rotation ranges of motion with the age, height, and weight were not significant. [Conclusion] The flexibility of the glenohumeral internal rotation is smaller in the dominant shoulder than of the nondominant shoulder in these junior female tennis players. Flexibility of the glenohumeral internal rotation may be a factor affecting performance in junior female tennis players.

  3. GeneRank: Using search engine technology for the analysis of microarray experiments

    Directory of Open Access Journals (Sweden)

    Breitling Rainer

    2005-09-01

    Full Text Available Abstract Background Interpretation of simple microarray experiments is usually based on the fold-change of gene expression between a reference and a "treated" sample where the treatment can be of many types from drug exposure to genetic variation. Interpretation of the results usually combines lists of differentially expressed genes with previous knowledge about their biological function. Here we evaluate a method – based on the PageRank algorithm employed by the popular search engine Google – that tries to automate some of this procedure to generate prioritized gene lists by exploiting biological background information. Results GeneRank is an intuitive modification of PageRank that maintains many of its mathematical properties. It combines gene expression information with a network structure derived from gene annotations (gene ontologies or expression profile correlations. Using both simulated and real data we find that the algorithm offers an improved ranking of genes compared to pure expression change rankings. Conclusion Our modification of the PageRank algorithm provides an alternative method of evaluating microarray experimental results which combines prior knowledge about the underlying network. GeneRank offers an improvement compared to assessing the importance of a gene based on its experimentally observed fold-change alone and may be used as a basis for further analytical developments.

  4. GeneRank: using search engine technology for the analysis of microarray experiments.

    Science.gov (United States)

    Morrison, Julie L; Breitling, Rainer; Higham, Desmond J; Gilbert, David R

    2005-09-21

    Interpretation of simple microarray experiments is usually based on the fold-change of gene expression between a reference and a "treated" sample where the treatment can be of many types from drug exposure to genetic variation. Interpretation of the results usually combines lists of differentially expressed genes with previous knowledge about their biological function. Here we evaluate a method--based on the PageRank algorithm employed by the popular search engine Google--that tries to automate some of this procedure to generate prioritized gene lists by exploiting biological background information. GeneRank is an intuitive modification of PageRank that maintains many of its mathematical properties. It combines gene expression information with a network structure derived from gene annotations (gene ontologies) or expression profile correlations. Using both simulated and real data we find that the algorithm offers an improved ranking of genes compared to pure expression change rankings. Our modification of the PageRank algorithm provides an alternative method of evaluating microarray experimental results which combines prior knowledge about the underlying network. GeneRank offers an improvement compared to assessing the importance of a gene based on its experimentally observed fold-change alone and may be used as a basis for further analytical developments.

  5. Statistical methods for ranking data

    CERN Document Server

    Alvo, Mayer

    2014-01-01

    This book introduces advanced undergraduate, graduate students and practitioners to statistical methods for ranking data. An important aspect of nonparametric statistics is oriented towards the use of ranking data. Rank correlation is defined through the notion of distance functions and the notion of compatibility is introduced to deal with incomplete data. Ranking data are also modeled using a variety of modern tools such as CART, MCMC, EM algorithm and factor analysis. This book deals with statistical methods used for analyzing such data and provides a novel and unifying approach for hypotheses testing. The techniques described in the book are illustrated with examples and the statistical software is provided on the authors’ website.

  6. CONSORT item adherence in top ranked anaesthesiology journals in 2011: a retrospective analysis.

    Science.gov (United States)

    Münter, Nils H; Stevanovic, Ana; Rossaint, Rolf; Stoppe, Christian; Sanders, Robert D; Coburn, Mark

    2015-02-01

    Randomised controlled trials (RCTs) are the gold standard for measuring the efficacy of any medical intervention. The present study assesses the implementation of the CONSORT statement in the top 11 anaesthesiology journals in 2011. We designed this study in order to determine how well authors in the top 11 ranked anaesthesiology journals follow the CONSORT statement's criteria. A retrospective cross-sectional data analysis. The study was performed at the RWTH Aachen University Hospital. Journals included Pain, Anesthesiology, British Journal of Anaesthesia, Regional Anesthesia and Pain Medicine, European Journal of Pain, Anesthesia and Analgesia, Anaesthesia, Minerva Anestesiologica, Canadian Journal of Anesthesia, Journal of Neurosurgical Anesthesiology and the European Journal of Anaesthesiology. All articles in the online table of contents from the top 11 anaesthesiology journals according to the ISI Web of Knowledge were screened for RCTs published in 2011. The RCTs were assessed using the CONSORT checklist. We also analysed the correlation between the number of citations and the adherence to CONSORT items. We evaluated 319 RCTs and found that, more than ten years after the publication of the CONSORT statement, the RCTs satisfied a median of 60.0% of the CONSORT criteria. Only 72.1% of the articles presented clearly defined primary and secondary outcome parameters. The number of citations is only weakly associated with the fulfilment of the CONSORT statement (r = 0.023). Adherence to the CONSORT criteria remains low in top-ranked anaesthesiology journals. We found only a very weak correlation between the number of citations and fulfilment of the requirements of the CONSORT statement.

  7. Male ruff colour as a rank signal in a monomorphic-horned mammal: behavioural correlates

    Science.gov (United States)

    Lovari, S.; Fattorini, N.; Boesi, R.; Bocci, A.

    2015-08-01

    Coexistence of individuals within a social group is possible through the establishment of a hierarchy. Social dominance is achieved through aggressive interactions, and, in wild sheep and goats, it is related mainly to age, body size and weapon size as rank signals. Adult male Himalayan tahr are much larger than females and subadult males. They have a prominent neck ruff, ranging in colour from yellow (5.5-9.5 years old, i.e. young adults, golden males) to brown (7.5-14.5 years old, i.e. older individuals, pale and dark brown males), with golden males being the most dominant. We investigated the social behaviour of male tahr and analysed the relationships between ruff colour, courtship and agonistic behaviour patterns during the rut. Colour classes varied in their use of several behaviour patterns (male dominance: approach, stare, horning vegetation; courtship: low stretch, naso- genital contact, rush). Golden-ruffed males used more threats than darker ones. Pale brown and dark brown males addressed threats significantly more often to males of lower or their own colour classes, respectively, whereas golden ones addressed threats to all colour classes, including their own. The courtship of dominant males was characterised by the assertive rush, whereas that of subordinates did not. Ruff colour of male Himalayan tahr may have evolved as a rank signal, homologous to horn size in wild sheep and goats.

  8. Sensitivity analysis of ranked data: from order statistics to quantiles

    NARCIS (Netherlands)

    Heidergott, B.F.; Volk-Makarewicz, W.

    2015-01-01

    In this paper we provide the mathematical theory for sensitivity analysis of order statistics of continuous random variables, where the sensitivity is with respect to a distributional parameter. Sensitivity analysis of order statistics over a finite number of observations is discussed before

  9. Multiview Bayesian Correlated Component Analysis

    DEFF Research Database (Denmark)

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

    2015-01-01

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

  10. Ranking of microRNA target prediction scores by Pareto front analysis.

    Science.gov (United States)

    Sahoo, Sudhakar; Albrecht, Andreas A

    2010-12-01

    Over the past ten years, a variety of microRNA target prediction methods has been developed, and many of the methods are constantly improved and adapted to recent insights into miRNA-mRNA interactions. In a typical scenario, different methods return different rankings of putative targets, even if the ranking is reduced to selected mRNAs that are related to a specific disease or cell type. For the experimental validation it is then difficult to decide in which order to process the predicted miRNA-mRNA bindings, since each validation is a laborious task and therefore only a limited number of mRNAs can be analysed. We propose a new ranking scheme that combines ranked predictions from several methods and - unlike standard thresholding methods - utilises the concept of Pareto fronts as defined in multi-objective optimisation. In the present study, we attempt a proof of concept by applying the new ranking scheme to hsa-miR-21, hsa-miR-125b, and hsa-miR-373 and prediction scores supplied by PITA and RNAhybrid. The scores are interpreted as a two-objective optimisation problem, and the elements of the Pareto front are ranked by the STarMir score with a subsequent re-calculation of the Pareto front after removal of the top-ranked mRNA from the basic set of prediction scores. The method is evaluated on validated targets of the three miRNA, and the ranking is compared to scores from DIANA-microT and TargetScan. We observed that the new ranking method performs well and consistent, and the first validated targets are elements of Pareto fronts at a relatively early stage of the recurrent procedure, which encourages further research towards a higher-dimensional analysis of Pareto fronts. Copyright © 2010 Elsevier Ltd. All rights reserved.

  11. Reduced Rank Regression

    DEFF Research Database (Denmark)

    Johansen, Søren

    2008-01-01

    The reduced rank regression model is a multivariate regression model with a coefficient matrix with reduced rank. The reduced rank regression algorithm is an estimation procedure, which estimates the reduced rank regression model. It is related to canonical correlations and involves calculating...

  12. Variable importance analysis based on rank aggregation with applications in metabolomics for biomarker discovery.

    Science.gov (United States)

    Yun, Yong-Huan; Deng, Bai-Chuan; Cao, Dong-Sheng; Wang, Wei-Ting; Liang, Yi-Zeng

    2016-03-10

    Biomarker discovery is one important goal in metabolomics, which is typically modeled as selecting the most discriminating metabolites for classification and often referred to as variable importance analysis or variable selection. Until now, a number of variable importance analysis methods to discover biomarkers in the metabolomics studies have been proposed. However, different methods are mostly likely to generate different variable ranking results due to their different principles. Each method generates a variable ranking list just as an expert presents an opinion. The problem of inconsistency between different variable ranking methods is often ignored. To address this problem, a simple and ideal solution is that every ranking should be taken into account. In this study, a strategy, called rank aggregation, was employed. It is an indispensable tool for merging individual ranking lists into a single "super"-list reflective of the overall preference or importance within the population. This "super"-list is regarded as the final ranking for biomarker discovery. Finally, it was used for biomarkers discovery and selecting the best variable subset with the highest predictive classification accuracy. Nine methods were used, including three univariate filtering and six multivariate methods. When applied to two metabolic datasets (Childhood overweight dataset and Tubulointerstitial lesions dataset), the results show that the performance of rank aggregation has improved greatly with higher prediction accuracy compared with using all variables. Moreover, it is also better than penalized method, least absolute shrinkage and selectionator operator (LASSO), with higher prediction accuracy or less number of selected variables which are more interpretable. Copyright © 2016 Elsevier B.V. All rights reserved.

  13. Reservoir characterization based on tracer response and rank analysis of production and injection rates

    Energy Technology Data Exchange (ETDEWEB)

    Refunjol, B.T. [Lagoven, S.A., Pdvsa (Venezuela); Lake, L.W. [Univ. of Texas, Austin, TX (United States)

    1997-08-01

    Quantification of the spatial distribution of properties is important for many reservoir-engineering applications. But, before applying any reservoir-characterization technique, the type of problem to be tackled and the information available should be analyzed. This is important because difficulties arise in reservoirs where production records are the only information for analysis. This paper presents the results of a practical technique to determine preferential flow trends in a reservoir. The technique is a combination of reservoir geology, tracer data, and Spearman rank correlation coefficient analysis. The Spearman analysis, in particular, will prove to be important because it appears to be insightful and uses injection/production data that are prevalent in circumstances where other data are nonexistent. The technique is applied to the North Buck Draw field, Campbell County, Wyoming. This work provides guidelines to assess information about reservoir continuity in interwell regions from widely available measurements of production and injection rates at existing wells. The information gained from the application of this technique can contribute to both the daily reservoir management and the future design, control, and interpretation of subsequent projects in the reservoir, without the need for additional data.

  14. Systematic differences in signal emitting and receiving revealed by PageRank analysis of a human protein interactome.

    Directory of Open Access Journals (Sweden)

    Donglei Du

    Full Text Available Most protein PageRank studies do not use signal flow direction information in protein interactions because this information was not readily available in large protein databases until recently. Therefore, four questions have yet to be answered: A What is the general difference between signal emitting and receiving in a protein interactome? B Which proteins are among the top ranked in directional ranking? C Are high ranked proteins more evolutionarily conserved than low ranked ones? D Do proteins with similar ranking tend to have similar subcellular locations? In this study, we address these questions using the forward, reverse, and non-directional PageRank approaches to rank an information-directional network of human proteins and study their evolutionary conservation. The forward ranking gives credit to information receivers, reverse ranking to information emitters, and non-directional ranking mainly to the number of interactions. The protein lists generated by the forward and non-directional rankings are highly correlated, but those by the reverse and non-directional rankings are not. The results suggest that the signal emitting/receiving system is characterized by key-emittings and relatively even receivings in the human protein interactome. Signaling pathway proteins are frequent in top ranked ones. Eight proteins are both informational top emitters and top receivers. Top ranked proteins, except a few species-related novel-function ones, are evolutionarily well conserved. Protein-subunit ranking position reflects subunit function. These results demonstrate the usefulness of different PageRank approaches in characterizing protein networks and provide insights to protein interaction in the cell.

  15. Systematic differences in signal emitting and receiving revealed by PageRank analysis of a human protein interactome.

    Science.gov (United States)

    Du, Donglei; Lee, Connie F; Li, Xiu-Qing

    2012-01-01

    Most protein PageRank studies do not use signal flow direction information in protein interactions because this information was not readily available in large protein databases until recently. Therefore, four questions have yet to be answered: A) What is the general difference between signal emitting and receiving in a protein interactome? B) Which proteins are among the top ranked in directional ranking? C) Are high ranked proteins more evolutionarily conserved than low ranked ones? D) Do proteins with similar ranking tend to have similar subcellular locations? In this study, we address these questions using the forward, reverse, and non-directional PageRank approaches to rank an information-directional network of human proteins and study their evolutionary conservation. The forward ranking gives credit to information receivers, reverse ranking to information emitters, and non-directional ranking mainly to the number of interactions. The protein lists generated by the forward and non-directional rankings are highly correlated, but those by the reverse and non-directional rankings are not. The results suggest that the signal emitting/receiving system is characterized by key-emittings and relatively even receivings in the human protein interactome. Signaling pathway proteins are frequent in top ranked ones. Eight proteins are both informational top emitters and top receivers. Top ranked proteins, except a few species-related novel-function ones, are evolutionarily well conserved. Protein-subunit ranking position reflects subunit function. These results demonstrate the usefulness of different PageRank approaches in characterizing protein networks and provide insights to protein interaction in the cell.

  16. The design and content of orthodontic practise websites in the UK is suboptimal and does not correlate with search ranking.

    Science.gov (United States)

    Patel, Annika; Cobourne, Martyn T

    2015-08-01

    This study investigated standards of ethical advertising; design and content; and information quality associated with UK dental practice websites offering orthodontic treatment. The World Wide Web was searched from a UK-based computer using the Google search engine combined with the term 'orthodontic braces'. The first 100 UK-based dental practice websites were pooled and saved following duplicate removal. Websites were evaluated for compliance with current General Dental Council ethical advertising guidelines; accessibility, usability, and reliability using the LIDA instrument (a validated outcome tool for healthcare website design and content evaluation); and quality of information using the DISCERN toolkit (a validated method of quality assessment for online written patient information). Nine per cent of websites demonstrated full compliance with current guidelines on ethical advertising. Mean total LIDA score was 110/144 (76%) [range: 51-135; 35-94%]. Eleven websites reached a gold standard of 90% or more for total LIDA score. Mean total DISCERN score was 48/75 (64%) [range: 19-73; 25-97%]. Five websites achieved a total DISCERN score above 90%. Spearman's rank correlation coefficients demonstrated no significant correlations between LIDA (0.1669; P = 0.4252, confidence interval [CI]: -0.2560 to 0.5362) or DISCERN (0.3572; P = 0.0796, CI: -0.0565 to 0.663) score and ranking amongst the 25 highest ranked websites. Most UK websites offering orthodontic services are not fully compliant with national guidelines relating to ethical advertising. Validated measures of website design (LIDA) and information quality (DISCERN) showed wide variation amongst sites. No correlation existed between ranking amongst the highest 25 sites and either of these measures. This investigation was limited to a subsample of UK-only websites; and whilst not representative of European-wide sites, it does suggest that in the UK at least website quality can be improved. © The Author 2014

  17. Ranking product aspects through sentiment analysis of online reviews

    Science.gov (United States)

    Wang, Wei; Wang, Hongwei; Song, Yuan

    2017-03-01

    The electronic word-of-mouth (e-WOM) is one of the most important among all the factors affecting consumers' behaviours. Opinions towards a product through online reviews will influence purchase decisions of other online consumers by changing their perceptions on the product quality. Furthermore, each product aspect may impact consumers' intentions differently. Thus, sentiment analysis and econometric models are incorporated to examine the relationship between purchase intentions and aspect-opinion pairs, which enable the weight estimation for each product aspect. We first identify product aspects and reduce dimensions to extract aspect-opinion pairs. Next the information gain is calculated for each aspect through entropy theory. Based on sentiment polarity and sentiment strength, we formulate an econometric model by integrating the information gain to measure the aspect's weight. In the experiment, we track 386 digital cameras on Amazon for 39 months, and results show that the aspect weight for digital cameras is detected more precisely than TF-ID and HAC algorithms. The results will bridge product aspects and consumption intention to facilitate e-WOM-based marketing.

  18. On bounded rank positive semidefinite matrix completions of extreme partial correlation matrices.

    NARCIS (Netherlands)

    M. Eisenberg-Nagy (Marianna); M. Laurent (Monique); A. Varvitsiotis (Antonios)

    2012-01-01

    htmlabstractWe study a new geometric graph parameter egd(G), defined as the smallest integer r ≥ 1 for which any partial symmetric matrix which is completable to a correlation matrix and whose entries are specified at the positions of the edges of G, can be completed to a matrix in the convex hull

  19. On bounded rank positive semidefinite matrix completions of extreme partial correlation matrices.

    NARCIS (Netherlands)

    M. Eisenberg-Nagy (Marianna); M. Laurent (Monique); A. Varvitsiotis (Antonios)

    2012-01-01

    textabstractWe study a new geometric graph parameter $egd(G)$, defined as the smallest integer $r\\ge 1$ for which any partial symmetric matrix which is completable to a correlation matrix and whose entries are specified at the positions of the edges of $G$, can be completed to a matrix in the convex

  20. Intermittency analysis of correlated data

    International Nuclear Information System (INIS)

    Wosiek, B.

    1992-01-01

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

  1. Cross-validation analysis for genetic evaluation models for ranking in endurance horses.

    Science.gov (United States)

    García-Ballesteros, S; Varona, L; Valera, M; Gutiérrez, J P; Cervantes, I

    2018-01-01

    Ranking trait was used as a selection criterion for competition horses to estimate racing performance. In the literature the most common approaches to estimate breeding values are the linear or threshold statistical models. However, recent studies have shown that a Thurstonian approach was able to fix the race effect (competitive level of the horses that participate in the same race), thus suggesting a better prediction accuracy of breeding values for ranking trait. The aim of this study was to compare the predictability of linear, threshold and Thurstonian approaches for genetic evaluation of ranking in endurance horses. For this purpose, eight genetic models were used for each approach with different combinations of random effects: rider, rider-horse interaction and environmental permanent effect. All genetic models included gender, age and race as systematic effects. The database that was used contained 4065 ranking records from 966 horses and that for the pedigree contained 8733 animals (47% Arabian horses), with an estimated heritability around 0.10 for the ranking trait. The prediction ability of the models for racing performance was evaluated using a cross-validation approach. The average correlation between real and predicted performances across genetic models was around 0.25 for threshold, 0.58 for linear and 0.60 for Thurstonian approaches. Although no significant differences were found between models within approaches, the best genetic model included: the rider and rider-horse random effects for threshold, only rider and environmental permanent effects for linear approach and all random effects for Thurstonian approach. The absolute correlations of predicted breeding values among models were higher between threshold and Thurstonian: 0.90, 0.91 and 0.88 for all animals, top 20% and top 5% best animals. For rank correlations these figures were 0.85, 0.84 and 0.86. The lower values were those between linear and threshold approaches (0.65, 0.62 and 0.51). In

  2. Reduced Rank Mixed Effects Models for Spatially Correlated Hierarchical Functional Data

    KAUST Repository

    Zhou, Lan

    2010-03-01

    Hierarchical functional data are widely seen in complex studies where sub-units are nested within units, which in turn are nested within treatment groups. We propose a general framework of functional mixed effects model for such data: within unit and within sub-unit variations are modeled through two separate sets of principal components; the sub-unit level functions are allowed to be correlated. Penalized splines are used to model both the mean functions and the principal components functions, where roughness penalties are used to regularize the spline fit. An EM algorithm is developed to fit the model, while the specific covariance structure of the model is utilized for computational efficiency to avoid storage and inversion of large matrices. Our dimension reduction with principal components provides an effective solution to the difficult tasks of modeling the covariance kernel of a random function and modeling the correlation between functions. The proposed methodology is illustrated using simulations and an empirical data set from a colon carcinogenesis study. Supplemental materials are available online.

  3. Outlier Ranking via Subspace Analysis in Multiple Views of the Data

    DEFF Research Database (Denmark)

    Muller, Emmanuel; Assent, Ira; Iglesias, Patricia

    2012-01-01

    , a novel outlier ranking concept. Outrank exploits subspace analysis to determine the degree of outlierness. It considers different subsets of the attributes as individual outlier properties. It compares clustered regions in arbitrary subspaces and derives an outlierness score for each object. Its...... principled integration of multiple views into an outlierness measure uncovers outliers that are not detectable in the full attribute space. Our experimental evaluation demonstrates that Outrank successfully determines a high quality outlier ranking, and outperforms state-of-the-art outlierness measures....

  4. Citation analysis of mental health nursing journals: how should we rank thee?

    Science.gov (United States)

    Hunt, Glenn E; Happell, Brenda; Chan, Sally W-C; Cleary, Michelle

    2012-12-01

    The journal impact factor (JIF), and how best to rate the performance of a journal and the articles they contain, are areas of great debate. The aim of this paper was to assess various ranking methods of journal quality for mental health nursing journals, and to list the top 10 articles that have received the most number of citations to date. Seven mental health nursing journals were chosen for the analysis of citations they received in 2010, as well as their current impact factors from two sources, and other data for ranking purposes. There was very little difference in the top four mental health nursing journals and their overall rankings when combining various bibliometric indicators. That said, the International Journal of Mental Health Nursing is currently the highest ranked mental health nursing journal based on JIF, but publishes fewer articles per year compared to other journals. Overall, very few articles received 50 or more citations. This study shows that researchers need to consider more than one ranking method when deciding where to send or publish their research. © 2012 The Authors. International Journal of Mental Health Nursing © 2012 Australian College of Mental Health Nurses Inc.

  5. Introducing trimming and function ranking to Solid Works based on function analysis

    NARCIS (Netherlands)

    Chechurin, Leonid S.; Wits, Wessel Willems; Bakker, Hans M.; Cascini, G.; Vaneker, Thomas H.J.

    2011-01-01

    TRIZ based Function Analysis models existing products based on functional interactions between product parts. Such a function model description is the ideal starting point for product innovation. Design engineers can apply (TRIZ) methods such as trimming and function ranking to this function model

  6. Introducing Trimming and Function Ranking to SolidWorks based on Function Analysis

    NARCIS (Netherlands)

    Chechurin, L.S.; Wits, Wessel Willems; Bakker, Hans M.; Vaneker, Thomas H.J.

    2015-01-01

    TRIZ based Function Analysis models existing products based on functional interactions between product parts. Such a function model description is the ideal starting point for product innovation. Design engineers can apply (TRIZ) methods such as trimming and function ranking to this function model

  7. Rank-ordered multifractal analysis for intermittent fluctuations with global crossover behavior

    International Nuclear Information System (INIS)

    Tam, Sunny W. Y.; Chang, Tom; Kintner, Paul M.; Klatt, Eric M.

    2010-01-01

    The rank-ordered multifractal analysis (ROMA), a recently developed technique that combines the ideas of parametric rank ordering and one-parameter scaling of monofractals, has the capabilities of deciphering the multifractal characteristics of intermittent fluctuations. The method allows one to understand the multifractal properties through rank-ordered scaling or nonscaling parametric variables. The idea of the ROMA technique is applied to analyze the multifractal characteristics of the auroral zone electric-field fluctuations observed by the SIERRA sounding rocket. The observed fluctuations span across contiguous multiple regimes of scales with different multifractal characteristics. We extend the ROMA technique such that it can take into account the crossover behavior - with the possibility of collapsing probability distribution functions - over these contiguous regimes.

  8. Support vector methods for survival analysis: a comparison between ranking and regression approaches.

    Science.gov (United States)

    Van Belle, Vanya; Pelckmans, Kristiaan; Van Huffel, Sabine; Suykens, Johan A K

    2011-10-01

    To compare and evaluate ranking, regression and combined machine learning approaches for the analysis of survival data. The literature describes two approaches based on support vector machines to deal with censored observations. In the first approach the key idea is to rephrase the task as a ranking problem via the concordance index, a problem which can be solved efficiently in a context of structural risk minimization and convex optimization techniques. In a second approach, one uses a regression approach, dealing with censoring by means of inequality constraints. The goal of this paper is then twofold: (i) introducing a new model combining the ranking and regression strategy, which retains the link with existing survival models such as the proportional hazards model via transformation models; and (ii) comparison of the three techniques on 6 clinical and 3 high-dimensional datasets and discussing the relevance of these techniques over classical approaches fur survival data. We compare svm-based survival models based on ranking constraints, based on regression constraints and models based on both ranking and regression constraints. The performance of the models is compared by means of three different measures: (i) the concordance index, measuring the model's discriminating ability; (ii) the logrank test statistic, indicating whether patients with a prognostic index lower than the median prognostic index have a significant different survival than patients with a prognostic index higher than the median; and (iii) the hazard ratio after normalization to restrict the prognostic index between 0 and 1. Our results indicate a significantly better performance for models including regression constraints above models only based on ranking constraints. This work gives empirical evidence that svm-based models using regression constraints perform significantly better than svm-based models based on ranking constraints. Our experiments show a comparable performance for methods

  9. Citation ranking versus peer evaluation of senior faculty research performance

    DEFF Research Database (Denmark)

    Meho, Lokman I.; Sonnenwald, Diane H.

    2000-01-01

    The purpose of this study is to analyze the relationship between citation ranking and peer evaluation in assessing senior faculty research performance. Other studies typically derive their peer evaluation data directly from referees, often in the form of ranking. This study uses two additional...... indicator of research performance of senior faculty members? Citation data, book reviews, and peer ranking were compiled and examined for faculty members specializing in Kurdish studies. Analysis shows that normalized citation ranking and citation content analysis data yield identical ranking results....... Analysis also shows that normalized citation ranking and citation content analysis, book reviews, and peer ranking perform similarly (i.e., are highly correlated) for high-ranked and low-ranked senior scholars. Additional evaluation methods and measures that take into account the context and content...

  10. Validation of models for analysis of ranks in horse breeding evaluation

    Directory of Open Access Journals (Sweden)

    Ricard Anne

    2010-01-01

    Full Text Available Abstract Background Ranks have been used as phenotypes in the genetic evaluation of horses for a long time through the use of earnings, normal score or raw ranks. A model, ("underlying model" of an unobservable underlying variable responsible for ranks exists. Recently, a full Bayesian analysis using this model was developed. In addition, in reality, competitions are structured into categories according to the technical level of difficulty linked to the technical ability of horses (horses considered to be the "best" meet their peers. The aim of this article was to validate the underlying model through simulations and to propose a more appropriate model with a mixture distribution of horses in the case of a structured competition. The simulations involved 1000 horses with 10 to 50 performances per horse and 4 to 20 horses per event with unstructured and structured competitions. Results The underlying model responsible for ranks performed well with unstructured competitions by drawing liabilities in the Gibbs sampler according to the following rule: the liability of each horse must be drawn in the interval formed by the liabilities of horses ranked before and after the particular horse. The estimated repeatability was the simulated one (0.25 and regression between estimated competing ability of horses and true ability was close to 1. Underestimations of repeatability (0.07 to 0.22 were obtained with other traditional criteria (normal score or raw ranks, but in the case of a structured competition, repeatability was underestimated (0.18 to 0.22. Our results show that the effect of an event, or category of event, is irrelevant in such a situation because ranks are independent of such an effect. The proposed mixture model pools horses according to their participation in different categories of competition during the period observed. This last model gave better results (repeatability 0.25, in particular, it provided an improved estimation of average

  11. Discrepancies between multicriteria decision analysis-based ranking and intuitive ranking for pharmaceutical benefit-risk profiles in a hypothetical setting.

    Science.gov (United States)

    Hoshikawa, K; Ono, S

    2017-02-01

    Multicriteria decision analysis (MCDA) has been generally considered a promising decision-making methodology for the assessment of drug benefit-risk profiles. There have been many discussions in both public and private sectors on its feasibility and applicability, but it has not been employed in official decision-makings. For the purpose of examining to what extent MCDA would reflect the first-hand, intuitive preference of evaluators in practical pharmaceutical assessments, we conducted a questionnaire survey involving the participation of employees of pharmaceutical companies. Showing profiles of the efficacy and safety of four hypothetical drugs, each respondent was asked to rank them following the standard MCDA process and then to rank them intuitively (i.e. without applying any analytical framework). These two approaches resulted in substantially different ranking patterns from the same individuals, and the concordance rate was surprisingly low (17%). Although many respondents intuitively showed a preference for mild, balanced risk-benefit profiles over profiles with a conspicuous advantage in either risk or benefit, the ranking orders based on MCDA scores did not reflect the intuitive preference. Observed discrepancies between the rankings seemed to be primarily attributed to the structural characteristics of MCDA, which assumes that evaluation on each benefit and risk component should have monotonic impact on final scores. It would be difficult for MCDA to reflect commonly observed non-monotonic preferences for risk and benefit profiles. Possible drawbacks of MCDA should be further investigated prior to the real-world application of its benefit-risk assessment. © 2016 John Wiley & Sons Ltd.

  12. A practical sensitivity analysis method for ranking sources of uncertainty in thermal–hydraulics applications

    Energy Technology Data Exchange (ETDEWEB)

    Pourgol-Mohammad, Mohammad, E-mail: pourgolmohammad@sut.ac.ir [Department of Mechanical Engineering, Sahand University of Technology, Tabriz (Iran, Islamic Republic of); Hoseyni, Seyed Mohsen [Department of Basic Sciences, East Tehran Branch, Islamic Azad University, Tehran (Iran, Islamic Republic of); Hoseyni, Seyed Mojtaba [Building & Housing Research Center, Tehran (Iran, Islamic Republic of); Sepanloo, Kamran [Nuclear Science and Technology Research Institute, Tehran (Iran, Islamic Republic of)

    2016-08-15

    Highlights: • Existing uncertainty ranking methods prove inconsistent for TH applications. • Introduction of a new method for ranking sources of uncertainty in TH codes. • Modified PIRT qualitatively identifies and ranks uncertainty sources more precisely. • The importance of parameters is calculated by a limited number of TH code executions. • Methodology is applied successfully on LOFT-LB1 test facility. - Abstract: In application to thermal–hydraulic calculations by system codes, sensitivity analysis plays an important role for managing the uncertainties of code output and risk analysis. Sensitivity analysis is also used to confirm the results of qualitative Phenomena Identification and Ranking Table (PIRT). Several methodologies have been developed to address uncertainty importance assessment. Generally, uncertainty importance measures, mainly devised for the Probabilistic Risk Assessment (PRA) applications, are not affordable for computationally demanding calculations of the complex thermal–hydraulics (TH) system codes. In other words, for effective quantification of the degree of the contribution of each phenomenon to the total uncertainty of the output, a practical approach is needed by considering high computational burden of TH calculations. This study aims primarily to show the inefficiency of the existing approaches and then introduces a solution to cope with the challenges in this area by modification of variance-based uncertainty importance method. Important parameters are identified by the modified PIRT approach qualitatively then their uncertainty importance is quantified by a local derivative index. The proposed index is attractive from its practicality point of view on TH applications. It is capable of calculating the importance of parameters by a limited number of TH code executions. Application of the proposed methodology is demonstrated on LOFT-LB1 test facility.

  13. A practical sensitivity analysis method for ranking sources of uncertainty in thermal–hydraulics applications

    International Nuclear Information System (INIS)

    Pourgol-Mohammad, Mohammad; Hoseyni, Seyed Mohsen; Hoseyni, Seyed Mojtaba; Sepanloo, Kamran

    2016-01-01

    Highlights: • Existing uncertainty ranking methods prove inconsistent for TH applications. • Introduction of a new method for ranking sources of uncertainty in TH codes. • Modified PIRT qualitatively identifies and ranks uncertainty sources more precisely. • The importance of parameters is calculated by a limited number of TH code executions. • Methodology is applied successfully on LOFT-LB1 test facility. - Abstract: In application to thermal–hydraulic calculations by system codes, sensitivity analysis plays an important role for managing the uncertainties of code output and risk analysis. Sensitivity analysis is also used to confirm the results of qualitative Phenomena Identification and Ranking Table (PIRT). Several methodologies have been developed to address uncertainty importance assessment. Generally, uncertainty importance measures, mainly devised for the Probabilistic Risk Assessment (PRA) applications, are not affordable for computationally demanding calculations of the complex thermal–hydraulics (TH) system codes. In other words, for effective quantification of the degree of the contribution of each phenomenon to the total uncertainty of the output, a practical approach is needed by considering high computational burden of TH calculations. This study aims primarily to show the inefficiency of the existing approaches and then introduces a solution to cope with the challenges in this area by modification of variance-based uncertainty importance method. Important parameters are identified by the modified PIRT approach qualitatively then their uncertainty importance is quantified by a local derivative index. The proposed index is attractive from its practicality point of view on TH applications. It is capable of calculating the importance of parameters by a limited number of TH code executions. Application of the proposed methodology is demonstrated on LOFT-LB1 test facility.

  14. Rank-Ordered Multifractal Analysis (ROMA of probability distributions in fluid turbulence

    Directory of Open Access Journals (Sweden)

    C. C. Wu

    2011-04-01

    Full Text Available Rank-Ordered Multifractal Analysis (ROMA was introduced by Chang and Wu (2008 to describe the multifractal characteristic of intermittent events. The procedure provides a natural connection between the rank-ordered spectrum and the idea of one-parameter scaling for monofractals. This technique has successfully been applied to MHD turbulence simulations and turbulence data observed in various space plasmas. In this paper, the technique is applied to the probability distributions in the inertial range of the turbulent fluid flow, as given in the vast Johns Hopkins University (JHU turbulence database. In addition, a new way of finding the continuous ROMA spectrum and the scaled probability distribution function (PDF simultaneously is introduced.

  15. [Analysis of phylogenetic criteria for estimation of the rank of taxa in methane-oxidizing bacteria].

    Science.gov (United States)

    Romanovskaia, V A; Rokitko, P V

    2011-01-01

    To determine a possibility of application of phylogenetic criteria for estimating the taxa rank, the intra- and interspecies, as well as intergeneric relatedness of methanotrophs on the basis of 16S rRNA gene sequences was estimated. We used sequences of 16S rRNA genes of the studied isolates of obligate methanotrophs which have been deposited in UCM (Ukrainian Collection of Microorganisms), and of type strains of other obligate methanotrophs species (from GenBank database). It is shown, that the levels of interspecies and intergeneric relatedness in different families of methanotrophs are not identical, and therefore they can be used for differentiation of taxa only within one family. The carried out analysis has shown, that it is necessary to reconsider taxonomic position: (1) of two phenotypically similar species of Methylomonas (M. aurantiaca and M. fodinarum), similarity of 16S rRNA genes which is 99.4%, similarity of their total DNA--up to 80% that rather testifies to strain differences, than to species differences; (2) of species Methylomicrobium agile and M album which are phylogenetically more related to genus Methylobacter (97% of affinity), than Methylomicrobium (94% of affinity); (3) of genera of the family Beijerinckiaceae (Methylocella and Methylocapsa), and also genera of the family Methylocystaceae (Methylosinus and Methylocystis), whereas high level of relatedness (97% and more) of these bacteria with other methanotrophic genera (within one family) practically corresponds to a range of relatedness of species (within some genera) in the family Methylococcaceae. When determining phylogenetic criteria which can characterize the ranks of taxa, it was revealed, that the levels of interspecies relatedness of methanotrophic genera of the families Methylocystaceae and Beijerinckiaceae (97.8-99.1% and 97.8%, accordingly) considerably exceed the level of genera formation in the family Methylococcaceae (94.0-98.2%) and, moreover, approach the value of

  16. Analysis of the Financial Times ranking "master in management" with machine learning

    OpenAIRE

    Jansen, Arthur

    2017-01-01

    University rankings play nowadays a major role in the decision of many students with regards to their future schools. Nonetheless, these rankings often remain quite opaque: not all data are made available, the methodology behind the rankings is not well defined, etc. One of the main ranking centred on business schools is the "Master in Management" from the Financial Times. This work aims to study the relevance of this ranking and its possible flaws. Several techniques are conducted, as a robu...

  17. Comparison of multianalyte proficiency test results by sum of ranking differences, principal component analysis, and hierarchical cluster analysis.

    Science.gov (United States)

    Škrbić, Biljana; Héberger, Károly; Durišić-Mladenović, Nataša

    2013-10-01

    Sum of ranking differences (SRD) was applied for comparing multianalyte results obtained by several analytical methods used in one or in different laboratories, i.e., for ranking the overall performances of the methods (or laboratories) in simultaneous determination of the same set of analytes. The data sets for testing of the SRD applicability contained the results reported during one of the proficiency tests (PTs) organized by EU Reference Laboratory for Polycyclic Aromatic Hydrocarbons (EU-RL-PAH). In this way, the SRD was also tested as a discriminant method alternative to existing average performance scores used to compare mutlianalyte PT results. SRD should be used along with the z scores--the most commonly used PT performance statistics. SRD was further developed to handle the same rankings (ties) among laboratories. Two benchmark concentration series were selected as reference: (a) the assigned PAH concentrations (determined precisely beforehand by the EU-RL-PAH) and (b) the averages of all individual PAH concentrations determined by each laboratory. Ranking relative to the assigned values and also to the average (or median) values pointed to the laboratories with the most extreme results, as well as revealed groups of laboratories with similar overall performances. SRD reveals differences between methods or laboratories even if classical test(s) cannot. The ranking was validated using comparison of ranks by random numbers (a randomization test) and using seven folds cross-validation, which highlighted the similarities among the (methods used in) laboratories. Principal component analysis and hierarchical cluster analysis justified the findings based on SRD ranking/grouping. If the PAH-concentrations are row-scaled, (i.e., z scores are analyzed as input for ranking) SRD can still be used for checking the normality of errors. Moreover, cross-validation of SRD on z scores groups the laboratories similarly. The SRD technique is general in nature, i.e., it can

  18. Ranking the Online Documents Based on Relative Credibility Measures

    Directory of Open Access Journals (Sweden)

    Ahmad Dahlan

    2013-09-01

    Full Text Available Information searching is the most popular activity in Internet. Usually the search engine provides the search results ranked by the relevance. However, for a certain purpose that concerns with information credibility, particularly citing information for scientific works, another approach of ranking the search engine results is required. This paper presents a study on developing a new ranking method based on the credibility of information. The method is built up upon two well-known algorithms, PageRank and Citation Analysis. The result of the experiment that used Spearman Rank Correlation Coefficient to compare the proposed rank (generated by the method with the standard rank (generated manually by a group of experts showed that the average Spearman 0 < rS < critical value. It means that the correlation was proven but it was not significant. Hence the proposed rank does not satisfy the standard but the performance could be improved.

  19. Ranking the Online Documents Based on Relative Credibility Measures

    Directory of Open Access Journals (Sweden)

    Ahmad Dahlan

    2009-05-01

    Full Text Available Information searching is the most popular activity in Internet. Usually the search engine provides the search results ranked by the relevance. However, for a certain purpose that concerns with information credibility, particularly citing information for scientific works, another approach of ranking the search engine results is required. This paper presents a study on developing a new ranking method based on the credibility of information. The method is built up upon two well-known algorithms, PageRank and Citation Analysis. The result of the experiment that used Spearman Rank Correlation Coefficient to compare the proposed rank (generated by the method with the standard rank (generated manually by a group of experts showed that the average Spearman 0 < rS < critical value. It means that the correlation was proven but it was not significant. Hence the proposed rank does not satisfy the standard but the performance could be improved.

  20. Uniform approximation is more appropriate for Wilcoxon Rank-Sum Test in gene set analysis.

    Directory of Open Access Journals (Sweden)

    Zhide Fang

    Full Text Available Gene set analysis is widely used to facilitate biological interpretations in the analyses of differential expression from high throughput profiling data. Wilcoxon Rank-Sum (WRS test is one of the commonly used methods in gene set enrichment analysis. It compares the ranks of genes in a gene set against those of genes outside the gene set. This method is easy to implement and it eliminates the dichotomization of genes into significant and non-significant in a competitive hypothesis testing. Due to the large number of genes being examined, it is impractical to calculate the exact null distribution for the WRS test. Therefore, the normal distribution is commonly used as an approximation. However, as we demonstrate in this paper, the normal approximation is problematic when a gene set with relative small number of genes is tested against the large number of genes in the complementary set. In this situation, a uniform approximation is substantially more powerful, more accurate, and less intensive in computation. We demonstrate the advantage of the uniform approximations in Gene Ontology (GO term analysis using simulations and real data sets.

  1. Generalized canonical correlation analysis with missing values

    NARCIS (Netherlands)

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

    2012-01-01

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

  2. Rank Dynamics

    Science.gov (United States)

    Gershenson, Carlos

    Studies of rank distributions have been popular for decades, especially since the work of Zipf. For example, if we rank words of a given language by use frequency (most used word in English is 'the', rank 1; second most common word is 'of', rank 2), the distribution can be approximated roughly with a power law. The same applies for cities (most populated city in a country ranks first), earthquakes, metabolism, the Internet, and dozens of other phenomena. We recently proposed ``rank diversity'' to measure how ranks change in time, using the Google Books Ngram dataset. Studying six languages between 1800 and 2009, we found that the rank diversity curves of languages are universal, adjusted with a sigmoid on log-normal scale. We are studying several other datasets (sports, economies, social systems, urban systems, earthquakes, artificial life). Rank diversity seems to be universal, independently of the shape of the rank distribution. I will present our work in progress towards a general description of the features of rank change in time, along with simple models which reproduce it

  3. Exponential Family Functional data analysis via a low-rank model.

    Science.gov (United States)

    Li, Gen; Huang, Jianhua Z; Shen, Haipeng

    2018-05-08

    In many applications, non-Gaussian data such as binary or count are observed over a continuous domain and there exists a smooth underlying structure for describing such data. We develop a new functional data method to deal with this kind of data when the data are regularly spaced on the continuous domain. Our method, referred to as Exponential Family Functional Principal Component Analysis (EFPCA), assumes the data are generated from an exponential family distribution, and the matrix of the canonical parameters has a low-rank structure. The proposed method flexibly accommodates not only the standard one-way functional data, but also two-way (or bivariate) functional data. In addition, we introduce a new cross validation method for estimating the latent rank of a generalized data matrix. We demonstrate the efficacy of the proposed methods using a comprehensive simulation study. The proposed method is also applied to a real application of the UK mortality study, where data are binomially distributed and two-way functional across age groups and calendar years. The results offer novel insights into the underlying mortality pattern. © 2018, The International Biometric Society.

  4. Functional Multiple-Set Canonical Correlation Analysis

    Science.gov (United States)

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

    2012-01-01

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

  5. Affective Ranking of Movie Scenes Using Physiological Signals and Content Analysis

    OpenAIRE

    Soleymani, Mohammad; Chanel, Guillaume; Kierkels, Joep Johannes Maria; Pun, Thierry

    2008-01-01

    In this paper, we propose an approach for affective ranking of movie scenes based on the emotions that are actually felt by spectators. Such a ranking can be used for characterizing the affective, or emotional, content of video clips. The ranking can for instance help determine which video clip from a database elicits, for a given user, the most joy. This in turn will permit video indexing and retrieval based on affective criteria corresponding to a personalized user affective profile.A datas...

  6. Personality correlates (BAS-BIS), self-perception of social ranking, and cortical (alpha frequency band) modulation in peer-group comparison.

    Science.gov (United States)

    Balconi, Michela; Pagani, Silvia

    2014-06-22

    The perception and interpretation of social hierarchies are a key part of our social life. In the present research we considered the activation of cortical areas, mainly the prefrontal cortex, related to social ranking perception in conjunction with some personality components (BAS - Behavioral Activation System - and BIS - Behavioral Inhibition System). In two experiments we manipulated the perceived superior/inferior status during a competitive cognitive task. Indeed, we created an explicit and strongly reinforced social hierarchy based on incidental rating in an attentional task. Specifically, a peer group comparison was undertaken and improved (Experiment 1) or decreased (Experiment 2) performance was artificially manipulated by the experimenter. For each experiment two groups were compared, based on a BAS and BIS dichotomy. Alpha band modulation in prefrontal cortex, behavioral measures (performance: error rate, ER; response times, RTs), and self-perceived ranking were considered. Repeated measures ANOVAs and regression analyses showed in Experiment 1 a significant improved cognitive performance (decreased ER and RTs) and higher self-perceived ranking in high-BAS participants. Moreover, their prefrontal activity was increased within the left side (alpha band decreasing). Conversely, in Experiment 2 a significant decreased cognitive performance (increased ER and RTs) and lower self-perceived ranking was observed in higher-BIS participants. Their prefrontal right activity was increased in comparison with higher BAS. The regression analyses confirmed the significant predictive role of alpha band modulation with respect of subjects' performance and self-perception of social ranking, differently for BAS/BIS components. The present results suggest that social status perception is directly modulated by cortical activity and personality correlates. Copyright © 2014 Elsevier Inc. All rights reserved.

  7. PageRank analysis reveals topologically expressed genes correspond to psoriasis and their functions are associated with apoptosis resistance.

    Science.gov (United States)

    Zeng, Xue; Zhao, Jingjing; Wu, Xiaohong; Shi, Hongbo; Liu, Wali; Cui, Bingnan; Yang, Li; Ding, Xu; Song, Ping

    2016-05-01

    Psoriasis is an inflammatory skin disease. Deceleration in keratinocyte apoptosis is the most significant pathological change observed in psoriasis. To detect a meaningful correlation between the genes and gene functions associated with the mechanism underlying psoriasis, 927 differentially expressed genes (DEGs) were identified using the Gene Expression Omnibus database, GSE13355 [false discovery rate (FDR) 1] with the package in R langue. The selected DEGs were further constructed using the search tool for the retrieval of interacting genes, in order to analyze the interaction network between the DEGs. Subsequent to PageRank analysis, 14 topological hub genes were identified, and the functions and pathways in the hub genes network were analyzed. The top‑ranked hub gene, estrogen receptor‑1 (ESR1) is downregulated in psoriasis, exhibited binding sites enriched with genes possessing anti‑apoptotic functions. The ESR1 gene encodes estrogen receptor α (ERα); a reduced level of ERα expression provides a crucial foundation in response to the anti‑apoptotic activity of psoriatic keratinocytes by activating the expression of anti‑apoptotic genes. Furthermore, it was detected that the pathway that is associated most significantly with psoriasis is the pathways in cancer. Pathways in cancer may protect psoriatic cells from apoptosis by inhibition of ESR1 expression. The present study provides support towards the investigation of ESR1 gene function and elucidates that the interaction with anti‑apoptotic genes is involved in the underlying biological mechanisms of resistance to apoptosis in psoriasis. However, further investigation is required to confirm the present results.

  8. MiRNA-TF-gene network analysis through ranking of biomolecules for multi-informative uterine leiomyoma dataset.

    Science.gov (United States)

    Mallik, Saurav; Maulik, Ujjwal

    2015-10-01

    Gene ranking is an important problem in bioinformatics. Here, we propose a new framework for ranking biomolecules (viz., miRNAs, transcription-factors/TFs and genes) in a multi-informative uterine leiomyoma dataset having both gene expression and methylation data using (statistical) eigenvector centrality based approach. At first, genes that are both differentially expressed and methylated, are identified using Limma statistical test. A network, comprising these genes, corresponding TFs from TRANSFAC and ITFP databases, and targeter miRNAs from miRWalk database, is then built. The biomolecules are then ranked based on eigenvector centrality. Our proposed method provides better average accuracy in hub gene and non-hub gene classifications than other methods. Furthermore, pre-ranked Gene set enrichment analysis is applied on the pathway database as well as GO-term databases of Molecular Signatures Database with providing a pre-ranked gene-list based on different centrality values for comparing among the ranking methods. Finally, top novel potential gene-markers for the uterine leiomyoma are provided. Copyright © 2015 Elsevier Inc. All rights reserved.

  9. College and University Rankings: Part 2--An Annotated Bibliography of Analysis, Criticism, and Evaluation.

    Science.gov (United States)

    Hattendorf, Lynn C.

    1987-01-01

    This annotated bibliography of recent articles and books on academic rankings updates an article in the Spring 1986 "RQ." Items are listed by subject and ranking in general; individual guides; subject areas including accounting, advertising, biogeography, business, communications, data communications, economics, music, publishing,…

  10. Optimal ranking regime analysis of intra- to multidecadal U.S. climate variability. Part I: Temperature

    Science.gov (United States)

    The Optimal Ranking Regime (ORR) method was used to identify intra- to multi-decadal (IMD) time windows containing significant ranking sequences in U.S. climate division temperature data. The simplicity of the ORR procedure’s output – a time series’ most significant non-overlapping periods of high o...

  11. Comparative Analysis of Rank Aggregation Techniques for Metasearch Using Genetic Algorithm

    Science.gov (United States)

    Kaur, Parneet; Singh, Manpreet; Singh Josan, Gurpreet

    2017-01-01

    Rank Aggregation techniques have found wide applications for metasearch along with other streams such as Sports, Voting System, Stock Markets, and Reduction in Spam. This paper presents the optimization of rank lists for web queries put by the user on different MetaSearch engines. A metaheuristic approach such as Genetic algorithm based rank…

  12. Performances of non-parametric statistics in sensitivity analysis and parameter ranking

    International Nuclear Information System (INIS)

    Saltelli, A.

    1987-01-01

    Twelve parametric and non-parametric sensitivity analysis techniques are compared in the case of non-linear model responses. The test models used are taken from the long-term risk analysis for the disposal of high level radioactive waste in a geological formation. They describe the transport of radionuclides through a set of engineered and natural barriers from the repository to the biosphere and to man. The output data from these models are the dose rates affecting the maximum exposed individual of a critical group at a given point in time. All the techniques are applied to the output from the same Monte Carlo simulations, where a modified version of Latin Hypercube method is used for the sample selection. Hypothesis testing is systematically applied to quantify the degree of confidence in the results given by the various sensitivity estimators. The estimators are ranked according to their robustness and stability, on the basis of two test cases. The conclusions are that no estimator can be considered the best from all points of view and recommend the use of more than just one estimator in sensitivity analysis

  13. Analysis of Survey Results in Terms of Selection of Characteristics of the Mining Rescuer to the Ranks of Rapid Response

    Science.gov (United States)

    Grodzicka, Aneta; Szlązak, Jan

    2016-06-01

    The authors of the current study undertook the subject of the analysis features of the mining rescuer as a member of the ranks of the rescue, with particular emphasis on the following parameters: heart rate, body weight, height, BMI, age and seniority in the mining and rescue. This publication concerns the analysis of the test results of these characteristics rescuer as a potential member of the ranks of the rescue, taking into account its risk appetite, stress resistance, attitude towards life, the role of the team, teamwork, attitude to work, motivation to work and physical fitness.

  14. ANALYSIS OF SURVEY RESULTS IN TERMS OF SELECTION OF CHARACTERISTICS OF THE MINING RESCUER TO THE RANKS OF RAPID RESPONSE

    Directory of Open Access Journals (Sweden)

    Aneta GRODZICKA

    2016-04-01

    Full Text Available The authors of the current study undertook the subject of the analysis features of the mining rescuer as a member of the ranks of the rescue, with particular emphasis on the following parameters: heart rate, body weight, height, BMI, age and seniority in the mining and rescue. This publication concerns the analysis of the test results of these characteristics rescuer as a potential member of the ranks of the rescue, taking into account its risk appetite, stress resistance, attitude towards life, the role of the team, teamwork, attitude to work, motivation to work and physical fitness.

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

    Science.gov (United States)

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

    2016-03-14

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

  16. Ranking of several ground-motion models for seismic hazard analysis in Iran

    International Nuclear Information System (INIS)

    Ghasemi, H; Zare, M; Fukushima, Y

    2008-01-01

    In this study, six attenuation relationships are classified with respect to the ranking scheme proposed by Scherbaum et al (2004 Bull. Seismol. Soc. Am. 94 1–22). First, the strong motions recorded during the 2002 Avaj, 2003 Bam, 2004 Kojour and 2006 Silakhor earthquakes are consistently processed. Then the normalized residual sets are determined for each selected ground-motion model, considering the strong-motion records chosen. The main advantage of these records is that corresponding information about the causative fault plane has been well studied for the selected events. Such information is used to estimate several control parameters which are essential inputs for attenuation relations. The selected relations (Zare et al (1999 Soil Dyn. Earthq. Eng. 18 101–23); Fukushima et al (2003 J. Earthq. Eng. 7 573–98); Sinaeian (2006 PhD Thesis International Institute of Earthquake Engineering and Seismology, Tehran, Iran); Boore and Atkinson (2007 PEER, Report 2007/01); Campbell and Bozorgnia (2007 PEER, Report 2007/02); and Chiou and Youngs (2006 PEER Interim Report for USGS Review)) have been deemed suitable for predicting peak ground-motion amplitudes in the Iranian plateau. Several graphical techniques and goodness-of-fit measures are also applied for statistical distribution analysis of the normalized residual sets. Such analysis reveals ground-motion models, developed using Iranian strong-motion records as the most appropriate ones in the Iranian context. The results of the present study are applicable in seismic hazard assessment projects in Iran

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

    International Nuclear Information System (INIS)

    Jung, Young Mee

    2003-01-01

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

  18. How to Rank Journals.

    Science.gov (United States)

    Bradshaw, Corey J A; Brook, Barry W

    2016-01-01

    There are now many methods available to assess the relative citation performance of peer-reviewed journals. Regardless of their individual faults and advantages, citation-based metrics are used by researchers to maximize the citation potential of their articles, and by employers to rank academic track records. The absolute value of any particular index is arguably meaningless unless compared to other journals, and different metrics result in divergent rankings. To provide a simple yet more objective way to rank journals within and among disciplines, we developed a κ-resampled composite journal rank incorporating five popular citation indices: Impact Factor, Immediacy Index, Source-Normalized Impact Per Paper, SCImago Journal Rank and Google 5-year h-index; this approach provides an index of relative rank uncertainty. We applied the approach to six sample sets of scientific journals from Ecology (n = 100 journals), Medicine (n = 100), Multidisciplinary (n = 50); Ecology + Multidisciplinary (n = 25), Obstetrics & Gynaecology (n = 25) and Marine Biology & Fisheries (n = 25). We then cross-compared the κ-resampled ranking for the Ecology + Multidisciplinary journal set to the results of a survey of 188 publishing ecologists who were asked to rank the same journals, and found a 0.68-0.84 Spearman's ρ correlation between the two rankings datasets. Our composite index approach therefore approximates relative journal reputation, at least for that discipline. Agglomerative and divisive clustering and multi-dimensional scaling techniques applied to the Ecology + Multidisciplinary journal set identified specific clusters of similarly ranked journals, with only Nature & Science separating out from the others. When comparing a selection of journals within or among disciplines, we recommend collecting multiple citation-based metrics for a sample of relevant and realistic journals to calculate the composite rankings and their relative uncertainty windows.

  19. Rank-shaping regularization of exponential spectral analysis for application to functional parametric mapping

    International Nuclear Information System (INIS)

    Turkheimer, Federico E; Hinz, Rainer; Gunn, Roger N; Aston, John A D; Gunn, Steve R; Cunningham, Vincent J

    2003-01-01

    Compartmental models are widely used for the mathematical modelling of dynamic studies acquired with positron emission tomography (PET). The numerical problem involves the estimation of a sum of decaying real exponentials convolved with an input function. In exponential spectral analysis (SA), the nonlinear estimation of the exponential functions is replaced by the linear estimation of the coefficients of a predefined set of exponential basis functions. This set-up guarantees fast estimation and attainment of the global optimum. SA, however, is hampered by high sensitivity to noise and, because of the positivity constraints implemented in the algorithm, cannot be extended to reference region modelling. In this paper, SA limitations are addressed by a new rank-shaping (RS) estimator that defines an appropriate regularization over an unconstrained least-squares solution obtained through singular value decomposition of the exponential base. Shrinkage parameters are conditioned on the expected signal-to-noise ratio. Through application to simulated and real datasets, it is shown that RS ameliorates and extends SA properties in the case of the production of functional parametric maps from PET studies

  20. Ranking environmental projects model based on multicriteria decision-making and the weight sensitivity analysis

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    With the fast growth of Chinese economic,more and more capital will be invested in environmental projects.How to select the environmental investment projects(alternatives)for obtaining the best environmental quality and economic benefits is an important problem for the decision makers.The purpose of this paper is to develop a decision-making model to rank a finite number of alternatives with several and sometimes conflicting criteria.A model for ranking the projects of municipal sewage treatment plants is proposed by using exports' information and the data of the real projects.And,the ranking result is given based on the PROMETHEE method. Furthermore,by means of the concept of the weight stability intervals(WSI),the sensitivity of the ranking results to the size of criteria values and the change of weights value of criteria are discussed.The result shows that some criteria,such as"proportion of benefit to projoct cost",will influence the ranking result of alternatives very strong while others not.The influence are not only from the value of criterion but also from the changing the weight of criterion.So,some criteria such as"proportion of benefit to projoct cost" are key critera for ranking the projects. Decision makers must be cautious to them.

  1. Performance evaluation and ranking of participation Asian countries in 2012 London Olympic Games through Data Envelopment Analysis

    Directory of Open Access Journals (Sweden)

    Hadi Shirouyehzad

    2014-07-01

    Full Text Available The Olympic Games ranking is done through lexicographic multi criteria method in each period. According to this method, the country receiving the most gold medals will have the highest score, and in case of having equal silver medals, comparison will be done according to bronze ones. The problem of this method is to pay the most attention merely to gold medals. Using data envelopment analysis, some studies have recently suggested various ranking for the Olympic Games. The present research uses DEA to rank the participating Asian countries in London Olympic that have at least won one medal. As an output-oriented BCC model, this one considers the number of male and female athletes, received medals in two previous Olympic as well as the number of their presence in the Olympic games as the inputs. Gold, silver and bronze medals are the only output of the model. This model is solved in two forms of female and male athlete combination and their separation. Solving this model makes this opportunity to present a new rankings model for participating Asian countries in the Olympic Games that can be compared with the ranking used by Olympic committee.

  2. Playing for First Place: An Analysis of Online Reviews and Their Impact on Local Market Rankings

    Directory of Open Access Journals (Sweden)

    Dipendra SINGH

    2016-06-01

    Full Text Available Whereas past research studied the impact of online reviews on a hotel’s image, the present study analyzes the impact of various measures of customer engagement on the local market ranking of a hotel. For these purposes, the researchers collected data on a sample of hotels including the number of reviews, absolute rating (i.e. 1-5 stars, and market ranking (i.e. 1st, 2nd, 3rd place on TripAdvisor. The authors tested the relationships between number of reviews, market ranking, overall rating and number of booking transactions. Results revealed that the absolute rating of the hotel was a significant factor in determining its market ranking, whereas other elements such as the number of reviews were not. Since the logarithm used by TripAdvisor and other review sites is of a proprietary nature, research that illuminates the relationships between overall rating, market ranking, and number of reviews, helps illuminate scholar’s and practitioner’s understanding of how to improve hotel performance and online image.

  3. A Ranking Analysis/An Interlinking Approach of New Triangular Fuzzy Cognitive Maps and Combined Effective Time Dependent Matrix

    Science.gov (United States)

    Adiga, Shreemathi; Saraswathi, A.; Praveen Prakash, A.

    2018-04-01

    This paper aims an interlinking approach of new Triangular Fuzzy Cognitive Maps (TrFCM) and Combined Effective Time Dependent (CETD) matrix to find the ranking of the problems of Transgenders. Section one begins with an introduction that briefly describes the scope of Triangular Fuzzy Cognitive Maps (TrFCM) and CETD Matrix. Section two provides the process of causes of problems faced by Transgenders using Fuzzy Triangular Fuzzy Cognitive Maps (TrFCM) method and performs the calculations using the collected data among the Transgender. In Section 3, the reasons for the main causes for the problems of the Transgenders. Section 4 describes the Charles Spearmans coefficients of rank correlation method by interlinking of Triangular Fuzzy Cognitive Maps (TrFCM) Method and CETD Matrix. Section 5 shows the results based on our study.

  4. A multi-criteria analysis approach for ranking and selection of microorganisms for the production of oils for biodiesel production.

    Science.gov (United States)

    Ahmad, Farah B; Zhang, Zhanying; Doherty, William O S; O'Hara, Ian M

    2015-08-01

    Oleaginous microorganisms have potential to be used to produce oils as alternative feedstock for biodiesel production. Microalgae (Chlorella protothecoides and Chlorella zofingiensis), yeasts (Cryptococcus albidus and Rhodotorula mucilaginosa), and fungi (Aspergillus oryzae and Mucor plumbeus) were investigated for their ability to produce oil from glucose, xylose and glycerol. Multi-criteria analysis (MCA) using analytic hierarchy process (AHP) and preference ranking organization method for the enrichment of evaluations (PROMETHEE) with graphical analysis for interactive aid (GAIA), was used to rank and select the preferred microorganisms for oil production for biodiesel application. This was based on a number of criteria viz., oil concentration, content, production rate and yield, substrate consumption rate, fatty acids composition, biomass harvesting and nutrient costs. PROMETHEE selected A. oryzae, M. plumbeus and R. mucilaginosa as the most prospective species for oil production. However, further analysis by GAIA Webs identified A. oryzae and M. plumbeus as the best performing microorganisms. Copyright © 2015 Elsevier Ltd. All rights reserved.

  5. An Analysis of "Rank-Shift" of Compound Complex Sentence Translation

    Science.gov (United States)

    Widarwati, Nunun Tri

    2015-01-01

    The focus of the research is to describe the "rank-shift" of compound complex sentence translation in Harry Potter and the Order of the Phoenix novel translation by Listiana Srisanti and also to describe the accuracy of those translation. This research belongs to qualitative descriptive research which document and informants are being…

  6. Optimal ranking regime analysis of U.S. climate variablility. Part II: Precipitation and streamflow

    Science.gov (United States)

    In a preceding companion paper the Optimal Ranking Regime (ORR) method was used to identify intra- to multi-decadal (IMD) regimes in U.S. climate division temperature data during 1896-2012. Here, the method is used to test for annual and seasonal precipitation regimes during that same period. In add...

  7. School Responsiveness to Quality Rankings. An Empirical Analysis of Secondary Education in the Netherlands

    NARCIS (Netherlands)

    Koning, P.W.C.; van der Wiel, K.

    2012-01-01

    This paper assesses the response of Dutch secondary schools to the publication of relative quality ratings in a national newspaper (Trouw). Our research design exploits the discontinuities in the ranking formula that was used to generate five consecutive levels for the overall quality of schools. We

  8. Structural Analysis of Covariance and Correlation Matrices.

    Science.gov (United States)

    Joreskog, Karl G.

    1978-01-01

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

  9. Correlation analysis in chemistry: recent advances

    National Research Council Canada - National Science Library

    Shorter, John; Chapman, Norman Bellamy

    1978-01-01

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

  10. Pathways of topological rank analysis (PoTRA: a novel method to detect pathways involved in hepatocellular carcinoma

    Directory of Open Access Journals (Sweden)

    Chaoxing Li

    2018-04-01

    Full Text Available Complex diseases such as cancer are usually the result of a combination of environmental factors and one or several biological pathways consisting of sets of genes. Each biological pathway exerts its function by delivering signaling through the gene network. Theoretically, a pathway is supposed to have a robust topological structure under normal physiological conditions. However, the pathway’s topological structure could be altered under some pathological condition. It is well known that a normal biological network includes a small number of well-connected hub nodes and a large number of nodes that are non-hubs. In addition, it is reported that the loss of connectivity is a common topological trait of cancer networks, which is an assumption of our method. Hence, from normal to cancer, the process of the network losing connectivity might be the process of disrupting the structure of the network, namely, the number of hub genes might be altered in cancer compared to that in normal or the distribution of topological ranks of genes might be altered. Based on this, we propose a new PageRank-based method called Pathways of Topological Rank Analysis (PoTRA to detect pathways involved in cancer. We use PageRank to measure the relative topological ranks of genes in each biological pathway, then select hub genes for each pathway, and use Fisher’s exact test to test if the number of hub genes in each pathway is altered from normal to cancer. Alternatively, if the distribution of topological ranks of gene in a pathway is altered between normal and cancer, this pathway might also be involved in cancer. Hence, we use the Kolmogorov–Smirnov test to detect pathways that have an altered distribution of topological ranks of genes between two phenotypes. We apply PoTRA to study hepatocellular carcinoma (HCC and several subtypes of HCC. Very interestingly, we discover that all significant pathways in HCC are cancer-associated generally, while several

  11. Pathways of topological rank analysis (PoTRA): a novel method to detect pathways involved in hepatocellular carcinoma.

    Science.gov (United States)

    Li, Chaoxing; Liu, Li; Dinu, Valentin

    2018-01-01

    Complex diseases such as cancer are usually the result of a combination of environmental factors and one or several biological pathways consisting of sets of genes. Each biological pathway exerts its function by delivering signaling through the gene network. Theoretically, a pathway is supposed to have a robust topological structure under normal physiological conditions. However, the pathway's topological structure could be altered under some pathological condition. It is well known that a normal biological network includes a small number of well-connected hub nodes and a large number of nodes that are non-hubs. In addition, it is reported that the loss of connectivity is a common topological trait of cancer networks, which is an assumption of our method. Hence, from normal to cancer, the process of the network losing connectivity might be the process of disrupting the structure of the network, namely, the number of hub genes might be altered in cancer compared to that in normal or the distribution of topological ranks of genes might be altered. Based on this, we propose a new PageRank-based method called Pathways of Topological Rank Analysis (PoTRA) to detect pathways involved in cancer. We use PageRank to measure the relative topological ranks of genes in each biological pathway, then select hub genes for each pathway, and use Fisher's exact test to test if the number of hub genes in each pathway is altered from normal to cancer. Alternatively, if the distribution of topological ranks of gene in a pathway is altered between normal and cancer, this pathway might also be involved in cancer. Hence, we use the Kolmogorov-Smirnov test to detect pathways that have an altered distribution of topological ranks of genes between two phenotypes. We apply PoTRA to study hepatocellular carcinoma (HCC) and several subtypes of HCC. Very interestingly, we discover that all significant pathways in HCC are cancer-associated generally, while several significant pathways in subtypes

  12. University Rankings: The Web Ranking

    Science.gov (United States)

    Aguillo, Isidro F.

    2012-01-01

    The publication in 2003 of the Ranking of Universities by Jiao Tong University of Shanghai has revolutionized not only academic studies on Higher Education, but has also had an important impact on the national policies and the individual strategies of the sector. The work gathers the main characteristics of this and other global university…

  13. Aspects of analysis of small-sample right censored data using generalized Wilcoxon rank tests

    OpenAIRE

    Öhman, Marie-Louise

    1994-01-01

    The estimated bias and variance of commonly applied and jackknife variance estimators and observed significance level and power of standardised generalized Wilcoxon linear rank sum test statistics and tests, respectively, of Gehan and Prentice are compared in a Monte Carlo simulation study. The variance estimators are the permutational-, the conditional permutational- and the jackknife variance estimators of the test statistic of Gehan, and the asymptotic- and the jackknife variance estimator...

  14. Analysis of international content of ranked nursing journals in 2005 using ex post facto design.

    Science.gov (United States)

    Dougherty, Molly C; Lin, Shu-Yuan; McKenna, Hugh P; Seers, Kate; Keeney, Sinead

    2011-06-01

    The purpose of this study was to examine articles in ISI-ranked nursing journals and to analyse the articles and journals, using definitions of international and article content. Growing emphasis on global health includes attention on international nursing literature. Contributions from Latin America and Africa have been reported. Attention to ranked nursing journals to support scholarship in global health is needed. Using an ex post facto design, characteristics of 2827 articles, authors and journals of 32 ranked nursing journals for the year 2005 were analysed between June 2006 and June 2007. Using definitions of international and of article content, research questions were analysed statistically. (a) 928 (32·8%) articles were international; (b) 2016 (71·3%) articles were empirical or scholarly; (c) 826 (89·3%) articles reflecting international content were scholarly or empirical; (d) among international articles more were empirical (66·3 % vs. 32·8 %; χ(2) ((1)) = 283·6, P international articles more were scholarly (29·2 % vs. 22·7 %; χ(2) ((1)) = 15·85, P international, based on author characteristics; (f) 20 (62·5 %) journals were led by an international editorial team; and (g) international journals had more international articles (3·6 % vs. 29·2 %; χ(2) ((1)) = 175·75, P international journals (t = -14·43, P international journals. Results indicate the need to examine the international relevance of the nursing literature. © 2011 Blackwell Publishing Ltd.

  15. Pipeline for the Analysis of ChIP-seq Data and New Motif Ranking Procedure

    KAUST Repository

    Ashoor, Haitham

    2011-06-01

    This thesis presents a computational methodology for ab-initio identification of transcription factor binding sites based on ChIP-seq data. This method consists of three main steps, namely ChIP-seq data processing, motif discovery and models selection. A novel method for ranking the models of motifs identified in this process is proposed. This method combines multiple factors in order to rank the provided candidate motifs. It combines the model coverage of the ChIP-seq fragments that contain motifs from which that model is built, the suitable background data made up of shuffled ChIP-seq fragments, and the p-value that resulted from evaluating the model on actual and background data. Two ChIP-seq datasets retrieved from ENCODE project are used to evaluate and demonstrate the ability of the method to predict correct TFBSs with high precision. The first dataset relates to neuron-restrictive silencer factor, NRSF, while the second one corresponds to growth-associated binding protein, GABP. The pipeline system shows high precision prediction for both datasets, as in both cases the top ranked motif closely resembles the known motifs for the respective transcription factors.

  16. A multi-criteria decision analysis approach for importance identification and ranking of network components

    International Nuclear Information System (INIS)

    Almoghathawi, Yasser; Barker, Kash; Rocco, Claudio M.; Nicholson, Charles D.

    2017-01-01

    Analyzing network vulnerability is a key element of network planning in order to be prepared for any disruptive event that might impact the performance of the network. Hence, many importance measures have been proposed to identify the important components in a network with respect to vulnerability and rank them accordingly based on individual importance measure. However, in this paper, we propose a new approach to identify the most important network components based on multiple importance measures using a multi criteria decision making (MCDM) method, namely the technique for order performance by similarity to ideal solution (TOPSIS), able to take into account the preferences of decision-makers. We consider multiple edge-specific flow-based importance measures provided as the multiple criteria of a network where the alternatives are the edges. Accordingly, TOPSIS is used to rank the edges of the network based on their importance considering multiple different importance measures. The proposed approach is illustrated through different networks with different densities along with the effects of weighs. - Highlights: • We integrate several perspectives on network vulnerability to generate a component importance ranking. • We apply these measures to determine the importance of edges after disruptions. • Networks of varying size and density are explored.

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

    Science.gov (United States)

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

    2018-03-01

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

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

    Directory of Open Access Journals (Sweden)

    Jinchao Feng

    2018-03-01

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

  19. Directional semivariogram analysis to identify and rank controls on the spatial variability of fracture networks

    Science.gov (United States)

    Hanke, John R.; Fischer, Mark P.; Pollyea, Ryan M.

    2018-03-01

    In this study, the directional semivariogram is deployed to investigate the spatial variability of map-scale fracture network attributes in the Paradox Basin, Utah. The relative variability ratio (R) is introduced as the ratio of integrated anisotropic semivariogram models, and R is shown to be an effective metric for quantifying the magnitude of spatial variability for any two azimuthal directions. R is applied to a GIS-based data set comprising roughly 1200 fractures, in an area which is bounded by a map-scale anticline and a km-scale normal fault. This analysis reveals that proximity to the fault strongly influences the magnitude of spatial variability for both fracture intensity and intersection density within 1-2 km. Additionally, there is significant anisotropy in the spatial variability, which is correlated with trends of the anticline and fault. The direction of minimum spatial correlation is normal to the fault at proximal distances, and gradually rotates and becomes subparallel to the fold axis over the same 1-2 km distance away from the fault. We interpret these changes to reflect varying scales of influence of the fault and the fold on fracture network development: the fault locally influences the magnitude and variability of fracture network attributes, whereas the fold sets the background level and structure of directional variability.

  20. Lake and Reservoir Evaporation Estimation: Sensitivity Analysis and Ranking Existing Methods

    Directory of Open Access Journals (Sweden)

    maysam majidi

    2016-02-01

    were acquired from the Doosti Dam weather station. Relative humidity, wind speed, atmospheric pressure and precipitation were acquired from the Pol−Khatoon weather station. Dew point temperature and sunshine data were collected from the Sarakhs weather station. Lake area was estimated from hypsometric curve in relation to lake level data. Temperature measurements were often performed in 16−day periods or biweekly from September 2011 to September 2012. Temperature profile of the lake (required for lake evaporation estimation was measured at different points of the reservoir using a portable multi−meter. The eighteen existing methods were compared and ranked based on Bowen ratio energy balance method (BREB. Results and Discussion: The estimated annual evaporation values by all of the applied methods in this study, ranged from 21 to 113mcm (million cubic meters. BREB annual evaporation obtained value was equal to 69.86mcm and evaporation rate averaged 5.47mm d-1 during the study period. According to the results, there is a relatively large difference between the obtained evaporation values from the adopted methods. The sensitivity analysis of evaporation methods for some input parameters indicated that the Hamon method (Eq. 16 was the most sensitive to the input parameters followed by the Brutsaert−Stricker and BREB, and radiation−temperature methods (Makkink, Jensen−Haise and Stephen−Stewart had the least sensitivity to input data. Besides, the air temperature, solar radiation (sunshine data, water surface temperature and wind speed data had the most effect on lake evaporation estimations, respectively. Finally, all evaporation estimation methods in this study have been ranked based on RMSD values. On a daily basis, the Jensen−Haise and the Makkink (solar radiation, temperature group, Penman (Combination group and Hamon (temperature, day length group methods had a relatively reasonable performance. As the results on a monthly scale, the Jensen−Haise and

  1. A rank-based algorithm of differential expression analysis for small cell line data with statistical control.

    Science.gov (United States)

    Li, Xiangyu; Cai, Hao; Wang, Xianlong; Ao, Lu; Guo, You; He, Jun; Gu, Yunyan; Qi, Lishuang; Guan, Qingzhou; Lin, Xu; Guo, Zheng

    2017-10-13

    To detect differentially expressed genes (DEGs) in small-scale cell line experiments, usually with only two or three technical replicates for each state, the commonly used statistical methods such as significance analysis of microarrays (SAM), limma and RankProd (RP) lack statistical power, while the fold change method lacks any statistical control. In this study, we demonstrated that the within-sample relative expression orderings (REOs) of gene pairs were highly stable among technical replicates of a cell line but often widely disrupted after certain treatments such like gene knockdown, gene transfection and drug treatment. Based on this finding, we customized the RankComp algorithm, previously designed for individualized differential expression analysis through REO comparison, to identify DEGs with certain statistical control for small-scale cell line data. In both simulated and real data, the new algorithm, named CellComp, exhibited high precision with much higher sensitivity than the original RankComp, SAM, limma and RP methods. Therefore, CellComp provides an efficient tool for analyzing small-scale cell line data. © The Author 2017. Published by Oxford University Press.

  2. Impact factor analysis: combining prediction with parameter ranking to reveal the impact of behavior on health outcome

    DEFF Research Database (Denmark)

    Doryab, Afsaneh; Frost, Mads; Faurholt-Jepsen, Maria

    2015-01-01

    An increasing number of healthcare systems allow people to monitor behavior and provide feedback on health and wellness. Most applications, however, only offer feedback on behavior in form of visualization and data summaries. This paper presents a different approach—called impact factor analysis—...... in monitoring and control of mental illness, and we argue that the impact factor analysis can be useful in the design of other health and wellness systems....... ten bipolar patients, in which we were able to estimate mood values with an average mean absolute error of 0.5. This was used to rank the behavior parameters whose variations indicate changes in the mental state. The rankings acquired from our algorithms correspond to the patients’ rankings......, identifying physical activity and sleep as the highest impact parameters. These results revealed the feasibility of identifying behavioral impact factors. This data analysis motivated us to design an impact factor inference engine as part of the MONARCA system. To our knowledge, this is a novel approach...

  3. [The relationship between Ridit analysis and rank sum test for one-way ordinal contingency table in medical research].

    Science.gov (United States)

    Wang, Ling; Xia, Jie-lai; Yu, Li-li; Li, Chan-juan; Wang, Su-zhen

    2008-06-01

    To explore several numerical methods of ordinal variable in one-way ordinal contingency table and their interrelationship, and to compare corresponding statistical analysis methods such as Ridit analysis and rank sum test. Formula deduction was based on five simplified grading approaches including rank_r(i), ridit_r(i), ridit_r(ci), ridit_r(mi), and table scores. Practical data set was verified by SAS8.2 in clinical practice (to test the effect of Shiwei solution in treatment for chronic tracheitis). Because of the linear relationship of rank_r(i) = N ridit_r(i) + 1/2 = N ridit_r(ci) = (N + 1) ridit_r(mi), the exact chi2 values in Ridit analysis based on ridit_r(i), ridit_r(ci), and ridit_r(mi), were completely the same, and they were equivalent to the Kruskal-Wallis H test. Traditional Ridit analysis was based on ridit_r(i), and its corresponding chi2 value calculated with an approximate variance (1/12) was conservative. The exact chi2 test of Ridit analysis should be used when comparing multiple groups in the clinical researches because of its special merits such as distribution of mean ridit value on (0,1) and clear graph expression. The exact chi2 test of Ridit analysis can be output directly by proc freq of SAS8.2 with ridit and modridit option (SCORES =). The exact chi2 test of Ridit analysis is equivalent to the Kruskal-Wallis H test, and should be used when comparing multiple groups in the clinical researches.

  4. Generalized canonical correlation analysis with missing values

    NARCIS (Netherlands)

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

    2009-01-01

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

  5. Detrended cross-correlation analysis of electroencephalogram

    International Nuclear Information System (INIS)

    Wang Jun; Zhao Da-Qing

    2012-01-01

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

  6. Variations of DOM quality in inflows of a drinking water reservoir: linking of van Krevelen diagrams with EEMF spectra by rank correlation.

    Science.gov (United States)

    Herzsprung, Peter; von Tümpling, Wolf; Hertkorn, Norbert; Harir, Mourad; Büttner, Olaf; Bravidor, Jenny; Friese, Kurt; Schmitt-Kopplin, Philippe

    2012-05-15

    Elevated concentrations of dissolved organic matter (DOM) such as humic substances in raw water pose significant challenges during the processing of the commercial drinking water supplies. This is a relevant issue in Saxony, Central East Germany, and many other regions worldwide, where drinking water is produced from raw waters with noticeable presence of chromophoric DOM (CDOM), which is assumed to originate from forested watersheds in spring regions of the catchment area. For improved comprehension of DOM molecular composition, the seasonal and spatial variations of humic-like fluorescence and elemental formulas in the catchment area of the Muldenberg reservoir were recorded by excitation emission matrix fluorescence (EEMF) and ultrahigh-resolution mass spectrometry (FT-ICR-MS). The Spearman rank correlation was applied to link the EEMF intensities with exact molecular formulas and their corresponding relative mass peak abundances. Thereby, humic-like fluorescence could be allocated to the pool of oxygen-rich and relatively unsaturated components with stoichiometries similar to those of tannic acids, which are suspected to have a comparatively high disinfection byproduct formation potential associated with the chlorination of raw water. Analogous relationships were established for UV absorption at 254 nm (UV(254)) and dissolved organic carbon (DOC) and compared to the EEMF correlation.

  7. Satisfaction with Information Centers, E-Journals and Specilized Databases and their Correlation with the Age and Academic Rank of Faculty Members

    Directory of Open Access Journals (Sweden)

    Mojdeh Salajegheh

    2010-04-01

    Full Text Available The present study intends to study the extent of utilization of information centers and e-journals as well as satisfaction rate and to correlate these with age and academic status of faculty members at medical schools in Iranian medical universities. A questionnaire was used for data collection. 700 faculty members were selected using regular random sampling. Results indicate that faculty members use e-journals more than printed journals. Satisfaction rate with databases as well as their utilization is high. Digital libraries are used heavily for document access. A combination of digital library and print library comes second, followed by using print libraries exclusively. The study further demonstrates that there is a link between variables such as age and using e-journals, age and using information centers, age and satisfaction with specialized databases. There was no correlation between academic status and e-journal usage, academic status and satisfaction with electronic databases and academic ranking with using information centers.

  8. Analysis of high-throughput biological data using their rank values.

    Science.gov (United States)

    Dembélé, Doulaye

    2018-01-01

    High-throughput biological technologies are routinely used to generate gene expression profiling or cytogenetics data. To achieve high performance, methods available in the literature become more specialized and often require high computational resources. Here, we propose a new versatile method based on the data-ordering rank values. We use linear algebra, the Perron-Frobenius theorem and also extend a method presented earlier for searching differentially expressed genes for the detection of recurrent copy number aberration. A result derived from the proposed method is a one-sample Student's t-test based on rank values. The proposed method is to our knowledge the only that applies to gene expression profiling and to cytogenetics data sets. This new method is fast, deterministic, and requires a low computational load. Probabilities are associated with genes to allow a statistically significant subset selection in the data set. Stability scores are also introduced as quality parameters. The performance and comparative analyses were carried out using real data sets. The proposed method can be accessed through an R package available from the CRAN (Comprehensive R Archive Network) website: https://cran.r-project.org/web/packages/fcros .

  9. Multicollinearity in canonical correlation analysis in maize.

    Science.gov (United States)

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

    2017-03-30

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

  10. Bayesian Correlation Analysis for Sequence Count Data.

    Directory of Open Access Journals (Sweden)

    Daniel Sánchez-Taltavull

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

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

    Science.gov (United States)

    Han, Fang; Liu, Han

    2017-02-01

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

  12. Wilcoxon signed-rank-based technique for the pulse-shape analysis of HPGe detectors

    Science.gov (United States)

    Martín, S.; Quintana, B.; Barrientos, D.

    2016-07-01

    The characterization of the electric response of segmented-contact high-purity germanium detectors requires scanning systems capable of accurately associating each pulse with the position of the interaction that generated it. This process requires an algorithm sensitive to changes above the electronic noise in the pulse shapes produced at different positions, depending on the resolution of the Ge crystal. In this work, a pulse-shape comparison technique based on the Wilcoxon signed-rank test has been developed. It provides a method to distinguish pulses coming from different interaction points in the germanium crystal. Therefore, this technique is a necessary step for building a reliable pulse-shape database that can be used later for the determination of the position of interaction for γ-ray tracking spectrometry devices such as AGATA, GRETA or GERDA. The method was validated by comparison with a χ2 test using simulated and experimental pulses corresponding to a Broad Energy germanium detector (BEGe).

  13. Wilcoxon signed-rank-based technique for the pulse-shape analysis of HPGe detectors

    International Nuclear Information System (INIS)

    Martín, S.; Quintana, B.; Barrientos, D.

    2016-01-01

    The characterization of the electric response of segmented-contact high-purity germanium detectors requires scanning systems capable of accurately associating each pulse with the position of the interaction that generated it. This process requires an algorithm sensitive to changes above the electronic noise in the pulse shapes produced at different positions, depending on the resolution of the Ge crystal. In this work, a pulse-shape comparison technique based on the Wilcoxon signed-rank test has been developed. It provides a method to distinguish pulses coming from different interaction points in the germanium crystal. Therefore, this technique is a necessary step for building a reliable pulse-shape database that can be used later for the determination of the position of interaction for γ-ray tracking spectrometry devices such as AGATA, GRETA or GERDA. The method was validated by comparison with a χ"2 test using simulated and experimental pulses corresponding to a Broad Energy germanium detector (BEGe).

  14. Preferences for domestic fuel. Analysis with socio-economic factors and rankings in Kolkata, India

    International Nuclear Information System (INIS)

    Gupta, Gautam; Koehlin, Gunnar

    2006-01-01

    The choice of domestic fuel is a matter of great concern for households and policy makers in India. This paper investigates the demand for domestic fuels when households face four choices: Fuelwood, Coal, Kerosene and LPG. The study is based on a survey of 500 households in Kolkata, India. The demand estimates are conducted using a two-stage process where the first stage investigates choice and the second the quantity used. Determinants of fuel demand are identified and their relative importance shown. Extending the study, the paper also analyses the choice of the main cooking fuel in terms of the households' stated rankings of six fuels for five attributes. The policy discussion indicates that subsidies have less potential to reduce polluting fuels such as coal and fuelwood due to weak cross-price elasticities, while increased availability of LPG and potentially also increased awareness of indoor air pollution have greater prospect. (author)

  15. A rank-based sequence aligner with applications in phylogenetic analysis.

    Directory of Open Access Journals (Sweden)

    Liviu P Dinu

    Full Text Available Recent tools for aligning short DNA reads have been designed to optimize the trade-off between correctness and speed. This paper introduces a method for assigning a set of short DNA reads to a reference genome, under Local Rank Distance (LRD. The rank-based aligner proposed in this work aims to improve correctness over speed. However, some indexing strategies to speed up the aligner are also investigated. The LRD aligner is improved in terms of speed by storing [Formula: see text]-mer positions in a hash table for each read. Another improvement, that produces an approximate LRD aligner, is to consider only the positions in the reference that are likely to represent a good positional match of the read. The proposed aligner is evaluated and compared to other state of the art alignment tools in several experiments. A set of experiments are conducted to determine the precision and the recall of the proposed aligner, in the presence of contaminated reads. In another set of experiments, the proposed aligner is used to find the order, the family, or the species of a new (or unknown organism, given only a set of short Next-Generation Sequencing DNA reads. The empirical results show that the aligner proposed in this work is highly accurate from a biological point of view. Compared to the other evaluated tools, the LRD aligner has the important advantage of being very accurate even for a very low base coverage. Thus, the LRD aligner can be considered as a good alternative to standard alignment tools, especially when the accuracy of the aligner is of high importance. Source code and UNIX binaries of the aligner are freely available for future development and use at http://lrd.herokuapp.com/aligners. The software is implemented in C++ and Java, being supported on UNIX and MS Windows.

  16. Graphology and personality: a correlational analysis

    OpenAIRE

    2008-01-01

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

  17. Global network centrality of university rankings

    Science.gov (United States)

    Guo, Weisi; Del Vecchio, Marco; Pogrebna, Ganna

    2017-10-01

    Universities and higher education institutions form an integral part of the national infrastructure and prestige. As academic research benefits increasingly from international exchange and cooperation, many universities have increased investment in improving and enabling their global connectivity. Yet, the relationship of university performance and its global physical connectedness has not been explored in detail. We conduct, to our knowledge, the first large-scale data-driven analysis into whether there is a correlation between university relative ranking performance and its global connectivity via the air transport network. The results show that local access to global hubs (as measured by air transport network betweenness) strongly and positively correlates with the ranking growth (statistical significance in different models ranges between 5% and 1% level). We also found that the local airport's aggregate flight paths (degree) and capacity (weighted degree) has no effect on university ranking, further showing that global connectivity distance is more important than the capacity of flight connections. We also examined the effect of local city economic development as a confounding variable and no effect was observed suggesting that access to global transportation hubs outweighs economic performance as a determinant of university ranking. The impact of this research is that we have determined the importance of the centrality of global connectivity and, hence, established initial evidence for further exploring potential connections between university ranking and regional investment policies on improving global connectivity.

  18. Diversity rankings among bacterial lineages in soil.

    Science.gov (United States)

    Youssef, Noha H; Elshahed, Mostafa S

    2009-03-01

    We used rarefaction curve analysis and diversity ordering-based approaches to rank the 11 most frequently encountered bacterial lineages in soil according to diversity in 5 previously reported 16S rRNA gene clone libraries derived from agricultural, undisturbed tall grass prairie and forest soils (n=26,140, 28 328, 31 818, 13 001 and 53 533). The Planctomycetes, Firmicutes and the delta-Proteobacteria were consistently ranked among the most diverse lineages in all data sets, whereas the Verrucomicrobia, Gemmatimonadetes and beta-Proteobacteria were consistently ranked among the least diverse. On the other hand, the rankings of alpha-Proteobacteria, Acidobacteria, Actinobacteria, Bacteroidetes and Chloroflexi varied widely in different soil clone libraries. In general, lineages exhibiting largest differences in diversity rankings also exhibited the largest difference in relative abundance in the data sets examined. Within these lineages, a positive correlation between relative abundance and diversity was observed within the Acidobacteria, Actinobacteria and Chloroflexi, and a negative diversity-abundance correlation was observed within the Bacteroidetes. The ecological and evolutionary implications of these results are discussed.

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

    Energy Technology Data Exchange (ETDEWEB)

    Ruusunen, M.

    2013-09-01

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

  20. Functional Multiplex PageRank

    Science.gov (United States)

    Iacovacci, Jacopo; Rahmede, Christoph; Arenas, Alex; Bianconi, Ginestra

    2016-10-01

    Recently it has been recognized that many complex social, technological and biological networks have a multilayer nature and can be described by multiplex networks. Multiplex networks are formed by a set of nodes connected by links having different connotations forming the different layers of the multiplex. Characterizing the centrality of the nodes in a multiplex network is a challenging task since the centrality of the node naturally depends on the importance associated to links of a certain type. Here we propose to assign to each node of a multiplex network a centrality called Functional Multiplex PageRank that is a function of the weights given to every different pattern of connections (multilinks) existent in the multiplex network between any two nodes. Since multilinks distinguish all the possible ways in which the links in different layers can overlap, the Functional Multiplex PageRank can describe important non-linear effects when large relevance or small relevance is assigned to multilinks with overlap. Here we apply the Functional Page Rank to the multiplex airport networks, to the neuronal network of the nematode C. elegans, and to social collaboration and citation networks between scientists. This analysis reveals important differences existing between the most central nodes of these networks, and the correlations between their so-called pattern to success.

  1. Getting to the top: an analysis of 25 years of career rankings trajectories for professional women's tennis.

    Science.gov (United States)

    Kovalchik, Stephanie A; Bane, Michael K; Reid, Machar

    2017-10-01

    Official rankings are the most common measure of success in professional women's tennis. Despite their importance for earning potential and tournament seeding, little is known about ranking trajectories of female players and their influence on career success. Our objective was to conduct a comprehensive study of the career progression of elite female tennis talent. The study examined the ranking trajectories of the top 250 female professionals between 1990 and 2015. Using regression modelling of yearly peak rankings, we found a strong association between the shape of the ranking trajectory and the highest career ranking earned. Players with the highest career peak ranking were the youngest when first ranked. For example, top 10 players were first ranked at age 15.5 years (99% CI = 14.8-15.9), 1.2 years (99% CI = 0.8-1.5) earlier than top 51-100 players. Top 10 players were also ranked in the top 100 longer than other players, holding a top 100 ranking until a mean age of 29.0 years (99% CI = 27.8-30.3) compared with age 24.4 years (99% CI = 23.7-25.2) for top 51-100 players. Ranking trajectories were more distinct with respect to player age than years from first ranking. The present study's findings will be instructive for players, coaches, and administrators in setting goals and assessing athlete development in women's tennis.

  2. Ukraine in the International Rankings of Investment Attractiveness: an Analysis of the Views of Global Agencies and Organizations

    Directory of Open Access Journals (Sweden)

    Shuba Maryna V

    2015-09-01

    Full Text Available The article is aimed at determination of the Ukraine's positions in the most prominent global investment and credit rankings. The article considers the estimations of Ukraine by the Index of investment attractiveness, carried out by the European Business Association, by the Index of economic freedom, the rating of investment attractiveness by the International Business Compass, Doing Business rating, credit ratings by the agencies S&P, Moody's and Fitch. The positive characteristics as to the investment climate in Ukraine have been summarized. To establish a relationship between the economic growth of Ukraine and inflows of the foreign direct investment, a coefficient of steamy correlation between GDP and the foreign direct investment in Ukraine has been calculated. The result of the calculation is indicative of the close relationship and a direct linear dependence between these indicators.

  3. Wilcoxon signed-rank-based technique for the pulse-shape analysis of HPGe detectors

    Energy Technology Data Exchange (ETDEWEB)

    Martín, S., E-mail: sergiomr@usal.es; Quintana, B.; Barrientos, D.

    2016-07-01

    The characterization of the electric response of segmented-contact high-purity germanium detectors requires scanning systems capable of accurately associating each pulse with the position of the interaction that generated it. This process requires an algorithm sensitive to changes above the electronic noise in the pulse shapes produced at different positions, depending on the resolution of the Ge crystal. In this work, a pulse-shape comparison technique based on the Wilcoxon signed-rank test has been developed. It provides a method to distinguish pulses coming from different interaction points in the germanium crystal. Therefore, this technique is a necessary step for building a reliable pulse-shape database that can be used later for the determination of the position of interaction for γ-ray tracking spectrometry devices such as AGATA, GRETA or GERDA. The method was validated by comparison with a χ{sup 2} test using simulated and experimental pulses corresponding to a Broad Energy germanium detector (BEGe).

  4. International Space Station Future Correlation Analysis Improvements

    Science.gov (United States)

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

    2018-01-01

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

  5. Bibliometric analysis of regional Latin America's scientific output in Public Health through SCImago Journal & Country Rank

    Science.gov (United States)

    2014-01-01

    Background In the greater framework of the essential functions of Public Health, our focus is on a systematic, objective, external evaluation of Latin American scientific output, to compare its publications in the area of Public Health with those of other major geographic zones. We aim to describe the regional distribution of output in Public Health, and the level of visibility and specialization, for Latin America; it can then be characterized and compared in the international context. Methods The primary source of information was the Scopus database, using the category “Public Health, Environmental and Occupational Health”, in the period 1996–2011. Data were obtained through the portal of SCImago Journal and Country Rank. Using a set of qualitative (citation-based), quantitative (document recount) and collaborative (authors from more than one country) indicators, we derived complementary data. The methodology serves as an analytical tool for researchers and scientific policy-makers. Results The contribution of Latin America to the arsenal of world science lies more or less midway on the international scale in terms of its output and visibility. Revealed as its greatest strengths are the high level of specialization in Public Health and the sustained growth of output. The main limitations identified were a relative decrease in collaboration and low visibility. Conclusions Collaboration is a key factor behind the development of scientific activity in Latin America. Although this finding can be useful for formulating research policy in Latin American countries, it also underlines the need for further research into patterns of scientific communication in this region, to arrive at more specific recommendations. PMID:24950735

  6. Ranking economic history journals

    DEFF Research Database (Denmark)

    Di Vaio, Gianfranco; Weisdorf, Jacob Louis

    2010-01-01

    This study ranks-for the first time-12 international academic journals that have economic history as their main topic. The ranking is based on data collected for the year 2007. Journals are ranked using standard citation analysis where we adjust for age, size and self-citation of journals. We also...... compare the leading economic history journals with the leading journals in economics in order to measure the influence on economics of economic history, and vice versa. With a few exceptions, our results confirm the general idea about what economic history journals are the most influential for economic...... history, and that, although economic history is quite independent from economics as a whole, knowledge exchange between the two fields is indeed going on....

  7. Ranking Economic History Journals

    DEFF Research Database (Denmark)

    Di Vaio, Gianfranco; Weisdorf, Jacob Louis

    This study ranks - for the first time - 12 international academic journals that have economic history as their main topic. The ranking is based on data collected for the year 2007. Journals are ranked using standard citation analysis where we adjust for age, size and self-citation of journals. We...... also compare the leading economic history journals with the leading journals in economics in order to measure the influence on economics of economic history, and vice versa. With a few exceptions, our results confirm the general idea about what economic history journals are the most influential...... for economic history, and that, although economic history is quite independent from economics as a whole, knowledge exchange between the two fields is indeed going on....

  8. Quantitative Analysis of Mixtures of Monoprotic Acids Applying Modified Model-Based Rank Annihilation Factor Analysis on Variation Matrices of Spectrophotometric Acid-Base Titrations

    Directory of Open Access Journals (Sweden)

    Ebrahim Ghorbani-Kalhor

    2015-04-01

    Full Text Available In the current work, a new version of rank annihilation factor analysis was developedto circumvent the rank deficiency problem in multivariate data measurements.Simultaneous determination of dissociation constant and concentration of monoprotic acids was performed by applying model-based rank annihilation factor analysis on variation matrices of spectrophotometric acid-base titrations data. Variation matrices can be obtained by subtracting first row of data matrix from all rows of the main data matrix. This method uses variation matrices instead of multivariate spectrophotometric acid-base titrations matrices to circumvent the rank deficiency problem in the rank quantitation step. The applicability of this approach was evaluated by simulated data at first stage, then the binary mixtures of ascorbic and sorbic acids as model compounds were investigated by the proposed method. At the end, the proposed method was successfully applied for resolving the ascorbic and sorbic acid in an orange juice real sample. Therefore, unique results were achieved by applying rank annihilation factor analysis on variation matrix and using hard soft model combination advantage without any problem and difficulty in rank determination. Normal 0 false false false EN-US X-NONE AR-SA /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin-top:0cm; mso-para-margin-right:0cm; mso-para-margin-bottom:10.0pt; mso-para-margin-left:0cm; line-height:115%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:Arial; mso-bidi-theme-font:minor-bidi; mso-bidi-language:AR-SA;}    

  9. Incorporation of Socio-Economic Features' Ranking in Multicriteria Analysis Based on Ecosystem Services for Marine Protected Area Planning.

    Directory of Open Access Journals (Sweden)

    Michelle E Portman

    Full Text Available Developed decades ago for spatial choice problems related to zoning in the urban planning field, multicriteria analysis (MCA has more recently been applied to environmental conflicts and presented in several documented cases for the creation of protected area management plans. Its application is considered here for the development of zoning as part of a proposed marine protected area management plan. The case study incorporates specially-explicit conservation features while considering stakeholder preferences, expert opinion and characteristics of data quality. It involves the weighting of criteria using a modified analytical hierarchy process. Experts ranked physical attributes which include socio-economically valued physical features. The parameters used for the ranking of (physical attributes important for socio-economic reasons are derived from the field of ecosystem services assessment. Inclusion of these feature values results in protection that emphasizes those areas closest to shore, most likely because of accessibility and familiarity parameters and because of data biases. Therefore, other spatial conservation prioritization methods should be considered to supplement the MCA and efforts should be made to improve data about ecosystem service values farther from shore. Otherwise, the MCA method allows incorporation of expert and stakeholder preferences and ecosystem services values while maintaining the advantages of simplicity and clarity.

  10. Neophilia Ranking of Scientific Journals.

    Science.gov (United States)

    Packalen, Mikko; Bhattacharya, Jay

    2017-01-01

    The ranking of scientific journals is important because of the signal it sends to scientists about what is considered most vital for scientific progress. Existing ranking systems focus on measuring the influence of a scientific paper (citations)-these rankings do not reward journals for publishing innovative work that builds on new ideas. We propose an alternative ranking based on the proclivity of journals to publish papers that build on new ideas, and we implement this ranking via a text-based analysis of all published biomedical papers dating back to 1946. In addition, we compare our neophilia ranking to citation-based (impact factor) rankings; this comparison shows that the two ranking approaches are distinct. Prior theoretical work suggests an active role for our neophilia index in science policy. Absent an explicit incentive to pursue novel science, scientists underinvest in innovative work because of a coordination problem: for work on a new idea to flourish, many scientists must decide to adopt it in their work. Rankings that are based purely on influence thus do not provide sufficient incentives for publishing innovative work. By contrast, adoption of the neophilia index as part of journal-ranking procedures by funding agencies and university administrators would provide an explicit incentive for journals to publish innovative work and thus help solve the coordination problem by increasing scientists' incentives to pursue innovative work.

  11. 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.

  12. International Space Station Model Correlation Analysis

    Science.gov (United States)

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

    2018-01-01

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

  13. Dynamic PET reconstruction using temporal patch-based low rank penalty for ROI-based brain kinetic analysis

    International Nuclear Information System (INIS)

    Kim, Kyungsang; Ye, Jong Chul; Son, Young Don; Cho, Zang Hee; Bresler, Yoram; Ra, Jong Beom

    2015-01-01

    Dynamic positron emission tomography (PET) is widely used to measure changes in the bio-distribution of radiopharmaceuticals within particular organs of interest over time. However, to retain sufficient temporal resolution, the number of photon counts in each time frame must be limited. Therefore, conventional reconstruction algorithms such as the ordered subset expectation maximization (OSEM) produce noisy reconstruction images, thus degrading the quality of the extracted time activity curves (TACs). To address this issue, many advanced reconstruction algorithms have been developed using various spatio-temporal regularizations. In this paper, we extend earlier results and develop a novel temporal regularization, which exploits the self-similarity of patches that are collected in dynamic images. The main contribution of this paper is to demonstrate that the correlation of patches can be exploited using a low-rank constraint that is insensitive to global intensity variations. The resulting optimization framework is, however, non-Lipschitz and non-convex due to the Poisson log-likelihood and low-rank penalty terms. Direct application of the conventional Poisson image deconvolution by an augmented Lagrangian (PIDAL) algorithm is, however, problematic due to its large memory requirements, which prevents its parallelization. Thus, we propose a novel optimization framework using the concave-convex procedure (CCCP) by exploiting the Legendre–Fenchel transform, which is computationally efficient and parallelizable. In computer simulation and a real in vivo experiment using a high-resolution research tomograph (HRRT) scanner, we confirm that the proposed algorithm can improve image quality while also extracting more accurate region of interests (ROI) based kinetic parameters. Furthermore, we show that the total reconstruction time for HRRT PET is significantly accelerated using our GPU implementation, which makes the algorithm very practical in clinical environments

  14. Wikipedia ranking of world universities

    Science.gov (United States)

    Lages, José; Patt, Antoine; Shepelyansky, Dima L.

    2016-03-01

    We use the directed networks between articles of 24 Wikipedia language editions for producing the wikipedia ranking of world Universities (WRWU) using PageRank, 2DRank and CheiRank algorithms. This approach allows to incorporate various cultural views on world universities using the mathematical statistical analysis independent of cultural preferences. The Wikipedia ranking of top 100 universities provides about 60% overlap with the Shanghai university ranking demonstrating the reliable features of this approach. At the same time WRWU incorporates all knowledge accumulated at 24 Wikipedia editions giving stronger highlights for historically important universities leading to a different estimation of efficiency of world countries in university education. The historical development of university ranking is analyzed during ten centuries of their history.

  15. System Reliability Analysis Considering Correlation of Performances

    Energy Technology Data Exchange (ETDEWEB)

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

    2017-04-15

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

  16. Metrics correlation and analysis service (MCAS)

    International Nuclear Information System (INIS)

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

    2010-01-01

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

  17. Metrics correlation and analysis service (MCAS)

    International Nuclear Information System (INIS)

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

    2009-01-01

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

  18. System Reliability Analysis Considering Correlation of Performances

    International Nuclear Information System (INIS)

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

    2017-01-01

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

  19. Ranking serials in oceanography: An analysis based on the Indian contributions and their citations

    Digital Repository Service at National Institute of Oceanography (India)

    Tapaswi, M.P.; Maheswarappa, B.S.

    An analysis of serials preferred and cited in various communications by the Indian oceanographers during 1963 to 1992 is presented. A shift in preference of serials from general sciences to oceanography (interdisciplinary) and to core subject...

  20. Leaders in Interdependent Contexts Suppress Nonverbal Assertiveness: A Multilevel Analysis of Japanese University Club Leaders' and Members' Rank Signaling.

    Science.gov (United States)

    Ito, Atsuki; Gobel, Matthias S; Uchida, Yukiko

    2018-01-01

    Previous research has shown that leadership is signaled through nonverbal assertiveness. However, those studies have been mostly conducted in individualistic cultural contexts, such as in the U.S. Here, we suggest that one important strategy for goal attainment in collectivistic cultures is for leaders to self-regulate their behaviors. Thus, contrary to the previous evidence from individualistic cultural contexts, in collectivistic cultural contexts, leaders might suppress nonverbal assertiveness. To test this possibility, we assessed nonverbal behaviors (NVB) of Japanese leaders and members, and how they were evaluated by observers. We recruited Japanese leaders and members of university clubs and video-recorded them while introducing their club. Then, we coded their nonverbal rank signaling behavior. Finally, we asked a new set of naïve observers to watch these video-clips and to judge targets' suitability for being possible club leaders. Results of a multilevel analysis (level 1: individual participants, level 2: clubs) suggested that the more the club culture focused on tasks (rather than relationships), the more likely were leaders (but not members) of those clubs to suppress their nonverbal assertiveness. Naïve observers judged individuals who restrained from emitting nonverbal assertiveness as being more suitable and worthy club leaders. Thus, our findings demonstrate the cultural fit between contextual effects at the collective level (i.e., cultural orientation of a group) and the signaling and perceiving of social ranks at the individual level (i.e., suppression of nonverbal assertiveness). We discuss the importance of studying the cultural fit between the collective reality that people inhabit and people's psychology for future research in cultural psychology.

  1. Leaders in Interdependent Contexts Suppress Nonverbal Assertiveness: A Multilevel Analysis of Japanese University Club Leaders' and Members' Rank Signaling

    Directory of Open Access Journals (Sweden)

    Atsuki Ito

    2018-05-01

    Full Text Available Previous research has shown that leadership is signaled through nonverbal assertiveness. However, those studies have been mostly conducted in individualistic cultural contexts, such as in the U.S. Here, we suggest that one important strategy for goal attainment in collectivistic cultures is for leaders to self-regulate their behaviors. Thus, contrary to the previous evidence from individualistic cultural contexts, in collectivistic cultural contexts, leaders might suppress nonverbal assertiveness. To test this possibility, we assessed nonverbal behaviors (NVB of Japanese leaders and members, and how they were evaluated by observers. We recruited Japanese leaders and members of university clubs and video-recorded them while introducing their club. Then, we coded their nonverbal rank signaling behavior. Finally, we asked a new set of naïve observers to watch these video-clips and to judge targets' suitability for being possible club leaders. Results of a multilevel analysis (level 1: individual participants, level 2: clubs suggested that the more the club culture focused on tasks (rather than relationships, the more likely were leaders (but not members of those clubs to suppress their nonverbal assertiveness. Naïve observers judged individuals who restrained from emitting nonverbal assertiveness as being more suitable and worthy club leaders. Thus, our findings demonstrate the cultural fit between contextual effects at the collective level (i.e., cultural orientation of a group and the signaling and perceiving of social ranks at the individual level (i.e., suppression of nonverbal assertiveness. We discuss the importance of studying the cultural fit between the collective reality that people inhabit and people's psychology for future research in cultural psychology.

  2. UQlust: combining profile hashing with linear-time ranking for efficient clustering and analysis of big macromolecular data.

    Science.gov (United States)

    Adamczak, Rafal; Meller, Jarek

    2016-12-28

    Advances in computing have enabled current protein and RNA structure prediction and molecular simulation methods to dramatically increase their sampling of conformational spaces. The quickly growing number of experimentally resolved structures, and databases such as the Protein Data Bank, also implies large scale structural similarity analyses to retrieve and classify macromolecular data. Consequently, the computational cost of structure comparison and clustering for large sets of macromolecular structures has become a bottleneck that necessitates further algorithmic improvements and development of efficient software solutions. uQlust is a versatile and easy-to-use tool for ultrafast ranking and clustering of macromolecular structures. uQlust makes use of structural profiles of proteins and nucleic acids, while combining a linear-time algorithm for implicit comparison of all pairs of models with profile hashing to enable efficient clustering of large data sets with a low memory footprint. In addition to ranking and clustering of large sets of models of the same protein or RNA molecule, uQlust can also be used in conjunction with fragment-based profiles in order to cluster structures of arbitrary length. For example, hierarchical clustering of the entire PDB using profile hashing can be performed on a typical laptop, thus opening an avenue for structural explorations previously limited to dedicated resources. The uQlust package is freely available under the GNU General Public License at https://github.com/uQlust . uQlust represents a drastic reduction in the computational complexity and memory requirements with respect to existing clustering and model quality assessment methods for macromolecular structure analysis, while yielding results on par with traditional approaches for both proteins and RNAs.

  3. Are Health Videos from Hospitals, Health Organizations, and Active Users Available to Health Consumers? An Analysis of Diabetes Health Video Ranking in YouTube

    Science.gov (United States)

    Borras-Morell, Jose-Enrique; Martinez-Millana, Antonio; Karlsen, Randi

    2017-01-01

    Health consumers are increasingly using the Internet to search for health information. The existence of overloaded, inaccurate, obsolete, or simply incorrect health information available on the Internet is a serious obstacle for finding relevant and good-quality data that actually helps patients. Search engines of multimedia Internet platforms are thought to help users to find relevant information according to their search. But, is the information recovered by those search engines from quality sources? Is the health information uploaded from reliable sources, such as hospitals and health organizations, easily available to patients? The availability of videos is directly related to the ranking position in YouTube search. The higher the ranking of the information is, the more accessible it is. The aim of this study is to analyze the ranking evolution of diabetes health videos on YouTube in order to discover how videos from reliable channels, such as hospitals and health organizations, are evolving in the ranking. The analysis was done by tracking the ranking of 2372 videos on a daily basis during a 30-day period using 20 diabetes-related queries. Our conclusions are that the current YouTube algorithm favors the presence of reliable videos in upper rank positions in diabetes-related searches. PMID:28243314

  4. Multi-Trait analysis of growth traits: fitting reduced rank models using principal components for Simmental beef cattle

    Directory of Open Access Journals (Sweden)

    Rodrigo Reis Mota

    2016-09-01

    Full Text Available ABSTRACT: The aim of this research was to evaluate the dimensional reduction of additive direct genetic covariance matrices in genetic evaluations of growth traits (range 100-730 days in Simmental cattle using principal components, as well as to estimate (covariance components and genetic parameters. Principal component analyses were conducted for five different models-one full and four reduced-rank models. Models were compared using Akaike information (AIC and Bayesian information (BIC criteria. Variance components and genetic parameters were estimated by restricted maximum likelihood (REML. The AIC and BIC values were similar among models. This indicated that parsimonious models could be used in genetic evaluations in Simmental cattle. The first principal component explained more than 96% of total variance in both models. Heritability estimates were higher for advanced ages and varied from 0.05 (100 days to 0.30 (730 days. Genetic correlation estimates were similar in both models regardless of magnitude and number of principal components. The first principal component was sufficient to explain almost all genetic variance. Furthermore, genetic parameter similarities and lower computational requirements allowed for parsimonious models in genetic evaluations of growth traits in Simmental cattle.

  5. A Ranking Analysis of the Management Schools in Greater China (2000-2010): Evidence from the SSCI Database

    Science.gov (United States)

    Hou, Mingjun; Fan, Peihua; Liu, Heng

    2014-01-01

    The authors rank the management schools in Greater China (including Mainland China, Hong Kong, Taiwan, and Macau) based on their academic publications in the Social Sciences Citation Index management and business journals from 2000 to 2010. Following K. Ritzberger's (2008) and X. Yu and Z. Gao's (2010) ranking method, the authors develop six…

  6. Sparse structure regularized ranking

    KAUST Repository

    Wang, Jim Jing-Yan; Sun, Yijun; Gao, Xin

    2014-01-01

    Learning ranking scores is critical for the multimedia database retrieval problem. In this paper, we propose a novel ranking score learning algorithm by exploring the sparse structure and using it to regularize ranking scores. To explore the sparse

  7. 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

  8. Embryotoxic and pharmacologic potency ranking of six azoles in the rat whole embryo culture by morphological and transcriptomic analysis

    International Nuclear Information System (INIS)

    Dimopoulou, Myrto; Verhoef, Aart; Pennings, Jeroen L.A.; Ravenzwaay, Bennard van; Rietjens, Ivonne M.C.M.; Piersma, Aldert H.

    2017-01-01

    Differential gene expression analysis in the rat whole embryo culture (WEC) assay provides mechanistic insight into the embryotoxicity of test compounds. In our study, we hypothesized that comparative analysis of the transcriptomes of rat embryos exposed to six azoles (flusilazole, triadimefon, ketoconazole, miconazole, difenoconazole and prothioconazole) could lead to a better mechanism-based understanding of their embryotoxicity and pharmacological action. For evaluating embryotoxicity, we applied the total morphological scoring system (TMS) in embryos exposed for 48 h. The compounds tested showed embryotoxicity in a dose-response fashion. Functional analysis of differential gene expression after 4 h exposure at the ID 10 (effective dose for 10% decreased TMS), revealed the sterol biosynthesis pathway and embryonic development genes, dominated by genes in the retinoic acid (RA) pathway, albeit in a differential way. Flusilazole, ketoconazole and triadimefon were the most potent compounds affecting the RA pathway, while in terms of regulation of sterol function, difenoconazole and ketoconazole showed the most pronounced effects. Dose-dependent analysis of the effects of flusilazole revealed that the RA pathway related genes were already differentially expressed at low dose levels while the sterol pathway showed strong regulation at higher embryotoxic doses, suggesting that this pathway is less predictive for the observed embryotoxicity. A similar analysis at the 24-hour time point indicated an additional time-dependent difference in the aforementioned pathways regulated by flusilazole. In summary, the rat WEC assay in combination with transcriptomics could add a mechanistic insight into the embryotoxic potency ranking and pharmacological mode of action of the tested compounds. - Highlights: • Embryonic exposure to azoles revealed concentration-dependent malformations. • Transcriptomics could enhance the mechanistic knowledge of embryotoxicants. • Retinoic

  9. Embryotoxic and pharmacologic potency ranking of six azoles in the rat whole embryo culture by morphological and transcriptomic analysis

    Energy Technology Data Exchange (ETDEWEB)

    Dimopoulou, Myrto, E-mail: myrto.dimopoulou@wur.nl [Division of Toxicology, Wageningen University (Netherlands); National Institute of Public Health and the Environment (RIVM), Bilthoven (Netherlands); Verhoef, Aart; Pennings, Jeroen L.A. [National Institute of Public Health and the Environment (RIVM), Bilthoven (Netherlands); Ravenzwaay, Bennard van [Division of Toxicology, Wageningen University (Netherlands); BASF SE, Experimental Toxicology and Ecology, Ludwigshafen (Germany); Rietjens, Ivonne M.C.M. [Division of Toxicology, Wageningen University (Netherlands); Piersma, Aldert H. [National Institute of Public Health and the Environment (RIVM), Bilthoven (Netherlands); Institute for Risk Assessment Sciences, Utrecht University, Utrecht (Netherlands)

    2017-05-01

    Differential gene expression analysis in the rat whole embryo culture (WEC) assay provides mechanistic insight into the embryotoxicity of test compounds. In our study, we hypothesized that comparative analysis of the transcriptomes of rat embryos exposed to six azoles (flusilazole, triadimefon, ketoconazole, miconazole, difenoconazole and prothioconazole) could lead to a better mechanism-based understanding of their embryotoxicity and pharmacological action. For evaluating embryotoxicity, we applied the total morphological scoring system (TMS) in embryos exposed for 48 h. The compounds tested showed embryotoxicity in a dose-response fashion. Functional analysis of differential gene expression after 4 h exposure at the ID{sub 10} (effective dose for 10% decreased TMS), revealed the sterol biosynthesis pathway and embryonic development genes, dominated by genes in the retinoic acid (RA) pathway, albeit in a differential way. Flusilazole, ketoconazole and triadimefon were the most potent compounds affecting the RA pathway, while in terms of regulation of sterol function, difenoconazole and ketoconazole showed the most pronounced effects. Dose-dependent analysis of the effects of flusilazole revealed that the RA pathway related genes were already differentially expressed at low dose levels while the sterol pathway showed strong regulation at higher embryotoxic doses, suggesting that this pathway is less predictive for the observed embryotoxicity. A similar analysis at the 24-hour time point indicated an additional time-dependent difference in the aforementioned pathways regulated by flusilazole. In summary, the rat WEC assay in combination with transcriptomics could add a mechanistic insight into the embryotoxic potency ranking and pharmacological mode of action of the tested compounds. - Highlights: • Embryonic exposure to azoles revealed concentration-dependent malformations. • Transcriptomics could enhance the mechanistic knowledge of embryotoxicants.

  10. Ranking the strategies for Indian medical tourism sector through the integration of SWOT analysis and TOPSIS method.

    Science.gov (United States)

    Ajmera, Puneeta

    2017-10-09

    Purpose Organizations have to evaluate their internal and external environments in this highly competitive world. Strengths, weaknesses, opportunities and threats (SWOT) analysis is a very useful technique which analyzes the strengths, weaknesses, opportunities and threats of an organization for taking strategic decisions and it also provides a foundation for the formulation of strategies. But the drawback of SWOT analysis is that it does not quantify the importance of individual factors affecting the organization and the individual factors are described in brief without weighing them. Because of this reason, SWOT analysis can be integrated with any multiple attribute decision-making (MADM) technique like the technique for order preference by similarity to ideal solution (TOPSIS), analytical hierarchy process, etc., to evaluate the best alternative among the available strategic alternatives. The paper aims to discuss these issues. Design/methodology/approach In this study, SWOT analysis is integrated with a multicriteria decision-making technique called TOPSIS to rank different strategies for Indian medical tourism in order of priority. Findings SO strategy (providing best facilitation and care to the medical tourists at par to developed countries) is the best strategy which matches with the four elements of S, W, O and T of SWOT matrix and 35 strategic indicators. Practical implications This paper proposes a solution based on a combined SWOT analysis and TOPSIS approach to help the organizations to evaluate and select strategies. Originality/value Creating a new technology or administering a new strategy always has some degree of resistance by employees. To minimize resistance, the author has used TOPSIS as it involves group thinking, requiring every manager of the organization to analyze and evaluate different alternatives and average measure of each parameter in final decision matrix.

  11. Hybrid Wavelet De-noising and Rank-Set Pair Analysis approach for forecasting hydro-meteorological time series

    Science.gov (United States)

    WANG, D.; Wang, Y.; Zeng, X.

    2017-12-01

    Accurate, fast forecasting of hydro-meteorological time series is presently a major challenge in drought and flood mitigation. This paper proposes a hybrid approach, Wavelet De-noising (WD) and Rank-Set Pair Analysis (RSPA), that takes full advantage of a combination of the two approaches to improve forecasts of hydro-meteorological time series. WD allows decomposition and reconstruction of a time series by the wavelet transform, and hence separation of the noise from the original series. RSPA, a more reliable and efficient version of Set Pair Analysis, is integrated with WD to form the hybrid WD-RSPA approach. Two types of hydro-meteorological data sets with different characteristics and different levels of human influences at some representative stations are used to illustrate the WD-RSPA approach. The approach is also compared to three other generic methods: the conventional Auto Regressive Integrated Moving Average (ARIMA) method, Artificial Neural Networks (ANNs) (BP-error Back Propagation, MLP-Multilayer Perceptron and RBF-Radial Basis Function), and RSPA alone. Nine error metrics are used to evaluate the model performance. The results show that WD-RSPA is accurate, feasible, and effective. In particular, WD-RSPA is found to be the best among the various generic methods compared in this paper, even when the extreme events are included within a time series.

  12. A STUDY ON RANKING METHOD IN RETRIEVING WEB PAGES BASED ON CONTENT AND LINK ANALYSIS: COMBINATION OF FOURIER DOMAIN SCORING AND PAGERANK SCORING

    Directory of Open Access Journals (Sweden)

    Diana Purwitasari

    2008-01-01

    Full Text Available Ranking module is an important component of search process which sorts through relevant pages. Since collection of Web pages has additional information inherent in the hyperlink structure of the Web, it can be represented as link score and then combined with the usual information retrieval techniques of content score. In this paper we report our studies about ranking score of Web pages combined from link analysis, PageRank Scoring, and content analysis, Fourier Domain Scoring. Our experiments use collection of Web pages relate to Statistic subject from Wikipedia with objectives to check correctness and performance evaluation of combination ranking method. Evaluation of PageRank Scoring show that the highest score does not always relate to Statistic. Since the links within Wikipedia articles exists so that users are always one click away from more information on any point that has a link attached, it it possible that unrelated topics to Statistic are most likely frequently mentioned in the collection. While the combination method show link score which is given proportional weight to content score of Web pages does effect the retrieval results.

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

    NARCIS (Netherlands)

    Braak, ter C.J.F.

    1990-01-01

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

  14. Minkowski metrics in creating universal ranking algorithms

    Directory of Open Access Journals (Sweden)

    Andrzej Ameljańczyk

    2014-06-01

    Full Text Available The paper presents a general procedure for creating the rankings of a set of objects, while the relation of preference based on any ranking function. The analysis was possible to use the ranking functions began by showing the fundamental drawbacks of commonly used functions in the form of a weighted sum. As a special case of the ranking procedure in the space of a relation, the procedure based on the notion of an ideal element and generalized Minkowski distance from the element was proposed. This procedure, presented as universal ranking algorithm, eliminates most of the disadvantages of ranking functions in the form of a weighted sum.[b]Keywords[/b]: ranking functions, preference relation, ranking clusters, categories, ideal point, universal ranking algorithm

  15. A Computer-Aided Bibliometrics System for Journal Citation Analysis and Departmental Core Journal Ranking List Generation

    Directory of Open Access Journals (Sweden)

    Yih-Chearng Shiue

    2004-12-01

    Full Text Available Due to the tremendous increase and variation in serial publications, faculties in department of university are finding it difficult to generate and update their departmental core journal list regularly and accurately, and libraries are finding it difficult to maintain their current serial collection for different departments. Therefore, the evaluation of a departmental core journal list is an important task for departmental faculties and librarians. A departmental core journal list not only helps departments understand research performances of faculties and students, but also helps librarians make decisions about which journals to retain and which to cancel. In this study, a Computer-Aided Bibliometrics System was implemented and two methodologies (JCDF and LibJF were proposed in order to generate a departmental core journal ranking list and make the journal citation analysis. Six departments were taken as examples, with MIS as the major one. One journal citation pattern was found and the ratio of Turning point-to-No. journal was always around 0.07 among the 10 journals and 6 departments. After comparing with four methodologies via overlapping rate and standard deviation distances, the two proposed methodologies were shown to be better than questionnaire and library subscription method.

  16. Linear-rank testing of a non-binary, responder-analysis, efficacy score to evaluate pharmacotherapies for substance use disorders.

    Science.gov (United States)

    Holmes, Tyson H; Li, Shou-Hua; McCann, David J

    2016-11-23

    The design of pharmacological trials for management of substance use disorders is shifting toward outcomes of successful individual-level behavior (abstinence or no heavy use). While binary success/failure analyses are common, McCann and Li (CNS Neurosci Ther 2012; 18: 414-418) introduced "number of beyond-threshold weeks of success" (NOBWOS) scores to avoid dichotomized outcomes. NOBWOS scoring employs an efficacy "hurdle" with values reflecting duration of success. Here, we evaluate NOBWOS scores rigorously. Formal analysis of mathematical structure of NOBWOS scores is followed by simulation studies spanning diverse conditions to assess operating characteristics of five linear-rank tests on NOBWOS scores. Simulations include assessment of Fisher's exact test applied to hurdle component. On average, statistical power was approximately equal for five linear-rank tests. Under none of conditions examined did Fisher's exact test exhibit greater statistical power than any of the linear-rank tests. These linear-rank tests provide good Type I and Type II error control for comparing distributions of NOBWOS scores between groups (e.g. active vs. placebo). All methods were applied to re-analyses of data from four clinical trials of differing lengths and substances of abuse. These linear-rank tests agreed across all trials in rejecting (or not) their null (equality of distributions) at ≤ 0.05. © The Author(s) 2016.

  17. The rank-heat plot is a novel way to present the results from a network meta-analysis including multiple outcomes.

    Science.gov (United States)

    Veroniki, Areti Angeliki; Straus, Sharon E; Fyraridis, Alexandros; Tricco, Andrea C

    2016-08-01

    To present a novel and simple graphical approach to improve the presentation of the treatment ranking in a network meta-analysis (NMA) including multiple outcomes. NMA simultaneously compares many relevant interventions for a clinical condition from a network of trials, and allows ranking of the effectiveness and/or safety of each intervention. There are numerous ways to present the NMA results, which can challenge their interpretation by research users. The rank-heat plot is a novel graph that can be used to quickly recognize which interventions are most likely the best or worst interventions with respect to their effectiveness and/or safety for a single or multiple outcome(s) and may increase interpretability. Using empirical NMAs, we show that the need for a concise and informative presentation of results is imperative, particularly as the number of competing treatments and outcomes in an NMA increases. The rank-heat plot is an efficient way to present the results of ranking statistics, particularly when a large amount of data is available, and it is targeted to users from various backgrounds. Copyright © 2016 Elsevier Inc. All rights reserved.

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

    Science.gov (United States)

    Chen, Yanguang

    2015-01-01

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

  19. A New Methodology of Spatial Cross-Correlation Analysis

    Science.gov (United States)

    Chen, Yanguang

    2015-01-01

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

  20. A hybrid wavelet de-noising and Rank-Set Pair Analysis approach for forecasting hydro-meteorological time series.

    Science.gov (United States)

    Wang, Dong; Borthwick, Alistair G; He, Handan; Wang, Yuankun; Zhu, Jieyu; Lu, Yuan; Xu, Pengcheng; Zeng, Xiankui; Wu, Jichun; Wang, Lachun; Zou, Xinqing; Liu, Jiufu; Zou, Ying; He, Ruimin

    2018-01-01

    Accurate, fast forecasting of hydro-meteorological time series is presently a major challenge in drought and flood mitigation. This paper proposes a hybrid approach, wavelet de-noising (WD) and Rank-Set Pair Analysis (RSPA), that takes full advantage of a combination of the two approaches to improve forecasts of hydro-meteorological time series. WD allows decomposition and reconstruction of a time series by the wavelet transform, and hence separation of the noise from the original series. RSPA, a more reliable and efficient version of Set Pair Analysis, is integrated with WD to form the hybrid WD-RSPA approach. Two types of hydro-meteorological data sets with different characteristics and different levels of human influences at some representative stations are used to illustrate the WD-RSPA approach. The approach is also compared to three other generic methods: the conventional Auto Regressive Integrated Moving Average (ARIMA) method, Artificial Neural Networks (ANNs) (BP-error Back Propagation, MLP-Multilayer Perceptron and RBF-Radial Basis Function), and RSPA alone. Nine error metrics are used to evaluate the model performance. Compared to three other generic methods, the results generated by WD-REPA model presented invariably smaller error measures which means the forecasting capability of the WD-REPA model is better than other models. The results show that WD-RSPA is accurate, feasible, and effective. In particular, WD-RSPA is found to be the best among the various generic methods compared in this paper, even when the extreme events are included within a time series. Copyright © 2017 Elsevier Inc. All rights reserved.

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

    International Nuclear Information System (INIS)

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

    2010-01-01

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

  2. Correlation analysis of fracture arrangement in space

    Science.gov (United States)

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

    2018-03-01

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

  3. Ranking Queries on Uncertain Data

    CERN Document Server

    Hua, Ming

    2011-01-01

    Uncertain data is inherent in many important applications, such as environmental surveillance, market analysis, and quantitative economics research. Due to the importance of those applications and rapidly increasing amounts of uncertain data collected and accumulated, analyzing large collections of uncertain data has become an important task. Ranking queries (also known as top-k queries) are often natural and useful in analyzing uncertain data. Ranking Queries on Uncertain Data discusses the motivations/applications, challenging problems, the fundamental principles, and the evaluation algorith

  4. Analysis of Baryon Angular Correlations with Pythia

    CERN Document Server

    Mccune, Amara

    2017-01-01

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

  5. Using both principal component analysis and reduced rank regression to study dietary patterns and diabetes in Chinese adults.

    Science.gov (United States)

    Batis, Carolina; Mendez, Michelle A; Gordon-Larsen, Penny; Sotres-Alvarez, Daniela; Adair, Linda; Popkin, Barry

    2016-02-01

    We examined the association between dietary patterns and diabetes using the strengths of two methods: principal component analysis (PCA) to identify the eating patterns of the population and reduced rank regression (RRR) to derive a pattern that explains the variation in glycated Hb (HbA1c), homeostasis model assessment of insulin resistance (HOMA-IR) and fasting glucose. We measured diet over a 3 d period with 24 h recalls and a household food inventory in 2006 and used it to derive PCA and RRR dietary patterns. The outcomes were measured in 2009. Adults (n 4316) from the China Health and Nutrition Survey. The adjusted odds ratio for diabetes prevalence (HbA1c≥6·5 %), comparing the highest dietary pattern score quartile with the lowest, was 1·26 (95 % CI 0·76, 2·08) for a modern high-wheat pattern (PCA; wheat products, fruits, eggs, milk, instant noodles and frozen dumplings), 0·76 (95 % CI 0·49, 1·17) for a traditional southern pattern (PCA; rice, meat, poultry and fish) and 2·37 (95 % CI 1·56, 3·60) for the pattern derived with RRR. By comparing the dietary pattern structures of RRR and PCA, we found that the RRR pattern was also behaviourally meaningful. It combined the deleterious effects of the modern high-wheat pattern (high intakes of wheat buns and breads, deep-fried wheat and soya milk) with the deleterious effects of consuming the opposite of the traditional southern pattern (low intakes of rice, poultry and game, fish and seafood). Our findings suggest that using both PCA and RRR provided useful insights when studying the association of dietary patterns with diabetes.

  6. PageRank and rank-reversal dependence on the damping factor

    Science.gov (United States)

    Son, S.-W.; Christensen, C.; Grassberger, P.; Paczuski, M.

    2012-12-01

    PageRank (PR) is an algorithm originally developed by Google to evaluate the importance of web pages. Considering how deeply rooted Google's PR algorithm is to gathering relevant information or to the success of modern businesses, the question of rank stability and choice of the damping factor (a parameter in the algorithm) is clearly important. We investigate PR as a function of the damping factor d on a network obtained from a domain of the World Wide Web, finding that rank reversal happens frequently over a broad range of PR (and of d). We use three different correlation measures, Pearson, Spearman, and Kendall, to study rank reversal as d changes, and we show that the correlation of PR vectors drops rapidly as d changes from its frequently cited value, d0=0.85. Rank reversal is also observed by measuring the Spearman and Kendall rank correlation, which evaluate relative ranks rather than absolute PR. Rank reversal happens not only in directed networks containing rank sinks but also in a single strongly connected component, which by definition does not contain any sinks. We relate rank reversals to rank pockets and bottlenecks in the directed network structure. For the network studied, the relative rank is more stable by our measures around d=0.65 than at d=d0.

  7. PageRank and rank-reversal dependence on the damping factor.

    Science.gov (United States)

    Son, S-W; Christensen, C; Grassberger, P; Paczuski, M

    2012-12-01

    PageRank (PR) is an algorithm originally developed by Google to evaluate the importance of web pages. Considering how deeply rooted Google's PR algorithm is to gathering relevant information or to the success of modern businesses, the question of rank stability and choice of the damping factor (a parameter in the algorithm) is clearly important. We investigate PR as a function of the damping factor d on a network obtained from a domain of the World Wide Web, finding that rank reversal happens frequently over a broad range of PR (and of d). We use three different correlation measures, Pearson, Spearman, and Kendall, to study rank reversal as d changes, and we show that the correlation of PR vectors drops rapidly as d changes from its frequently cited value, d_{0}=0.85. Rank reversal is also observed by measuring the Spearman and Kendall rank correlation, which evaluate relative ranks rather than absolute PR. Rank reversal happens not only in directed networks containing rank sinks but also in a single strongly connected component, which by definition does not contain any sinks. We relate rank reversals to rank pockets and bottlenecks in the directed network structure. For the network studied, the relative rank is more stable by our measures around d=0.65 than at d=d_{0}.

  8. Generalized reduced rank tests using the singular value decomposition

    NARCIS (Netherlands)

    Kleibergen, F.R.; Paap, R.

    2002-01-01

    We propose a novel statistic to test the rank of a matrix. The rank statistic overcomes deficiencies of existing rank statistics, like: necessity of a Kronecker covariance matrix for the canonical correlation rank statistic of Anderson (1951), sensitivity to the ordering of the variables for the LDU

  9. Generalized Reduced Rank Tests using the Singular Value Decomposition

    NARCIS (Netherlands)

    F.R. Kleibergen (Frank); R. Paap (Richard)

    2003-01-01

    textabstractWe propose a novel statistic to test the rank of a matrix. The rank statistic overcomes deficiencies of existing rank statistics, like: necessity of a Kronecker covariance matrix for the canonical correlation rank statistic of Anderson (1951), sensitivity to the ordering of the variables

  10. Local constructions of gender-based violence amongst IDPs in northern Uganda: analysis of archival data collected using a gender- and age-segmented participatory ranking methodology.

    Science.gov (United States)

    Ager, Alastair; Bancroft, Carolyn; Berger, Elizabeth; Stark, Lindsay

    2018-01-01

    Gender-based violence (GBV) is a significant problem in conflict-affected settings. Understanding local constructions of such violence is crucial to developing preventive and responsive interventions to address this issue. This study reports on a secondary analysis of archived data collected as part of formative qualitative work - using a group participatory ranking methodology (PRM) - informing research on the prevalence of GBV amongst IDPs in northern Uganda in 2006. Sixty-four PRM group discussions were held with women, with men, with girls (aged 14 to 18 years), and with boys (aged 14 to 18 years) selected on a randomized basis across four internally displaced persons (IDP) camps in Lira District. Discussions elicited problems facing women in the camps, and - through structured participatory methods - consensus ranking of their importance and narrative accounts explaining these judgments. Amongst forms of GBV faced by women, rape was ranked as the greatest concern amongst participants (with a mean problem rank of 3.4), followed by marital rape (mean problem rank of 4.5) and intimate partner violence (mean problem rank of 4.9). Girls ranked all forms of GBV as higher priority concerns than other participants. Discussions indicated that these forms of GBV were generally considered normalized within the camp. Gender roles and power, economic deprivation, and physical and social characteristics of the camp setting emerged as key explanatory factors in accounts of GBV prevalence, although these played out in different ways with respect to differing forms of violence. All groups acknowledged GBV to represent a significant threat - among other major concerns such as transportation, water, shelter, food and security - for women residing in the camps. Given evidence of the significantly higher risk in the camp of intimate partner violence and marital rape, the relative prominence of the issue of rape in all rankings suggests normalization of violence within the home

  11. A comparison of hierarchical cluster analysis and league table rankings as methods for analysis and presentation of district health system performance data in Uganda.

    Science.gov (United States)

    Tashobya, Christine K; Dubourg, Dominique; Ssengooba, Freddie; Speybroeck, Niko; Macq, Jean; Criel, Bart

    2016-03-01

    In 2003, the Uganda Ministry of Health introduced the district league table for district health system performance assessment. The league table presents district performance against a number of input, process and output indicators and a composite index to rank districts. This study explores the use of hierarchical cluster analysis for analysing and presenting district health systems performance data and compares this approach with the use of the league table in Uganda. Ministry of Health and district plans and reports, and published documents were used to provide information on the development and utilization of the Uganda district league table. Quantitative data were accessed from the Ministry of Health databases. Statistical analysis using SPSS version 20 and hierarchical cluster analysis, utilizing Wards' method was used. The hierarchical cluster analysis was conducted on the basis of seven clusters determined for each year from 2003 to 2010, ranging from a cluster of good through moderate-to-poor performers. The characteristics and membership of clusters varied from year to year and were determined by the identity and magnitude of performance of the individual variables. Criticisms of the league table include: perceived unfairness, as it did not take into consideration district peculiarities; and being oversummarized and not adequately informative. Clustering organizes the many data points into clusters of similar entities according to an agreed set of indicators and can provide the beginning point for identifying factors behind the observed performance of districts. Although league table ranking emphasize summation and external control, clustering has the potential to encourage a formative, learning approach. More research is required to shed more light on factors behind observed performance of the different clusters. Other countries especially low-income countries that share many similarities with Uganda can learn from these experiences. © The Author 2015

  12. Ranking Operations Management conferences

    NARCIS (Netherlands)

    Steenhuis, H.J.; de Bruijn, E.J.; Gupta, Sushil; Laptaned, U

    2007-01-01

    Several publications have appeared in the field of Operations Management which rank Operations Management related journals. Several ranking systems exist for journals based on , for example, perceived relevance and quality, citation, and author affiliation. Many academics also publish at conferences

  13. CONSRANK: a server for the analysis, comparison and ranking of docking models based on inter-residue contacts

    KAUST Repository

    Chermak, Edrisse; Petta, A.; Serra, L.; Vangone, A.; Scarano, V.; Cavallo, Luigi; Oliva, R.

    2014-01-01

    Summary: Herein, we present CONSRANK, a web tool for analyzing, comparing and ranking protein–protein and protein–nucleic acid docking models, based on the conservation of inter-residue contacts and its visualization in 2D and 3D interactive contact maps.

  14. CONSRANK: a server for the analysis, comparison and ranking of docking models based on inter-residue contacts

    KAUST Repository

    Chermak, Edrisse

    2014-12-21

    Summary: Herein, we present CONSRANK, a web tool for analyzing, comparing and ranking protein–protein and protein–nucleic acid docking models, based on the conservation of inter-residue contacts and its visualization in 2D and 3D interactive contact maps.

  15. Statistical analysis of angular correlation measurements

    International Nuclear Information System (INIS)

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

    1986-01-01

    Obtaining the multipole mixing ratio, δ, of γ transitions in angular correlation measurements is a statistical problem characterized by the small number of angles in which the observation is made and by the limited statistic of counting, α. The inexistence of a sufficient statistics for the estimator of δ, is shown. Three different estimators for δ were constructed and their properties of consistency, bias and efficiency were tested. Tests were also performed in experimental results obtained in γ-γ directional correlation measurements. (Author) [pt

  16. Uncertainty analysis with statistically correlated failure data

    International Nuclear Information System (INIS)

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

    1987-01-01

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

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

    International Nuclear Information System (INIS)

    Jesse, Stephen; Kalinin, Sergei V

    2009-01-01

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

  18. A hybrid correlation analysis with application to imaging genetics

    Science.gov (United States)

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

    2018-03-01

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

  19. University rankings in computer science

    DEFF Research Database (Denmark)

    Ehret, Philip; Zuccala, Alesia Ann; Gipp, Bela

    2017-01-01

    This is a research-in-progress paper concerning two types of institutional rankings, the Leiden and QS World ranking, and their relationship to a list of universities’ ‘geo-based’ impact scores, and Computing Research and Education Conference (CORE) participation scores in the field of computer...... science. A ‘geo-based’ impact measure examines the geographical distribution of incoming citations to a particular university’s journal articles for a specific period of time. It takes into account both the number of citations and the geographical variability in these citations. The CORE participation...... score is calculated on the basis of the number of weighted proceedings papers that a university has contributed to either an A*, A, B, or C conference as ranked by the Computing Research and Education Association of Australasia. In addition to calculating the correlations between the distinct university...

  20. Removing Size as a Determinant of Quality: A Per Capita Approach to Ranking Doctoral Programs in Finance

    Science.gov (United States)

    White, Roger McNeill; White, John Bryan; Barth, Michael M.

    2011-01-01

    Rankings of finance doctoral programs generally fall into two categories: a qualitative opinion survey or a quantitative analysis of research productivity. The consistency of these rankings suggests either the best programs have the most productive faculty, or that the university affiliations most often seen in publications are correlated with…

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

    Science.gov (United States)

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

    2015-01-01

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

  2. Statistically based uncertainty analysis for ranking of component importance in the thermal-hydraulic safety analysis of the Advanced Neutron Source Reactor

    International Nuclear Information System (INIS)

    Wilson, G.E.

    1992-01-01

    The Analytic Hierarchy Process (AHP) has been used to help determine the importance of components and phenomena in thermal-hydraulic safety analyses of nuclear reactors. The AHP results are based, in part on expert opinion. Therefore, it is prudent to evaluate the uncertainty of the AHP ranks of importance. Prior applications have addressed uncertainty with experimental data comparisons and bounding sensitivity calculations. These methods work well when a sufficient experimental data base exists to justify the comparisons. However, in the case of limited or no experimental data the size of the uncertainty is normally made conservatively large. Accordingly, the author has taken another approach, that of performing a statistically based uncertainty analysis. The new work is based on prior evaluations of the importance of components and phenomena in the thermal-hydraulic safety analysis of the Advanced Neutron Source Reactor (ANSR), a new facility now in the design phase. The uncertainty during large break loss of coolant, and decay heat removal scenarios is estimated by assigning a probability distribution function (pdf) to the potential error in the initial expert estimates of pair-wise importance between the components. Using a Monte Carlo sampling technique, the error pdfs are propagated through the AHP software solutions to determine a pdf of uncertainty in the system wide importance of each component. To enhance the generality of the results, study of one other problem having different number of elements is reported, as are the effects of a larger assumed pdf error in the expert ranks. Validation of the Monte Carlo sample size and repeatability are also documented

  3. Sparse structure regularized ranking

    KAUST Repository

    Wang, Jim Jing-Yan

    2014-04-17

    Learning ranking scores is critical for the multimedia database retrieval problem. In this paper, we propose a novel ranking score learning algorithm by exploring the sparse structure and using it to regularize ranking scores. To explore the sparse structure, we assume that each multimedia object could be represented as a sparse linear combination of all other objects, and combination coefficients are regarded as a similarity measure between objects and used to regularize their ranking scores. Moreover, we propose to learn the sparse combination coefficients and the ranking scores simultaneously. A unified objective function is constructed with regard to both the combination coefficients and the ranking scores, and is optimized by an iterative algorithm. Experiments on two multimedia database retrieval data sets demonstrate the significant improvements of the propose algorithm over state-of-the-art ranking score learning algorithms.

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

    Science.gov (United States)

    El Alaoui, Marwane; Benbachir, Saâd

    2013-12-01

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

  5. Thematic mapper studies band correlation analysis

    Science.gov (United States)

    Ungar, S. G.; Kiang, R.

    1976-01-01

    Spectral data representative of thematic mapper candidate bands 1 and 3 to 7 were obtained by selecting appropriate combinations of bands from the JSC 24 channel multispectral scanner. Of all the bands assigned, only candidate bands 4 (.74 mu to .80 mu) and 5 (.80 mu to .91 mu) showed consistently high intercorrelation from region to region and time to time. This extremely high correlation persisted when looking at the composite data set in a multitemporal, multilocation domain. The GISS investigations lend positive confirmation to the hypothesis, that TM bands 4 and 5 are redundant.

  6. Handwriting: Feature Correlation Analysis for Biometric Hashes

    Science.gov (United States)

    Vielhauer, Claus; Steinmetz, Ralf

    2004-12-01

    In the application domain of electronic commerce, biometric authentication can provide one possible solution for the key management problem. Besides server-based approaches, methods of deriving digital keys directly from biometric measures appear to be advantageous. In this paper, we analyze one of our recently published specific algorithms of this category based on behavioral biometrics of handwriting, the biometric hash. Our interest is to investigate to which degree each of the underlying feature parameters contributes to the overall intrapersonal stability and interpersonal value space. We will briefly discuss related work in feature evaluation and introduce a new methodology based on three components: the intrapersonal scatter (deviation), the interpersonal entropy, and the correlation between both measures. Evaluation of the technique is presented based on two data sets of different size. The method presented will allow determination of effects of parameterization of the biometric system, estimation of value space boundaries, and comparison with other feature selection approaches.

  7. 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.

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

    Directory of Open Access Journals (Sweden)

    Jae Kwon Kim

    2017-01-01

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

  9. Construction and Capacity Analysis of High-Rank LoS MIMO Channels in High Speed Railway Scenarios

    Directory of Open Access Journals (Sweden)

    Jingya Yang

    2012-01-01

    Full Text Available The validity of the maximum capacity criterion applied to realize high-rank line-of-sight (LoS multiple-input multiple-output (MIMO channels is investigated for high speed railway scenarios. Performance is evaluated by ergodic capacity. Numerical results demonstrate that by simply adjusting antenna spacing according to the maximum capacity criterion, significant capacity gains are achievable. We find relatively low sensitivity of the system to displacements from the optimal point and angle in relatively short range. Thus, we present two proposals to reconfigure antenna arrays so as to maximize LoS MIMO capacity in the high speed railway scenarios

  10. Extension of Latin hypercube samples with correlated variables

    Energy Technology Data Exchange (ETDEWEB)

    Sallaberry, C.J. [Sandia National Laboratories, Department 6784, MS 0776, Albuquerque, NM 87185-0776 (United States); Helton, J.C. [Department of Mathematics and Statistics, Arizona State University, Tempe, AZ 85287-1804 (United States)], E-mail: jchelto@sandia.gov; Hora, S.C. [University of Hawaii at Hilo, Hilo, HI 96720-4091 (United States)

    2008-07-15

    A procedure for extending the size of a Latin hypercube sample (LHS) with rank correlated variables is described and illustrated. The extension procedure starts with an LHS of size m and associated rank correlation matrix C and constructs a new LHS of size 2m that contains the elements of the original LHS and has a rank correlation matrix that is close to the original rank correlation matrix C. The procedure is intended for use in conjunction with uncertainty and sensitivity analysis of computationally demanding models in which it is important to make efficient use of a necessarily limited number of model evaluations.

  11. Extension of Latin hypercube samples with correlated variables

    International Nuclear Information System (INIS)

    Sallaberry, C.J.; Helton, J.C.; Hora, S.C.

    2008-01-01

    A procedure for extending the size of a Latin hypercube sample (LHS) with rank correlated variables is described and illustrated. The extension procedure starts with an LHS of size m and associated rank correlation matrix C and constructs a new LHS of size 2m that contains the elements of the original LHS and has a rank correlation matrix that is close to the original rank correlation matrix C. The procedure is intended for use in conjunction with uncertainty and sensitivity analysis of computationally demanding models in which it is important to make efficient use of a necessarily limited number of model evaluations

  12. Extension of latin hypercube samples with correlated variables.

    Energy Technology Data Exchange (ETDEWEB)

    Hora, Stephen Curtis (University of Hawaii at Hilo, HI); Helton, Jon Craig (Arizona State University, Tempe, AZ); Sallaberry, Cedric J. PhD. (.; .)

    2006-11-01

    A procedure for extending the size of a Latin hypercube sample (LHS) with rank correlated variables is described and illustrated. The extension procedure starts with an LHS of size m and associated rank correlation matrix C and constructs a new LHS of size 2m that contains the elements of the original LHS and has a rank correlation matrix that is close to the original rank correlation matrix C. The procedure is intended for use in conjunction with uncertainty and sensitivity analysis of computationally demanding models in which it is important to make efficient use of a necessarily limited number of model evaluations.

  13. Validating rankings in soccer championships

    Directory of Open Access Journals (Sweden)

    Annibal Parracho Sant'Anna

    2012-08-01

    Full Text Available The final ranking of a championship is determined by quality attributes combined with other factors which should be filtered out of any decision on relegation or draft for upper level tournaments. Factors like referees' mistakes and difficulty of certain matches due to its accidental importance to the opponents should have their influence reduced. This work tests approaches to combine classification rules considering the imprecision of the number of points as a measure of quality and of the variables that provide reliable explanation for it. Two home-advantage variables are tested and shown to be apt to enter as explanatory variables. Independence between the criteria is checked against the hypothesis of maximal correlation. The importance of factors and of composition rules is evaluated on the basis of correlation between rank vectors, number of classes and number of clubs in tail classes. Data from five years of the Brazilian Soccer Championship are analyzed.

  14. Semiclassical analysis spectral correlations in mesoscopic systems

    International Nuclear Information System (INIS)

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

    1991-07-01

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

  15. Communities in Large Networks: Identification and Ranking

    DEFF Research Database (Denmark)

    Olsen, Martin

    2008-01-01

    We study the problem of identifying and ranking the members of a community in a very large network with link analysis only, given a set of representatives of the community. We define the concept of a community justified by a formal analysis of a simple model of the evolution of a directed graph. ...... and its immediate surroundings. The members are ranked with a “local” variant of the PageRank algorithm. Results are reported from successful experiments on identifying and ranking Danish Computer Science sites and Danish Chess pages using only a few representatives....

  16. Analysis and research of influence factors ranking of fuzzy language translation accuracy in literary works based on catastrophe progression method

    Directory of Open Access Journals (Sweden)

    Wei Dong

    2017-02-01

    Full Text Available This paper researches the problem of decline in translation accuracy caused by language “vagueness” in literary translation, and proposes to use the catastrophe model for importance ranking of various factors affecting the fuzzy language translation accuracy in literary works, and finally gives out the order of factors to be considered before translation. The multi-level evaluation system can be used to construct the relevant catastrophe progression model, and the normalization formula can be used to calculate the relative membership degree of each system and evaluation index, and make evaluation combined with the evaluation criteria table. The results show that, in the fuzzy language translation, in order to improve the translation accuracy, there is a need to consider the indicators ranking: A2 fuzzy language context → A1 words attribute → A3 specific meaning of digital words; B2 fuzzy semantics, B3 blur color words → B1 multiple meanings of words → B4 fuzzy digital words; C3 combination with context and cultural background, C4 specific connotation of color words → C1 combination with words emotion, C2 selection of words meaning → C5 combination with digits and language background.

  17. A special case of reduced rank models for identification and modelling of time varying effects in survival analysis.

    Science.gov (United States)

    Perperoglou, Aris

    2016-12-10

    Flexible survival models are in need when modelling data from long term follow-up studies. In many cases, the assumption of proportionality imposed by a Cox model will not be valid. Instead, a model that can identify time varying effects of fixed covariates can be used. Although there are several approaches that deal with this problem, it is not always straightforward how to choose which covariates should be modelled having time varying effects and which not. At the same time, it is up to the researcher to define appropriate time functions that describe the dynamic pattern of the effects. In this work, we suggest a model that can deal with both fixed and time varying effects and uses simple hypotheses tests to distinguish which covariates do have dynamic effects. The model is an extension of the parsimonious reduced rank model of rank 1. As such, the number of parameters is kept low, and thus, a flexible set of time functions, such as b-splines, can be used. The basic theory is illustrated along with an efficient fitting algorithm. The proposed method is applied to a dataset of breast cancer patients and compared with a multivariate fractional polynomials approach for modelling time-varying effects. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

  18. The application of soft X-ray microscopy to the in-situ analysis of sporopollenin/sporinite in a rank variable suite of organic rich sediments

    Energy Technology Data Exchange (ETDEWEB)

    Cody, G.D.; Botto, R.E. [Argonne National Lab., IL (United States). Chemistry Div.; Ade, H. [North Carolina State Univ., Raleigh, NC (United States). Dept. of Physics; Wirick, S. [State Univ. of New York, Stony Brook, NY (United States). Dept. of Physics

    1997-07-01

    Soft X-ray imaging and carbon near edge absorption fine structure spectroscopy (C-NEXAFS) has been used for the in-situ analysis of sporinite in a rank variable suite of organic rich sediments extending from recent up to high volatile A bituminous coal. The acquisition of chemically based images (contrast based on the 1s - 1{pi}* transition of unsaturated carbon), revealed a homogeneous chemical structure in the spore exine. C-NEXAFS microanalysis indicates chemical structural evolution in sporopollenin/sporinite with increases in maturation. The most significant change in the C-NEXAFS spectrum is an increase in unsaturated carbon, presumably aromatic, with rank. The rate of aromatization in sporinite exceeds that of the surrounding vitrinite. Increases in the concentration of unsaturated carbon are compensated by losses of aliphatic and hydroxylated aliphatic carbon components. Carboxyl groups are present in low and variable concentrations. Absorption due to carboxyl persists in the most mature specimen in this series, a high volatile A rank coal. The reactions which drive sporopollenin chemical structural evolution during diagenesis presumably involve dehydration, Diels-Alder cyclo-addition, and dehydrogenation reactions which ultimately lead to a progressively aromatized bio/geopolymer.

  19. PageRank (II): Mathematics

    African Journals Online (AJOL)

    maths/stats

    ... GAUSS SEIDEL'S. NUMERICAL ALGORITHMS IN PAGE RANK ANALYSIS. ... The convergence is guaranteed, if the absolute value of the largest eigen ... improved Gauss-Seidel iteration algorithm, based on the decomposition. U. L. D. M. +. +. = ..... This corresponds to determine the eigen vector of T with eigen value 1.

  20. A hybrid method of grey relational analysis and data envelopment analysis for evaluating and selecting efficient suppliers plus a novel ranking method for grey numbers

    Directory of Open Access Journals (Sweden)

    Mohsen Sayyah Markabi

    2014-10-01

    Full Text Available Purpose: Evaluation and selection of efficient suppliers is one of the key issues in supply chain management which depends on wide range of qualitative and quantitative criteria. The aim of this research is to develop a mathematical model for evaluating and selecting efficient suppliers when faced with supply and demand uncertainties.Design/methodology/approach: In this research Grey Relational Analysis (GRA and Data Envelopment Analysis (DEA are used to evaluate and select efficient suppliers under uncertainties. Furthermore, a novel ranking method is introduced for the units that their efficiencies are obtained in the form of interval grey numbers.Findings: The study indicates that the proposed model in addition to providing satisfactory and acceptable results avoids time-consuming computations and consequently reduces the solution time. To name another advantage of the proposed model, we can point out that it enables us to make decision based on different levels of risk.Originality/value: The paper presents a mathematical model for evaluating and selecting efficient suppliers in a stochastic environment so that companies can use in order to make better decisions.

  1. Nominal versus Attained Weights in Universitas 21 Ranking

    Science.gov (United States)

    Soh, Kaycheng

    2014-01-01

    Universitas 21 Ranking of National Higher Education Systems (U21 Ranking) is one of the three new ranking systems appearing in 2012. In contrast with the other systems, U21 Ranking uses countries as the unit of analysis. It has several features which lend it with greater trustworthiness, but it also shared some methodological issues with the other…

  2. Two-dimensional multifractal cross-correlation analysis

    International Nuclear Information System (INIS)

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

    2017-01-01

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

  3. An integrated study of spatial multicriteria analysis and mathematical modelling for managed aquifer recharge site suitability mapping and site ranking at Northern Gaza coastal aquifer.

    Science.gov (United States)

    Rahman, Mohammad Azizur; Rusteberg, Bernd; Uddin, Mohammad Salah; Lutz, Annegret; Saada, Muath Abu; Sauter, Martin

    2013-07-30

    This paper describes an integrated approach of site suitability mapping and ranking of the most suitable sites, for the implementation of Managed Aquifer Recharge (MAR) projects, using spatial multicriteria decision analysis (SMCDA) techniques and mathematical modelling. The SMCDA procedure contains constraint mapping, site suitability analysis with criteria standardization and weighting, criteria overlay by analytical hierarchy process (AHP) combined with weighted linear combination (WLC) and ordered weighted averaging (OWA), and sensitivity analysis. The hydrogeological impacts of the selected most suitable sites were quantified by using groundwater flow and transport modelling techniques. Finally, ranking of the selected sites was done with the WLC method. The integrated approach is demonstrated by a case study in the coastal aquifer of North Gaza. Constraint mapping shows that 50% of the total study area is suitable for MAR implementation. About 25% of the total area is "very good" and 25% percent is "good" for MAR, according to the site suitability analysis. Six locations were selected and ranked against six representative decision criteria. Long term (year 2003 to year 2040) groundwater flow and transport simulations were performed to quantify the selected criteria under MAR project operation conditions at the selected sites. Finally, the suitability mapping and hydrogeological investigation recommends that the location of the existing infiltration ponds, constructed near the planned North Gaza Wastewater Treatment Plant (NGWWTP) is most suitable for MAR project implementation. This paper concludes that mathematical modelling should be combined with the SMCDA technique in order to select the best location for MAR project implementation. Besides MAR project implementation, the generalised approach can be applicable for any other water resources development project that deals with site selection and implementation. Copyright © 2013 Elsevier Ltd. All rights

  4. Psychobiological Correlates of Vaginismus: An Exploratory Analysis.

    Science.gov (United States)

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

    2017-11-01

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

  5. On Page Rank

    NARCIS (Netherlands)

    Hoede, C.

    In this paper the concept of page rank for the world wide web is discussed. The possibility of describing the distribution of page rank by an exponential law is considered. It is shown that the concept is essentially equal to that of status score, a centrality measure discussed already in 1953 by

  6. On Rank and Nullity

    Science.gov (United States)

    Dobbs, David E.

    2012-01-01

    This note explains how Emil Artin's proof that row rank equals column rank for a matrix with entries in a field leads naturally to the formula for the nullity of a matrix and also to an algorithm for solving any system of linear equations in any number of variables. This material could be used in any course on matrix theory or linear algebra.

  7. Hitting the Rankings Jackpot

    Science.gov (United States)

    Chapman, David W.

    2008-01-01

    Recently, Samford University was ranked 27th in the nation in a report released by "Forbes" magazine. In this article, the author relates how the people working at Samford University were surprised at its ranking. Although Samford is the largest privately institution in Alabama, its distinguished academic achievements aren't even…

  8. Motif discovery in ranked lists of sequences

    DEFF Research Database (Denmark)

    Nielsen, Morten Muhlig; Tataru, Paula; Madsen, Tobias

    2016-01-01

    Motif analysis has long been an important method to characterize biological functionality and the current growth of sequencing-based genomics experiments further extends its potential. These diverse experiments often generate sequence lists ranked by some functional property. There is therefore...... advantage of the regular expression feature, including enrichments for combinations of different microRNA seed sites. The method is implemented and made publicly available as an R package and supports high parallelization on multi-core machinery....... a growing need for motif analysis methods that can exploit this coupled data structure and be tailored for specific biological questions. Here, we present an exploratory motif analysis tool, Regmex (REGular expression Motif EXplorer), which offers several methods to evaluate the correlation of motifs...

  9. Parameter Optimization for Selected Correlation Analysis of Intracranial Pathophysiology

    Directory of Open Access Journals (Sweden)

    Rupert Faltermeier

    2015-01-01

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

  10. Nonlinear canonical correlation analysis with k sets of variables

    NARCIS (Netherlands)

    van der Burg, Eeke; de Leeuw, Jan

    1987-01-01

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

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

    African Journals Online (AJOL)

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

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

    Science.gov (United States)

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

    2015-01-01

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

  13. A Ranking Approach to Genomic Selection.

    Science.gov (United States)

    Blondel, Mathieu; Onogi, Akio; Iwata, Hiroyoshi; Ueda, Naonori

    2015-01-01

    Genomic selection (GS) is a recent selective breeding method which uses predictive models based on whole-genome molecular markers. Until now, existing studies formulated GS as the problem of modeling an individual's breeding value for a particular trait of interest, i.e., as a regression problem. To assess predictive accuracy of the model, the Pearson correlation between observed and predicted trait values was used. In this paper, we propose to formulate GS as the problem of ranking individuals according to their breeding value. Our proposed framework allows us to employ machine learning methods for ranking which had previously not been considered in the GS literature. To assess ranking accuracy of a model, we introduce a new measure originating from the information retrieval literature called normalized discounted cumulative gain (NDCG). NDCG rewards more strongly models which assign a high rank to individuals with high breeding value. Therefore, NDCG reflects a prerequisite objective in selective breeding: accurate selection of individuals with high breeding value. We conducted a comparison of 10 existing regression methods and 3 new ranking methods on 6 datasets, consisting of 4 plant species and 25 traits. Our experimental results suggest that tree-based ensemble methods including McRank, Random Forests and Gradient Boosting Regression Trees achieve excellent ranking accuracy. RKHS regression and RankSVM also achieve good accuracy when used with an RBF kernel. Traditional regression methods such as Bayesian lasso, wBSR and BayesC were found less suitable for ranking. Pearson correlation was found to correlate poorly with NDCG. Our study suggests two important messages. First, ranking methods are a promising research direction in GS. Second, NDCG can be a useful evaluation measure for GS.

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

    Science.gov (United States)

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

    2012-01-01

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

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

    Science.gov (United States)

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

    2018-03-01

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

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

    African Journals Online (AJOL)

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

  17. Analysis of temporal-longitudinal-latitudinal characteristics in the global ionosphere based on tensor rank-1 decomposition

    Science.gov (United States)

    Lu, Shikun; Zhang, Hao; Li, Xihai; Li, Yihong; Niu, Chao; Yang, Xiaoyun; Liu, Daizhi

    2018-03-01

    Combining analyses of spatial and temporal characteristics of the ionosphere is of great significance for scientific research and engineering applications. Tensor decomposition is performed to explore the temporal-longitudinal-latitudinal characteristics in the ionosphere. Three-dimensional tensors are established based on the time series of ionospheric vertical total electron content maps obtained from the Centre for Orbit Determination in Europe. To obtain large-scale characteristics of the ionosphere, rank-1 decomposition is used to obtain U^{(1)}, U^{(2)}, and U^{(3)}, which are the resulting vectors for the time, longitude, and latitude modes, respectively. Our initial finding is that the correspondence between the frequency spectrum of U^{(1)} and solar variation indicates that rank-1 decomposition primarily describes large-scale temporal variations in the global ionosphere caused by the Sun. Furthermore, the time lags between the maxima of the ionospheric U^{(2)} and solar irradiation range from 1 to 3.7 h without seasonal dependence. The differences in time lags may indicate different interactions between processes in the magnetosphere-ionosphere-thermosphere system. Based on the dataset displayed in the geomagnetic coordinates, the position of the barycenter of U^{(3)} provides evidence for north-south asymmetry (NSA) in the large-scale ionospheric variations. The daily variation in such asymmetry indicates the influences of solar ionization. The diurnal geomagnetic coordinate variations in U^{(3)} show that the large-scale EIA (equatorial ionization anomaly) variations during the day and night have similar characteristics. Considering the influences of geomagnetic disturbance on ionospheric behavior, we select the geomagnetic quiet GIMs to construct the ionospheric tensor. The results indicate that the geomagnetic disturbances have little effect on large-scale ionospheric characteristics.

  18. Multiscale Detrended Cross-Correlation Analysis of STOCK Markets

    Science.gov (United States)

    Yin, Yi; Shang, Pengjian

    2014-06-01

    In this paper, we employ the detrended cross-correlation analysis (DCCA) to investigate the cross-correlations between different stock markets. We report the results of cross-correlated behaviors in US, Chinese and European stock markets in period 1997-2012 by using DCCA method. The DCCA shows the cross-correlated behaviors of intra-regional and inter-regional stock markets in the short and long term which display the similarities and differences of cross-correlated behaviors simply and roughly and the persistence of cross-correlated behaviors of fluctuations. Then, because of the limitation and inapplicability of DCCA method, we propose multiscale detrended cross-correlation analysis (MSDCCA) method to avoid "a priori" selecting the ranges of scales over which two coefficients of the classical DCCA method are identified, and employ MSDCCA to reanalyze these cross-correlations to exhibit some important details such as the existence and position of minimum, maximum and bimodal distribution which are lost if the scale structure is described by two coefficients only and essential differences and similarities in the scale structures of cross-correlation of intra-regional and inter-regional markets. More statistical characteristics of cross-correlation obtained by MSDCCA method help us to understand how two different stock markets influence each other and to analyze the influence from thus two inter-regional markets on the cross-correlation in detail, thus we get a richer and more detailed knowledge of the complex evolutions of dynamics of the cross-correlations between stock markets. The application of MSDCCA is important to promote our understanding of the internal mechanisms and structures of financial markets and helps to forecast the stock indices based on our current results demonstrated the cross-correlations between stock indices. We also discuss the MSDCCA methods of secant rolling window with different sizes and, lastly, provide some relevant implications and

  19. Network meta-analysis of diagnostic test accuracy studies identifies and ranks the optimal diagnostic tests and thresholds for health care policy and decision-making.

    Science.gov (United States)

    Owen, Rhiannon K; Cooper, Nicola J; Quinn, Terence J; Lees, Rosalind; Sutton, Alex J

    2018-07-01

    Network meta-analyses (NMA) have extensively been used to compare the effectiveness of multiple interventions for health care policy and decision-making. However, methods for evaluating the performance of multiple diagnostic tests are less established. In a decision-making context, we are often interested in comparing and ranking the performance of multiple diagnostic tests, at varying levels of test thresholds, in one simultaneous analysis. Motivated by an example of cognitive impairment diagnosis following stroke, we synthesized data from 13 studies assessing the efficiency of two diagnostic tests: Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA), at two test thresholds: MMSE accounting for the correlations between multiple test accuracy measures from the same study. We developed and successfully fitted a model comparing multiple tests/threshold combinations while imposing threshold constraints. Using this model, we found that MoCA at threshold decision making. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

  20. Statistical Optimality in Multipartite Ranking and Ordinal Regression.

    Science.gov (United States)

    Uematsu, Kazuki; Lee, Yoonkyung

    2015-05-01

    Statistical optimality in multipartite ranking is investigated as an extension of bipartite ranking. We consider the optimality of ranking algorithms through minimization of the theoretical risk which combines pairwise ranking errors of ordinal categories with differential ranking costs. The extension shows that for a certain class of convex loss functions including exponential loss, the optimal ranking function can be represented as a ratio of weighted conditional probability of upper categories to lower categories, where the weights are given by the misranking costs. This result also bridges traditional ranking methods such as proportional odds model in statistics with various ranking algorithms in machine learning. Further, the analysis of multipartite ranking with different costs provides a new perspective on non-smooth list-wise ranking measures such as the discounted cumulative gain and preference learning. We illustrate our findings with simulation study and real data analysis.

  1. The role of growth form and correlated traits in competitive ranking of six perennial ruderal plant species grown in unbalanced mixtures

    Science.gov (United States)

    Dietz, Hansjörg; Steinlein, Thomas; Ullmann, Isolde

    1998-02-01

    The competitive abilities of six perennial ruderal plants of three different growth forms were compared via yield measures using an additive diallel experimental design with unbalanced mixtures (9:3 or 3:9 plants per pot, respectively). Thus, in a given mixture species A was grown in two configurations: three individuals in centre position of the pot together with nine plants of species B in border position and vice versa. Effect competitive abilities as well as response competitive abilities of the species were significantly related to canopy height and plant biomass. The species with lower rosette growth form and smaller biomasses were weaker competitors than the species possessing elevated canopies along with higher biomasses, whereas total leaf area was not significantly correlated with competitive ability between species. Species differences in competitive ability were stronger between the plants grown in the central position than between those grown in the border position. Furthermore, interactions between species-specific traits and configuration could be observed, indicating the importance of species proportions and arrangement patterns for evaluation of competitive outcome in the field. The degree of complete transitivity of the competitive network of the six ruderal species, which was significantly higher than expected under the null model in our experimental design, also seemed to depend on species proportions in mixture. Shifts in root:shoot ratio of the centre plants when faced with competition by the border plants were in the direction of higher shoot allocation for the weak competitors with rosette growth form irrespective of the neighbour species, except for Bunias orientalis, which showed a more plastic response. The stronger competitors showed higher root allocation ( Urtica dioica) or were hardly affected at all. Consistent with the results of our experiment, the weaker competitors occur at rather frequently disturbed and therefore transient

  2. 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...

  3. Prevalence and correlates of hypertension in Maharashtra, India: A multilevel analysis.

    Directory of Open Access Journals (Sweden)

    Mahadev D Bhise

    Full Text Available In the last few decades, the prevalence of hypertension has been drastically increased in India. The present study estimates the current prevalence of hypertension and its correlates in the state of Maharashtra. The variation in the prevalence of hypertension associated with individual-level characteristics is explained at the community and district level.Data is used from the recent round of District Level Household & Facility Survey (DLHS-4, 2012-13. The DLHS-4 has used the nationally representative sample, collected through multistage stratified sampling procedure. A similar sampling frame, used in NSSO-2007-08, has been followed. The chi-square test is used to show the significance level of the association between the estimated prevalence of hypertension and its correlates. Multilevel regression analysis is carried out to investigate the effects of individual and community level factors on the prevalence of hypertension.The overall prevalence of hypertension is 25% in Maharashtra, and a huge variation in the prevalence of hypertension is found across the districts. Dhule, Gadchiroli (with a low HDI rank, Mumbai and Satara (with higher HDI rank are the districts with the higher (above 30% prevalence of high blood pressure. The prevalence also significantly varies according to different correlates. The prevalence of high blood pressure is higher among elderly population (40%, among males (28%, in the urban areas (27% and in the richest wealth quintile (28%. The prevalence is also higher among cigarette smokers (31%, alcohol consumers (30% and people with obesity (38% as compared to their counterparts. The results of the multilevel analysis show that the older and obese persons are at four-time higher risk of hypertension. Again, age, sex, marital status, place of residence, wealth status, unhealthy habits (i.e. smoking and alcohol consumption and BMI are significantly associated with hypertension. The results of VPC statistics show that 14% of

  4. How Many Alternatives Can Be Ranked? A Comparison of the Paired Comparison and Ranking Methods.

    Science.gov (United States)

    Ock, Minsu; Yi, Nari; Ahn, Jeonghoon; Jo, Min-Woo

    2016-01-01

    To determine the feasibility of converting ranking data into paired comparison (PC) data and suggest the number of alternatives that can be ranked by comparing a PC and a ranking method. Using a total of 222 health states, a household survey was conducted in a sample of 300 individuals from the general population. Each respondent performed a PC 15 times and a ranking method 6 times (two attempts of ranking three, four, and five health states, respectively). The health states of the PC and the ranking method were constructed to overlap each other. We converted the ranked data into PC data and examined the consistency of the response rate. Applying probit regression, we obtained the predicted probability of each method. Pearson correlation coefficients were determined between the predicted probabilities of those methods. The mean absolute error was also assessed between the observed and the predicted values. The overall consistency of the response rate was 82.8%. The Pearson correlation coefficients were 0.789, 0.852, and 0.893 for ranking three, four, and five health states, respectively. The lowest mean absolute error was 0.082 (95% confidence interval [CI] 0.074-0.090) in ranking five health states, followed by 0.123 (95% CI 0.111-0.135) in ranking four health states and 0.126 (95% CI 0.113-0.138) in ranking three health states. After empirically examining the consistency of the response rate between a PC and a ranking method, we suggest that using five alternatives in the ranking method may be superior to using three or four alternatives. Copyright © 2016 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

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

    Science.gov (United States)

    Zhou, Jinzhi; Tang, Xiaofang

    2015-08-01

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

  6. Recurrent fuzzy ranking methods

    Science.gov (United States)

    Hajjari, Tayebeh

    2012-11-01

    With the increasing development of fuzzy set theory in various scientific fields and the need to compare fuzzy numbers in different areas. Therefore, Ranking of fuzzy numbers plays a very important role in linguistic decision-making, engineering, business and some other fuzzy application systems. Several strategies have been proposed for ranking of fuzzy numbers. Each of these techniques has been shown to produce non-intuitive results in certain case. In this paper, we reviewed some recent ranking methods, which will be useful for the researchers who are interested in this area.

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

    Science.gov (United States)

    Langfelder, Peter; Horvath, Steve

    2008-12-29

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

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

    Science.gov (United States)

    Saatci, Esra

    2018-01-01

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

  9. PageRank as a method to rank biomedical literature by importance.

    Science.gov (United States)

    Yates, Elliot J; Dixon, Louise C

    2015-01-01

    Optimal ranking of literature importance is vital in overcoming article overload. Existing ranking methods are typically based on raw citation counts, giving a sum of 'inbound' links with no consideration of citation importance. PageRank, an algorithm originally developed for ranking webpages at the search engine, Google, could potentially be adapted to bibliometrics to quantify the relative importance weightings of a citation network. This article seeks to validate such an approach on the freely available, PubMed Central open access subset (PMC-OAS) of biomedical literature. On-demand cloud computing infrastructure was used to extract a citation network from over 600,000 full-text PMC-OAS articles. PageRanks and citation counts were calculated for each node in this network. PageRank is highly correlated with citation count (R = 0.905, P PageRank can be trivially computed on commodity cluster hardware and is linearly correlated with citation count. Given its putative benefits in quantifying relative importance, we suggest it may enrich the citation network, thereby overcoming the existing inadequacy of citation counts alone. We thus suggest PageRank as a feasible supplement to, or replacement of, existing bibliometric ranking methods.

  10. Ranking as parameter estimation

    Czech Academy of Sciences Publication Activity Database

    Kárný, Miroslav; Guy, Tatiana Valentine

    2009-01-01

    Roč. 4, č. 2 (2009), s. 142-158 ISSN 1745-7645 R&D Projects: GA MŠk 2C06001; GA AV ČR 1ET100750401; GA MŠk 1M0572 Institutional research plan: CEZ:AV0Z10750506 Keywords : ranking * Bayesian estimation * negotiation * modelling Subject RIV: BB - Applied Statistics, Operational Research http://library.utia.cas.cz/separaty/2009/AS/karny- ranking as parameter estimation.pdf

  11. Hierarchical partial order ranking

    International Nuclear Information System (INIS)

    Carlsen, Lars

    2008-01-01

    Assessing the potential impact on environmental and human health from the production and use of chemicals or from polluted sites involves a multi-criteria evaluation scheme. A priori several parameters are to address, e.g., production tonnage, specific release scenarios, geographical and site-specific factors in addition to various substance dependent parameters. Further socio-economic factors may be taken into consideration. The number of parameters to be included may well appear to be prohibitive for developing a sensible model. The study introduces hierarchical partial order ranking (HPOR) that remedies this problem. By HPOR the original parameters are initially grouped based on their mutual connection and a set of meta-descriptors is derived representing the ranking corresponding to the single groups of descriptors, respectively. A second partial order ranking is carried out based on the meta-descriptors, the final ranking being disclosed though average ranks. An illustrative example on the prioritisation of polluted sites is given. - Hierarchical partial order ranking of polluted sites has been developed for prioritization based on a large number of parameters

  12. Citation graph based ranking in Invenio

    CERN Document Server

    Marian, Ludmila; Rajman, Martin; Vesely, Martin

    2010-01-01

    Invenio is the web-based integrated digital library system developed at CERN. Within this framework, we present four types of ranking models based on the citation graph that complement the simple approach based on citation counts: time-dependent citation counts, a relevancy ranking which extends the PageRank model, a time-dependent ranking which combines the freshness of citations with PageRank and a ranking that takes into consideration the external citations. We present our analysis and results obtained on two main data sets: Inspire and CERN Document Server. Our main contributions are: (i) a study of the currently available ranking methods based on the citation graph; (ii) the development of new ranking methods that correct some of the identified limitations of the current methods such as treating all citations of equal importance, not taking time into account or considering the citation graph complete; (iii) a detailed study of the key parameters for these ranking methods. (The original publication is ava...

  13. Correlation analysis of the Taurus molecular cloud complex

    International Nuclear Information System (INIS)

    Kleiner, S.C.

    1985-01-01

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

  14. Conservation threats and the phylogenetic utility of IUCN Red List rankings in Incilius toads.

    Science.gov (United States)

    Schachat, Sandra R; Mulcahy, Daniel G; Mendelson, Joseph R

    2016-02-01

    Phylogenetic analysis of extinction threat is an emerging tool in the field of conservation. However, there are problems with the methods and data as commonly used. Phylogenetic sampling usually extends to the level of family or genus, but International Union for Conservation of Nature (IUCN) rankings are available only for individual species, and, although different species within a taxonomic group may have the same IUCN rank, the species may have been ranked as such for different reasons. Therefore, IUCN rank may not reflect evolutionary history and thus may not be appropriate for use in a phylogenetic context. To be used appropriately, threat-risk data should reflect the cause of extinction threat rather than the IUCN threat ranking. In a case study of the toad genus Incilius, with phylogenetic sampling at the species level (so that the resolution of the phylogeny matches character data from the IUCN Red List), we analyzed causes of decline and IUCN threat rankings by calculating metrics of phylogenetic signal (such as Fritz and Purvis' D). We also analyzed the extent to which cause of decline and threat ranking overlap by calculating phylogenetic correlation between these 2 types of character data. Incilius species varied greatly in both threat ranking and cause of decline; this variability would be lost at a coarser taxonomic resolution. We found far more phylogenetic signal, likely correlated with evolutionary history, for causes of decline than for IUCN threat ranking. Individual causes of decline and IUCN threat rankings were largely uncorrelated on the phylogeny. Our results demonstrate the importance of character selection and taxonomic resolution when extinction threat is analyzed in a phylogenetic context. © 2015 Society for Conservation Biology.

  15. Clinical prognostic significance and pro-metastatic activity of RANK/RANKL via the AKT pathway in endometrial cancer.

    Science.gov (United States)

    Wang, Jing; Liu, Yao; Wang, Lihua; Sun, Xiao; Wang, Yudong

    2016-02-02

    RANK/RANKL plays a key role in metastasis of certain malignant tumors, which makes it a promising target for developing novel therapeutic strategies for cancer. However, the prognostic value and pro-metastatic activity of RANK in endometrial cancer (EC) remain to be determined. Thus, the present study investigated the effect of RANK on the prognosis of EC patients, as well as the pro-metastatic activity of EC cells. The results indicated that those with high expression of RANK showed decreased overall survival and progression-free survival. Statistical analysis revealed the positive correlations between RANK/RANKL expression and metastasis-related factors. Additionally, RANK/RANKL significantly promoted cell migration/invasion via activating AKT/β-catenin/Snail pathway in vitro. However, RANK/RANKL-induced AKT activation could be suppressed after osteoprotegerin (OPG) treatment. Furthermore, the combination of medroxyprogesterone acetate (MPA) and RANKL could in turn attenuate the effect of RANKL alone. Similarly, MPA could partially inhibit the RANK-induced metastasis in an orthotopic mouse model via suppressing AKT/β-catenin/Snail pathway. Therefore, therapeutic inhibition of MPA in RANK/RANKL-induced metastasis was mediated by AKT/β-catenin/Snail pathway both in vitro and in vivo, suggesting a potential target of RANK for gene-based therapy for EC.

  16. 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...

  17. Analysis of charge-dependent azimuthal correlations with HADES

    Energy Technology Data Exchange (ETDEWEB)

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

    2016-07-01

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

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

    Science.gov (United States)

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

    2017-07-01

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

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

    International Nuclear Information System (INIS)

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

    2013-01-01

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

  20. Multiplex PageRank.

    Science.gov (United States)

    Halu, Arda; Mondragón, Raúl J; Panzarasa, Pietro; Bianconi, Ginestra

    2013-01-01

    Many complex systems can be described as multiplex networks in which the same nodes can interact with one another in different layers, thus forming a set of interacting and co-evolving networks. Examples of such multiplex systems are social networks where people are involved in different types of relationships and interact through various forms of communication media. The ranking of nodes in multiplex networks is one of the most pressing and challenging tasks that research on complex networks is currently facing. When pairs of nodes can be connected through multiple links and in multiple layers, the ranking of nodes should necessarily reflect the importance of nodes in one layer as well as their importance in other interdependent layers. In this paper, we draw on the idea of biased random walks to define the Multiplex PageRank centrality measure in which the effects of the interplay between networks on the centrality of nodes are directly taken into account. In particular, depending on the intensity of the interaction between layers, we define the Additive, Multiplicative, Combined, and Neutral versions of Multiplex PageRank, and show how each version reflects the extent to which the importance of a node in one layer affects the importance the node can gain in another layer. We discuss these measures and apply them to an online multiplex social network. Findings indicate that taking the multiplex nature of the network into account helps uncover the emergence of rankings of nodes that differ from the rankings obtained from one single layer. Results provide support in favor of the salience of multiplex centrality measures, like Multiplex PageRank, for assessing the prominence of nodes embedded in multiple interacting networks, and for shedding a new light on structural properties that would otherwise remain undetected if each of the interacting networks were analyzed in isolation.

  1. Multiplex PageRank.

    Directory of Open Access Journals (Sweden)

    Arda Halu

    Full Text Available Many complex systems can be described as multiplex networks in which the same nodes can interact with one another in different layers, thus forming a set of interacting and co-evolving networks. Examples of such multiplex systems are social networks where people are involved in different types of relationships and interact through various forms of communication media. The ranking of nodes in multiplex networks is one of the most pressing and challenging tasks that research on complex networks is currently facing. When pairs of nodes can be connected through multiple links and in multiple layers, the ranking of nodes should necessarily reflect the importance of nodes in one layer as well as their importance in other interdependent layers. In this paper, we draw on the idea of biased random walks to define the Multiplex PageRank centrality measure in which the effects of the interplay between networks on the centrality of nodes are directly taken into account. In particular, depending on the intensity of the interaction between layers, we define the Additive, Multiplicative, Combined, and Neutral versions of Multiplex PageRank, and show how each version reflects the extent to which the importance of a node in one layer affects the importance the node can gain in another layer. We discuss these measures and apply them to an online multiplex social network. Findings indicate that taking the multiplex nature of the network into account helps uncover the emergence of rankings of nodes that differ from the rankings obtained from one single layer. Results provide support in favor of the salience of multiplex centrality measures, like Multiplex PageRank, for assessing the prominence of nodes embedded in multiple interacting networks, and for shedding a new light on structural properties that would otherwise remain undetected if each of the interacting networks were analyzed in isolation.

  2. Application of rank annihilation factor analysis to the spectrophotometric determination of the formation constant of complex of a new synthesized tripodal ligand with Co2+

    Directory of Open Access Journals (Sweden)

    Reza Golbedaghi

    2017-05-01

    Full Text Available The complex formation between a new synthesized tripodal ligand (L22py and the cation Co2+ in water was studied spectrophotometrically using rank annihilation factor analysis (RAFA. According to molar ratio data the stoichiometry of complexation between the ligand and the cation Co2+ was 1:1. Formation constant of this complex was derived using RAFA on spectrophotometric data. In this process the contribution of ligand is removed from the absorbance data matrix when the complex stability constant acts as an optimizing object and simply combined with the pure spectrum of ligand, the rank of original data matrix can be reduced by one by annihilating the information of the ligand from the original data matrix. The effect of ethanol, dimethylformamide (DMF and acetonitrile (AN was investigated on the formation constant of the Co2+ complex. Complex formation constant in water was estimated as log Kf = 5.09 ± 0.02. In mixtures of solvents of water and DMF and water and AN, the formation constant of the complex was increased because of lowering donor number of the solvent and in mixture of water and ethanol, the complex formation constant was decreased because of lowering of dielectric constant of the solvent.

  3. Ranking scientific publications: the effect of nonlinearity

    Science.gov (United States)

    Yao, Liyang; Wei, Tian; Zeng, An; Fan, Ying; di, Zengru

    2014-10-01

    Ranking the significance of scientific publications is a long-standing challenge. The network-based analysis is a natural and common approach for evaluating the scientific credit of papers. Although the number of citations has been widely used as a metric to rank papers, recently some iterative processes such as the well-known PageRank algorithm have been applied to the citation networks to address this problem. In this paper, we introduce nonlinearity to the PageRank algorithm when aggregating resources from different nodes to further enhance the effect of important papers. The validation of our method is performed on the data of American Physical Society (APS) journals. The results indicate that the nonlinearity improves the performance of the PageRank algorithm in terms of ranking effectiveness, as well as robustness against malicious manipulations. Although the nonlinearity analysis is based on the PageRank algorithm, it can be easily extended to other iterative ranking algorithms and similar improvements are expected.

  4. Ranking scientific publications: the effect of nonlinearity.

    Science.gov (United States)

    Yao, Liyang; Wei, Tian; Zeng, An; Fan, Ying; Di, Zengru

    2014-10-17

    Ranking the significance of scientific publications is a long-standing challenge. The network-based analysis is a natural and common approach for evaluating the scientific credit of papers. Although the number of citations has been widely used as a metric to rank papers, recently some iterative processes such as the well-known PageRank algorithm have been applied to the citation networks to address this problem. In this paper, we introduce nonlinearity to the PageRank algorithm when aggregating resources from different nodes to further enhance the effect of important papers. The validation of our method is performed on the data of American Physical Society (APS) journals. The results indicate that the nonlinearity improves the performance of the PageRank algorithm in terms of ranking effectiveness, as well as robustness against malicious manipulations. Although the nonlinearity analysis is based on the PageRank algorithm, it can be easily extended to other iterative ranking algorithms and similar improvements are expected.

  5. Groundwater contaminant plume ranking

    International Nuclear Information System (INIS)

    1988-08-01

    Containment plumes at Uranium Mill Tailings Remedial Action (UMTRA) Project sites were ranked to assist in Subpart B (i.e., restoration requirements of 40 CFR Part 192) compliance strategies for each site, to prioritize aquifer restoration, and to budget future requests and allocations. The rankings roughly estimate hazards to the environment and human health, and thus assist in determining for which sites cleanup, if appropriate, will provide the greatest benefits for funds available. The rankings are based on the scores that were obtained using the US Department of Energy's (DOE) Modified Hazard Ranking System (MHRS). The MHRS and HRS consider and score three hazard modes for a site: migration, fire and explosion, and direct contact. The migration hazard mode score reflects the potential for harm to humans or the environment from migration of a hazardous substance off a site by groundwater, surface water, and air; it is a composite of separate scores for each of these routes. For ranking the containment plumes at UMTRA Project sites, it was assumed that each site had been remediated in compliance with the EPA standards and that relict contaminant plumes were present. Therefore, only the groundwater route was scored, and the surface water and air routes were not considered. Section 2.0 of this document describes the assumptions and procedures used to score the groundwater route, and Section 3.0 provides the resulting scores for each site. 40 tabs

  6. Relationship Between the Brazilian Soccer Confederation Rankings and the Economical-Financial Indicators of Soccer Teams

    Directory of Open Access Journals (Sweden)

    Cleston Alexandre dos Santos

    2017-02-01

    Full Text Available Brazilian soccer teams are required to present good results inside and outside the field. The main demand is about winning titles, to present continuous and increasing profits, and, consequently, to reach economic-financial stability. The present study aims at analyzing the relationship between the ranking formed by the Brazilian Soccer Confederation (CBF and the economic-financial indicators of the Brazilian soccer teams. The sample consisted of 36 Brazilian soccer teams that belong to the series A, B and C. Such teams are linked to CBF and published their financial statements of 2014. For data analysis, we used multi-criteria decision making method VIKOR that was applied along with Kendall rank correlation. Results revealed that the majority of Brazilian soccer teams have insufficient economical liquidity; they cannot bear their own expenses; they dependent of third-party resources; and they present negative profitability. Results also showed, through VIKOR technique, that the soccer teams studied occupy different positions in CBF ranking and in the economical-financial indicators, except for Botafogo club. Kendall rank correlation revealed no correlation and no significance between the rankings. Findings seem to support the idea that there is no relationship between CBF rankings and the economical-financial indicators of Brazilian soccer teams.

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

    International Nuclear Information System (INIS)

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

    1978-01-01

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

  8. Dynamic Matrix Rank

    DEFF Research Database (Denmark)

    Frandsen, Gudmund Skovbjerg; Frandsen, Peter Frands

    2009-01-01

    We consider maintaining information about the rank of a matrix under changes of the entries. For n×n matrices, we show an upper bound of O(n1.575) arithmetic operations and a lower bound of Ω(n) arithmetic operations per element change. The upper bound is valid when changing up to O(n0.575) entries...... in a single column of the matrix. We also give an algorithm that maintains the rank using O(n2) arithmetic operations per rank one update. These bounds appear to be the first nontrivial bounds for the problem. The upper bounds are valid for arbitrary fields, whereas the lower bound is valid for algebraically...... closed fields. The upper bound for element updates uses fast rectangular matrix multiplication, and the lower bound involves further development of an earlier technique for proving lower bounds for dynamic computation of rational functions....

  9. Comparing classical and quantum PageRanks

    Science.gov (United States)

    Loke, T.; Tang, J. W.; Rodriguez, J.; Small, M.; Wang, J. B.

    2017-01-01

    Following recent developments in quantum PageRanking, we present a comparative analysis of discrete-time and continuous-time quantum-walk-based PageRank algorithms. Relative to classical PageRank and to different extents, the quantum measures better highlight secondary hubs and resolve ranking degeneracy among peripheral nodes for all networks we studied in this paper. For the discrete-time case, we investigated the periodic nature of the walker's probability distribution for a wide range of networks and found that the dominant period does not grow with the size of these networks. Based on this observation, we introduce a new quantum measure using the maximum probabilities of the associated walker during the first couple of periods. This is particularly important, since it leads to a quantum PageRanking scheme that is scalable with respect to network size.

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

    OpenAIRE

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

    2016-01-01

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

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

    African Journals Online (AJOL)

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

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

    African Journals Online (AJOL)

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

  13. Use of fuel failure correlations in accident analysis

    International Nuclear Information System (INIS)

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

    1975-05-01

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

  14. Model-independent analysis with BPM correlation matrices

    International Nuclear Information System (INIS)

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

    1998-06-01

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

  15. Ranking Adverse Drug Reactions With Crowdsourcing

    KAUST Repository

    Gottlieb, Assaf

    2015-03-23

    Background: There is no publicly available resource that provides the relative severity of adverse drug reactions (ADRs). Such a resource would be useful for several applications, including assessment of the risks and benefits of drugs and improvement of patient-centered care. It could also be used to triage predictions of drug adverse events. Objective: The intent of the study was to rank ADRs according to severity. Methods: We used Internet-based crowdsourcing to rank ADRs according to severity. We assigned 126,512 pairwise comparisons of ADRs to 2589 Amazon Mechanical Turk workers and used these comparisons to rank order 2929 ADRs. Results: There is good correlation (rho=.53) between the mortality rates associated with ADRs and their rank. Our ranking highlights severe drug-ADR predictions, such as cardiovascular ADRs for raloxifene and celecoxib. It also triages genes associated with severe ADRs such as epidermal growth-factor receptor (EGFR), associated with glioblastoma multiforme, and SCN1A, associated with epilepsy. Conclusions: ADR ranking lays a first stepping stone in personalized drug risk assessment. Ranking of ADRs using crowdsourcing may have useful clinical and financial implications, and should be further investigated in the context of health care decision making.

  16. Ranking adverse drug reactions with crowdsourcing.

    Science.gov (United States)

    Gottlieb, Assaf; Hoehndorf, Robert; Dumontier, Michel; Altman, Russ B

    2015-03-23

    There is no publicly available resource that provides the relative severity of adverse drug reactions (ADRs). Such a resource would be useful for several applications, including assessment of the risks and benefits of drugs and improvement of patient-centered care. It could also be used to triage predictions of drug adverse events. The intent of the study was to rank ADRs according to severity. We used Internet-based crowdsourcing to rank ADRs according to severity. We assigned 126,512 pairwise comparisons of ADRs to 2589 Amazon Mechanical Turk workers and used these comparisons to rank order 2929 ADRs. There is good correlation (rho=.53) between the mortality rates associated with ADRs and their rank. Our ranking highlights severe drug-ADR predictions, such as cardiovascular ADRs for raloxifene and celecoxib. It also triages genes associated with severe ADRs such as epidermal growth-factor receptor (EGFR), associated with glioblastoma multiforme, and SCN1A, associated with epilepsy. ADR ranking lays a first stepping stone in personalized drug risk assessment. Ranking of ADRs using crowdsourcing may have useful clinical and financial implications, and should be further investigated in the context of health care decision making.

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

    International Nuclear Information System (INIS)

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

    2009-01-01

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

  18. Investigation of formation constant of complex of a new synthesized tripodal ligand with Cu2+ using rank annihilation factor analysis in surfactant media

    Directory of Open Access Journals (Sweden)

    R. Golbedaghi

    2014-01-01

    Full Text Available The complex formation between a newly synthesized tripodal ligand and the cation Cu2+ in water and surfactant media was studied spectrophotometrically using rank annihilation factor analysis (RAFA. According to molar ratio data the stoichiometry of complexation between the ligand and the cation Cu2+ was 1:1. Formation constant of this complex was derived using RAFA on spectrophotometric data. The performance of the method has been evaluated by using synthetic data. Also concentration and spectral profiles of ligand and complex can be obtained by using the stability constant and appropriate equations. The effect of surfactants such as sodium dodecyl sulfate (SDS, cetyltrimethylammonium bromide (CTAB and Triton X-100 on complex formation constant of Cu2+ with the ligand was investigated.

  19. PageRank versatility analysis of multilayer modality-based network for exploring the evolution of oil-water slug flow.

    Science.gov (United States)

    Gao, Zhong-Ke; Dang, Wei-Dong; Li, Shan; Yang, Yu-Xuan; Wang, Hong-Tao; Sheng, Jing-Ran; Wang, Xiao-Fan

    2017-07-14

    Numerous irregular flow structures exist in the complicated multiphase flow and result in lots of disparate spatial dynamical flow behaviors. The vertical oil-water slug flow continually attracts plenty of research interests on account of its significant importance. Based on the spatial transient flow information acquired through our designed double-layer distributed-sector conductance sensor, we construct multilayer modality-based network to encode the intricate spatial flow behavior. Particularly, we calculate the PageRank versatility and multilayer weighted clustering coefficient to quantitatively explore the inferred multilayer modality-based networks. Our analysis allows characterizing the complicated evolution of oil-water slug flow, from the opening formation of oil slugs, to the succedent inter-collision and coalescence among oil slugs, and then to the dispersed oil bubbles. These properties render our developed method particularly powerful for mining the essential flow features from the multilayer sensor measurements.

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

    Science.gov (United States)

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

    2017-12-01

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

  1. Diversifying customer review rankings.

    Science.gov (United States)

    Krestel, Ralf; Dokoohaki, Nima

    2015-06-01

    E-commerce Web sites owe much of their popularity to consumer reviews accompanying product descriptions. On-line customers spend hours and hours going through heaps of textual reviews to decide which products to buy. At the same time, each popular product has thousands of user-generated reviews, making it impossible for a buyer to read everything. Current approaches to display reviews to users or recommend an individual review for a product are based on the recency or helpfulness of each review. In this paper, we present a framework to rank product reviews by optimizing the coverage of the ranking with respect to sentiment or aspects, or by summarizing all reviews with the top-K reviews in the ranking. To accomplish this, we make use of the assigned star rating for a product as an indicator for a review's sentiment polarity and compare bag-of-words (language model) with topic models (latent Dirichlet allocation) as a mean to represent aspects. Our evaluation on manually annotated review data from a commercial review Web site demonstrates the effectiveness of our approach, outperforming plain recency ranking by 30% and obtaining best results by combining language and topic model representations. Copyright © 2015 Elsevier Ltd. All rights reserved.

  2. College Rankings. ERIC Digest.

    Science.gov (United States)

    Holub, Tamara

    The popularity of college ranking surveys published by "U.S. News and World Report" and other magazines is indisputable, but the methodologies used to measure the quality of higher education institutions have come under fire by scholars and college officials. Criticisms have focused on methodological flaws, such as failure to consider…

  3. OutRank

    DEFF Research Database (Denmark)

    Müller, Emmanuel; Assent, Ira; Steinhausen, Uwe

    2008-01-01

    Outlier detection is an important data mining task for consistency checks, fraud detection, etc. Binary decision making on whether or not an object is an outlier is not appropriate in many applications and moreover hard to parametrize. Thus, recently, methods for outlier ranking have been proposed...

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

    Science.gov (United States)

    Chu, Delin; Liao, Li-Zhi; Ng, Michael K; Zhang, Xiaowei

    2013-12-01

    In this paper, we study canonical correlation analysis (CCA), which is a powerful tool in multivariate data analysis for finding the correlation between two sets of multidimensional variables. The main contributions of the paper are: 1) to reveal the equivalent relationship between a recursive formula and a trace formula for the multiple CCA problem, 2) to obtain the explicit characterization for all solutions of the multiple CCA problem even when the corresponding covariance matrices are singular, 3) to develop a new sparse CCA algorithm, and 4) to establish the equivalent relationship between the uncorrelated linear discriminant analysis and the CCA problem. We test several simulated and real-world datasets in gene classification and cross-language document retrieval to demonstrate the effectiveness of the proposed algorithm. The performance of the proposed method is competitive with the state-of-the-art sparse CCA algorithms.

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

    Science.gov (United States)

    Rajivan, Prashanth; Cooke, Nancy J

    2018-03-01

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

  6. 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.

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

    DEFF Research Database (Denmark)

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

    2002-01-01

    This paper deals with decompositioning of multiset data. Friedman's alternating conditional expectations (ACE) algorithm is extended to handle multiple sets of variables of different mixtures. The new algorithm finds estimates of the optimal transformations of the involved variables that maximize...... the sum of the pair-wise correlations over all sets. The new algorithm is termed multi-set ACE (MACE) and can find multiple orthogonal eigensolutions. MACE is a generalization of the linear multiset correlations analysis (MCCA). It handles multivariate multisets of arbitrary mixtures of both continuous...

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

    Science.gov (United States)

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

    2015-08-01

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

  9. Augmenting the Deliberative Method for Ranking Risks.

    Science.gov (United States)

    Susel, Irving; Lasley, Trace; Montezemolo, Mark; Piper, Joel

    2016-01-01

    The Department of Homeland Security (DHS) characterized and prioritized the physical cross-border threats and hazards to the nation stemming from terrorism, market-driven illicit flows of people and goods (illegal immigration, narcotics, funds, counterfeits, and weaponry), and other nonmarket concerns (movement of diseases, pests, and invasive species). These threats and hazards pose a wide diversity of consequences with very different combinations of magnitudes and likelihoods, making it very challenging to prioritize them. This article presents the approach that was used at DHS to arrive at a consensus regarding the threats and hazards that stand out from the rest based on the overall risk they pose. Due to time constraints for the decision analysis, it was not feasible to apply multiattribute methodologies like multiattribute utility theory or the analytic hierarchy process. Using a holistic approach was considered, such as the deliberative method for ranking risks first published in this journal. However, an ordinal ranking alone does not indicate relative or absolute magnitude differences among the risks. Therefore, the use of the deliberative method for ranking risks is not sufficient for deciding whether there is a material difference between the top-ranked and bottom-ranked risks, let alone deciding what the stand-out risks are. To address this limitation of ordinal rankings, the deliberative method for ranking risks was augmented by adding an additional step to transform the ordinal ranking into a ratio scale ranking. This additional step enabled the selection of stand-out risks to help prioritize further analysis. © 2015 Society for Risk Analysis.

  10. Analysis and Ranking of Protein-Protein Docking Models Using Inter-Residue Contacts and Inter-Molecular Contact Maps

    KAUST Repository

    Oliva, Romina; Chermak, Edrisse; Cavallo, Luigi

    2015-01-01

    In view of the increasing interest both in inhibitors of protein-protein interactions and in protein drugs themselves, analysis of the three-dimensional structure of protein-protein complexes is assuming greater relevance in drug design. In the many cases where an experimental structure is not available, protein-protein docking becomes the method of choice for predicting the arrangement of the complex. However, reliably scoring protein-protein docking poses is still an unsolved problem. As a consequence, the screening of many docking models is usually required in the analysis step, to possibly single out the correct ones. Here, making use of exemplary cases, we review our recently introduced methods for the analysis of protein complex structures and for the scoring of protein docking poses, based on the use of inter-residue contacts and their visualization in inter-molecular contact maps. We also show that the ensemble of tools we developed can be used in the context of rational drug design targeting protein-protein interactions.

  11. A comparison of partial order technique with three methods of multi-criteria analysis for ranking of chemical substances.

    Science.gov (United States)

    Lerche, Dorte; Brüggemann, Rainer; Sørensen, Peter; Carlsen, Lars; Nielsen, Ole John

    2002-01-01

    An alternative to the often cumbersome and time-consuming risk assessments of chemical substances could be more reliable and advanced priority setting methods. An elaboration of the simple scoring methods is provided by Hasse Diagram Technique (HDT) and/or Multi-Criteria Analysis (MCA). The present study provides an in depth evaluation of HDT relative to three MCA techniques. The new and main methodological step in the comparison is the use of probability concepts based on mathematical tools such as linear extensions of partially ordered sets and Monte Carlo simulations. A data set consisting of 12 High Production Volume Chemicals (HPVCs) is used for illustration. It is a paradigm in this investigation to claim that the need of external input (often subjective weightings of criteria) should be minimized and that the transparency should be maximized in any multicriteria prioritisation. The study illustrates that the Hasse diagram technique (HDT) needs least external input, is most transparent and is least subjective. However, HDT has some weaknesses if there are criteria which exclude each other. Then weighting is needed. Multi-Criteria Analysis (i.e. Utility Function approach, PROMETHEE and concordance analysis) can deal with such mutual exclusions because their formalisms to quantify preferences allow participation e.g. weighting of criteria. Consequently MCA include more subjectivity and loose transparency. The recommendation which arises from this study is that the first step in decision making is to run HDT and as the second step possibly is to run one of the MCA algorithms.

  12. Analysis and Ranking of Protein-Protein Docking Models Using Inter-Residue Contacts and Inter-Molecular Contact Maps

    KAUST Repository

    Oliva, Romina

    2015-07-01

    In view of the increasing interest both in inhibitors of protein-protein interactions and in protein drugs themselves, analysis of the three-dimensional structure of protein-protein complexes is assuming greater relevance in drug design. In the many cases where an experimental structure is not available, protein-protein docking becomes the method of choice for predicting the arrangement of the complex. However, reliably scoring protein-protein docking poses is still an unsolved problem. As a consequence, the screening of many docking models is usually required in the analysis step, to possibly single out the correct ones. Here, making use of exemplary cases, we review our recently introduced methods for the analysis of protein complex structures and for the scoring of protein docking poses, based on the use of inter-residue contacts and their visualization in inter-molecular contact maps. We also show that the ensemble of tools we developed can be used in the context of rational drug design targeting protein-protein interactions.

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

    International Nuclear Information System (INIS)

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

    1974-01-01

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

  14. Characterizing Microseismicity at the Newberry Volcano Geothermal Site using PageRank

    Science.gov (United States)

    Aguiar, A. C.; Myers, S. C.

    2015-12-01

    The Newberry Volcano, within the Deschutes National Forest in Oregon, has been designated as a candidate site for the Department of Energy's Frontier Observatory for Research in Geothermal Energy (FORGE) program. This site was stimulated using high-pressure fluid injection during the fall of 2012, which generated several hundred microseismic events. Exploring the spatial and temporal development of microseismicity is key to understanding how subsurface stimulation modifies stress, fractures rock, and increases permeability. We analyze Newberry seismicity using both surface and borehole seismometers from the AltaRock and LLNL seismic networks. For our analysis we adapt PageRank, Google's initial search algorithm, to evaluate microseismicity during the 2012 stimulation. PageRank is a measure of connectivity, where higher ranking represents highly connected windows. In seismic applications connectivity is measured by the cross correlation of 2 time windows recorded on a common seismic station and channel. Aguiar and Beroza (2014) used PageRank based on cross correlation to detect low-frequency earthquakes, which are highly repetitive but difficult to detect. We expand on this application by using PageRank to define signal-correlation topology for micro-earthquakes, including the identification of signals that are connected to the largest number of other signals. We then use this information to create signal families and compare PageRank families to the spatial and temporal proximity of associated earthquakes. Studying signal PageRank will potentially allow us to efficiently group earthquakes with similar physical characteristics, such as focal mechanisms and stress drop. Our ultimate goal is to determine whether changes in the state of stress and/or changes in the generation of subsurface fracture networks can be detected using PageRank topology. This work performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under

  15. Improving Ranking Using Quantum Probability

    OpenAIRE

    Melucci, Massimo

    2011-01-01

    The paper shows that ranking information units by quantum probability differs from ranking them by classical probability provided the same data used for parameter estimation. As probability of detection (also known as recall or power) and probability of false alarm (also known as fallout or size) measure the quality of ranking, we point out and show that ranking by quantum probability yields higher probability of detection than ranking by classical probability provided a given probability of ...

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

    Science.gov (United States)

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

    2012-03-01

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

  17. Relationships between nurse- and physician-to-population ratios and state health rankings.

    Science.gov (United States)

    Bigbee, Jeri L

    2008-01-01

    To evaluate the relationship between nurse-to-population ratios and population health, as indicated by state health ranking, and to compare the findings with physician-to-population ratios. Secondary analysis correlational design. The sample consisted of all 50 states in the United States. Data sources included the United Health Foundation's 2006 state health rankings, the 2004 National Sample Survey for Registered Nurses, and the U.S. Health Workforce Profile from the New York Center for Health Workforce Studies. Significant relationships between nurse-to-population ratio and overall state health ranking (rho=-.446, p tf?>=.001) and 11 of the 18 components of that ranking were found. Significant components included motor vehicle death rate, high school graduation rate, violent crime rate, infectious disease rate, percentage of children in poverty, percentage of uninsured residents, immunization rate, adequacy of prenatal care, number of poor mental health days, number of poor physical health days, and premature death rate, with higher nurse-to-population ratios associated with higher health rankings. Specialty (public health and school) nurse-to-population ratios were not as strongly related to state health ranking. Physician-to-population ratios were also significantly related to state health ranking, but were associated with different components than nurses. These findings suggest that greater nurses per capita may be uniquely associated with healthier communities; however, further multivariate research is needed.

  18. Windowed Multitaper Correlation Analysis of Multimodal Brain Monitoring Parameters

    Directory of Open Access Journals (Sweden)

    Rupert Faltermeier

    2015-01-01

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

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

    Science.gov (United States)

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

    2015-01-01

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

  20. Message Correlation Analysis Tool for NOvA

    CERN Multimedia

    CERN. Geneva

    2012-01-01

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

  1. Message Correlation Analysis Tool for NOvA

    International Nuclear Information System (INIS)

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

    2012-01-01

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

  2. Message correlation analysis tool for NOvA

    Energy Technology Data Exchange (ETDEWEB)

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

    2012-01-01

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

  3. Using Spatial Multi-Criteria Analysis and Ranking Tool (SMART in earthquake risk assessment: a case study of Delhi region, India

    Directory of Open Access Journals (Sweden)

    Nishant Sinha

    2016-03-01

    Full Text Available This article is aimed at earthquake hazard, vulnerability and risk assessment as a case study to demonstrate the applicability of Spatial Multi-Criteria Analysis and Ranking Tool (SMART, which is based on Saaty's multi-criteria decision analysis (MCDA technique. The three specific study sites of Delhi were chosen for research as it corresponds to a typical patch of the urban environs, completely engrossed with residential, commercial and industrial units. The earthquake hazard affecting components are established in the form of geographic information system data-set layers including seismic zone, peak ground acceleration (PGA, soil characteristics, liquefaction potential, geological characteristics, land use, proximity to fault and epicentre. The physical vulnerability layers comprising building information, namely number of stories, year-built range, area, occupancy and construction type, derived from remote sensing imagery, were only considered for the current research. SMART was developed for earthquake risk assessment, and weights were derived both at component and its element level. Based on weighted overlay techniques, the earthquake hazard and vulnerability layers were created from which the risk maps were derived through multiplicative analysis. The developed risk maps may prove useful in decision-making process and formulating risk mitigation measures.

  4. Experienced stigma and its impacts in psychosis: The role of social rank and external shame.

    Science.gov (United States)

    Wood, Lisa; Irons, Chris

    2017-09-01

    Experienced stigma is detrimental to those who experience psychosis and can cause emotional distress and hinder recovery. This study aimed to explore the relationship between experienced stigma with emotional distress and recovery in people with psychosis. It explored the role of external shame and social rank as mediators in these relationships. A cross-sectional design was implemented. Fifty-two service users were administered a battery of questionnaires examining experienced stigma, external shame, social rank, personal recovery, positive symptoms, depression, and anxiety. Correlation and multiple regression analysis were conducted on the data. Where appropriate, mediation analysis was employed to explore social rank and external shame as mediatory variables. Experienced stigma was significantly related to shame (social rank and external shame), positive symptoms, emotional distress (depression and anxiety), and personal recovery. The impact of experienced stigma on depression was mediated by external shame. Social rank was a mediator between experienced stigma and personal recovery only. People with psychosis who have experienced stigma are likely to experience emotional distress and be inhibited in their recovery. This was found to be partly mediated by external shame and low social rank. Clinical approaches to stigma need to target these as potential maintenance factors. Experienced stigma is significantly related to shame (social rank and external shame) emotional distress, and reduced personal recovery. External shame mediated the relationship between experienced stigma and depression in psychosis. Social rank mediated the relationship between experienced stigma and personal recovery. Clinical approaches to stigma should include the assessment of external shame and low social rank. © 2017 The British Psychological Society.

  5. Analysis of Cell Phone Usage Using Correlation Techniques

    OpenAIRE

    T S R MURTHY; D. SIVA RAMA KRISHNA

    2011-01-01

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

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

    International Nuclear Information System (INIS)

    Costa, Valter Magalhaes

    2011-01-01

    was trained and the results were satisfactory since the IEA-R1 Data Acquisition System reactor monitors 64 variables and, with a set of 9 input variables resulting from the correlation analysis, it was possible to monitor 51 variables using neural networks. (author)

  7. 1991 Acceptance priority ranking

    International Nuclear Information System (INIS)

    1991-12-01

    The Standard Contract for Disposal of Spent Nuclear Fuel and/or High- Level Radioactive Waste (10 CFR Part 961) that the Department of Energy (DOE) has executed with the owners and generators of civilian spent nuclear fuel requires annual publication of the Acceptance Priority Ranking (APR). The 1991 APR details the order in which DOE will allocate Federal waste acceptance capacity. As required by the Standard Contract, the ranking is based on the age of permanently discharged spent nuclear fuel (SNF), with the owners of the oldest SNF, on an industry-wide basis, given the highest priority. the 1991 APR will be the basis for the annual allocation of waste acceptance capacity to the Purchasers in the 1991 Annual Capacity Report (ACR), to be issued later this year. This document is based on SNF discharges as of December 31, 1990, and reflects Purchaser comments and corrections, as appropriate, to the draft APR issued on May 15, 1991

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

    Science.gov (United States)

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

    2016-11-14

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

  9. Peak career in world-ranked swimmers: Age’s analysis of 2008 Beijing Olympic Games participants

    Directory of Open Access Journals (Sweden)

    Tiago M. Barbosa

    2013-01-01

    Full Text Available The aim of this paper was to: (i describe the Beijing 2008 Olympic Games swimmer’s ages and; (ii compare ages according to swimmer’s gender. It was analyzed 1101 inscriptions (588 men and 513 women for all swimming events held at the Beijing 2008 Olympic Games: 50 meters freestyle (L50, 100 meters freestyle (L100, 200 meters freestyle (L200, 400 meters freestyle (L400, 800 meters freestyle (L800, only women 1500 meters freestyle (L1500, only men, 100 meters backstroke (C100, 200 meters backstroke (C200, 100 meters breaststroke (B100, 200 meters breaststroke (B200, 100 meters butterfly (M100, 200 meters butterfly (M200. The final result lists was consulted at the Beijing 2008 Olympic Games official internet site, collecting the swimmer’s name and chronological age for each event. Afterwards, chronological age was converted into decimal age at the day of the event heats. From the quartile analysis became clear that there was a tendency for the age median and variance to decrease from the shorter to the longest events for both genders. There were significant variations in the age, according to gender at the L400 ( p = .01, L1500/L800 ( p = .02, C100 ( p < .01, C200 ( p < .01, B100 ( p = .02, B200 ( p = .04, M100 ( p = .05 and M200 ( p < .01. For all these events, decimal age was higher for men than for women.

  10. Generation and relaxation of high rank coherences in AX3 systems in a selectively methionine labelled SH2 domain

    International Nuclear Information System (INIS)

    Kloiber, Karin; Fischer, Michael; Ledolter, Karin; Nagl, Michael; Schmid, Walther; Konrat, Robert

    2007-01-01

    The usefulness of selective isotope labelling patterns is demonstrated using the C-terminal SH2 domain of PLC-γ1 selectively 13 C labelled at methionine methyl groups. We demonstrate the generation and relaxation of coherences that are second rank in protons and first rank in carbons that derive from quadrupolar order in protons. The decay rates of second rank double quantum proton coherences are measured. These terms exhibit fewer channels for cross-correlated relaxation compared to single quantum coherences. Our results indicate the potential application of the measurement of high order proton coherences to the analysis of dynamics in methyl-bearing side chains

  11. Process correlation analysis model for process improvement identification.

    Science.gov (United States)

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

    2014-01-01

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

  12. Correlation analysis between ceramic insulator pollution and acoustic emissions

    Directory of Open Access Journals (Sweden)

    Benjamín Álvarez-Nasrallah

    2015-01-01

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

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

    Science.gov (United States)

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

    2013-08-12

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

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

    Science.gov (United States)

    Atkinson, J E

    1978-01-01

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

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

    DEFF Research Database (Denmark)

    Clemmensen, Line Katrine Harder

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

  16. Long-range correlation analysis of urban traffic data

    International Nuclear Information System (INIS)

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

    2010-01-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

    Costa, Valter Magalhaes; Pereira, Iraci Martinez, E-mail: valter.costa@usp.b [Instituto de Pesquisas Energeticas e Nucleares (IPEN/CNEN-SP), Sao Paulo, SP (Brazil)

    2011-07-01

    The monitoring of variables and diagnosis of sensor fault in nuclear power plants or processes industries is very important because a previous diagnosis allows the correction of the fault and, like this, to prevent the production stopped, improving operator's security and it's not provoking economics losses. The objective of this work is to build a set, using bivariate correlation and canonical correlation, which will be the set of input variables of an artificial neural network to monitor the greater number of variables. This methodology was applied to the IEA-R1 Research Reactor at IPEN. Initially, for the input set of neural network we selected the variables: nuclear power, primary circuit flow rate, control/safety rod position and difference in pressure in the core of the reactor, because almost whole of monitoring variables have relation with the variables early described or its effect can be result of the interaction of two or more. The nuclear power is related to the increasing and decreasing of temperatures as well as the amount radiation due fission of the uranium; the rods are controls of power and influence in the amount of radiation and increasing and decreasing of temperatures; the primary circuit flow rate has the function of energy transport by removing the nucleus heat. An artificial neural network was trained and the results were satisfactory since the IEA-R1 Data Acquisition System reactor monitors 64 variables and, with a set of 9 input variables resulting from the correlation analysis, it was possible to monitor 51 variables. (author)

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

    International Nuclear Information System (INIS)

    Costa, Valter Magalhaes; Pereira, Iraci Martinez

    2011-01-01

    The monitoring of variables and diagnosis of sensor fault in nuclear power plants or processes industries is very important because a previous diagnosis allows the correction of the fault and, like this, to prevent the production stopped, improving operator's security and it's not provoking economics losses. The objective of this work is to build a set, using bivariate correlation and canonical correlation, which will be the set of input variables of an artificial neural network to monitor the greater number of variables. This methodology was applied to the IEA-R1 Research Reactor at IPEN. Initially, for the input set of neural network we selected the variables: nuclear power, primary circuit flow rate, control/safety rod position and difference in pressure in the core of the reactor, because almost whole of monitoring variables have relation with the variables early described or its effect can be result of the interaction of two or more. The nuclear power is related to the increasing and decreasing of temperatures as well as the amount radiation due fission of the uranium; the rods are controls of power and influence in the amount of radiation and increasing and decreasing of temperatures; the primary circuit flow rate has the function of energy transport by removing the nucleus heat. An artificial neural network was trained and the results were satisfactory since the IEA-R1 Data Acquisition System reactor monitors 64 variables and, with a set of 9 input variables resulting from the correlation analysis, it was possible to monitor 51 variables. (author)

  19. Scalable Faceted Ranking in Tagging Systems

    Science.gov (United States)

    Orlicki, José I.; Alvarez-Hamelin, J. Ignacio; Fierens, Pablo I.

    Nowadays, web collaborative tagging systems which allow users to upload, comment on and recommend contents, are growing. Such systems can be represented as graphs where nodes correspond to users and tagged-links to recommendations. In this paper we analyze the problem of computing a ranking of users with respect to a facet described as a set of tags. A straightforward solution is to compute a PageRank-like algorithm on a facet-related graph, but it is not feasible for online computation. We propose an alternative: (i) a ranking for each tag is computed offline on the basis of tag-related subgraphs; (ii) a faceted order is generated online by merging rankings corresponding to all the tags in the facet. Based on the graph analysis of YouTube and Flickr, we show that step (i) is scalable. We also present efficient algorithms for step (ii), which are evaluated by comparing their results with two gold standards.

  20. Evaluation of treatment effects by ranking

    DEFF Research Database (Denmark)

    Halekoh, U; Kristensen, K

    2008-01-01

    In crop experiments measurements are often made by a judge evaluating the crops' conditions after treatment. In the present paper an analysis is proposed for experiments where plots of crops treated differently are mutually ranked. In the experimental layout the crops are treated on consecutive...... plots usually placed side by side in one or more rows. In the proposed method a judge ranks several neighbouring plots, say three, by ranking them from best to worst. For the next observation the judge moves on by no more than two plots, such that up to two plots will be re-evaluated again...... in a comparison with the new plot(s). Data from studies using this set-up were analysed by a Thurstonian random utility model, which assumed that the judge's rankings were obtained by comparing latent continuous utilities or treatment effects. For the latent utilities a variance component model was considered...

  1. Who's bigger? where historical figures really rank

    CERN Document Server

    Skiena, Steven

    2014-01-01

    Is Hitler bigger than Napoleon? Washington bigger than Lincoln? Picasso bigger than Einstein? Quantitative analysts are rapidly finding homes in social and cultural domains, from finance to politics. What about history? In this fascinating book, Steve Skiena and Charles Ward bring quantitative analysis to bear on ranking and comparing historical reputations. They evaluate each person by aggregating the traces of millions of opinions, just as Google ranks webpages. The book includes a technical discussion for readers interested in the details of the methods, but no mathematical or computational background is necessary to understand the rankings or conclusions. Along the way, the authors present the rankings of more than one thousand of history's most significant people in science, politics, entertainment, and all areas of human endeavor. Anyone interested in history or biography can see where their favorite figures place in the grand scheme of things.

  2. Ranking Baltic States Researchers

    Directory of Open Access Journals (Sweden)

    Gyula Mester

    2017-10-01

    Full Text Available In this article, using the h-index and the total number of citations, the best 10 Lithuanian, Latvian and Estonian researchers from several disciplines are ranked. The list may be formed based on the h-index and the total number of citations, given in Web of Science, Scopus, Publish or Perish Program and Google Scholar database. Data for the first 10 researchers are presented. Google Scholar is the most complete. Therefore, to define a single indicator, h-index calculated by Google Scholar may be a good and simple one. The author chooses the Google Scholar database as it is the broadest one.

  3. Fourth-rank cosmology

    International Nuclear Information System (INIS)

    Marrakchi, A.E.L.; Tapia, V.

    1992-05-01

    Some cosmological implications of the recently proposed fourth-rank theory of gravitation are studied. The model exhibits the possibility of being free from the horizon and flatness problems at the price of introducing a negative pressure. The field equations we obtain are compatible with k obs =0 and Ω obs t clas approx. 10 20 t Planck approx. 10 -23 s. When interpreted at the light of General Relativity the treatment is shown to be almost equivalent to that of the standard model of cosmology combined with the inflationary scenario. Hence, an interpretation of the negative pressure hypothesis is provided. (author). 8 refs

  4. University Rankings and Social Science

    OpenAIRE

    Marginson, S.

    2014-01-01

    University rankings widely affect the behaviours of prospective students and their families, university executive leaders, academic faculty, governments and investors in higher education. Yet the social science foundations of global rankings receive little scrutiny. Rankings that simply recycle reputation without any necessary connection to real outputs are of no common value. It is necessary that rankings be soundly based in scientific terms if a virtuous relationship between performance and...

  5. Protein structure similarity from principle component correlation analysis

    Directory of Open Access Journals (Sweden)

    Chou James

    2006-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Jianhua Ni

    2016-08-01

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

  7. Parametric uncertainty and global sensitivity analysis in a model of the carotid bifurcation: Identification and ranking of most sensitive model parameters.

    Science.gov (United States)

    Gul, R; Bernhard, S

    2015-11-01

    In computational cardiovascular models, parameters are one of major sources of uncertainty, which make the models unreliable and less predictive. In order to achieve predictive models that allow the investigation of the cardiovascular diseases, sensitivity analysis (SA) can be used to quantify and reduce the uncertainty in outputs (pressure and flow) caused by input (electrical and structural) model parameters. In the current study, three variance based global sensitivity analysis (GSA) methods; Sobol, FAST and a sparse grid stochastic collocation technique based on the Smolyak algorithm were applied on a lumped parameter model of carotid bifurcation. Sensitivity analysis was carried out to identify and rank most sensitive parameters as well as to fix less sensitive parameters at their nominal values (factor fixing). In this context, network location and temporal dependent sensitivities were also discussed to identify optimal measurement locations in carotid bifurcation and optimal temporal regions for each parameter in the pressure and flow waves, respectively. Results show that, for both pressure and flow, flow resistance (R), diameter (d) and length of the vessel (l) are sensitive within right common carotid (RCC), right internal carotid (RIC) and right external carotid (REC) arteries, while compliance of the vessels (C) and blood inertia (L) are sensitive only at RCC. Moreover, Young's modulus (E) and wall thickness (h) exhibit less sensitivities on pressure and flow at all locations of carotid bifurcation. Results of network location and temporal variabilities revealed that most of sensitivity was found in common time regions i.e. early systole, peak systole and end systole. Copyright © 2015 Elsevier Inc. All rights reserved.

  8. Research of Subgraph Estimation Page Rank Algorithm for Web Page Rank

    Directory of Open Access Journals (Sweden)

    LI Lan-yin

    2017-04-01

    Full Text Available The traditional PageRank algorithm can not efficiently perform large data Webpage scheduling problem. This paper proposes an accelerated algorithm named topK-Rank,which is based on PageRank on the MapReduce platform. It can find top k nodes efficiently for a given graph without sacrificing accuracy. In order to identify top k nodes,topK-Rank algorithm prunes unnecessary nodes and edges in each iteration to dynamically construct subgraphs,and iteratively estimates lower/upper bounds of PageRank scores through subgraphs. Theoretical analysis shows that this method guarantees result exactness. Experiments show that topK-Rank algorithm can find k nodes much faster than the existing approaches.

  9. University Rankings and Social Science

    Science.gov (United States)

    Marginson, Simon

    2014-01-01

    University rankings widely affect the behaviours of prospective students and their families, university executive leaders, academic faculty, governments and investors in higher education. Yet the social science foundations of global rankings receive little scrutiny. Rankings that simply recycle reputation without any necessary connection to real…

  10. Microseismic Event Relocation and Focal Mechanism Estimation Based on PageRank Linkage

    Science.gov (United States)

    Aguiar, A. C.; Myers, S. C.

    2017-12-01

    Microseismicity associated with enhanced geothermal systems (EGS) is key in understanding how subsurface stimulation can modify stress, fracture rock, and increase permeability. Large numbers of microseismic events are commonly associated with hydroshearing an EGS, making data mining methods useful in their analysis. We focus on PageRank, originally developed as Google's search engine, and subsequently adapted for use in seismology to detect low-frequency earthquakes by linking events directly and indirectly through cross-correlation (Aguiar and Beroza, 2014). We expand on this application by using PageRank to define signal-correlation topology for micro-earthquakes from the Newberry Volcano EGS in Central Oregon, which has been stimulated two times using high-pressure fluid injection. We create PageRank signal families from both data sets and compare these to the spatial and temporal proximity of associated earthquakes. PageRank families are relocated using differential travel times measured by waveform cross-correlation (CC) and the Bayesloc approach (Myers et al., 2007). Prior to relocation events are loosely clustered with events at a distance from the cluster. After relocation, event families are found to be tightly clustered. Indirect linkage of signals using PageRank is a reliable way to increase the number of events confidently determined to be similar, suggesting an efficient and effective grouping of earthquakes with similar physical characteristics (ie. location, focal mechanism, stress drop). We further explore the possibility of using PageRank families to identify events with similar relative phase polarities and estimate focal mechanisms following Shelly et al. (2016) method, where CC measurements are used to determine individual polarities within event clusters. Given a positive result, PageRank might be a useful tool in adaptive approaches to enhance production at well-instrumented geothermal sites. Prepared by LLNL under Contract DE-AC52-07NA27344

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

    Science.gov (United States)

    Olszewski, Adam; Broniowski, Wojciech

    2017-11-01

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

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

    Science.gov (United States)

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

    2018-02-01

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

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

    Directory of Open Access Journals (Sweden)

    Paolo Bianchini

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

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

    Science.gov (United States)

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

    2017-08-01

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

  15. Rank distributions: A panoramic macroscopic outlook

    Science.gov (United States)

    Eliazar, Iddo I.; Cohen, Morrel H.

    2014-01-01

    This paper presents a panoramic macroscopic outlook of rank distributions. We establish a general framework for the analysis of rank distributions, which classifies them into five macroscopic "socioeconomic" states: monarchy, oligarchy-feudalism, criticality, socialism-capitalism, and communism. Oligarchy-feudalism is shown to be characterized by discrete macroscopic rank distributions, and socialism-capitalism is shown to be characterized by continuous macroscopic size distributions. Criticality is a transition state between oligarchy-feudalism and socialism-capitalism, which can manifest allometric scaling with multifractal spectra. Monarchy and communism are extreme forms of oligarchy-feudalism and socialism-capitalism, respectively, in which the intrinsic randomness vanishes. The general framework is applied to three different models of rank distributions—top-down, bottom-up, and global—and unveils each model's macroscopic universality and versatility. The global model yields a macroscopic classification of the generalized Zipf law, an omnipresent form of rank distributions observed across the sciences. An amalgamation of the three models establishes a universal rank-distribution explanation for the macroscopic emergence of a prevalent class of continuous size distributions, ones governed by unimodal densities with both Pareto and inverse-Pareto power-law tails.

  16. Linearized spectrum correlation analysis for line emission measurements.

    Science.gov (United States)

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

    2017-08-01

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

  17. Ranking and analysis administrative barriers of fundamental principles and rights at work from the perspective of employers by using parametrical analysis and the TOPSIS method

    Directory of Open Access Journals (Sweden)

    Gholam Reza Bordbar

    2014-10-01

    Full Text Available ILO, adopted and communicated several types of document which include Conventions, recommendations, resolutions and statements etc.among all of them, convention has a special place because the members states accept duties and obligations. Among these conventions, those conventions that are related to the fundamental rights of labor had special importance and prestige. Member countries of the Organization like Iran are required to implement the relevant commitments. this study aimed to analyze administrative obstacles of the Fundamental Principles and Rights at Work by getting weight to problems and ranking them. The result of study show that Prohibition of child labor is more important than other aspects of Fundamental Principles and Rights at Work. in aspect of child labor most important obstacle was "red tape" ,in others categories result was as follow: in lack of collective bargaining most important obstacle was made emotional decisions, in forced labor most important obstacle was distrust of other workers, in gender discrimination most important obstacle was Working environment, in people inequality most important obstacle was Subjective judgments manager.

  18. Fractional cointegration rank estimation

    DEFF Research Database (Denmark)

    Lasak, Katarzyna; Velasco, Carlos

    the parameters of the model under the null hypothesis of the cointegration rank r = 1, 2, ..., p-1. This step provides consistent estimates of the cointegration degree, the cointegration vectors, the speed of adjustment to the equilibrium parameters and the common trends. In the second step we carry out a sup......-likelihood ratio test of no-cointegration on the estimated p - r common trends that are not cointegrated under the null. The cointegration degree is re-estimated in the second step to allow for new cointegration relationships with different memory. We augment the error correction model in the second step...... to control for stochastic trend estimation effects from the first step. The critical values of the tests proposed depend only on the number of common trends under the null, p - r, and on the interval of the cointegration degrees b allowed, but not on the true cointegration degree b0. Hence, no additional...

  19. On the Kendall Correlation Coefficient

    OpenAIRE

    Stepanov, Alexei

    2015-01-01

    In the present paper, we first discuss the Kendall rank correlation coefficient. In continuous case, we define the Kendall rank correlation coefficient in terms of the concomitants of order statistics, find the expected value of the Kendall rank correlation coefficient and show that the later is free of n. We also prove that in continuous case the Kendall correlation coefficient converges in probability to its expected value. We then propose to consider the expected value of the Kendall rank ...

  20. Rankings, creatividad y urbanismo

    Directory of Open Access Journals (Sweden)

    JOAQUÍN SABATÉ

    2008-08-01

    Full Text Available La competencia entre ciudades constituye uno de los factores impulsores de procesos de renovación urbana y los rankings han devenido instrumentos de medida de la calidad de las ciudades. Nos detendremos en el caso de un antiguo barrio industrial hoy en vías de transformación en distrito "creativo" por medio de una intervención urbanística de gran escala. Su análisis nos descubre tres claves críticas. En primer lugar, nos obliga a plantearnos la definición de innovación urbana y cómo se integran el pasado, la identidad y la memoria en la construcción del futuro. Nos lleva a comprender que la innovación y el conocimiento no se "dan" casualmente, sino que son el fruto de una larga y compleja red en la que participan saberes, espacios, actores e instituciones diversas en naturaleza, escala y magnitud. Por último nos obliga a reflexionar sobre el valor que se le otorga a lo local en los procesos de renovación urbana.Competition among cities constitutes one ofthe main factors o furban renewal, and rankings have become instruments to indícate cities quality. Studying the transformation of an old industrial quarter into a "creative district" by the means ofa large scale urban project we highlight three main conclusions. First, itasks us to reconsider the notion ofurban innovation and hoto past, identity and memory should intégrate the future development. Second, it shows that innovation and knowledge doesn't yield per chance, but are the result ofa large and complex grid of diverse knowledges, spaces, agents and institutions. Finally itforces us to reflect about the valué attributed to the "local" in urban renewalprocesses.

  1. VaRank: a simple and powerful tool for ranking genetic variants

    Directory of Open Access Journals (Sweden)

    Véronique Geoffroy

    2015-03-01

    Full Text Available Background. Most genetic disorders are caused by single nucleotide variations (SNVs or small insertion/deletions (indels. High throughput sequencing has broadened the catalogue of human variation, including common polymorphisms, rare variations or disease causing mutations. However, identifying one variation among hundreds or thousands of others is still a complex task for biologists, geneticists and clinicians.Results. We have developed VaRank, a command-line tool for the ranking of genetic variants detected by high-throughput sequencing. VaRank scores and prioritizes variants annotated either by Alamut Batch or SnpEff. A barcode allows users to quickly view the presence/absence of variants (with homozygote/heterozygote status in analyzed samples. VaRank supports the commonly used VCF input format for variants analysis thus allowing it to be easily integrated into NGS bioinformatics analysis pipelines. VaRank has been successfully applied to disease-gene identification as well as to molecular diagnostics setup for several hundred patients.Conclusions. VaRank is implemented in Tcl/Tk, a scripting language which is platform-independent but has been tested only on Unix environment. The source code is available under the GNU GPL, and together with sample data and detailed documentation can be downloaded from http://www.lbgi.fr/VaRank/.

  2. Ranking nodes in growing networks: When PageRank fails.

    Science.gov (United States)

    Mariani, Manuel Sebastian; Medo, Matúš; Zhang, Yi-Cheng

    2015-11-10

    PageRank is arguably the most popular ranking algorithm which is being applied in real systems ranging from information to biological and infrastructure networks. Despite its outstanding popularity and broad use in different areas of science, the relation between the algorithm's efficacy and properties of the network on which it acts has not yet been fully understood. We study here PageRank's performance on a network model supported by real data, and show that realistic temporal effects make PageRank fail in individuating the most valuable nodes for a broad range of model parameters. Results on real data are in qualitative agreement with our model-based findings. This failure of PageRank reveals that the static approach to information filtering is inappropriate for a broad class of growing systems, and suggest that time-dependent algorithms that are based on the temporal linking patterns of these systems are needed to better rank the nodes.

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

    Directory of Open Access Journals (Sweden)

    K. Rehfeld

    2011-06-01

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

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

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

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

    Directory of Open Access Journals (Sweden)

    Alexandria N Ardissone

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

  5. Analysis of the predictive qualities of betting odds and FIFA World Ranking: evidence from the 2006, 2010 and 2014 Football World Cups.

    Science.gov (United States)

    Wunderlich, Fabian; Memmert, Daniel

    2016-12-01

    The present study aims to investigate the ability of a new framework enabling to derive more detailed model-based predictions from ranking systems. These were compared to predictions from the bet market including data from the World Cups 2006, 2010, and 2014. The results revealed that the FIFA World Ranking has essentially improved its predictive qualities compared to the bet market since the mode of calculation was changed in 2006. While both predictors were useful to obtain accurate predictions in general, the world ranking was able to outperform the bet market significantly for the World Cup 2014 and when the data from the World Cups 2010 and 2014 were pooled. Our new framework can be extended in future research to more detailed prediction tasks (i.e., predicting the final scores of a match or the tournament progress of a team).

  6. Correlation set analysis: detecting active regulators in disease populations using prior causal knowledge

    Directory of Open Access Journals (Sweden)

    Huang Chia-Ling

    2012-03-01

    Full Text Available Abstract Background Identification of active causal regulators is a crucial problem in understanding mechanism of diseases or finding drug targets. Methods that infer causal regulators directly from primary data have been proposed and successfully validated in some cases. These methods necessarily require very large sample sizes or a mix of different data types. Recent studies have shown that prior biological knowledge can successfully boost a method's ability to find regulators. Results We present a simple data-driven method, Correlation Set Analysis (CSA, for comprehensively detecting active regulators in disease populations by integrating co-expression analysis and a specific type of literature-derived causal relationships. Instead of investigating the co-expression level between regulators and their regulatees, we focus on coherence of regulatees of a regulator. Using simulated datasets we show that our method performs very well at recovering even weak regulatory relationships with a low false discovery rate. Using three separate real biological datasets we were able to recover well known and as yet undescribed, active regulators for each disease population. The results are represented as a rank-ordered list of regulators, and reveals both single and higher-order regulatory relationships. Conclusions CSA is an intuitive data-driven way of selecting directed perturbation experiments that are relevant to a disease population of interest and represent a starting point for further investigation. Our findings demonstrate that combining co-expression analysis on regulatee sets with a literature-derived network can successfully identify causal regulators and help develop possible hypothesis to explain disease progression.

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

    International Nuclear Information System (INIS)

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

    1998-01-01

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

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

    OpenAIRE

    Zhao, Feng

    2013-01-01

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

  9. Pitch ranking, electrode discrimination, and physiological spread-of-excitation using Cochlear's dual-electrode mode.

    Science.gov (United States)

    Goehring, Jenny L; Neff, Donna L; Baudhuin, Jacquelyn L; Hughes, Michelle L

    2014-08-01

    This study compared pitch ranking, electrode discrimination, and electrically evoked compound action potential (ECAP) spatial excitation patterns for adjacent physical electrodes (PEs) and the corresponding dual electrodes (DEs) for newer-generation Cochlear devices (Cochlear Ltd., Macquarie, New South Wales, Australia). The first goal was to determine whether pitch ranking and electrode discrimination yield similar outcomes for PEs and DEs. The second goal was to determine if the amount of spatial separation among ECAP excitation patterns (separation index, Σ) between adjacent PEs and the PE-DE pairs can predict performance on the psychophysical tasks. Using non-adaptive procedures, 13 subjects completed pitch ranking and electrode discrimination for adjacent PEs and the corresponding PE-DE pairs (DE versus each flanking PE) from the basal, middle, and apical electrode regions. Analysis of d' scores indicated that pitch-ranking and electrode-discrimination scores were not significantly different, but rather produced similar levels of performance. As expected, accuracy was significantly better for the PE-PE comparison than either PE-DE comparison. Correlations of the psychophysical versus ECAP Σ measures were positive; however, not all test/region correlations were significant across the array. Thus, the ECAP separation index is not sensitive enough to predict performance on behavioral tasks of pitch ranking or electrode discrimination for adjacent PEs or corresponding DEs.

  10. A flexible time recording and time correlation analysis system

    International Nuclear Information System (INIS)

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

    1983-01-01

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

  11. Brillouin optical correlation domain analysis in composite material beams

    DEFF Research Database (Denmark)

    Stern, Yonatan; London, Yosef; Preter, Eyal

    2017-01-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2012-02-01

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

  13. ROLE ASSESSMENT OF GIS ANALYSIS AND ITS RELIABILITY WHILE RANKING URBAN SUSTAINABILITY USING SCENARIOS SPECIFIC TO REGIONAL CLIMATE, COMMUNITY AND CULTURE

    Directory of Open Access Journals (Sweden)

    H. Al Salmi

    2012-07-01

    Full Text Available Urban Sustainability expresses the level of conservation of a city while living a town or consuming its urban resources, but the measurement of urban sustainability depends on what are considered important indicators of conservation besides the permitted levels of consumption in accordance with adopted criteria. This criterion should have common factors that are shared for all the members tested or cities to be evaluated as in this particular case for Abu Dhabi, but also have specific factors that are related to the geographic place, community and culture, that is the measures of urban sustainability specific to a middle east climate, community and culture where GIS Vector and Raster analysis have a role or add a value in urban sustainability measurements or grading are considered herein. Scenarios were tested using various GIS data types to replicate urban history (ten years period, current status and expected future of Abu Dhabi City setting factors to climate, community needs and culture. The useful Vector or Raster GIS data sets that are related to every scenario where selected and analysed in the sense of how and how much it can benefit the urban sustainability ranking in quantity and quality tests, this besides assessing the suitable data nature, type and format, the important topology rules to be considered, the useful attributes to be added, the relationships which should be maintained between data types of a geo- database, and specify its usage in a specific scenario test, then setting weights to each and every data type representing some elements of a phenomenon related to urban suitability factor. The results of assessing the role of GIS analysis provided data collection specifications such as the measures of accuracy reliable to a certain type of GIS functional analysis used in an urban sustainability ranking scenario tests. This paper reflects the prior results of the research that is conducted to test the multidiscipline evaluation

  14. Role Assessment of GIS Analysis and its Reliability while Ranking Urban Sustainability Using Scenarios Specific to Regional Climate, Community and Culture

    Science.gov (United States)

    Salmi, H. Al; Abdulmuttalib, H. M.

    2012-07-01

    Urban Sustainability expresses the level of conservation of a city while living a town or consuming its urban resources, but the measurement of urban sustainability depends on what are considered important indicators of conservation besides the permitted levels of consumption in accordance with adopted criteria. This criterion should have common factors that are shared for all the members tested or cities to be evaluated as in this particular case for Abu Dhabi, but also have specific factors that are related to the geographic place, community and culture, that is the measures of urban sustainability specific to a middle east climate, community and culture where GIS Vector and Raster analysis have a role or add a value in urban sustainability measurements or grading are considered herein. Scenarios were tested using various GIS data types to replicate urban history (ten years period), current status and expected future of Abu Dhabi City setting factors to climate, community needs and culture. The useful Vector or Raster GIS data sets that are related to every scenario where selected and analysed in the sense of how and how much it can benefit the urban sustainability ranking in quantity and quality tests, this besides assessing the suitable data nature, type and format, the important topology rules to be considered, the useful attributes to be added, the relationships which should be maintained between data types of a geo- database, and specify its usage in a specific scenario test, then setting weights to each and every data type representing some elements of a phenomenon related to urban suitability factor. The results of assessing the role of GIS analysis provided data collection specifications such as the measures of accuracy reliable to a certain type of GIS functional analysis used in an urban sustainability ranking scenario tests. This paper reflects the prior results of the research that is conducted to test the multidiscipline evaluation of urban

  15. An R package for analyzing and modeling ranking data.

    Science.gov (United States)

    Lee, Paul H; Yu, Philip L H

    2013-05-14

    In medical informatics, psychology, market research and many other fields, researchers often need to analyze and model ranking data. However, there is no statistical software that provides tools for the comprehensive analysis of ranking data. Here, we present pmr, an R package for analyzing and modeling ranking data with a bundle of tools. The pmr package enables descriptive statistics (mean rank, pairwise frequencies, and marginal matrix), Analytic Hierarchy Process models (with Saaty's and Koczkodaj's inconsistencies), probability models (Luce model, distance-based model, and rank-ordered logit model), and the visualization of ranking data with multidimensional preference analysis. Examples of the use of package pmr are given using a real ranking dataset from medical informatics, in which 566 Hong Kong physicians ranked the top five incentives (1: competitive pressures; 2: increased savings; 3: government regulation; 4: improved efficiency; 5: improved quality care; 6: patient demand; 7: financial incentives) to the computerization of clinical practice. The mean rank showed that item 4 is the most preferred item and item 3 is the least preferred item, and significance difference was found between physicians' preferences with respect to their monthly income. A multidimensional preference analysis identified two dimensions that explain 42% of the total variance. The first can be interpreted as the overall preference of the seven items (labeled as "internal/external"), and the second dimension can be interpreted as their overall variance of (labeled as "push/pull factors"). Various statistical models were fitted, and the best were found to be weighted distance-based models with Spearman's footrule distance. In this paper, we presented the R package pmr, the first package for analyzing and modeling ranking data. The package provides insight to users through descriptive statistics of ranking data. Users can also visualize ranking data by applying a thought

  16. Low-rank coal research

    Energy Technology Data Exchange (ETDEWEB)

    Weber, G. F.; Laudal, D. L.

    1989-01-01

    This work is a compilation of reports on ongoing research at the University of North Dakota. Topics include: Control Technology and Coal Preparation Research (SO{sub x}/NO{sub x} control, waste management), Advanced Research and Technology Development (turbine combustion phenomena, combustion inorganic transformation, coal/char reactivity, liquefaction reactivity of low-rank coals, gasification ash and slag characterization, fine particulate emissions), Combustion Research (fluidized bed combustion, beneficiation of low-rank coals, combustion characterization of low-rank coal fuels, diesel utilization of low-rank coals), Liquefaction Research (low-rank coal direct liquefaction), and Gasification Research (hydrogen production from low-rank coals, advanced wastewater treatment, mild gasification, color and residual COD removal from Synfuel wastewaters, Great Plains Gasification Plant, gasifier optimization).

  17. Ranking Specific Sets of Objects.

    Science.gov (United States)

    Maly, Jan; Woltran, Stefan

    2017-01-01

    Ranking sets of objects based on an order between the single elements has been thoroughly studied in the literature. In particular, it has been shown that it is in general impossible to find a total ranking - jointly satisfying properties as dominance and independence - on the whole power set of objects. However, in many applications certain elements from the entire power set might not be required and can be neglected in the ranking process. For instance, certain sets might be ruled out due to hard constraints or are not satisfying some background theory. In this paper, we treat the computational problem whether an order on a given subset of the power set of elements satisfying different variants of dominance and independence can be found, given a ranking on the elements. We show that this problem is tractable for partial rankings and NP-complete for total rankings.

  18. Understanding structure of urban traffic network based on spatial-temporal correlation analysis

    Science.gov (United States)

    Yang, Yanfang; Jia, Limin; Qin, Yong; Han, Shixiu; Dong, Honghui

    2017-08-01

    Understanding the structural characteristics of urban traffic network comprehensively can provide references for improving road utilization rate and alleviating traffic congestion. This paper focuses on the spatial-temporal correlations between different pairs of traffic series and proposes a complex network-based method of constructing the urban traffic network. In the network, the nodes represent road segments, and an edge between a pair of nodes is added depending on the result of significance test for the corresponding spatial-temporal correlation. Further, a modified PageRank algorithm, named the geographical weight-based PageRank algorithm (GWPA), is proposed to analyze the spatial distribution of important segments in the road network. Finally, experiments are conducted by using three kinds of traffic series collected from the urban road network in Beijing. Experimental results show that the urban traffic networks constructed by three traffic variables all indicate both small-world and scale-free characteristics. Compared with the results of PageRank algorithm, GWPA is proved to be valid in evaluating the importance of segments and identifying the important segments with small degree.

  19. An Analysis of the Perceptions of "U.S. News and World Report" College Ranking Systems by Enrollment Managers of American Jesuit Colleges and Universities

    Science.gov (United States)

    Stoltz, Adam C.

    2012-01-01

    The focus of this study involves the perceptions held by enrollment managers at the American Jesuit Catholic colleges and universities of national rankings of colleges and universities and the strategic use of this information. Enrollment management emerged within colleges and universities in response to increasing competition for incoming…

  20. Brillouin Optical Correlation Domain Analysis in Composite Material Beams

    Directory of Open Access Journals (Sweden)

    Yonatan Stern

    2017-10-01

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

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

    Science.gov (United States)

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

    2017-10-02

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

  2. 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.

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

    International Nuclear Information System (INIS)

    He Lingyun; Chen Shupeng

    2011-01-01

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

  4. Correlation and network analysis of global financial indices.

    Science.gov (United States)

    Kumar, Sunil; Deo, Nivedita

    2012-08-01

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

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

    Directory of Open Access Journals (Sweden)

    Kevin Schwahn

    2017-12-01

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

  6. 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.

  7. Prognostic value of correlation analysis of perinatal anamnesis

    Directory of Open Access Journals (Sweden)

    V. V. Sofronov

    2017-01-01

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

  8. Ranking nodes in growing networks: When PageRank fails

    Science.gov (United States)

    Mariani, Manuel Sebastian; Medo, Matúš; Zhang, Yi-Cheng

    2015-11-01

    PageRank is arguably the most popular ranking algorithm which is being applied in real systems ranging from information to biological and infrastructure networks. Despite its outstanding popularity and broad use in different areas of science, the relation between the algorithm’s efficacy and properties of the network on which it acts has not yet been fully understood. We study here PageRank’s performance on a network model supported by real data, and show that realistic temporal effects make PageRank fail in individuating the most valuable nodes for a broad range of model parameters. Results on real data are in qualitative agreement with our model-based findings. This failure of PageRank reveals that the static approach to information filtering is inappropriate for a broad class of growing systems, and suggest that time-dependent algorithms that are based on the temporal linking patterns of these systems are needed to better rank the nodes.

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

    Science.gov (United States)

    Kim, Hyoung M.; Kaouk, Mohamed

    2000-01-01

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

  10. Ranking related entities: components and analyses

    NARCIS (Netherlands)

    Bron, M.; Balog, K.; de Rijke, M.

    2010-01-01

    Related entity finding is the task of returning a ranked list of homepages of relevant entities of a specified type that need to engage in a given relationship with a given source entity. We propose a framework for addressing this task and perform a detailed analysis of four core components;

  11. Primate Innovation: Sex, Age and Social Rank

    NARCIS (Netherlands)

    Reader, S.M.; Laland, K.N.

    2001-01-01

    Analysis of an exhaustive survey of primate behavior collated from the published literature revealed significant variation in rates of innovation among individuals of different sex, age and social rank. We searched approximately 1,000 articles in four primatology journals, together with other

  12. A generalization of Friedman's rank statistic

    NARCIS (Netherlands)

    Kroon, de J.; Laan, van der P.

    1983-01-01

    In this paper a very natural generalization of the two·way analysis of variance rank statistic of FRIEDMAN is given. The general distribution-free test procedure based on this statistic for the effect of J treatments in a random block design can be applied in general two-way layouts without

  13. Asymmetric correlation matrices: an analysis of financial data

    Science.gov (United States)

    Livan, G.; Rebecchi, L.

    2012-06-01

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

  14. Low Rank Approximation Algorithms, Implementation, Applications

    CERN Document Server

    Markovsky, Ivan

    2012-01-01

    Matrix low-rank approximation is intimately related to data modelling; a problem that arises frequently in many different fields. Low Rank Approximation: Algorithms, Implementation, Applications is a comprehensive exposition of the theory, algorithms, and applications of structured low-rank approximation. Local optimization methods and effective suboptimal convex relaxations for Toeplitz, Hankel, and Sylvester structured problems are presented. A major part of the text is devoted to application of the theory. Applications described include: system and control theory: approximate realization, model reduction, output error, and errors-in-variables identification; signal processing: harmonic retrieval, sum-of-damped exponentials, finite impulse response modeling, and array processing; machine learning: multidimensional scaling and recommender system; computer vision: algebraic curve fitting and fundamental matrix estimation; bioinformatics for microarray data analysis; chemometrics for multivariate calibration; ...

  15. Resolution of ranking hierarchies in directed networks

    Science.gov (United States)

    Barucca, Paolo; Lillo, Fabrizio

    2018-01-01

    Identifying hierarchies and rankings of nodes in directed graphs is fundamental in many applications such as social network analysis, biology, economics, and finance. A recently proposed method identifies the hierarchy by finding the ordered partition of nodes which minimises a score function, termed agony. This function penalises the links violating the hierarchy in a way depending on the strength of the violation. To investigate the resolution of ranking hierarchies we introduce an ensemble of random graphs, the Ranked Stochastic Block Model. We find that agony may fail to identify hierarchies when the structure is not strong enough and the size of the classes is small with respect to the whole network. We analytically characterise the resolution threshold and we show that an iterated version of agony can partly overcome this resolution limit. PMID:29394278

  16. Systematic monitoring of male circumcision scale-up in Nyanza, Kenya: exploratory factor analysis of service quality instrument and performance ranking.

    Science.gov (United States)

    Omondi Aduda, Dickens S; Ouma, Collins; Onyango, Rosebella; Onyango, Mathews; Bertrand, Jane

    2014-01-01

    Considerable conceptual and operational complexities related to service quality measurements and variability in delivery contexts of scaled-up medical male circumcision, pose real challenges to monitoring implementation of quality and safety. Clarifying latent factors of the quality instruments can enhance contextual applicability and the likelihood that observed service outcomes are appropriately assessed. To explore factors underlying SYMMACS service quality assessment tool (adopted from the WHO VMMC quality toolkit) and; determine service quality performance using composite quality index derived from the latent factors. Using a comparative process evaluation of Voluntary Medical Male Circumcision Scale-Up in Kenya site level data was collected among health facilities providing VMMC over two years. Systematic Monitoring of the Medical Male Circumcision Scale-Up quality instrument was used to assess availability of guidelines, supplies and equipment, infection control, and continuity of care services. Exploratory factor analysis was performed to clarify quality structure. Fifty four items and 246 responses were analyzed. Based on Eigenvalue >1.00 cut-off, factors 1, 2 & 3 were retained each respectively having eigenvalues of 5.78; 4.29; 2.99. These cumulatively accounted for 29.1% of the total variance (12.9%; 9.5%; 6.7%) with final communality estimates being 13.06. Using a cut-off factor loading value of ≥0.4, fifteen items loading on factor 1, five on factor 2 and one on factor 3 were retained. Factor 1 closely relates to preparedness to deliver safe male circumcisions while factor two depicts skilled task performance and compliance with protocols. Of the 28 facilities, 32% attained between 90th and 95th percentile (excellent); 45% between 50th and 75th percentiles (average) and 14.3% below 25th percentile (poor). the service quality assessment instrument may be simplified to have nearly 20 items that relate more closely to service outcomes. Ranking of

  17. Clinical trial registration, reporting, publication and FDAAA compliance: a cross-sectional analysis and ranking of new drugs approved by the FDA in 2012

    Science.gov (United States)

    Miller, Jennifer E; Korn, David; Ross, Joseph S

    2015-01-01

    Objective To evaluate clinical trial registration, reporting and publication rates for new drugs by: (1) legal requirements and (2) the ethical standard that all human subjects research should be publicly accessible to contribute to generalisable knowledge. Design Cross-sectional analysis of all clinical trials submitted to the Food and Drug Administration (FDA) for drugs approved in 2012, sponsored by large biopharmaceutical companies. Data sources Information from Drugs@FDA, ClinicalTrials.gov, MEDLINE-indexed journals and drug company communications. Main outcome measures Clinical trial registration and results reporting in ClinicalTrials.gov, publication in the medical literature, and compliance with the 2007 FDA Amendments Acts (FDAAA), analysed on the drug level. Results The FDA approved 15 drugs sponsored by 10 large companies in 2012. We identified 318 relevant trials involving 99 599 research participants. Per drug, a median of 57% (IQR 32–83%) of trials were registered, 20% (IQR 12–28%) reported results in ClinicalTrials.gov, 56% (IQR 41–83%) were published, and 65% (IQR 41–83%) were either published or reported results. Almost half of all reviewed drugs had at least one undisclosed phase II or III trial. Per drug, a median of 17% (IQR 8–20%) of trials supporting FDA approvals were subject to FDAAA mandated public disclosure; of these, a median of 67% (IQR 0–100%) were FDAAA-compliant. 68% of research participants (67 629 of 99 599) participated in FDAAA-subject trials, with 51% (33 405 of 67 629) enrolled in non-compliant trials. Transparency varied widely among companies. Conclusions Trial disclosures for new drugs remain below legal and ethics standards, with wide variation in practices among drugs and their sponsors. Best practices are emerging. 2 of our 10 reviewed companies disclosed all trials and complied with legal disclosure requirements for their 2012 approved drugs. Ranking new drugs on transparency criteria may improve

  18. Ranking agricultural, environmental and natural resource economics journals: A note

    OpenAIRE

    Halkos, George; Tzeremes, Nickolaos

    2012-01-01

    This paper by applying Data Envelopment Analysis (DEA) ranks for the first time Economics journals in the field of Agricultural, Environmental and Natural Resource. Specifically, by using one composite input and one composite output the paper ranks 32 journals. In addition for the first time three different quality ranking reports have been incorporated to the DEA modelling problem in order to classify the journals into four categories (‘A’ to ‘D’). The results reveal that the journals with t...

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

    Science.gov (United States)

    Dutta, Srimonti; Ghosh, Dipak; Chatterjee, Sucharita

    2016-12-01

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

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

    Science.gov (United States)

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

    2017-05-01

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

  1. Econophysics of a ranked demand and supply resource allocation problem

    Science.gov (United States)

    Priel, Avner; Tamir, Boaz

    2018-01-01

    We present a two sided resource allocation problem, between demands and supplies, where both parties are ranked. For example, in Big Data problems where a set of different computational tasks is divided between a set of computers each with its own resources, or between employees and employers where both parties are ranked, the employees by their fitness and the employers by their package benefits. The allocation process can be viewed as a repeated game where in each iteration the strategy is decided by a meta-rule, based on the ranks of both parties and the results of the previous games. We show the existence of a phase transition between an absorbing state, where all demands are satisfied, and an active one where part of the demands are always left unsatisfied. The phase transition is governed by the ratio between supplies and demand. In a job allocation problem we find positive correlation between the rank of the workers and the rank of the factories; higher rank workers are usually allocated to higher ranked factories. These all suggest global emergent properties stemming from local variables. To demonstrate the global versus local relations, we introduce a local inertial force that increases the rank of employees in proportion to their persistence time in the same factory. We show that such a local force induces non trivial global effects, mostly to benefit the lower ranked employees.

  2. Engineering Properties and Correlation Analysis of Fiber Cementitious Materials

    Directory of Open Access Journals (Sweden)

    Wei-Ting Lin

    2014-11-01

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

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

    Science.gov (United States)

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

    2017-10-01

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

  4. PageRank tracker: from ranking to tracking.

    Science.gov (United States)

    Gong, Chen; Fu, Keren; Loza, Artur; Wu, Qiang; Liu, Jia; Yang, Jie

    2014-06-01

    Video object tracking is widely used in many real-world applications, and it has been extensively studied for over two decades. However, tracking robustness is still an issue in most existing methods, due to the difficulties with adaptation to environmental or target changes. In order to improve adaptability, this paper formulates the tracking process as a ranking problem, and the PageRank algorithm, which is a well-known webpage ranking algorithm used by Google, is applied. Labeled and unlabeled samples in tracking application are analogous to query webpages and the webpages to be ranked, respectively. Therefore, determining the target is equivalent to finding the unlabeled sample that is the most associated with existing labeled set. We modify the conventional PageRank algorithm in three aspects for tracking application, including graph construction, PageRank vector acquisition and target filtering. Our simulations with the use of various challenging public-domain video sequences reveal that the proposed PageRank tracker outperforms mean-shift tracker, co-tracker, semiboosting and beyond semiboosting trackers in terms of accuracy, robustness and stability.

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

    International Nuclear Information System (INIS)

    Lu Xinhua; Cai Bin; Wang Dawei; Wu Liping

    2003-01-01

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

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

    OpenAIRE

    Düllmann, Klaus; Scheicher, Martin; Schmieder, Christian

    2007-01-01

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

  7. 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

  8. The effect of corporate sustainability information on share returns: analysis of companies included in the Global Ranking 100 [doi: 10.21529/RECADM.2017010

    Directory of Open Access Journals (Sweden)

    Nathállya Etyenne Figueira Silva

    2017-10-01

    Full Text Available This study aimed to analyze the effect of corporate returns after the disclosure of inclusion in the Global 100 ranking. For this purpose, the methodology of the Study of Events was used, based on the hypothesis of a semi-strong efficient market. The Global 100 rankings considered in this study were the ones released over 12 years, from 2005 to 2016. The survey sample composed of the shares of the companies that had data on the date of their inclusion, and thus consisting of 266 shares. The variable used was daily quotations of companies' shares during the estimation period (160 days and event window (21 days and the market indices of the countries in which the share was quoted, collected in the Thomson Reuters Database®. The results showed that the release of the Global 100 ranking did not cause significant positive or negative effect on the cumulative abnormal returns (CARs of the shares of listed companies.   Keywords Global 100; Corporate social responsibility; Sustainability; Financial performance.

  9. Correlation of contrast-detail analysis and clinical image quality assessment in chest radiography with a human cadaver study.

    Science.gov (United States)

    De Crop, An; Bacher, Klaus; Van Hoof, Tom; Smeets, Peter V; Smet, Barbara S; Vergauwen, Merel; Kiendys, Urszula; Duyck, Philippe; Verstraete, Koenraad; D'Herde, Katharina; Thierens, Hubert

    2012-01-01

    To determine the correlation between the clinical and physical image quality of chest images by using cadavers embalmed with the Thiel technique and a contrast-detail phantom. The use of human cadavers fulfilled the requirements of the institutional ethics committee. Clinical image quality was assessed by using three human cadavers embalmed with the Thiel technique, which results in excellent preservation of the flexibility and plasticity of organs and tissues. As a result, lungs can be inflated during image acquisition to simulate the pulmonary anatomy seen on a chest radiograph. Both contrast-detail phantom images and chest images of the Thiel-embalmed bodies were acquired with an amorphous silicon flat-panel detector. Tube voltage (70, 81, 90, 100, 113, 125 kVp), copper filtration (0.1, 0.2, 0.3 mm Cu), and exposure settings (200, 280, 400, 560, 800 speed class) were altered to simulate different quality levels. Four experienced radiologists assessed the image quality by using a visual grading analysis (VGA) technique based on European Quality Criteria for Chest Radiology. The phantom images were scored manually and automatically with use of dedicated software, both resulting in an inverse image quality figure (IQF). Spearman rank correlations between inverse IQFs and VGA scores were calculated. A statistically significant correlation (r = 0.80, P chest radiography. © RSNA, 2011.

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

    International Nuclear Information System (INIS)

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

    2013-01-01

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

  11. Linear analysis of degree correlations in complex networks

    Indian Academy of Sciences (India)

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

  12. Reliability assessment and correlation analysis of evaluating orthodontic treatment outcome in Chinese patients.

    Science.gov (United States)

    Song, Guang-Ying; Zhao, Zhi-He; Ding, Yin; Bai, Yu-Xing; Wang, Lin; He, Hong; Shen, Gang; Li, Wei-Ran; Baumrind, Sheldon; Geng, Zhi; Xu, Tian-Min

    2014-03-01

    This study aimed to assess the reliability of experienced Chinese orthodontists in evaluating treatment outcome and to determine the correlations between three diagnostic information sources. Sixty-nine experienced Chinese orthodontic specialists each evaluated the outcome of orthodontic treatment of 108 Chinese patients. Three different information sources: study casts (SC), lateral cephalometric X-ray images (LX) and facial photographs (PH) were generated at the end of treatment for 108 patients selected randomly from six orthodontic treatment centers throughout China. Six different assessments of treatment outcome were made by each orthodontist using data from the three information sources separately and in combination. Each assessment included both ranking and grading for each patient. The rankings of each of the 69 judges for the 108 patients were correlated with the rankings of each of the other judges yielding 13 873 Spearman rs values, ranging from -0.08 to +0.85. Of these, 90% were greater than 0.4, showing moderate-to-high consistency among the 69 orthodontists. In the combined evaluations, study casts were the most significant predictive component (R(2)=0.86, P<0.000 1), while the inclusion of lateral cephalometric films and facial photographs also contributed to a more comprehensive assessment (R(2)=0.96, P<0.000 1). Grading scores for SC+LX and SC+PH were highly significantly correlated with those for SC+LX+PH (r(SC+LX)vs.(SC+LX+PH)=0.96, r(SC+PH)vs.(SC+LX+PH)=0.97), showing that either SC+LX or SC+PH is an excellent substitute for all three combined assessment.

  13. Composite multi-parameter ranking of real and virtual compounds for design of MC4R agonists: renaissance of the Free-Wilson methodology.

    Science.gov (United States)

    Nilsson, Ingemar; Polla, Magnus O

    2012-10-01

    Drug design is a multi-parameter task present in the analysis of experimental data for synthesized compounds and in the prediction of new compounds with desired properties. This article describes the implementation of a binned scoring and composite ranking scheme for 11 experimental parameters that were identified as key drivers in the MC4R project. The composite ranking scheme was implemented in an AstraZeneca tool for analysis of project data, thereby providing an immediate re-ranking as new experimental data was added. The automated ranking also highlighted compounds overlooked by the project team. The successful implementation of a composite ranking on experimental data led to the development of an equivalent virtual score, which was based on Free-Wilson models of the parameters from the experimental ranking. The individual Free-Wilson models showed good to high predictive power with a correlation coefficient between 0.45 and 0.97 based on the external test set. The virtual ranking adds value to the selection of compounds for synthesis but error propagation must be controlled. The experimental ranking approach adds significant value, is parameter independent and can be tuned and applied to any drug discovery project.

  14. Ranking accounting, banking and finance journals: A note

    OpenAIRE

    Halkos, George; Tzeremes, Nickolaos

    2012-01-01

    This paper by applying Data Envelopment Analysis (DEA) ranks Economics journals in the field of Accounting, Banking and Finance. By using one composite input and one composite output the paper ranks 57 journals. In addition for the first time three different quality ranking reports have been incorporated to the DEA modelling problem in order to classify the journals into four categories (‘A’ to ‘D’). The results reveal that the journals with the highest rankings in the field are Journal of Fi...

  15. Methodology for ranking restoration options

    International Nuclear Information System (INIS)

    Hedemann Jensen, Per

    1999-04-01

    The work described in this report has been performed as a part of the RESTRAT Project FI4P-CT95-0021a (PL 950128) co-funded by the Nuclear Fission Safety Programme of the European Commission. The RESTRAT project has the overall objective of developing generic methodologies for ranking restoration techniques as a function of contamination and site characteristics. The project includes analyses of existing remediation methodologies and contaminated sites, and is structured in the following steps: characterisation of relevant contaminated sites; identification and characterisation of relevant restoration techniques; assessment of the radiological impact; development and application of a selection methodology for restoration options; formulation of generic conclusions and development of a manual. The project is intended to apply to situations in which sites with nuclear installations have been contaminated with radioactive materials as a result of the operation of these installations. The areas considered for remedial measures include contaminated land areas, rivers and sediments in rivers, lakes, and sea areas. Five contaminated European sites have been studied. Various remedial measures have been envisaged with respect to the optimisation of the protection of the populations being exposed to the radionuclides at the sites. Cost-benefit analysis and multi-attribute utility analysis have been applied for optimisation. Health, economic and social attributes have been included and weighting factors for the different attributes have been determined by the use of scaling constants. (au)

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

    Science.gov (United States)

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

    2014-05-15

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

  17. Universal scaling in sports ranking

    International Nuclear Information System (INIS)

    Deng Weibing; Li Wei; Cai Xu; Bulou, Alain; Wang Qiuping A

    2012-01-01

    Ranking is a ubiquitous phenomenon in human society. On the web pages of Forbes, one may find all kinds of rankings, such as the world's most powerful people, the world's richest people, the highest-earning tennis players, and so on and so forth. Herewith, we study a specific kind—sports ranking systems in which players' scores and/or prize money are accrued based on their performances in different matches. By investigating 40 data samples which span 12 different sports, we find that the distributions of scores and/or prize money follow universal power laws, with exponents nearly identical for most sports. In order to understand the origin of this universal scaling we focus on the tennis ranking systems. By checking the data we find that, for any pair of players, the probability that the higher-ranked player tops the lower-ranked opponent is proportional to the rank difference between the pair. Such a dependence can be well fitted to a sigmoidal function. By using this feature, we propose a simple toy model which can simulate the competition of players in different matches. The simulations yield results consistent with the empirical findings. Extensive simulation studies indicate that the model is quite robust with respect to the modifications of some parameters. (paper)

  18. Adsorption isotherms and kinetics of activated carbons produced from coals of different ranks.

    Science.gov (United States)

    Purevsuren, B; Lin, Chin-Jung; Davaajav, Y; Ariunaa, A; Batbileg, S; Avid, B; Jargalmaa, S; Huang, Yu; Liou, Sofia Ya-Hsuan

    2015-01-01

    Activated carbons (ACs) from six coals, ranging from low-rank lignite brown coal to high-rank stone coal, were utilized as adsorbents to remove basic methylene blue (MB) from an aqueous solution. The surface properties of the obtained ACs were characterized via thermal analysis, N2 isothermal sorption, scanning electron microscopy, Fourier transform infrared spectroscopy, X-ray photoelectron spectroscopy and Boehm titration. As coal rank decreased, an increase in the heterogeneity of the pore structures and abundance of oxygen-containing functional groups increased MB coverage on its surface. The equilibrium data fitted well with the Langmuir model, and adsorption capacity of MB ranged from 51.8 to 344.8 mg g⁻¹. Good correlation coefficients were obtained using the intra-particle diffusion model, indicating that the adsorption of MB onto ACs is diffusion controlled. The values of the effective diffusion coefficient ranged from 0.61 × 10⁻¹⁰ to 7.1 × 10⁻¹⁰ m² s⁻¹, indicating that ACs from lower-rank coals have higher effective diffusivities. Among all the ACs obtained from selected coals, the AC from low-rank lignite brown coal was the most effective in removing MB from an aqueous solution.

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

    Science.gov (United States)

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

    2013-09-01

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

  20. On the ranking of chemicals based on their PBT characteristics: comparison of different ranking methodologies using selected POPs as an illustrative example.

    Science.gov (United States)

    Sailaukhanuly, Yerbolat; Zhakupbekova, Arai; Amutova, Farida; Carlsen, Lars

    2013-01-01

    Knowledge of the environmental behavior of chemicals is a fundamental part of the risk assessment process. The present paper discusses various methods of ranking of a series of persistent organic pollutants (POPs) according to the persistence, bioaccumulation and toxicity (PBT) characteristics. Traditionally ranking has been done as an absolute (total) ranking applying various multicriteria data analysis methods like simple additive ranking (SAR) or various utility functions (UFs) based rankings. An attractive alternative to these ranking methodologies appears to be partial order ranking (POR). The present paper compares different ranking methods like SAR, UF and POR. Significant discrepancies between the rankings are noted and it is concluded that partial order ranking, as a method without any pre-assumptions concerning possible relation between the single parameters, appears as the most attractive ranking methodology. In addition to the initial ranking partial order methodology offers a wide variety of analytical tools to elucidate the interplay between the objects to be ranked and the ranking parameters. In the present study is included an analysis of the relative importance of the single P, B and T parameters. Copyright © 2012 Elsevier Ltd. All rights reserved.

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

    Science.gov (United States)

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

    2011-01-01

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

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

    International Nuclear Information System (INIS)

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

    1997-01-01

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

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

    International Nuclear Information System (INIS)

    Morishita, T.; Lin, C.D.

    1999-01-01

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

  4. PageRank of integers

    International Nuclear Information System (INIS)

    Frahm, K M; Shepelyansky, D L; Chepelianskii, A D

    2012-01-01

    We up a directed network tracing links from a given integer to its divisors and analyze the properties of the Google matrix of this network. The PageRank vector of this matrix is computed numerically and it is shown that its probability is approximately inversely proportional to the PageRank index thus being similar to the Zipf law and the dependence established for the World Wide Web. The spectrum of the Google matrix of integers is characterized by a large gap and a relatively small number of nonzero eigenvalues. A simple semi-analytical expression for the PageRank of integers is derived that allows us to find this vector for matrices of billion size. This network provides a new PageRank order of integers. (paper)

  5. Trachomatous Scar Ranking: A Novel Outcome for Trachoma Studies.

    Science.gov (United States)

    Baldwin, Angela; Ryner, Alexander M; Tadesse, Zerihun; Shiferaw, Ayalew; Callahan, Kelly; Fry, Dionna M; Zhou, Zhaoxia; Lietman, Thomas M; Keenan, Jeremy D

    2017-06-01

    AbstractWe evaluated a new trachoma scarring ranking system with potential use in clinical research. The upper right tarsal conjunctivas of 427 individuals from Ethiopian villages with hyperendemic trachoma were photographed. An expert grader first assigned a scar grade to each photograph using the 1981 World Health Organization (WHO) grading system. Then, all photographs were ranked from least (rank = 1) to most scarring (rank = 427). Photographic grading found 79 (18.5%) conjunctivae without scarring (C0), 191 (44.7%) with minimal scarring (C1), 105 (24.6%) with moderate scarring (C2), and 52 (12.2%) with severe scarring (C3). The ranking method demonstrated good internal validity, exhibiting a monotonic increase in the median rank across the levels of the 1981 WHO grading system. Intrarater repeatability was better for the ranking method (intraclass correlation coefficient = 0.84, 95% CI = 0.74-0.94). Exhibiting better internal and external validity, this ranking method may be useful for evaluating the difference in scarring between groups of individuals.

  6. Freudenthal ranks: GHZ versus W

    International Nuclear Information System (INIS)

    Borsten, L

    2013-01-01

    The Hilbert space of three-qubit pure states may be identified with a Freudenthal triple system. Every state has an unique Freudenthal rank ranging from 1 to 4, which is determined by a set of automorphism group covariants. It is shown here that the optimal success rates for winning a three-player non-local game, varying over all local strategies, are strictly ordered by the Freudenthal rank of the shared three-qubit resource. (paper)

  7. Análise descritiva por ordenação: aplicação na caracterização sensorial de biscoitos laminados salgados Ranking descriptive analysis: application in the sensory characterization of cracker biscuits

    Directory of Open Access Journals (Sweden)

    Lorena Carnelocce

    2012-12-01

    Full Text Available A Análise Descritiva por Ordenação (ADO foi aplicada na caracterização de biscoitos cream cracker e água e sal comerciais, empregando julgadores pré-selecionados, mas sem experiência prévia em análise sensorial. O método compreendeu as etapas de levantamento e conceituação dos atributos, treinamento qualitativo e análise final, utilizando o procedimento de ordenação. Para verificação da eficiência na discriminação das amostras, o procedimento de ordenação foi comparado ao uso de escala não estruturada. Dados de caracterização instrumental de textura e cor foram comparados aos obtidos na descrição sensorial dos biscoitos. Análise Procrustes Generalizada foi utilizada na avaliação dos dados de ordenação ou escala, e os resultados da ordenação foram também avaliados por Teste de Friedman. A eficiência da equipe e a configuração das amostras foram similares no procedimento de ordenação e com o uso de escala. Após um treinamento qualitativo e uma avaliação inicial das amostras por um procedimento de ordenação, os julgadores não apresentaram divergência de comportamento, mesmo empregando um procedimento mais difícil (uso de escala. Cor e aroma de assado e sabor tostado, aroma de manteiga e sabor amanteigado, crocância (manual e na boca e uniformidade da cor foram os atributos mais importantes na discriminação. A ADO permitiu a caracterização e a discriminação de modo concordante com a composição indicada no rótulo dos produtos e os resultados instrumentais de textura e cor.Ranking Descriptive Analysis (RDA was applied to the characterization of commercial cream cracker and water and salt biscuits, using pre-selected assessors with no previous experience in sensory analysis. The method had the following steps: development of attributes, glossary and references, qualitative training and final analysis using the ranking procedure. To check the efficiency in discriminating the samples, the ranking

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

    Science.gov (United States)

    Angelucci, Filippo; Javeed, Mehzad; Mcgowan, Paul

    1992-01-01

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

  9. Ranking in evolving complex networks

    Science.gov (United States)

    Liao, Hao; Mariani, Manuel Sebastian; Medo, Matúš; Zhang, Yi-Cheng; Zhou, Ming-Yang

    2017-05-01

    Complex networks have emerged as a simple yet powerful framework to represent and analyze a wide range of complex systems. The problem of ranking the nodes and the edges in complex networks is critical for a broad range of real-world problems because it affects how we access online information and products, how success and talent are evaluated in human activities, and how scarce resources are allocated by companies and policymakers, among others. This calls for a deep understanding of how existing ranking algorithms perform, and which are their possible biases that may impair their effectiveness. Many popular ranking algorithms (such as Google's PageRank) are static in nature and, as a consequence, they exhibit important shortcomings when applied to real networks that rapidly evolve in time. At the same time, recent advances in the understanding and modeling of evolving networks have enabled the development of a wide and diverse range of ranking algorithms that take the temporal dimension into account. The aim of this review is to survey the existing ranking algorithms, both static and time-aware, and their applications to evolving networks. We emphasize both the impact of network evolution on well-established static algorithms and the benefits from including the temporal dimension for tasks such as prediction of network traffic, prediction of future links, and identification of significant nodes.

  10. Analysis of factors correlating with medical radiological examination frequencies

    International Nuclear Information System (INIS)

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

    2015-01-01

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

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

    International Nuclear Information System (INIS)

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

    1976-12-01

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

  12. Effect of harmonic rank on the streaming of complex tones

    DEFF Research Database (Denmark)

    Madsen, Sara Miay Kim; Dau, Torsten; Moore, Brian C.J.

    2015-01-01

    The effect of the rank of the harmonics on sequential stream segregation of complex tones was investigated for normal-hearing participants with no musical training. It was hypothesized that stream segregation would be greater for tones with high pitch salience, as assessed by fundamental frequency....... There was a significant trend for less stream segregation with increasing harmonic rank. The amount of stream segregation was inversely correlated with the f0 difference limens, consistent with the hypothesis....

  13. RANK and RANK ligand expression in primary human osteosarcoma

    Directory of Open Access Journals (Sweden)

    Daniel Branstetter

    2015-09-01

    Our results demonstrate RANKL expression was observed in the tumor element in 68% of human OS using IHC. However, the staining intensity was relatively low and only 37% (29/79 of samples exhibited≥10% RANKL positive tumor cells. RANK expression was not observed in OS tumor cells. In contrast, RANK expression was clearly observed in other cells within OS samples, including the myeloid osteoclast precursor compartment, osteoclasts and in giant osteoclast cells. The intensity and frequency of RANKL and RANK staining in OS samples were substantially less than that observed in GCTB samples. The observation that RANKL is expressed in OS cells themselves suggests that these tumors may mediate an osteoclastic response, and anti-RANKL therapy may potentially be protective against bone pathologies in OS. However, the absence of RANK expression in primary human OS cells suggests that any autocrine RANKL/RANK signaling in human OS tumor cells is not operative, and anti-RANKL therapy would not directly affect the tumor.

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

    African Journals Online (AJOL)

    use

    2011-12-12

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

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

    International Nuclear Information System (INIS)

    Kuo, H.H.; Durkee, M.

    1983-01-01

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

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

    African Journals Online (AJOL)

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

  17. Linear analysis of degree correlations in complex networks

    Indian Academy of Sciences (India)

    2016-11-02

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

  18. Correlational Analysis of Servant Leadership and School Climate

    Science.gov (United States)

    Black, Glenda Lee

    2010-01-01

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

  19. Analysis of Current HT9 Creep Correlations and Modification

    International Nuclear Information System (INIS)

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

    2014-01-01

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

  20. OPG/RANKL/RANK cytokine system in renal osteodystrophy

    Directory of Open Access Journals (Sweden)

    Ivica Avberšek-Lužnik

    2007-11-01

    Full Text Available Background: Renal osteodystrophy is one of the most common complications affecting patients with endstage renal disease treated with hemodialysis (HD. The action of calciotropic hormones in renal osteodystrophy is regulated by the OPG/RANKL/RANK system. Its function is modulated by interleukines, calcitriol and parathyroid hormone (PTH.The aim of our study was to confirm that this system is involved in the pathogenesis of renal osteodystrophy and supports the mechanism of PTH action on bone.Methods: 106 HD patients (mean age 60 years and 50 healthy volunteers (mean age 64 years were enrolled in the study. In serum samples of patients and controls we determined concentrations of OPG, RANKL, tartarat resistant acid phosphatase 5b (TRAP 5b, serum Cterminal telopeptide cross-links of type I collagen (CTx, bone specific alkaline phosphatase (BALP, osteocalcin (OC and parathyroid hormone (PTH. We compared serum measurements of HD patients and controls and assessed the correlation of OPG and RANKL with bone markers. The most frequent OPG promotor gene polymorphisms were also determined. SPSS 12.1 for Windows was used for statistical analysis.Results: Median OPG concentrations were approximately three times higher in HD patients (0.804 µg/l than in healthy volunteers (0.272 µg/l. Mean serum RANKL concentrations were 1.66- fold higher in HD patients (1.36 pmol/l than in controls (0.82 pmol/l. Serum RANKL levels significantly differed between patients with and without calcitriol therapy (p = 0.001. After dividing HD patients into tertiles according to PTH, we observed significantly higher OPG values in the lower and RANKL in the upper tertile (p < 0.001. OPG did not correlate with bone resorption markers. Only weak correlation of bone formation markers with osteocalcin was noted. In contrast to OPG, RANKL correlated well with PTH, OC and CTX. OPG promoter gene polymorphisms (149 T → C, 163 A → G, 950 T → C do not influence OPG expression and

  1. Technique for information retrieval using enhanced latent semantic analysis generating rank approximation matrix by factorizing the weighted morpheme-by-document matrix

    Science.gov (United States)

    Chew, Peter A; Bader, Brett W

    2012-10-16

    A technique for information retrieval includes parsing a corpus to identify a number of wordform instances within each document of the corpus. A weighted morpheme-by-document matrix is generated based at least in part on the number of wordform instances within each document of the corpus and based at least in part on a weighting function. The weighted morpheme-by-document matrix separately enumerates instances of stems and affixes. Additionally or alternatively, a term-by-term alignment matrix may be generated based at least in part on the number of wordform instances within each document of the corpus. At least one lower rank approximation matrix is generated by factorizing the weighted morpheme-by-document matrix and/or the term-by-term alignment matrix.

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

    International Nuclear Information System (INIS)

    Robinson, D.P.

    1981-01-01

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

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

    International Nuclear Information System (INIS)

    Clifton, P.M.

    1985-03-01

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

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

    Science.gov (United States)

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

    2003-11-01

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

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

    Directory of Open Access Journals (Sweden)

    Y. X. Li

    2013-07-01

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

  6. Dynamics of market correlations: Taxonomy and portfolio analysis

    Science.gov (United States)

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

    2003-11-01

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

  7. Correlation analysis on alpha attenuation and nasal skin temperature

    International Nuclear Information System (INIS)

    Nozawa, Akio; Tacano, Munecazu

    2009-01-01

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

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

    International Nuclear Information System (INIS)

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

    1998-01-01

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

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

    Science.gov (United States)

    Delignières, Didier; Marmelat, Vivien

    2014-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Yixiong Feng

    2017-03-01

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

  11. Ranking species in mutualistic networks

    Science.gov (United States)

    Domínguez-García, Virginia; Muñoz, Miguel A.

    2015-02-01

    Understanding the architectural subtleties of ecological networks, believed to confer them enhanced stability and robustness, is a subject of outmost relevance. Mutualistic interactions have been profusely studied and their corresponding bipartite networks, such as plant-pollinator networks, have been reported to exhibit a characteristic ``nested'' structure. Assessing the importance of any given species in mutualistic networks is a key task when evaluating extinction risks and possible cascade effects. Inspired in a recently introduced algorithm -similar in spirit to Google's PageRank but with a built-in non-linearity- here we propose a method which -by exploiting their nested architecture- allows us to derive a sound ranking of species importance in mutualistic networks. This method clearly outperforms other existing ranking schemes and can become very useful for ecosystem management and biodiversity preservation, where decisions on what aspects of ecosystems to explicitly protect need to be made.

  12. Ranking Theory and Conditional Reasoning.

    Science.gov (United States)

    Skovgaard-Olsen, Niels

    2016-05-01

    Ranking theory is a formal epistemology that has been developed in over 600 pages in Spohn's recent book The Laws of Belief, which aims to provide a normative account of the dynamics of beliefs that presents an alternative to current probabilistic approaches. It has long been received in the AI community, but it has not yet found application in experimental psychology. The purpose of this paper is to derive clear, quantitative predictions by exploiting a parallel between ranking theory and a statistical model called logistic regression. This approach is illustrated by the development of a model for the conditional inference task using Spohn's (2013) ranking theoretic approach to conditionals. Copyright © 2015 Cognitive Science Society, Inc.

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

    OpenAIRE

    Han, Fang; Liu, Han

    2016-01-01

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

  14. Feasibility study of component risk ranking for plant maintenance

    International Nuclear Information System (INIS)

    Ushijima, Koji; Yonebayashi, Kenji; Narumiya, Yoshiyuki; Sakata, Kaoru; Kumano, Tetsuji

    1999-01-01

    Nuclear power is the base load electricity source in Japan, and reduction of operation and maintenance cost maintaining or improving plant safety is one of the major issues. Recently, Risk Informed Management (RIM) is focused as a solution. In this paper, the outline regarding feasibility study of component risk ranking for plant maintenance for a typical Japanese PWR plant is described. A feasibility study of component risk raking for plant maintenance optimization is performed on check valves and motor-operated valves. Risk ranking is performed in two steps using probabilistic analysis (quantitative method) for risk ranking of components, and deterministic examination (qualitative method) for component review. In this study, plant components are ranked from the viewpoint of plant safety / reliability, and the applicability for maintenance is assessed. As a result, distribution of maintenance resources using risk ranking is considered effective. (author)

  15. Subtracting a best rank-1 approximation may increase tensor rank

    NARCIS (Netherlands)

    Stegeman, Alwin; Comon, Pierre

    2010-01-01

    It has been shown that a best rank-R approximation of an order-k tensor may not exist when R >= 2 and k >= 3. This poses a serious problem to data analysts using tensor decompositions it has been observed numerically that, generally, this issue cannot be solved by consecutively computing and

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

    Science.gov (United States)

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

    2018-03-01

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

  17. 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.

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

    Science.gov (United States)

    Gallardo-Pujol, David; Andrés-Pueyo, Antonio

    2006-08-01

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

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

    Directory of Open Access Journals (Sweden)

    Marius-Corneliu Marinas

    2006-05-01

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

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

    Directory of Open Access Journals (Sweden)

    Marius-Corneliu Marinas

    2006-03-01

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

  1. Consistent ranking of volatility models

    DEFF Research Database (Denmark)

    Hansen, Peter Reinhard; Lunde, Asger

    2006-01-01

    We show that the empirical ranking of volatility models can be inconsistent for the true ranking if the evaluation is based on a proxy for the population measure of volatility. For example, the substitution of a squared return for the conditional variance in the evaluation of ARCH-type models can...... variance in out-of-sample evaluations rather than the squared return. We derive the theoretical results in a general framework that is not specific to the comparison of volatility models. Similar problems can arise in comparisons of forecasting models whenever the predicted variable is a latent variable....

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

    Science.gov (United States)

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

    2011-07-01

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

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

    Science.gov (United States)

    Scanlon, T. M.

    2008-12-01

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

  4. Development and first application of an operating events ranking tool

    International Nuclear Information System (INIS)

    Šimić, Zdenko; Zerger, Benoit; Banov, Reni

    2015-01-01

    Highlights: • A method using analitycal hierarchy process for ranking operating events is developed and tested. • The method is applied for 5 years of U.S. NRC Licensee Event Reports (1453 events). • Uncertainty and sensitivity of the ranking results are evaluated. • Real events assessment shows potential of the method for operating experience feedback. - Abstract: The operating experience feedback is important for maintaining and improving safety and availability in nuclear power plants. Detailed investigation of all events is challenging since it requires excessive resources, especially in case of large event databases. This paper presents an event groups ranking method to complement the analysis of individual operating events. The basis for the method is the use of an internationally accepted events characterization scheme that allows different ways of events grouping and ranking. The ranking method itself consists of implementing the analytical hierarchy process (AHP) by means of a custom developed tool which allows events ranking based on ranking indexes pre-determined by expert judgment. Following the development phase, the tool was applied to analyze a complete set of 5 years of real nuclear power plants operating events (1453 events). The paper presents the potential of this ranking method to identify possible patterns throughout the event database and therefore to give additional insights into the events as well as to give quantitative input for the prioritization of further more detailed investigation of selected event groups

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

    Indian Academy of Sciences (India)

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

  6. correlation studies and path coefficient analysis for seed yield

    African Journals Online (AJOL)

    Prof. Adipala Ekwamu

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

  7. 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.

  8. 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.

  9. Analysis of Correlations between the Level of Partnering Relations and their Influence on the Time, Cost, Quality and Safety of Implementation of Construction Projects

    Directory of Open Access Journals (Sweden)

    Radziszewska-Zielina Elżbieta

    2014-11-01

    Full Text Available The present paper uses the developed model of the influence of partnering relations on the time, cost, quality and safety of implementation of construction projects. On its basis, a questionnaire has been created and a preliminary survey has been conducted. The paper presents an analysis of correlations between the level of partnering relations in the context of the partnering measures indicated in the model and their influence on the time, cost, quality and safety of implementation of construction projects. The analysis was conducted based on the data collected in 52 construction projects. The values of the Spearman rank correlation coefficient and the Pearson product-moment correlation coefficient have been calculated for the examined relations. The analysis allowed for indicating the measures of partnering whose improvement most often brings benefits with regard to the time, cost, quality and safety of implementation of construction projects. Among the 80 analysed correlations, the ones identified as strong were: 15 relations connected with the time, 8 with the cost, 5 with the quality and 1 with the safety of implementation of construction projects.

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

    Science.gov (United States)

    Ruan, Qingsong; Yang, Bingchan

    2017-10-01

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

  11. Let Us Rank Journalism Programs

    Science.gov (United States)

    Weber, Joseph

    2014-01-01

    Unlike law, business, and medical schools, as well as universities in general, journalism schools and journalism programs have rarely been ranked. Publishers such as "U.S. News & World Report," "Forbes," "Bloomberg Businessweek," and "Washington Monthly" do not pay them much mind. What is the best…

  12. On Rank Driven Dynamical Systems

    Science.gov (United States)

    Veerman, J. J. P.; Prieto, F. J.

    2014-08-01

    We investigate a class of models related to the Bak-Sneppen (BS) model, initially proposed to study evolution. The BS model is extremely simple and yet captures some forms of "complex behavior" such as self-organized criticality that is often observed in physical and biological systems. In this model, random fitnesses in are associated to agents located at the vertices of a graph . Their fitnesses are ranked from worst (0) to best (1). At every time-step the agent with the worst fitness and some others with a priori given rank probabilities are replaced by new agents with random fitnesses. We consider two cases: The exogenous case where the new fitnesses are taken from an a priori fixed distribution, and the endogenous case where the new fitnesses are taken from the current distribution as it evolves. We approximate the dynamics by making a simplifying independence assumption. We use Order Statistics and Dynamical Systems to define a rank-driven dynamical system that approximates the evolution of the distribution of the fitnesses in these rank-driven models, as well as in the BS model. For this simplified model we can find the limiting marginal distribution as a function of the initial conditions. Agreement with experimental results of the BS model is excellent.

  13. Multiple graph regularized protein domain ranking

    KAUST Repository

    Wang, Jim Jing-Yan

    2012-11-19

    Background: Protein domain ranking is a fundamental task in structural biology. Most protein domain ranking methods rely on the pairwise comparison of protein domains while neglecting the global manifold structure of the protein domain database. Recently, graph regularized ranking that exploits the global structure of the graph defined by the pairwise similarities has been proposed. However, the existing graph regularized ranking methods are very sensitive to the choice of the graph model and parameters, and this remains a difficult problem for most of the protein domain ranking methods.Results: To tackle this problem, we have developed the Multiple Graph regularized Ranking algorithm, MultiG-Rank. Instead of using a single graph to regularize the ranking scores, MultiG-Rank approximates the intrinsic manifold of protein domain distribution by combining multiple initial graphs for the regularization. Graph weights are learned with ranking scores jointly and automatically, by alternately minimizing an objective function in an iterative algorithm. Experimental results on a subset of the ASTRAL SCOP protein domain database demonstrate that MultiG-Rank achieves a better ranking performance than single graph regularized ranking methods and pairwise similarity based ranking methods.Conclusion: The problem of graph model and parameter selection in graph regularized protein domain ranking can be solved effectively by combining multiple graphs. This aspect of generalization introduces a new frontier in applying multiple graphs to solving protein domain ranking applications. 2012 Wang et al; licensee BioMed Central Ltd.

  14. Multiple graph regularized protein domain ranking

    KAUST Repository

    Wang, Jim Jing-Yan; Bensmail, Halima; Gao, Xin

    2012-01-01

    Background: Protein domain ranking is a fundamental task in structural biology. Most protein domain ranking methods rely on the pairwise comparison of protein domains while neglecting the global manifold structure of the protein domain database. Recently, graph regularized ranking that exploits the global structure of the graph defined by the pairwise similarities has been proposed. However, the existing graph regularized ranking methods are very sensitive to the choice of the graph model and parameters, and this remains a difficult problem for most of the protein domain ranking methods.Results: To tackle this problem, we have developed the Multiple Graph regularized Ranking algorithm, MultiG-Rank. Instead of using a single graph to regularize the ranking scores, MultiG-Rank approximates the intrinsic manifold of protein domain distribution by combining multiple initial graphs for the regularization. Graph weights are learned with ranking scores jointly and automatically, by alternately minimizing an objective function in an iterative algorithm. Experimental results on a subset of the ASTRAL SCOP protein domain database demonstrate that MultiG-Rank achieves a better ranking performance than single graph regularized ranking methods and pairwise similarity based ranking methods.Conclusion: The problem of graph model and parameter selection in graph regularized protein domain ranking can be solved effectively by combining multiple graphs. This aspect of generalization introduces a new frontier in applying multiple graphs to solving protein domain ranking applications. 2012 Wang et al; licensee BioMed Central Ltd.

  15. 14 CFR 1214.1105 - Final ranking.

    Science.gov (United States)

    2010-01-01

    ... 14 Aeronautics and Space 5 2010-01-01 2010-01-01 false Final ranking. 1214.1105 Section 1214.1105... Recruitment and Selection Program § 1214.1105 Final ranking. Final rankings will be based on a combination of... preference will be included in this final ranking in accordance with applicable regulations. ...

  16. Multiple graph regularized protein domain ranking.

    Science.gov (United States)

    Wang, Jim Jing-Yan; Bensmail, Halima; Gao, Xin

    2012-11-19

    Protein domain ranking is a fundamental task in structural biology. Most protein domain ranking methods rely on the pairwise comparison of protein domains while neglecting the global manifold structure of the protein domain database. Recently, graph regularized ranking that exploits the global structure of the graph defined by the pairwise similarities has been proposed. However, the existing graph regularized ranking methods are very sensitive to the choice of the graph model and parameters, and this remains a difficult problem for most of the protein domain ranking methods. To tackle this problem, we have developed the Multiple Graph regularized Ranking algorithm, MultiG-Rank. Instead of using a single graph to regularize the ranking scores, MultiG-Rank approximates the intrinsic manifold of protein domain distribution by combining multiple initial graphs for the regularization. Graph weights are learned with ranking scores jointly and automatically, by alternately minimizing an objective function in an iterative algorithm. Experimental results on a subset of the ASTRAL SCOP protein domain database demonstrate that MultiG-Rank achieves a better ranking performance than single graph regularized ranking methods and pairwise similarity based ranking methods. The problem of graph model and parameter selection in graph regularized protein domain ranking can be solved effectively by combining multiple graphs. This aspect of generalization introduces a new frontier in applying multiple graphs to solving protein domain ranking applications.

  17. Multiple graph regularized protein domain ranking

    Directory of Open Access Journals (Sweden)

    Wang Jim

    2012-11-01

    Full Text Available Abstract Background Protein domain ranking is a fundamental task in structural biology. Most protein domain ranking methods rely on the pairwise comparison of protein domains while neglecting the global manifold structure of the protein domain database. Recently, graph regularized ranking that exploits the global structure of the graph defined by the pairwise similarities has been proposed. However, the existing graph regularized ranking methods are very sensitive to the choice of the graph model and parameters, and this remains a difficult problem for most of the protein domain ranking methods. Results To tackle this problem, we have developed the Multiple Graph regularized Ranking algorithm, MultiG-Rank. Instead of using a single graph to regularize the ranking scores, MultiG-Rank approximates the intrinsic manifold of protein domain distribution by combining multiple initial graphs for the regularization. Graph weights are learned with ranking scores jointly and automatically, by alternately minimizing an objective function in an iterative algorithm. Experimental results on a subset of the ASTRAL SCOP protein domain database demonstrate that MultiG-Rank achieves a better ranking performance than single graph regularized ranking methods and pairwise similarity based ranking methods. Conclusion The problem of graph model and parameter selection in graph regularized protein domain ranking can be solved effectively by combining multiple graphs. This aspect of generalization introduces a new frontier in applying multiple graphs to solving protein domain ranking applications.

  18. Diffusion of scientific credits and the ranking of scientists

    Science.gov (United States)

    Radicchi, Filippo; Fortunato, Santo; Markines, Benjamin; Vespignani, Alessandro

    2009-11-01

    Recently, the abundance of digital data is enabling the implementation of graph-based ranking algorithms that provide system level analysis for ranking publications and authors. Here, we take advantage of the entire Physical Review publication archive (1893-2006) to construct authors’ networks where weighted edges, as measured from opportunely normalized citation counts, define a proxy for the mechanism of scientific credit transfer. On this network, we define a ranking method based on a diffusion algorithm that mimics the spreading of scientific credits on the network. We compare the results obtained with our algorithm with those obtained by local measures such as the citation count and provide a statistical analysis of the assignment of major career awards in the area of physics. A website where the algorithm is made available to perform customized rank analysis can be found at the address http://www.physauthorsrank.org.

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

    African Journals Online (AJOL)

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

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

    Science.gov (United States)

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

    2010-12-20

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

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

    International Nuclear Information System (INIS)

    Clifton, P.M.

    1984-12-01

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

  2. A Survey on PageRank Computing

    OpenAIRE

    Berkhin, Pavel

    2005-01-01

    This survey reviews the research related to PageRank computing. Components of a PageRank vector serve as authority weights for web pages independent of their textual content, solely based on the hyperlink structure of the web. PageRank is typically used as a web search ranking component. This defines the importance of the model and the data structures that underly PageRank processing. Computing even a single PageRank is a difficult computational task. Computing many PageRanks is a much mor...

  3. Time evolution of Wikipedia network ranking

    Science.gov (United States)

    Eom, Young-Ho; Frahm, Klaus M.; Benczúr, András; Shepelyansky, Dima L.

    2013-12-01

    We study the time evolution of ranking and spectral properties of the Google matrix of English Wikipedia hyperlink network during years 2003-2011. The statistical properties of ranking of Wikipedia articles via PageRank and CheiRank probabilities, as well as the matrix spectrum, are shown to be stabilized for 2007-2011. A special emphasis is done on ranking of Wikipedia personalities and universities. We show that PageRank selection is dominated by politicians while 2DRank, which combines PageRank and CheiRank, gives more accent on personalities of arts. The Wikipedia PageRank of universities recovers 80% of top universities of Shanghai ranking during the considered time period.

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

    International Nuclear Information System (INIS)

    Uehara, Sandro Toshio

    2009-01-01

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

  5. Analysis of three particle correlations with the INDRA detector

    International Nuclear Information System (INIS)

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

    1997-01-01

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

  6. The application of low-rank and sparse decomposition method in the field of climatology

    Science.gov (United States)

    Gupta, Nitika; Bhaskaran, Prasad K.

    2018-04-01

    The present study reports a low-rank and sparse decomposition method that separates the mean and the variability of a climate data field. Until now, the application of this technique was limited only in areas such as image processing, web data ranking, and bioinformatics data analysis. In climate science, this method exactly separates the original data into a set of low-rank and sparse components, wherein the low-rank components depict the linearly correlated dataset (expected or mean behavior), and the sparse component represents the variation or perturbation in the dataset from its mean behavior. The study attempts to verify the efficacy of this proposed technique in the field of climatology with two examples of real world. The first example attempts this technique on the maximum wind-speed (MWS) data for the Indian Ocean (IO) region. The study brings to light a decadal reversal pattern in the MWS for the North Indian Ocean (NIO) during the months of June, July, and August (JJA). The second example deals with the sea surface temperature (SST) data for the Bay of Bengal region that exhibits a distinct pattern in the sparse component. The study highlights the importance of the proposed technique used for interpretation and visualization of climate data.

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

    International Nuclear Information System (INIS)

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

    1995-01-01

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

  8. Ranking agility factors affecting hospitals in Iran

    Directory of Open Access Journals (Sweden)

    M. Abdi Talarposht

    2017-04-01

    Full Text Available Background: Agility is an effective response to the changing and unpredictable environment and using these changes as opportunities for organizational improvement. Objective: The aim of the present study was to rank the factors affecting agile supply chain of hospitals of Iran. Methods: This applied study was conducted by cross sectional-descriptive method at some point of 2015 for one year. The research population included managers, administrators, faculty members and experts were selected hospitals. A total of 260 people were selected as sample from the health centers. The construct validity of the questionnaire was approved by confirmatory factor analysis test and its reliability was approved by Cronbach's alpha (α=0.97. All data were analyzed by Kolmogorov-Smirnov, Chi-square and Friedman tests. Findings: The development of staff skills, the use of information technology, the integration of processes, appropriate planning, and customer satisfaction and product quality had a significant impact on the agility of public hospitals of Iran (P<0.001. New product introductions had earned the highest ranking and the development of staff skills earned the lowest ranking. Conclusion: The new product introduction, market responsiveness and sensitivity, reduce costs, and the integration of organizational processes, ratings better to have acquired agility hospitals in Iran. Therefore, planners and officials of hospitals have to, through the promotion quality and variety of services customer-oriented, providing a basis for investing in the hospital and etc to apply for agility supply chain public hospitals of Iran.

  9. NDVI and Panchromatic Image Correlation Using Texture Analysis

    Science.gov (United States)

    2010-03-01

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

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

    International Nuclear Information System (INIS)

    Kashiwase, Takako; Nagasaka, Hideo

    2000-01-01

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

  11. Dual channel rank-based intensity weighting for quantitative co-localization of microscopy images

    LENUS (Irish Health Repository)

    Singan, Vasanth R

    2011-10-21

    Abstract Background Accurate quantitative co-localization is a key parameter in the context of understanding the spatial co-ordination of molecules and therefore their function in cells. Existing co-localization algorithms consider either the presence of co-occurring pixels or correlations of intensity in regions of interest. Depending on the image source, and the algorithm selected, the co-localization coefficients determined can be highly variable, and often inaccurate. Furthermore, this choice of whether co-occurrence or correlation is the best approach for quantifying co-localization remains controversial. Results We have developed a novel algorithm to quantify co-localization that improves on and addresses the major shortcomings of existing co-localization measures. This algorithm uses a non-parametric ranking of pixel intensities in each channel, and the difference in ranks of co-localizing pixel positions in the two channels is used to weight the coefficient. This weighting is applied to co-occurring pixels thereby efficiently combining both co-occurrence and correlation. Tests with synthetic data sets show that the algorithm is sensitive to both co-occurrence and correlation at varying levels of intensity. Analysis of biological data sets demonstrate that this new algorithm offers high sensitivity, and that it is capable of detecting subtle changes in co-localization, exemplified by studies on a well characterized cargo protein that moves through the secretory pathway of cells. Conclusions This algorithm provides a novel way to efficiently combine co-occurrence and correlation components in biological images, thereby generating an accurate measure of co-localization. This approach of rank weighting of intensities also eliminates the need for manual thresholding of the image, which is often a cause of error in co-localization quantification. We envisage that this tool will facilitate the quantitative analysis of a wide range of biological data sets

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

    International Nuclear Information System (INIS)

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

    2015-01-01

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

  13. Decomposition of the Google PageRank and Optimal Linking Strategy

    NARCIS (Netherlands)

    Avrachenkov, Konstatin; Litvak, Nelli

    We provide the analysis of the Google PageRank from the perspective of the Markov Chain Theory. First we study the Google PageRank for a Web that can be decomposed into several connected components which do not have any links to each other. We show that in order to determine the Google PageRank for

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

    Science.gov (United States)

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

    2018-06-01

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

  15. DNA microarray data and contextual analysis of correlation graphs

    Directory of Open Access Journals (Sweden)

    Hingamp Pascal

    2003-04-01

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

  16. RUSSIAN UNIVERSITIES IN THE LOOP OF THE WORLD EDUCATION RANKINGS

    Directory of Open Access Journals (Sweden)

    Екатерина Сергеевна Иноземцева

    2013-04-01

    Full Text Available Purpose: a research on different sociological and economic aspects of world education rankings (THE, ARWU, QS, evaluation of their role and impact on the world education market’s main consumers (i.e. students and academic staff as a subject to discussion in terms of the customers’ preferences and choice motivators.  Methodology: general scientific research tools were applied throughout the research: analysis, synthesis, deduction.Results: world ranking approach and methodology was assessed, defined and systemized, a unique general ranking of the countries was developed and performed (based on the researched body – the US ranked #1, Russia #30, expert recommendations for Russian universities have been developed and concluded.Practical implications: the main statements could be used within learning courses on the internationalization of higher education and applied in sociological and economic research dedicated to macroeconomic problems and issues analysis.DOI: http://dx.doi.org/10.12731/2218-7405-2013-2-18

  17. RUSSIAN UNIVERSITIES IN THE LOOP OF THE WORLD EDUCATION RANKINGS

    Directory of Open Access Journals (Sweden)

    Inozemtseva Ekaterina Sergeevna

    2013-02-01

    Full Text Available Purpose: a research on different sociological and economic aspects of world education rankings (THE, ARWU, QS, evaluation of their role and impact on the world education market’s main consumers (i.e. students and academic staff as a subject to discussion in terms of the customers’ preferences and choice motivators. Methodology: general scientific research tools were applied throughout the research: analysis, synthesis, deduction. Results: world ranking approach and methodology was assessed, defined and systemized, a unique general ranking of the countries was developed and performed (based on the researched body – the US ranked #1, Russia #30, expert recommendations for Russian universities have been developed and concluded. Practical implications: the main statements could be used within learning courses on the internationalization of higher education and applied in sociological and economic research dedicated to macroeconomic problems and issues analysis.

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

    Science.gov (United States)

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

    2018-03-01

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

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

    Science.gov (United States)

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

    2014-12-01

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

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

    Science.gov (United States)

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

    2008-06-18

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