The Marketing of Canadian University Rankings: A Misadventure Now 24 Years Old

Science.gov (United States)

Cramer, Kenneth M.; Page, Stewart; Burrows, Vanessa; Lamoureux, Chastine; Mackay, Sarah; Pedri, Victoria; Pschibul, Rebecca

2016-01-01

Based on analyses of Maclean's ranking data pertaining to Canadian universities published over the last 24 years, we present a summary of statistical findings of annual ranking exercises, as well as discussion about their current status and the effects upon student welfare. Some illustrative tables are also presented. Using correlational and…

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.

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;

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.

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.

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

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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

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.

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.

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.

Low-rank coal study. Volume 4. Regulatory, environmental, and market analyses

Energy Technology Data Exchange (ETDEWEB)

1980-11-01

The regulatory, environmental, and market constraints to development of US low-rank coal resources are analyzed. Government-imposed environmental and regulatory requirements are among the most important factors that determine the markets for low-rank coal and the technology used in the extraction, delivery, and utilization systems. Both state and federal controls are examined, in light of available data on impacts and effluents associated with major low-rank coal development efforts. The market analysis examines both the penetration of existing markets by low-rank coal and the evolution of potential markets in the future. The electric utility industry consumes about 99 percent of the total low-rank coal production. This use in utility boilers rose dramatically in the 1970's and is expected to continue to grow rapidly. In the late 1980's and 1990's, industrial direct use of low-rank coal and the production of synthetic fuels are expected to start growing as major new markets.

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.

Disentangling the effects of forage, social rank, and risk on movement autocorrelation of elephants using Fourier and wavelet analyses.

Science.gov (United States)

Wittemyer, George; Polansky, Leo; Douglas-Hamilton, Iain; Getz, Wayne M

2008-12-09

The internal state of an individual-as it relates to thirst, hunger, fear, or reproductive drive-can be inferred by referencing points on its movement path to external environmental and sociological variables. Using time-series approaches to characterize autocorrelative properties of step-length movements collated every 3 h for seven free-ranging African elephants, we examined the influence of social rank, predation risk, and seasonal variation in resource abundance on periodic properties of movement. The frequency domain methods of Fourier and wavelet analyses provide compact summaries of temporal autocorrelation and show both strong diurnal and seasonal based periodicities in the step-length time series. This autocorrelation is weaker during the wet season, indicating random movements are more common when ecological conditions are good. Periodograms of socially dominant individuals are consistent across seasons, whereas subordinate individuals show distinct differences diverging from that of dominants during the dry season. We link temporally localized statistical properties of movement to landscape features and find that diurnal movement correlation is more common within protected wildlife areas, and multiday movement correlations found among lower ranked individuals are typically outside of protected areas where predation risks are greatest. A frequency-related spatial analysis of movement-step lengths reveal that rest cycles related to the spatial distribution of critical resources (i.e., forage and water) are responsible for creating the observed patterns. Our approach generates unique information regarding the spatial-temporal interplay between environmental and individual characteristics, providing an original approach for understanding the movement ecology of individual animals and the spatial organization of animal populations.

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.

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.

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.

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.

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.

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

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.

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.

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.

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.

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

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

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.

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.

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.

Evaluation of the osteoclastogenic process associated with RANK / RANK-L / OPG in odontogenic myxomas

Science.gov (United States)

González-Galván, María del Carmen; Mosqueda-Taylor, Adalberto; Bologna-Molina, Ronell; Setien-Olarra, Amaia; Marichalar-Mendia, Xabier; Aguirre-Urizar, José-Manuel

2018-01-01

Background Odontogenic myxoma (OM) is a benign intraosseous neoplasm that exhibits local aggressiveness and high recurrence rates. Osteoclastogenesis is an important phenomenon in the tumor growth of maxillary neoplasms. RANK (Receptor Activator of Nuclear Factor κappa B) is the signaling receptor of RANK-L (Receptor activator of nuclear factor kappa-Β ligand) that activates the osteoclasts. OPG (osteoprotegerin) is a decoy receptor for RANK-L that inhibits pro-osteoclastogenesis. The RANK / RANKL / OPG system participates in the regulation of osteolytic activity under normal conditions, and its alteration has been associated with greater bone destruction, and also with tumor growth. Objectives To analyze the immunohistochemical expression of OPG, RANK and RANK-L proteins in odontogenic myxomas (OMs) and their relationship with the tumor size. Material and Methods Eighteen OMs, 4 small ( 3cm) and 18 dental follicles (DF) that were included as control were studied by means of standard immunohistochemical procedure with RANK, RANKL and OPG antibodies. For the evaluation, 5 fields (40x) of representative areas of OM and DF were selected where the expression of each antibody was determined. Descriptive and comparative statistical analyses were performed with the obtained data. Results There are significant differences in the expression of RANK in OM samples as compared to DF (p = 0.022) and among the OMSs and OMLs (p = 0.032). Also a strong association is recognized in the expression of RANK-L and OPG in OM samples. Conclusions Activation of the RANK / RANK-L / OPG triad seems to be involved in the mechanisms of bone balance and destruction, as well as associated with tumor growth in odontogenic myxomas. Key words:Odontogenic myxoma, dental follicle, RANK, RANK-L, OPG, osteoclastogenesis. PMID:29680857

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

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

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.

Does resident ranking during recruitment accurately predict subsequent performance as a surgical resident?

Science.gov (United States)

Fryer, Jonathan P; Corcoran, Noreen; George, Brian; Wang, Ed; Darosa, Debra

2012-01-01

While the primary goal of ranking applicants for surgical residency training positions is to identify the candidates who will subsequently perform best as surgical residents, the effectiveness of the ranking process has not been adequately studied. We evaluated our general surgery resident recruitment process between 2001 and 2011 inclusive, to determine if our recruitment ranking parameters effectively predicted subsequent resident performance. We identified 3 candidate ranking parameters (United States Medical Licensing Examination [USMLE] Step 1 score, unadjusted ranking score [URS], and final adjusted ranking [FAR]), and 4 resident performance parameters (American Board of Surgery In-Training Examination [ABSITE] score, PGY1 resident evaluation grade [REG], overall REG, and independent faculty rating ranking [IFRR]), and assessed whether the former were predictive of the latter. Analyses utilized Spearman correlation coefficient. We found that the URS, which is based on objective and criterion based parameters, was a better predictor of subsequent performance than the FAR, which is a modification of the URS based on subsequent determinations of the resident selection committee. USMLE score was a reliable predictor of ABSITE scores only. However, when we compared our worst residence performances with the performances of the other residents in this evaluation, the data did not produce convincing evidence that poor resident performances could be reliably predicted by any of the recruitment ranking parameters. Finally, stratifying candidates based on their rank range did not effectively define a ranking cut-off beyond which resident performance would drop off. Based on these findings, we recommend surgery programs may be better served by utilizing a more structured resident ranking process and that subsequent adjustments to the rank list generated by this process should be undertaken with caution. Copyright © 2012 Association of Program Directors in Surgery

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

Science.gov (United States)

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

2009-11-01

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

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.

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.

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.

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.

A Citation-Based Ranking of Strategic Management Journals

OpenAIRE

Azar, Ofer H.; Brock, David M.

2007-01-01

Rankings of strategy journals are important for authors, readers, and promotion and tenure committees. We present several rankings, based either on the number of articles that cited the journal or the per-article impact. Our analyses cover various periods between 1991 and 2006, for most of which the Strategic Management Journal was in first place and Journal of Economics & Management Strategy (JEMS) second, although JEMS ranked first in certain instances. Long Range Planning and Technology An...

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 ...

Application of digital-image-correlation techniques in analysing ...

Indian Academy of Sciences (India)

Basis theory of strain analysis using the digital image correlation method .... Type 304N Stainless Steel (Modulus of Elasticity = 193 MPa, Tensile Yield .... also proves the accuracy of the qualitative analyses by using the DIC ... We thank the National Science Council of Taiwan for supporting this research through grant. No.

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...

Control by Numbers: New Managerialism and Ranking in Higher Education

Science.gov (United States)

Lynch, Kathleen

2015-01-01

This paper analyses the role of rankings as an instrument of new managerialism. It shows how rankings are reconstituting the purpose of universities, the role of academics and the definition of what it is to be a student. The paper opens by examining the forces that have facilitated the emergence of the ranking industry and the ideologies…

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...

Influence of rank and macerals on the burnout behaviour of pulverized Indian coal

Energy Technology Data Exchange (ETDEWEB)

Choudhury, Nandita; Biswas, S.; Sarkar, P.; Kumar, Manish; Mukherjee, A.; Choudhury, A. [Central Institute of Mining and Fuel Research, Digwadih Campus (Formerly Central Fuel Research Institute), P.O. FRI, Dhanbad-828 108, Jharkhand (India); Ghosal, Sujit; Mitra, Tandra [Jadavpur University, Kolkata-700 032, West Bengal (India)

2008-04-03

The combustion behaviour of coal is significantly influenced by its rank and maceral and microlithotype compositions. Different macerals, due to their distinct and unique physical properties and chemical makeup, have different burning characteristics. This paper deals with the burning behaviour of coals of Indian origin by thermo gravimetric analysis (TGA) and in drop tube furnace (DTF) with particular emphasis on the role of macerals and their associations. Four coals of different rank and petrographic makeup, along with their two density fractions, with enriched vitrinite and inertinites, respectively,were studied in both TGA and DTF. The burnout behaviour was estimated from the chemical analyses of the char samples collected from the DTF. The burning characteristics of one of the coals deviate from the trend expected with the variations of rank. The behaviour of the density fractions in DTF was found to be different from that observed in TGA analyses. An attempt has been made to correlate the burnout with the petrographic macerals and microlithotypes present in the coals. The morphology of the residual chars indicates the contributions of the inertinites towards the formation of cenospheres and network types of reactive chars. The superior burning behaviour of the higher density inertinite-rich fractions over the raw coals and also some vitrinite-rich fractions indicate the better reactivity of the inertinites towards combustion. (author)

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...

Application of digital image correlation method for analysing crack ...

Indian Academy of Sciences (India)

centrated strain by imitating the treatment of micro-cracks using the finite element ... water and moisture to penetrate the concrete leading to serious rust of the ... The correlations among various grey values of digital images are analysed for ...

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.

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.

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

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.

Model assessment using a multi-metric ranking technique

Science.gov (United States)

Fitzpatrick, P. J.; Lau, Y.; Alaka, G.; Marks, F.

2017-12-01

Validation comparisons of multiple models presents challenges when skill levels are similar, especially in regimes dominated by the climatological mean. Assessing skill separation will require advanced validation metrics and identifying adeptness in extreme events, but maintain simplicity for management decisions. Flexibility for operations is also an asset. This work postulates a weighted tally and consolidation technique which ranks results by multiple types of metrics. Variables include absolute error, bias, acceptable absolute error percentages, outlier metrics, model efficiency, Pearson correlation, Kendall's Tau, reliability Index, multiplicative gross error, and root mean squared differences. Other metrics, such as root mean square difference and rank correlation were also explored, but removed when the information was discovered to be generally duplicative to other metrics. While equal weights are applied, weights could be altered depending for preferred metrics. Two examples are shown comparing ocean models' currents and tropical cyclone products, including experimental products. The importance of using magnitude and direction for tropical cyclone track forecasts instead of distance, along-track, and cross-track are discussed. Tropical cyclone intensity and structure prediction are also assessed. Vector correlations are not included in the ranking process, but found useful in an independent context, and will be briefly reported.

Semiparametric Gaussian copula models : Geometry and efficient rank-based estimation

NARCIS (Netherlands)

Segers, J.; van den Akker, R.; Werker, B.J.M.

2014-01-01

We propose, for multivariate Gaussian copula models with unknown margins and structured correlation matrices, a rank-based, semiparametrically efficient estimator for the Euclidean copula parameter. This estimator is defined as a one-step update of a rank-based pilot estimator in the direction of

Fair ranking of researchers and research teams.

Science.gov (United States)

Vavryčuk, Václav

2018-01-01

The main drawback of ranking of researchers by the number of papers, citations or by the Hirsch index is ignoring the problem of distributing authorship among authors in multi-author publications. So far, the single-author or multi-author publications contribute to the publication record of a researcher equally. This full counting scheme is apparently unfair and causes unjust disproportions, in particular, if ranked researchers have distinctly different collaboration profiles. These disproportions are removed by less common fractional or authorship-weighted counting schemes, which can distribute the authorship credit more properly and suppress a tendency to unjustified inflation of co-authors. The urgent need of widely adopting a fair ranking scheme in practise is exemplified by analysing citation profiles of several highly-cited astronomers and astrophysicists. While the full counting scheme often leads to completely incorrect and misleading ranking, the fractional or authorship-weighted schemes are more accurate and applicable to ranking of researchers as well as research teams. In addition, they suppress differences in ranking among scientific disciplines. These more appropriate schemes should urgently be adopted by scientific publication databases as the Web of Science (Thomson Reuters) or the Scopus (Elsevier).

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

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.

The THE-QS World University Rankings, 2004 – 2009

Directory of Open Access Journals (Sweden)

Richard Holmes

2010-06-01

Full Text Available This paper reviews the origin, development and demise of the Times Higher Education Supplement (now Times Higher Education – QS Quacquarelli Symonds (QS World University Rankings between 2004 and 2009. It describes the structure and methodology of the rankings, their public impact and various criticisms that have been made. It also analyses changes that were introduced between 2005 and 2009 and concludes by noting the development of two distinct ranking systems by the magazine Times Higher Education (THE and by its former partner, the consulting company Quacquarelli Symonds.

International Conference on Robust Rank-Based and Nonparametric Methods

CERN Document Server

McKean, Joseph

2016-01-01

The contributors to this volume include many of the distinguished researchers in this area. Many of these scholars have collaborated with Joseph McKean to develop underlying theory for these methods, obtain small sample corrections, and develop efficient algorithms for their computation. The papers cover the scope of the area, including robust nonparametric rank-based procedures through Bayesian and big data rank-based analyses. Areas of application include biostatistics and spatial areas. Over the last 30 years, robust rank-based and nonparametric methods have developed considerably. These procedures generalize traditional Wilcoxon-type methods for one- and two-sample location problems. Research into these procedures has culminated in complete analyses for many of the models used in practice including linear, generalized linear, mixed, and nonlinear models. Settings are both multivariate and univariate. With the development of R packages in these areas, computation of these procedures is easily shared with r...

Comparing the rankings obtained from two biodiversity indices: the Fair Proportion Index and the Shapley Value.

Science.gov (United States)

Wicke, Kristina; Fischer, Mareike

2017-10-07

The Shapley Value and the Fair Proportion Index of phylogenetic trees have been frequently discussed as prioritization tools in conservation biology. Both indices rank species according to their contribution to total phylogenetic diversity, allowing for a simple conservation criterion. While both indices have their specific advantages and drawbacks, it has recently been shown that both values are closely related. However, as different authors use different definitions of the Shapley Value, the specific degree of relatedness depends on the specific version of the Shapley Value - it ranges from a high correlation index to equality of the indices. In this note, we first give an overview of the different indices. Then we turn our attention to the mere ranking order provided by either of the indices. We compare the rankings obtained from different versions of the Shapley Value for a phylogenetic tree of European amphibians and illustrate their differences. We then undertake further analyses on simulated data and show that even though the chance of two rankings being exactly identical (when obtained from different versions of the Shapley Value) decreases with an increasing number of taxa, the distance between the two rankings converges to zero, i.e., the rankings are becoming more and more alike. Moreover, we introduce our freely available software package FairShapley, which was implemented in Perl and with which all calculations have been performed. Copyright © 2017 Elsevier Ltd. All rights reserved.

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.

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

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.

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.

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.

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

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.

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

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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.

RankProdIt: A web-interactive Rank Products analysis tool

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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

RankExplorer: Visualization of Ranking Changes in Large Time Series Data.

Science.gov (United States)

Shi, Conglei; Cui, Weiwei; Liu, Shixia; Xu, Panpan; Chen, Wei; Qu, Huamin

2012-12-01

For many applications involving time series data, people are often interested in the changes of item values over time as well as their ranking changes. For example, people search many words via search engines like Google and Bing every day. Analysts are interested in both the absolute searching number for each word as well as their relative rankings. Both sets of statistics may change over time. For very large time series data with thousands of items, how to visually present ranking changes is an interesting challenge. In this paper, we propose RankExplorer, a novel visualization method based on ThemeRiver to reveal the ranking changes. Our method consists of four major components: 1) a segmentation method which partitions a large set of time series curves into a manageable number of ranking categories; 2) an extended ThemeRiver view with embedded color bars and changing glyphs to show the evolution of aggregation values related to each ranking category over time as well as the content changes in each ranking category; 3) a trend curve to show the degree of ranking changes over time; 4) rich user interactions to support interactive exploration of ranking changes. We have applied our method to some real time series data and the case studies demonstrate that our method can reveal the underlying patterns related to ranking changes which might otherwise be obscured in traditional visualizations.

Reconsidering the use of rankings in the valuation of health states: a model for estimating cardinal values from ordinal data

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Salomon Joshua A

2003-12-01

Full Text Available Abstract Background In survey studies on health-state valuations, ordinal ranking exercises often are used as precursors to other elicitation methods such as the time trade-off (TTO or standard gamble, but the ranking data have not been used in deriving cardinal valuations. This study reconsiders the role of ordinal ranks in valuing health and introduces a new approach to estimate interval-scaled valuations based on aggregate ranking data. Methods Analyses were undertaken on data from a previously published general population survey study in the United Kingdom that included rankings and TTO values for hypothetical states described using the EQ-5D classification system. The EQ-5D includes five domains (mobility, self-care, usual activities, pain/discomfort and anxiety/depression with three possible levels on each. Rank data were analysed using a random utility model, operationalized through conditional logit regression. In the statistical model, probabilities of observed rankings were related to the latent utilities of different health states, modeled as a linear function of EQ-5D domain scores, as in previously reported EQ-5D valuation functions. Predicted valuations based on the conditional logit model were compared to observed TTO values for the 42 states in the study and to predictions based on a model estimated directly from the TTO values. Models were evaluated using the intraclass correlation coefficient (ICC between predictions and mean observations, and the root mean squared error of predictions at the individual level. Results Agreement between predicted valuations from the rank model and observed TTO values was very high, with an ICC of 0.97, only marginally lower than for predictions based on the model estimated directly from TTO values (ICC = 0.99. Individual-level errors were also comparable in the two models, with root mean squared errors of 0.503 and 0.496 for the rank-based and TTO-based predictions, respectively. Conclusions

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.

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).…

ATTITUDES OF FOOTBALL PLAYERS OF DIFFERENT RANKS TOWARDS TRAINING EXERCISES OF RECOVERY

Directory of Open Access Journals (Sweden)

Slavko Molnar

2009-11-01

Full Text Available Training exercises of recovery of sportsmen include both exercises implying hig- her level of training and exercises of optimal recovery of sportsmen. In order to use training exercises of recovery best way it is necessary to know how they react to the body of a sportsman concerning their character and length. It is also necessary to take into consideration the fact that human body adapts equally both to burden and adequ- ate recovery exercises. To increase the efficiency of training exercises of recovery it is inevitable to use different exercises and methods changing their use, that is, they should be applied in a complex way considering their change depending on sport activities and structure of training process. The aim of the study is to check and analyse attitudes of fooyball players of different ranks towards training exercises of recovery. The sample of examinees consists of 120 footballers of different ranks (super league of Serbia = 43, the first league of Serbia = 40 and Serbian league = 37. The sample of variables consists of the system of 10 attitudes (claims, and each attitude (claim consists of 5 verbal ca- tegories (marked from -2 to +2. To determine multivariate and univariate significance of differences between footballers of different competition ranks multivariate analysis of variance (MANOVA and univariate analysis of variance (ANOVA have been ap- plied. Concerning the attitudes of training exercises of recovery statistically significant differences were got between the groups where 7 out of 10 attitudes were different. Con- cerning the correlation two types of attitudes were noticed. Footballers of different competition ranks do not have the same attitudes towards training exercises of recovery.

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

. Facial attractiveness: ranking of end-of-treatment facial photographs by pairs of Chinese and US orthodontists.

Science.gov (United States)

Xu, Tian-Min; Korn, Edward L; Liu, Yan; Oh, Hee Soo; Lee, Ki Heon; Boyd, Robert L; Baumrind, Sheldon

2008-07-01

In this study, we assessed agreement and disagreement among pairs of Chinese and US orthodontists in the ranking for "facial attractiveness" of end-of-treatment photographs of growing Chinese and white orthodontic patients. Two groups of orthodontist-judges participated: from the University of the Pacific, School of Dentistry, in California and from Peking University School and Hospital of Stomatology in China. Each judge independently ranked standard clinical sets of profile, frontal, and frontal-smiling photographs of 43 white patients and 48 Chinese patients. Pearson correlations were generated for a total of 1980 rankings by pairs of judges. The resulting correlations ranged from +0.004 to +0.96 with a median of +0.54. Of these, 18.7% were lower than 0.4; 41.0% were lower than 0.5; 68.8% were lower than 0.6; 91.6% were lower than 0.7; and only 8.4% were greater than 0.7. As had been anticipated, correlations between judges were higher when they ranked patients of their own ethnicity than when they ranked patients of different ethnicity, but the differences were smaller than had been expected. The rankings of no pair of judges correlated negatively. This is to say that no pair of judges, whether of the same or different ethnicity, ranked the patients so that those 1 judge tended to find attractive were consistently found unattractive by the other. The distribution of levels of agreement between pairs of orthodontists did not differ substantially whether the pairs included 2 US orthodontists, 2 Chinese orthodontists, or 1 US and 1 Chinese orthodontist. As might be expected, the pairs of Chinese orthodontists agreed with each other slightly better on average when ranking Chinese patients, and the pairs of US orthodontists agreed with each other slightly better on average when ranking white American patients, but the overall differences were small. These findings appear consistent with the inference that, on average, judgments of "facial attractiveness" by

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.

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.

Importance of neutralization sieve analyses when seeking correlates of HIV-1 vaccine efficacy.

Science.gov (United States)

Montefiori, David C

2014-01-01

This commentary describes a rationale for the use of breakthrough viruses from clinical trial participants to assess neutralizing antibodies as a correlate of HIV-1 vaccine efficacy. The rationale is based on principles of a genetic sieve analysis, where the 2 analyses may be cooperative for delineating neutralizing antibodies as a mechanistic correlate of protection.

RANK/RANK-Ligand/OPG: Ein neuer Therapieansatz in der Osteoporosebehandlung

Directory of Open Access Journals (Sweden)

Preisinger E

2007-01-01

Full Text Available Die Erforschung der Kopplungsmechanismen zur Osteoklastogenese, Knochenresorption und Remodellierung eröffnete neue mögliche Therapieansätze in der Behandlung der Osteoporose. Eine Schlüsselrolle beim Knochenabbau spielt der RANK- ("receptor activator of nuclear factor (NF- κB"- Ligand (RANKL. Durch die Bindung von RANKL an den Rezeptor RANK wird die Knochenresorption eingeleitet. OPG (Osteoprotegerin sowie der für den klinischen Gebrauch entwickelte humane monoklonale Antikörper (IgG2 Denosumab blockieren die Bindung von RANK-Ligand an RANK und verhindern den Knochenabbau.

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....

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.

Zeolite facies and regional rank of bituminous coals

Energy Technology Data Exchange (ETDEWEB)

Kisch, H J

1966-01-01

The author has correlated diagnostic analcime-, heulandite-, and laumontite-bearing mineral assemblages from four areas in the Upper Carboniferous and the Permian of New South Wales with the rank of the associated coals, represented by the carbon content of vitrinite. The results show that lowest-grade regional metamorphism of the zeolite facies reflects at least in part the same physical conditions of metamorphism as the increase in degree of coalification (rank) in the bituminous coal range. Degree of coalification is probably independent of partial pressures of H/sub 2/O and CO/sub 2/: it is controlled mainly by maximum depth of burial, its duration, and the geothermal gradient.

A human fecal contamination index for ranking impaired ...

Science.gov (United States)

Human fecal pollution of surface water remains a public health concern worldwide. As a result, there is a growing interest in the application of human-associated fecal source identification quantitative real-time PCR (qPCR) technologies for recreational water quality risk management. The transition from a research subject to a management tool requires the integration of standardized water sampling, laboratory, and data analysis procedures. In this study, a standardized HF183/BacR287 qPCR method was combined with a water sampling strategy and Bayesian data algorithm to establish a human fecal contamination index that can be used to rank impaired recreational water sites polluted with human waste. Stability and bias of index predictions were investigated under various parameters including siteswith different pollution levels, sampling period time range (1-15 weeks), and number of qPCR replicates per sample (2-14 replicates). Sensitivity analyses were conducted with simulated data sets (100 iterations) seeded with HF183/BacR287 qPCR laboratory measurements from water samples collected from three Southern California sites (588 qPCR measurements). Findings suggest that site ranking is feasible and that all parameters tested influence stability and bias in human fecal contamination indexscoring. Trends identified by sensitivity analyses will provide managers with the information needed to design and conduct field studies to rank impaired recreational water sites based

bc-GenExMiner 3.0: new mining module computes breast cancer gene expression correlation analyses.

Science.gov (United States)

Jézéquel, Pascal; Frénel, Jean-Sébastien; Campion, Loïc; Guérin-Charbonnel, Catherine; Gouraud, Wilfried; Ricolleau, Gabriel; Campone, Mario

2013-01-01

We recently developed a user-friendly web-based application called bc-GenExMiner (http://bcgenex.centregauducheau.fr), which offered the possibility to evaluate prognostic informativity of genes in breast cancer by means of a 'prognostic module'. In this study, we develop a new module called 'correlation module', which includes three kinds of gene expression correlation analyses. The first one computes correlation coefficient between 2 or more (up to 10) chosen genes. The second one produces two lists of genes that are most correlated (positively and negatively) to a 'tested' gene. A gene ontology (GO) mining function is also proposed to explore GO 'biological process', 'molecular function' and 'cellular component' terms enrichment for the output lists of most correlated genes. The third one explores gene expression correlation between the 15 telomeric and 15 centromeric genes surrounding a 'tested' gene. These correlation analyses can be performed in different groups of patients: all patients (without any subtyping), in molecular subtypes (basal-like, HER2+, luminal A and luminal B) and according to oestrogen receptor status. Validation tests based on published data showed that these automatized analyses lead to results consistent with studies' conclusions. In brief, this new module has been developed to help basic researchers explore molecular mechanisms of breast cancer. DATABASE URL: http://bcgenex.centregauducheau.fr

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.

A New Direction of Cancer Classification: Positive Effect of Low-Ranking MicroRNAs.

Science.gov (United States)

Li, Feifei; Piao, Minghao; Piao, Yongjun; Li, Meijing; Ryu, Keun Ho

2014-10-01

Many studies based on microRNA (miRNA) expression profiles showed a new aspect of cancer classification. Because one characteristic of miRNA expression data is the high dimensionality, feature selection methods have been used to facilitate dimensionality reduction. The feature selection methods have one shortcoming thus far: they just consider the problem of where feature to class is 1:1 or n:1. However, because one miRNA may influence more than one type of cancer, human miRNA is considered to be ranked low in traditional feature selection methods and are removed most of the time. In view of the limitation of the miRNA number, low-ranking miRNAs are also important to cancer classification. We considered both high- and low-ranking features to cover all problems (1:1, n:1, 1:n, and m:n) in cancer classification. First, we used the correlation-based feature selection method to select the high-ranking miRNAs, and chose the support vector machine, Bayes network, decision tree, k-nearest-neighbor, and logistic classifier to construct cancer classification. Then, we chose Chi-square test, information gain, gain ratio, and Pearson's correlation feature selection methods to build the m:n feature subset, and used the selected miRNAs to determine cancer classification. The low-ranking miRNA expression profiles achieved higher classification accuracy compared with just using high-ranking miRNAs in traditional feature selection methods. Our results demonstrate that the m:n feature subset made a positive impression of low-ranking miRNAs in cancer classification.

"Times Higher Education" 100 under 50 Ranking: Old Wine in a New Bottle?

Science.gov (United States)

Soh, Kaycheng

2013-01-01

"Times Higher Education" 100 under 50 ranking is a new twist to the university ranking. It focuses on universities that have a history of 50 years or less with the purpose of offsetting the advantage of prestige of the older ones. This article re-analysed the data publicly available and looked into relevant conceptual and statistical issues. The…

Tracking and fixed ranking of leukocyte telomere length across the adult life course

DEFF Research Database (Denmark)

Benetos, Athanase; Kark, Jeremy D; Susser, Ezra

2013-01-01

whether age-dependent LTL attrition during adulthood can substantially affect individuals' LTL ranking (e.g., longer or shorter LTL) in relation to their peers. We measured LTL in samples donated 12 years apart on average by 1156 participants in four longitudinal studies. We observed correlations of 0.......91-0.96 between baseline and follow-up LTLs. Ranking individuals by deciles revealed that 94.1% (95% confidence interval of 92.6-95.4%) showed no rank change or a 1 decile change over time. We conclude that in adults, LTL is virtually anchored to a given rank with the passage of time. Accordingly, the links...... of LTL with atherosclerosis and longevity appear to be established early in life. It is unlikely that lifestyle and its modification during adulthood exert a major impact on LTL ranking....

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/.

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.

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).

PageRank for low frequency earthquake detection

Science.gov (United States)

Aguiar, A. C.; Beroza, G. C.

2013-12-01

We have analyzed Hi-Net seismic waveform data during the April 2006 tremor episode in the Nankai Trough in SW Japan using the autocorrelation approach of Brown et al. (2008), which detects low frequency earthquakes (LFEs) based on pair-wise waveform matching. We have generalized this to exploit the fact that waveforms may repeat multiple times, on more than just a pair-wise basis. We are working towards developing a sound statistical basis for event detection, but that is complicated by two factors. First, the statistical behavior of the autocorrelations varies between stations. Analyzing one station at a time assures that the detection threshold will only depend on the station being analyzed. Second, the positive detections do not satisfy "closure." That is, if window A correlates with window B, and window B correlates with window C, then window A and window C do not necessarily correlate with one another. We want to evaluate whether or not a linked set of windows are correlated due to chance. To do this, we map our problem on to one that has previously been solved for web search, and apply Google's PageRank algorithm. PageRank is the probability of a 'random surfer' to visit a particular web page; it assigns a ranking for a webpage based on the amount of links associated with that page. For windows of seismic data instead of webpages, the windows with high probabilities suggest likely LFE signals. Once identified, we stack the matched windows to improve the snr and use these stacks as template signals to find other LFEs within continuous data. We compare the results among stations and declare a detection if they are found in a statistically significant number of stations, based on multinomial statistics. We compare our detections using the single-station method to detections found by Shelly et al. (2007) for the April 2006 tremor sequence in Shikoku, Japan. We find strong similarity between the results, as well as many new detections that were not found using

Money counts for a Times Higher Education top-rank

NARCIS (Netherlands)

Marconi, G.; Ritzen, J.M.M.

2014-01-01

This paper analyses the relationship between a university’s expenditure per student and its position in international university rankings. We take into account other factors that are expected to play a role, such as university mission, size, and productive inefficiency. We formalise these concepts

RANWAR: rank-based weighted association rule mining from gene expression and methylation data.

Science.gov (United States)

Mallik, Saurav; Mukhopadhyay, Anirban; Maulik, Ujjwal

2015-01-01

Ranking of association rules is currently an interesting topic in data mining and bioinformatics. The huge number of evolved rules of items (or, genes) by association rule mining (ARM) algorithms makes confusion to the decision maker. In this article, we propose a weighted rule-mining technique (say, RANWAR or rank-based weighted association rule-mining) to rank the rules using two novel rule-interestingness measures, viz., rank-based weighted condensed support (wcs) and weighted condensed confidence (wcc) measures to bypass the problem. These measures are basically depended on the rank of items (genes). Using the rank, we assign weight to each item. RANWAR generates much less number of frequent itemsets than the state-of-the-art association rule mining algorithms. Thus, it saves time of execution of the algorithm. We run RANWAR on gene expression and methylation datasets. The genes of the top rules are biologically validated by Gene Ontologies (GOs) and KEGG pathway analyses. Many top ranked rules extracted from RANWAR that hold poor ranks in traditional Apriori, are highly biologically significant to the related diseases. Finally, the top rules evolved from RANWAR, that are not in Apriori, are reported.

Impact factor, eigenfactor, article influence, scopus SNIP, and SCImage journal rank of occupational therapy journals.

Science.gov (United States)

Brown, Ted; Gutman, Sharon A

2018-05-18

Journals are currently assessed and ranked using a number of different quantitative performance metrics. To compare and correlate the publication metrics of English-language occupational therapy journals published in 2015. Bibliometric data was sourced for 14 English-language occupational therapy journals including the Journal Citations Report (JCR) 2-year impact factor (IF), Eigenfactor Score (EFS), Article Influence Score (AIS), Scopus Source Normalized Impact per Paper (SNIP), Scopus Citescore, and SCImago Journal Rank (SJR) score. The JCR, Scopus, and SJR 2015 bibliometric data were correlated. The top six English-language occupational therapy journals in relation to JCR IF, EFS, AIS, SNIP, Citescore, SJR score, and SJR IIF were AJOT, AOTJ, POPT, CJOT, SJOT, and BJOT. JCR IF, EFS, JCR AIS, SNIP, Citescore, SJR score and SJR IIF were all significantly correlated with coefficients ranging from 0.751 to 0.961 (p article rankings rather than the singular use of IF scores that currently and frequently occurs in many jurisdictions.

Consumer preference in ranking walking function utilizing the walking index for spinal cord injury II.

Science.gov (United States)

Patrick, M; Ditunno, P; Ditunno, J F; Marino, R J; Scivoletto, G; Lam, T; Loffree, J; Tamburella, F; Leiby, B

2011-12-01

Blinded rank ordering. To determine consumer preference in walking function utilizing the walking Index for spinal cord injury II (WISCI II) in individuals with spinal cord injury (SCI)from the Canada, the Italy and the United States of America. In all, 42 consumers with incomplete SCI (25 cervical, 12 thoracic, 5 lumbar) from Canada (12/42), Italy (14/42) and the United States of America (16/42) ranked the 20 levels of the WISCI II scale by their individual preference for walking. Subjects were blinded to the original ranking of the WISCI II scale by clinical scientists. Photographs of each WISCI II level used in a previous pilot study were randomly shuffled and rank ordered. Percentile, conjoint/cluster and graphic analyses were performed. All three analyses illustrated consumer ranking followed a bimodal distribution. Ranking for two levels with physical assistance and two levels with a walker were bimodal with a difference of five to six ranks between consumer subgroups (quartile analysis). The larger cluster (N=20) showed preference for walking with assistance over the smaller cluster (N=12), whose preference was walking without assistance and more devices. In all, 64% (27/42) of consumers ranked WISCI II level with no devices or braces and 1 person assistance higher than multiple levels of the WISCI II requiring no assistance. These results were unexpected, as the hypothesis was that consumers would rank independent walking higher than walking with assistance. Consumer preference for walking function should be considered in addition to objective measures in designing SCI trials that use significant improvement in walking function as an outcome measure.

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.

A folk-psychological ranking of personality facets

Directory of Open Access Journals (Sweden)

Eka Roivainen

2016-10-01

Full Text Available Background Which personality facets should a general personality test measure? No consensus exists on the facet structure of personality, the nature of facets, or the correct method of identifying the most significant facets. However, it can be hypothesized (the lexical hypothesis that high frequency personality describing words more likely represent important personality facets and rarely used words refer to less significant aspects of personality. Participants and procedure A ranking of personality facets was performed by studying the frequency of the use of popular personality adjectives in causal clauses (because he is a kind person on the Internet and in books as attributes of the word person (kind person. Results In Study 1, the 40 most frequently used adjectives had a cumulative usage frequency equal to that of the rest of the 295 terms studied. When terms with a higher-ranking dictionary synonym or antonym were eliminated, 23 terms remained, which represent 23 different facets. In Study 2, clusters of synonymous terms were examined. Within the top 30 clusters, personality terms were used 855 times compared to 240 for the 70 lower-ranking clusters. Conclusions It is hypothesized that personality facets represented by the top-ranking terms and clusters of terms are important and impactful independent of their correlation with abstract underlying personality factors (five/six factor models. Compared to hierarchical personality models, lists of important facets probably better cover those aspects of personality that are situated between the five or six major domains.

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

An improved Greengenes taxonomy with explicit ranks for ecological and evolutionary analyses of bacteria and archaea.

Science.gov (United States)

McDonald, Daniel; Price, Morgan N; Goodrich, Julia; Nawrocki, Eric P; DeSantis, Todd Z; Probst, Alexander; Andersen, Gary L; Knight, Rob; Hugenholtz, Philip

2012-03-01

Reference phylogenies are crucial for providing a taxonomic framework for interpretation of marker gene and metagenomic surveys, which continue to reveal novel species at a remarkable rate. Greengenes is a dedicated full-length 16S rRNA gene database that provides users with a curated taxonomy based on de novo tree inference. We developed a 'taxonomy to tree' approach for transferring group names from an existing taxonomy to a tree topology, and used it to apply the Greengenes, National Center for Biotechnology Information (NCBI) and cyanoDB (Cyanobacteria only) taxonomies to a de novo tree comprising 408,315 sequences. We also incorporated explicit rank information provided by the NCBI taxonomy to group names (by prefixing rank designations) for better user orientation and classification consistency. The resulting merged taxonomy improved the classification of 75% of the sequences by one or more ranks relative to the original NCBI taxonomy with the most pronounced improvements occurring in under-classified environmental sequences. We also assessed candidate phyla (divisions) currently defined by NCBI and present recommendations for consolidation of 34 redundantly named groups. All intermediate results from the pipeline, which includes tree inference, jackknifing and transfer of a donor taxonomy to a recipient tree (tax2tree) are available for download. The improved Greengenes taxonomy should provide important infrastructure for a wide range of megasequencing projects studying ecosystems on scales ranging from our own bodies (the Human Microbiome Project) to the entire planet (the Earth Microbiome Project). The implementation of the software can be obtained from http://sourceforge.net/projects/tax2tree/.

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.

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.

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.

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.

Learning Preference Models from Data: On the Problem of Label Ranking and Its Variants

Science.gov (United States)

Hüllermeier, Eyke; Fürnkranz, Johannes

The term “preference learning” refers to the application of machine learning methods for inducing preference models from empirical data. In the recent literature, corresponding problems appear in various guises. After a brief overview of the field, this work focuses on a particular learning scenario called label ranking where the problem is to learn a mapping from instances to rankings over a finite number of labels. Our approach for learning such a ranking function, called ranking by pairwise comparison (RPC), first induces a binary preference relation from suitable training data, using a natural extension of pairwise classification. A ranking is then derived from this relation by means of a ranking procedure. This paper elaborates on a key advantage of such an approach, namely the fact that our learner can be adapted to different loss functions by using different ranking procedures on the same underlying order relations. In particular, the Spearman rank correlation is minimized by using a simple weighted voting procedure. Moreover, we discuss a loss function suitable for settings where candidate labels must be tested successively until a target label is found. In this context, we propose the idea of “empirical conditioning” of class probabilities. A related ranking procedure, called “ranking through iterated choice”, is investigated experimentally.

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

Rank restriction for the variational calculation of two-electron reduced density matrices of many-electron atoms and molecules

International Nuclear Information System (INIS)

Naftchi-Ardebili, Kasra; Hau, Nathania W.; Mazziotti, David A.

2011-01-01

Variational minimization of the ground-state energy as a function of the two-electron reduced density matrix (2-RDM), constrained by necessary N-representability conditions, provides a polynomial-scaling approach to studying strongly correlated molecules without computing the many-electron wave function. Here we introduce a route to enhancing necessary conditions for N representability through rank restriction of the 2-RDM. Rather than adding computationally more expensive N-representability conditions, we directly enhance the accuracy of two-particle (2-positivity) conditions through rank restriction, which removes degrees of freedom in the 2-RDM that are not sufficiently constrained. We select the rank of the particle-hole 2-RDM by deriving the ranks associated with model wave functions, including both mean-field and antisymmetrized geminal power (AGP) wave functions. Because the 2-positivity conditions are exact for quantum systems with AGP ground states, the rank of the particle-hole 2-RDM from the AGP ansatz provides a minimum for its value in variational 2-RDM calculations of general quantum systems. To implement the rank-restricted conditions, we extend a first-order algorithm for large-scale semidefinite programming. The rank-restricted conditions significantly improve the accuracy of the energies; for example, the percentages of correlation energies recovered for HF, CO, and N 2 improve from 115.2%, 121.7%, and 121.5% without rank restriction to 97.8%, 101.1%, and 100.0% with rank restriction. Similar results are found at both equilibrium and nonequilibrium geometries. While more accurate, the rank-restricted N-representability conditions are less expensive computationally than the full-rank conditions.

Evaluation of Term Ranking Algorithms for Pseudo-Relevance Feedback in MEDLINE Retrieval.

Science.gov (United States)

Yoo, Sooyoung; Choi, Jinwook

2011-06-01

The purpose of this study was to investigate the effects of query expansion algorithms for MEDLINE retrieval within a pseudo-relevance feedback framework. A number of query expansion algorithms were tested using various term ranking formulas, focusing on query expansion based on pseudo-relevance feedback. The OHSUMED test collection, which is a subset of the MEDLINE database, was used as a test corpus. Various ranking algorithms were tested in combination with different term re-weighting algorithms. Our comprehensive evaluation showed that the local context analysis ranking algorithm, when used in combination with one of the reweighting algorithms - Rocchio, the probabilistic model, and our variants - significantly outperformed other algorithm combinations by up to 12% (paired t-test; p algorithm pairs, at least in the context of the OHSUMED corpus. Comparative experiments on term ranking algorithms were performed in the context of a subset of MEDLINE documents. With medical documents, local context analysis, which uses co-occurrence with all query terms, significantly outperformed various term ranking methods based on both frequency and distribution analyses. Furthermore, the results of the experiments demonstrated that the term rank-based re-weighting method contributed to a remarkable improvement in mean average precision.

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.

Management a marketing sportovní akce: ICF Slalom World Ranking Race Prague 2009

OpenAIRE

Kubričan, Lukáš

2009-01-01

Title: Management and marketing of sport's event: ICF Slalom World Ranking Race Prague 2009 Objectives: Present strengths and weaknesses of ICF Slalom World Ranking Race Prague 2009 based on analyse of recent years and present ideas for its improvement. Methods: Descriptive analysis, SWOT analysis and interview with expert. Results: Conclusion and advices for organizers of sport's events. Key words: Management, marketing, SWOT analysis, descriptive analysis, sport's event, canoe slalom compet...

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.

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.

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.

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.

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.

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.

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.

Associations of Power at V̇O2peak and Anaerobic Threshold with Rank in British High Performance Junior Surfers

Directory of Open Access Journals (Sweden)

Barlow Matthew John

2015-03-01

Full Text Available Purpose. The objective of this study was to determine the relationships of peak oxygen uptake ( V̇O2peak, power at V̇O2peak and power at the anaerobic threshold (AT with national ranking in a sample of British high performance junior surfers. Methods. Eighteen male surfers (aged 15.4 ± 1.4 years from the British Junior Surfing team were tested for V̇O2peak and AT using an adapted kayak ergometer; national ranking was used to indicate performance level. The AT was identified as the point at which V̇E/V̇O2 started to rise without a concomitant increase in V̇E/V̇CO2. Spearman’s rank (rs and partial correlations (rp controlling for age were used to identify the relationships between the physiological variables and national ranking. Results. Mean V̇O2peak was 3.1 ± 0.5 l · min-1 (47.7 ± 7.2 ml · kg-1 · min-1 and mean AT occurred at 48.1 ± 12.2 W. There were significant correlations between national ranking and power at V̇O2peak (rs = -0.549, p = 0.028, power at AT (rs = -0.646, p = 0.009, and age (rs = -0.579, p = 0.012. Significant partial correlations were established controlling for age between national ranking and power at V̇O2peak (rp = -0.839, p = 0.000 and power at AT (rp = -0.541, p < 0.046. Conclusions. The power outputs associated with V̇O2peak and AT were significantly related to surfer ranking in this sample. However, due to the low coefficient of determination associated with the AT/ranking relationship, AT does not discriminate well between the ranking of surfers. These findings support the inclusion of power at V̇O2peak in assessment batteries for junior competitive surfers.

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 ...

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.

What's wrong with hazard-ranking systems? An expository note.

Science.gov (United States)

Cox, Louis Anthony Tony

2009-07-01

Two commonly recommended principles for allocating risk management resources to remediate uncertain hazards are: (1) select a subset to maximize risk-reduction benefits (e.g., maximize the von Neumann-Morgenstern expected utility of the selected risk-reducing activities), and (2) assign priorities to risk-reducing opportunities and then select activities from the top of the priority list down until no more can be afforded. When different activities create uncertain but correlated risk reductions, as is often the case in practice, then these principles are inconsistent: priority scoring and ranking fails to maximize risk-reduction benefits. Real-world risk priority scoring systems used in homeland security and terrorism risk assessment, environmental risk management, information system vulnerability rating, business risk matrices, and many other important applications do not exploit correlations among risk-reducing opportunities or optimally diversify risk-reducing investments. As a result, they generally make suboptimal risk management recommendations. Applying portfolio optimization methods instead of risk prioritization ranking, rating, or scoring methods can achieve greater risk-reduction value for resources spent.

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

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.

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.

A multi-criteria evaluation system for marine litter pollution based on statistical analyses of OSPAR beach litter monitoring time series.

Science.gov (United States)

Schulz, Marcus; Neumann, Daniel; Fleet, David M; Matthies, Michael

2013-12-01

During the last decades, marine pollution with anthropogenic litter has become a worldwide major environmental concern. Standardized monitoring of litter since 2001 on 78 beaches selected within the framework of the Convention for the Protection of the Marine Environment of the North-East Atlantic (OSPAR) has been used to identify temporal trends of marine litter. Based on statistical analyses of this dataset a two-part multi-criteria evaluation system for beach litter pollution of the North-East Atlantic and the North Sea is proposed. Canonical correlation analyses, linear regression analyses, and non-parametric analyses of variance were used to identify different temporal trends. A classification of beaches was derived from cluster analyses and served to define different states of beach quality according to abundances of 17 input variables. The evaluation system is easily applicable and relies on the above-mentioned classification and on significant temporal trends implied by significant rank correlations. Copyright © 2013 Elsevier Ltd. All rights reserved.

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...

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.

Statistical analyses of scatterplots to identify important factors in large-scale simulations, 1: Review and comparison of techniques

International Nuclear Information System (INIS)

Kleijnen, J.P.C.; Helton, J.C.

1999-01-01

Procedures for identifying patterns in scatterplots generated in Monte Carlo sensitivity analyses are described and illustrated. These procedures attempt to detect increasingly complex patterns in scatterplots and involve the identification of (i) linear relationships with correlation coefficients, (ii) monotonic relationships with rank correlation coefficients, (iii) trends in central tendency as defined by means, medians and the Kruskal-Wallis statistic, (iv) trends in variability as defined by variances and interquartile ranges, and (v) deviations from randomness as defined by the chi-square statistic. A sequence of example analyses with a large model for two-phase fluid flow illustrates how the individual procedures can differ in the variables that they identify as having effects on particular model outcomes. The example analyses indicate that the use of a sequence of procedures is a good analysis strategy and provides some assurance that an important effect is not overlooked

A new classification of spin in systematic reviews and meta-analyses was developed and ranked according to the severity

DEFF Research Database (Denmark)

Yavchitz, Amélie; Ravaud, Philippe; Altman, Douglas G

2016-01-01

Objectives We aimed to (1) identify and classify spin (i.e., a description that overstates efficacy and/or understates harm) in systematic reviews and (2) rank spin in abstracts of systematic reviews according to their severity (i.e., the likelihood of distorting readers' interpretation......, 28 from the main text and 21 from the abstract; 13 were specific to the systematic review design. Spin was classified into three categories: (1) misleading reporting, (2) misleading interpretation, and (3) inappropriate extrapolation. Spin ranked as the most severe by the 122 people who participated...... avoid spin in reports of systematic reviews. © 2016 Elsevier Inc....

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…

Correlation, Regression and Path Analyses of Seed Yield Components in Crambe abyssinica, a Promising Industrial Oil Crop

OpenAIRE

Huang, Banglian; Yang, Yiming; Luo, Tingting; Wu, S.; Du, Xuezhu; Cai, Detian; Loo, van, E.N.; Huang Bangquan

2013-01-01

In the present study correlation, regression and path analyses were carried out to decide correlations among the agro- nomic traits and their contributions to seed yield per plant in Crambe abyssinica. Partial correlation analysis indicated that plant height (X1) was significantly correlated with branching height and the number of first branches (P <0.01); Branching height (X2) was significantly correlated with pod number of primary inflorescence (P <0.01) and number of secondary branch...

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...

24 CFR 599.401 - Ranking of applications.

Science.gov (United States)

2010-04-01

... 24 Housing and Urban Development 3 2010-04-01 2010-04-01 false Ranking of applications. 599.401... Communities § 599.401 Ranking of applications. (a) Ranking order. Rural and urban applications will be ranked... applications ranked first. (b) Separate ranking categories. After initial ranking, both rural and urban...

Can Future Academic Surgeons be Identified in the Residency Ranking Process?

Science.gov (United States)

Beninato, Toni; Kleiman, David A; Zarnegar, Rasa; Fahey, Thomas J

2016-01-01

The goal of surgical residency training programs is to train competent surgeons. Academic surgical training programs also have as a mission training future academicians-surgical scientists, teachers, and leaders. However, selection of surgical residents is dependent on a relatively unscientific process. Here we sought to determine how well the residency selection process is able to identify future academicians in surgery. Rank lists from an academic surgical residency program from 1992 to 1997 were examined. All ranked candidates׳ career paths after residency were reviewed to determine whether they stayed in academics, were university affiliated, or in private practice. The study was performed at New York Presbyterian Hospital-Weill Cornell Medical College, New York, NY. A total of 663 applicants for general surgery residency participated in this study. In total 6 rank lists were evaluated, which included 663 candidates. Overall 76% remained in a general surgery subspecialty. Of those who remained in general surgery, 49% were in private practice, 20% were university affiliated, and 31% had academic careers. Approximately 47% of candidates that were ranked in the top 20 had ≥20 publications, with decreasing percentages as rank number increased. There was a strong correlation between the candidates׳ rank position and pursuing an academic career (p career. The residency selection process can identify candidates likely to be future academicians. Copyright © 2016 Association of Program Directors in Surgery. Published by Elsevier Inc. All rights reserved.

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

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.

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...

An Automated Approach for Ranking Journals to Help in Clinician Decision Support

Science.gov (United States)

Jonnalagadda, Siddhartha R.; Moosavinasab, Soheil; Nath, Chinmoy; Li, Dingcheng; Chute, Christopher G.; Liu, Hongfang

2014-01-01

Point of care access to knowledge from full text journal articles supports decision-making and decreases medical errors. However, it is an overwhelming task to search through full text journal articles and find quality information needed by clinicians. We developed a method to rate journals for a given clinical topic, Congestive Heart Failure (CHF). Our method enables filtering of journals and ranking of journal articles based on source journal in relation to CHF. We also obtained a journal priority score, which automatically rates any journal based on its importance to CHF. Comparing our ranking with data gathered by surveying 169 cardiologists, who publish on CHF, our best Multiple Linear Regression model showed a correlation of 0.880, based on five-fold cross validation. Our ranking system can be extended to other clinical topics. PMID:25954382

The Times Higher Education Ranking Product: Visualising Excellence through Media

Science.gov (United States)

Stack, Michelle L.

2013-01-01

This paper will examine the Times Higher Education's (THE) World University Rankings as a corporate media product. A number of empirical studies have critiqued the methodology of the THE, yet individuals, Higher Education Institutions (HEIs) and governments continue to use them for decision-making. This paper analyses the influence of…

RANK rewires energy homeostasis in lung cancer cells and drives primary lung cancer.

Science.gov (United States)

Rao, Shuan; Sigl, Verena; Wimmer, Reiner Alois; Novatchkova, Maria; Jais, Alexander; Wagner, Gabriel; Handschuh, Stephan; Uribesalgo, Iris; Hagelkruys, Astrid; Kozieradzki, Ivona; Tortola, Luigi; Nitsch, Roberto; Cronin, Shane J; Orthofer, Michael; Branstetter, Daniel; Canon, Jude; Rossi, John; D'Arcangelo, Manolo; Botling, Johan; Micke, Patrick; Fleur, Linnea La; Edlund, Karolina; Bergqvist, Michael; Ekman, Simon; Lendl, Thomas; Popper, Helmut; Takayanagi, Hiroshi; Kenner, Lukas; Hirsch, Fred R; Dougall, William; Penninger, Josef M

2017-10-15

Lung cancer is the leading cause of cancer deaths. Besides smoking, epidemiological studies have linked female sex hormones to lung cancer in women; however, the underlying mechanisms remain unclear. Here we report that the receptor activator of nuclear factor-kB (RANK), the key regulator of osteoclastogenesis, is frequently expressed in primary lung tumors, an active RANK pathway correlates with decreased survival, and pharmacologic RANK inhibition reduces tumor growth in patient-derived lung cancer xenografts. Clonal genetic inactivation of KRas G12D in mouse lung epithelial cells markedly impairs the progression of KRas G12D -driven lung cancer, resulting in a significant survival advantage. Mechanistically, RANK rewires energy homeostasis in human and murine lung cancer cells and promotes expansion of lung cancer stem-like cells, which is blocked by inhibiting mitochondrial respiration. Our data also indicate survival differences in KRas G12D -driven lung cancer between male and female mice, and we show that female sex hormones can promote lung cancer progression via the RANK pathway. These data uncover a direct role for RANK in lung cancer and may explain why female sex hormones accelerate lung cancer development. Inhibition of RANK using the approved drug denosumab may be a therapeutic drug candidate for primary lung cancer. © 2017 Rao et al.; Published by Cold Spring Harbor Laboratory Press.

When sparse coding meets ranking: a joint framework for learning sparse codes and ranking scores

KAUST Repository

Wang, Jim Jing-Yan

2017-06-28

Sparse coding, which represents a data point as a sparse reconstruction code with regard to a dictionary, has been a popular data representation method. Meanwhile, in database retrieval problems, learning the ranking scores from data points plays an important role. Up to now, these two problems have always been considered separately, assuming that data coding and ranking are two independent and irrelevant problems. However, is there any internal relationship between sparse coding and ranking score learning? If yes, how to explore and make use of this internal relationship? In this paper, we try to answer these questions by developing the first joint sparse coding and ranking score learning algorithm. To explore the local distribution in the sparse code space, and also to bridge coding and ranking problems, we assume that in the neighborhood of each data point, the ranking scores can be approximated from the corresponding sparse codes by a local linear function. By considering the local approximation error of ranking scores, the reconstruction error and sparsity of sparse coding, and the query information provided by the user, we construct a unified objective function for learning of sparse codes, the dictionary and ranking scores. We further develop an iterative algorithm to solve this optimization problem.

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…

A logical framework for ranking landslide inventory maps

Science.gov (United States)

Santangelo, Michele; Fiorucci, Federica; Bucci, Francesco; Cardinali, Mauro; Ardizzone, Francesca; Marchesini, Ivan; Cesare Mondini, Alessandro; Reichenbach, Paola; Rossi, Mauro; Guzzetti, Fausto

2014-05-01

Landslides inventory maps are essential for quantitative landslide hazard and risk assessments, and for geomorphological and ecological studies. Landslide maps, including geomorphological, event based, multi-temporal, and seasonal inventory maps, are most commonly prepared through the visual interpretation of (i) monoscopic and stereoscopic aerial photographs, (ii) satellite images, (iii) LiDAR derived images, aided by more or less extensive field surveys. Landslide inventory maps are the basic information for a number of different scientific, technical and civil protection purposes, such as: (i) quantitative geomorphic analyses, (ii) erosion studies, (iii) deriving landslide statistics, (iv) urban development planning (v) landslide susceptibility, hazard and risk evaluation, and (vi) landslide monitoring systems. Despite several decades of activity in landslide inventory making, still no worldwide-accepted standards, best practices and protocols exist for the ranking and the production of landslide inventory maps. Standards for the preparation (and/or ranking) of landslide inventories should indicate the minimum amount of information for a landslide inventory map, given the scale, the type of images, the instrumentation available, and the available ancillary data. We recently attempted at a systematic description and evaluation of a total of 22 geomorphological inventories, 6 multi-temporal inventories, 10 event inventories, and 3 seasonal inventories, in the scale range between 1:10,000 and 1:500,000, prepared for areas in different geological and geomorphological settings. All of the analysed inventories were carried out by using image interpretation techniques, or field surveys. Firstly, a detailed characterisation was performed for each landslide inventory, mainly collecting metadata related (i) to the amount of information used for preparing the landslide inventory (i.e. images used, instrumentation, ancillary data, digitalisation method, legend, validation

Deep Multimodal Distance Metric Learning Using Click Constraints for Image Ranking.

Science.gov (United States)

Yu, Jun; Yang, Xiaokang; Gao, Fei; Tao, Dacheng

2017-12-01

How do we retrieve images accurately? Also, how do we rank a group of images precisely and efficiently for specific queries? These problems are critical for researchers and engineers to generate a novel image searching engine. First, it is important to obtain an appropriate description that effectively represent the images. In this paper, multimodal features are considered for describing images. The images unique properties are reflected by visual features, which are correlated to each other. However, semantic gaps always exist between images visual features and semantics. Therefore, we utilize click feature to reduce the semantic gap. The second key issue is learning an appropriate distance metric to combine these multimodal features. This paper develops a novel deep multimodal distance metric learning (Deep-MDML) method. A structured ranking model is adopted to utilize both visual and click features in distance metric learning (DML). Specifically, images and their related ranking results are first collected to form the training set. Multimodal features, including click and visual features, are collected with these images. Next, a group of autoencoders is applied to obtain initially a distance metric in different visual spaces, and an MDML method is used to assign optimal weights for different modalities. Next, we conduct alternating optimization to train the ranking model, which is used for the ranking of new queries with click features. Compared with existing image ranking methods, the proposed method adopts a new ranking model to use multimodal features, including click features and visual features in DML. We operated experiments to analyze the proposed Deep-MDML in two benchmark data sets, and the results validate the effects of the method.

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.

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)

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

Ranking Support Vector Machine with Kernel Approximation.

Science.gov (United States)

Chen, Kai; Li, Rongchun; Dou, Yong; Liang, Zhengfa; Lv, Qi

2017-01-01

Learning to rank algorithm has become important in recent years due to its successful application in information retrieval, recommender system, and computational biology, and so forth. Ranking support vector machine (RankSVM) is one of the state-of-art ranking models and has been favorably used. Nonlinear RankSVM (RankSVM with nonlinear kernels) can give higher accuracy than linear RankSVM (RankSVM with a linear kernel) for complex nonlinear ranking problem. However, the learning methods for nonlinear RankSVM are still time-consuming because of the calculation of kernel matrix. In this paper, we propose a fast ranking algorithm based on kernel approximation to avoid computing the kernel matrix. We explore two types of kernel approximation methods, namely, the Nyström method and random Fourier features. Primal truncated Newton method is used to optimize the pairwise L2-loss (squared Hinge-loss) objective function of the ranking model after the nonlinear kernel approximation. Experimental results demonstrate that our proposed method gets a much faster training speed than kernel RankSVM and achieves comparable or better performance over state-of-the-art ranking algorithms.

Ranking Support Vector Machine with Kernel Approximation

Directory of Open Access Journals (Sweden)

Kai Chen

2017-01-01

Full Text Available Learning to rank algorithm has become important in recent years due to its successful application in information retrieval, recommender system, and computational biology, and so forth. Ranking support vector machine (RankSVM is one of the state-of-art ranking models and has been favorably used. Nonlinear RankSVM (RankSVM with nonlinear kernels can give higher accuracy than linear RankSVM (RankSVM with a linear kernel for complex nonlinear ranking problem. However, the learning methods for nonlinear RankSVM are still time-consuming because of the calculation of kernel matrix. In this paper, we propose a fast ranking algorithm based on kernel approximation to avoid computing the kernel matrix. We explore two types of kernel approximation methods, namely, the Nyström method and random Fourier features. Primal truncated Newton method is used to optimize the pairwise L2-loss (squared Hinge-loss objective function of the ranking model after the nonlinear kernel approximation. Experimental results demonstrate that our proposed method gets a much faster training speed than kernel RankSVM and achieves comparable or better performance over state-of-the-art ranking algorithms.

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…

Two-dimensional ranking of Wikipedia articles

Science.gov (United States)

Zhirov, A. O.; Zhirov, O. V.; Shepelyansky, D. L.

2010-10-01

The Library of Babel, described by Jorge Luis Borges, stores an enormous amount of information. The Library exists ab aeterno. Wikipedia, a free online encyclopaedia, becomes a modern analogue of such a Library. Information retrieval and ranking of Wikipedia articles become the challenge of modern society. While PageRank highlights very well known nodes with many ingoing links, CheiRank highlights very communicative nodes with many outgoing links. In this way the ranking becomes two-dimensional. Using CheiRank and PageRank we analyze the properties of two-dimensional ranking of all Wikipedia English articles and show that it gives their reliable classification with rich and nontrivial features. Detailed studies are done for countries, universities, personalities, physicists, chess players, Dow-Jones companies and other categories.

Linear Subspace Ranking Hashing for Cross-Modal Retrieval.

Science.gov (United States)

Li, Kai; Qi, Guo-Jun; Ye, Jun; Hua, Kien A

2017-09-01

Hashing has attracted a great deal of research in recent years due to its effectiveness for the retrieval and indexing of large-scale high-dimensional multimedia data. In this paper, we propose a novel ranking-based hashing framework that maps data from different modalities into a common Hamming space where the cross-modal similarity can be measured using Hamming distance. Unlike existing cross-modal hashing algorithms where the learned hash functions are binary space partitioning functions, such as the sign and threshold function, the proposed hashing scheme takes advantage of a new class of hash functions closely related to rank correlation measures which are known to be scale-invariant, numerically stable, and highly nonlinear. Specifically, we jointly learn two groups of linear subspaces, one for each modality, so that features' ranking orders in different linear subspaces maximally preserve the cross-modal similarities. We show that the ranking-based hash function has a natural probabilistic approximation which transforms the original highly discontinuous optimization problem into one that can be efficiently solved using simple gradient descent algorithms. The proposed hashing framework is also flexible in the sense that the optimization procedures are not tied up to any specific form of loss function, which is typical for existing cross-modal hashing methods, but rather we can flexibly accommodate different loss functions with minimal changes to the learning steps. We demonstrate through extensive experiments on four widely-used real-world multimodal datasets that the proposed cross-modal hashing method can achieve competitive performance against several state-of-the-arts with only moderate training and testing time.

Comparison of different eigensolvers for calculating vibrational spectra using low-rank, sum-of-product basis functions

Science.gov (United States)

Leclerc, Arnaud; Thomas, Phillip S.; Carrington, Tucker

2017-08-01

Vibrational spectra and wavefunctions of polyatomic molecules can be calculated at low memory cost using low-rank sum-of-product (SOP) decompositions to represent basis functions generated using an iterative eigensolver. Using a SOP tensor format does not determine the iterative eigensolver. The choice of the interative eigensolver is limited by the need to restrict the rank of the SOP basis functions at every stage of the calculation. We have adapted, implemented and compared different reduced-rank algorithms based on standard iterative methods (block-Davidson algorithm, Chebyshev iteration) to calculate vibrational energy levels and wavefunctions of the 12-dimensional acetonitrile molecule. The effect of using low-rank SOP basis functions on the different methods is analysed and the numerical results are compared with those obtained with the reduced rank block power method. Relative merits of the different algorithms are presented, showing that the advantage of using a more sophisticated method, although mitigated by the use of reduced-rank SOP functions, is noticeable in terms of CPU time.

Educational Background and Academic Rank of Faculty Members within US Schools of Pharmacy.

Science.gov (United States)

Assemi, Mitra; Hudmon, Karen Suchanek; Sowinski, Kevin M; Corelli, Robin L

2016-05-25

Objective. To characterize the educational background and academic rank of faculty members in US schools of pharmacy, estimate the extent to which they are employed by institutions where they received previous training, and determine whether differences in degree origin and rank exist between faculty members in established (≤1995) vs newer programs. Methods. A cross-sectional study was conducted using the American Association of Colleges of Pharmacy (AACP) faculty database and demographic information from the public domain. Results. Among 5516 faculty members, 50.3% held two or more types of degrees. Established schools had a higher median number of faculty members and a higher mean faculty rank than did newer schools. Conclusion. The difference in mean faculty rank highlights the shortage of experienced faculty members in newer schools. Future research efforts should investigate educational attainment in correlation to other faculty and school characteristics and prospectively track and report trends related to pharmacy faculty members composition.

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.

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.

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. ...

Accuracy Evaluation of C4.5 and Naive Bayes Classifiers Using Attribute Ranking Method

Directory of Open Access Journals (Sweden)

S. Sivakumari

2009-03-01

Full Text Available This paper intends to classify the Ljubljana Breast Cancer dataset using C4.5 Decision Tree and Nai?ve Bayes classifiers. In this work, classification is carriedout using two methods. In the first method, dataset is analysed using all the attributes in the dataset. In the second method, attributes are ranked using information gain ranking technique and only the high ranked attributes are used to build the classification model. We are evaluating the results of C4.5 Decision Tree and Nai?ve Bayes classifiers in terms of classifier accuracy for various folds of cross validation. Our results show that both the classifiers achieve good accuracy on the dataset.

Rank-based Tests of the Cointegrating Rank in Semiparametric Error Correction Models

NARCIS (Netherlands)

Hallin, M.; van den Akker, R.; Werker, B.J.M.

2012-01-01

Abstract: This paper introduces rank-based tests for the cointegrating rank in an Error Correction Model with i.i.d. elliptical innovations. The tests are asymptotically distribution-free, and their validity does not depend on the actual distribution of the innovations. This result holds despite the

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)

Quantitative assessments of municipal waste management systems: using different indicators to compare and rank programs in New York State.

Science.gov (United States)

Greene, Krista L; Tonjes, David J

2014-04-01

The primary objective of waste management technologies and policies in the United States is to reduce the harmful environmental impacts of waste, particularly those relating to energy consumption and climate change. Performance indicators are frequently used to evaluate the environmental quality of municipal waste systems, as well as to compare and rank programs relative to each other in terms of environmental performance. However, there currently is no consensus on the best indicator for performing these environmental evaluations. The purpose of this study is to examine the common performance indicators used to assess the environmental benefits of municipal waste systems to determine if there is agreement between them regarding which system performs best environmentally. Focus is placed on how indicator selection influences comparisons between municipal waste management programs and subsequent system rankings. The waste systems of ten municipalities in the state of New York, USA, were evaluated using each common performance indicator and Spearman correlations were calculated to see if there was a significant association between system rank orderings. Analyses showed that rank orders of waste systems differ substantially when different indicators are used. Therefore, comparative system assessments based on indicators should be considered carefully, especially those intended to gauge environmental quality. Insight was also gained into specific factors which may lead to one system achieving higher rankings than another. However, despite the insufficiencies of indicators for comparative quality assessments, they do provide important information for waste managers and they can assist in evaluating internal programmatic performance and progress. To enhance these types of assessments, a framework for scoring indicators based on criteria that evaluate their utility and value for system evaluations was developed. This framework was used to construct an improved model for

Bladder transitional cell carcinoma: correlation of contrast enhancement on computed tomography with histological grade and tumour angiogenesis

International Nuclear Information System (INIS)

Xie, Q.; Zhang, J.; Wu, P.-H.; Jiang, X.-Q.; Chen, S.-L.; Wang, Q.-L.; Xu, J.; Chen, G.-D.; Deng, J.-H.

2005-01-01

AIM: To investigate the correlation between the degree of contrast enhancement of bladder cancer in the early enhanced phase of helical computed tomography (CT) and microvessel density (MVD), vascular endothelial growth factor (VEGF) and histological grade. MATERIALS AND METHODS: Sixty-five patients with transitional cell carcinoma of the bladder were examined by incremental unenhanced CT and helical CT at 40-45 s after initiation of intravenous administration of contrast medium before surgery. The CT density in Hounsfield units of bladder carcinomas were measured in the middle of the maximum diameter section of the cancer lesions on unenhanced and enhanced CT. The degree of contrast enhancement of the tumour was determined as the absolute increase in Hounsfield units. Histological grade, VEGF and MVD were analysed for each cancer. The Pearson and Spearman correlation tests were used to determine the strength of the relationships between CT enhancement and histological grade, VEGF expression and MVD. RESULTS: Different degrees of enhancement were observed in 91 cancers during the early enhanced phase of helical CT. Mean MVDs and mean CT enhancing values of different histological grade groups were statistically different (p<0.001). A positive correlation was found in the CT-enhancing value of bladder cancer and MVD (Pearson correlation test; r=0.938, p<0.001) and histological grade (Spearman rank correlation; r=0.734, p<0.001). VEGF of bladder cancer did not correlate with the change in CT attenuation (Spearman rank correlation; r=0.087, p=0.410) and MVD (Spearman rank correlation, r=0.103, p=0.330). CONCLUSION: In bladder cancer, the degree of contrast enhancement during the early enhanced helical CT is correlated with the MVD and histological grade of tumour. It is possible that MVD is the histopathological basis of early contrast enhancement of bladder cancer

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

A combined QSAR and partial order ranking approach to risk assessment.

Science.gov (United States)

Carlsen, L

2006-04-01

QSAR generated data appear as an attractive alternative to experimental data as foreseen in the proposed new chemicals legislation REACH. A preliminary risk assessment for the aquatic environment can be based on few factors, i.e. the octanol-water partition coefficient (Kow), the vapour pressure (VP) and the potential biodegradability of the compound in combination with the predicted no-effect concentration (PNEC) and the actual tonnage in which the substance is produced. Application of partial order ranking, allowing simultaneous inclusion of several parameters leads to a mutual prioritisation of the investigated substances, the prioritisation possibly being further analysed through the concept of linear extensions and average ranks. The ranking uses endpoint values (log Kow and log VP) derived from strictly linear 'noise-deficient' QSAR models as input parameters. Biodegradation estimates were adopted from the BioWin module of the EPI Suite. The population growth impairment of Tetrahymena pyriformis was used as a surrogate for fish lethality.

Inverted rank distributions: Macroscopic statistics, universality classes, and critical exponents

Science.gov (United States)

Eliazar, Iddo; Cohen, Morrel H.

2014-01-01

An inverted rank distribution is an infinite sequence of positive sizes ordered in a monotone increasing fashion. Interlacing together Lorenzian and oligarchic asymptotic analyses, we establish a macroscopic classification of inverted rank distributions into five “socioeconomic” universality classes: communism, socialism, criticality, feudalism, and absolute monarchy. We further establish that: (i) communism and socialism are analogous to a “disordered phase”, feudalism and absolute monarchy are analogous to an “ordered phase”, and criticality is the “phase transition” between order and disorder; (ii) the universality classes are characterized by two critical exponents, one governing the ordered phase, and the other governing the disordered phase; (iii) communism, criticality, and absolute monarchy are characterized by sharp exponent values, and are inherently deterministic; (iv) socialism is characterized by a continuous exponent range, is inherently stochastic, and is universally governed by continuous power-law statistics; (v) feudalism is characterized by a continuous exponent range, is inherently stochastic, and is universally governed by discrete exponential statistics. The results presented in this paper yield a universal macroscopic socioeconophysical perspective of inverted rank distributions.

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.

Seasonal change in body fat of the Hyrax Procavia capensis (Pallas, 1766 using a body fat ranking index

Directory of Open Access Journals (Sweden)

L.J. Fourie

1985-11-01

Full Text Available Changes in the body fat content of the hyrax Procavia capensis were used as an indicator of physiological condition. Body fat rankings for the different sexes showed seasonal variations related to physiologically stressful periods (rutting, gestation and lactation. The subjective body fat rankings were correlated significantly with total body fat.

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.

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

An inequality between the weighted average and the rowwise correlation coefficient for proximity matrices

NARCIS (Netherlands)

Krijnen, WP

De Vries (1993) discusses Pearson's product-moment correlation, Spearman's rank correlation, and Kendall's rank-correlation coefficient for assessing the association between the rows of two proximity matrices. For each of these he introduces a weighted average variant and a rowwise variant. In this

AN INEQUALITY BETWEEN THE WEIGHTED AVERAGE AND THE ROWWISE CORRELATION-COEFFICIENT FOR PROXIMITY MATRICES

NARCIS (Netherlands)

KRIJNEN, WP

De Vries (1993) discusses Pearson's product-moment correlation, Spearman's rank correlation, and Kendall's rank-correlation coefficient for assessing the association between the rows of two proximity matrices. For each of these he introduces a weighted average variant and a rowwise variant. In this

Country-specific determinants of world university rankings

OpenAIRE

Pietrucha, Jacek

2017-01-01

This paper examines country-specific factors that affect the three most influential world university rankings (the Academic Ranking of World Universities, the QS World University Ranking, and the Times Higher Education World University Ranking). We run a cross sectional regression that covers 42–71 countries (depending on the ranking and data availability). We show that the position of universities from a country in the ranking is determined by the following country-specific variables: econom...

Characteristics of fundamental combustion and NOx emission using various rank coals.

Science.gov (United States)

Kim, Sung Su; Kang, Youn Suk; Lee, Hyun Dong; Kim, Jae-Kwan; Hong, Sung Chang

2011-03-01

Eight types of coals of different rank were selected and their fundamental combustion characteristics were examined along with the conversion of volatile nitrogen (N) to nitrogen oxides (NOx)/fuel N to NOx. The activation energy, onset temperature, and burnout temperature were obtained from the differential thermogravimetry curve and Arrhenius plot, which were derived through thermo-gravimetric analysis. In addition, to derive the combustion of volatile N to NOx/fuel N to NOx, the coal sample, which was pretreated at various temperatures, was burned, and the results were compared with previously derived fundamental combustion characteristics. The authors' experimental results confirmed that coal rank was highly correlated with the combustion of volatile N to NOx/fuel N to NOx.

AptRank: an adaptive PageRank model for protein function prediction on   bi-relational graphs.

Science.gov (United States)

Jiang, Biaobin; Kloster, Kyle; Gleich, David F; Gribskov, Michael

2017-06-15

Diffusion-based network models are widely used for protein function prediction using protein network data and have been shown to outperform neighborhood-based and module-based methods. Recent studies have shown that integrating the hierarchical structure of the Gene Ontology (GO) data dramatically improves prediction accuracy. However, previous methods usually either used the GO hierarchy to refine the prediction results of multiple classifiers, or flattened the hierarchy into a function-function similarity kernel. No study has taken the GO hierarchy into account together with the protein network as a two-layer network model. We first construct a Bi-relational graph (Birg) model comprised of both protein-protein association and function-function hierarchical networks. We then propose two diffusion-based methods, BirgRank and AptRank, both of which use PageRank to diffuse information on this two-layer graph model. BirgRank is a direct application of traditional PageRank with fixed decay parameters. In contrast, AptRank utilizes an adaptive diffusion mechanism to improve the performance of BirgRank. We evaluate the ability of both methods to predict protein function on yeast, fly and human protein datasets, and compare with four previous methods: GeneMANIA, TMC, ProteinRank and clusDCA. We design four different validation strategies: missing function prediction, de novo function prediction, guided function prediction and newly discovered function prediction to comprehensively evaluate predictability of all six methods. We find that both BirgRank and AptRank outperform the previous methods, especially in missing function prediction when using only 10% of the data for training. The MATLAB code is available at https://github.rcac.purdue.edu/mgribsko/aptrank . gribskov@purdue.edu. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Universal emergence of PageRank

Energy Technology Data Exchange (ETDEWEB)

Frahm, K M; Georgeot, B; Shepelyansky, D L, E-mail: frahm@irsamc.ups-tlse.fr, E-mail: georgeot@irsamc.ups-tlse.fr, E-mail: dima@irsamc.ups-tlse.fr [Laboratoire de Physique Theorique du CNRS, IRSAMC, Universite de Toulouse, UPS, 31062 Toulouse (France)

2011-11-18

The PageRank algorithm enables us to rank the nodes of a network through a specific eigenvector of the Google matrix, using a damping parameter {alpha} Element-Of ]0, 1[. Using extensive numerical simulations of large web networks, with a special accent on British University networks, we determine numerically and analytically the universal features of the PageRank vector at its emergence when {alpha} {yields} 1. The whole network can be divided into a core part and a group of invariant subspaces. For {alpha} {yields} 1, PageRank converges to a universal power-law distribution on the invariant subspaces whose size distribution also follows a universal power law. The convergence of PageRank at {alpha} {yields} 1 is controlled by eigenvalues of the core part of the Google matrix, which are extremely close to unity, leading to large relaxation times as, for example, in spin glasses. (paper)

Universal emergence of PageRank

International Nuclear Information System (INIS)

Frahm, K M; Georgeot, B; Shepelyansky, D L

2011-01-01

The PageRank algorithm enables us to rank the nodes of a network through a specific eigenvector of the Google matrix, using a damping parameter α ∈ ]0, 1[. Using extensive numerical simulations of large web networks, with a special accent on British University networks, we determine numerically and analytically the universal features of the PageRank vector at its emergence when α → 1. The whole network can be divided into a core part and a group of invariant subspaces. For α → 1, PageRank converges to a universal power-law distribution on the invariant subspaces whose size distribution also follows a universal power law. The convergence of PageRank at α → 1 is controlled by eigenvalues of the core part of the Google matrix, which are extremely close to unity, leading to large relaxation times as, for example, in spin glasses. (paper)

Robust Visual Tracking via Online Discriminative and Low-Rank Dictionary Learning.

Science.gov (United States)

Zhou, Tao; Liu, Fanghui; Bhaskar, Harish; Yang, Jie

2017-09-12

In this paper, we propose a novel and robust tracking framework based on online discriminative and low-rank dictionary learning. The primary aim of this paper is to obtain compact and low-rank dictionaries that can provide good discriminative representations of both target and background. We accomplish this by exploiting the recovery ability of low-rank matrices. That is if we assume that the data from the same class are linearly correlated, then the corresponding basis vectors learned from the training set of each class shall render the dictionary to become approximately low-rank. The proposed dictionary learning technique incorporates a reconstruction error that improves the reliability of classification. Also, a multiconstraint objective function is designed to enable active learning of a discriminative and robust dictionary. Further, an optimal solution is obtained by iteratively computing the dictionary, coefficients, and by simultaneously learning the classifier parameters. Finally, a simple yet effective likelihood function is implemented to estimate the optimal state of the target during tracking. Moreover, to make the dictionary adaptive to the variations of the target and background during tracking, an online update criterion is employed while learning the new dictionary. Experimental results on a publicly available benchmark dataset have demonstrated that the proposed tracking algorithm performs better than other state-of-the-art trackers.

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.

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....

Strategic alternatives ranking methodology: Multiple RCRA incinerator evaluation test case

International Nuclear Information System (INIS)

Baker, G.; Thomson, R.D.; Reece, J.; Springer, L.; Main, D.

1988-01-01

This paper presents an important process approach to permit quantification and ranking of multiple alternatives being considered in remedial actions or hazardous waste strategies. This process is a methodology for evaluating programmatic options in support of site selection or environmental analyses. Political or other less tangible motivations for alternatives may be quantified by means of establishing the range of significant variables, weighting their importance, and by establishing specific criteria for scoring individual alternatives. An application of the process to a recent AFLC program permitted ranking incineration alternatives from a list of over 130 options. The process forced participation by the organizations to be effected, allowed a consensus of opinion to be achieved, allowed complete flexibility to evaluate factor sensitivity, and resulted in strong, quantifiable support for any subsequent site-selection action NEPA documents

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.

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…

A tilting approach to ranking influence

KAUST Repository

Genton, Marc G.

2014-12-01

We suggest a new approach, which is applicable for general statistics computed from random samples of univariate or vector-valued or functional data, to assessing the influence that individual data have on the value of a statistic, and to ranking the data in terms of that influence. Our method is based on, first, perturbing the value of the statistic by ‘tilting’, or reweighting, each data value, where the total amount of tilt is constrained to be the least possible, subject to achieving a given small perturbation of the statistic, and, then, taking the ranking of the influence of data values to be that which corresponds to ranking the changes in data weights. It is shown, both theoretically and numerically, that this ranking does not depend on the size of the perturbation, provided that the perturbation is sufficiently small. That simple result leads directly to an elegant geometric interpretation of the ranks; they are the ranks of the lengths of projections of the weights onto a ‘line’ determined by the first empirical principal component function in a generalized measure of covariance. To illustrate the generality of the method we introduce and explore it in the case of functional data, where (for example) it leads to generalized boxplots. The method has the advantage of providing an interpretable ranking that depends on the statistic under consideration. For example, the ranking of data, in terms of their influence on the value of a statistic, is different for a measure of location and for a measure of scale. This is as it should be; a ranking of data in terms of their influence should depend on the manner in which the data are used. Additionally, the ranking recognizes, rather than ignores, sign, and in particular can identify left- and right-hand ‘tails’ of the distribution of a random function or vector.

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.

Statistical Analyses of Scatterplots to Identify Important Factors in Large-Scale Simulations

Energy Technology Data Exchange (ETDEWEB)

Kleijnen, J.P.C.; Helton, J.C.

1999-04-01

The robustness of procedures for identifying patterns in scatterplots generated in Monte Carlo sensitivity analyses is investigated. These procedures are based on attempts to detect increasingly complex patterns in the scatterplots under consideration and involve the identification of (1) linear relationships with correlation coefficients, (2) monotonic relationships with rank correlation coefficients, (3) trends in central tendency as defined by means, medians and the Kruskal-Wallis statistic, (4) trends in variability as defined by variances and interquartile ranges, and (5) deviations from randomness as defined by the chi-square statistic. The following two topics related to the robustness of these procedures are considered for a sequence of example analyses with a large model for two-phase fluid flow: the presence of Type I and Type II errors, and the stability of results obtained with independent Latin hypercube samples. Observations from analysis include: (1) Type I errors are unavoidable, (2) Type II errors can occur when inappropriate analysis procedures are used, (3) physical explanations should always be sought for why statistical procedures identify variables as being important, and (4) the identification of important variables tends to be stable for independent Latin hypercube samples.

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

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.

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.

AP600 passive containment cooling system phenomena identification and ranking table

International Nuclear Information System (INIS)

Spencer, D.R.; Woodcock, Joel

1999-01-01

This paper presents the Phenomena Identification and Ranking Table (PIRT) used in the containment Design Basis Analysis (DBA) for the AP600 nuclear power plant. The PIRT is a tool generally applied to best estimate thermal hydraulic analyses. In the conservative analytical modeling approach used for the AP600 DBA containment pressure response, the PIRT was a tool used to show completeness and relevance of the test database in accordance with the Code of Federal Regulations for advanced plant design. Additionally, the ranking of phenomena by relative importance in a PIRT allows appropriate focusing of resources during model development and licensing review. The focus of the paper is on the organization and structure of the PIRT to show level of detail and format accepted for the AP600, for potential application to other containment designs or accident scenarios. Conclusions of general interest are discussed regarding table organization and structure, the process for developing relative ranking and incorporating expert opinion, and the definition and usage of the relative ranking in support of the conservative evaluation model. The AP600 containment evaluation model approach, as influenced by the relative rankings, is briefly described to put into context this unique application of the PIRT to a conservative methodology. The bases for relative ranking of each phenomenon, which included expert opinion, and quantitative results of scaling and testing, was submitted to the NRC as part of AP600-specific evaluations. Since a PIRT supports the sufficiency of both a testing program and analytical modeling, the process followed to generate and confirm the PIRT, an important part of the licensing acceptance, was a focus of extensive NRC review. General descriptions of key phenomena are provided to aid in understanding the containment PIRT for more general applications for containment evaluations of other PWR designs or for other scenarios. (author)

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.

Country-specific determinants of world university rankings.

Science.gov (United States)

Pietrucha, Jacek

2018-01-01

This paper examines country-specific factors that affect the three most influential world university rankings (the Academic Ranking of World Universities, the QS World University Ranking, and the Times Higher Education World University Ranking). We run a cross sectional regression that covers 42-71 countries (depending on the ranking and data availability). We show that the position of universities from a country in the ranking is determined by the following country-specific variables: economic potential of the country, research and development expenditure, long-term political stability (freedom from war, occupation, coups and major changes in the political system), and institutional variables, including government effectiveness.

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.

Concordance-based Kendall's Correlation for Computationally-Light vs. Computationally-Heavy Centrality Metrics: Lower Bound for Correlation

Directory of Open Access Journals (Sweden)

Natarajan Meghanathan

2017-01-01

Full Text Available We identify three different levels of correlation (pair-wise relative ordering, network-wide ranking and linear regression that could be assessed between a computationally-light centrality metric and a computationally-heavy centrality metric for real-world networks. The Kendall's concordance-based correlation measure could be used to quantitatively assess how well we could consider the relative ordering of two vertices vi and vj with respect to a computationally-light centrality metric as the relative ordering of the same two vertices with respect to a computationally-heavy centrality metric. We hypothesize that the pair-wise relative ordering (concordance-based assessment of the correlation between centrality metrics is the most strictest of all the three levels of correlation and claim that the Kendall's concordance-based correlation coefficient will be lower than the correlation coefficient observed with the more relaxed levels of correlation measures (linear regression-based Pearson's product-moment correlation coefficient and the network wide ranking-based Spearman's correlation coefficient. We validate our hypothesis by evaluating the three correlation coefficients between two sets of centrality metrics: the computationally-light degree and local clustering coefficient complement-based degree centrality metrics and the computationally-heavy eigenvector centrality, betweenness centrality and closeness centrality metrics for a diverse collection of 50 real-world networks.

Synchronous correlation matrices and Connes’ embedding conjecture

Energy Technology Data Exchange (ETDEWEB)

Dykema, Kenneth J., E-mail: kdykema@math.tamu.edu [Department of Mathematics, Texas A& M University, College Station, Texas 77843-3368 (United States); Paulsen, Vern, E-mail: vern@math.uh.edu [Department of Mathematics, University of Houston, Houston, Texas 77204 (United States)

2016-01-15

In the work of Paulsen et al. [J. Funct. Anal. (in press); preprint arXiv:1407.6918], the concept of synchronous quantum correlation matrices was introduced and these were shown to correspond to traces on certain C*-algebras. In particular, synchronous correlation matrices arose in their study of various versions of quantum chromatic numbers of graphs and other quantum versions of graph theoretic parameters. In this paper, we develop these ideas further, focusing on the relations between synchronous correlation matrices and microstates. We prove that Connes’ embedding conjecture is equivalent to the equality of two families of synchronous quantum correlation matrices. We prove that if Connes’ embedding conjecture has a positive answer, then the tracial rank and projective rank are equal for every graph. We then apply these results to more general non-local games.

RANKL/RANK/OPG cytokine receptor system: mRNA expression pattern in BPH, primary and metastatic prostate cancer disease.

Science.gov (United States)

Christoph, Frank; König, Frank; Lebentrau, Steffen; Jandrig, Burkhard; Krause, Hans; Strenziok, Romy; Schostak, Martin

2018-02-01

The cytokine system RANKL (receptor activator of NF-κB ligand), its receptor RANK and the antagonist OPG (osteoprotegerin) play a critical role in bone turnover. Our investigation was conducted to describe the gene expression at primary tumour site in prostate cancer patients and correlate the results with Gleason Score and PSA level. Seventy-one samples were obtained from prostate cancer patients at the time of radical prostatectomy and palliative prostate resection (n = 71). Patients with benign prostate hyperplasia served as controls (n = 60). We performed real-time RT-PCR after microdissection of the samples. The mRNA expression of RANK was highest in tumour tissue from patients with bone metastases (p BPH or locally confined tumours, also shown in clinical subgroups distinguished by Gleason Score (BPH tissue but did not exceed as much as in the tumour tissue. We demonstrated that RANK, RANKL and OPG are directly expressed by prostate cancer cells at the primary tumour site and showed a clear correlation with Gleason Score, serum PSA level and advanced disease. In BPH, mRNA expression is also detectable, but RANK expression does not exceed as much as compared to tumour tissue.

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

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.

Analysing the Correlations between Primary School Teachers' Teaching Styles and Their Critical Thinking Disposition

Science.gov (United States)

Sen, Özgür

2018-01-01

This study aims to analyse the correlations between teaching styles primary school teachers prefer to use and their critical thinking disposition. The research was conducted with the participation of 380 primary school teachers teaching in schools located in Ankara. The study employs relational survey model. In this study "Teaching Styles…

Inhibition of osteoclastogenesis by RNA interference targeting RANK

Directory of Open Access Journals (Sweden)

Ma Ruofan

2012-08-01

Full Text Available Abstract Background Osteoclasts and osteoblasts regulate bone resorption and formation to allow bone remodeling and homeostasis. The balance between bone resorption and formation is disturbed by abnormal recruitment of osteoclasts. Osteoclast differentiation is dependent on the receptor activator of nuclear factor NF-kappa B (RANK ligand (RANKL as well as the macrophage colony-stimulating factor (M-CSF. The RANKL/RANK system and RANK signaling induce osteoclast formation mediated by various cytokines. The RANK/RANKL pathway has been primarily implicated in metabolic, degenerative and neoplastic bone disorders or osteolysis. The central role of RANK/RANKL interaction in osteoclastogenesis makes RANK an attractive target for potential therapies in treatment of osteolysis. The purpose of this study was to assess the effect of inhibition of RANK expression in mouse bone marrow macrophages on osteoclast differentiation and bone resorption. Methods Three pairs of short hairpin RNAs (shRNA targeting RANK were designed and synthesized. The optimal shRNA was selected among three pairs of shRNAs by RANK expression analyzed by Western blot and Real-time PCR. We investigated suppression of osteoclastogenesis of mouse bone marrow macrophages (BMMs using the optimal shRNA by targeting RANK. Results Among the three shRANKs examined, shRANK-3 significantly suppressed [88.3%] the RANK expression (p Conclusions These findings suggest that retrovirus-mediated shRNA targeting RANK inhibits osteoclast differentiation and osteolysis. It may appear an attractive target for preventing osteolysis in humans with a potential clinical application.

Ranking of sabotage/tampering avoidance technology alternatives

Energy Technology Data Exchange (ETDEWEB)

Andrews, W.B.; Tabatabai, A.S.; Powers, T.B.; Daling, P.M.; Fecht, B.A.; Gore, B.F.; Overcast, T.D.; Rankin, W.R.; Schreiber, R.E.; Tawil, J.J.

1986-01-01

Pacific Northwest Laboratory conducted a study to evaluate alternatives to the design and operation of nuclear power plants, emphasizing a reduction of their vulnerability to sabotage. Estimates of core melt accident frequency during normal operations and from sabotage/tampering events were used to rank the alternatives. Core melt frequency for normal operations was estimated using sensitivity analysis of results of probabilistic risk assessments. Core melt frequency for sabotage/tampering was estimated by developing a model based on probabilistic risk analyses, historic data, engineering judgment, and safeguards analyses of plant locations where core melt events could be initiated. Results indicate the most effective alternatives focus on large areas of the plant, increase safety system redundancy, and reduce reliance on single locations for mitigation of transients. Less effective options focus on specific areas of the plant, reduce reliance on some plant areas for safe shutdown, and focus on less vulnerable targets.

Ranking of sabotage/tampering avoidance technology alternatives

International Nuclear Information System (INIS)

Andrews, W.B.; Tabatabai, A.S.; Powers, T.B.

1986-01-01

Pacific Northwest Laboratory conducted a study to evaluate alternatives to the design and operation of nuclear power plants, emphasizing a reduction of their vulnerability to sabotage. Estimates of core melt accident frequency during normal operations and from sabotage/tampering events were used to rank the alternatives. Core melt frequency for normal operations was estimated using sensitivity analysis of results of probabilistic risk assessments. Core melt frequency for sabotage/tampering was estimated by developing a model based on probabilistic risk analyses, historic data, engineering judgment, and safeguards analyses of plant locations where core melt events could be initiated. Results indicate the most effective alternatives focus on large areas of the plant, increase safety system redundancy, and reduce reliance on single locations for mitigation of transients. Less effective options focus on specific areas of the plant, reduce reliance on some plant areas for safe shutdown, and focus on less vulnerable targets

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.

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....

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....

A Universal Rank-Size Law

Science.gov (United States)

2016-01-01

A mere hyperbolic law, like the Zipf’s law power function, is often inadequate to describe rank-size relationships. An alternative theoretical distribution is proposed based on theoretical physics arguments starting from the Yule-Simon distribution. A modeling is proposed leading to a universal form. A theoretical suggestion for the “best (or optimal) distribution”, is provided through an entropy argument. The ranking of areas through the number of cities in various countries and some sport competition ranking serves for the present illustrations. PMID:27812192

Text mixing shapes the anatomy of rank-frequency distributions

Science.gov (United States)

Williams, Jake Ryland; Bagrow, James P.; Danforth, Christopher M.; Dodds, Peter Sheridan

2015-05-01

Natural languages are full of rules and exceptions. One of the most famous quantitative rules is Zipf's law, which states that the frequency of occurrence of a word is approximately inversely proportional to its rank. Though this "law" of ranks has been found to hold across disparate texts and forms of data, analyses of increasingly large corpora since the late 1990s have revealed the existence of two scaling regimes. These regimes have thus far been explained by a hypothesis suggesting a separability of languages into core and noncore lexica. Here we present and defend an alternative hypothesis that the two scaling regimes result from the act of aggregating texts. We observe that text mixing leads to an effective decay of word introduction, which we show provides accurate predictions of the location and severity of breaks in scaling. Upon examining large corpora from 10 languages in the Project Gutenberg eBooks collection, we find emphatic empirical support for the universality of our claim.

Multi-Label Classification Based on Low Rank Representation for Image Annotation

Directory of Open Access Journals (Sweden)

Qiaoyu Tan

2017-01-01

Full Text Available Annotating remote sensing images is a challenging task for its labor demanding annotation process and requirement of expert knowledge, especially when images can be annotated with multiple semantic concepts (or labels. To automatically annotate these multi-label images, we introduce an approach called Multi-Label Classification based on Low Rank Representation (MLC-LRR. MLC-LRR firstly utilizes low rank representation in the feature space of images to compute the low rank constrained coefficient matrix, then it adapts the coefficient matrix to define a feature-based graph and to capture the global relationships between images. Next, it utilizes low rank representation in the label space of labeled images to construct a semantic graph. Finally, these two graphs are exploited to train a graph-based multi-label classifier. To validate the performance of MLC-LRR against other related graph-based multi-label methods in annotating images, we conduct experiments on a public available multi-label remote sensing images (Land Cover. We perform additional experiments on five real-world multi-label image datasets to further investigate the performance of MLC-LRR. Empirical study demonstrates that MLC-LRR achieves better performance on annotating images than these comparing methods across various evaluation criteria; it also can effectively exploit global structure and label correlations of multi-label images.

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.

Block models and personalized PageRank.

Science.gov (United States)

Kloumann, Isabel M; Ugander, Johan; Kleinberg, Jon

2017-01-03

Methods for ranking the importance of nodes in a network have a rich history in machine learning and across domains that analyze structured data. Recent work has evaluated these methods through the "seed set expansion problem": given a subset [Formula: see text] of nodes from a community of interest in an underlying graph, can we reliably identify the rest of the community? We start from the observation that the most widely used techniques for this problem, personalized PageRank and heat kernel methods, operate in the space of "landing probabilities" of a random walk rooted at the seed set, ranking nodes according to weighted sums of landing probabilities of different length walks. Both schemes, however, lack an a priori relationship to the seed set objective. In this work, we develop a principled framework for evaluating ranking methods by studying seed set expansion applied to the stochastic block model. We derive the optimal gradient for separating the landing probabilities of two classes in a stochastic block model and find, surprisingly, that under reasonable assumptions the gradient is asymptotically equivalent to personalized PageRank for a specific choice of the PageRank parameter [Formula: see text] that depends on the block model parameters. This connection provides a formal motivation for the success of personalized PageRank in seed set expansion and node ranking generally. We use this connection to propose more advanced techniques incorporating higher moments of landing probabilities; our advanced methods exhibit greatly improved performance, despite being simple linear classification rules, and are even competitive with belief propagation.

A framework for automatic information quality ranking of diabetes websites.

Science.gov (United States)

Belen Sağlam, Rahime; Taskaya Temizel, Tugba

2015-01-01

Objective: When searching for particular medical information on the internet the challenge lies in distinguishing the websites that are relevant to the topic, and contain accurate information. In this article, we propose a framework that automatically identifies and ranks diabetes websites according to their relevance and information quality based on the website content. Design: The proposed framework ranks diabetes websites according to their content quality, relevance and evidence based medicine. The framework combines information retrieval techniques with a lexical resource based on Sentiwordnet making it possible to work with biased and untrusted websites while, at the same time, ensuring the content relevance. Measurement: The evaluation measurements used were Pearson-correlation, true positives, false positives and accuracy. We tested the framework with a benchmark data set consisting of 55 websites with varying degrees of information quality problems. Results: The proposed framework gives good results that are comparable with the non-automated information quality measuring approaches in the literature. The correlation between the results of the proposed automated framework and ground-truth is 0.68 on an average with p < 0.001 which is greater than the other proposed automated methods in the literature (r score in average is 0.33).

VHB-JOURQUAL2: Method, Results, and Implications of the German Academic Association for Business Research's Journal Ranking

OpenAIRE

Schrader, Ulf; Hennig-Thurau, Thorsten

2009-01-01

VHB-JOURQUAL represents the official journal ranking of the German Academic Association for Business Research. Since its introduction in 2003, the ranking has become the most influential journal evaluation approach in German-speaking countries, impacting several key managerial decisions of German, Austrian, and Swiss business schools. This article reports the methodological approach of the ranking’s second edition. It also presents the main results and additional analyses on the validity of t...

A Versatile Software Package for Inter-subject Correlation Based Analyses of fMRI

Directory of Open Access Journals (Sweden)

Jukka-Pekka eKauppi

2014-01-01

Full Text Available In the inter-subject correlation (ISC based analysis of the functional magnetic resonance imaging (fMRI data, the extent of shared processing across subjects during the experiment is determined by calculating correlation coefficients between the fMRI time series of the subjects in the corresponding brain locations. This implies that ISC can be used to analyze fMRI data without explicitly modelling the stimulus and thus ISC is a potential method to analyze fMRI data acquired under complex naturalistic stimuli. Despite of the suitability of ISC based approach to analyze complex fMRI data, no generic software tools have been made available for this purpose, limiting a widespread use of ISC based analysis techniques among neuroimaging community. In this paper, we present a graphical user interface (GUI based software package, ISC Toolbox, implemented in Matlab for computing various ISC based analyses. Many advanced computations such as comparison of ISCs between different stimuli, time window ISC, and inter-subject phase synchronization are supported by the toolbox. The analyses are coupled with re-sampling based statistical inference. The ISC based analyses are data and computation intensive and the ISC toolbox is equipped with mechanisms to execute the parallel computations in a cluster environment automatically and with an automatic detection of the cluster environment in use. Currently, SGE-based (Oracle Grid Engine, Son of a Grid Engine or Open Grid Scheduler and Slurm environments are supported. In this paper, we present a detailed account on the methods behind the ISC Toolbox, the implementation of the toolbox and demonstrate the possible use of the toolbox by summarizing selected example applications. We also report the computation time experiments both using a single desktop computer and two grid environments demonstrating that parallelization effectively reduces the computing time. The ISC Toolbox is available in https://code.google.com/p/isc-toolbox/.

A versatile software package for inter-subject correlation based analyses of fMRI.

Science.gov (United States)

Kauppi, Jukka-Pekka; Pajula, Juha; Tohka, Jussi

2014-01-01

In the inter-subject correlation (ISC) based analysis of the functional magnetic resonance imaging (fMRI) data, the extent of shared processing across subjects during the experiment is determined by calculating correlation coefficients between the fMRI time series of the subjects in the corresponding brain locations. This implies that ISC can be used to analyze fMRI data without explicitly modeling the stimulus and thus ISC is a potential method to analyze fMRI data acquired under complex naturalistic stimuli. Despite of the suitability of ISC based approach to analyze complex fMRI data, no generic software tools have been made available for this purpose, limiting a widespread use of ISC based analysis techniques among neuroimaging community. In this paper, we present a graphical user interface (GUI) based software package, ISC Toolbox, implemented in Matlab for computing various ISC based analyses. Many advanced computations such as comparison of ISCs between different stimuli, time window ISC, and inter-subject phase synchronization are supported by the toolbox. The analyses are coupled with re-sampling based statistical inference. The ISC based analyses are data and computation intensive and the ISC toolbox is equipped with mechanisms to execute the parallel computations in a cluster environment automatically and with an automatic detection of the cluster environment in use. Currently, SGE-based (Oracle Grid Engine, Son of a Grid Engine, or Open Grid Scheduler) and Slurm environments are supported. In this paper, we present a detailed account on the methods behind the ISC Toolbox, the implementation of the toolbox and demonstrate the possible use of the toolbox by summarizing selected example applications. We also report the computation time experiments both using a single desktop computer and two grid environments demonstrating that parallelization effectively reduces the computing time. The ISC Toolbox is available in https://code.google.com/p/isc-toolbox/

Adiabatic quantum algorithm for search engine ranking.

Science.gov (United States)

Garnerone, Silvano; Zanardi, Paolo; Lidar, Daniel A

2012-06-08

We propose an adiabatic quantum algorithm for generating a quantum pure state encoding of the PageRank vector, the most widely used tool in ranking the relative importance of internet pages. We present extensive numerical simulations which provide evidence that this algorithm can prepare the quantum PageRank state in a time which, on average, scales polylogarithmically in the number of web pages. We argue that the main topological feature of the underlying web graph allowing for such a scaling is the out-degree distribution. The top-ranked log(n) entries of the quantum PageRank state can then be estimated with a polynomial quantum speed-up. Moreover, the quantum PageRank state can be used in "q-sampling" protocols for testing properties of distributions, which require exponentially fewer measurements than all classical schemes designed for the same task. This can be used to decide whether to run a classical update of the PageRank.

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.

Improved efficacy of soluble human receptor activator of nuclear factor kappa B (RANK) fusion protein by site-directed mutagenesis.

Science.gov (United States)

Son, Young Jun; Han, Jihye; Lee, Jae Yeon; Kim, HaHyung; Chun, Taehoon

2015-06-01

Soluble human receptor activator of nuclear factor kappa B fusion immunoglobulin (hRANK-Ig) has been considered as one of the therapeutic agents to treat osteoporosis or diseases associated with bone destruction by blocking the interaction between RANK and the receptor activator of nuclear factor kappa B ligand (RANKL). However, no scientific record showing critical amino acid residues within the structural interface between the human RANKL and RANK complex is yet available. In this study, we produced several mutants of hRANK-Ig by replacement of amino acid residue(s) and tested whether the mutants had increased binding affinity to human RANKL. Based on the results from flow cytometry and surface plasmon resonance analyses, the replacement of E(125) with D(125), or E(125) and C(127) with D(125) and F(127) within loop 3 of cysteine-rich domain 3 of hRANK-Ig increases binding affinity to human RANKL over the wild-type hRANK-Ig. This result may provide the first example of improvement in the efficacy of hRANK-Ig by protein engineering and may give additional information to understand a more defined structural interface between hRANK and RANKL.

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.

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.

Contests with rank-order spillovers

NARCIS (Netherlands)

M.R. Baye (Michael); D. Kovenock (Dan); C.G. de Vries (Casper)

2012-01-01

textabstractThis paper presents a unified framework for characterizing symmetric equilibrium in simultaneous move, two-player, rank-order contests with complete information, in which each player's strategy generates direct or indirect affine "spillover" effects that depend on the rank-order of her

Development of a multi-criteria assessment model for ranking of renewable and non-renewable transportation fuel vehicles

International Nuclear Information System (INIS)

Safaei Mohamadabadi, H.; Tichkowsky, G.; Kumar, A.

2009-01-01

Several factors, including economical, environmental, and social factors, are involved in selection of the best fuel-based vehicles for road transportation. This leads to a multi-criteria selection problem for multi-alternatives. In this study, a multi-criteria assessment model was developed to rank different road transportation fuel-based vehicles (both renewable and non-renewable) using a method called Preference Ranking Organization Method for Enrichment and Evaluations (PROMETHEE). This method combines qualitative and quantitative criteria to rank various alternatives. In this study, vehicles based on gasoline, gasoline-electric (hybrid), E85 ethanol, diesel, B100 biodiesel, and compressed natural gas (CNG) were considered as alternatives. These alternatives were ranked based on five criteria: vehicle cost, fuel cost, distance between refueling stations, number of vehicle options available to the consumer, and greenhouse gas (GHG) emissions per unit distance traveled. In addition, sensitivity analyses were performed to study the impact of changes in various parameters on final ranking. Two base cases and several alternative scenarios were evaluated. In the base case scenario with higher weight on economical parameters, gasoline-based vehicle was ranked higher than other vehicles. In the base case scenario with higher weight on environmental parameters, hybrid vehicle was ranked first followed by biodiesel-based vehicle

Development of a multi-criteria assessment model for ranking of renewable and non-renewable transportation fuel vehicles

Energy Technology Data Exchange (ETDEWEB)

Safaei Mohamadabadi, H.; Tichkowsky, G.; Kumar, A. [Department of Mechanical Engineering, University of Alberta, Edmonton, Alberta (Canada)

2009-01-15

Several factors, including economical, environmental, and social factors, are involved in selection of the best fuel-based vehicles for road transportation. This leads to a multi-criteria selection problem for multi-alternatives. In this study, a multi-criteria assessment model was developed to rank different road transportation fuel-based vehicles (both renewable and non-renewable) using a method called Preference Ranking Organization Method for Enrichment and Evaluations (PROMETHEE). This method combines qualitative and quantitative criteria to rank various alternatives. In this study, vehicles based on gasoline, gasoline-electric (hybrid), E85 ethanol, diesel, B100 biodiesel, and compressed natural gas (CNG) were considered as alternatives. These alternatives were ranked based on five criteria: vehicle cost, fuel cost, distance between refueling stations, number of vehicle options available to the consumer, and greenhouse gas (GHG) emissions per unit distance traveled. In addition, sensitivity analyses were performed to study the impact of changes in various parameters on final ranking. Two base cases and several alternative scenarios were evaluated. In the base case scenario with higher weight on economical parameters, gasoline-based vehicle was ranked higher than other vehicles. In the base case scenario with higher weight on environmental parameters, hybrid vehicle was ranked first followed by biodiesel-based vehicle. (author)

Comparison of Anthropometry and Lower Limb Power Qualities According to Different Levels and Ranking Position of Competitive Surfers.

Science.gov (United States)

Fernandez-Gamboa, Iosu; Yanci, Javier; Granados, Cristina; Camara, Jesus

2017-08-01

Fernandez-Gamboa, I, Yanci, J, Granados, C, and Camara, J. Comparison of anthropometry and lower limb power qualities according to different levels and ranking position of competitive surfers. J Strength Cond Res 31(8): 2231-2237, 2017-The aim of this study was to compare competitive surfers' lower limb power output depending on their competitive level, and to evaluate the association between competition rankings. Twenty competitive surfers were divided according to the competitive level as follows: international (INT) or national (NAT), and competitive ranking (RANK1-50 or RANK51-100). Vertical jump and maximal peak power of the lower limbs were measured. No differences were found between INT and NAT surfers in the anthropometric variables, in the vertical jump, or in lower extremity power; although the NAT group had higher levels on the elasticity index, squat jumps (SJs), and counter movement jumps (CMJs) compared with the INT group. The RANK1-50 group had a lower biceps skinfold (p RANK1-50 group. Moderate to large significant correlations were obtained between the surfers' ranking position and some skinfolds, the sum of skinfolds, and vertical jump. Results demonstrate that surfers' physical performance seems to be an accurate indicator of ranking positioning, also revealing that vertical jump capacity and anthropometric variables play an important role in their competitive performance, which may be important when considering their power training.

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.

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.

Importance of intrinsic and non-network contribution in PageRank centrality and its effect on PageRank localization

OpenAIRE

Deyasi, Krishanu

2016-01-01

PageRank centrality is used by Google for ranking web-pages to present search result for a user query. Here, we have shown that PageRank value of a vertex also depends on its intrinsic, non-network contribution. If the intrinsic, non-network contributions of the vertices are proportional to their degrees or zeros, then their PageRank centralities become proportion to their degrees. Some simulations and empirical data are used to support our study. In addition, we have shown that localization ...

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

Correlation and regression analyses of genetic effects for different types of cells in mammals under radiation and chemical treatment

International Nuclear Information System (INIS)

Slutskaya, N.G.; Mosseh, I.B.

2006-01-01

Data about genetic mutations under radiation and chemical treatment for different types of cells have been analyzed with correlation and regression analyses. Linear correlation between different genetic effects in sex cells and somatic cells have found. The results may be extrapolated on sex cells of human and mammals. (authors)

A DYNAMIC FEATURE SELECTION METHOD FOR DOCUMENT RANKING WITH RELEVANCE FEEDBACK APPROACH

Directory of Open Access Journals (Sweden)

K. Latha

2010-07-01

Full Text Available Ranking search results is essential for information retrieval and Web search. Search engines need to not only return highly relevant results, but also be fast to satisfy users. As a result, not all available features can be used for ranking, and in fact only a small percentage of these features can be used. Thus, it is crucial to have a feature selection mechanism that can find a subset of features that both meets latency requirements and achieves high relevance. In this paper we describe a 0/1 knapsack procedure for automatically selecting features to use within Generalization model for Document Ranking. We propose an approach for Relevance Feedback using Expectation Maximization method and evaluate the algorithm on the TREC Collection for describing classes of feedback textual information retrieval features. Experimental results, evaluated on standard TREC-9 part of the OHSUMED collections, show that our feature selection algorithm produces models that are either significantly more effective than, or equally effective as, models such as Markov Random Field model, Correlation Co-efficient and Count Difference method

Measurement of Rank and Other Properties of Direct and Scattered Signals

Directory of Open Access Journals (Sweden)

Svante Björklund

2016-01-01

Full Text Available We have designed an experiment for low-cost indoor measurements of rank and other properties of direct and scattered signals with radar interference suppression in mind. The signal rank is important also in many other applications, for example, DOA (Direction of Arrival estimation, estimation of the number of and location of transmitters in electronic warfare, and increasing the capacity in wireless communications. In real radar applications, such measurements can be very expensive, for example, involving airborne radars with array antennas. We have performed the measurements in an anechoic chamber with several transmitters, a receiving array antenna, and a moving reflector. Our experiment takes several aspects into account: transmitted signals with different correlation, decorrelation of the signals during the acquisition interval, covariance matrix estimation, noise eigenvalue spread, calibration, near-field compensation, scattering in a rough surface, and good control of the influencing factors. With our measurements we have observed rank, DOA spectrum, and eigenpatterns of direct and scattered signals. The agreement of our measured properties with theoretic and simulated results in the literature shows that our experiment is realistic and sound. The detailed description of our experiment could serve as help for conducting other well-controlled experiments.

Customer love: Research on the ranking of food and beverage locations

Directory of Open Access Journals (Sweden)

Bahar Türk

2015-09-01

Full Text Available Intense competition in today’s markets has meant that customer loyalty is no longer as strong as it used to be. In this context, many researchers have aimed to add new values to the concept of loyalty, particularly focusing on the concept of “love”. This study explores customers’ feelings towards location in order to identify their preferred - or “most loved” - food and beverage locations. A questionnaire was administered to 395 adult customers living in the city centre of Erzurum, Turkey. The fuzzy Shannon’s entropy method is used to identify the weights of each criterion of love, while the fuzzy VIKOR method is used to rank alternative locations. As a result of the analyses, the most prominent expression was found as “I love this location!”, and customers’ most loved places were identified as those serving regional dishes in Erzurum Province, Turkey. The study uses fuzzy numbers to rank alternatives according to the criteria of love. In addition, the ranking is based on degrees of fuzziness by changing the α-cut levels of the fuzzy numbers. The study examines how customers’ preferences between alternatives alter via this change

Perturbation theory for nematic liquid crystals of axially symmetric molecules: Evaluation of fourth rank orientational order parameter

International Nuclear Information System (INIS)

Singh, K.

1993-11-01

Using a statistical mechanical perturbation theory for isotropic-nematic transition we report a calculation of second and fourth rank orientation order parameters and thermodynamic properties for a model system of prolate ellipsoids of revolution parameterized by its length-to-width ratio. The influence of attractive potential represented by dispersion interaction on a variety of thermodynamic properties is analysed. Inclusion of fourth rank orientational order parameter in calculation slightly changes the transition parameter. (author). 7 refs, 1 tab

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.

Reading Comprehension and Phonics Research: Review of Correlational Analyses with Deaf and Hard-of-Hearing Students

Science.gov (United States)

Luft, Pamela

2018-01-01

This manuscript reviews 28 studies of reading research on deaf and hard-of-hearing (DHH) students published since 2000 that used correlational analyses. The examination focused on assessment issues affecting measurement and analysis of relationships between early phonological or orthographic skills and reading comprehension. Mixed outcomes…

Journal Rankings by Health Management Faculty Members: Are There Differences by Rank, Leadership Status, or Area of Expertise?

Science.gov (United States)

Menachemi, Nir; Hogan, Tory H; DelliFraine, Jami L

2015-01-01

Health administration (HA) faculty members publish in a variety of journals, including journals focused on management, economics, policy, and information technology. HA faculty members are evaluated on the basis of the quality and quantity of their journal publications. However, it is unclear how perceptions of these journals vary by subdiscipline, department leadership role, or faculty rank. It is also not clear how perceptions of journals may have changed over the past decade since the last evaluation of journal rankings in the field was published. The purpose of the current study is to examine how respondents rank journals in the field of HA, as well as the variation in perception by academic rank, department leadership status, and area of expertise. Data were drawn from a survey of HA faculty members at U.S. universities, which was completed in 2012. Different journal ranking patterns were noted for faculty members of different subdisciplines. The health management-oriented journals (Health Care Management Review and Journal of Healthcare Management) were ranked higher than in previous research, suggesting that journal ranking perceptions may have changed over the intervening decade. Few differences in perceptions were noted by academic rank, but we found that department chairs were more likely than others to select Health Affairs in their top three most prestigious journals (β = 0.768; p journal prestige varied between a department chair and untenured faculty in different disciplines, and this perceived difference could have implications for promotion and tenure decisions.

Algebraic and computational aspects of real tensor ranks

CERN Document Server

Sakata, Toshio; Miyazaki, Mitsuhiro

2016-01-01

This book provides comprehensive summaries of theoretical (algebraic) and computational aspects of tensor ranks, maximal ranks, and typical ranks, over the real number field. Although tensor ranks have been often argued in the complex number field, it should be emphasized that this book treats real tensor ranks, which have direct applications in statistics. The book provides several interesting ideas, including determinant polynomials, determinantal ideals, absolutely nonsingular tensors, absolutely full column rank tensors, and their connection to bilinear maps and Hurwitz-Radon numbers. In addition to reviews of methods to determine real tensor ranks in details, global theories such as the Jacobian method are also reviewed in details. The book includes as well an accessible and comprehensive introduction of mathematical backgrounds, with basics of positive polynomials and calculations by using the Groebner basis. Furthermore, this book provides insights into numerical methods of finding tensor ranks through...

Alternatives to Pearson's and Spearman's Correlation Coefficients

OpenAIRE

Smarandache, Florentin

2008-01-01

This article presents several alternatives to Pearson's correlation coefficient and many examples. In the samples where the rank in a discrete variable counts more than the variable values, the mixtures that we propose of Pearson's and Spearman's correlation coefficients give better results.

Co-integration Rank Testing under Conditional Heteroskedasticity

DEFF Research Database (Denmark)

Cavaliere, Guiseppe; Rahbæk, Anders; Taylor, A.M. Robert

null distributions of the rank statistics coincide with those derived by previous authors who assume either i.i.d. or (strict and covariance) stationary martingale difference innovations. We then propose wild bootstrap implementations of the co-integrating rank tests and demonstrate that the associated...... bootstrap rank statistics replicate the first-order asymptotic null distributions of the rank statistics. We show the same is also true of the corresponding rank tests based on the i.i.d. bootstrap of Swensen (2006). The wild bootstrap, however, has the important property that, unlike the i.i.d. bootstrap......, it preserves in the re-sampled data the pattern of heteroskedasticity present in the original shocks. Consistent with this, numerical evidence sug- gests that, relative to tests based on the asymptotic critical values or the i.i.d. bootstrap, the wild bootstrap rank tests perform very well in small samples un...

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.

Tile Low Rank Cholesky Factorization for Climate/Weather Modeling Applications on Manycore Architectures

KAUST Repository

Akbudak, Kadir; Ltaief, Hatem; Mikhalev, Aleksandr; Keyes, David E.

2017-01-01

Covariance matrices are ubiquitous in computational science and engineering. In particular, large covariance matrices arise from multivariate spatial data sets, for instance, in climate/weather modeling applications to improve prediction using statistical methods and spatial data. One of the most time-consuming computational steps consists in calculating the Cholesky factorization of the symmetric, positive-definite covariance matrix problem. The structure of such covariance matrices is also often data-sparse, in other words, effectively of low rank, though formally dense. While not typically globally of low rank, covariance matrices in which correlation decays with distance are nearly always hierarchically of low rank. While symmetry and positive definiteness should be, and nearly always are, exploited for performance purposes, exploiting low rank character in this context is very recent, and will be a key to solving these challenging problems at large-scale dimensions. The authors design a new and flexible tile row rank Cholesky factorization and propose a high performance implementation using OpenMP task-based programming model on various leading-edge manycore architectures. Performance comparisons and memory footprint saving on up to 200K×200K covariance matrix size show a gain of more than an order of magnitude for both metrics, against state-of-the-art open-source and vendor optimized numerical libraries, while preserving the numerical accuracy fidelity of the original model. This research represents an important milestone in enabling large-scale simulations for covariance-based scientific applications.

Tile Low Rank Cholesky Factorization for Climate/Weather Modeling Applications on Manycore Architectures

KAUST Repository

Akbudak, Kadir

2017-05-11

Covariance matrices are ubiquitous in computational science and engineering. In particular, large covariance matrices arise from multivariate spatial data sets, for instance, in climate/weather modeling applications to improve prediction using statistical methods and spatial data. One of the most time-consuming computational steps consists in calculating the Cholesky factorization of the symmetric, positive-definite covariance matrix problem. The structure of such covariance matrices is also often data-sparse, in other words, effectively of low rank, though formally dense. While not typically globally of low rank, covariance matrices in which correlation decays with distance are nearly always hierarchically of low rank. While symmetry and positive definiteness should be, and nearly always are, exploited for performance purposes, exploiting low rank character in this context is very recent, and will be a key to solving these challenging problems at large-scale dimensions. The authors design a new and flexible tile row rank Cholesky factorization and propose a high performance implementation using OpenMP task-based programming model on various leading-edge manycore architectures. Performance comparisons and memory footprint saving on up to 200K×200K covariance matrix size show a gain of more than an order of magnitude for both metrics, against state-of-the-art open-source and vendor optimized numerical libraries, while preserving the numerical accuracy fidelity of the original model. This research represents an important milestone in enabling large-scale simulations for covariance-based scientific applications.

Perils of parsimony: properties of reduced-rank estimates of genetic covariance matrices.

Science.gov (United States)

Meyer, Karin; Kirkpatrick, Mark

2008-10-01

Eigenvalues and eigenvectors of covariance matrices are important statistics for multivariate problems in many applications, including quantitative genetics. Estimates of these quantities are subject to different types of bias. This article reviews and extends the existing theory on these biases, considering a balanced one-way classification and restricted maximum-likelihood estimation. Biases are due to the spread of sample roots and arise from ignoring selected principal components when imposing constraints on the parameter space, to ensure positive semidefinite estimates or to estimate covariance matrices of chosen, reduced rank. In addition, it is shown that reduced-rank estimators that consider only the leading eigenvalues and -vectors of the "between-group" covariance matrix may be biased due to selecting the wrong subset of principal components. In a genetic context, with groups representing families, this bias is inverse proportional to the degree of genetic relationship among family members, but is independent of sample size. Theoretical results are supplemented by a simulation study, demonstrating close agreement between predicted and observed bias for large samples. It is emphasized that the rank of the genetic covariance matrix should be chosen sufficiently large to accommodate all important genetic principal components, even though, paradoxically, this may require including a number of components with negligible eigenvalues. A strategy for rank selection in practical analyses is outlined.

Model of Decision Making through Consensus in Ranking Case

Science.gov (United States)

Tarigan, Gim; Darnius, Open

2018-01-01

The basic problem to determine ranking consensus is a problem to combine some rankings those are decided by two or more Decision Maker (DM) into ranking consensus. DM is frequently asked to present their preferences over a group of objects in terms of ranks, for example to determine a new project, new product, a candidate in a election, and so on. The problem in ranking can be classified into two major categories; namely, cardinal and ordinal rankings. The objective of the study is to obtin the ranking consensus by appying some algorithms and methods. The algorithms and methods used in this study were partial algorithm, optimal ranking consensus, BAK (Borde-Kendal)Model. A method proposed as an alternative in ranking conssensus is a Weighted Distance Forward-Backward (WDFB) method, which gave a little difference i ranking consensus result compare to the result oethe example solved by Cook, et.al (2005).

The Privilege of Ranking: Google Plays Ball.

Science.gov (United States)

Wiggins, Richard

2003-01-01

Discussion of ranking systems used in various settings, including college football and academic admissions, focuses on the Google search engine. Explains the PageRank mathematical formula that scores Web pages by connecting the number of links; limitations, including authenticity and accuracy of ranked Web pages; relevancy; adjusting algorithms;…

Probabilistic relation between In-Degree and PageRank

NARCIS (Netherlands)

Litvak, Nelli; Scheinhardt, Willem R.W.; Volkovich, Y.

2008-01-01

This paper presents a novel stochastic model that explains the relation between power laws of In-Degree and PageRank. PageRank is a popularity measure designed by Google to rank Web pages. We model the relation between PageRank and In-Degree through a stochastic equation, which is inspired by the

Generalized PageRank on Directed Configuration Networks

NARCIS (Netherlands)

Chen, Ningyuan; Litvak, Nelli; Olvera-Cravioto, Mariana

2017-01-01

Note: formula is not displayed correctly. This paper studies the distribution of a family of rankings, which includes Google’s PageRank, on a directed configuration model. In particular, it is shown that the distribution of the rank of a randomly chosen node in the graph converges in distribution to

Multi-criteria Ranking Under Pareto Inclusive Criterion of Preference: An Application in Ranking Some Fungi Species with Respect to Their Toxicity

Directory of Open Access Journals (Sweden)

Gniadek Agnieszka

2014-12-01

Full Text Available This study aims at demonstrating the usefulness of the Pareto in- clusive criterion methodology for comparative analyses of fungi toxicity. The toxicity of fungi is usually measured using a scale of several ranks. In practice, the ranks of toxicity are routinely grouped into only four conventional classes of toxicity: from a class of no toxicity, low toxicity, and moderate toxicity, to a class of high toxicity. The illustrative material included the N = 61 fungi samples obtained from three species: A. ochraceus, A. niger and A. flavus. In accordance with the Pareto approach, four partial criterions of the worst toxi- city were defined, a single criterion used for each conventional class of toxicity. Finally, the odds ratios (OR were calculated separately for each partial cri- terion, and the significance of the hypotheses OR = 1 was estimated. It was stated that A. ochraceus fungi are distinctly more toxic than the two remaining ones with respect to the all considered four partial criterions, with significance equal to p = 0.04, p = 0.04, p = 0.007 and p = 0.005, respectively. Thus, the suggested method illustrated its utility in the case under study.

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...

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.

The structure of completely positive matrices according to their CP-rank and CP-plus-rank

NARCIS (Netherlands)

Dickinson, Peter James Clair; Bomze, Immanuel M.; Still, Georg J.

2015-01-01

We study the topological properties of the cp-rank operator $\\mathrm{cp}(A)$ and the related cp-plus-rank operator $\\mathrm{cp}^+(A)$ (which is introduced in this paper) in the set $\\mathcal{S}^n$ of symmetric $n\\times n$-matrices. For the set of completely positive matrices, $\\mathcal{CP}^n$, we

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....

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.

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…

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…

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

The BiPublishers ranking: Main results and methodological problems when constructing rankings of academic publishers

Directory of Open Access Journals (Sweden)

Torres-Salinas, Daniel

2015-12-01

Full Text Available We present the results of the Bibliometric Indicators for Publishers project (also known as BiPublishers. This project represents the first attempt to systematically develop bibliometric publisher rankings. The data for this project was derived from the Book Citation Index and the study time period was 2009-2013. We have developed 42 rankings: 4 by fields and 38 by disciplines. We display six indicators for publishers divided into three types: output, impact and publisher’s profile. The aim is to capture different characteristics of the research performance of publishers. 254 publishers were processed and classified according to publisher type: commercial publishers and university presses. We present the main publishers by field and then discuss the principal challenges presented when developing this type of tool. The BiPublishers ranking is an on-going project which aims to develop and explore new data sources and indicators to better capture and define the research impact of publishers.Presentamos los resultados del proyecto Bibliometric Indicators for Publishers (BiPublishers. Es el primer proyecto que desarrolla de manera sistemática rankings bibliométricos de editoriales. La fuente de datos empleada es el Book Citation Index y el periodo de análisis 2009-2013. Se presentan 42 rankings: 4 por áreas y 38 por disciplinas. Mostramos seis indicadores por editorial divididos según su tipología: producción, impacto y características editoriales. Se procesaron 254 editoriales y se clasificaron según el tipo: comerciales y universitarias. Se presentan las principales editoriales por áreas. Después, se discuten los principales retos a superar en el desarrollo de este tipo de herramientas. El ranking Bipublishers es un proyecto en desarrollo que persigue analizar y explorar nuevas fuentes de datos e indicadores para captar y definir el impacto de las editoriales académicas.

Correlated statistical uncertainties in coded-aperture imaging

International Nuclear Information System (INIS)

Fleenor, Matthew C.; Blackston, Matthew A.; Ziock, Klaus P.

2015-01-01

In nuclear security applications, coded-aperture imagers can provide a wealth of information regarding the attributes of both the radioactive and nonradioactive components of the objects being imaged. However, for optimum benefit to the community, spatial attributes need to be determined in a quantitative and statistically meaningful manner. To address a deficiency of quantifiable errors in coded-aperture imaging, we present uncertainty matrices containing covariance terms between image pixels for MURA mask patterns. We calculated these correlated uncertainties as functions of variation in mask rank, mask pattern over-sampling, and whether or not anti-mask data are included. Utilizing simulated point source data, we found that correlations arose when two or more image pixels were summed. Furthermore, we found that the presence of correlations was heightened by the process of over-sampling, while correlations were suppressed by the inclusion of anti-mask data and with increased mask rank. As an application of this result, we explored how statistics-based alarming is impacted in a radiological search scenario

PageRank in scale-free random graphs

NARCIS (Netherlands)

Chen, Ningyuan; Litvak, Nelli; Olvera-Cravioto, Mariana; Bonata, Anthony; Chung, Fan; Pralat, Paweł

2014-01-01

We analyze the distribution of PageRank on a directed configuration model and show that as the size of the graph grows to infinity, the PageRank of a randomly chosen node can be closely approximated by the PageRank of the root node of an appropriately constructed tree. This tree approximation is in

46 CFR 282.11 - Ranking of flags.

Science.gov (United States)

2010-10-01

... 46 Shipping 8 2010-10-01 2010-10-01 false Ranking of flags. 282.11 Section 282.11 Shipping... COMMERCE OF THE UNITED STATES Foreign-Flag Competition § 282.11 Ranking of flags. The operators under each... priority of costs which are representative of the flag. For liner cargo vessels, the ranking of operators...

Ranking Businesses and Municipal Locations by Spatiotemporal Cardiac Arrest Risk to Guide Public Defibrillator Placement.

Science.gov (United States)

Sun, Christopher L F; Brooks, Steven C; Morrison, Laurie J; Chan, Timothy C Y

2017-03-21

Efforts to guide automated external defibrillator placement for out-of-hospital cardiac arrest (OHCA) treatment have focused on identifying broadly defined location categories without considering hours of operation. Broad location categories may be composed of many businesses with varying accessibility. Identifying specific locations for automated external defibrillator deployment incorporating operating hours and time of OHCA occurrence may improve automated external defibrillator accessibility. We aim to identify specific businesses and municipal locations that maximize OHCA coverage on the basis of spatiotemporal assessment of OHCA risk in the immediate vicinity of franchise locations. This study was a retrospective population-based cohort study using data from the Toronto Regional RescuNET Epistry cardiac arrest database. We identified all nontraumatic public OHCAs occurring in Toronto, ON, Canada, from January 2007 through December 2015. We identified 41 unique businesses and municipal location types with ≥20 locations in Toronto from the YellowPages, Canadian Franchise Association, and the City of Toronto Open Data Portal. We obtained their geographic coordinates and hours of operation from Web sites, by phone, or in person. We determined the number of OHCAs that occurred within 100 m of each location when it was open (spatiotemporal coverage) for Toronto overall and downtown. The businesses and municipal locations were then ranked by spatiotemporal OHCA coverage. To evaluate temporal stability of the rankings, we calculated intraclass correlation of the annual coverage values. There were 2654 nontraumatic public OHCAs. Tim Hortons ranked first in Toronto, covering 286 OHCAs. Starbucks ranked first in downtown, covering 110 OHCAs. Coffee shops and bank machines from the 5 largest Canadian banks occupied 8 of the top 10 spots in both Toronto and downtown. The rankings exhibited high temporal stability with intraclass correlation values of 0.88 (95

Low-ranking female Japanese macaques make efforts for social grooming.

Science.gov (United States)

Kurihara, Yosuke

2016-04-01

Grooming is essential to build social relationships in primates. Its importance is universal among animals from different ranks; however, rank-related differences in feeding patterns can lead to conflicts between feeding and grooming in low-ranking animals. Unifying the effects of dominance rank on feeding and grooming behaviors contributes to revealing the importance of grooming. Here, I tested whether the grooming behavior of low-ranking females were similar to that of high-ranking females despite differences in their feeding patterns. I followed 9 Japanese macaques Macaca fuscata fuscata adult females from the Arashiyama group, and analyzed the feeding patterns and grooming behaviors of low- and high-ranking females. Low-ranking females fed on natural foods away from the provisioning site, whereas high-ranking females obtained more provisioned food at the site. Due to these differences in feeding patterns, low-ranking females spent less time grooming than high-ranking females. However, both low- and high-ranking females performed grooming around the provisioning site, which was linked to the number of neighboring individuals for low-ranking females and feeding on provisioned foods at the site for high-ranking females. The similarity in grooming area led to a range and diversity of grooming partners that did not differ with rank. Thus, low-ranking females can obtain small amounts of provisioned foods and perform grooming with as many partners around the provisioning site as high-ranking females. These results highlight the efforts made by low-ranking females to perform grooming and suggest the importance of grooming behavior in group-living primates.

Low-ranking female Japanese macaques make efforts for social grooming

Science.gov (United States)

Kurihara, Yosuke

2016-01-01

Abstract Grooming is essential to build social relationships in primates. Its importance is universal among animals from different ranks; however, rank-related differences in feeding patterns can lead to conflicts between feeding and grooming in low-ranking animals. Unifying the effects of dominance rank on feeding and grooming behaviors contributes to revealing the importance of grooming. Here, I tested whether the grooming behavior of low-ranking females were similar to that of high-ranking females despite differences in their feeding patterns. I followed 9 Japanese macaques Macaca fuscata fuscata adult females from the Arashiyama group, and analyzed the feeding patterns and grooming behaviors of low- and high-ranking females. Low-ranking females fed on natural foods away from the provisioning site, whereas high-ranking females obtained more provisioned food at the site. Due to these differences in feeding patterns, low-ranking females spent less time grooming than high-ranking females. However, both low- and high-ranking females performed grooming around the provisioning site, which was linked to the number of neighboring individuals for low-ranking females and feeding on provisioned foods at the site for high-ranking females. The similarity in grooming area led to a range and diversity of grooming partners that did not differ with rank. Thus, low-ranking females can obtain small amounts of provisioned foods and perform grooming with as many partners around the provisioning site as high-ranking females. These results highlight the efforts made by low-ranking females to perform grooming and suggest the importance of grooming behavior in group-living primates. PMID:29491896

Ranking Entities in Networks via Lefschetz Duality

DEFF Research Database (Denmark)

Aabrandt, Andreas; Hansen, Vagn Lundsgaard; Poulsen, Bjarne

2014-01-01

then be ranked according to how essential their positions are in the network by considering the effect of their respective absences. Defining a ranking of a network which takes the individual position of each entity into account has the purpose of assigning different roles to the entities, e.g. agents......, in the network. In this paper it is shown that the topology of a given network induces a ranking of the entities in the network. Further, it is demonstrated how to calculate this ranking and thus how to identify weak sub-networks in any given network....

A Hybrid Distance-Based Ideal-Seeking Consensus Ranking Model

Directory of Open Access Journals (Sweden)

Madjid Tavana

2007-01-01

Full Text Available Ordinal consensus ranking problems have received much attention in the management science literature. A problem arises in situations where a group of k decision makers (DMs is asked to rank order n alternatives. The question is how to combine the DM rankings into one consensus ranking. Several different approaches have been suggested to aggregate DM responses into a compromise or consensus ranking; however, the similarity of consensus rankings generated by the different algorithms is largely unknown. In this paper, we propose a new hybrid distance-based ideal-seeking consensus ranking model (DCM. The proposed hybrid model combines parts of the two commonly used consensus ranking techniques of Beck and Lin (1983 and Cook and Kress (1985 into an intuitive and computationally simple model. We illustrate our method and then run a Monte Carlo simulation across a range of k and n to compare the similarity of the consensus rankings generated by our method with the best-known method of Borda and Kendall (Kendall 1962 and the two methods proposed by Beck and Lin (1983 and Cook and Kress (1985. DCM and Beck and Lin's method yielded the most similar consensus rankings, whereas the Cook-Kress method and the Borda-Kendall method yielded the least similar consensus rankings.

Correlation of macroscopic osteoarthrotic changes and radiographic findings in the acromioclavicular joint

International Nuclear Information System (INIS)

Stenlund, B.; Marions, O.; Engstroem, K.F.; Goldie, I.; Soedersjukhuset, Stockholm; Karolinska Sjukhuset, Stockholm

1988-01-01

In a total of 108 acromioclavicular articulations from cadavers the osteoarthrotic changes were studied. The articulations were macroscopically and radiographically ranked according to their grade of osteoarthrosis. The two ranking lines were correlated statistically and showed a rank correlation of 0.741. In 38 articulations tomography was also carried out. These articulations were classified into five grades of osteoarthrosis and the macroscopic, conventional radiographic and tomographic gradings were compared. The correlation coefficient for tomography versus macroscopy was 0.714. Tomography versus standard radiography showed a correlation of 0.767 and standard radiography versus macroscopy a correlation of 0.841. The standard radiographic investigation reveals moderate and severe osteoarthrotic changes in the acromioclavicular joint but cannot depict smaller changes. Tomography does not seem to improve the specificity. There is a need for a better radiologic technique in the examination of the acromioclavicular joint. Radiography during some kind of loading might be a practical way of improving the specificity and make it possible to show early osteoarthrosis in the acromioclavicular articulation. (orig.)

Correlation of macroscopic osteoarthrotic changes and radiographic findings in the acromioclavicular joint

Energy Technology Data Exchange (ETDEWEB)

Stenlund, B.; Marions, O.; Engstroem, K.F.; Goldie, I.

In a total of 108 acromioclavicular articulations from cadavers the osteoarthrotic changes were studied. The articulations were macroscopically and radiographically ranked according to their grade of osteoarthrosis. The two ranking lines were correlated statistically and showed a rank correlation of 0.741. In 38 articulations tomography was also carried out. These articulations were classified into five grades of osteoarthrosis and the macroscopic, conventional radiographic and tomographic gradings were compared. The correlation coefficient for tomography versus macroscopy was 0.714. Tomography versus standard radiography showed a correlation of 0.767 and standard radiography versus macroscopy a correlation of 0.841. The standard radiographic investigation reveals moderate and severe osteoarthrotic changes in the acromioclavicular joint but cannot depict smaller changes. Tomography does not seem to improve the specificity. There is a need for a better radiologic technique in the examination of the acromioclavicular joint. Radiography during some kind of loading might be a practical way of improving the specificity and make it possible to show early osteoarthrosis in the acromioclavicular articulation.

WHEN THE DISTURBANCES ARE SPATIALLY CORRELATED

African Journals Online (AJOL)

correlation, spatial error process. INTRODUCTION. Consider the linear regression model for spatial correlation y=XB +u, u=Ce, (1) where y is a Txl observable random vector, X is a Txk matrix of known constants with full column rank k, B is a k xl vector of unknown parameters,. :2 is a Txl random vector with expectation zero ...

Exploiting Cross Correlations and Joint Analyses

Energy Technology Data Exchange (ETDEWEB)

Rhodes, J. [Caltech; Allen, S. [SLAC; Benson, B. A. [Chicago U., Astron. Astrophys. Ctr.; Chang, T. [Taipei, Inst. Astron. Astrophys.; de Putter, R. [Caltech; Dodelson, S. [Chicago U., Astron. Astrophys. Ctr.; Doré, O. [Caltech; Honscheid, K. [Ohio State U., CCAPP; Linder, E. [UC, Berkeley; Ménard, B. [Tokyo U., IPMU; Newman, J. [Pittsburgh U.; Nord, B. [Fermilab; Rozo, E. [SLAC; Rykoff, E. [SLAC; Vallinotto, A. [LBL, Berkeley; Weinberg, D. [Ohio State U., CCAPP

2014-02-28

In this report, we present a wide variety of ways in which information from multiple probes of dark energy may be combined to obtain additional information not accessible when they are considered separately. Fundamentally, because all major probes are affected by the underlying distribution of matter in the regions studied, there exist covariances between them that can provide information on cosmology. Combining multiple probes allows for more accurate (less contaminated by systematics) and more precise (since there is cosmological information encoded in cross-correlation statistics) measurements of dark energy. The potential of cross-correlation methods is only beginning to be realized. By bringing in information from other wavelengths, the capabilities of the existing probes of dark energy can be enhanced and systematic effects can be mitigated further. We present a mixture of work in progress and suggestions for future scientific efforts. Given the scope of future dark energy experiments, the greatest gains may only be realized with more coordination and cooperation between multiple project teams; we recommend that this interchange should begin sooner, rather than later, to maximize scientific gains.

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.

Treatment plan ranking using physical and biological indices

International Nuclear Information System (INIS)

Ebert, M. A.; University of Western Asutralia, WA

2001-01-01

Full text: The ranking of dose distributions is of importance in several areas such as i) comparing rival treatment plans, ii) comparing iterations in an optimisation routine, and iii) dose-assessment of clinical trial data. This study aimed to investigate the influence of choice of objective function in ranking tumour dose distributions. A series of physical (mean, maximum, minimum, standard deviation of dose) dose-volume histogram (DVH) reduction indices and biologically-based (tumour-control probability - TCP; equivalent uniform dose -EUD) indices were used to rank a series of hypothetical DVHs, as well as DVHs obtained from a series of 18 prostate patients. The distribution in ranking and change in distribution with change in indice parameters were investigated. It is found that not only is the ranking of DVHs dependent on the actual model used to perform the DVH reduction, it is also found to depend on the inherent characteristics of each model (i.e., selected parameters). The adjacent figure shows an example where the 18 prostate patients are ranked (grey-scale from black to white) by EUD when an α value of 0.8 Gy -1 is used in the model. The change of ranking as α varies is evident. Conclusion: This study has shown that the characteristics of the model selected in plan optimisation or DVH ranking will have an impact on the ranking obtained. Copyright (2001) Australasian College of Physical Scientists and Engineers in Medicine

Rank diversity of languages: generic behavior in computational linguistics.

Science.gov (United States)

Cocho, Germinal; Flores, Jorge; Gershenson, Carlos; Pineda, Carlos; Sánchez, Sergio

2015-01-01

Statistical studies of languages have focused on the rank-frequency distribution of words. Instead, we introduce here a measure of how word ranks change in time and call this distribution rank diversity. We calculate this diversity for books published in six European languages since 1800, and find that it follows a universal lognormal distribution. Based on the mean and standard deviation associated with the lognormal distribution, we define three different word regimes of languages: "heads" consist of words which almost do not change their rank in time, "bodies" are words of general use, while "tails" are comprised by context-specific words and vary their rank considerably in time. The heads and bodies reflect the size of language cores identified by linguists for basic communication. We propose a Gaussian random walk model which reproduces the rank variation of words in time and thus the diversity. Rank diversity of words can be understood as the result of random variations in rank, where the size of the variation depends on the rank itself. We find that the core size is similar for all languages studied.

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...

Intensity rankings of plyometric exercises using joint power absorption.

Science.gov (United States)

Van Lieshout, Kathryn G; Anderson, Joy G; Shelburne, Kevin B; Davidson, Bradley S

2014-09-01

Athletic trainers and physical therapists often progress patients through rehabilitation by selecting plyometric exercises of increasing intensity in preparation for return to sport. The purpose of this study was to quantify the intensity of seven plyometric movements commonly used in lower-extremity rehabilitation by joint-specific peak power absorption and the sum of the peak power. Ten collegiate athletes performed submaximal plyometric exercises in a single test session: vertical jump, forward jump, backward jump, box drop, box jump up, tuck jump, and depth jump. Three-dimensional kinematics and force platform data were collected to generate joint kinetics. Peak power absorption normalized to body mass was calculated at the ankle, knee, and hip, and averaged across repetitions. Joint peak power data were pooled across athletes and summed to obtain the sum of peak power. Movements were ranked from 1 (low) to 7 (high) based on the sum of peak power and joint peak power (ankle, knee, hip). The sum of peak power did not correspond with standard low, medium, and high subjective intensity ratings or joint peak power in all joints. Mixed model analyses revealed significant variance between the sum of peak power and joint peak power ranks in the forward jump, backward jump, box drop, and depth jump (P<0.05), but not in the vertical jump, box jump up, and tuck jump. Results provide intensity rankings that can be used directly by athletic trainers and physical therapists in developing protocols for rehabilitation specific to the injured joint. Copyright © 2014 Elsevier Ltd. All rights reserved.

Beyond Low Rank: A Data-Adaptive Tensor Completion Method

OpenAIRE

Zhang, Lei; Wei, Wei; Shi, Qinfeng; Shen, Chunhua; Hengel, Anton van den; Zhang, Yanning

2017-01-01

Low rank tensor representation underpins much of recent progress in tensor completion. In real applications, however, this approach is confronted with two challenging problems, namely (1) tensor rank determination; (2) handling real tensor data which only approximately fulfils the low-rank requirement. To address these two issues, we develop a data-adaptive tensor completion model which explicitly represents both the low-rank and non-low-rank structures in a latent tensor. Representing the no...

Ignition behaviour of different rank coals in an entrained flow reactor

Energy Technology Data Exchange (ETDEWEB)

J. Faundez; A. Arenillas; F. Rubiera; X. Garcia; A.L. Gordon; J.J. Pis [Instituto Nacional del Carbon (INCAR), Oviedo (Spain)

2005-12-01

An experimental study to determine the temperature and mechanism of coal ignition was carried out by using an entrained flow reactor (EFR) at relatively high coal feed rates (0.5 g min{sup -1}). Seven coals ranging in rank from subbituminous to semianthracite, were tested and the evolved gases (O{sub 2}, CO, CO{sub 2}, NO) were measured continuously. The ignition temperature was evaluated from the gas evolution profiles, and it was found to be inversely correlated to the reactivity of the coal, as reflected by the increasing values of the ignition temperature in the sequence: subbituminous, high volatile bituminous, low volatile bituminous and semianthracite coals. The mechanism of ignition varied from a heterogeneous mechanism for subbituminous, low volatile bituminous and semianthracite coals, to a homogeneous mechanism for high volatile bituminous coals. A thermogravimetric analyser (TGA) was also used to evaluate coal ignition behaviour. Both methods, TGA and EFR, were in agreement as regards the mechanism of coal ignition. From the SEM micrographs of the coal particles retrieved from the cyclone, it was possible to observe the external appearance of the particles before, during and after ignition. The micrographs confirmed the mechanism deduced from the gas profiles. 23 refs., 5 figs., 1 tab.

CNN-based ranking for biomedical entity normalization.

Science.gov (United States)

Li, Haodi; Chen, Qingcai; Tang, Buzhou; Wang, Xiaolong; Xu, Hua; Wang, Baohua; Huang, Dong

2017-10-03

Most state-of-the-art biomedical entity normalization systems, such as rule-based systems, merely rely on morphological information of entity mentions, but rarely consider their semantic information. In this paper, we introduce a novel convolutional neural network (CNN) architecture that regards biomedical entity normalization as a ranking problem and benefits from semantic information of biomedical entities. The CNN-based ranking method first generates candidates using handcrafted rules, and then ranks the candidates according to their semantic information modeled by CNN as well as their morphological information. Experiments on two benchmark datasets for biomedical entity normalization show that our proposed CNN-based ranking method outperforms traditional rule-based method with state-of-the-art performance. We propose a CNN architecture that regards biomedical entity normalization as a ranking problem. Comparison results show that semantic information is beneficial to biomedical entity normalization and can be well combined with morphological information in our CNN architecture for further improvement.

RANK und RANKL - Vom Knochen zum Mammakarzinom

Directory of Open Access Journals (Sweden)

Sigl V

2012-01-01

Full Text Available RANK („Receptor Activator of NF-κB“ und sein Ligand RANKL sind Schlüsselmoleküle im Knochenmetabolismus und spielen eine essenzielle Rolle in der Entstehung von pathologischen Knochenveränderungen. Die Deregulation des RANK/RANKL-Systems ist zum Beispiel ein Hauptgrund für das Auftreten von postmenopausaler Osteoporose bei Frauen. Eine weitere wesentliche Funktion von RANK und RANKL liegt in der Entwicklung von milchsekretierenden Drüsen während der Schwangerschaft. Dabei regulieren Sexualhormone, wie zum Beispiel Progesteron, die Expression von RANKL und induzieren dadurch die Proliferation von epithelialen Zellen der Brust. Seit Längerem war schon bekannt, dass RANK und RANKL in der Metastasenbildung von Brustkrebszellen im Knochengewebe beteiligt sind. Wir konnten nun das RANK/RANKLSystem auch als essenziellen Mechanismus in der Entstehung von hormonellem Brustkrebs identifizieren. In diesem Beitrag werden wir daher den neuesten Erkenntnissen besondere Aufmerksamkeit schenken und diese kritisch in Bezug auf Brustkrebsentwicklung betrachten.

Using incomplete citation data for MEDLINE results ranking.

Science.gov (United States)

Herskovic, Jorge R; Bernstam, Elmer V

2005-01-01

Information overload is a significant problem for modern medicine. Searching MEDLINE for common topics often retrieves more relevant documents than users can review. Therefore, we must identify documents that are not only relevant, but also important. Our system ranks articles using citation counts and the PageRank algorithm, incorporating data from the Science Citation Index. However, citation data is usually incomplete. Therefore, we explore the relationship between the quantity of citation information available to the system and the quality of the result ranking. Specifically, we test the ability of citation count and PageRank to identify "important articles" as defined by experts from large result sets with decreasing citation information. We found that PageRank performs better than simple citation counts, but both algorithms are surprisingly robust to information loss. We conclude that even an incomplete citation database is likely to be effective for importance ranking.

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.

Using centrality to rank web snippets

NARCIS (Netherlands)

Jijkoun, V.; de Rijke, M.; Peters, C.; Jijkoun, V.; Mandl, T.; Müller, H.; Oard, D.W.; Peñas, A.; Petras, V.; Santos, D.

2008-01-01

We describe our participation in the WebCLEF 2007 task, targeted at snippet retrieval from web data. Our system ranks snippets based on a simple similarity-based centrality, inspired by the web page ranking algorithms. We experimented with retrieval units (sentences and paragraphs) and with the

Neural Ranking Models with Weak Supervision

NARCIS (Netherlands)

Dehghani, M.; Zamani, H.; Severyn, A.; Kamps, J.; Croft, W.B.

2017-01-01

Despite the impressive improvements achieved by unsupervised deep neural networks in computer vision and NLP tasks, such improvements have not yet been observed in ranking for information retrieval. The reason may be the complexity of the ranking problem, as it is not obvious how to learn from

Generalization Performance of Regularized Ranking With Multiscale Kernels.

Science.gov (United States)

Zhou, Yicong; Chen, Hong; Lan, Rushi; Pan, Zhibin

2016-05-01

The regularized kernel method for the ranking problem has attracted increasing attentions in machine learning. The previous regularized ranking algorithms are usually based on reproducing kernel Hilbert spaces with a single kernel. In this paper, we go beyond this framework by investigating the generalization performance of the regularized ranking with multiscale kernels. A novel ranking algorithm with multiscale kernels is proposed and its representer theorem is proved. We establish the upper bound of the generalization error in terms of the complexity of hypothesis spaces. It shows that the multiscale ranking algorithm can achieve satisfactory learning rates under mild conditions. Experiments demonstrate the effectiveness of the proposed method for drug discovery and recommendation tasks.

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.

Rank Diversity of Languages: Generic Behavior in Computational Linguistics

Science.gov (United States)

Cocho, Germinal; Flores, Jorge; Gershenson, Carlos; Pineda, Carlos; Sánchez, Sergio

2015-01-01

Statistical studies of languages have focused on the rank-frequency distribution of words. Instead, we introduce here a measure of how word ranks change in time and call this distribution rank diversity. We calculate this diversity for books published in six European languages since 1800, and find that it follows a universal lognormal distribution. Based on the mean and standard deviation associated with the lognormal distribution, we define three different word regimes of languages: “heads” consist of words which almost do not change their rank in time, “bodies” are words of general use, while “tails” are comprised by context-specific words and vary their rank considerably in time. The heads and bodies reflect the size of language cores identified by linguists for basic communication. We propose a Gaussian random walk model which reproduces the rank variation of words in time and thus the diversity. Rank diversity of words can be understood as the result of random variations in rank, where the size of the variation depends on the rank itself. We find that the core size is similar for all languages studied. PMID:25849150

Differential invariants for higher-rank tensors. A progress report

International Nuclear Information System (INIS)

Tapial, V.

2004-07-01

We outline the construction of differential invariants for higher-rank tensors. In section 2 we outline the general method for the construction of differential invariants. A first result is that the simplest tensor differential invariant contains derivatives of the same order as the rank of the tensor. In section 3 we review the construction for the first-rank tensors (vectors) and second-rank tensors (metrics). In section 4 we outline the same construction for higher-rank tensors. (author)

Statistical analyses of scatterplots to identify important factors in large-scale simulations, 2: robustness of techniques

International Nuclear Information System (INIS)

Kleijnen, J.P.C.; Helton, J.C.

1999-01-01

The robustness of procedures for identifying patterns in scatterplots generated in Monte Carlo sensitivity analyses is investigated. These procedures are based on attempts to detect increasingly complex patterns in the scatterplots under consideration and involve the identification of (i) linear relationships with correlation coefficients, (ii) monotonic relationships with rank correlation coefficients, (iii) trends in central tendency as defined by means, medians and the Kruskal-Wallis statistic, (iv) trends in variability as defined by variances and interquartile ranges, and (v) deviations from randomness as defined by the chi-square statistic. The following two topics related to the robustness of these procedures are considered for a sequence of example analyses with a large model for two-phase fluid flow: the presence of Type I and Type II errors, and the stability of results obtained with independent Latin hypercube samples. Observations from analysis include: (i) Type I errors are unavoidable, (ii) Type II errors can occur when inappropriate analysis procedures are used, (iii) physical explanations should always be sought for why statistical procedures identify variables as being important, and (iv) the identification of important variables tends to be stable for independent Latin hypercube samples

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.

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...

Adaptive distributional extensions to DFR ranking

DEFF Research Database (Denmark)

Petersen, Casper; Simonsen, Jakob Grue; Järvelin, Kalervo

2016-01-01

-fitting distribution. We call this model Adaptive Distributional Ranking (ADR) because it adapts the ranking to the statistics of the specific dataset being processed each time. Experiments on TREC data show ADR to outperform DFR models (and their extensions) and be comparable in performance to a query likelihood...

Discovering author impact: A PageRank perspective

OpenAIRE

Yan, Erjia; Ding, Ying

2010-01-01

This article provides an alternative perspective for measuring author impact by applying PageRank algorithm to a coauthorship network. A weighted PageRank algorithm considering citation and coauthorship network topology is proposed. We test this algorithm under different damping factors by evaluating author impact in the informetrics research community. In addition, we also compare this weighted PageRank with the h-index, citation, and program committee (PC) membership of the International So...

Social class rank, threat vigilance, and hostile reactivity.

Science.gov (United States)

Kraus, Michael W; Horberg, E J; Goetz, Jennifer L; Keltner, Dacher

2011-10-01

Lower-class individuals, because of their lower rank in society, are theorized to be more vigilant to social threats relative to their high-ranking upper-class counterparts. This class-related vigilance to threat, the authors predicted, would shape the emotional content of social interactions in systematic ways. In Study 1, participants engaged in a teasing interaction with a close friend. Lower-class participants--measured in terms of social class rank in society and within the friendship--more accurately tracked the hostile emotions of their friend. As a result, lower-class individuals experienced more hostile emotion contagion relative to upper-class participants. In Study 2, lower-class participants manipulated to experience lower subjective socioeconomic rank showed more hostile reactivity to ambiguous social scenarios relative to upper-class participants and to lower-class participants experiencing elevated socioeconomic rank. The results suggest that class affects expectations, perception, and experience of hostile emotion, particularly in situations in which lower-class individuals perceive their subordinate rank.

Are university rankings useful to improve research? A systematic review.

Science.gov (United States)

Vernon, Marlo M; Balas, E Andrew; Momani, Shaher

2018-01-01

Concerns about reproducibility and impact of research urge improvement initiatives. Current university ranking systems evaluate and compare universities on measures of academic and research performance. Although often useful for marketing purposes, the value of ranking systems when examining quality and outcomes is unclear. The purpose of this study was to evaluate usefulness of ranking systems and identify opportunities to support research quality and performance improvement. A systematic review of university ranking systems was conducted to investigate research performance and academic quality measures. Eligibility requirements included: inclusion of at least 100 doctoral granting institutions, be currently produced on an ongoing basis and include both global and US universities, publish rank calculation methodology in English and independently calculate ranks. Ranking systems must also include some measures of research outcomes. Indicators were abstracted and contrasted with basic quality improvement requirements. Exploration of aggregation methods, validity of research and academic quality indicators, and suitability for quality improvement within ranking systems were also conducted. A total of 24 ranking systems were identified and 13 eligible ranking systems were evaluated. Six of the 13 rankings are 100% focused on research performance. For those reporting weighting, 76% of the total ranks are attributed to research indicators, with 24% attributed to academic or teaching quality. Seven systems rely on reputation surveys and/or faculty and alumni awards. Rankings influence academic choice yet research performance measures are the most weighted indicators. There are no generally accepted academic quality indicators in ranking systems. No single ranking system provides a comprehensive evaluation of research and academic quality. Utilizing a combined approach of the Leiden, Thomson Reuters Most Innovative Universities, and the SCImago ranking systems may provide

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)

Ranking U-Sapiens 2010-2

Directory of Open Access Journals (Sweden)

Carlos-Roberto Peña-Barrera

2011-08-01

Full Text Available Los principales objetivos de esta investigación son los siguientes: (1 que la comunidad científica nacional e internacional y la sociedad en general co-nozcan los resultados del Ranking U-Sapiens Colombia 2010_2, el cual clasifica a cada institución de educación superior colombiana según puntaje, posición y cuartil; (2 destacar los movimientos más importantes al comparar los resultados del ranking 2010_1 con los del 2010_2; (3 publicar las respuestas de algunos actores de la academia nacional con respecto a la dinámica de la investigación en el país; (4 reconocer algunas instituciones, medios de comunicación e investigadores que se han interesado a modo de reflexión, referenciación o citación por esta investigación; y (5 dar a conocer el «Sello Ranking U-Sapiens Colombia» para las IES clasificadas. El alcance de este estudio en cuanto a actores abordó todas y cada una de las IES nacionales (aunque solo algunas lograran entrar al ranking y en cuanto a tiempo, un periodo referido al primer semestre de 2010 con respecto a: (1 los resultados 2010-1 de revistas indexadas en Publindex, (2 los programas de maestrías y doctorados activos durante 2010-1 según el Ministerio de Educación Nacional, y (3 los resultados de grupos de investigación clasificados para 2010 según Colciencias. El método empleado para esta investigación es el mismo que para el ranking 2010_1, salvo por una especificación aún más detallada en uno de los pasos del modelo (las variables α, β, γ; es completamente cuantitativo y los datos de las variables que fundamentan sus resultados provienen de Colciencias y el Ministerio de Educación Nacional; y en esta ocasión se darán a conocer los resultados por variable para 2010_1 y 2010_2. Los resultados más relevantes son estos: (1 entraron 8 IES al ranking y salieron 3; (2 las 3 primeras IES son públicas; (3 en total hay 6 instituciones universitarias en el ranking; (4 7 de las 10 primeras IES son

Ranking Quality in Higher Education: Guiding or Misleading?

Science.gov (United States)

Bergseth, Brita; Petocz, Peter; Abrandt Dahlgren, Madeleine

2014-01-01

The study examines two different models of measuring, assessing and ranking quality in higher education. Do different systems of quality assessment lead to equivalent conclusions about the quality of education? This comparative study is based on the rankings of 24 Swedish higher education institutions. Two ranking actors have independently…

Blind Reduced-Rank MMSE Detector for DS-CDMA Systems

Directory of Open Access Journals (Sweden)

Xiaodong Cai

2003-01-01

Full Text Available We first develop a reduced-rank minimum mean squared error (MMSE detector for direct-sequence (DS code division multiple access (CDMA by forcing the linear MMSE detector to lie in a signal subspace of a reduced dimension. While a reduced-rank MMSE detector has lower complexity, it cannot outperform the full-rank MMSE detector. We then concentrate on the blind reduced-rank MMSE detector which is obtained from an estimated covariance matrix. Our analysis and simulation results show that when the desired user′s signal is in a low-dimensional subspace, there exists an optimal subspace so that the blind reduced-rank MMSE detector lying in this subspace has the best performance. By properly choosing a subsspace, we guarantee that the optimal blind reduced-rank MMSE detector is obtained. An adaptive blind reduced-rank MMSE detector, based on a subspace tracking algorithm, is developed. The adaptive blind reduced-rank MMSE detector exhibits superior steady-state performance and fast convergence speed.

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

Hyper-local, directions-based ranking of places

DEFF Research Database (Denmark)

Venetis, Petros; Gonzalez, Hector; Jensen, Christian S.

2011-01-01

they are numerous and contain precise locations. Specifically, the paper proposes a framework that takes a user location and a collection of near-by places as arguments, producing a ranking of the places. The framework enables a range of aspects of directions queries to be exploited for the ranking of places......, including the frequency with which places have been referred to in directions queries. Next, the paper proposes an algorithm and accompanying data structures capable of ranking places in response to hyper-local web queries. Finally, an empirical study with very large directions query logs offers insight...... into the potential of directions queries for the ranking of places and suggests that the proposed algorithm is suitable for use in real web search engines....

Reduced-Rank Adaptive Filtering Using Krylov Subspace

Directory of Open Access Journals (Sweden)

Sergueï Burykh

2003-01-01

Full Text Available A unified view of several recently introduced reduced-rank adaptive filters is presented. As all considered methods use Krylov subspace for rank reduction, the approach taken in this work is inspired from Krylov subspace methods for iterative solutions of linear systems. The alternative interpretation so obtained is used to study the properties of each considered technique and to relate one reduced-rank method to another as well as to algorithms used in computational linear algebra. Practical issues are discussed and low-complexity versions are also included in our study. It is believed that the insight developed in this paper can be further used to improve existing reduced-rank methods according to known results in the domain of Krylov subspace methods.

The effect of new links on Google PageRank

NARCIS (Netherlands)

Avrachenkov, Konstatin; Litvak, Nelli

2004-01-01

PageRank is one of the principle criteria according to which Google ranks Web pages. PageRank can be interpreted as a frequency of visiting a Web page by a random surfer and thus it reflects the popularity of a Web page. We study the effect of newly created links on Google PageRank. We discuss to

Quantum probability ranking principle for ligand-based virtual screening

Science.gov (United States)

Al-Dabbagh, Mohammed Mumtaz; Salim, Naomie; Himmat, Mubarak; Ahmed, Ali; Saeed, Faisal

2017-04-01

Chemical libraries contain thousands of compounds that need screening, which increases the need for computational methods that can rank or prioritize compounds. The tools of virtual screening are widely exploited to enhance the cost effectiveness of lead drug discovery programs by ranking chemical compounds databases in decreasing probability of biological activity based upon probability ranking principle (PRP). In this paper, we developed a novel ranking approach for molecular compounds inspired by quantum mechanics, called quantum probability ranking principle (QPRP). The QPRP ranking criteria would make an attempt to draw an analogy between the physical experiment and molecular structure ranking process for 2D fingerprints in ligand based virtual screening (LBVS). The development of QPRP criteria in LBVS has employed the concepts of quantum at three different levels, firstly at representation level, this model makes an effort to develop a new framework of molecular representation by connecting the molecular compounds with mathematical quantum space. Secondly, estimate the similarity between chemical libraries and references based on quantum-based similarity searching method. Finally, rank the molecules using QPRP approach. Simulated virtual screening experiments with MDL drug data report (MDDR) data sets showed that QPRP outperformed the classical ranking principle (PRP) for molecular chemical compounds.

Quantum probability ranking principle for ligand-based virtual screening.

Science.gov (United States)

Al-Dabbagh, Mohammed Mumtaz; Salim, Naomie; Himmat, Mubarak; Ahmed, Ali; Saeed, Faisal

2017-04-01

Chemical libraries contain thousands of compounds that need screening, which increases the need for computational methods that can rank or prioritize compounds. The tools of virtual screening are widely exploited to enhance the cost effectiveness of lead drug discovery programs by ranking chemical compounds databases in decreasing probability of biological activity based upon probability ranking principle (PRP). In this paper, we developed a novel ranking approach for molecular compounds inspired by quantum mechanics, called quantum probability ranking principle (QPRP). The QPRP ranking criteria would make an attempt to draw an analogy between the physical experiment and molecular structure ranking process for 2D fingerprints in ligand based virtual screening (LBVS). The development of QPRP criteria in LBVS has employed the concepts of quantum at three different levels, firstly at representation level, this model makes an effort to develop a new framework of molecular representation by connecting the molecular compounds with mathematical quantum space. Secondly, estimate the similarity between chemical libraries and references based on quantum-based similarity searching method. Finally, rank the molecules using QPRP approach. Simulated virtual screening experiments with MDL drug data report (MDDR) data sets showed that QPRP outperformed the classical ranking principle (PRP) for molecular chemical compounds.

Correlation analyses revealed global microRNA-mRNA expression associations in human peripheral blood mononuclear cells.

Science.gov (United States)

Wang, Lan; Zhu, Jiang; Deng, Fei-Yan; Wu, Long-Fei; Mo, Xing-Bo; Zhu, Xiao-Wei; Xia, Wei; Xie, Fang-Fei; He, Pei; Bing, Peng-Fei; Qiu, Ying-Hua; Lin, Xiang; Lu, Xin; Zhang, Lei; Yi, Neng-Jun; Zhang, Yong-Hong; Lei, Shu-Feng

2018-02-01

MicroRNAs (miRNAs) can regulate gene expression through binding to complementary sites in the 3'-untranslated regions of target mRNAs, which will lead to existence of correlation in expression between miRNA and mRNA. However, the miRNA-mRNA correlation patterns are complex and remain largely unclear yet. To establish the global correlation patterns in human peripheral blood mononuclear cells (PBMCs), multiple miRNA-mRNA correlation analyses and expression quantitative trait locus (eQTL) analysis were conducted in this study. We predicted and achieved 861 miRNA-mRNA pairs (65 miRNAs, 412 mRNAs) using multiple bioinformatics programs, and found global negative miRNA-mRNA correlations in PBMC from all 46 study subjects. Among the 861 pairs of correlations, 19.5% were significant (P correlation network was complex and highlighted key miRNAs/genes in PBMC. Some miRNAs, such as hsa-miR-29a, hsa-miR-148a, regulate a cluster of target genes. Some genes, e.g., TNRC6A, are regulated by multiple miRNAs. The identified genes tend to be enriched in molecular functions of DNA and RNA binding, and biological processes such as protein transport, regulation of translation and chromatin modification. The results provided a global view of the miRNA-mRNA expression correlation profile in human PBMCs, which would facilitate in-depth investigation of biological functions of key miRNAs/mRNAs and better understanding of the pathogenesis underlying PBMC-related diseases.

A novel three-stage distance-based consensus ranking method

Science.gov (United States)

Aghayi, Nazila; Tavana, Madjid

2018-05-01

In this study, we propose a three-stage weighted sum method for identifying the group ranks of alternatives. In the first stage, a rank matrix, similar to the cross-efficiency matrix, is obtained by computing the individual rank position of each alternative based on importance weights. In the second stage, a secondary goal is defined to limit the vector of weights since the vector of weights obtained in the first stage is not unique. Finally, in the third stage, the group rank position of alternatives is obtained based on a distance of individual rank positions. The third stage determines a consensus solution for the group so that the ranks obtained have a minimum distance from the ranks acquired by each alternative in the previous stage. A numerical example is presented to demonstrate the applicability and exhibit the efficacy of the proposed method and algorithms.

The Interplay between QSAR/QSPR Studiesand Partial Order Ranking and Formal Concept Analyses

Directory of Open Access Journals (Sweden)

Lars Carlsen

2009-04-01

Full Text Available The often observed scarcity of physical-chemical and well as toxicological data hampers the assessment of potentially hazardous chemicals released to the environment. In such cases Quantitative Structure-Activity Relationships/Quantitative Structure-Property Relationships (QSAR/QSPR constitute an obvious alternative for rapidly, effectively and inexpensively generatng missing experimental values. However, typically further treatment of the data appears necessary, e.g., to elucidate the possible relations between the single compounds as well as implications and associations between the various parameters used for the combined characterization of the compounds under investigation. In the present paper the application of QSAR/QSPR in combination with Partial Order Ranking (POR methodologies will be reviewed and new aspects using Formal Concept Analysis (FCA will be introduced. Where POR constitutes an attractive method for, e.g., prioritizing a series of chemical substances based on a simultaneous inclusion of a range of parameters, FCA gives important information on the implications associations between the parameters. The combined approach thus constitutes an attractive method to a preliminary assessment of the impact on environmental and human health by primary pollutants or possibly by a primary pollutant well as a possible suite of transformation subsequent products that may be both persistent in and bioaccumulating and toxic.The present review focus on the environmental – and human health impact by residuals of the rocket fuel 1,1-dimethyl- hydrazine (heptyl and its transformation products as an illustrative example.

Learning to rank figures within a biomedical article.

Directory of Open Access Journals (Sweden)

Feifan Liu

Full Text Available Hundreds of millions of figures are available in biomedical literature, representing important biomedical experimental evidence. This ever-increasing sheer volume has made it difficult for scientists to effectively and accurately access figures of their interest, the process of which is crucial for validating research facts and for formulating or testing novel research hypotheses. Current figure search applications can't fully meet this challenge as the "bag of figures" assumption doesn't take into account the relationship among figures. In our previous study, hundreds of biomedical researchers have annotated articles in which they serve as corresponding authors. They ranked each figure in their paper based on a figure's importance at their discretion, referred to as "figure ranking". Using this collection of annotated data, we investigated computational approaches to automatically rank figures. We exploited and extended the state-of-the-art listwise learning-to-rank algorithms and developed a new supervised-learning model BioFigRank. The cross-validation results show that BioFigRank yielded the best performance compared with other state-of-the-art computational models, and the greedy feature selection can further boost the ranking performance significantly. Furthermore, we carry out the evaluation by comparing BioFigRank with three-level competitive domain-specific human experts: (1 First Author, (2 Non-Author-In-Domain-Expert who is not the author nor co-author of an article but who works in the same field of the corresponding author of the article, and (3 Non-Author-Out-Domain-Expert who is not the author nor co-author of an article and who may or may not work in the same field of the corresponding author of an article. Our results show that BioFigRank outperforms Non-Author-Out-Domain-Expert and performs as well as Non-Author-In-Domain-Expert. Although BioFigRank underperforms First Author, since most biomedical researchers are either in- or

Learning to rank figures within a biomedical article.

Science.gov (United States)

Liu, Feifan; Yu, Hong

2014-01-01

Hundreds of millions of figures are available in biomedical literature, representing important biomedical experimental evidence. This ever-increasing sheer volume has made it difficult for scientists to effectively and accurately access figures of their interest, the process of which is crucial for validating research facts and for formulating or testing novel research hypotheses. Current figure search applications can't fully meet this challenge as the "bag of figures" assumption doesn't take into account the relationship among figures. In our previous study, hundreds of biomedical researchers have annotated articles in which they serve as corresponding authors. They ranked each figure in their paper based on a figure's importance at their discretion, referred to as "figure ranking". Using this collection of annotated data, we investigated computational approaches to automatically rank figures. We exploited and extended the state-of-the-art listwise learning-to-rank algorithms and developed a new supervised-learning model BioFigRank. The cross-validation results show that BioFigRank yielded the best performance compared with other state-of-the-art computational models, and the greedy feature selection can further boost the ranking performance significantly. Furthermore, we carry out the evaluation by comparing BioFigRank with three-level competitive domain-specific human experts: (1) First Author, (2) Non-Author-In-Domain-Expert who is not the author nor co-author of an article but who works in the same field of the corresponding author of the article, and (3) Non-Author-Out-Domain-Expert who is not the author nor co-author of an article and who may or may not work in the same field of the corresponding author of an article. Our results show that BioFigRank outperforms Non-Author-Out-Domain-Expert and performs as well as Non-Author-In-Domain-Expert. Although BioFigRank underperforms First Author, since most biomedical researchers are either in- or out

Social class rank, essentialism, and punitive judgment.

Science.gov (United States)

Kraus, Michael W; Keltner, Dacher

2013-08-01

Recent evidence suggests that perceptions of social class rank influence a variety of social cognitive tendencies, from patterns of causal attribution to moral judgment. In the present studies we tested the hypotheses that upper-class rank individuals would be more likely to endorse essentialist lay theories of social class categories (i.e., that social class is founded in genetically based, biological differences) than would lower-class rank individuals and that these beliefs would decrease support for restorative justice--which seeks to rehabilitate offenders, rather than punish unlawful action. Across studies, higher social class rank was associated with increased essentialism of social class categories (Studies 1, 2, and 4) and decreased support for restorative justice (Study 4). Moreover, manipulated essentialist beliefs decreased preferences for restorative justice (Study 3), and the association between social class rank and class-based essentialist theories was explained by the tendency to endorse beliefs in a just world (Study 2). Implications for how class-based essentialist beliefs potentially constrain social opportunity and mobility are discussed.

Low-Rank Sparse Coding for Image Classification

KAUST Repository

Zhang, Tianzhu; Ghanem, Bernard; Liu, Si; Xu, Changsheng; Ahuja, Narendra

2013-01-01

In this paper, we propose a low-rank sparse coding (LRSC) method that exploits local structure information among features in an image for the purpose of image-level classification. LRSC represents densely sampled SIFT descriptors, in a spatial neighborhood, collectively as low-rank, sparse linear combinations of code words. As such, it casts the feature coding problem as a low-rank matrix learning problem, which is different from previous methods that encode features independently. This LRSC has a number of attractive properties. (1) It encourages sparsity in feature codes, locality in codebook construction, and low-rankness for spatial consistency. (2) LRSC encodes local features jointly by considering their low-rank structure information, and is computationally attractive. We evaluate the LRSC by comparing its performance on a set of challenging benchmarks with that of 7 popular coding and other state-of-the-art methods. Our experiments show that by representing local features jointly, LRSC not only outperforms the state-of-the-art in classification accuracy but also improves the time complexity of methods that use a similar sparse linear representation model for feature coding.

Low-Rank Sparse Coding for Image Classification

KAUST Repository

Zhang, Tianzhu

2013-12-01

In this paper, we propose a low-rank sparse coding (LRSC) method that exploits local structure information among features in an image for the purpose of image-level classification. LRSC represents densely sampled SIFT descriptors, in a spatial neighborhood, collectively as low-rank, sparse linear combinations of code words. As such, it casts the feature coding problem as a low-rank matrix learning problem, which is different from previous methods that encode features independently. This LRSC has a number of attractive properties. (1) It encourages sparsity in feature codes, locality in codebook construction, and low-rankness for spatial consistency. (2) LRSC encodes local features jointly by considering their low-rank structure information, and is computationally attractive. We evaluate the LRSC by comparing its performance on a set of challenging benchmarks with that of 7 popular coding and other state-of-the-art methods. Our experiments show that by representing local features jointly, LRSC not only outperforms the state-of-the-art in classification accuracy but also improves the time complexity of methods that use a similar sparse linear representation model for feature coding.

Image Re-Ranking Based on Topic Diversity.

Science.gov (United States)

Qian, Xueming; Lu, Dan; Wang, Yaxiong; Zhu, Li; Tang, Yuan Yan; Wang, Meng

2017-08-01

Social media sharing Websites allow users to annotate images with free tags, which significantly contribute to the development of the web image retrieval. Tag-based image search is an important method to find images shared by users in social networks. However, how to make the top ranked result relevant and with diversity is challenging. In this paper, we propose a topic diverse ranking approach for tag-based image retrieval with the consideration of promoting the topic coverage performance. First, we construct a tag graph based on the similarity between each tag. Then, the community detection method is conducted to mine the topic community of each tag. After that, inter-community and intra-community ranking are introduced to obtain the final retrieved results. In the inter-community ranking process, an adaptive random walk model is employed to rank the community based on the multi-information of each topic community. Besides, we build an inverted index structure for images to accelerate the searching process. Experimental results on Flickr data set and NUS-Wide data sets show the effectiveness of the proposed approach.

Classification of rank 2 cluster varieties

DEFF Research Database (Denmark)

Mandel, Travis

We classify rank 2 cluster varieties (those whose corresponding skew-form has rank 2) according to the deformation type of a generic fiber U of their X-spaces, as defined by Fock and Goncharov. Our approach is based on the work of Gross, Hacking, and Keel for cluster varieties and log Calabi...

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.

Sign rank versus Vapnik-Chervonenkis dimension

Science.gov (United States)

Alon, N.; Moran, Sh; Yehudayoff, A.

2017-12-01

This work studies the maximum possible sign rank of sign (N × N)-matrices with a given Vapnik-Chervonenkis dimension d. For d=1, this maximum is three. For d=2, this maximum is \\widetilde{\\Theta}(N1/2). For d >2, similar but slightly less accurate statements hold. The lower bounds improve on previous ones by Ben-David et al., and the upper bounds are novel. The lower bounds are obtained by probabilistic constructions, using a theorem of Warren in real algebraic topology. The upper bounds are obtained using a result of Welzl about spanning trees with low stabbing number, and using the moment curve. The upper bound technique is also used to: (i) provide estimates on the number of classes of a given Vapnik-Chervonenkis dimension, and the number of maximum classes of a given Vapnik-Chervonenkis dimension--answering a question of Frankl from 1989, and (ii) design an efficient algorithm that provides an O(N/log(N)) multiplicative approximation for the sign rank. We also observe a general connection between sign rank and spectral gaps which is based on Forster's argument. Consider the adjacency (N × N)-matrix of a Δ-regular graph with a second eigenvalue of absolute value λ and Δ ≤ N/2. We show that the sign rank of the signed version of this matrix is at least Δ/λ. We use this connection to prove the existence of a maximum class C\\subseteq\\{+/- 1\\}^N with Vapnik-Chervonenkis dimension 2 and sign rank \\widetilde{\\Theta}(N1/2). This answers a question of Ben-David et al. regarding the sign rank of large Vapnik-Chervonenkis classes. We also describe limitations of this approach, in the spirit of the Alon-Boppana theorem. We further describe connections to communication complexity, geometry, learning theory, and combinatorics. Bibliography: 69 titles.

The Rankings Game: Who's Playing Whom?

Science.gov (United States)

Burness, John F.

2008-01-01

This summer, Forbes magazine published its new rankings of "America's Best Colleges," implying that it had developed a methodology that would give the public the information that it needed to choose a college wisely. "U.S. News & World Report," which in 1983 published the first annual ranking, just announced its latest ratings last week--including…

Evaluating ranking methods on heterogeneous digital library collections

CERN Document Server

Canévet, Olivier; Marian, Ludmila; Chonavel, Thierry

In the frame of research in particle physics, CERN has been developing its own web-based software /Invenio/ to run the digital library of all the documents related to CERN and fundamental physics. The documents (articles, photos, news, thesis, ...) can be retrieved through a search engine. The results matching the query of the user can be displayed in several ways: sorted by latest first, author, title and also ranked by word similarity. The purpose of this project is to study and implement a new ranking method in Invenio: distributed-ranking (D-Rank). This method aims at aggregating several ranking scores coming from different ranking methods into a new score. In addition to query-related scores such as word similarity, the goal of the work is to take into account non-query-related scores such as citations, journal impact factor and in particular scores related to the document access frequency in the database. The idea is that for two equally query-relevant documents, if one has been more downloaded for inst...

Ranking spreaders by decomposing complex networks

International Nuclear Information System (INIS)

Zeng, An; Zhang, Cheng-Jun

2013-01-01

Ranking the nodes' ability of spreading in networks is crucial for designing efficient strategies to hinder spreading in the case of diseases or accelerate spreading in the case of information dissemination. In the well-known k-shell method, nodes are ranked only according to the links between the remaining nodes (residual links) while the links connecting to the removed nodes (exhausted links) are entirely ignored. In this Letter, we propose a mixed degree decomposition (MDD) procedure in which both the residual degree and the exhausted degree are considered. By simulating the epidemic spreading process on real networks, we show that the MDD method can outperform the k-shell and degree methods in ranking spreaders.

Service Quality Evaluation and Ranking of Container Terminal Operators

Directory of Open Access Journals (Sweden)

Jafar Sayareh

2016-12-01

Full Text Available In the service industry, the regular assessment of service quality is considered as a means of promoting the quality of services. Container market is no exception, and the quality of providing service in a container terminal is of prime importance in attracting new customers and maintaining the existing ones. The main aim of present research is to evaluate the quality of service being offered at Shahid Rajaee Container Terminal (SRCT in Bandar Abbas port. The evaluation process uses SERVQUAL model which is an appropriate tool for measuring the service quality, identifying and analyzing available gaps between service expectations and perceptions. Target population in this research includes customers of SRCT. The standard and customized questionnaires were distributed among 165 samples, out of which 127 (77% were returned. For the purpose of data analyses, initially the reliability of SERVQUAL model was checked, and then paired sample t-test was performed to reveal any possible gap between expectations and perceptions of respondents. Finally, TOPSIS was used to rank the 9 main container service companies in the SRCT. The results indicated that there are significant gaps between customers’ expectations and perceptions in SRCT, in all five dimensions of services quality. Additionally, from weighing point of view, ‘Tangibles’ was the most important dimension, followed by ‘Reliability’, ‘Assurance’, ‘Responsiveness’ and ‘Empathy’. In addition, ‘Tangibles’ dimension had maximum gap and ‘Empathy’ dimension had minimum gap between customers’ expectations and perceptions. Finally, after ranking companies, BandarAbbas Aria Container Terminal (BACT Company was ranked first among nine companies in satisfying customers’ expectations.

Variation in performance measure criteria significantly affects cardiology practice rankings: Insights from the National Cardiovascular Data Registry's Practice Innovation and Clinical Excellence Registry.

Science.gov (United States)

Eapen, Zubin J; Tang, Fengming; Jones, Phil G; Maddox, Thomas M; Oetgen, William J; Spertus, John A; Rumsfeld, John S; Heidenreich, Paul A; Peterson, Eric D; Drozda, Joseph P

2015-06-01

Million Hearts is a national initiative to prevent 1 million heart attacks and strokes over 5 years by improving cardiovascular prevention. An important tool in the success of programs like Million Hearts is public ranking on the quality of practices, yet different measures may provide different rankings, so the true quality of practices is difficult to discern. We evaluated the quality of ambulatory cardiology care using performance measure metrics. We compared rankings of practices participating in the National Cardiovascular Data Registry's Practice Innovation and Clinical Excellence Registry using measures from (1) the physician quality reporting system and (2) the American College of Cardiology/American Heart Association/Physician Consortium for Performance Improvement. We compared achievement rates for measures between the 2 frameworks and determined correlations in rankings using Spearman correlation coefficients. From January 1, 2008 to December 31, 2012, there were 1,711,326 patients enrolled from 111 US practices. Among eligible patients, the physician quality reporting system and American College of Cardiology/American Heart Association/Physician Consortium for Performance Improvement measures were achieved in 76.1% versus 77.4% for antiplatelet prescription (P performance and failing to achieve public health goals. Copyright © 2015 Elsevier Inc. All rights reserved.

The ranking of negative-cost emissions reduction measures

International Nuclear Information System (INIS)

Taylor, Simon

2012-01-01

A flaw has been identified in the calculation of the cost-effectiveness in marginal abatement cost curves (MACCs). The problem affects “negative-cost” emissions reduction measures—those that produce a return on investment. The resulting ranking sometimes favours measures that produce low emissions savings and is therefore unreliable. The issue is important because incorrect ranking means a potential failure to achieve the best-value outcome. A simple mathematical analysis shows that not only is the standard cost-effectiveness calculation inadequate for ranking negative-cost measures, but there is no possible replacement that satisfies reasonable requirements. Furthermore, the concept of negative cost-effectiveness is found to be unsound and its use should be avoided. Among other things, this means that MACCs are unsuitable for ranking negative-cost measures. As a result, MACCs produced by a range of organizations including UK government departments may need to be revised. An alternative partial ranking method has been devised by making use of Pareto optimization. The outcome can be presented as a stacked bar chart that indicates both the preferred ordering and the total emissions saving available for each measure without specifying a cost-effectiveness. - Highlights: ► Marginal abatement cost curves (MACCs) are used to rank emission reduction measures. ► There is a flaw in the standard ranking method for negative-cost measures. ► Negative values of cost-effectiveness (in £/tC or equivalent) are invalid. ► There may be errors in published MACCs. ► A method based on Pareto principles provides an alternative ranking method.

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

An adaptive ES with a ranking based constraint handling strategy

Directory of Open Access Journals (Sweden)

Kusakci Ali Osman

2014-01-01

Full Text Available To solve a constrained optimization problem, equality constraints can be used to eliminate a problem variable. If it is not feasible, the relations imposed implicitly by the constraints can still be exploited. Most conventional constraint handling methods in Evolutionary Algorithms (EAs do not consider the correlations between problem variables imposed by the constraints. This paper relies on the idea that a proper search operator, which captures mentioned implicit correlations, can improve performance of evolutionary constrained optimization algorithms. To realize this, an Evolution Strategy (ES along with a simplified Covariance Matrix Adaptation (CMA based mutation operator is used with a ranking based constraint-handling method. The proposed algorithm is tested on 13 benchmark problems as well as on a real life design problem. The outperformance of the algorithm is significant when compared with conventional ES-based methods.

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

Using Power-Law Degree Distribution to Accelerate PageRank

Directory of Open Access Journals (Sweden)

Zhaoyan Jin

2012-12-01

Full Text Available The PageRank vector of a network is very important, for it can reflect the importance of a Web page in the World Wide Web, or of a people in a social network. However, with the growth of the World Wide Web and social networks, it needs more and more time to compute the PageRank vector of a network. In many real-world applications, the degree and PageRank distributions of these complex networks conform to the Power-Law distribution. This paper utilizes the degree distribution of a network to initialize its PageRank vector, and presents a Power-Law degree distribution accelerating algorithm of PageRank computation. Experiments on four real-world datasets show that the proposed algorithm converges more quickly than the original PageRank algorithm.

Reduced-Rank Shift-Invariant Technique and Its Application for Synchronization and Channel Identification in UWB Systems

Directory of Open Access Journals (Sweden)

Kennedy RodneyA

2008-01-01

Full Text Available Abstract We investigate reduced-rank shift-invariant technique and its application for synchronization and channel identification in UWB systems. Shift-invariant techniques, such as ESPRIT and the matrix pencil method, have high resolution ability, but the associated high complexity makes them less attractive in real-time implementations. Aiming at reducing the complexity, we developed novel reduced-rank identification of principal components (RIPC algorithms. These RIPC algorithms can automatically track the principal components and reduce the computational complexity significantly by transforming the generalized eigen-problem in an original high-dimensional space to a lower-dimensional space depending on the number of desired principal signals. We then investigate the application of the proposed RIPC algorithms for joint synchronization and channel estimation in UWB systems, where general correlator-based algorithms confront many limitations. Technical details, including sampling and the capture of synchronization delay, are provided. Experimental results show that the performance of the RIPC algorithms is only slightly inferior to the general full-rank algorithms.

The metrics and correlates of physician migration from Africa

Directory of Open Access Journals (Sweden)

Arah Onyebuchi A

2007-05-01

Full Text Available Abstract Background Physician migration from poor to rich countries is considered an important contributor to the growing health workforce crisis in the developing world. This is particularly true for Africa. The perceived magnitude of such migration for each source country might, however, depend on the choice of metrics used in the analysis. This study examined the influence of choice of migration metrics on the rankings of African countries that suffered the most physician migration, and investigated the correlates of physician migration. Methods Ranking and correlational analyses were conducted on African physician migration data adjusted for bilateral net flows, and supplemented with developmental, economic and health system data. The setting was the 53 African birth countries of African-born physicians working in nine wealthier destination countries. Three metrics of physician migration were used: total number of physician émigrés; emigration fraction defined as the proportion of the potential physician pool working in destination countries; and physician migration density defined as the number of physician émigrés per 1000 population of the African source country. Results Rankings based on any of the migration metrics differed substantially from those based on the other two metrics. Although the emigration fraction and physician migration density metrics gave proportionality to the migration crisis, only the latter was consistently associated with source countries' workforce capacity, health, health spending, economic and development characteristics. As such, higher physician migration density was seen among African countries with relatively higher health workforce capacity (0.401 ≤ r ≤ 0.694, p ≤ 0.011, health status, health spending, and development. Conclusion The perceived magnitude of physician migration is sensitive to the choice of metrics. Complementing the emigration fraction, the physician migration density is a metric

A Case-Based Reasoning Method with Rank Aggregation

Science.gov (United States)

Sun, Jinhua; Du, Jiao; Hu, Jian

2018-03-01

In order to improve the accuracy of case-based reasoning (CBR), this paper addresses a new CBR framework with the basic principle of rank aggregation. First, the ranking methods are put forward in each attribute subspace of case. The ordering relation between cases on each attribute is got between cases. Then, a sorting matrix is got. Second, the similar case retrieval process from ranking matrix is transformed into a rank aggregation optimal problem, which uses the Kemeny optimal. On the basis, a rank aggregation case-based reasoning algorithm, named RA-CBR, is designed. The experiment result on UCI data sets shows that case retrieval accuracy of RA-CBR algorithm is higher than euclidean distance CBR and mahalanobis distance CBR testing.So we can get the conclusion that RA-CBR method can increase the performance and efficiency of CBR.

Gr/gr deletions on Y-chromosome correlate with male infertility: an original study, meta-analyses, and trial sequential analyses

Science.gov (United States)

Bansal, Sandeep Kumar; Jaiswal, Deepika; Gupta, Nishi; Singh, Kiran; Dada, Rima; Sankhwar, Satya Narayan; Gupta, Gopal; Rajender, Singh

2016-02-01

We analyzed the AZFc region of the Y-chromosome for complete (b2/b4) and distinct partial deletions (gr/gr, b1/b3, b2/b3) in 822 infertile and 225 proven fertile men. We observed complete AZFc deletions in 0.97% and partial deletions in 6.20% of the cases. Among partial deletions, the frequency of gr/gr deletions was the highest (5.84%). The comparison of partial deletion data between cases and controls suggested a significant association of the gr/gr deletions with infertility (P = 0.0004); however, the other partial deletions did not correlate with infertility. In cohort analysis, men with gr/gr deletions had a relatively poor sperm count (54.20 ± 57.45 million/ml) in comparison to those without deletions (72.49 ± 60.06), though the difference was not statistically significant (p = 0.071). Meta-analysis also suggested that gr/gr deletions are significantly associated with male infertility risk (OR = 1.821, 95% CI = 1.39-2.37, p = 0.000). We also performed trial sequential analyses that strengthened the evidence for an overall significant association of gr/gr deletions with the risk of male infertility. Another meta-analysis suggested a significant association of the gr/gr deletions with low sperm count. In conclusion, the gr/gr deletions show a strong correlation with male infertility risk and low sperm count, particularly in the Caucasian populations.

Power-law and exponential rank distributions: A panoramic Gibbsian perspective

International Nuclear Information System (INIS)

Eliazar, Iddo

2015-01-01

Rank distributions are collections of positive sizes ordered either increasingly or decreasingly. Many decreasing rank distributions, formed by the collective collaboration of human actions, follow an inverse power-law relation between ranks and sizes. This remarkable empirical fact is termed Zipf’s law, and one of its quintessential manifestations is the demography of human settlements — which exhibits a harmonic relation between ranks and sizes. In this paper we present a comprehensive statistical-physics analysis of rank distributions, establish that power-law and exponential rank distributions stand out as optimal in various entropy-based senses, and unveil the special role of the harmonic relation between ranks and sizes. Our results extend the contemporary entropy-maximization view of Zipf’s law to a broader, panoramic, Gibbsian perspective of increasing and decreasing power-law and exponential rank distributions — of which Zipf’s law is one out of four pillars

Power-law and exponential rank distributions: A panoramic Gibbsian perspective

Energy Technology Data Exchange (ETDEWEB)

Eliazar, Iddo, E-mail: eliazar@post.tau.ac.il

2015-04-15

Rank distributions are collections of positive sizes ordered either increasingly or decreasingly. Many decreasing rank distributions, formed by the collective collaboration of human actions, follow an inverse power-law relation between ranks and sizes. This remarkable empirical fact is termed Zipf’s law, and one of its quintessential manifestations is the demography of human settlements — which exhibits a harmonic relation between ranks and sizes. In this paper we present a comprehensive statistical-physics analysis of rank distributions, establish that power-law and exponential rank distributions stand out as optimal in various entropy-based senses, and unveil the special role of the harmonic relation between ranks and sizes. Our results extend the contemporary entropy-maximization view of Zipf’s law to a broader, panoramic, Gibbsian perspective of increasing and decreasing power-law and exponential rank distributions — of which Zipf’s law is one out of four pillars.

Communities in Large Networks: Identification and Ranking

DEFF Research Database (Denmark)

Olsen, Martin

2008-01-01

show that the problem of deciding whether a non trivial community exists is NP complete. Nevertheless, experiments show that a very simple greedy approach can identify members of a community in the Danish part of the web graph with time complexity only dependent on the size of the found community...... 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....

Correlations between cephalometric and photographic measurements of facial attractiveness in Chinese and US patients after orthodontic treatment.

Science.gov (United States)

Oh, Hee Soo; Korn, Edward L; Zhang, Xiaoyun; Liu, Yan; Xu, Tianmin; Boyd, Robert; Baumrind, Sheldon

2009-12-01

Orthodontists rely on esthetic judgments from facial photographs. Concordance between estimates of facial attractiveness made from lateral cephalograms and those made from clinical photographs has not been determined. We conducted a preliminary examination to correlate clinicians' rankings of facial attractiveness from standardized end-of-treatment facial photographs (Photo Attractiveness Rank) with cephalometric measurements of facial attractiveness made for the same subjects at the same time. Forty-five Chinese and US orthodontic clinicians ranked end-of-treatment photographs of separate samples of 45 US and 48 Chinese adolescent patients for facial attractiveness. Separately for each sample, the photographic rankings were correlated with the values of 21 conventional hard- and soft-tissue measures from lateral cephalograms taken at the same visits as the photographs. Among US patients, higher rank for facial attractiveness on the photographs was strongly associated with higher values for profile angle, chin prominence, lower lip prominence, and Z-angle, and also with lower values for angle of convexity, H-angle, and ANB. Among Chinese patients, higher rank for facial attractiveness on the photographs was strongly associated with higher values for Z-angle and chin prominence, and also with lower values for angle of convexity, H-angle, B-line to upper lip, and mandibular plane angle. Chinese patients whose %lower face height values approximated the ethnic "ideal" (54%) tended to rank higher for facial attractiveness than patients with either higher or lower values for %lower face height. The absolute values of the correlations for the 7 US measures noted above ranged from 0.41 to 0.59; those of the 7 Chinese measures ranged from 0.39 to 0.49.The P value of the least statistically significant of these 14 correlations was 0.006, unadjusted for multiple comparisons. On the other hand, many cephalometric measures believed by clinicians to be indicators of facial

A cross-benchmark comparison of 87 learning to rank methods

NARCIS (Netherlands)

Tax, N.; Bockting, S.; Hiemstra, D.

2015-01-01

Learning to rank is an increasingly important scientific field that comprises the use of machine learning for the ranking task. New learning to rank methods are generally evaluated on benchmark test collections. However, comparison of learning to rank methods based on evaluation results is hindered

Feature ranking and rank aggregation for automatic sleep stage classification: a comparative study.

Science.gov (United States)

Najdi, Shirin; Gharbali, Ali Abdollahi; Fonseca, José Manuel

2017-08-18

Nowadays, sleep quality is one of the most important measures of healthy life, especially considering the huge number of sleep-related disorders. Identifying sleep stages using polysomnographic (PSG) signals is the traditional way of assessing sleep quality. However, the manual process of sleep stage classification is time-consuming, subjective and costly. Therefore, in order to improve the accuracy and efficiency of the sleep stage classification, researchers have been trying to develop automatic classification algorithms. Automatic sleep stage classification mainly consists of three steps: pre-processing, feature extraction and classification. Since classification accuracy is deeply affected by the extracted features, a poor feature vector will adversely affect the classifier and eventually lead to low classification accuracy. Therefore, special attention should be given to the feature extraction and selection process. In this paper the performance of seven feature selection methods, as well as two feature rank aggregation methods, were compared. Pz-Oz EEG, horizontal EOG and submental chin EMG recordings of 22 healthy males and females were used. A comprehensive feature set including 49 features was extracted from these recordings. The extracted features are among the most common and effective features used in sleep stage classification from temporal, spectral, entropy-based and nonlinear categories. The feature selection methods were evaluated and compared using three criteria: classification accuracy, stability, and similarity. Simulation results show that MRMR-MID achieves the highest classification performance while Fisher method provides the most stable ranking. In our simulations, the performance of the aggregation methods was in the average level, although they are known to generate more stable results and better accuracy. The Borda and RRA rank aggregation methods could not outperform significantly the conventional feature ranking methods. Among

Rank Two Affine Manifolds in Genus 3

OpenAIRE

Aulicino, David; Nguyen, Duc-Manh

2016-01-01

We complete the classification of rank two affine manifolds in the moduli space of translation surfaces in genus three. Combined with a recent result of Mirzakhani and Wright, this completes the classification of higher rank affine manifolds in genus three.

Sensitivity ranking for freshwater invertebrates towards hydrocarbon contaminants.

Science.gov (United States)

Gerner, Nadine V; Cailleaud, Kevin; Bassères, Anne; Liess, Matthias; Beketov, Mikhail A

2017-11-01

Hydrocarbons have an utmost economical importance but may also cause substantial ecological impacts due to accidents or inadequate transportation and use. Currently, freshwater biomonitoring methods lack an indicator that can unequivocally reflect the impacts caused by hydrocarbons while being independent from effects of other stressors. The aim of the present study was to develop a sensitivity ranking for freshwater invertebrates towards hydrocarbon contaminants, which can be used in hydrocarbon-specific bioindicators. We employed the Relative Sensitivity method and developed the sensitivity ranking S hydrocarbons based on literature ecotoxicological data supplemented with rapid and mesocosm test results. A first validation of the sensitivity ranking based on an earlier field study has been conducted and revealed the S hydrocarbons ranking to be promising for application in sensitivity based indicators. Thus, the first results indicate that the ranking can serve as the core component of future hydrocarbon-specific and sensitivity trait based bioindicators.

Tensor rank of the tripartite state |W>xn

International Nuclear Information System (INIS)

Yu Nengkun; Guo Cheng; Duan Runyao; Chitambar, Eric

2010-01-01

Tensor rank refers to the number of product states needed to express a given multipartite quantum state. Its nonadditivity as an entanglement measure has recently been observed. In this Brief Report, we estimate the tensor rank of multiple copies of the tripartite state |W>=(1/√(3))(|100>+|010>+|001>). Both an upper bound and a lower bound of this rank are derived. In particular, it is proven that the rank of |W> x 2 is 7, thus resolving a previously open problem. Some implications of this result are discussed in terms of transformation rates between |W> xn and multiple copies of the state |GHZ>=(1/√(2))(|000>+|111>).

Low-Rank Matrix Factorization With Adaptive Graph Regularizer.

Science.gov (United States)

Lu, Gui-Fu; Wang, Yong; Zou, Jian

2016-05-01

In this paper, we present a novel low-rank matrix factorization algorithm with adaptive graph regularizer (LMFAGR). We extend the recently proposed low-rank matrix with manifold regularization (MMF) method with an adaptive regularizer. Different from MMF, which constructs an affinity graph in advance, LMFAGR can simultaneously seek graph weight matrix and low-dimensional representations of data. That is, graph construction and low-rank matrix factorization are incorporated into a unified framework, which results in an automatically updated graph rather than a predefined one. The experimental results on some data sets demonstrate that the proposed algorithm outperforms the state-of-the-art low-rank matrix factorization methods.

Dominance-based ranking functions for interval-valued intuitionistic fuzzy sets.

Science.gov (United States)

Chen, Liang-Hsuan; Tu, Chien-Cheng

2014-08-01

The ranking of interval-valued intuitionistic fuzzy sets (IvIFSs) is difficult since they include the interval values of membership and nonmembership. This paper proposes ranking functions for IvIFSs based on the dominance concept. The proposed ranking functions consider the degree to which an IvIFS dominates and is not dominated by other IvIFSs. Based on the bivariate framework and the dominance concept, the functions incorporate not only the boundary values of membership and nonmembership, but also the relative relations among IvIFSs in comparisons. The dominance-based ranking functions include bipolar evaluations with a parameter that allows the decision-maker to reflect his actual attitude in allocating the various kinds of dominance. The relationship for two IvIFSs that satisfy the dual couple is defined based on four proposed ranking functions. Importantly, the proposed ranking functions can achieve a full ranking for all IvIFSs. Two examples are used to demonstrate the applicability and distinctiveness of the proposed ranking functions.

Ranking of Unwarranted Variations in Healthcare Treatments

NARCIS (Netherlands)

Moes, Herry; Brekelmans, Ruud; Hamers, Herbert; Hasaart, F.

2017-01-01

In this paper, we introduce a framework designed to identify and rank possible unwarranted variation of treatments in healthcare. The innovative aspect of this framework is a ranking procedure that aims to identify healthcare institutions where unwarranted variation is most severe, and diagnosis

Exploratory Metabolomic Analyses Reveal Compounds Correlated with Lutein Concentration in Frontal Cortex, Hippocampus, and Occipital Cortex of Human Infant Brain.

Directory of Open Access Journals (Sweden)

Jacqueline C Lieblein-Boff

Full Text Available Lutein is a dietary carotenoid well known for its role as an antioxidant in the macula, and recent reports implicate a role for lutein in cognitive function. Lutein is the dominant carotenoid in both pediatric and geriatric brain tissue. In addition, cognitive function in older adults correlated with macular and postmortem brain lutein concentrations. Furthermore, lutein was found to preferentially accumulate in the infant brain in comparison to other carotenoids that are predominant in diet. While lutein is consistently related to cognitive function, the mechanisms by which lutein may influence cognition are not clear. In an effort to identify potential mechanisms through which lutein might influence neurodevelopment, an exploratory study relating metabolite signatures and lutein was completed. Post-mortem metabolomic analyses were performed on human infant brain tissues in three regions important for learning and memory: the frontal cortex, hippocampus, and occipital cortex. Metabolomic profiles were compared to lutein concentration, and correlations were identified and reported here. A total of 1276 correlations were carried out across all brain regions. Of 427 metabolites analyzed, 257 were metabolites of known identity. Unidentified metabolite correlations (510 were excluded. In addition, moderate correlations with xenobiotic relationships (2 or those driven by single outliers (3 were excluded from further study. Lutein concentrations correlated with lipid pathway metabolites, energy pathway metabolites, brain osmolytes, amino acid neurotransmitters, and the antioxidant homocarnosine. These correlations were often brain region-specific. Revealing relationships between lutein and metabolic pathways may help identify potential candidates on which to complete further analyses and may shed light on important roles of lutein in the human brain during development.

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.

Low-rank coal research. Quarterly report, January--March 1990

Energy Technology Data Exchange (ETDEWEB)

1990-08-01

This document contains several quarterly progress reports for low-rank coal research that was performed from January-March 1990. Reports in Control Technology and Coal Preparation Research are in Flue Gas Cleanup, Waste Management, and Regional Energy Policy Program for the Northern Great Plains. Reports in Advanced Research and Technology Development are presented in Turbine Combustion Phenomena, Combustion Inorganic Transformation (two sections), Liquefaction Reactivity of Low-Rank Coals, Gasification Ash and Slag Characterization, and Coal Science. Reports in Combustion Research cover Fluidized-Bed Combustion, Beneficiation of Low-Rank Coals, Combustion Characterization of Low-Rank Coal Fuels, Diesel Utilization of Low-Rank Coals, and Produce and Characterize HWD (hot-water drying) Fuels for Heat Engine Applications. Liquefaction Research is reported in Low-Rank Coal Direct Liquefaction. Gasification Research progress is discussed for Production of Hydrogen and By-Products from Coal and for Chemistry of Sulfur Removal in Mild Gas.

Simultaneous multislice magnetic resonance fingerprinting with low-rank and subspace modeling.

Science.gov (United States)

Bo Zhao; Bilgic, Berkin; Adalsteinsson, Elfar; Griswold, Mark A; Wald, Lawrence L; Setsompop, Kawin

2017-07-01

Magnetic resonance fingerprinting (MRF) is a new quantitative imaging paradigm that enables simultaneous acquisition of multiple magnetic resonance tissue parameters (e.g., T 1 , T 2 , and spin density). Recently, MRF has been integrated with simultaneous multislice (SMS) acquisitions to enable volumetric imaging with faster scan time. In this paper, we present a new image reconstruction method based on low-rank and subspace modeling for improved SMS-MRF. Here the low-rank model exploits strong spatiotemporal correlation among contrast-weighted images, while the subspace model captures the temporal evolution of magnetization dynamics. With the proposed model, the image reconstruction problem is formulated as a convex optimization problem, for which we develop an algorithm based on variable splitting and the alternating direction method of multipliers. The performance of the proposed method has been evaluated by numerical experiments, and the results demonstrate that the proposed method leads to improved accuracy over the conventional approach. Practically, the proposed method has a potential to allow for a 3× speedup with minimal reconstruction error, resulting in less than 5 sec imaging time per slice.

Male rank affects reproductive success and offspring performance in bank voles.

Science.gov (United States)

Kruczek, Małgorzata; Zatorska, Magdalena

2008-07-05

Laboratory studies reveal that in several rodent species the females prefer dominant males as mating partners. Here we investigate the correlation between males' social rank and their reproductive success. Similar numbers of females mating with relatively more dominant or relatively more subordinate males produced a litter, and parturition took place 19-21 days after mating. Relatively more dominant males tended to sire more pups than did relatively more subordinates, but the mean number of offspring per litter did not differ significantly between the two groups. Significantly more pups fathered by relatively more dominant males survived to weaning than those sired by relatively more subordinate fathers. Dominance had a long-term effect on the reproductive activity of the offspring: their rate of sexual maturation was increased. In pups sired by a relatively more dominant father, the uteruses of females, and the testes and accessory sex glands of males, were significantly heavier than those of offspring born to relatively more subordinate males. Our results suggest that social rank is an important determinant of the reproductive success of bank vole males.

Level-rank duality of untwisted and twisted D-branes

International Nuclear Information System (INIS)

Naculich, Stephen G.; Schnitzer, Howard J.

2006-01-01

Level-rank duality of untwisted and twisted D-branes of WZW models is explored. We derive the relation between D0-brane charges of level-rank dual untwisted D-branes of su-bar (N) K and sp-bar (n) k , and of level-rank dual twisted D-branes of su-bar (2n+1) 2k+1 . The analysis of level-rank duality of twisted D-branes of su-bar (2n+1) 2k+1 is facilitated by their close relation to untwisted D-branes of sp-bar (n) k . We also demonstrate level-rank duality of the spectrum of an open string stretched between untwisted or twisted D-branes in each of these cases

Indirect two-sided relative ranking: a robust similarity measure for gene expression data

Directory of Open Access Journals (Sweden)

Licamele Louis

2010-03-01

Full Text Available Abstract Background There is a large amount of gene expression data that exists in the public domain. This data has been generated under a variety of experimental conditions. Unfortunately, these experimental variations have generally prevented researchers from accurately comparing and combining this wealth of data, which still hides many novel insights. Results In this paper we present a new method, which we refer to as indirect two-sided relative ranking, for comparing gene expression profiles that is robust to variations in experimental conditions. This method extends the current best approach, which is based on comparing the correlations of the up and down regulated genes, by introducing a comparison based on the correlations in rankings across the entire database. Because our method is robust to experimental variations, it allows a greater variety of gene expression data to be combined, which, as we show, leads to richer scientific discoveries. Conclusions We demonstrate the benefit of our proposed indirect method on several datasets. We first evaluate the ability of the indirect method to retrieve compounds with similar therapeutic effects across known experimental barriers, namely vehicle and batch effects, on two independent datasets (one private and one public. We show that our indirect method is able to significantly improve upon the previous state-of-the-art method with a substantial improvement in recall at rank 10 of 97.03% and 49.44%, on each dataset, respectively. Next, we demonstrate that our indirect method results in improved accuracy for classification in several additional datasets. These datasets demonstrate the use of our indirect method for classifying cancer subtypes, predicting drug sensitivity/resistance, and classifying (related cell types. Even in the absence of a known (i.e., labeled experimental barrier, the improvement of the indirect method in each of these datasets is statistically significant.

Order-disorder transition in conflicting dynamics leading to rank-frequency generalized beta distributions

Science.gov (United States)

Alvarez-Martinez, R.; Martinez-Mekler, G.; Cocho, G.

2011-01-01

The behavior of rank-ordered distributions of phenomena present in a variety of fields such as biology, sociology, linguistics, finance and geophysics has been a matter of intense research. Often power laws have been encountered; however, their validity tends to hold mainly for an intermediate range of rank values. In a recent publication (Martínez-Mekler et al., 2009 [7]), a generalization of the functional form of the beta distribution has been shown to give excellent fits for many systems of very diverse nature, valid for the whole range of rank values, regardless of whether or not a power law behavior has been previously suggested. Here we give some insight on the significance of the two free parameters which appear as exponents in the functional form, by looking into discrete probabilistic branching processes with conflicting dynamics. We analyze a variety of realizations of these so-called expansion-modification models first introduced by Wentian Li (1989) [10]. We focus our attention on an order-disorder transition we encounter as we vary the modification probability p. We characterize this transition by means of the fitting parameters. Our numerical studies show that one of the fitting exponents is related to the presence of long-range correlations exhibited by power spectrum scale invariance, while the other registers the effect of disordering elements leading to a breakdown of these properties. In the absence of long-range correlations, this parameter is sensitive to the occurrence of unlikely events. We also introduce an approximate calculation scheme that relates this dynamics to multinomial multiplicative processes. A better understanding through these models of the meaning of the generalized beta-fitting exponents may contribute to their potential for identifying and characterizing universality classes.

UTV Expansion Pack: Special-Purpose Rank-Revealing Algorithms

DEFF Research Database (Denmark)

Fierro, Ricardo D.; Hansen, Per Christian

2005-01-01

This collection of Matlab 7.0 software supplements and complements the package UTV Tools from 1999, and includes implementations of special-purpose rank-revealing algorithms developed since the publication of the original package. We provide algorithms for computing and modifying symmetric rank-r...... values of a sparse or structured matrix. These new algorithms have applications in signal processing, optimization and LSI information retrieval.......This collection of Matlab 7.0 software supplements and complements the package UTV Tools from 1999, and includes implementations of special-purpose rank-revealing algorithms developed since the publication of the original package. We provide algorithms for computing and modifying symmetric rank......-revealing VSV decompositions, we expand the algorithms for the ULLV decomposition of a matrix pair to handle interference-type problems with a rank-deficient covariance matrix, and we provide a robust and reliable Lanczos algorithm which - despite its simplicity - is able to capture all the dominant singular...

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 .

Evaluating e-Government and Good Governance Correlation

Directory of Open Access Journals (Sweden)

Suhardi Suhardi

2016-03-01

Full Text Available Assessing the achievement of Indonesian government institutions in implementing e-government has been conducted since around a decade ago. Several national assessments are available with almost the same ranking results. There is an agreement that the ultimate goal of e-government implementation is to achieve good government governance (GGG, while success stories of e-government require good governance practices. This study explored the correlation between e-government achievement and GGG achievement in Indonesia. Spearman’s rank correlation was used to characterize the relationship strength between e-government assessment results and good governance assessment results. The data were collected from institutions that participated in e-government and good governance assessments. The results showed that the correlation between these two entities is not very strong. Most cases showed that e-government implementation and the achievement of good governance have only a moderate positive correlation and none of the studied cases indicated a significant connection. This result can be attributed to the lack of emphasis on goals achievement in the assessments. Thus, it is recommended that future Indonesian e-government assessments should involve impact indicators.

Rank 2 fusion rings are complete intersections

DEFF Research Database (Denmark)

Andersen, Troels Bak

We give a non-constructive proof that fusion rings attached to a simple complex Lie algebra of rank 2 are complete intersections.......We give a non-constructive proof that fusion rings attached to a simple complex Lie algebra of rank 2 are complete intersections....

Entity Ranking using Wikipedia as a Pivot

NARCIS (Netherlands)

R. Kaptein; P. Serdyukov; A.P. de Vries (Arjen); J. Kamps

2010-01-01

htmlabstractIn this paper we investigate the task of Entity Ranking on the Web. Searchers looking for entities are arguably better served by presenting a ranked list of entities directly, rather than a list of web pages with relevant but also potentially redundant information about

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; ...

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

LogDet Rank Minimization with Application to Subspace Clustering

Directory of Open Access Journals (Sweden)

Zhao Kang

2015-01-01

Full Text Available Low-rank matrix is desired in many machine learning and computer vision problems. Most of the recent studies use the nuclear norm as a convex surrogate of the rank operator. However, all singular values are simply added together by the nuclear norm, and thus the rank may not be well approximated in practical problems. In this paper, we propose using a log-determinant (LogDet function as a smooth and closer, though nonconvex, approximation to rank for obtaining a low-rank representation in subspace clustering. Augmented Lagrange multipliers strategy is applied to iteratively optimize the LogDet-based nonconvex objective function on potentially large-scale data. By making use of the angular information of principal directions of the resultant low-rank representation, an affinity graph matrix is constructed for spectral clustering. Experimental results on motion segmentation and face clustering data demonstrate that the proposed method often outperforms state-of-the-art subspace clustering algorithms.

Low rank magnetic resonance fingerprinting.

Science.gov (United States)

Mazor, Gal; Weizman, Lior; Tal, Assaf; Eldar, Yonina C

2016-08-01

Magnetic Resonance Fingerprinting (MRF) is a relatively new approach that provides quantitative MRI using randomized acquisition. Extraction of physical quantitative tissue values is preformed off-line, based on acquisition with varying parameters and a dictionary generated according to the Bloch equations. MRF uses hundreds of radio frequency (RF) excitation pulses for acquisition, and therefore high under-sampling ratio in the sampling domain (k-space) is required. This under-sampling causes spatial artifacts that hamper the ability to accurately estimate the quantitative tissue values. In this work, we introduce a new approach for quantitative MRI using MRF, called Low Rank MRF. We exploit the low rank property of the temporal domain, on top of the well-known sparsity of the MRF signal in the generated dictionary domain. We present an iterative scheme that consists of a gradient step followed by a low rank projection using the singular value decomposition. Experiments on real MRI data demonstrate superior results compared to conventional implementation of compressed sensing for MRF at 15% sampling ratio.

Two Ranking Methods of Single Valued Triangular Neutrosophic Numbers to Rank and Evaluate Information Systems Quality

Directory of Open Access Journals (Sweden)

Samah Ibrahim Abdel Aal

2018-03-01

Full Text Available The concept of neutrosophic can provide a generalization of fuzzy set and intuitionistic fuzzy set that make it is the best fit in representing indeterminacy and uncertainty. Single Valued Triangular Numbers (SVTrN-numbers is a special case of neutrosophic set that can handle ill-known quantity very difficult problems. This work intended to introduce a framework with two types of ranking methods. The results indicated that each ranking method has its own advantage. In this perspective, the weighted value and ambiguity based method gives more attention to uncertainty in ranking and evaluating ISQ as well as it takes into account cut sets of SVTrN numbers that can reflect the information on Truth-membership-membership degree, false membership-membership degree and Indeterminacy-membership degree. The value index and ambiguity index method can reflect the decision maker's subjectivity attitude to the SVTrN- numbers.

Lerot: An Online Learning to Rank Framework

NARCIS (Netherlands)

Schuth, A.; Hofmann, K.; Whiteson, S.; de Rijke, M.

2013-01-01

Online learning to rank methods for IR allow retrieval systems to optimize their own performance directly from interactions with users via click feedback. In the software package Lerot, presented in this paper, we have bundled all ingredients needed for experimenting with online learning to rank for

Entity ranking using Wikipedia as a pivot

NARCIS (Netherlands)

Kaptein, R.; Serdyukov, P.; de Vries, A.; Kamps, J.; Huang, X.J.; Jones, G.; Koudas, N.; Wu, X.; Collins-Thompson, K.

2010-01-01

In this paper we investigate the task of Entity Ranking on the Web. Searchers looking for entities are arguably better served by presenting a ranked list of entities directly, rather than a list of web pages with relevant but also potentially redundant information about these entities. Since

Encoding of QC-LDPC Codes of Rank Deficient Parity Matrix

Directory of Open Access Journals (Sweden)

Mohammed Kasim Mohammed Al-Haddad

2016-05-01

Full Text Available the encoding of long low density parity check (LDPC codes presents a challenge compared to its decoding. The Quasi Cyclic (QC LDPC codes offer the advantage for reducing the complexity for both encoding and decoding due to its QC structure. Most QC-LDPC codes have rank deficient parity matrix and this introduces extra complexity over the codes with full rank parity matrix. In this paper an encoding scheme of QC-LDPC codes is presented that is suitable for codes with full rank parity matrix and rank deficient parity matrx. The extra effort required by the codes with rank deficient parity matrix over the codes of full rank parity matrix is investigated.

7 CFR 1491.6 - Ranking considerations and proposal selection.

Science.gov (United States)

2010-01-01

... 7 Agriculture 10 2010-01-01 2010-01-01 false Ranking considerations and proposal selection. 1491.6... PROGRAM General Provisions § 1491.6 Ranking considerations and proposal selection. (a) Before the State.... The national ranking criteria will be established by the Chief and the State criteria will be...

Extracting Rankings for Spatial Keyword Queries from GPS Data

DEFF Research Database (Denmark)

Keles, Ilkcan; Jensen, Christian Søndergaard; Saltenis, Simonas

2018-01-01

Studies suggest that many search engine queries have local intent. We consider the evaluation of ranking functions important for such queries. The key challenge is to be able to determine the “best” ranking for a query, as this enables evaluation of the results of ranking functions. We propose...

Revisiting the Relationship between Institutional Rank and Student Engagement

Science.gov (United States)

Zilvinskis, John; Louis Rocconi

2018-01-01

College rankings dominate the conversation regarding quality in postsecondary education. However, the criteria used to rank institutions often have nothing to do with the quality of education students receive. A decade ago, Pike (2004) demonstrated that institutional rank had little association with student involvement in educational activities.…

Rank of quantized universal enveloping algebras and modular functions

International Nuclear Information System (INIS)

Majid, S.; Soibelman, Ya.S.

1991-01-01

We compute an intrinsic rank invariant for quasitriangular Hopf algebras in the case of general quantum groups U q (g). As a function of q the rank has remarkable number theoretic properties connected with modular covariance and Galois theory. A number of examples are treated in detail, including rank (U q (su(3)) and rank (U q (e 8 )). We briefly indicate a physical interpretation as relating Chern-Simons theory with the theory of a quantum particle confined to an alcove of g. (orig.)

Ranking Music Data by Relevance and Importance

DEFF Research Database (Denmark)

Ruxanda, Maria Magdalena; Nanopoulos, Alexandros; Jensen, Christian Søndergaard

2008-01-01

Due to the rapidly increasing availability of audio files on the Web, it is relevant to augment search engines with advanced audio search functionality. In this context, the ranking of the retrieved music is an important issue. This paper proposes a music ranking method capable of flexibly fusing...

Academic Ranking--From Its Genesis to Its International Expansion

Science.gov (United States)

Vieira, Rosilene C.; Lima, Manolita C.

2015-01-01

Given the visibility and popularity of rankings that encompass the measurement of quality of post-graduate courses, for instance, the MBA (Master of Business Administration) or graduate studies program (MSc and PhD) as do global academic rankings--Academic Ranking of World Universities-ARWU, Times Higher/Thomson Reuters World University Ranking…

RANK/RANKL/OPG Signalization Implication in Periodontitis: New Evidence from a RANK Transgenic Mouse Model

Directory of Open Access Journals (Sweden)

Bouchra Sojod

2017-05-01

Full Text Available Periodontitis is based on a complex inflammatory over-response combined with possible genetic predisposition factors. The RANKL/RANK/OPG signaling pathway is implicated in bone resorption through its key function in osteoclast differentiation and activation, as well as in the inflammatory response. This central element of osteo-immunology has been suggested to be perturbed in several diseases, including periodontitis, as it is a predisposing factor for this disease. The aim of the present study was to validate this hypothesis using a transgenic mouse line, which over-expresses RANK (RTg and develops a periodontitis-like phenotype at 5 months of age. RTg mice exhibited severe alveolar bone loss, an increased number of TRAP positive cells, and disorganization of periodontal ligaments. This phenotype was more pronounced in females. We also observed dental root resorption lacunas. Hyperplasia of the gingival epithelium, including Malassez epithelial rests, was visible as early as 25 days, preceding any other symptoms. These results demonstrate that perturbations of the RANKL/RANK/OPG system constitute a core element of periodontitis, and more globally, osteo-immune diseases.

RANK/RANKL/OPG Signalization Implication in Periodontitis: New Evidence from a RANK Transgenic Mouse Model

Science.gov (United States)

Sojod, Bouchra; Chateau, Danielle; Mueller, Christopher G.; Babajko, Sylvie; Berdal, Ariane; Lézot, Frédéric; Castaneda, Beatriz

2017-01-01

Periodontitis is based on a complex inflammatory over-response combined with possible genetic predisposition factors. The RANKL/RANK/OPG signaling pathway is implicated in bone resorption through its key function in osteoclast differentiation and activation, as well as in the inflammatory response. This central element of osteo-immunology has been suggested to be perturbed in several diseases, including periodontitis, as it is a predisposing factor for this disease. The aim of the present study was to validate this hypothesis using a transgenic mouse line, which over-expresses RANK (RTg) and develops a periodontitis-like phenotype at 5 months of age. RTg mice exhibited severe alveolar bone loss, an increased number of TRAP positive cells, and disorganization of periodontal ligaments. This phenotype was more pronounced in females. We also observed dental root resorption lacunas. Hyperplasia of the gingival epithelium, including Malassez epithelial rests, was visible as early as 25 days, preceding any other symptoms. These results demonstrate that perturbations of the RANKL/RANK/OPG system constitute a core element of periodontitis, and more globally, osteo-immune diseases. PMID:28596739

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....

An Adaptive Reordered Method for Computing PageRank

Directory of Open Access Journals (Sweden)

Yi-Ming Bu

2013-01-01

Full Text Available We propose an adaptive reordered method to deal with the PageRank problem. It has been shown that one can reorder the hyperlink matrix of PageRank problem to calculate a reduced system and get the full PageRank vector through forward substitutions. This method can provide a speedup for calculating the PageRank vector. We observe that in the existing reordered method, the cost of the recursively reordering procedure could offset the computational reduction brought by minimizing the dimension of linear system. With this observation, we introduce an adaptive reordered method to accelerate the total calculation, in which we terminate the reordering procedure appropriately instead of reordering to the end. Numerical experiments show the effectiveness of this adaptive reordered method.

A Note on the PageRank of Undirected Graphs

OpenAIRE

Grolmusz, Vince

2012-01-01

The PageRank is a widely used scoring function of networks in general and of the World Wide Web graph in particular. The PageRank is defined for directed graphs, but in some special cases applications for undirected graphs occur. In the literature it is widely noted that the PageRank for undirected graphs are proportional to the degrees of the vertices of the graph. We prove that statement for a particular personalization vector in the definition of the PageRank, and we also show that in gene...

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.

Multidimensional ranking the design and development of U-Multirank

CERN Document Server

Ziegele, Frank

2012-01-01

During the last decades ranking has become one of the most controversial issues in higher education and research. It is widely recognized now that, although some of the current rankings can be severely criticized, they seem to be here to stay. In addition, rankings appear to have a great impact on decision-makers at all levels of higher education and research systems worldwide, including in universities. Rankings reflect a growing international competition among universities for talent and resources; at the same time they reinforce competition by their very results. Yet major concerns remain a

Is there a 'Mid-Rank Trap' for Universities'

OpenAIRE

Chang Da Wan

2015-01-01

The middle-income trap is an economic phenomenon to describe economies that have stagnated at the middle-income level and failed to progress into the high-income level. Inspired by this economic concept, this paper explores a hypothesis: is there a 'mid-rank trap' for universities in the exercise to rank universities globally' Using the rankings between 2004 and 2014 that were jointly and separately developed by Times Higher Education and Quacquarelli Symonds Company, this paper argues that t...

A Rational Method for Ranking Engineering Programs.

Science.gov (United States)

Glower, Donald D.

1980-01-01

Compares two methods for ranking academic programs, the opinion poll v examination of career successes of the program's alumni. For the latter, "Who's Who in Engineering" and levels of research funding provided data. Tables display resulting data and compare rankings by the two methods for chemical engineering and civil engineering. (CS)

Mining Feedback in Ranking and Recommendation Systems

Science.gov (United States)

Zhuang, Ziming

2009-01-01

The amount of online information has grown exponentially over the past few decades, and users become more and more dependent on ranking and recommendation systems to address their information seeking needs. The advance in information technologies has enabled users to provide feedback on the utilities of the underlying ranking and recommendation…

Monte Carlo methods of PageRank computation

NARCIS (Netherlands)

Litvak, Nelli

2004-01-01

We describe and analyze an on-line Monte Carlo method of PageRank computation. The PageRank is being estimated basing on results of a large number of short independent simulation runs initiated from each page that contains outgoing hyperlinks. The method does not require any storage of the hyperlink

Dynamic collective entity representations for entity ranking

NARCIS (Netherlands)

Graus, D.; Tsagkias, M.; Weerkamp, W.; Meij, E.; de Rijke, M.

2016-01-01

Entity ranking, i.e., successfully positioning a relevant entity at the top of the ranking for a given query, is inherently difficult due to the potential mismatch between the entity's description in a knowledge base, and the way people refer to the entity when searching for it. To counter this

Comparative Case Studies on Indonesian Higher Education Rankings

Science.gov (United States)

Kurniasih, Nuning; Hasyim, C.; Wulandari, A.; Setiawan, M. I.; Ahmar, A. S.

2018-01-01

The quality of the higher education is the result of a continuous process. There are many indicators that can be used to assess the quality of a higher education. The existence of different indicators makes the different result of university rankings. This research aims to find variables that can connect ranking indicators that are used by Indonesian Ministry of Research, Technology, and Higher Education with indicators that are used by international rankings by taking two kind of ranking systems i.e. Webometrics and 4icu. This research uses qualitative research method with comparative case studies approach. The result of the research shows that to bridge the indicators that are used by Indonesian Ministry or Research, Technology, and Higher Education with web-based ranking system like Webometrics and 4icu so that the Indonesian higher education institutions need to open access towards either scientific or non-scientific that are publicly used into web-based environment. One of the strategies that can be used to improve the openness and access towards scientific work of a university is by involving in open science and collaboration.

Is there a 'Mid-Rank Trap' for Universities'

Directory of Open Access Journals (Sweden)

Chang Da Wan

2015-10-01

Full Text Available The middle-income trap is an economic phenomenon to describe economies that have stagnated at the middle-income level and failed to progress into the high-income level. Inspired by this economic concept, this paper explores a hypothesis: is there a 'mid-rank trap' for universities in the exercise to rank universities globally' Using the rankings between 2004 and 2014 that were jointly and separately developed by Times Higher Education and Quacquarelli Symonds Company, this paper argues that there is indeed a phenomenon, which I term as 'mid-rank trap' whereby universities remain stagnant for a decade in a similar band of the rankings. Having established the hypothesis for universities, the paper examines policies and interventions that have been successfully carried out to elevate economies away from the middle-income trap, and importantly, to draw out the underlying principles of these economic policies and interventions that can be incorporated into policymaking and strategic planning for universities using the Malaysian higher education system as a case study.

Refining dermatology journal impact factors using PageRank.

Science.gov (United States)

Dellavalle, Robert P; Schilling, Lisa M; Rodriguez, Marko A; Van de Sompel, Herbert; Bollen, Johan

2007-07-01

Thomson Institute for Scientific Information's journal impact factor, the most common measure of journal status, is based on crude citation counts that do not account for the quality of the journals where the citations originate. This study examines how accounting for citation origin affects the impact factor ranking of dermatology journals. The 2003 impact factors of dermatology journals were adjusted by a weighted PageRank algorithm that assigned greater weight to citations originating in more frequently cited journals. Adjusting for citation origin moved the rank of the Journal of the American Academy of Dermatology higher than that of the Archives of Dermatology (third to second) but did not affect the ranking of the highest impact dermatology journal, the Journal of Investigative Dermatology. The dermatology journals most positively affected by adjusting for citation origin were Contact Dermatitis (moving from 22nd to 7th in rankings) and Burns (21st to 10th). Dermatology journals most negatively affected were Seminars in Cutaneous Medicine and Surgery (5th to 14th), the Journal of Cutaneous Medicine and Surgery (19th to 27th), and the Journal of Investigative Dermatology Symposium Proceedings (26th to 34th). Current measures of dermatology journal status do not incorporate survey data from dermatologists regarding which journals dermatologists esteem most. Adjusting for citation origin provides a more refined measure of journal status and changes relative dermatology journal rankings.

10 CFR 455.131 - State ranking of grant applications.

Science.gov (United States)

2010-01-01

... 10 Energy 3 2010-01-01 2010-01-01 false State ranking of grant applications. 455.131 Section 455... State ranking of grant applications. (a) Except as provided by § 455.92 of this part, all eligible... audit or energy use evaluation pursuant to § 455.20(k). Each State shall develop separate rankings for...

Tutorial: Calculating Percentile Rank and Percentile Norms Using SPSS

Science.gov (United States)

Baumgartner, Ted A.

2009-01-01

Practitioners can benefit from using norms, but they often have to develop their own percentile rank and percentile norms. This article is a tutorial on how to quickly and easily calculate percentile rank and percentile norms using SPSS, and this information is presented for a data set. Some issues in calculating percentile rank and percentile…

A new measure of output ranking performance in automatic document retrieval systems

International Nuclear Information System (INIS)

Ebinuma, Yukio

1987-01-01

A new measure of output ranking performance is proposed on the basis of recall-precision pairs corresponding to ranks of relevant documents when documents are arranged in decreasing order of their scores given by a ranking function. This measure is constructed to take a single value in starting from the area under a recall-precision graph for a ranked output and to distinguish meaningful ranking with a positive value between 0 and 1 from meaningless ranking with a negative value. It is clarified too that the measure must be useful in practice to evaluate the ranking performance made by various ranking function models and to choose the best ranking models among them. (author)

Consequence ranking of radionuclides in Hanford tank waste

International Nuclear Information System (INIS)

Schmittroth, F.A.; De Lorenzo, T.H.

1995-09-01

Radionuclides in the Hanford tank waste are ranked relative to their consequences for the Low-Level Tank Waste program. The ranking identifies key radionuclides where further study is merited. In addition to potential consequences for intrude and drinking-water scenarios supporting low-level waste activities, a ranking based on shielding criteria is provided. The radionuclide production inventories are based on a new and independent ORIGEN2 calculation representing the operation of all Hanford single-pass reactors and the N Reactor

Reduced Rank Adaptive Filtering in Impulsive Noise Environments

KAUST Repository

Soury, Hamza

2014-01-06

An impulsive noise environment is used in this paper. A new aspect of signal truncation is deployed to reduce the harmful effect of the impulsive noise to the signal. A full rank direct solution is derived followed by an iterative solution. The reduced rank adaptive filter is presented in this environment by using two methods for rank reduction. The minimized objective function is defined using the Lp norm. The results are presented and the efficiency of each algorithm is discussed.

Reduced Rank Adaptive Filtering in Impulsive Noise Environments

KAUST Repository

Soury, Hamza; Abed-Meraim, Karim; Alouini, Mohamed-Slim

2014-01-01

An impulsive noise environment is used in this paper. A new aspect of signal truncation is deployed to reduce the harmful effect of the impulsive noise to the signal. A full rank direct solution is derived followed by an iterative solution. The reduced rank adaptive filter is presented in this environment by using two methods for rank reduction. The minimized objective function is defined using the Lp norm. The results are presented and the efficiency of each algorithm is discussed.

Correlation between centrality metrics and their application to the opinion model

NARCIS (Netherlands)

Li, C.; Li, Q.; Van Mieghem, P.F.A.; Stanley, H.E.; Wang, H.

2015-01-01

In recent decades, a number of centrality metrics describing network properties of nodes have been proposed to rank the importance of nodes. In order to understand the correlations between centrality metrics and to approximate a high-complexity centrality metric by a strongly correlated

The Visual Analogue Scale for Rating, Ranking and Paired-Comparison (VAS-RRP): A new technique for psychological measurement.

Science.gov (United States)

Sung, Yao-Ting; Wu, Jeng-Shin

2018-04-17

Traditionally, the visual analogue scale (VAS) has been proposed to overcome the limitations of ordinal measures from Likert-type scales. However, the function of VASs to overcome the limitations of response styles to Likert-type scales has not yet been addressed. Previous research using ranking and paired comparisons to compensate for the response styles of Likert-type scales has suffered from limitations, such as that the total score of ipsative measures is a constant that cannot be analyzed by means of many common statistical techniques. In this study we propose a new scale, called the Visual Analogue Scale for Rating, Ranking, and Paired-Comparison (VAS-RRP), which can be used to collect rating, ranking, and paired-comparison data simultaneously, while avoiding the limitations of each of these data collection methods. The characteristics, use, and analytic method of VAS-RRPs, as well as how they overcome the disadvantages of Likert-type scales, ranking, and VASs, are discussed. On the basis of analyses of simulated and empirical data, this study showed that VAS-RRPs improved reliability, response style bias, and parameter recovery. Finally, we have also designed a VAS-RRP Generator for researchers' construction and administration of their own VAS-RRPs.

Proceedings of the sixteenth biennial low-rank fuels symposium

International Nuclear Information System (INIS)

1991-01-01

Low-rank coals represent a major energy resource for the world. The Low-Rank Fuels Symposium, building on the traditions established by the Lignite Symposium, focuses on the key opportunities for this resource. This conference offers a forum for leaders from industry, government, and academia to gather to share current information on the opportunities represented by low-rank coals. In the United States and throughout the world, the utility industry is the primary user of low-rank coals. As such, current experiences and future opportunities for new technologies in this industry were the primary focuses of the symposium

Proceedings of the sixteenth biennial low-rank fuels symposium

Energy Technology Data Exchange (ETDEWEB)

1991-01-01

Low-rank coals represent a major energy resource for the world. The Low-Rank Fuels Symposium, building on the traditions established by the Lignite Symposium, focuses on the key opportunities for this resource. This conference offers a forum for leaders from industry, government, and academia to gather to share current information on the opportunities represented by low-rank coals. In the United States and throughout the world, the utility industry is the primary user of low-rank coals. As such, current experiences and future opportunities for new technologies in this industry were the primary focuses of the symposium.

Maximising information recovery from rank-order codes

Science.gov (United States)

Sen, B.; Furber, S.

2007-04-01

The central nervous system encodes information in sequences of asynchronously generated voltage spikes, but the precise details of this encoding are not well understood. Thorpe proposed rank-order codes as an explanation of the observed speed of information processing in the human visual system. The work described in this paper is inspired by the performance of SpikeNET, a biologically inspired neural architecture using rank-order codes for information processing, and is based on the retinal model developed by VanRullen and Thorpe. This model mimics retinal information processing by passing an input image through a bank of Difference of Gaussian (DoG) filters and then encoding the resulting coefficients in rank-order. To test the effectiveness of this encoding in capturing the information content of an image, the rank-order representation is decoded to reconstruct an image that can be compared with the original. The reconstruction uses a look-up table to infer the filter coefficients from their rank in the encoded image. Since the DoG filters are approximately orthogonal functions, they are treated as their own inverses in the reconstruction process. We obtained a quantitative measure of the perceptually important information retained in the reconstructed image relative to the original using a slightly modified version of an objective metric proposed by Petrovic. It is observed that around 75% of the perceptually important information is retained in the reconstruction. In the present work we reconstruct the input using a pseudo-inverse of the DoG filter-bank with the aim of improving the reconstruction and thereby extracting more information from the rank-order encoded stimulus. We observe that there is an increase of 10 - 15% in the information retrieved from a reconstructed stimulus as a result of inverting the filter-bank.

A Ranking Method for Evaluating Constructed Responses

Science.gov (United States)

Attali, Yigal

2014-01-01

This article presents a comparative judgment approach for holistically scored constructed response tasks. In this approach, the grader rank orders (rather than rate) the quality of a small set of responses. A prior automated evaluation of responses guides both set formation and scaling of rankings. Sets are formed to have similar prior scores and…

Enhancing the Ranking of a Web Page in the Ocean of Data

Directory of Open Access Journals (Sweden)

Hitesh KUMAR SHARMA

2013-10-01

Full Text Available In today's world, web is considered as ocean of data and information (like text, videos, multimedia etc. consisting of millions and millions of web pages in which web pages are linked with each other like a tree. It is often argued that, especially considering the dynamic of the internet, too much time has passed since the scientific work on PageRank, as that it still could be the basis for the ranking methods of the Google search engine. There is no doubt that within the past years most likely many changes, adjustments and modifications regarding the ranking methods of Google have taken place, but PageRank was absolutely crucial for Google's success, so that at least the fundamental concept behind PageRank should still be constitutive. This paper describes the components which affects the ranking of the web pages and helps in increasing the popularity of web site. By adapting these factors website developers can increase their site's page rank and within the PageRank concept, considering the rank of a document is given by the rank of those documents which link to it. Their rank again is given by the rank of documents which link to them. The PageRank of a document is always determined recursively by the PageRank of other documents.

Ranking beta sheet topologies of proteins

DEFF Research Database (Denmark)

Fonseca, Rasmus; Helles, Glennie; Winter, Pawel

2010-01-01

One of the challenges of protein structure prediction is to identify long-range interactions between amino acids. To reliably predict such interactions, we enumerate, score and rank all beta-topologies (partitions of beta-strands into sheets, orderings of strands within sheets and orientations...... of paired strands) of a given protein. We show that the beta-topology corresponding to the native structure is, with high probability, among the top-ranked. Since full enumeration is very time-consuming, we also suggest a method to deal with proteins with many beta-strands. The results reported...... in this paper are highly relevant for ab initio protein structure prediction methods based on decoy generation. The top-ranked beta-topologies can be used to find initial conformations from which conformational searches can be started. They can also be used to filter decoys by removing those with poorly...

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)

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.

Reduced rank adaptive filtering in impulsive noise environments

KAUST Repository

Soury, Hamza

2014-11-01

An impulsive noise environment is considered in this paper. A new aspect of signal truncation is deployed to reduce the harmful effect of the impulsive noise to the signal. A full rank direct solution is derived followed by an iterative solution. The reduced rank adaptive filter is presented in this environment by using two methods for rank reduction, while the minimized objective function is defined using the Lp norm. The results are presented and the efficiency of each method is discussed. © 2014 IEEE.

An epidermal equivalent assay for identification and ranking potency of contact sensitizers

Energy Technology Data Exchange (ETDEWEB)

Gibbs, Susan, E-mail: S.Gibbs@VUMC.nl [Department of Dermatology, VU University Medical Centre, Dept of Oral Cell Biology, ACTA, Amsterdam (Netherlands); Corsini, Emanuela [Laboratory of Toxicology, DiSFeB, Università degli Studi di Milano (Italy); Spiekstra, Sander W. [Department of Dermatology, VU University Medical Centre, Dept of Oral Cell Biology, ACTA, Amsterdam (Netherlands); Galbiati, Valentina [Laboratory of Toxicology, DiSFeB, Università degli Studi di Milano (Italy); Fuchs, Horst W. [CellSystems GmbH, Troisdorf (Germany); DeGeorge, George; Troese, Matthew [MB Research Labs, Spinnerstown, PA (United States); Hayden, Patrick; Deng, Wei [MatTek Corporation, Ashland, MA (United States); Roggen, Erwin [3Rs Management and Consultancy (Denmark)

2013-10-15

The purpose of this study was to explore the possibility of combining the epidermal equivalent (EE) potency assay with the assay which assesses release of interleukin-18 (IL-18) to provide a single test for identification and classification of skin sensitizing chemicals, including chemicals of low water solubility or stability. A protocol was developed using different 3D-epidermal models including in house VUMC model, epiCS® (previously EST1000™), MatTek EpiDerm™ and SkinEthic™ RHE and also the impact of different vehicles (acetone:olive oil 4:1, 1% DMSO, ethanol, water) was investigated. Following topical exposure for 24 h to 17 contact allergens and 13 non-sensitizers a robust increase in IL-18 release was observed only after exposure to contact allergens. A putative prediction model is proposed from data obtained from two laboratories yielding 95% accuracy. Correlating the in vitro EE sensitizer potency data, which assesses the chemical concentration which results in 50% cytotoxicity (EE-EC{sub 50}) with human and animal data showed a superior correlation with human DSA{sub 05} (μg/cm{sup 2}) data (Spearman r = 0.8500; P value (two-tailed) = 0.0061) compared to LLNA data (Spearman r = 0.5968; P value (two-tailed) = 0.0542). DSA{sub 05} = induction dose per skin area that produces a positive response in 5% of the tested population Also a good correlation was observed for release of IL-18 (SI-2) into culture supernatants with human DSA{sub 05} data (Spearman r = 0.8333; P value (two-tailed) = 0.0154). This easily transferable human in vitro assay appears to be very promising, but additional testing of a larger chemical set with the different EE models is required to fully evaluate the utility of this assay and to establish a definitive prediction model. - Highlights: • A potential epidermal equivalent assay to label and classify sensitizers • Il-18 release distinguishes sensitizers from non sensitizers • IL-18 release can rank sensitizer potency �

An epidermal equivalent assay for identification and ranking potency of contact sensitizers

International Nuclear Information System (INIS)

Gibbs, Susan; Corsini, Emanuela; Spiekstra, Sander W.; Galbiati, Valentina; Fuchs, Horst W.; DeGeorge, George; Troese, Matthew; Hayden, Patrick; Deng, Wei; Roggen, Erwin

2013-01-01

The purpose of this study was to explore the possibility of combining the epidermal equivalent (EE) potency assay with the assay which assesses release of interleukin-18 (IL-18) to provide a single test for identification and classification of skin sensitizing chemicals, including chemicals of low water solubility or stability. A protocol was developed using different 3D-epidermal models including in house VUMC model, epiCS® (previously EST1000™), MatTek EpiDerm™ and SkinEthic™ RHE and also the impact of different vehicles (acetone:olive oil 4:1, 1% DMSO, ethanol, water) was investigated. Following topical exposure for 24 h to 17 contact allergens and 13 non-sensitizers a robust increase in IL-18 release was observed only after exposure to contact allergens. A putative prediction model is proposed from data obtained from two laboratories yielding 95% accuracy. Correlating the in vitro EE sensitizer potency data, which assesses the chemical concentration which results in 50% cytotoxicity (EE-EC 50 ) with human and animal data showed a superior correlation with human DSA 05 (μg/cm 2 ) data (Spearman r = 0.8500; P value (two-tailed) = 0.0061) compared to LLNA data (Spearman r = 0.5968; P value (two-tailed) = 0.0542). DSA 05 = induction dose per skin area that produces a positive response in 5% of the tested population Also a good correlation was observed for release of IL-18 (SI-2) into culture supernatants with human DSA 05 data (Spearman r = 0.8333; P value (two-tailed) = 0.0154). This easily transferable human in vitro assay appears to be very promising, but additional testing of a larger chemical set with the different EE models is required to fully evaluate the utility of this assay and to establish a definitive prediction model. - Highlights: • A potential epidermal equivalent assay to label and classify sensitizers • Il-18 release distinguishes sensitizers from non sensitizers • IL-18 release can rank sensitizer potency • EC50 (chemical

Highlighting Entanglement of Cultures via Ranking of Multilingual Wikipedia Articles

Science.gov (United States)

Eom, Young-Ho; Shepelyansky, Dima L.

2013-01-01

How different cultures evaluate a person? Is an important person in one culture is also important in the other culture? We address these questions via ranking of multilingual Wikipedia articles. With three ranking algorithms based on network structure of Wikipedia, we assign ranking to all articles in 9 multilingual editions of Wikipedia and investigate general ranking structure of PageRank, CheiRank and 2DRank. In particular, we focus on articles related to persons, identify top 30 persons for each rank among different editions and analyze distinctions of their distributions over activity fields such as politics, art, science, religion, sport for each edition. We find that local heroes are dominant but also global heroes exist and create an effective network representing entanglement of cultures. The Google matrix analysis of network of cultures shows signs of the Zipf law distribution. This approach allows to examine diversity and shared characteristics of knowledge organization between cultures. The developed computational, data driven approach highlights cultural interconnections in a new perspective. Dated: June 26, 2013 PMID:24098338

Highlighting entanglement of cultures via ranking of multilingual Wikipedia articles.

Directory of Open Access Journals (Sweden)

Young-Ho Eom

Full Text Available How different cultures evaluate a person? Is an important person in one culture is also important in the other culture? We address these questions via ranking of multilingual Wikipedia articles. With three ranking algorithms based on network structure of Wikipedia, we assign ranking to all articles in 9 multilingual editions of Wikipedia and investigate general ranking structure of PageRank, CheiRank and 2DRank. In particular, we focus on articles related to persons, identify top 30 persons for each rank among different editions and analyze distinctions of their distributions over activity fields such as politics, art, science, religion, sport for each edition. We find that local heroes are dominant but also global heroes exist and create an effective network representing entanglement of cultures. The Google matrix analysis of network of cultures shows signs of the Zipf law distribution. This approach allows to examine diversity and shared characteristics of knowledge organization between cultures. The developed computational, data driven approach highlights cultural interconnections in a new perspective. Dated: June 26, 2013.

Correlation between model observer and human observer performance in CT imaging when lesion location is uncertain

Energy Technology Data Exchange (ETDEWEB)

Leng, Shuai; Yu, Lifeng; Zhang, Yi; McCollough, Cynthia H. [Department of Radiology, Mayo Clinic, 200 First Street Southwest, Rochester, Minnesota 55905 (United States); Carter, Rickey [Department of Biostatistics, Mayo Clinic, 200 First Street Southwest, Rochester, Minnesota 55905 (United States); Toledano, Alicia Y. [Biostatistics Consulting, LLC, 10606 Wheatley Street, Kensington, Maryland 20895 (United States)

2013-08-15

Purpose: The purpose of this study was to investigate the correlation between model observer and human observer performance in CT imaging for the task of lesion detection and localization when the lesion location is uncertain.Methods: Two cylindrical rods (3-mm and 5-mm diameters) were placed in a 35 × 26 cm torso-shaped water phantom to simulate lesions with −15 HU contrast at 120 kV. The phantom was scanned 100 times on a 128-slice CT scanner at each of four dose levels (CTDIvol = 5.7, 11.4, 17.1, and 22.8 mGy). Regions of interest (ROIs) around each lesion were extracted to generate images with signal-present, with each ROI containing 128 × 128 pixels. Corresponding ROIs of signal-absent images were generated from images without lesion mimicking rods. The location of the lesion (rod) in each ROI was randomly distributed by moving the ROIs around each lesion. Human observer studies were performed by having three trained observers identify the presence or absence of lesions, indicating the lesion location in each image and scoring confidence for the detection task on a 6-point scale. The same image data were analyzed using a channelized Hotelling model observer (CHO) with Gabor channels. Internal noise was added to the decision variables for the model observer study. Area under the curve (AUC) of ROC and localization ROC (LROC) curves were calculated using a nonparametric approach. The Spearman's rank order correlation between the average performance of the human observers and the model observer performance was calculated for the AUC of both ROC and LROC curves for both the 3- and 5-mm diameter lesions.Results: In both ROC and LROC analyses, AUC values for the model observer agreed well with the average values across the three human observers. The Spearman's rank order correlation values for both ROC and LROC analyses for both the 3- and 5-mm diameter lesions were all 1.0, indicating perfect rank ordering agreement of the figures of merit (AUC

Correlates of health-related social media use among adults.

Science.gov (United States)

Thackeray, Rosemary; Crookston, Benjamin T; West, Joshua H

2013-01-30

Sixty percent of Internet users report using the Internet to look for health information. Social media sites are emerging as a potential source for online health information. However, little is known about how people use social media for such purposes. The purpose of this study was two-fold: (1) to establish the frequency of various types of online health-seeking behaviors, and (2) to identify correlates of 2 health-related online activities, social networking sites (SNS) for health-related activities and consulting online user-generated content for answers about health care providers, health facilities, or medical treatment. The study consisted of a telephone survey of 1745 adults who reported going online to look for health-related information. Four subscales were created to measure use of online resources for (1) using SNS for health-related activities; (2) consulting online rankings and reviews of doctors, hospitals or medical facilities, and drugs or medical treatments; (3) posting a review online of doctors, hospitals or medical facilities, and drugs or medical treatments, and (4) posting a comment or question about health or medical issues on various social media. Univariate and multivariate logistic regression analyses were performed. Respondents consulted online rankings or reviews (41.15%), used SNS for health (31.58%), posted reviews (9.9%1), and posted a comment, question, or information (15.19%). Respondents with a chronic disease were nearly twice as likely to consult online rankings (odds ratio [OR] 2.09, 95% CI 1.66-2.63, Psocial media for seeking health information. However, individuals are more likely to consume information than they are to contribute to the dialog. The inherent value of "social" in social media is not being captured with online health information seeking. People with a regular health care provider, chronic disease, and those in younger age groups are more likely to consult online rankings and reviews and use SNS for health

Podium: Ranking Data Using Mixed-Initiative Visual Analytics.

Science.gov (United States)

Wall, Emily; Das, Subhajit; Chawla, Ravish; Kalidindi, Bharath; Brown, Eli T; Endert, Alex

2018-01-01

People often rank and order data points as a vital part of making decisions. Multi-attribute ranking systems are a common tool used to make these data-driven decisions. Such systems often take the form of a table-based visualization in which users assign weights to the attributes representing the quantifiable importance of each attribute to a decision, which the system then uses to compute a ranking of the data. However, these systems assume that users are able to quantify their conceptual understanding of how important particular attributes are to a decision. This is not always easy or even possible for users to do. Rather, people often have a more holistic understanding of the data. They form opinions that data point A is better than data point B but do not necessarily know which attributes are important. To address these challenges, we present a visual analytic application to help people rank multi-variate data points. We developed a prototype system, Podium, that allows users to drag rows in the table to rank order data points based on their perception of the relative value of the data. Podium then infers a weighting model using Ranking SVM that satisfies the user's data preferences as closely as possible. Whereas past systems help users understand the relationships between data points based on changes to attribute weights, our approach helps users to understand the attributes that might inform their understanding of the data. We present two usage scenarios to describe some of the potential uses of our proposed technique: (1) understanding which attributes contribute to a user's subjective preferences for data, and (2) deconstructing attributes of importance for existing rankings. Our proposed approach makes powerful machine learning techniques more usable to those who may not have expertise in these areas.

A multivariate rank test for comparing mass size distributions

KAUST Repository

Lombard, F.

2012-04-01

Particle size analyses of a raw material are commonplace in the mineral processing industry. Knowledge of particle size distributions is crucial in planning milling operations to enable an optimum degree of liberation of valuable mineral phases, to minimize plant losses due to an excess of oversize or undersize material or to attain a size distribution that fits a contractual specification. The problem addressed in the present paper is how to test the equality of two or more underlying size distributions. A distinguishing feature of these size distributions is that they are not based on counts of individual particles. Rather, they are mass size distributions giving the fractions of the total mass of a sampled material lying in each of a number of size intervals. As such, the data are compositional in nature, using the terminology of Aitchison [1] that is, multivariate vectors the components of which add to 100%. In the literature, various versions of Hotelling\\'s T 2 have been used to compare matched pairs of such compositional data. In this paper, we propose a robust test procedure based on ranks as a competitor to Hotelling\\'s T 2. In contrast to the latter statistic, the power of the rank test is not unduly affected by the presence of outliers or of zeros among the data. © 2012 Copyright Taylor and Francis Group, LLC.

Block models and personalized PageRank

OpenAIRE

Kloumann, Isabel M.; Ugander, Johan; Kleinberg, Jon

2016-01-01

Methods for ranking the importance of nodes in a network have a rich history in machine learning and across domains that analyze structured data. Recent work has evaluated these methods though the seed set expansion problem: given a subset $S$ of nodes from a community of interest in an underlying graph, can we reliably identify the rest of the community? We start from the observation that the most widely used techniques for this problem, personalized PageRank and heat kernel methods, operate...

A model-based approach to operational event groups ranking

Energy Technology Data Exchange (ETDEWEB)

Simic, Zdenko [European Commission Joint Research Centre, Petten (Netherlands). Inst. for Energy and Transport; Maqua, Michael [Gesellschaft fuer Anlagen- und Reaktorsicherheit mbH (GRS), Koeln (Germany); Wattrelos, Didier [Institut de Radioprotection et de Surete Nucleaire (IRSN), Fontenay-aux-Roses (France)

2014-04-15

The operational experience (OE) feedback provides improvements in all industrial activities. Identification of the most important and valuable groups of events within accumulated experience is important in order to focus on a detailed investigation of events. The paper describes the new ranking method and compares it with three others. Methods have been described and applied to OE events utilised by nuclear power plants in France and Germany for twenty years. The results show that different ranking methods only roughly agree on which of the event groups are the most important ones. In the new ranking method the analytical hierarchy process is applied in order to assure consistent and comprehensive weighting determination for ranking indexes. The proposed method allows a transparent and flexible event groups ranking and identification of the most important OE for further more detailed investigation in order to complete the feedback. (orig.)

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.

Ranking benchmarks of top 100 players in men's professional tennis.

Science.gov (United States)

Reid, Machar; Morris, Craig

2013-01-01

In men's professional tennis, players aspire to hold the top ranking position. On the way to the top spot, reaching the top 100 can be seen as a significant career milestone. National Federations undertake extensive efforts to assist their players to reach the top 100. However, objective data considering reasonable ranking yardsticks for top 100 success in men's professional tennis are lacking. Therefore, it is difficult for National Federations and those involved in player development to give empirical programming advice to young players. By taking a closer look at the ranking history of professional male tennis players, this article tries to provide those involved in player development a more objective basis for decision-making. The 100 names, countries, birthdates and ranking histories of the top 100 players listed in the Association of Tennis Professionals (ATP) at 31 December 2009 were recorded from websites in the public domain. Descriptive statistics were reported for the ranking milestones of interest. Results confirmed the merits of the International Tennis Federation's junior tour with 91% of the top 100 professionals earning a junior ranking, the mean peak of which was 94.1, s=148.9. On average, top 100 professionals achieved their best junior rankings and earned their first ATP point at similar ages, suggesting that players compete on both the junior and professional tours during their transition. Once professionally ranked, players took an average 4.5, s=2.1 years to reach the ATP top 100 at the mean age of 21.5, s=2.6 years, which contrasts with the mean current age of the top 100 of 26.8, s=3.2. The best professional rankings of players born in 1982 or earlier were positively related to the ages at which players earned their first ATP point and then entered the top 100, suggesting that the ages associated with these ranking milestones may have some forecasting potential. Future work should focus on the change in top 100 demographics over time as well

Social Rank, Stress, Fitness, and Life Expectancy in Wild Rabbits

Science.gov (United States)

von Holst, Dietrich; Hutzelmeyer, Hans; Kaetzke, Paul; Khaschei, Martin; Schönheiter, Ronald

Wild rabbits of the two sexes have separate linear rank orders, which are established and maintained by intensive fights. The social rank of individuals strongly influence their fitness: males and females that gain a high social rank, at least at the outset of their second breeding season, have a much higher lifetime fitness than subordinate individuals. This is because of two separate factors: a much higher fecundity and annual reproductive success and a 50% longer reproductive life span. These results are in contrast to the view in evolutionary biology that current reproduction can be increased only at the expense of future survival and/or fecundity. These concepts entail higher physiological costs in high-ranking mammals, which is not supported by our data: In wild rabbits the physiological costs of social positions are caused predominantly by differential psychosocial stress responses that are much lower in high-ranking than in low-ranking individuals.

Tensor completion and low-n-rank tensor recovery via convex optimization

International Nuclear Information System (INIS)

Gandy, Silvia; Yamada, Isao; Recht, Benjamin

2011-01-01

In this paper we consider sparsity on a tensor level, as given by the n-rank of a tensor. In an important sparse-vector approximation problem (compressed sensing) and the low-rank matrix recovery problem, using a convex relaxation technique proved to be a valuable solution strategy. Here, we will adapt these techniques to the tensor setting. We use the n-rank of a tensor as a sparsity measure and consider the low-n-rank tensor recovery problem, i.e. the problem of finding the tensor of the lowest n-rank that fulfills some linear constraints. We introduce a tractable convex relaxation of the n-rank and propose efficient algorithms to solve the low-n-rank tensor recovery problem numerically. The algorithms are based on the Douglas–Rachford splitting technique and its dual variant, the alternating direction method of multipliers

A Fast Algorithm for Generating Permutation Distribution of Ranks in ...

African Journals Online (AJOL)

... function of the distribution of the ranks. This further gives insight into the permutation distribution of a rank statistics. The algorithm is implemented with the aid of the computer algebra system Mathematica. Key words: Combinatorics, generating function, permutation distribution, rank statistics, partitions, computer algebra.

Variation in rank abundance replicate samples and impact of clustering

NARCIS (Netherlands)

Neuteboom, J.H.; Struik, P.C.

2005-01-01

Calculating a single-sample rank abundance curve by using the negative-binomial distribution provides a way to investigate the variability within rank abundance replicate samples and yields a measure of the degree of heterogeneity of the sampled community. The calculation of the single-sample rank

Predictive-property-ranked variable reduction in partial least squares modelling with final complexity adapted models: comparison of properties for ranking.

Science.gov (United States)

Andries, Jan P M; Vander Heyden, Yvan; Buydens, Lutgarde M C

2013-01-14

The calibration performance of partial least squares regression for one response (PLS1) can be improved by eliminating uninformative variables. Many variable-reduction methods are based on so-called predictor-variable properties or predictive properties, which are functions of various PLS-model parameters, and which may change during the steps of the variable-reduction process. Recently, a new predictive-property-ranked variable reduction method with final complexity adapted models, denoted as PPRVR-FCAM or simply FCAM, was introduced. It is a backward variable elimination method applied on the predictive-property-ranked variables. The variable number is first reduced, with constant PLS1 model complexity A, until A variables remain, followed by a further decrease in PLS complexity, allowing the final selection of small numbers of variables. In this study for three data sets the utility and effectiveness of six individual and nine combined predictor-variable properties are investigated, when used in the FCAM method. The individual properties include the absolute value of the PLS1 regression coefficient (REG), the significance of the PLS1 regression coefficient (SIG), the norm of the loading weight (NLW) vector, the variable importance in the projection (VIP), the selectivity ratio (SR), and the squared correlation coefficient of a predictor variable with the response y (COR). The selective and predictive performances of the models resulting from the use of these properties are statistically compared using the one-tailed Wilcoxon signed rank test. The results indicate that the models, resulting from variable reduction with the FCAM method, using individual or combined properties, have similar or better predictive abilities than the full spectrum models. After mean-centring of the data, REG and SIG, provide low numbers of informative variables, with a meaning relevant to the response, and lower than the other individual properties, while the predictive abilities are

Cointegration rank testing under conditional heteroskedasticity

DEFF Research Database (Denmark)

Cavaliere, Giuseppe; Rahbek, Anders Christian; Taylor, Robert M.

2010-01-01

We analyze the properties of the conventional Gaussian-based cointegrating rank tests of Johansen (1996, Likelihood-Based Inference in Cointegrated Vector Autoregressive Models) in the case where the vector of series under test is driven by globally stationary, conditionally heteroskedastic......, relative to tests based on the asymptotic critical values or the i.i.d. bootstrap, the wild bootstrap rank tests perform very well in small samples under a variety of conditionally heteroskedastic innovation processes. An empirical application to the term structure of interest rates is given....

VisualRank: applying PageRank to large-scale image search.

Science.gov (United States)

Jing, Yushi; Baluja, Shumeet

2008-11-01

Because of the relative ease in understanding and processing text, commercial image-search systems often rely on techniques that are largely indistinguishable from text-search. Recently, academic studies have demonstrated the effectiveness of employing image-based features to provide alternative or additional signals. However, it remains uncertain whether such techniques will generalize to a large number of popular web queries, and whether the potential improvement to search quality warrants the additional computational cost. In this work, we cast the image-ranking problem into the task of identifying "authority" nodes on an inferred visual similarity graph and propose VisualRank to analyze the visual link structures among images. The images found to be "authorities" are chosen as those that answer the image-queries well. To understand the performance of such an approach in a real system, we conducted a series of large-scale experiments based on the task of retrieving images for 2000 of the most popular products queries. Our experimental results show significant improvement, in terms of user satisfaction and relevancy, in comparison to the most recent Google Image Search results. Maintaining modest computational cost is vital to ensuring that this procedure can be used in practice; we describe the techniques required to make this system practical for large scale deployment in commercial search engines.

SRS: Site ranking system for hazardous chemical and radioactive waste

International Nuclear Information System (INIS)

Rechard, R.P.; Chu, M.S.Y.; Brown, S.L.

1988-05-01

This report describes the rationale and presents instructions for a site ranking system (SRS). SRS ranks hazardous chemical and radioactive waste sites by scoring important and readily available factors that influence risk to human health. Using SRS, sites can be ranked for purposes of detailed site investigations. SRS evaluates the relative risk as a combination of potentially exposed population, chemical toxicity, and potential exposure of release from a waste site; hence, SRS uses the same concepts found in a detailed assessment of health risk. Basing SRS on the concepts of risk assessment tends to reduce the distortion of results found in other ranking schemes. More importantly, a clear logic helps ensure the successful application of the ranking procedure and increases its versatility when modifications are necessary for unique situations. Although one can rank sites using a detailed risk assessment, it is potentially costly because of data and resources required. SRS is an efficient approach to provide an order-of-magnitude ranking, requiring only readily available data (often only descriptive) and hand calculations. Worksheets are included to make the system easier to understand and use. 88 refs., 19 figs., 58 tabs

ACORNS, Covariance and Correlation Matrix Diagonalization

International Nuclear Information System (INIS)

Szondi, E.J.

1990-01-01

1 - Description of program or function: The program allows the user to verify the different types of covariance/correlation matrices used in the activation neutron spectrometry. 2 - Method of solution: The program performs the diagonalization of the input covariance/relative covariance/correlation matrices. The Eigen values are then analyzed to determine the rank of the matrices. If the Eigen vectors of the pertinent correlation matrix have also been calculated, the program can perform a complete factor analysis (generation of the factor matrix and its rotation in Kaiser's 'varimax' sense to select the origin of the correlations). 3 - Restrictions on the complexity of the problem: Matrix size is limited to 60 on PDP and to 100 on IBM PC/AT

Cell adhesion signaling regulates RANK expression in osteoclast precursors.

Directory of Open Access Journals (Sweden)

Ayako Mochizuki

Full Text Available Cells with monocyte/macrophage lineage expressing receptor activator of NF-κB (RANK differentiate into osteoclasts following stimulation with the RANK ligand (RANKL. Cell adhesion signaling is also required for osteoclast differentiation from precursors. However, details of the mechanism by which cell adhesion signals induce osteoclast differentiation have not been fully elucidated. To investigate the participation of cell adhesion signaling in osteoclast differentiation, mouse bone marrow-derived macrophages (BMMs were used as osteoclast precursors, and cultured on either plastic cell culture dishes (adherent condition or the top surface of semisolid methylcellulose gel loaded in culture tubes (non-adherent condition. BMMs cultured under the adherent condition differentiated into osteoclasts in response to RANKL stimulation. However, under the non-adherent condition, the efficiency of osteoclast differentiation was markedly reduced even in the presence of RANKL. These BMMs retained macrophage characteristics including phagocytic function and gene expression profile. Lipopolysaccharide (LPS and tumor necrosis factor -αTNF-α activated the NF-κB-mediated signaling pathways under both the adherent and non-adherent conditions, while RANKL activated the pathways only under the adherent condition. BMMs highly expressed RANK mRNA and protein under the adherent condition as compared to the non-adherent condition. Also, BMMs transferred from the adherent to non-adherent condition showed downregulated RANK expression within 24 hours. In contrast, transferring those from the non-adherent to adherent condition significantly increased the level of RANK expression. Moreover, interruption of cell adhesion signaling by echistatin, an RGD-containing disintegrin, decreased RANK expression in BMMs, while forced expression of either RANK or TNFR-associated factor 6 (TRAF6 in BMMs induced their differentiation into osteoclasts even under the non

Discriminative Multi-View Interactive Image Re-Ranking.

Science.gov (United States)

Li, Jun; Xu, Chang; Yang, Wankou; Sun, Changyin; Tao, Dacheng

2017-07-01

Given an unreliable visual patterns and insufficient query information, content-based image retrieval is often suboptimal and requires image re-ranking using auxiliary information. In this paper, we propose a discriminative multi-view interactive image re-ranking (DMINTIR), which integrates user relevance feedback capturing users' intentions and multiple features that sufficiently describe the images. In DMINTIR, heterogeneous property features are incorporated in the multi-view learning scheme to exploit their complementarities. In addition, a discriminatively learned weight vector is obtained to reassign updated scores and target images for re-ranking. Compared with other multi-view learning techniques, our scheme not only generates a compact representation in the latent space from the redundant multi-view features but also maximally preserves the discriminative information in feature encoding by the large-margin principle. Furthermore, the generalization error bound of the proposed algorithm is theoretically analyzed and shown to be improved by the interactions between the latent space and discriminant function learning. Experimental results on two benchmark data sets demonstrate that our approach boosts baseline retrieval quality and is competitive with the other state-of-the-art re-ranking strategies.

Texture Repairing by Unified Low Rank Optimization

Institute of Scientific and Technical Information of China (English)

Xiao Liang; Xiang Ren; Zhengdong Zhang; Yi Ma

2016-01-01

In this paper, we show how to harness both low-rank and sparse structures in regular or near-regular textures for image completion. Our method is based on a unified formulation for both random and contiguous corruption. In addition to the low rank property of texture, the algorithm also uses the sparse assumption of the natural image: because the natural image is piecewise smooth, it is sparse in certain transformed domain (such as Fourier or wavelet transform). We combine low-rank and sparsity properties of the texture image together in the proposed algorithm. Our algorithm based on convex optimization can automatically and correctly repair the global structure of a corrupted texture, even without precise information about the regions to be completed. This algorithm integrates texture rectification and repairing into one optimization problem. Through extensive simulations, we show our method can complete and repair textures corrupted by errors with both random and contiguous supports better than existing low-rank matrix recovery methods. Our method demonstrates significant advantage over local patch based texture synthesis techniques in dealing with large corruption, non-uniform texture, and large perspective deformation.

A Ranking Approach on Large-Scale Graph With Multidimensional Heterogeneous Information.

Science.gov (United States)

Wei, Wei; Gao, Bin; Liu, Tie-Yan; Wang, Taifeng; Li, Guohui; Li, Hang

2016-04-01

Graph-based ranking has been extensively studied and frequently applied in many applications, such as webpage ranking. It aims at mining potentially valuable information from the raw graph-structured data. Recently, with the proliferation of rich heterogeneous information (e.g., node/edge features and prior knowledge) available in many real-world graphs, how to effectively and efficiently leverage all information to improve the ranking performance becomes a new challenging problem. Previous methods only utilize part of such information and attempt to rank graph nodes according to link-based methods, of which the ranking performances are severely affected by several well-known issues, e.g., over-fitting or high computational complexity, especially when the scale of graph is very large. In this paper, we address the large-scale graph-based ranking problem and focus on how to effectively exploit rich heterogeneous information of the graph to improve the ranking performance. Specifically, we propose an innovative and effective semi-supervised PageRank (SSP) approach to parameterize the derived information within a unified semi-supervised learning framework (SSLF-GR), then simultaneously optimize the parameters and the ranking scores of graph nodes. Experiments on the real-world large-scale graphs demonstrate that our method significantly outperforms the algorithms that consider such graph information only partially.