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 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.

Sparse subspace clustering for data with missing entries and high-rank matrix completion.

Science.gov (United States)

Fan, Jicong; Chow, Tommy W S

2017-09-01

Many methods have recently been proposed for subspace clustering, but they are often unable to handle incomplete data because of missing entries. Using matrix completion methods to recover missing entries is a common way to solve the problem. Conventional matrix completion methods require that the matrix should be of low-rank intrinsically, but most matrices are of high-rank or even full-rank in practice, especially when the number of subspaces is large. In this paper, a new method called Sparse Representation with Missing Entries and Matrix Completion is proposed to solve the problems of incomplete-data subspace clustering and high-rank matrix completion. The proposed algorithm alternately computes the matrix of sparse representation coefficients and recovers the missing entries of a data matrix. The proposed algorithm recovers missing entries through minimizing the representation coefficients, representation errors, and matrix rank. Thorough experimental study and comparative analysis based on synthetic data and natural images were conducted. The presented results demonstrate that the proposed algorithm is more effective in subspace clustering and matrix completion compared with other existing methods. Copyright © 2017 Elsevier Ltd. All rights reserved.

Hierarchical low-rank approximation for high dimensional approximation

KAUST Repository

Nouy, Anthony

2016-01-07

Tensor methods are among the most prominent tools for the numerical solution of high-dimensional problems where functions of multiple variables have to be approximated. Such high-dimensional approximation problems naturally arise in stochastic analysis and uncertainty quantification. In many practical situations, the approximation of high-dimensional functions is made computationally tractable by using rank-structured approximations. In this talk, we present algorithms for the approximation in hierarchical tensor format using statistical methods. Sparse representations in a given tensor format are obtained with adaptive or convex relaxation methods, with a selection of parameters using crossvalidation methods.

Hierarchical low-rank approximation for high dimensional approximation

KAUST Repository

Nouy, Anthony

2016-01-01

Tensor methods are among the most prominent tools for the numerical solution of high-dimensional problems where functions of multiple variables have to be approximated. Such high-dimensional approximation problems naturally arise in stochastic analysis and uncertainty quantification. In many practical situations, the approximation of high-dimensional functions is made computationally tractable by using rank-structured approximations. In this talk, we present algorithms for the approximation in hierarchical tensor format using statistical methods. Sparse representations in a given tensor format are obtained with adaptive or convex relaxation methods, with a selection of parameters using crossvalidation methods.

Face the hierarchy: ERP and oscillatory brain responses in social rank processing.

Science.gov (United States)

Breton, Audrey; Jerbi, Karim; Henaff, Marie-Anne; Cheylus, Anne; Baudouin, Jean-Yves; Schmitz, Christina; Krolak-Salmon, Pierre; Van der Henst, Jean-Baptiste

2014-01-01

Recognition of social hierarchy is a key feature that helps us navigate through our complex social environment. Neuroimaging studies have identified brain structures involved in the processing of hierarchical stimuli but the precise temporal dynamics of brain activity associated with such processing remains largely unknown. Here, we used electroencephalography to examine the effect of social hierarchy on neural responses elicited by faces. In contrast to previous studies, the key manipulation was that a hierarchical context was constructed, not by varying facial expressions, but by presenting neutral-expression faces in a game setting. Once the performance-based hierarchy was established, participants were presented with high-rank, middle-rank and low-rank player faces and had to evaluate the rank of each face with respect to their own position. Both event-related potentials and task-related oscillatory activity were investigated. Three main findings emerge from the study. First, the experimental manipulation had no effect on the early N170 component, which may suggest that hierarchy did not modulate the structural encoding of neutral-expression faces. Second, hierarchy significantly modulated the amplitude of the late positive potential (LPP) within a 400-700 ms time-window, with more a prominent LPP occurring when the participants processed the face of the highest-rank player. Third, high-rank faces were associated with the highest reduction of alpha power. Taken together these findings provide novel electrophysiological evidence for enhanced allocation of attentional resource in the presence of high-rank faces. At a broader level, this study brings new insights into the neural processing underlying social categorization.

The Influence of Gender, Age, Matriline and Hierarchical Rank on Individual Social Position, Role and Interactional Patterns in Macaca sylvanus at 'La Forêt des Singes': A Multilevel Social Network Approach.

Science.gov (United States)

Sosa, Sebastian

2016-01-01

A society is a complex system composed of individuals that can be characterized by their own attributes that influence their behaviors. In this study, a specific analytical protocol based on social network analysis was adopted to investigate the influence of four attributes (gender, age, matriline, and hierarchical rank) on affiliative (allogrooming) and agonistic networks in a non-human primate species, Macaca sylvanus, at the park La Forêt des Singes in France. The results show significant differences with respect to the position (i.e., centric, peripheral) and role (i.e., implication in the network cohesiveness) of an individual within a social network and hence interactional patterns. Females are more central, more active, and have a denser ego network in the affiliative social network tan males; thus, they contribute in a greater way to the cohesive structure of the network. High-ranking individuals are likely to receive fewer agonistic behaviors than low-ranking individuals, and high-ranking females receive more allogrooming. I also observe homophily for affiliative interactions regarding all attributes and homophily for agonistic interactions regarding gender and age. Revealing the positions, the roles, and the interactional behavioral patterns of individuals can help understand the mechanisms that shape the overall structure of a social network.

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/.

The influence of gender, age, matriline and hierarchical rank on individual social position, role and interactional patterns in Macaca sylvanus at ‘La Forêt des singes’: A multilevel social network approach

Directory of Open Access Journals (Sweden)

Sebastian OROZCO SOSA

2016-04-01

Full Text Available A society is a complex system composed of individuals that can be characterized by their own attributes that influence their behaviors. In this study, a specific analytical protocol based on social network analysis was adopted to investigate the influence of four attributes (gender, age, matriline, and hierarchical rank on affiliative (allogrooming and agonistic networks in a non-human primate species, Macaca sylvanus, at the park La Forêt des Singes in France. The results show significant differences with respect to the position (i.e. centric, peripheral and role (i.e. implication in the network cohesiveness of an individual within a social network and hence interactional patterns. Females are more central, more active, and have a denser ego network in the affiliative social network tan males; thus, they contribute in a greater way to the cohesive structure of the network. High-ranking individuals are likely to receive fewer agonistic behaviors than low-ranking individuals, and high-ranking females receive more allogrooming. I also observe homophily for affiliative interactions regarding all attributes and homophily for agonistic interactions regarding gender and age. Revealing the positions, the roles, and the interactional behavioral patterns of individuals can help understand the mechanisms that shape the overall structure of a social network.

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.

Classical impurities associated to high rank algebras

Energy Technology Data Exchange (ETDEWEB)

Doikou, Anastasia, E-mail: A.Doikou@hw.ac.uk [Department of Mathematics, Heriot–Watt University, EH14 4AS, Edinburgh (United Kingdom); Department of Computer Engineering and Informatics, University of Patras, Patras GR-26500 (Greece)

2014-07-15

Classical integrable impurities associated with high rank (gl{sub N}) algebras are investigated. A particular prototype, i.e. the vector non-linear Schrödinger (NLS) model, is chosen as an example. A systematic construction of local integrals of motion as well as the time components of the corresponding Lax pairs is presented based on the underlying classical algebra. Suitable gluing conditions compatible with integrability are also extracted. The defect contribution is also examined in the case where non-trivial integrable conditions are implemented. It turns out that the integrable boundaries may drastically alter the bulk behavior, and in particular the defect contribution.

Classical impurities associated to high rank algebras

International Nuclear Information System (INIS)

Doikou, Anastasia

2014-01-01

Classical integrable impurities associated with high rank (gl N ) algebras are investigated. A particular prototype, i.e. the vector non-linear Schrödinger (NLS) model, is chosen as an example. A systematic construction of local integrals of motion as well as the time components of the corresponding Lax pairs is presented based on the underlying classical algebra. Suitable gluing conditions compatible with integrability are also extracted. The defect contribution is also examined in the case where non-trivial integrable conditions are implemented. It turns out that the integrable boundaries may drastically alter the bulk behavior, and in particular the defect contribution

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.

Knockouts of high-ranking males have limited impact on baboon social networks.

Science.gov (United States)

Franz, Mathias; Altmann, Jeanne; Alberts, Susan C

Social network structures can crucially impact complex social processes such as collective behaviour or the transmission of information and diseases. However, currently it is poorly understood how social networks change over time. Previous studies on primates suggest that `knockouts' (due to death or dispersal) of high-ranking individuals might be important drivers for structural changes in animal social networks. Here we test this hypothesis using long-term data on a natural population of baboons, examining the effects of 29 natural knockouts of alpha or beta males on adult female social networks. We investigated whether and how knockouts affected (1) changes in grooming and association rates among adult females, and (2) changes in mean degree and global clustering coefficient in these networks. The only significant effect that we found was a decrease in mean degree in grooming networks in the first month after knockouts, but this decrease was rather small, and grooming networks rebounded to baseline levels by the second month after knockouts. Taken together our results indicate that the removal of high-ranking males has only limited or no lasting effects on social networks of adult female baboons. This finding calls into question the hypothesis that the removal of high-ranking individuals has a destabilizing effect on social network structures in social animals.

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 .

Ranking mutual funds using Sortino method

Directory of Open Access Journals (Sweden)

Khosro Faghani Makrani

2014-04-01

Full Text Available One of the primary concerns on most business activities is to determine an efficient method for ranking mutual funds. This paper performs an empirical investigation to rank 42 mutual funds listed on Tehran Stock Exchange using Sortino method over the period 2011-2012. The results of survey have been compared with market return and the results have confirmed that there were some positive and meaningful relationships between Sortino return and market return. In addition, there were some positive and meaningful relationship between two Sortino methods.

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

Ranking multiple docking solutions based on the conservation of inter-residue contacts

KAUST Repository

Oliva, Romina M.

2013-06-17

Molecular docking is the method of choice for investigating the molecular basis of recognition in a large number of functional protein complexes. However, correctly scoring the obtained docking solutions (decoys) to rank native-like (NL) conformations in the top positions is still an open problem. Herein we present CONSRANK, a simple and effective tool to rank multiple docking solutions, which relies on the conservation of inter-residue contacts in the analyzed decoys ensemble. First it calculates a conservation rate for each inter-residue contact, then it ranks decoys according to their ability to match the more frequently observed contacts. We applied CONSRANK to 102 targets from three different benchmarks, RosettaDock, DOCKGROUND, and Critical Assessment of PRedicted Interactions (CAPRI). The method performs consistently well, both in terms of NL solutions ranked in the top positions and of values of the area under the receiver operating characteristic curve. Its ideal application is to solutions coming from different docking programs and procedures, as in the case of CAPRI targets. For all the analyzed CAPRI targets where a comparison is feasible, CONSRANK outperforms the CAPRI scorers. The fraction of NL solutions in the top ten positions in the RosettaDock, DOCKGROUND, and CAPRI benchmarks is enriched on average by a factor of 3.0, 1.9, and 9.9, respectively. Interestingly, CONSRANK is also able to specifically single out the high/medium quality (HMQ) solutions from the docking decoys ensemble: it ranks 46.2 and 70.8% of the total HMQ solutions available for the RosettaDock and CAPRI targets, respectively, within the top 20 positions. © 2013 Wiley Periodicals, Inc.

Approximation of High-Dimensional Rank One Tensors

KAUST Repository

Bachmayr, Markus

2013-11-12

Many real world problems are high-dimensional in that their solution is a function which depends on many variables or parameters. This presents a computational challenge since traditional numerical techniques are built on model classes for functions based solely on smoothness. It is known that the approximation of smoothness classes of functions suffers from the so-called \\'curse of dimensionality\\'. Avoiding this curse requires new model classes for real world functions that match applications. This has led to the introduction of notions such as sparsity, variable reduction, and reduced modeling. One theme that is particularly common is to assume a tensor structure for the target function. This paper investigates how well a rank one function f(x 1,...,x d)=f 1(x 1)⋯f d(x d), defined on Ω=[0,1]d can be captured through point queries. It is shown that such a rank one function with component functions f j in W∞ r([0,1]) can be captured (in L ∞) to accuracy O(C(d,r)N -r) from N well-chosen point evaluations. The constant C(d,r) scales like d dr. The queries in our algorithms have two ingredients, a set of points built on the results from discrepancy theory and a second adaptive set of queries dependent on the information drawn from the first set. Under the assumption that a point z∈Ω with nonvanishing f(z) is known, the accuracy improves to O(dN -r). © 2013 Springer Science+Business Media New York.

Approximation of High-Dimensional Rank One Tensors

KAUST Repository

Bachmayr, Markus; Dahmen, Wolfgang; DeVore, Ronald; Grasedyck, Lars

2013-01-01

Many real world problems are high-dimensional in that their solution is a function which depends on many variables or parameters. This presents a computational challenge since traditional numerical techniques are built on model classes for functions based solely on smoothness. It is known that the approximation of smoothness classes of functions suffers from the so-called 'curse of dimensionality'. Avoiding this curse requires new model classes for real world functions that match applications. This has led to the introduction of notions such as sparsity, variable reduction, and reduced modeling. One theme that is particularly common is to assume a tensor structure for the target function. This paper investigates how well a rank one function f(x 1,...,x d)=f 1(x 1)⋯f d(x d), defined on Ω=[0,1]d can be captured through point queries. It is shown that such a rank one function with component functions f j in W∞ r([0,1]) can be captured (in L ∞) to accuracy O(C(d,r)N -r) from N well-chosen point evaluations. The constant C(d,r) scales like d dr. The queries in our algorithms have two ingredients, a set of points built on the results from discrepancy theory and a second adaptive set of queries dependent on the information drawn from the first set. Under the assumption that a point z∈Ω with nonvanishing f(z) is known, the accuracy improves to O(dN -r). © 2013 Springer Science+Business Media New York.

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...

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

Science.gov (United States)

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

2017-05-12

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

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

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.

Detection of Crossing White Matter Fibers with High-Order Tensors and Rank-k Decompositions

KAUST Repository

Jiao, Fangxiang; Gur, Yaniv; Johnson, Chris R.; Joshi, Sarang

2011-01-01

Fundamental to high angular resolution diffusion imaging (HARDI), is the estimation of a positive-semidefinite orientation distribution function (ODF) and extracting the diffusion properties (e.g., fiber directions). In this work we show that these two goals can be achieved efficiently by using homogeneous polynomials to represent the ODF in the spherical deconvolution approach, as was proposed in the Cartesian Tensor-ODF (CT-ODF) formulation. Based on this formulation we first suggest an estimation method for positive-semidefinite ODF by solving a linear programming problem that does not require special parameterization of the ODF. We also propose a rank-k tensor decomposition, known as CP decomposition, to extract the fibers information from the estimated ODF. We show that this decomposition is superior to the fiber direction estimation via ODF maxima detection as it enables one to reach the full fiber separation resolution of the estimation technique. We assess the accuracy of this new framework by applying it to synthetic and experimentally obtained HARDI data. © 2011 Springer-Verlag.

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

Directory of Open Access Journals (Sweden)

Zirui Huang

2017-01-01

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

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

Global Rankings in the Nordic Region: Challenging the Identity of Research-Intensive Universities?

Science.gov (United States)

Elken, Mari; Hovdhaugen, Elisabeth; Stensaker, Bjørn

2016-01-01

Global university rankings currently attract considerable attention, and it is often assumed that such rankings may cause universities to prioritize activities and outcomes that will have a positive effect in their ranking position. A possible consequence of this could be the spread of a particular model of an "ideal" university. This…

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.

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

Authors and editors assort on gender and geography in high-rank ecological publications.

Directory of Open Access Journals (Sweden)

Kezia R Manlove

Full Text Available Peer-reviewed publication volume and caliber are widely-recognized proxies for academic merit, and a strong publication record is essential for academic success and advancement. However, recent work suggests that publication productivity for particular author groups may also be determined in part by implicit biases lurking in the publication pipeline. Here, we explore patterns of gender, geography, and institutional rank among authors, editorial board members, and handling editors in high-impact ecological publications during 2015 and 2016. A higher proportion of lead authors had female first names (33.9% than editorial board members (28.9%, and the proportion of female first names among handling editors was even lower (21.1%. Female editors disproportionately edited publications with female lead authors (40.3% of publications with female lead authors were handled by female editors, though female editors handled only 34.4% of all studied publications. Additionally, ecological authors and editors were overwhelmingly from countries in the G8, and high-ranking academic institutions accounted for a large portion of both the published work, and its editorship. Editors and lead authors with female names were typically affiliated with higher-ranking institutions than their male peers. This description of author and editor features provides a baseline for benchmarking future trends in the ecological publishing culture.

Authors and editors assort on gender and geography in high-rank ecological publications.

Science.gov (United States)

Manlove, Kezia R; Belou, Rebecca M

2018-01-01

Peer-reviewed publication volume and caliber are widely-recognized proxies for academic merit, and a strong publication record is essential for academic success and advancement. However, recent work suggests that publication productivity for particular author groups may also be determined in part by implicit biases lurking in the publication pipeline. Here, we explore patterns of gender, geography, and institutional rank among authors, editorial board members, and handling editors in high-impact ecological publications during 2015 and 2016. A higher proportion of lead authors had female first names (33.9%) than editorial board members (28.9%), and the proportion of female first names among handling editors was even lower (21.1%). Female editors disproportionately edited publications with female lead authors (40.3% of publications with female lead authors were handled by female editors, though female editors handled only 34.4% of all studied publications). Additionally, ecological authors and editors were overwhelmingly from countries in the G8, and high-ranking academic institutions accounted for a large portion of both the published work, and its editorship. Editors and lead authors with female names were typically affiliated with higher-ranking institutions than their male peers. This description of author and editor features provides a baseline for benchmarking future trends in the ecological publishing culture.

The Logistics Potential of Ukraine in the International Ranking

Directory of Open Access Journals (Sweden)

Kuchkova Olga V.

2017-01-01

Full Text Available The article is aimed at studying the ranking of countries by the LPI index, identifying causes of the low positioning of Ukraine and ways to restructure its logistics system. It has been proved that, by the level of development of the logistics industry, Ukraine’s position in the world standings every year worsens. Over the past four years the country has lost 19 positions and in 2016 has moved into the 80 place among the 160 countries. On the basis of analysis of the components of LPI was determined that the worst indicator among all evaluated characteristics Ukraine had demonstrated as to customs handling of cargo (116th place, the best – as to timeliness of delivery of goods to destinations (54th place, relatively well – as to logistics coverage and cargo tracking – 61st place. In order to restructure the logistics system of Ukraine and improve its position in the world ranking the priorities are: intensification of developing innovative technology; further integration into the world community, studying and introduction of international experience; construction of logistics centers and developing infrastructure throughout the country; education of highly qualified personnel through the development of institutions of higher education and business programs of advanced training.

Highly accelerated cardiac cine parallel MRI using low-rank matrix completion and partial separability model

Science.gov (United States)

Lyu, Jingyuan; Nakarmi, Ukash; Zhang, Chaoyi; Ying, Leslie

2016-05-01

This paper presents a new approach to highly accelerated dynamic parallel MRI using low rank matrix completion, partial separability (PS) model. In data acquisition, k-space data is moderately randomly undersampled at the center kspace navigator locations, but highly undersampled at the outer k-space for each temporal frame. In reconstruction, the navigator data is reconstructed from undersampled data using structured low-rank matrix completion. After all the unacquired navigator data is estimated, the partial separable model is used to obtain partial k-t data. Then the parallel imaging method is used to acquire the entire dynamic image series from highly undersampled data. The proposed method has shown to achieve high quality reconstructions with reduction factors up to 31, and temporal resolution of 29ms, when the conventional PS method fails.

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.

PageRank and rank-reversal dependence on the damping factor

Science.gov (United States)

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

2012-12-01

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

PageRank and rank-reversal dependence on the damping factor.

Science.gov (United States)

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

2012-12-01

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

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)

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.

Occupational stress and cardiovascular risk factors in high-ranking government officials and office workers.

Science.gov (United States)

Mirmohammadi, Seyyed Jalil; Taheri, Mahmoud; Mehrparvar, Amir Houshang; Heydari, Mohammad; Saadati Kanafi, Ali; Mostaghaci, Mehrdad

2014-08-01

Cardiovascular diseases are among the most important sources of mortality and morbidity, and have a high disease burden. There are some major well-known risk factors, which contribute to the development of these diseases. Occupational stress is caused due to imbalance between job demands and individual's ability, and it has been implicated as an etiology for cardiovascular diseases. This study was conducted to evaluate the cardiovascular risk factors and different dimensions of occupational stress in high-ranking government officials, comparing an age and sex-matched group of office workers with them. We invited 90 high-ranking officials who managed the main governmental offices in a city, and 90 age and sex-matched office workers. The subjects were required to fill the occupational role questionnaire (Osipow) which evaluated their personal and medical history as well as occupational stress. Then, we performed physical examination and laboratory tests to check for cardiovascular risk factors. Finally, the frequency of cardiovascular risk factors and occupational stress of two groups were compared. High-ranking officials in our study had less work experience in their current jobs and smoked fewer pack-years of cigarette, but they had higher waist and hip circumference, higher triglyceride level, more stress from role overload and responsibility, and higher total stress score. Our group of office workers had more occupational stress because of role ambiguity and insufficiency, but their overall job stress was less than officials. The officials have higher scores in some dimensions of occupational stress and higher overall stress score. Some cardiovascular risk factors were also more frequent in managers.

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

Science.gov (United States)

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

2014-04-01

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

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.

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

Directory of Open Access Journals (Sweden)

Jingya Yang

2012-01-01

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

Acclimation to high CO2 in maize is related to water status and dependent on leaf rank.

Science.gov (United States)

Prins, Anneke; Mukubi, Josephine Muchwesi; Pellny, Till K; Verrier, Paul J; Beyene, Getu; Lopes, Marta Silva; Emami, Kaveh; Treumann, Achim; Lelarge-Trouverie, Caroline; Noctor, Graham; Kunert, Karl J; Kerchev, Pavel; Foyer, Christine H

2011-02-01

The responses of C(3) plants to rising atmospheric CO(2) levels are considered to be largely dependent on effects exerted through altered photosynthesis. In contrast, the nature of the responses of C(4) plants to high CO(2) remains controversial because of the absence of CO(2) -dependent effects on photosynthesis. In this study, the effects of atmospheric CO(2) availability on the transcriptome, proteome and metabolome profiles of two ranks of source leaves in maize (Zea mays L.) were studied in plants grown under ambient CO(2) conditions (350 +/- 20 µL L(-1) CO(2) ) or with CO(2) enrichment (700 +/- 20 µL L(-1) CO(2) ). Growth at high CO(2) had no effect on photosynthesis, photorespiration, leaf C/N ratios or anthocyanin contents. However, leaf transpiration rates, carbohydrate metabolism and protein carbonyl accumulation were altered at high CO(2) in a leaf-rank specific manner. Although no significant CO(2) -dependent changes in the leaf transcriptome were observed, qPCR analysis revealed that the abundance of transcripts encoding a Bowman-Birk protease inhibitor and a serpin were changed by the growth CO(2) level in a leaf rank specific manner. Moreover, CO(2) -dependent changes in the leaf proteome were most evident in the oldest source leaves. Small changes in water status may be responsible for the observed responses to high CO(2,) particularly in the older leaf ranks. © 2010 Blackwell Publishing Ltd.

An improved rank based disease prediction using web navigation patterns on bio-medical databases

Directory of Open Access Journals (Sweden)

P. Dhanalakshmi

2017-12-01

Full Text Available Applying machine learning techniques to on-line biomedical databases is a challenging task, as this data is collected from large number of sources and it is multi-dimensional. Also retrieval of relevant document from large repository such as gene document takes more processing time and an increased false positive rate. Generally, the extraction of biomedical document is based on the stream of prior observations of gene parameters taken at different time periods. Traditional web usage models such as Markov, Bayesian and Clustering models are sensitive to analyze the user navigation patterns and session identification in online biomedical database. Moreover, most of the document ranking models on biomedical database are sensitive to sparsity and outliers. In this paper, a novel user recommendation system was implemented to predict the top ranked biomedical documents using the disease type, gene entities and user navigation patterns. In this recommendation system, dynamic session identification, dynamic user identification and document ranking techniques were used to extract the highly relevant disease documents on the online PubMed repository. To verify the performance of the proposed model, the true positive rate and runtime of the model was compared with that of traditional static models such as Bayesian and Fuzzy rank. Experimental results show that the performance of the proposed ranking model is better than the traditional models.

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.

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...

Ranking Spain's medical schools by their performance in the national residency examination.

Science.gov (United States)

Lopez-Valcarcel, B G; Ortún, V; Barber, P; Harris, J E; García, B

2013-12-01

Medical school graduates in Spain must take a uniform national exam (called "examen MIR") in order to enter postgraduate training in a specialty. Its results offer a unique opportunity to rank medical schools according to this exam. We measured differences in the MIR exam results among Spanish medical schools and assessed the stability of the MIR-based rankings for the period 2003-2011. In the year 2011 a total of 6873 residency positions nationwide were offered by the Spanish Ministry of Health, Social Services and Equality. These positions covered 47 specialties distributed over 231 training centers. A total of 11,550 medical graduates (including 1997 foreign graduates) took the MIR examination. Marked differences among medical schools were evident. The median graduate from medical school #1 and #29 occupied the positions 1477 and 5383, respectively. These figures correspond to a standardized ranking of 21 out of 100 for medical school #1 (that is, 1477/6873; half of medical school #1 obtained better [below position 21%] and half worse [over position 21%] results) and a standardized ranking of 70 out of 100 for medical school #29. While 81% of the medical school #1 graduates were amongst the best 3000 MIR exams and only 5% above the 5000 position the corresponding figures for medical school #29 graduates were 21% and 44%, respectively. The ranking position of the 29 medical schools was very stable between the years 2003 and 2011. There are marked differences in medical schools in Spain and these differences are very consistent over the years 2003-2011. Copyright © 2013 Elsevier España, S.L. All rights reserved.

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 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

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.

Reduced Rank Regression

DEFF Research Database (Denmark)

Johansen, Søren

2008-01-01

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

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.

RankProdIt: A web-interactive Rank Products analysis tool

Directory of Open Access Journals (Sweden)

Laing Emma

2010-08-01

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

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.

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

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.

Validation of SmartRank: A likelihood ratio software for searching national DNA databases with complex DNA profiles.

Science.gov (United States)

Benschop, Corina C G; van de Merwe, Linda; de Jong, Jeroen; Vanvooren, Vanessa; Kempenaers, Morgane; Kees van der Beek, C P; Barni, Filippo; Reyes, Eusebio López; Moulin, Léa; Pene, Laurent; Haned, Hinda; Sijen, Titia

2017-07-01

Searching a national DNA database with complex and incomplete profiles usually yields very large numbers of possible matches that can present many candidate suspects to be further investigated by the forensic scientist and/or police. Current practice in most forensic laboratories consists of ordering these 'hits' based on the number of matching alleles with the searched profile. Thus, candidate profiles that share the same number of matching alleles are not differentiated and due to the lack of other ranking criteria for the candidate list it may be difficult to discern a true match from the false positives or notice that all candidates are in fact false positives. SmartRank was developed to put forward only relevant candidates and rank them accordingly. The SmartRank software computes a likelihood ratio (LR) for the searched profile and each profile in the DNA database and ranks database entries above a defined LR threshold according to the calculated LR. In this study, we examined for mixed DNA profiles of variable complexity whether the true donors are retrieved, what the number of false positives above an LR threshold is and the ranking position of the true donors. Using 343 mixed DNA profiles over 750 SmartRank searches were performed. In addition, the performance of SmartRank and CODIS were compared regarding DNA database searches and SmartRank was found complementary to CODIS. We also describe the applicable domain of SmartRank and provide guidelines. The SmartRank software is open-source and freely available. Using the best practice guidelines, SmartRank enables obtaining investigative leads in criminal cases lacking a suspect. Copyright © 2017 Elsevier B.V. All rights reserved.

Detecting positive quadrant dependence and positive function dependence

NARCIS (Netherlands)

Janic-Wróblewska, A.; Kallenberg, W.C.M.; Ledwina, T.

2004-01-01

There is a lot of interest in positive dependence going beyond linear correlation. In this paper three new rank tests for testing independence against positive dependence are introduced. The first one is directed on positive quadrant dependence, the second and third one concentrate on positive

Detecting positive quadrant dependence and positive function dependence

NARCIS (Netherlands)

Janic-Wróblewska, A.; Kallenberg, W.C.M.; Ledwina, T.

2003-01-01

There is a lot of interest in positive dependence going beyond linear correlation. In this paper three new rank tests for testing independence against positive dependence are introduced. The first one is directed on positive quadrant dependence, the second and third one concentrate on positive

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.

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.

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.

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.

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.

Use of recommended score chart and ranking of clinical features in ...

African Journals Online (AJOL)

The ranking of symptoms by all respondents were persistent non remitting cough (1), weight loss or failure to thrive (2&3), history of contact with adult with smear positive tuberculosis (4), radiographic abnormalities (5). Weight loss and failure to thrive was scored highest in ranks (2) and (3). There was a difference in the ...

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

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...

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.

Finding differentially expressed genes in high dimensional data: Rank based test statistic via a distance measure.

Science.gov (United States)

Mathur, Sunil; Sadana, Ajit

2015-12-01

We present a rank-based test statistic for the identification of differentially expressed genes using a distance measure. The proposed test statistic is highly robust against extreme values and does not assume the distribution of parent population. Simulation studies show that the proposed test is more powerful than some of the commonly used methods, such as paired t-test, Wilcoxon signed rank test, and significance analysis of microarray (SAM) under certain non-normal distributions. The asymptotic distribution of the test statistic, and the p-value function are discussed. The application of proposed method is shown using a real-life data set. © The Author(s) 2011.

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.

Ranking low, feeling high: How hierarchical position and experienced power promote prosocial behavior in response to procedural justice.

Science.gov (United States)

van Dijke, Marius; De Cremer, David; Langendijk, Gerben; Anderson, Cameron

2018-02-01

Research shows that power can lead to prosocial behavior by facilitating the behavioral expression of dispositional prosocial motivation. However, it is not clear how power may facilitate responses to contextual factors that promote prosocial motivation. Integrating fairness heuristic theory and the situated focus theory of power, we argue that in particular, organization members in lower (vs. higher) hierarchical positions who simultaneously experience a high (vs. low) sense of power respond with prosocial behavior to 1 important antecedent of prosocial motivation, that is, the enactment of procedural justice. The results from a multisource survey among employees and their leaders from various organizations (Study 1) and an experiment using a public goods dilemma (Study 2) support this prediction. Three subsequent experiments (Studies 3-5) show that this effect is mediated by perceptions of authority trustworthiness. Taken together, this research (a) helps resolve the debate regarding whether power promotes or undermines prosocial behavior, (b) demonstrates that hierarchical position and the sense of power can have very different effects on processes that are vital to the functioning of an organization, and (c) helps solve ambiguity regarding the roles of hierarchical position and power in fairness heuristic theory. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Receptor activator of nuclear factor kappa B (RANK as a determinant of peri-implantitis

Directory of Open Access Journals (Sweden)

Rakić Mia

2013-01-01

Full Text Available Background/Aim. Peri-implantitis presents inflammatory process that affects soft and hard supporting tissues of osseointegrated implant based on inflammatory osteoclastogenesis. The aim of this study was to investigate whether receptor activator of nuclear factor kappa B (RANK concentrations in peri-implant crevicular fluid could be associated with clinical parameters that reflect inflammatory nature of peri-implantitis. Methods. The study included 67 patients, 22 with diagnosed peri-implantitis, 22 persons with healthy peri-implant tissues and 23 patients with periodontitis. Clinical parameters from each patient were recorded and samples of peri-implant/gingival crevicular fluid were collected for the enzyme-linked immunosorbent assay (ELISA analysis. Results. RANK concentration was significantly increased in samples from the patients with periimplantitis when compared to healthy implants (p < 0.0001, where the average levels were 9 times higher. At the same time RANK concentration was significantly higher in periimplantitis than in periodontitis sites (p < 0.0001. In implant patients pocket depths and bleeding on probing values were positively associated with high RANK concentrations (p < 0.0001. Conclusion. These results revealed association of increased RANK concentration in samples of periimplant/ gingival crevicular fluid with peri-implant inflammation and suggests that RANK could be a pathologic determinant of peri-implantitis, thereby a potential parameter in assessment of peri-implant tissue inflammation and a potential target in designing treatment strategies.

A C++11 implementation of arbitrary-rank tensors for high-performance computing

Science.gov (United States)

Aragón, Alejandro M.

2014-11-01

This article discusses an efficient implementation of tensors of arbitrary rank by using some of the idioms introduced by the recently published C++ ISO Standard (C++11). With the aims at providing a basic building block for high-performance computing, a single Array class template is carefully crafted, from which vectors, matrices, and even higher-order tensors can be created. An expression template facility is also built around the array class template to provide convenient mathematical syntax. As a result, by using templates, an extra high-level layer is added to the C++ language when dealing with algebraic objects and their operations, without compromising performance. The implementation is tested running on both CPU and GPU.

Clean utilization of low-rank coals for low-cost power generation

International Nuclear Information System (INIS)

Sondreal, E.A.

1992-01-01

Despite the unique utilization problems of low-rank coals, the ten US steam electric plants having the lowest operating cost in 1990 were all fueled on either lignite or subbituminous coal. Ash deposition problems, which have been a major barrier to sustaining high load on US boilers burning high-sodium low-rank coals, have been substantially reduced by improvements in coal selection, boiler design, on-line cleaning, operating conditions, and additives. Advantages of low-rank coals in advanced systems are their noncaking behavior when heated, their high reactivity allowing more complete reaction at lower temperatures, and the low sulfur content of selected deposits. The principal barrier issues are the high-temperature behavior of ash and volatile alkali derived from the coal-bound sodium found in some low-rank coals. Successful upgrading of low-rank coals requires that the product be both stable and suitable for end use in conventional and advanced systems. Coal-water fuel produced by hydrothermal processing of high-moisture low-rank coal meets these criteria, whereas most dry products from drying or carbonizing in hot gas tend to create dust and spontaneous ignition problems unless coated, agglomerated, briquetted, or afforded special handling

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 quadratic semidefinite programming

KAUST Repository

Yuan, Ganzhao

2013-04-01

Low rank matrix approximation is an attractive model in large scale machine learning problems, because it can not only reduce the memory and runtime complexity, but also provide a natural way to regularize parameters while preserving learning accuracy. In this paper, we address a special class of nonconvex quadratic matrix optimization problems, which require a low rank positive semidefinite solution. Despite their non-convexity, we exploit the structure of these problems to derive an efficient solver that converges to their local optima. Furthermore, we show that the proposed solution is capable of dramatically enhancing the efficiency and scalability of a variety of concrete problems, which are of significant interest to the machine learning community. These problems include the Top-k Eigenvalue problem, Distance learning and Kernel learning. Extensive experiments on UCI benchmarks have shown the effectiveness and efficiency of our proposed method. © 2012.

Low-rank quadratic semidefinite programming

KAUST Repository

Yuan, Ganzhao; Zhang, Zhenjie; Ghanem, Bernard; Hao, Zhifeng

2013-01-01

Low rank matrix approximation is an attractive model in large scale machine learning problems, because it can not only reduce the memory and runtime complexity, but also provide a natural way to regularize parameters while preserving learning accuracy. In this paper, we address a special class of nonconvex quadratic matrix optimization problems, which require a low rank positive semidefinite solution. Despite their non-convexity, we exploit the structure of these problems to derive an efficient solver that converges to their local optima. Furthermore, we show that the proposed solution is capable of dramatically enhancing the efficiency and scalability of a variety of concrete problems, which are of significant interest to the machine learning community. These problems include the Top-k Eigenvalue problem, Distance learning and Kernel learning. Extensive experiments on UCI benchmarks have shown the effectiveness and efficiency of our proposed method. © 2012.

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

Non-intrusive low-rank separated approximation of high-dimensional stochastic models

KAUST Repository

Doostan, Alireza; Validi, AbdoulAhad; Iaccarino, Gianluca

2013-01-01

This work proposes a sampling-based (non-intrusive) approach within the context of low-. rank separated representations to tackle the issue of curse-of-dimensionality associated with the solution of models, e.g., PDEs/ODEs, with high-dimensional random inputs. Under some conditions discussed in details, the number of random realizations of the solution, required for a successful approximation, grows linearly with respect to the number of random inputs. The construction of the separated representation is achieved via a regularized alternating least-squares regression, together with an error indicator to estimate model parameters. The computational complexity of such a construction is quadratic in the number of random inputs. The performance of the method is investigated through its application to three numerical examples including two ODE problems with high-dimensional random inputs. © 2013 Elsevier B.V.

Non-intrusive low-rank separated approximation of high-dimensional stochastic models

KAUST Repository

Doostan, Alireza

2013-08-01

This work proposes a sampling-based (non-intrusive) approach within the context of low-. rank separated representations to tackle the issue of curse-of-dimensionality associated with the solution of models, e.g., PDEs/ODEs, with high-dimensional random inputs. Under some conditions discussed in details, the number of random realizations of the solution, required for a successful approximation, grows linearly with respect to the number of random inputs. The construction of the separated representation is achieved via a regularized alternating least-squares regression, together with an error indicator to estimate model parameters. The computational complexity of such a construction is quadratic in the number of random inputs. The performance of the method is investigated through its application to three numerical examples including two ODE problems with high-dimensional random inputs. © 2013 Elsevier B.V.

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...

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).

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.

Returns to Tenure: Time or Rank?

DEFF Research Database (Denmark)

Buhai, Ioan Sebastian

-specific investment, efficiency-wages or adverse-selection models. However, rent extracting arguments as suggested by the theory of internal labor markets, indicate that the relative position of the worker in the seniority hierarchy of the firm, her 'seniority rank', may also explain part of the observed returns...... relative to their peer workers), as predicted by theories on unionized and insider-outsider markets....

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).

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.

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

Low ranks make the difference : How achievement goals and ranking information affect cooperation intentions

NARCIS (Netherlands)

Poortvliet, P. Marijn; Janssen, Onne; Van Yperen, N.W.; Van de Vliert, E.

This investigation tested the joint effect of achievement goals and ranking information on information exchange intentions with a commensurate exchange partner. Results showed that individuals with performance goals were less inclined to cooperate with an exchange partner when they had low or high

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

Directory of Open Access Journals (Sweden)

Liviu P Dinu

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

Assessment of low-rank (LRC) drying technologies

International Nuclear Information System (INIS)

Willson, W.G.; Young, B.C.; Irwinj, W.

1992-01-01

This paper reports that low-rank coals (LRCs), brown, lignitic, and subbituminous coals, represent nearly half of the estimated coal resources in the world. In many of the developing nations, LRCs are the only source of low-cost energy. LRCs are geologically younger than higher-rank bituminous coals and are typically present in thick seams with less cover (overburden) than bituminous coals, making them recoverable by low-cost strip mining. Current pit-head coal prices for LRCs range from a low of around $0.25 per MM Btus for subbituminous coals from the USA's Powder River Basin, to highs of around $1,00 for those that are more costly to mine. On the other hand, the pit-head price of bituminous coals in the USA range from a low of around $1 to over $2 per MM Btu. Unfortunately, this differential in favor of LRC is more than offset in distant markers where, until now, it has been considered a nuisance. Often less than half of its weight is combustible, the rest being water and ash. Thus the cost of hauling it any distance at all in its untreated dry bulk form is prohibitive. However, from a utilization aspect, LRCs have a lower fuel ration (fixed carbon to volatile matter) and are typically an order of magnitude more reactive than bituminous coals. Many LRCs, including the enormous reserves in Alaska, Australia, and Indonesia, also have extremely low sulfur contents of only a few tenths of a percent. Low mining costs, high reactivity, and extremely low sulfur content would make these coals premium fuel were it not for their high moisture levels, which range from around 25% w/w to over 60% w/w. High moisture creates a mistaken perception, among major coal importers, of inferior quality, and the many positive features of LRCs are overlooked

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.

Contextual effects on the perceived health benefits of exercise: the exercise rank hypothesis.

Science.gov (United States)

Maltby, John; Wood, Alex M; Vlaev, Ivo; Taylor, Michael J; Brown, Gordon D A

2012-12-01

Many accounts of social influences on exercise participation describe how people compare their behaviors to those of others. We develop and test a novel hypothesis, the exercise rank hypothesis, of how this comparison can occur. The exercise rank hypothesis, derived from evolutionary theory and the decision by sampling model of judgment, suggests that individuals' perceptions of the health benefits of exercise are influenced by how individuals believe the amount of exercise ranks in comparison with other people's amounts of exercise. Study 1 demonstrated that individuals' perceptions of the health benefits of their own current exercise amounts were as predicted by the exercise rank hypothesis. Study 2 demonstrated that the perceptions of the health benefits of an amount of exercise can be manipulated by experimentally changing the ranked position of the amount within a comparison context. The discussion focuses on how social norm-based interventions could benefit from using rank information.

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.

Time-Aware Service Ranking Prediction in the Internet of Things Environment.

Science.gov (United States)

Huang, Yuze; Huang, Jiwei; Cheng, Bo; He, Shuqing; Chen, Junliang

2017-04-27

With the rapid development of the Internet of things (IoT), building IoT systems with high quality of service (QoS) has become an urgent requirement in both academia and industry. During the procedures of building IoT systems, QoS-aware service selection is an important concern, which requires the ranking of a set of functionally similar services according to their QoS values. In reality, however, it is quite expensive and even impractical to evaluate all geographically-dispersed IoT services at a single client to obtain such a ranking. Nevertheless, distributed measurement and ranking aggregation have to deal with the high dynamics of QoS values and the inconsistency of partial rankings. To address these challenges, we propose a time-aware service ranking prediction approach named TSRPred for obtaining the global ranking from the collection of partial rankings. Specifically, a pairwise comparison model is constructed to describe the relationships between different services, where the partial rankings are obtained by time series forecasting on QoS values. The comparisons of IoT services are formulated by random walks, and thus, the global ranking can be obtained by sorting the steady-state probabilities of the underlying Markov chain. Finally, the efficacy of TSRPred is validated by simulation experiments based on large-scale real-world datasets.

Time-Aware Service Ranking Prediction in the Internet of Things Environment

Directory of Open Access Journals (Sweden)

Yuze Huang

2017-04-01

Full Text Available With the rapid development of the Internet of things (IoT, building IoT systems with high quality of service (QoS has become an urgent requirement in both academia and industry. During the procedures of building IoT systems, QoS-aware service selection is an important concern, which requires the ranking of a set of functionally similar services according to their QoS values. In reality, however, it is quite expensive and even impractical to evaluate all geographically-dispersed IoT services at a single client to obtain such a ranking. Nevertheless, distributed measurement and ranking aggregation have to deal with the high dynamics of QoS values and the inconsistency of partial rankings. To address these challenges, we propose a time-aware service ranking prediction approach named TSRPred for obtaining the global ranking from the collection of partial rankings. Specifically, a pairwise comparison model is constructed to describe the relationships between different services, where the partial rankings are obtained by time series forecasting on QoS values. The comparisons of IoT services are formulated by random walks, and thus, the global ranking can be obtained by sorting the steady-state probabilities of the underlying Markov chain. Finally, the efficacy of TSRPred is validated by simulation experiments based on large-scale real-world datasets.

Use of rank sum method in identifying high occupational dose jobs for ALARA implementation

International Nuclear Information System (INIS)

Cho, Yeong Ho; Kang, Chang Sun

1998-01-01

The cost-effective reduction of occupational radiation exposure (ORE) dose at a nuclear power plant could not be achieved without going through an extensive analysis of accumulated ORE dose data of existing plants. It is necessary to identify what are high ORE jobs for ALARA implementation. In this study, the Rank Sum Method (RSM) is used in identifying high ORE jobs. As a case study, the database of ORE-related maintenance and repair jobs for Kori Units 3 and 4 is used for assessment, and top twenty high ORE jobs are identified. The results are also verified and validated using the Friedman test, and RSM is found to be a very efficient way of analyzing the data. (author)

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.

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.

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.

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 ...

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.

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.

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

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.

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...

Impacts of Natural Surfactant Soybean Phospholipid on Wettability of High-rank Coal Reservoir

Science.gov (United States)

Lyu, S.; Xiao, Y.; Yuan, M.; Wang, S.

2017-12-01

It is significant to change the surface wettability of coal rock with the surfactant in coal mining and coalbed methane exploitation. Soybean phospholipid (SP) is a kind of natural zwitterionic surfactant which is non-toxic and degradable. In order to study the effects of soybean phospholipid on wettability of high-rank coal in Qinshui Basin, some experiments including surface tension test, contact angle measurement on the coal surface, coal fines imbibition, observation of dispersion effect and gas permeability test were carried out, and water locking mechanism of fracturing fluid in micro fractures of coal reservoir was analyzed. The results show that the surface of high-rank coal was negatively charged in solution and of weak hydrophilicity. The soybean phospholipid with the mass fraction of 0.1% reduced the surface tension of water by 69%, and increased the wettability of coal. Meanwhile, the soybean phospholipid helped coal fines to disperse by observation of the filter cake with the scanning electron microscope. The rising rate of soybean phospholipid solution in the pipe filled with coal fines was lower than that of anionic and cationic surfactant, higher than that of clean water and non-ionic surfactant. Composite surfactant made up of soybean phospholipid and OP-10 at the ratio of 1:3 having a low surface tension and large contact angle, reduced the capillary force effectively, which could be conducive to discharge of fracturing fluid from coal reservoir micro fracture and improve the migration channels of gas. Therefore it has a broad application prospect.

Immunolocalization of RANK and RANKL along the root surface and in the periodontal membrane of human primary and permanent teeth

DEFF Research Database (Denmark)

Bille, Marie-Louise Bastholm; Thomsen, Bjarke; Andersen, Thomas Levin

2012-01-01

Abstract Objective. Root resorption, impaired tooth eruption and early tooth loss have been described in relation to diseases that involve defects in the RANK-RANKL-OPG-expression. The aim of the present immunhistochemical study was to localize and compare the reactions for RANK and membrane...... in odontoblasts and in cells along denticles in one primary tooth. RANK was located in mononuclear cells in the pulp and in multinucleated odontoclasts along resorbed root surfaces and along resorbed dentin surfaces in the pulp in primary teeth and one permanent tooth. Conclusions. This study demonstrated RANK...... positivity in resorption areas in primary and permanent teeth. RANKL was positive in the pulp of one primary tooth. RANK expression in odontoclasts and RANKL expression in the pulp may indicate that RANK/RANKL play a role during resorption....

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

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.

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.

Testing the encoding elaboration hypothesis: The effects of exemplar ranking on recognition and recall.

Science.gov (United States)

Schnur, P

1977-11-01

Two experiments investigated the effects of exemplar ranking on retention. High-ranking exemplars are words judged to be prototypical of a given category; low-ranking exemplars are words judged to be atypical of a given category. In Experiment 1, an incidental learning paradigm was used to measure reaction time to answer an encoding question as well as subsequent recognition. It was found that low-ranking exemplars were classified more slowly but recognized better than high-ranking exemplars. Other comparisons of the effects of category encoding, rhyme encoding, and typescript encoding on response latency and recognition replicated the results of Craik and Tulving (1975). In Experiment 2, unanticipated free recall of live previously learned paired associate lists revealed that a list composed of low-ranking exemplars was better recalled than a comparable list composed of high-ranking exemplars. Moreover, this was true only when the lists were studied in the context of appropriate category cues. These findings are discussed in terms of the encoding elaboration hypothesis.

Competition in the Brain. The Contribution of EEG and fNIRS Modulation and Personality Effects in Social Ranking.

Science.gov (United States)

Balconi, Michela; Vanutelli, Maria E

2016-01-01

In the present study, the social ranking perception in competition was explored. Brain response (alpha band oscillations, EEG; hemodynamic activity, O2Hb), as well as self-perception of social ranking, cognitive performance, and personality trait (Behavioral Activation System, BAS) were considered during a competitive joint-action. Subjects were required to develop a strategy to obtain a better outcome than a competitor (C) (in term of error rate, and response time, RT). A pre-feedback (without a specific feedback on the performance) and a post-feedback condition (which reinforced the improved performance) were provided. It was found that higher-BAS participants responded in greater measure to perceived higher cognitive performance (post-feedback condition), with increased left prefrontal activity, higher ranking perception, and a better real performance (reduced RTs). These results were explained in term of increased sense of self-efficacy and social position, probably based on higher-BAS sensitivity to reinforcing conditions. In addition, the hemispheric effect in favor of the left side characterized the competitive behavior, showing an imbalance for high-BAS in comparison to low-BAS in the case of a rewarding (post-feedback) context. Therefore, the present results confirmed the significance of BAS in modulating brain responsiveness, self-perceived social position, and real performance during an interpersonal competitive action which is considered highly relevant for social status.

Group social rank is associated with performance on a spatial learning task.

Science.gov (United States)

Langley, Ellis J G; van Horik, Jayden O; Whiteside, Mark A; Madden, Joah R

2018-02-01

Dominant individuals differ from subordinates in their performances on cognitive tasks across a suite of taxa. Previous studies often only consider dyadic relationships, rather than the more ecologically relevant social hierarchies or networks, hence failing to account for how dyadic relationships may be adjusted within larger social groups. We used a novel statistical method: randomized Elo-ratings, to infer the social hierarchy of 18 male pheasants, Phasianus colchicus , while in a captive, mixed-sex group with a linear hierarchy. We assayed individual learning performance of these males on a binary spatial discrimination task to investigate whether inter-individual variation in performance is associated with group social rank. Task performance improved with increasing trial number and was positively related to social rank, with higher ranking males showing greater levels of success. Motivation to participate in the task was not related to social rank or task performance, thus indicating that these rank-related differences are not a consequence of differences in motivation to complete the task. Our results provide important information about how variation in cognitive performance relates to an individual's social rank within a group. Whether the social environment causes differences in learning performance or instead, inherent differences in learning ability predetermine rank remains to be tested.

An exploration in the will psychology of Otto Rank: human intentionality and individuality.

Science.gov (United States)

Isono, Masayo

2012-12-01

The author explores the meaning and the importance of the will in Rank's relation-based self-creative, self-constructive psychology and argues for the consideration of the concept of the will in psychoanalysis. The paper shows that Rank's concept of the will explains what gives a human being the impetus to choose an action, positive or negative. When validated by the other, this will, the power of intention, enables a person to create his/her unique individuality. The paper reviews Rank's definition of will and traces the evolution of his ideas of intentionality in his writings. Further, the author discusses how Rank attempts to capture the subtle movements of the human mind as suffused with struggles and dynamic interplay between external and internal forces.

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...

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

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

institutions with a more effective feedback for research improvement. Rankings which extensively rely on subjective reputation and "luxury" indicators, such as award winning faculty or alumni who are high ranking executives, are not well suited for academic or research performance improvement initiatives. Future efforts should better explore measurement of the university research performance through comprehensive and standardized indicators. This paper could serve as a general literature citation when one or more of university ranking systems are used in efforts to improve academic prominence and research performance.

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...

Using a consensus approach based on the conservation of inter-residue contacts to rank CAPRI models

KAUST Repository

Vangone, Anna

2013-10-17

Herein we propose the use of a consensus approach, CONSRANK, for ranking CAPRI models. CONSRANK relies on the conservation of inter-residue contacts in the analyzed decoys ensemble. Models are ranked according to their ability to match the most frequently observed contacts. We applied CONSRANK to 19 CAPRI protein-protein targets, covering a wide range of prediction difficulty and involved in a variety of biological functions. CONSRANK results are consistently good, both in terms of native-like (NL) solutions ranked in the top positions and of values of the Area Under the receiver operating characteristic Curve (AUC). For targets having a percentage of NL solutions above 3%, an excellent performance is found, with AUC values approaching 1. For the difficult target T46, having only 3.4% NL solutions, the number of NL solutions in the top 5 and 10 ranked positions is enriched by a factor 30, and the AUC value is as high as 0.997. AUC values below 0.8 are only found for targets featuring a percentage of NL solutions within 1.1%. Remarkably, a false consensus emerges only in one case, T42, which happens to be an artificial protein, whose assembly details remain uncertain, based on controversial experimental data. We also show that CONSRANK still performs very well on a limited number of models, provided that more than 1 NL solution is included in the ensemble, thus extending its applicability to cases where few dozens of models are available.© 2013 Wiley Periodicals, Inc.

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

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…

Recovering task fMRI signals from highly under-sampled data with low-rank and temporal subspace constraints.

Science.gov (United States)

Chiew, Mark; Graedel, Nadine N; Miller, Karla L

2018-07-01

Recent developments in highly accelerated fMRI data acquisition have employed low-rank and/or sparsity constraints for image reconstruction, as an alternative to conventional, time-independent parallel imaging. When under-sampling factors are high or the signals of interest are low-variance, however, functional data recovery can be poor or incomplete. We introduce a method for improving reconstruction fidelity using external constraints, like an experimental design matrix, to partially orient the estimated fMRI temporal subspace. Combining these external constraints with low-rank constraints introduces a new image reconstruction model that is analogous to using a mixture of subspace-decomposition (PCA/ICA) and regression (GLM) models in fMRI analysis. We show that this approach improves fMRI reconstruction quality in simulations and experimental data, focusing on the model problem of detecting subtle 1-s latency shifts between brain regions in a block-design task-fMRI experiment. Successful latency discrimination is shown at acceleration factors up to R = 16 in a radial-Cartesian acquisition. We show that this approach works with approximate, or not perfectly informative constraints, where the derived benefit is commensurate with the information content contained in the constraints. The proposed method extends low-rank approximation methods for under-sampled fMRI data acquisition by leveraging knowledge of expected task-based variance in the data, enabling improvements in the speed and efficiency of fMRI data acquisition without the loss of subtle features. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

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)

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.

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…

Task 27 -- Alaskan low-rank coal-water fuel demonstration project

Energy Technology Data Exchange (ETDEWEB)

NONE

1995-10-01

Development of coal-water-fuel (CWF) technology has to-date been predicated on the use of high-rank bituminous coal only, and until now the high inherent moisture content of low-rank coal has precluded its use for CWF production. The unique feature of the Alaskan project is the integration of hot-water-drying (HWD) into CWF technology as a beneficiation process. Hot-water-drying is an EERC developed technology unavailable to the competition that allows the range of CWF feedstock to be extended to low-rank coals. The primary objective of the Alaskan Project, is to promote interest in the CWF marketplace by demonstrating the commercial viability of low-rank coal-water-fuel (LRCWF). While commercialization plans cannot be finalized until the implementation and results of the Alaskan LRCWF Project are known and evaluated, this report has been prepared to specifically address issues concerning business objectives for the project, and outline a market development plan for meeting those objectives.

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.

Rank Detector Preprocessor for Glint Reduction in a Tracking Radar

CSIR Research Space (South Africa)

Guest, IW

1993-04-01

Full Text Available A rank detector is used to defect instantaneous received power fades in tracking radar. On detection of a fade, censorship of the angular position measurement is implemented in a Kalman tracking filter. It is shown that this technique can typically...

1991 Acceptance priority ranking

International Nuclear Information System (INIS)

1991-12-01

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

Simpson's Paradox and Confounding Factors in University Rankings: A Demonstration Using QS 2011-12 Data

Science.gov (United States)

Soh, Kay Cheng

2012-01-01

University ranking has become ritualistic in higher education. Ranking results are taken as bona fide by rank users. Ranking systems usually use large data sets from highly heterogeneous universities of varied backgrounds. This poses the problem of Simpson's Paradox and the lurking variables causing it. Using QS 2011-2012 Ranking data, the dual…

Separability problem for multipartite states of rank at most 4

International Nuclear Information System (INIS)

Chen, Lin; Đoković, Dragomir Ž

2013-01-01

One of the most important problems in quantum information is the separability problem, which asks whether a given quantum state is separable. We investigate multipartite states of rank at most 4 which are PPT (i.e., all their partial transposes are positive semidefinite). We show that any PPT state of rank 2 or 3 is separable and has length at most 4. For separable states of rank 4, we show that they have length at most 6. It is six only for some qubit–qutrit or multiqubit states. It turns out that any PPT entangled state of rank 4 is necessarily supported on a 3⊗3 or a 2⊗2⊗2 subsystem. We obtain a very simple criterion for the separability problem of the PPT states of rank at most 4: such a state is entangled if and only if its range contains no product vectors. This criterion can be easily applied since a four-dimensional subspace in the 3⊗3 or 2⊗2⊗2 system contains a product vector if and only if its Plücker coordinates satisfy a homogeneous polynomial equation (the Chow form of the corresponding Segre variety). We have computed an explicit determinantal expression for the Chow form in the former case, while such an expression was already known in the latter case. (paper)

Rank-dependent grooming patterns and cortisol alleviation in Barbary macaques.

Science.gov (United States)

Sonnweber, Ruth S; Ravignani, Andrea; Stobbe, Nina; Schiestl, Gisela; Wallner, Bernard; Fitch, W Tecumseh

2015-06-01

Flexibly adapting social behavior to social and environmental challenges helps to alleviate glucocorticoid (GC) levels, which may have positive fitness implications for an individual. For primates, the predominant social behavior is grooming. Giving grooming to others is particularly efficient in terms of GC mitigation. However, grooming is confined by certain limitations such as time constraints or restricted access to other group members. For instance, dominance hierarchies may impact grooming partner availability in primate societies. Consequently specific grooming patterns emerge. In despotic species focusing grooming activity on preferred social partners significantly ameliorates GC levels in females of all ranks. In this study we investigated grooming patterns and GC management in Barbary macaques, a comparably relaxed species. We monitored changes in grooming behavior and cortisol (C) for females of different ranks. Our results show that the C-amelioration associated with different grooming patterns had a gradual connection with dominance hierarchy: while higher-ranking individuals showed lowest urinary C measures when they focused their grooming on selected partners within their social network, lower-ranking individuals expressed lowest C levels when dispersing their grooming activity evenly across their social partners. We argue that the relatively relaxed social style of Barbary macaque societies allows individuals to flexibly adapt grooming patterns, which is associated with rank-specific GC management. © 2015 Wiley Periodicals, Inc.

Smoking is rank! But, not as rank as other drugs and bullying say New Zealand parents of pre-adolescent children.

Science.gov (United States)

Glover, Marewa; Kira, Anette; Min, Sandar; Scragg, Robert; Nosa, Vili; McCool, Judith; Bullen, Chris

2011-12-01

Despite the established risks associated with smoking, 21% of New Zealand adults smoke. Prevalence among Māori (indigenous) and Pacific Island New Zealanders is disproportionately high. Prevention of smoking initiation is a key component of tobacco control. Keeping Kids Smokefree--a quasi-experimental trial--aimed to do this by changing parental smoking behaviour and attitudes. However, little is known about parents' attitudes to smoking in comparison with other concerns. Parents of 4,144 children attending five urban schools in a high smoking prevalence population in Auckland, New Zealand, were asked to rank seven concerns on a paper-based questionnaire, including smoking, alcohol and bullying, from most to least serious. Methamphetamine and other illicit 'hard' drugs were ranked as most serious followed by marijuana smoking, alcohol drinking, bullying, cigarette smoking, sex and obesity. Never smokers ranked cigarette smoking as more serious than current or ex-smokers. Parents' under-estimation of the serious nature of tobacco smoking relative to other drugs could partly explain low participation rates in parent-focused smoking initiation prevention programs.

[Lack of interest in general practice during the National Ranking Examination in 2005].

Science.gov (United States)

Lanson, Yves

2006-03-01

The second national ranking test took place in 2005 in the same conditions as the year before. Analysis of the results permits us to assess whether the objectives of this reform have been met so far. Data crossing of the results provided by the national testing center allowed us to rank: 1) the appeal of specializations for each geographic subdivision, 2) the candidates by medical school, and 3) the appeal of each subdivision by candidate rank. 66% of the students were classified high enough to be able to choose any specialization. Trends observed from the first examination, in 2004, were confirmed, with the clear desirability of medical specializations and a certain lack of interest in occupational medicine and public health. All the surgery posts were filled, even though the number of posts had increased enormously since the first examination. After adjustment for the number of posts available, the specializations in decreasing order of popularity were: medical, surgical, pediatrics, anesthesiology, gynecology-obstetrics, general medicine, psychiatry, and biology. Approximately 1000 posts in general medicine were not filled. The medical schools whose students ranked highest were Paris Pitié, Paris V, Paris West, Lyon North, Grenoble, and Aix-Marseille. Some medical schools did less well than previously: Marseille very slightly and Angers substantially. Strasbourg, Nancy Amiens and Bobigny were at the bottom of the list. The cities most desired for internships were Paris, Toulouse, Lyon, and Aix-Marseille, while Brest, Nancy, Limoges and the West Indies were ranked lowest, although each was chosen by highly ranked candidate. Two thirds of the students were ranked high enough to allow them a free choice of specializations. All the specializations except public health and occupational medicine had very highly ranked students. Medical specializations are the most desired, but surgery remains highly demanded, despite a substantial increase in the number of posts. All

Design of an Interface for Page Rank Calculation using Web Link Attributes Information

Directory of Open Access Journals (Sweden)

Jeyalatha SIVARAMAKRISHNAN

2010-01-01

Full Text Available This paper deals with the Web Structure Mining and the different Structure Mining Algorithms like Page Rank, HITS, Trust Rank and Sel-HITS. The functioning of these algorithms are discussed. An incremental algorithm for calculation of PageRank using an interface has been formulated. This algorithm makes use of Web Link Attributes Information as key parameters and has been implemented using Visibility and Position of a Link. The application of Web Structure Mining Algorithm in an Academic Search Application has been discussed. The present work can be a useful input to Web Users, Faculty, Students and Web Administrators in a University Environment.

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. ...

A Study of Rank Defect and Network Effect in Processing the CMONOC Network on Bernese

Directory of Open Access Journals (Sweden)

Weiwei Wu

2018-02-01

Full Text Available High-precision GPS data processing on Bernese has been employed to routinely resolve daily position solutions of GPS stations in the Crustal Movement Observation Network of China (CMONOC. The rank-deficient problems of the normal equation (NEQ system and the network effect on the frame alignment of NEQs in the processing of CMONOC data on Bernese still present difficulties. In this study, we diagnose the rank-deficient problems of the original NEQ, review the efficiency of the controlled datum removal (CDR method in filtering out the three frame-origin-related datum contents, investigate the reliabilities of the inherited frame orientation and scale information from the fixation of the GPS satellite orbits and the Earth rotation parameters in establishing the NEQ of the CMONOC network on Bernese, and analyze the impact of the network effect on the position time series of GPS stations. Our results confirm the nonsingularity of the original NEQ and the efficiency of the CDR filtering in resolving the rank-deficient problems; show that the frame origin parameters are weakly defined and should be stripped off, while the frame orientation and scale parameters should be retained due to their insufficient redefinition from the minimal constraint (MC implementation through inhomogeneous and asymmetrical fiducial networks; and reveal the superiority of a globally distributed fiducial network for frame alignment of the reconstructed NEQs via No-Net-Translation (NNT MC conditions. Finally, we attribute the two apparent discontinuities in the position time series to the terrestrial reference frame (TRF conversions of the GPS satellite orbits, and identify it as the orbit TRF effect.

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

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)

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

The optimized expansion based low-rank method for wavefield extrapolation

KAUST Repository

Wu, Zedong

2014-03-01

Spectral methods are fast becoming an indispensable tool for wavefield extrapolation, especially in anisotropic media because it tends to be dispersion and artifact free as well as highly accurate when solving the wave equation. However, for inhomogeneous media, we face difficulties in dealing with the mixed space-wavenumber domain extrapolation operator efficiently. To solve this problem, we evaluated an optimized expansion method that can approximate this operator with a low-rank variable separation representation. The rank defines the number of inverse Fourier transforms for each time extrapolation step, and thus, the lower the rank, the faster the extrapolation. The method uses optimization instead of matrix decomposition to find the optimal wavenumbers and velocities needed to approximate the full operator with its explicit low-rank representation. As a result, we obtain lower rank representations compared with the standard low-rank method within reasonable accuracy and thus cheaper extrapolations. Additional bounds set on the range of propagated wavenumbers to adhere to the physical wave limits yield unconditionally stable extrapolations regardless of the time step. An application on the BP model provided superior results compared to those obtained using the decomposition approach. For transversely isotopic media, because we used the pure P-wave dispersion relation, we obtained solutions that were free of the shear wave artifacts, and the algorithm does not require that n > 0. In addition, the required rank for the optimization approach to obtain high accuracy in anisotropic media was lower than that obtained by the decomposition approach, and thus, it was more efficient. A reverse time migration result for the BP tilted transverse isotropy model using this method as a wave propagator demonstrated the ability of the algorithm.

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.

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.

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.

Global cities rankings. A research agenda or a neoliberal urban planning tool?

Directory of Open Access Journals (Sweden)

Cándida Gago García

2017-03-01

Full Text Available This paper contains a theoretical reflection about the methodology and meaning given to the global city rankings. There is a very large academic production about the role that some cities have in global territorial processes, which has been related to the concept of global city. Many recent contributions from the mass media, advertising and consulting services must be considered also in the analysis. All of them have included new indicators in order to show the main role that cultural services have acquired in the urban economy. Also the city rankings are being used as a tool in neoliberal policies. These policies stress the position that cities have in the rankings, which are used in practices of city-branding and to justify the neoliberal decisions that are being taken. In fact, we think that rankings are used inappropriately and that it is necessary a deep and new reflection about them.

Implementation of preference ranking organization method for enrichment evaluation (Promethee) on selection system of student’s achievement

Science.gov (United States)

Karlitasari, L.; Suhartini, D.; Nurrosikawati, L.

2018-03-01

Selection of Student Achievement is conducted every year, starting from the level of Study Program, Faculty, to University, which then rank one will be sent to Kopertis level. The criteria made for the selection are Academic and Rich Scientific, Organizational, Personality, and English. In order for the selection of Student Achievement is Objective, then in addition to the presence of the jury is expected to use methods that support the decision to be more optimal in determining the Student Achievement. One method used is the Promethee Method. Preference Ranking Organization Method for Enrichment Evaluation (Promethee) is a method of ranking in Multi Criteria Decision Making (MCDM). PROMETHEE has the advantage that there is a preference type against the criteria that can take into account alternatives with other alternatives on the same criteria. The conjecture of alternate dominance over a criterion used in PROMETHEE is the use of values in the relationships between alternative ranking values. Based on the calculation result, from 7 applicants between Manual and Promethee Matrices, rank 1, 2, and 3, did not change, only 4 to 7 positions were changed. However, after the sensitivity test, almost all criteria experience a high level of sensitivity. Although it does not affect the students who will be sent to the next level, but can bring psychological impact on prospective student’s achievement

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

Bias and Stability of Single Variable Classifiers for Feature Ranking and Selection.

Science.gov (United States)

Fakhraei, Shobeir; Soltanian-Zadeh, Hamid; Fotouhi, Farshad

2014-11-01

Feature rankings are often used for supervised dimension reduction especially when discriminating power of each feature is of interest, dimensionality of dataset is extremely high, or computational power is limited to perform more complicated methods. In practice, it is recommended to start dimension reduction via simple methods such as feature rankings before applying more complex approaches. Single Variable Classifier (SVC) ranking is a feature ranking based on the predictive performance of a classifier built using only a single feature. While benefiting from capabilities of classifiers, this ranking method is not as computationally intensive as wrappers. In this paper, we report the results of an extensive study on the bias and stability of such feature ranking method. We study whether the classifiers influence the SVC rankings or the discriminative power of features themselves has a dominant impact on the final rankings. We show the common intuition of using the same classifier for feature ranking and final classification does not always result in the best prediction performance. We then study if heterogeneous classifiers ensemble approaches provide more unbiased rankings and if they improve final classification performance. Furthermore, we calculate an empirical prediction performance loss for using the same classifier in SVC feature ranking and final classification from the optimal choices.

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.

Validation of a model for ranking aquaculture facilities for risk-based disease surveillance.

Science.gov (United States)

Diserens, Nicolas; Falzon, Laura Cristina; von Siebenthal, Beat; Schüpbach-Regula, Gertraud; Wahli, Thomas

2017-09-15

A semi-quantitative model for risk ranking of aquaculture facilities in Switzerland with regard to the introduction and spread of Viral Haemorrhagic Septicaemia (VHS) and Infectious Haematopoietic Necrosis (IHN) was developed in a previous study (Diserens et al., 2013). The objective of the present study was to validate this model using data collected during field visits on aquaculture sites in four Swiss cantons compared to data collected through a questionnaire in the previous study. A discrepancy between the values obtained with the two different methods was found in 32.8% of the parameters, resulting in a significant difference (pranking of Swiss aquaculture facilities according to their risk of getting infected with or spreading of VHS and IHN, as the five facilities that tested positive for these diseases in the last ten years were ranked as medium or high risk. Moreover, because the seven fish farms that were infected with Infectious Pancreatic Necrosis (IPN) during the same period also belonged to the risk categories medium and high, the classification appeared to correlate with the occurrence of this third viral fish disease. Copyright © 2017 Elsevier B.V. All rights reserved.

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

Estimation of rank correlation for clustered data.

Science.gov (United States)

Rosner, Bernard; Glynn, Robert J

2017-06-30

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

Elliptic fibrations of maximal rank on a supersingular K3 surface

International Nuclear Information System (INIS)

Shioda, Tetsuji

2013-01-01

We study a class of elliptic K3 surfaces defined by an explicit Weierstrass equation to find elliptic fibrations of maximal rank on K3 surface in positive characteristic. In particular, we show that the supersingular K3 surface of Artin invariant 1 (unique by Ogus) admits at least one elliptic fibration with maximal rank 20 in every characteristic p>7, p≠13, and further that the number, say N(p), of such elliptic fibrations (up to isomorphisms), is unbounded as p → ∞; in fact, we prove that lim p→∞ N(p)/p 2 ≥(1/12) 2 .

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)

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....

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.

Multimodal biometric system using rank-level fusion approach.

Science.gov (United States)

Monwar, Md Maruf; Gavrilova, Marina L

2009-08-01

In many real-world applications, unimodal biometric systems often face significant limitations due to sensitivity to noise, intraclass variability, data quality, nonuniversality, and other factors. Attempting to improve the performance of individual matchers in such situations may not prove to be highly effective. Multibiometric systems seek to alleviate some of these problems by providing multiple pieces of evidence of the same identity. These systems help achieve an increase in performance that may not be possible using a single-biometric indicator. This paper presents an effective fusion scheme that combines information presented by multiple domain experts based on the rank-level fusion integration method. The developed multimodal biometric system possesses a number of unique qualities, starting from utilizing principal component analysis and Fisher's linear discriminant methods for individual matchers (face, ear, and signature) identity authentication and utilizing the novel rank-level fusion method in order to consolidate the results obtained from different biometric matchers. The ranks of individual matchers are combined using the highest rank, Borda count, and logistic regression approaches. The results indicate that fusion of individual modalities can improve the overall performance of the biometric system, even in the presence of low quality data. Insights on multibiometric design using rank-level fusion and its performance on a variety of biometric databases are discussed in the concluding section.

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…

$C^1$ actions on manifolds by lattices in Lie groups with sufficiently high rank

OpenAIRE

Damjanovic, Danijela; Zhang, Zhiyuan

2018-01-01

In this paper we study Zimmer's conjecture for $C^1$ actions of higher-rank lattices of a connected, semisimple Lie group with finite center on compact manifolds. We show that if the Lie group has no compact factor, and all of whose non-compact factors are of ranks in some sense sufficiently large with respect to the dimension of the manifold, then every $C^1$ action of an irreducible, co-compact lattice has a finite image. As a corollary of our results, for every (uniform or non-uniform) lat...

Self-appraisal of hockey players of high class of different playing position

Directory of Open Access Journals (Sweden)

Oleksiy Mikhnov

2014-12-01

Full Text Available Purpose: to expose the features of display of self-appraisal for the hockey players of high class of different playing position. Material and Methods: for the exposure of level of self-appraisal for hockey players, information of sportsmen of high class, taking part in the matches of the Kontinental hockey league (KHL in a season 2013–2014 was probed sixteen hockey players, having a sporting digit MS and MSWC, took part in researches. Methods were used: pedagogical supervision, pedagogical analysis and generalization of front-rank experience, psychological testing, analysis of data of the special scientific-methodical literature, expert questioning, an analysis of data is the Internet. Results: findings allowed to set that the players of line of attack (central and extreme forward have more high level of self-appraisal for certain, than players of defence and hockey goalkeepers. This tendency is looked over both on the separate constituents of self-appraisal and on the whole on all spectrums of the studied indexes. The got results of researches rotined that the hockey players of high class had or middle or high level of self-appraisal. Among testable hockey players, players were not exposed with the low level of self-appraisal. Conclusions: the exposed distinctions in the level of self-appraisal of hockey players of high class can be used for diagnostics of playing predisposition and choice of playing line of business in a command.

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

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.

Test Scores, Class Rank and College Performance: Lessons for Broadening Access and Promoting Success.

Science.gov (United States)

Niu, Sunny X; Tienda, Marta

2012-04-01

Using administrative data for five Texas universities that differ in selectivity, this study evaluates the relative influence of two key indicators for college success-high school class rank and standardized tests. Empirical results show that class rank is the superior predictor of college performance and that test score advantages do not insulate lower ranked students from academic underperformance. Using the UT-Austin campus as a test case, we conduct a simulation to evaluate the consequences of capping students admitted automatically using both achievement metrics. We find that using class rank to cap the number of students eligible for automatic admission would have roughly uniform impacts across high schools, but imposing a minimum test score threshold on all students would have highly unequal consequences by greatly reduce the admission eligibility of the highest performing students who attend poor high schools while not jeopardizing admissibility of students who attend affluent high schools. We discuss the implications of the Texas admissions experiment for higher education in Europe.

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.

Ranking network of a captive rhesus macaque society: a sophisticated corporative kingdom.

Science.gov (United States)

Fushing, Hsieh; McAssey, Michael P; Beisner, Brianne; McCowan, Brenda

2011-03-15

We develop a three-step computing approach to explore a hierarchical ranking network for a society of captive rhesus macaques. The computed network is sufficiently informative to address the question: Is the ranking network for a rhesus macaque society more like a kingdom or a corporation? Our computations are based on a three-step approach. These steps are devised to deal with the tremendous challenges stemming from the transitivity of dominance as a necessary constraint on the ranking relations among all individual macaques, and the very high sampling heterogeneity in the behavioral conflict data. The first step simultaneously infers the ranking potentials among all network members, which requires accommodation of heterogeneous measurement error inherent in behavioral data. Our second step estimates the social rank for all individuals by minimizing the network-wide errors in the ranking potentials. The third step provides a way to compute confidence bounds for selected empirical features in the social ranking. We apply this approach to two sets of conflict data pertaining to two captive societies of adult rhesus macaques. The resultant ranking network for each society is found to be a sophisticated mixture of both a kingdom and a corporation. Also, for validation purposes, we reanalyze conflict data from twenty longhorn sheep and demonstrate that our three-step approach is capable of correctly computing a ranking network by eliminating all ranking error.

Ranking network of a captive rhesus macaque society: a sophisticated corporative kingdom.

Directory of Open Access Journals (Sweden)

Hsieh Fushing

2011-03-01

Full Text Available We develop a three-step computing approach to explore a hierarchical ranking network for a society of captive rhesus macaques. The computed network is sufficiently informative to address the question: Is the ranking network for a rhesus macaque society more like a kingdom or a corporation? Our computations are based on a three-step approach. These steps are devised to deal with the tremendous challenges stemming from the transitivity of dominance as a necessary constraint on the ranking relations among all individual macaques, and the very high sampling heterogeneity in the behavioral conflict data. The first step simultaneously infers the ranking potentials among all network members, which requires accommodation of heterogeneous measurement error inherent in behavioral data. Our second step estimates the social rank for all individuals by minimizing the network-wide errors in the ranking potentials. The third step provides a way to compute confidence bounds for selected empirical features in the social ranking. We apply this approach to two sets of conflict data pertaining to two captive societies of adult rhesus macaques. The resultant ranking network for each society is found to be a sophisticated mixture of both a kingdom and a corporation. Also, for validation purposes, we reanalyze conflict data from twenty longhorn sheep and demonstrate that our three-step approach is capable of correctly computing a ranking network by eliminating all ranking error.

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.

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.

Ranking multiple docking solutions based on the conservation of inter-residue contacts

KAUST Repository

Oliva, Romina M.; Vangone, Anna; Cavallo, Luigi

2013-01-01

) conformations in the top positions is still an open problem. Herein we present CONSRANK, a simple and effective tool to rank multiple docking solutions, which relies on the conservation of inter-residue contacts in the analyzed decoys ensemble. First

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.

Application of third order stochastic dominance algorithm in investments ranking

Directory of Open Access Journals (Sweden)

Lončar Sanja

2012-01-01

Full Text Available The paper presents the use of third order stochastic dominance in ranking Investment alternatives, using TSD algorithms (Levy, 2006for testing third order stochastic dominance. The main goal of using TSD rule is minimization of efficient investment set for investor with risk aversion, who prefers more money and likes positive skew ness.

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.

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

Ranked retrieval of segmented nuclei for objective assessment of cancer gene repositioning

Directory of Open Access Journals (Sweden)

Cukierski William J

2012-09-01

correlation coefficients between the gene position measurements were above 0.9 (p Conclusions Accurate segmentation is necessary to automate quantitative image analysis for applications such as gene repositioning. However, due to heterogeneity within images and across different applications, no segmentation algorithm provides a satisfactory solution. Automated assessment of segmentations by ranked retrieval is capable of reducing or even eliminating the need to select segmented objects by hand and represents a significant improvement over binary classification. The method can be extended to other high-throughput applications requiring accurate detection of cells or nuclei across a range of biomedical applications.

Sparse Contextual Activation for Efficient Visual Re-Ranking.

Science.gov (United States)

Bai, Song; Bai, Xiang

2016-03-01

In this paper, we propose an extremely efficient algorithm for visual re-ranking. By considering the original pairwise distance in the contextual space, we develop a feature vector called sparse contextual activation (SCA) that encodes the local distribution of an image. Hence, re-ranking task can be simply accomplished by vector comparison under the generalized Jaccard metric, which has its theoretical meaning in the fuzzy set theory. In order to improve the time efficiency of re-ranking procedure, inverted index is successfully introduced to speed up the computation of generalized Jaccard metric. As a result, the average time cost of re-ranking for a certain query can be controlled within 1 ms. Furthermore, inspired by query expansion, we also develop an additional method called local consistency enhancement on the proposed SCA to improve the retrieval performance in an unsupervised manner. On the other hand, the retrieval performance using a single feature may not be satisfactory enough, which inspires us to fuse multiple complementary features for accurate retrieval. Based on SCA, a robust feature fusion algorithm is exploited that also preserves the characteristic of high time efficiency. We assess our proposed method in various visual re-ranking tasks. Experimental results on Princeton shape benchmark (3D object), WM-SRHEC07 (3D competition), YAEL data set B (face), MPEG-7 data set (shape), and Ukbench data set (image) manifest the effectiveness and efficiency of SCA.

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.

Reliability analysis of visual ranking of coronary artery calcification on low-dose CT of the thorax for lung cancer screening: comparison with ECG-gated calcium scoring CT.

Science.gov (United States)

Kim, Yoon Kyung; Sung, Yon Mi; Cho, So Hyun; Park, Young Nam; Choi, Hye-Young

2014-12-01

Coronary artery calcification (CAC) is frequently detected on low-dose CT (LDCT) of the thorax. Concurrent assessment of CAC and lung cancer screening using LDCT is beneficial in terms of cost and radiation dose reduction. The aim of our study was to evaluate the reliability of visual ranking of positive CAC on LDCT compared to Agatston score (AS) on electrocardiogram (ECG)-gated calcium scoring CT. We studied 576 patients who were consecutively registered for health screening and undergoing both LDCT and ECG-gated calcium scoring CT. We excluded subjects with an AS of zero. The final study cohort included 117 patients with CAC (97 men; mean age, 53.4 ± 8.5). AS was used as the gold standard (mean score 166.0; range 0.4-3,719.3). Two board-certified radiologists and two radiology residents participated in an observer performance study. Visual ranking of CAC was performed according to four categories (1-10, 11-100, 101-400, and 401 or higher) for coronary artery disease risk stratification. Weighted kappa statistics were used to measure the degree of reliability on visual ranking of CAC on LDCT. The degree of reliability on visual ranking of CAC on LDCT compared to ECG-gated calcium scoring CT was excellent for board-certified radiologists and good for radiology residents. A high degree of association was observed with 71.6% of visual rankings in the same category as the Agatston category and 98.9% varying by no more than one category. Visual ranking of positive CAC on LDCT is reliable for predicting AS rank categorization.

Ranking of biomass pellets by integration of economic, environmental and technical factors

International Nuclear Information System (INIS)

Sultana, Arifa; Kumar, Amit

2012-01-01

Interest in biomass as a renewable energy source has increased recently in response to a need to reduce greenhouse gas (GHG) emissions. The objective of this study is to develop a multi-criteria assessment model and rank different biomass feedstock-based pellets, in terms of their suitability for use in large heat and power generation plants and show the importance of environmental, economical and technical factors in making decision about different pellets. Five pellet alternatives, each produced from a different sustainable biomass feedstock i.e., wood, straw, switchgrass, alfalfa and poultry litter, are ranked according to eleven criteria, using the Preference Ranking Organization Method for Enrichment and Evaluation (PROMETHEE). Both quantitative and qualitative criteria are considered, including environmental, technical and economic factors. Three scenarios, namely base case, environmental and economic, are developed by changing the weight assigned to different criteria. In the base case scenario, equal weights are assigned to each criterion. In the economic and environmental scenarios, more weight is given to the economic and environmental factors, respectively. Based on the PROMETHEE rankings, wood pellets are the best source of energy for all scenarios followed by switchgrass, straw, poultry litter and alfalfa pellets except economic scenario, where straw pellets held higher position than switchgrass pellets. Sensitivity analysis on weights, threshold values, preference function and production cost indicate that the ranking was stable. The ranking in all scenarios remained same when qualitative criteria were omitted from the model; this indicates the stronger influence of quantitative criteria. -- Highlights: ► This study ranks the pellets produced from different biomass feedstocks. ► The ranking of the pellets is based on technical, economical and environmental factors. ► This study uses PROMETHEE method for ranking pellets based on a range of

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

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

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.

A study on ranking ethical factors influencing customer loyalty

Directory of Open Access Journals (Sweden)

Mahmood Modiri

2013-10-01

Full Text Available Having loyal customer is the primary objective of any business owner since loyal customers purchase on regular basis, create sustainable growth and reduce risk of bankruptcy. During the past few years, many people argue that customer loyalty must be established through ethical values. In this paper, we present an empirical investigation to detect ethical factors influencing customer loyalty. The proposed study determines five criteria including customer repurchase, interest in brand, recommending brand to others, positive attitude toward brand and cognitive loyalty to brand. These criteria have been ranked using fuzzy analytical network process. The study determines 14 different ethical values, which may play essential role on customer loyalty and using VIKOR, different ethical values are ranked. The study indicates that welcoming customers is the most important factor followed by cheerfulness, on time delivery, being informative and having appropriate standards.

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.

Low-rank coal study : national needs for resource development. Volume 2. Resource characterization

Energy Technology Data Exchange (ETDEWEB)

1980-11-01

Comprehensive data are presented on the quantity, quality, and distribution of low-rank coal (subbituminous and lignite) deposits in the United States. The major lignite-bearing areas are the Fort Union Region and the Gulf Lignite Region, with the predominant strippable reserves being in the states of North Dakota, Montana, and Texas. The largest subbituminous coal deposits are in the Powder River Region of Montana and Wyoming, The San Juan Basin of New Mexico, and in Northern Alaska. For each of the low-rank coal-bearing regions, descriptions are provided of the geology; strippable reserves; active and planned mines; classification of identified resources by depth, seam thickness, sulfur content, and ash content; overburden characteristics; aquifers; and coal properties and characteristics. Low-rank coals are distinguished from bituminous coals by unique chemical and physical properties that affect their behavior in extraction, utilization, or conversion processes. The most characteristic properties of the organic fraction of low-rank coals are the high inherent moisture and oxygen contents, and the correspondingly low heating value. Mineral matter (ash) contents and compositions of all coals are highly variable; however, low-rank coals tend to have a higher proportion of the alkali components CaO, MgO, and Na/sub 2/O. About 90% of the reserve base of US low-rank coal has less than one percent sulfur. Water resources in the major low-rank coal-bearing regions tend to have highly seasonal availabilities. Some areas appear to have ample water resources to support major new coal projects; in other areas such as Texas, water supplies may be constraining factor on development.

Charting taxonomic knowledge through ontologies and ranking algorithms

Science.gov (United States)

Huber, Robert; Klump, Jens

2009-04-01

Since the inception of geology as a modern science, paleontologists have described a large number of fossil species. This makes fossilized organisms an important tool in the study of stratigraphy and past environments. Since taxonomic classifications of organisms, and thereby their names, change frequently, the correct application of this tool requires taxonomic expertise in finding correct synonyms for a given species name. Much of this taxonomic information has already been published in journals and books where it is compiled in carefully prepared synonymy lists. Because this information is scattered throughout the paleontological literature, it is difficult to find and sometimes not accessible. Also, taxonomic information in the literature is often difficult to interpret for non-taxonomists looking for taxonomic synonymies as part of their research. The highly formalized structure makes Open Nomenclature synonymy lists ideally suited for computer aided identification of taxonomic synonyms. Because a synonymy list is a list of citations related to a taxon name, its bibliographic nature allows the application of bibliometric techniques to calculate the impact of synonymies and taxonomic concepts. TaxonRank is a ranking algorithm based on bibliometric analysis and Internet page ranking algorithms. TaxonRank uses published synonymy list data stored in TaxonConcept, a taxonomic information system. The basic ranking algorithm has been modified to include a measure of confidence on species identification based on the Open Nomenclature notation used in synonymy list, as well as other synonymy specific criteria. The results of our experiments show that the output of the proposed ranking algorithm gives a good estimate of the impact a published taxonomic concept has on the taxonomic opinions in the geological community. Also, our results show that treating taxonomic synonymies as part of on an ontology is a way to record and manage taxonomic knowledge, and thus contribute

Ranking Practice Variability in the Medical Student Performance Evaluation: So Bad, It's "Good".

Science.gov (United States)

Boysen Osborn, Megan; Mattson, James; Yanuck, Justin; Anderson, Craig; Tekian, Ara; Fox, John Christian; Harris, Ilene B

2016-11-01

To examine the variability among medical schools in ranking systems used in medical student performance evaluations (MSPEs). The authors reviewed MSPEs from U.S. MD-granting medical schools received by the University of California, Irvine emergency medicine and internal medicine residency programs during 2012-2013 and 2014-2015. They recorded whether the school used a ranking system, the type of ranking system used, the size and description of student categories, the location of the ranking statement and category legend, and whether nonranking schools used language suggestive of rank. Of the 134 medical schools in the study sample, the majority (n = 101; 75%) provided ranks for students in the MSPE. Most of the ranking schools (n = 63; 62%) placed students into named category groups, but the number and size of groups varied. The most common descriptors used for these 63 schools' top, second, third, and lowest groups were "outstanding," "excellent," "very good," and "good," respectively, but each of these terms was used across a broad range of percentile ranks. Student ranks and school category legends were found in various locations. Many of the 33 schools that did not rank students included language suggestive of rank. There is extensive variation in ranking systems used in MSPEs. Program directors may find it difficult to use MSPEs to compare applicants, which may diminish the MSPE's value in the residency application process and negatively affect high-achieving students. A consistent approach to ranking students would benefit program directors, students, and student affairs officers.

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

Science.gov (United States)

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

2016-07-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2016-07-01

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

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

International Nuclear Information System (INIS)

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

2016-01-01

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

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.

Research on B Cell Algorithm for Learning to Rank Method Based on Parallel Strategy.

Science.gov (United States)

Tian, Yuling; Zhang, Hongxian

2016-01-01

For the purposes of information retrieval, users must find highly relevant documents from within a system (and often a quite large one comprised of many individual documents) based on input query. Ranking the documents according to their relevance within the system to meet user needs is a challenging endeavor, and a hot research topic-there already exist several rank-learning methods based on machine learning techniques which can generate ranking functions automatically. This paper proposes a parallel B cell algorithm, RankBCA, for rank learning which utilizes a clonal selection mechanism based on biological immunity. The novel algorithm is compared with traditional rank-learning algorithms through experimentation and shown to outperform the others in respect to accuracy, learning time, and convergence rate; taken together, the experimental results show that the proposed algorithm indeed effectively and rapidly identifies optimal ranking functions.

Theory of Bessel Functions of High Rank - I: Fundamental Bessel Functions

OpenAIRE

Qi, Zhi

2014-01-01

In this article we introduce a new category of special functions called fundamental Bessel functions arising from the Voronoi summation formula for $\\mathrm{GL}_n (\\mathbb{R})$. The fundamental Bessel functions of rank one and two are the oscillatory exponential functions $e^{\\pm i x}$ and the classical Bessel functions respectively. The main implements and subjects of our study of fundamental Bessel functions are their formal integral representations and Bessel equations.

A Comparison of Three Major Academic Rankings for World Universities: From a Research Evaluation Perspective

Directory of Open Access Journals (Sweden)

Mu-hsuan Huang

2011-06-01

Full Text Available This paper introduces three current major university ranking systems. The Performance Ranking of Scientific Papers for World Universities by Higher Education Evaluation and Accreditation Council of Taiwan (HEEACT Ranking emphasizes both the quality and quantity of research and current research performance. The Academic Ranking of World Universities by Shanghai Jiao Tung University (ARWU focuses on outstanding performance of universities with indicators such as Nobel Prize winners. The QS World University Ranking (2004-2009 by Times Higher Education (THE-QS emphasizes on peer review with high weighting in evaluation. This paper compares the 2009 ranking results from the three ranking systems. Differences exist in the top 20 universities in three ranking systems except the Harvard University, which scored top one in all of the three rankings. Comparisons also revealed that the THE-QS favored UK universities. Further, obvious differences can be observed between THE-QS and the other two rankings when ranking results of some European countries (Germany, UK, Netherlands, & Switzerland and Chinese speaking regions were compared.

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

International Nuclear Information System (INIS)

Li Bo; Kwek, Leong Chuan; Fan Heng

2012-01-01

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

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.

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.

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

Rationality alters the rank between peer punishment and social exclusion

Science.gov (United States)

Sui, Xiukai; Wu, Bin; Wang, Long

2018-02-01

Peer punishment and social exclusion are two ways to punish free-riders. Previous work usually focuses on how their presence, either peer punishment or social exclusion, shapes the evolution of cooperation. Little attention has been given to which of these two strategies is favored by natural selection when they are both present. Here we investigate how rationality alters the ranking of these two strategies. Under weak rationality, for compulsory public goods games, peer punishment has an evolutionary advantage over social exclusion if the efficiency of punishment or the cost of exclusion is high. Furthermore, this rank is preserved for voluntary public goods games where loners are involved. Under strong rationality, however, peer punishment cannot prevail over social exclusion for both compulsory and voluntary public goods games. This indicates that rationality greatly alters the rank between peer punishment and social exclusion. Moreover, we find that this ranking is sensitive to the rationality. Our work thus gives an insight into how different types of punishment evolve.

Leveraging Multiactions to Improve Medical Personalized Ranking for Collaborative Filtering

Directory of Open Access Journals (Sweden)

Shan Gao

2017-01-01

Full Text Available Nowadays, providing high-quality recommendation services to users is an essential component in web applications, including shopping, making friends, and healthcare. This can be regarded either as a problem of estimating users’ preference by exploiting explicit feedbacks (numerical ratings, or as a problem of collaborative ranking with implicit feedback (e.g., purchases, views, and clicks. Previous works for solving this issue include pointwise regression methods and pairwise ranking methods. The emerging healthcare websites and online medical databases impose a new challenge for medical service recommendation. In this paper, we develop a model, MBPR (Medical Bayesian Personalized Ranking over multiple users’ actions, based on the simple observation that users tend to assign higher ranks to some kind of healthcare services that are meanwhile preferred in users’ other actions. Experimental results on the real-world datasets demonstrate that MBPR achieves more accurate recommendations than several state-of-the-art methods and shows its generality and scalability via experiments on the datasets from one mobile shopping app.

Leveraging Multiactions to Improve Medical Personalized Ranking for Collaborative Filtering.

Science.gov (United States)

Gao, Shan; Guo, Guibing; Li, Runzhi; Wang, Zongmin

2017-01-01

Nowadays, providing high-quality recommendation services to users is an essential component in web applications, including shopping, making friends, and healthcare. This can be regarded either as a problem of estimating users' preference by exploiting explicit feedbacks (numerical ratings), or as a problem of collaborative ranking with implicit feedback (e.g., purchases, views, and clicks). Previous works for solving this issue include pointwise regression methods and pairwise ranking methods. The emerging healthcare websites and online medical databases impose a new challenge for medical service recommendation. In this paper, we develop a model, MBPR (Medical Bayesian Personalized Ranking over multiple users' actions), based on the simple observation that users tend to assign higher ranks to some kind of healthcare services that are meanwhile preferred in users' other actions. Experimental results on the real-world datasets demonstrate that MBPR achieves more accurate recommendations than several state-of-the-art methods and shows its generality and scalability via experiments on the datasets from one mobile shopping app.

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

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

Global sensitivity analysis using low-rank tensor approximations

International Nuclear Information System (INIS)

Konakli, Katerina; Sudret, Bruno

2016-01-01

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

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.

The highest-ranking rooster has priority to announce the break of dawn.

Science.gov (United States)

Shimmura, Tsuyoshi; Ohashi, Shosei; Yoshimura, Takashi

2015-07-23

The "cock-a-doodle-doo" crowing of roosters, which symbolizes the break of dawn in many cultures, is controlled by the circadian clock. When one rooster announces the break of dawn, others in the vicinity immediately follow. Chickens are highly social animals, and they develop a linear and fixed hierarchy in small groups. We found that when chickens were housed in small groups, the top-ranking rooster determined the timing of predawn crowing. Specifically, the top-ranking rooster always started to crow first, followed by its subordinates, in descending order of social rank. When the top-ranking rooster was physically removed from a group, the second-ranking rooster initiated crowing. The presence of a dominant rooster significantly reduced the number of predawn crows in subordinates. However, the number of crows induced by external stimuli was independent of social rank, confirming that subordinates have the ability to crow. Although the timing of subordinates' predawn crowing was strongly dependent on that of the top-ranking rooster, free-running periods of body temperature rhythms differed among individuals, and crowing rhythm did not entrain to a crowing sound stimulus. These results indicate that in a group situation, the top-ranking rooster has priority to announce the break of dawn, and that subordinate roosters are patient enough to wait for the top-ranking rooster's first crow every morning and thus compromise their circadian clock for social reasons.

Website visibility the theory and practice of improving rankings

CERN Document Server

Weideman, Melius

2009-01-01

The quest to achieve high website rankings in search engine results is a prominent subject for both academics and website owners/coders. Website Visibility marries academic research results to the world of the information practitioner and contains a focused look at the elements which contribute to website visibility, providing support for the application of each element with relevant research. A series of real-world case studies with tested examples of research on website visibility elements and their effect on rankings are reviewed.Written by a well-respected academic and practitioner in the

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.

Next Generation Nuclear Plant Phenomena Identification and Ranking Tables (PIRTs) Volume 5: Graphite PIRTs

International Nuclear Information System (INIS)

Burchell, Timothy D.; Bratton, Rob; Marsden, Barry; Srinivasan, Makuteswara; Penfield, Scott; Mitchell, Mark; Windes, Will

2008-01-01

Here we report the outcome of the application of the Nuclear Regulatory Commission (NRC) Phenomena Identification and Ranking Table (PIRT) process to the issue of nuclear-grade graphite for the moderator and structural components of a next generation nuclear plant (NGNP), considering both routine (normal operation) and postulated accident conditions for the NGNP. The NGNP is assumed to be a modular high-temperature gas-cooled reactor (HTGR), either a gas-turbine modular helium reactor (GTMHR) version (a prismatic-core modular reactor (PMR)] or a pebble-bed modular reactor (PBMR) version (a pebble bed reactor (PBR)] design, with either a direct- or indirect-cycle gas turbine (Brayton cycle) system for electric power production, and an indirect-cycle component for hydrogen production. NGNP design options with a high-pressure steam generator (Rankine cycle) in the primary loop are not considered in this PIRT. This graphite PIRT was conducted in parallel with four other NRC PIRT activities, taking advantage of the relationships and overlaps in subject matter. The graphite PIRT panel identified numerous phenomena, five of which were ranked high importance-low knowledge. A further nine were ranked with high importance and medium knowledge rank. Two phenomena were ranked with medium importance and low knowledge, and a further 14 were ranked medium importance and medium knowledge rank. The last 12 phenomena were ranked with low importance and high knowledge rank (or similar combinations suggesting they have low priority). The ranking/scoring rationale for the reported graphite phenomena is discussed. Much has been learned about the behavior of graphite in reactor environments in the 60-plus years since the first graphite rectors went into service. The extensive list of references in the Bibliography is plainly testament to this fact. Our current knowledge base is well developed. Although data are lacking for the specific grades being considered for Generation IV (Gen IV

Effects of microwave irradiation treatment on physicochemical characteristics of Chinese low-rank coals

International Nuclear Information System (INIS)

Ge, Lichao; Zhang, Yanwei; Wang, Zhihua; Zhou, Junhu; Cen, Kefa

2013-01-01

Highlights: • Typical Chinese lignites with various ranks are upgraded through microwave. • The pore distribution extends to micropore region, BET area and volume increase. • FTIR show the change of microstructure and improvement in coal rank after upgrading. • Upgraded coals exhibit weak combustion similar to Da Tong bituminous coal. • More evident effects are obtained for raw brown coal with relative lower rank. - Abstract: This study investigates the effects of microwave irradiation treatment on coal composition, pore structure, coal rank, function groups, and combustion characteristics of typical Chinese low-rank coals. Results showed that the upgrading process (microwave irradiation treatment) significantly reduced the coals’ inherent moisture, and increased their calorific value and fixed carbon content. It was also found that the upgrading process generated micropores and increased pore volume and surface area of the coals. Results on the oxygen/carbon ratio parameter indicated that the low-rank coals were upgraded to high-rank coals after the upgrading process, which is in agreement with the findings from Fourier transform infrared spectroscopy. Unstable components in the coal were converted into stable components during the upgrading process. Thermo-gravimetric analysis showed that the combustion processes of upgraded coals were delayed toward the high-temperature region, the ignition and burnout temperatures increased, and the comprehensive combustion parameter decreased. Compared with raw brown coals, the upgraded coals exhibited weak combustion characteristics similar to bituminous coal. The changes in physicochemical characteristics became more notable when processing temperature increased from 130 °C to 160 °C or the rank of raw brown coal was lower. Microwave irradiation treatment could be considered as an effective dewatering and upgrading process

Pacing Behavior and Tactical Positioning in 500- and 1000-m Short-Track Speed Skating.

Science.gov (United States)

Noorbergen, Olaf S; Konings, Marco J; Micklewright, Dominic; Elferink-Gemser, Marije T; Hettinga, Florentina J

2016-09-01

To explore pacing behavior and tactical positioning during the shorter 500- and 1000-m short-track competitions. Lap times and intermediate rankings of elite 500- and 1000-m short-track-skating competitors were collected over the 2012-13 season. First, lap times were analyzed using a MANOVA, and for each lap, differences between sex, race type, final ranking, and stage of competition were determined. Second, Kendall tau-b correlations were used to assess relationships between intermediate and final rankings. In addition, intermediate rankings of the winner of each race were examined. Top-placed athletes appeared faster than bottom-placed athletes in every lap in the 500-m, while in the 1000-m no differences were found until the final 4 laps (P < .05). Correlations between intermediate and final rankings were already high at the beginning stages of the 50-m (lap 1: r = .59) but not for the 1000-m (lap 1: r = .21). Although 500- and 1000-m short-track races are both relatively short, fundamental differences in pacing behavior and tactical positioning were found. A fast-start strategy seems to be optimal for 500-m races, while the crucial segment in 1000-m races seems to be from the 6th lap to the finish line (ie, after ± 650 m). These findings provide evidence to suggest that athletes balance between choosing an energetically optimal profile and the tactical and positional benefits that play a role when riding against an opponent, as well as contributing to developing novel insights in exploring athletic behavior when racing against opponents.

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.

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....

Synfuels from low-rank coals at the Great Plains Gasification Plant

International Nuclear Information System (INIS)

Pollock, D.

1992-01-01

This presentation focuses on the use of low rank coals to form synfuels. A worldwide abundance of low rank coals exists. Large deposits in the United States are located in Texas and North Dakota. Low rank coal deposits are also found in Europe, India and Australia. Because of the high moisture content of lignite ranging from 30% to 60% or higher, it is usually utilized in mine mouth applications. Lignite is generally very reactive and contains varying amounts of ash and sulfur. Typical uses for lignite are listed. A commercial application using lignite as feedstock to a synfuels plant, Dakota Gasification Company's Great Plains Gasification Plant, is discussed

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...

RANKL/RANK: from bone loss to the prevention of breast cancer.

Science.gov (United States)

Sigl, Verena; Jones, Laundette P; Penninger, Josef M

2016-11-01

RANK and RANKL, a receptor ligand pair belonging to the tumour necrosis factor family, are the critical regulators of osteoclast development and bone metabolism. Besides their essential function in bone, RANK and RANKL have also been identified as the key factors for the formation of a lactating mammary gland in pregnancy. Mechanistically, RANK and RANKL link the sex hormone progesterone with stem cell expansion and proliferation of mammary epithelial cells. Based on their normal physiology, RANKL/RANK control the onset of hormone-induced breast cancer through the expansion of mammary progenitor cells. Recently, we and others were able to show that RANK and RANKL are also critical regulators of BRCA1-mutation-driven breast cancer. Currently, the preventive strategy for BRCA1-mutation carriers includes preventive mastectomy, associated with wide-ranging risks and psychosocial effects. The search for an alternative non-invasive prevention strategy is therefore of paramount importance. As our work strongly implicates RANK and RANKL as key molecules involved in the initiation of BRCA1-associated breast cancer, we propose that anti-RANKL therapy could be a feasible preventive strategy for women carrying BRCA1 mutations, and by extension to other women with high risk of breast cancer. © 2016 The Authors.

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.

Relationship between Particle Size Distribution of Low-Rank Pulverized Coal and Power Plant Performance

Directory of Open Access Journals (Sweden)

Rajive Ganguli

2012-01-01

Full Text Available The impact of particle size distribution (PSD of pulverized, low rank high volatile content Alaska coal on combustion related power plant performance was studied in a series of field scale tests. Performance was gauged through efficiency (ratio of megawatt generated to energy consumed as coal, emissions (SO2, NOx, CO, and carbon content of ash (fly ash and bottom ash. The study revealed that the tested coal could be burned at a grind as coarse as 50% passing 76 microns, with no deleterious impact on power generation and emissions. The PSD’s tested in this study were in the range of 41 to 81 percent passing 76 microns. There was negligible correlation between PSD and the followings factors: efficiency, SO2, NOx, and CO. Additionally, two tests where stack mercury (Hg data was collected, did not demonstrate any real difference in Hg emissions with PSD. The results from the field tests positively impacts pulverized coal power plants that burn low rank high volatile content coals (such as Powder River Basin coal. These plants can potentially reduce in-plant load by grinding the coal less (without impacting plant performance on emissions and efficiency and thereby, increasing their marketability.

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

Directory of Open Access Journals (Sweden)

Cleston Alexandre dos Santos

2017-02-01

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

Closing the Gender Gap in Leadership Positions: Can Expanding the Pipeline Increase Parity?

OpenAIRE

Brown, Ryan; Mansour, Hani; O'Connell, Stephen D.

2018-01-01

Gender gaps in leadership roles may be reduced by increasing the number of women in career stages that typically precede high-status positions. This can occur by increasing the supply of experienced women, inspiring new female candidates for these positions, and/or changing beliefs about women as leaders. In this study, we investigate whether and how adding women to a career pipeline can reduce gender gaps in higher-ranking positions over time. Specifically, we examine the effects of women's ...

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).

Influence of the hydrothermal dewatering on the combustion characteristics of Chinese low-rank coals

International Nuclear Information System (INIS)

Ge, Lichao; Zhang, Yanwei; Xu, Chang; Wang, Zhihua; Zhou, Junhu; Cen, Kefa

2015-01-01

This study investigates the influence of hydrothermal dewatering performed at different temperatures on the combustion characteristics of Chinese low-rank coals with different coalification maturities. It was found that the upgrading process significantly decreased the inherent moisture and oxygen content, increased the calorific value and fixed carbon content, and promoted the damage of the hydrophilic oxygen functional groups. The results of oxygen/carbon atomic ratio indicated that the upgrading process converted the low-rank coals near to high-rank coals which can also be gained using the Fourier transform infrared spectroscopy. The thermogravimetric analysis showed that the combustion processes of upgraded coals were delayed toward the high temperature region, and the upgraded coals had higher ignition and burnout temperature. On the other hand, based on the higher average combustion rate and comprehensive combustion parameter, the upgraded coals performed better compared with raw brown coals and the Da Tong bituminous coal. In ignition segment, the activation energy increased after treatment but decreased in the combustion stage. The changes in coal compositions, microstructure, rank, and combustion characteristics were more notable as the temperature in hydrothermal dewatering increased from 250 to 300 °C or coals of lower ranks were used. - Highlights: • Typical Chinese lignites with various ranks are upgraded by hydrothermal dewatering. • Upgraded coals exhibit chemical compositions comparable with that of bituminous coal. • FTIR show the change of microstructure and improvement in coal rank after upgrading. • Upgraded coals exhibit difficulty in ignition but combust easily. • More evident effects are obtained for raw brown coal with relative lower rank.

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

Cross-cultural differences in processing of architectural ranking: evidence from an event-related potential study.

Science.gov (United States)

Mecklinger, Axel; Kriukova, Olga; Mühlmann, Heiner; Grunwald, Thomas

2014-01-01

Visual object identification is modulated by perceptual experience. In a cross-cultural ERP study we investigated whether cultural expertise determines how buildings that vary in their ranking between high and low according to the Western architectural decorum are perceived. Two groups of German and Chinese participants performed an object classification task in which high- and low-ranking Western buildings had to be discriminated from everyday life objects. ERP results indicate that an early stage of visual object identification (i.e., object model selection) is facilitated for high-ranking buildings for the German participants, only. At a later stage of object identification, in which object knowledge is complemented by information from semantic and episodic long-term memory, no ERP evidence for cultural differences was obtained. These results suggest that the identification of architectural ranking is modulated by culturally specific expertise with Western-style architecture already at an early processing stage.

The BACON Approach for Rank-Deficient Data

Directory of Open Access Journals (Sweden)

Athanassios Kondylis

2012-07-01

Full Text Available Normal 0 false false false EN-US X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Times New Roman","serif";} Rank-deficient data are not uncommon in practice. They result from highly collinear variables and/or high-dimensional data. A special case of the latter occurs when the number of recorded variables exceeds the number of observations. The use of the BACON algorithm for outlier detection in multivariate data is extended here to include rank-deficient data. We present two approaches to identifying outliers in rank-deficient data based on the original BACON algorithm. The first algorithm projects the data onto a robust subspace of reduced dimension, while the second employs a ridge type regularization on the covariance matrix. Both algorithms are tested on real as well as simulated data sets with good results in terms of their effectiveness in outlier detection. They are also examined in terms of computational efficiency and found to be very fast, with particularly good scaling properties for increasing dimension.

A Ranking Method for Neutral Pion and Eta Selection in Hadronic Events

International Nuclear Information System (INIS)

Bingoel, A.

2004-01-01

The selection of neutral pions and etas with a high purity while maintaining also a high efficiency can be important in the formation of statistically significant mass spectra in the reconstruction of short-lived particles such as the omega meson (ω→π + + π - + π 0 ). In this study a Ranking method has been optimized for data from the ALEPH Experiment, CERN. The results show that the Ranking method, when applied to high multiplicity events, yields significant improvements in the purity of selected pion candidates and facilitates the relaxation of standard cuts thereby avoiding some systematic uncertainties

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

Customer Ranking Model for Project Businesses: A Case Study from the Automotive Industry

Directory of Open Access Journals (Sweden)

Bernd Markus Zunk

2014-03-01

Full Text Available For technology-orientated enterprises that operate project-based businesses, the goal-oriented allocation of scarce marketing resources has great potential to help consolidate their competitive position. An important precondition for goal-oriented management is the identification of the most valuable customers. This enables technology-orientated enterprises to segment markets in order to make tactical marketing decisions. This theorybased paper aims to develop and test a holistic customer ranking model. By deploying the five steps presented in this paper, customer relationship managers are better able to identify and to rank their customers in project-based businesses. A case study provides an example of the application of the method from the automotive industry in Austria. The experiences derived from this case study show that using a customer ranking framework is a crucial factor for enterprises in narrow technology markets to be successful and to achieve their corporate goals.

Ranking the adaptive capacity of nations to climate change when socio-political goals are explicit

International Nuclear Information System (INIS)

Haddad, B.M.

2005-01-01

The typical categories for measuring national adaptive capacity to climate change include a nation's wealth, technology, education, information, skills, infrastructure, access to resources, and management capabilities. Resulting rankings predictably mirror more general rankings of economic development, such as the Human Development Index. This approach is incomplete since it does not consider the normative or motivational context of adaptation. For what purpose or toward what goal does a nation aspire, and in that context, what is its adaptive capacity? This paper posits 11 possible national socio-political goals that fall into the three categories of teleological legitimacy, procedural legitimacy, and norm-based decision rules. A model that sorts nations in terms of adaptive capacity based on national socio-political aspirations is presented. While the aspiration of maximizing summed utility matches typical existing rankings, alternative aspirations, including contractarian liberalism, technocratic management, and dictatorial/religious rule alter the rankings. An example describes how this research can potentially inform how priorities are set for international assistance for climate change adaptation. (author)

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.

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....

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…

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.

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.

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...

Creation or destruction of the perspective of EVA® value in the Exame Magazine ranking of largest companies

Directory of Open Access Journals (Sweden)

Anelise Florencio de Meneses

2012-12-01

association between the companies that create value (EVA® with the Brazilian regions and sectors. It was found that 217 companies have created value while 99 destroyed value. Test results showed that the Midwest and the wholesale and retail sectors are associated with a high value creation, not confirming the first and second research hypotheses. The results also indicated that only 5 companies remained in the same positions when comparing the ranking of the magazine Exame with that prepared by EVA® perspective, not confirming the third research hypothesis.

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.

Accelerated cardiac cine MRI using locally low rank and finite difference constraints.

Science.gov (United States)

Miao, Xin; Lingala, Sajan Goud; Guo, Yi; Jao, Terrence; Usman, Muhammad; Prieto, Claudia; Nayak, Krishna S

2016-07-01

To evaluate the potential value of combining multiple constraints for highly accelerated cardiac cine MRI. A locally low rank (LLR) constraint and a temporal finite difference (FD) constraint were combined to reconstruct cardiac cine data from highly undersampled measurements. Retrospectively undersampled 2D Cartesian reconstructions were quantitatively evaluated against fully-sampled data using normalized root mean square error, structural similarity index (SSIM) and high frequency error norm (HFEN). This method was also applied to 2D golden-angle radial real-time imaging to facilitate single breath-hold whole-heart cine (12 short-axis slices, 9-13s single breath hold). Reconstruction was compared against state-of-the-art constrained reconstruction methods: LLR, FD, and k-t SLR. At 10 to 60 spokes/frame, LLR+FD better preserved fine structures and depicted myocardial motion with reduced spatio-temporal blurring in comparison to existing methods. LLR yielded higher SSIM ranking than FD; FD had higher HFEN ranking than LLR. LLR+FD combined the complimentary advantages of the two, and ranked the highest in all metrics for all retrospective undersampled cases. Single breath-hold multi-slice cardiac cine with prospective undersampling was enabled with in-plane spatio-temporal resolutions of 2×2mm(2) and 40ms. Highly accelerated cardiac cine is enabled by the combination of 2D undersampling and the synergistic use of LLR and FD constraints. Copyright © 2016 Elsevier Inc. All rights reserved.

A welfare ranking of multilateral reductions in real and tariff trade barriers when firms are heterogenous

DEFF Research Database (Denmark)

Schröder, Philipp; Sørensen, Allan

2014-01-01

heterogeneous-firms-trade model with Pareto distributed productivities. We derive analytical welfare rankings of all four liberalization channels for an equal effect on two openness measures, for any trade cost level and while all four barriers are simultaneously present, i.e. for any initial equilibrium. We...... to the most preferred mode of liberalization. Among the other three barriers we etablished a universal welfare ranking for any strictly positive level of revenue redistribution and for either measure of openness....

INTEL: Intel based systems move up in supercomputing ranks

CERN Multimedia

2002-01-01

"The TOP500 supercomputer rankings released today at the Supercomputing 2002 conference show a dramatic increase in the number of Intel-based systems being deployed in high-performance computing (HPC) or supercomputing areas" (1/2 page).

Batched Tile Low-Rank GEMM on GPUs

KAUST Repository

Charara, Ali

2018-02-01

Dense General Matrix-Matrix (GEMM) multiplication is a core operation of the Basic Linear Algebra Subroutines (BLAS) library, and therefore, often resides at the bottom of the traditional software stack for most of the scientific applications. In fact, chip manufacturers give a special attention to the GEMM kernel implementation since this is exactly where most of the high-performance software libraries extract the hardware performance. With the emergence of big data applications involving large data-sparse, hierarchically low-rank matrices, the off-diagonal tiles can be compressed to reduce the algorithmic complexity and the memory footprint. The resulting tile low-rank (TLR) data format is composed of small data structures, which retains the most significant information for each tile. However, to operate on low-rank tiles, a new GEMM operation and its corresponding API have to be designed on GPUs so that it can exploit the data sparsity structure of the matrix while leveraging the underlying TLR compression format. The main idea consists in aggregating all operations onto a single kernel launch to compensate for their low arithmetic intensities and to mitigate the data transfer overhead on GPUs. The new TLR GEMM kernel outperforms the cuBLAS dense batched GEMM by more than an order of magnitude and creates new opportunities for TLR advance algorithms.

Positive Correlation Between Academic Library Services and High-Impact Practices for

Directory of Open Access Journals (Sweden)

Saori Wendy Herman, MLIS, AHIP

2016-03-01

Full Text Available Objective – To investigate the perceived alignment between academic library services and high-impact practices (HIPs that affect student retention. Design – Survey questionnaire. Setting – Public comprehensive universities in the United States of America with a Carnegie classification of master’s level as of January 2013. Subjects – 68 library deans or directors out of the 271 who were originally contacted. Methods – The author used Qualtrics software to create a survey based on the HIPs, tested the survey for reliability, and then distributed it to 271 universities. Library services were grouped into 1 of 3 library scales: library collection, library instruction, or library facilities. The survey consisted of a matrix of 10 Likert-style questions addressing the perceived level of alignment between the library scales and the HIPs. Each question provided an opportunity for the respondent to enter a “brief description of support practices” (p 477. Additional demographic questions addressed the years of experience of the respondent, undergraduate student enrollment of the university, and whether librarians held faculty rank. Main Results – The author measured Pearson correlation coefficients and found a positive correlation between the library scales and the HIPs. All three library scales displayed a moderately strong positive correlation between first-year seminars and experiences (HIP 1, common intellectual experiences (HIP 2, writing-intensive courses (HIP 4, undergraduate research (HIP 6, diversity and global learning (HIP 7, service learning and community-based learning (HIP 8, internships (HIP 9, and capstone courses and projects (HIP 10. The library collections scale and library facilities scale displayed a moderately strong correlation with learning communities (HIP 3 and collaborative assignments and projects (HIP 5. The library instruction scale displayed a strong positive correlation with HIP 3 and a very strong

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.

You Cannot Judge a Book by Its Cover: The Problems with Journal Rankings

Science.gov (United States)

Sangster, Alan

2015-01-01

Journal rankings lists have impacted and are impacting accounting educators and accounting education researchers around the world. Nowhere is the impact positive. It ranges from slight constraints on academic freedom to admonition, censure, reduced research allowances, non-promotion, non-short-listing for jobs, increased teaching loads, and…

Social Feedback and the Emergence of Rank in Animal Society.

Science.gov (United States)

Hobson, Elizabeth A; DeDeo, Simon

2015-09-01

Dominance hierarchies are group-level properties that emerge from the aggression of individuals. Although individuals can gain critical benefits from their position in a hierarchy, we do not understand how real-world hierarchies form. Nor do we understand what signals and decision-rules individuals use to construct and maintain hierarchies in the absence of simple cues such as size or spatial location. A study of conflict in two groups of captive monk parakeets (Myiopsitta monachus) found that a transition to large-scale order in aggression occurred in newly-formed groups after one week, with individuals thereafter preferring to direct aggression more frequently against those nearby in rank. We consider two cognitive mechanisms underlying the emergence of this order: inference based on overall levels of aggression, or on subsets of the aggression network. Both mechanisms were predictive of individual decisions to aggress, but observed patterns were better explained by rank inference through subsets of the aggression network. Based on these results, we present a new theory, of a feedback loop between knowledge of rank and consequent behavior. This loop explains the transition to strategic aggression and the formation and persistence of dominance hierarchies in groups capable of both social memory and inference.

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).

Ranking Features on Psychological Dynamics of Cooperative Team Work through Bayesian Networks

Directory of Open Access Journals (Sweden)

Pilar Fuster-Parra

2016-05-01

Full Text Available The aim of this study is to rank some features that characterize the psychological dynamics of cooperative team work in order to determine priorities for interventions and formation: leading positive feedback, cooperative manager and collaborative manager features. From a dataset of 20 cooperative sport teams (403 soccer players, the characteristics of the prototypical sports teams are studied using an average Bayesian network (BN and two special types of BNs, the Bayesian classifiers: naive Bayes (NB and tree augmented naive Bayes (TAN. BNs are selected as they are able to produce probability estimates rather than predictions. BN results show that the antecessors (the “top” features ranked are the team members’ expectations and their attraction to the social aspects of the task. The main node is formed by the cooperative behaviors, the consequences ranked at the BN bottom (ratified by the TAN trees and the instantiations made, the roles assigned to the members and their survival inside the same team. These results should help managers to determine contents and priorities when they have to face team-building actions.

Next Generation Nuclear Plant Phenomena Identification and Ranking Tables (PIRTs) Volume 4: High-Temperature Materials PIRTs

Energy Technology Data Exchange (ETDEWEB)

Corwin, William R [ORNL; Ballinger, R. [Massachusetts Institute of Technology (MIT); Majumdar, S. [Argonne National Laboratory (ANL); Weaver, K. D. [Idaho National Laboratory (INL)

2008-03-01

The Phenomena Identification and Ranking Table (PIRT) technique was used to identify safety-relevant/safety-significant phenomena and assess the importance and related knowledge base of high-temperature structural materials issues for the Next Generation Nuclear Plant (NGNP), a very high temperature gas-cooled reactor (VHTR). The major aspects of materials degradation phenomena that may give rise to regulatory safety concern for the NGNP were evaluated for major structural components and the materials comprising them, including metallic and nonmetallic materials for control rods, other reactor internals, and primary circuit components; metallic alloys for very high-temperature service for heat exchangers and turbomachinery, metallic alloys for high-temperature service for the reactor pressure vessel (RPV), other pressure vessels and components in the primary and secondary circuits; and metallic alloys for secondary heat transfer circuits and the balance of plant. These materials phenomena were primarily evaluated with regard to their potential for contributing to fission product release at the site boundary under a variety of event scenarios covering normal operation, anticipated transients, and accidents. Of all the high-temperature metallic components, the one most likely to be heavily challenged in the NGNP will be the intermediate heat exchanger (IHX). Its thin, internal sections must be able to withstand the stresses associated with thermal loading and pressure drops between the primary and secondary loops under the environments and temperatures of interest. Several important materials-related phenomena related to the IHX were identified, including crack initiation and propagation; the lack of experience of primary boundary design methodology limitations for new IHX structures; and manufacturing phenomena for new designs. Specific issues were also identified for RPVs that will likely be too large for shop fabrication and transportation. Validated procedures

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.

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...

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.

Pacing Behavior and Tactical Positioning in 1500-m Short-Track Speed Skating.

Science.gov (United States)

Konings, Marco J; Noorbergen, Olaf S; Parry, David; Hettinga, Florentina J

2016-01-01

To gain more insight in pacing behavior and tactical positioning in 1500-m short-track speed skating, a sport in which several athletes directly compete in the same race. Lap times and intermediate rankings of elite 1500-m short-track- skating competitors were collected over the season 2012-13 (N = 510, 85 races). Two statistical approaches were used to assess pacing behavior and tactical positioning. First, lap times were analyzed using a MANOVA, and for each lap differences between sex, race type, final rankings, and stage of competition were determined. Second, Kendall tau b correlations were used to assess relationships between intermediate and final rankings. In addition, intermediate rankings of the winner of each race were examined. In 1500 m (13.5 laps of 111.12 m), correlations between intermediate and final ranking gradually increased throughout the race (eg, lap 1, r = .05; lap 7, r = .26; lap 13, r = .85). Moreover, the percentage of race winners skating in the leading position was over 50% during the last 3 laps. Top finishers were faster than bottom-place finishers only during the last 5 laps, with on average 0.1- to 1.5-s faster lap times of the race winners compared with the others during the last 5 laps. Although a fast start led to faster finishing times, top finishers were faster than bottom-placed finishers only during the last 5 laps. Moreover, tactical positioning at 1 of the foremost positions during the latter phase of the race appeared to be a strong determinant of finishing position.

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

Grooming Up the Hierarchy: The Exchange of Grooming and Rank-Related Benefits in a New World Primate

OpenAIRE

Tiddi, Barbara; Aureli, Filippo; Schino, Gabriele

2012-01-01

Seyfarth’s model assumes that female primates derive rank-related benefits from higher-ranking females in exchange for grooming. As a consequence, the model predicts females prefer high-ranking females as grooming partners and compete for the opportunity to groom them. Therefore, allogrooming is expected to be directed up the dominance hierarchy and to occur more often between females with adjacent ranks. Although data from Old World primates generally support the model, studies o...

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...

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.

Among-sibling differences in the phenotypes of juvenile fish depend on their location within the egg mass and maternal dominance rank

Science.gov (United States)

Burton, Tim; Hoogenboom, M. O.; Beevers, N. D.; Armstrong, J. D.; Metcalfe, N. B.

2013-01-01

We investigated whether among-sibling differences in the phenotypes of juvenile fish were systematically related to the position in the egg mass where each individual developed during oogenesis. We sampled eggs from the front, middle and rear thirds of the egg mass in female brown trout of known dominance rank. In the resulting juveniles, we then measured traits that are related to individual fitness: body size, social status and standard metabolic rate (SMR). When controlling for differences among females in mean egg size, siblings from dominant mothers were initially larger (and had a lower mass-corrected SMR) if they developed from eggs at the rear of the egg mass. However, heterogeneity in the size of siblings from different positions in the egg mass diminished in lower-ranking females. Location of the egg within the egg mass also affected the social dominance of the resulting juvenile fish, although the direction of this effect varied with developmental age. This study provides the first evidence of a systematic basis for among-sibling differences in the phenotypes of offspring in a highly fecund organism. PMID:23193132

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

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.

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.

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

Science.gov (United States)

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

2011-10-01

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

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.

Outlier Ranking via Subspace Analysis in Multiple Views of the Data

DEFF Research Database (Denmark)

Muller, Emmanuel; Assent, Ira; Iglesias, Patricia

2012-01-01

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

How did Malaysia Manage its Position as Top 10 World Tourist Destinations in UNWTO Ranking in 2012?

Directory of Open Access Journals (Sweden)

Nor’Ain Othman

2014-03-01

Full Text Available There are many reasons contributing to the achievement of Malaysia for being rank as top 10 most visited destinations in the world for the last four years. Among the factors are structures, resources, strategy, policy and leadership. In order to identify how Malaysia manage to be at this rank, a study was carried out on destination branding of Malaysian tourism from destination marketers’ perspectives. The objectives are to identify tourism marketing messages that influence international tourists desire to visit Malaysia and to examine destination marketing agencies attitude towards building “Brand Malaysia” in tourism products. The subject of this research is the most recent promotion involving a new brand entitled “Malaysia Truly Asia” and examines the initiative within the framework of the country’s destination branding and destination image development strategies. An assessment of the part played by destination branding in Malaysian tourism industry at large forms the wider context for the study and conclusions of more general relevance are drawn from the particularities of the case. A quantitative research method is used to examine the attitude of destination marketers towards the awareness on marketing mix used in creating “Brand Malaysia” tourism branding. A total of 300 questionnaires were distributed to travel agencies based on purposive convenient sampling.

Ranking the adaptive capacity of nations to climate change when socio-political goals are explicit

Energy Technology Data Exchange (ETDEWEB)

Haddad, B.M. [University of California, Santa Cruz, CA (United States)

2005-07-01

The typical categories for measuring national adaptive capacity to climate change include a nation's wealth, technology, education, information, skills, infrastructure, access to resources, and management capabilities. Resulting rankings predictably mirror more general rankings of economic development, such as the Human Development Index. This approach is incomplete since it does not consider the normative or motivational context of adaptation. For what purpose or toward what goal does a nation aspire, and in that context, what is its adaptive capacity? This paper posits 11 possible national socio-political goals that fall into the three categories of teleological legitimacy, procedural legitimacy, and norm-based decision rules. A model that sorts nations in terms of adaptive capacity based on national socio-political aspirations is presented. While the aspiration of maximizing summed utility matches typical existing rankings, alternative aspirations, including contractarian liberalism, technocratic management, and dictatorial/religious rule alter the rankings. An example describes how this research can potentially inform how priorities are set for international assistance for climate change adaptation. (author)

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)

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...

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...

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...

Through a Gender Lens: A View of Gender and Leadership Positions in a Department of Medicine.

Science.gov (United States)

Monroe, Anne K; Levine, Rachel B; Clark, Jeanne M; Bickel, Janet; MacDonald, Susan M; Resar, Linda M S

2015-10-01

Despite increasing numbers in academic medicine, women remain underrepresented in top leadership positions. The objectives of this study were to characterize leadership positions held by department of medicine (DOM) faculty at all ranks at one Academic Health Center and to compare leadership positions held by male and female faculty. This was a cross-sectional survey to collect information on all leadership positions from 16 divisions in the DOM at the Johns Hopkins University School of Medicine in early 2012, including type of position, method used to fill the position, and financial compensation. Chi-square testing was used to compare leadership position characteristics by rank and gender. The study included 474 DOM faculty at the rank of instructor or higher; 38% were women. Of the 258 leadership positions identified, 35% were held by women. More leadership positions among assistant professors were held by women compared with men (56% of positions vs. 44%), with women assistant professors more likely to hold a leadership position than men (p=0.03). Numbers of women faculty declined at higher ranks, with leadership positions remaining proportionate to faculty representation. Most division director positions (88%) were held by men, and most leadership positions were compensated (89%) and appointed by the DOM chair or a division director (80%). Leadership positions held by women and men were proportionate to faculty representation, although the top leadership positions were held almost exclusively by men. While female assistant professors were more likely to hold leadership positions than male assistant professors, these positions appear to be low status positions and it is not clear that they contribute to professional advancement, as few women hold the rank of full professor. Effective interventions are needed to address the gender disparity in top leadership positions.

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

Enabling multi-level relevance feedback on PubMed by integrating rank learning into DBMS.

Science.gov (United States)

Yu, Hwanjo; Kim, Taehoon; Oh, Jinoh; Ko, Ilhwan; Kim, Sungchul; Han, Wook-Shin

2010-04-16

Finding relevant articles from PubMed is challenging because it is hard to express the user's specific intention in the given query interface, and a keyword query typically retrieves a large number of results. Researchers have applied machine learning techniques to find relevant articles by ranking the articles according to the learned relevance function. However, the process of learning and ranking is usually done offline without integrated with the keyword queries, and the users have to provide a large amount of training documents to get a reasonable learning accuracy. This paper proposes a novel multi-level relevance feedback system for PubMed, called RefMed, which supports both ad-hoc keyword queries and a multi-level relevance feedback in real time on PubMed. RefMed supports a multi-level relevance feedback by using the RankSVM as the learning method, and thus it achieves higher accuracy with less feedback. RefMed "tightly" integrates the RankSVM into RDBMS to support both keyword queries and the multi-level relevance feedback in real time; the tight coupling of the RankSVM and DBMS substantially improves the processing time. An efficient parameter selection method for the RankSVM is also proposed, which tunes the RankSVM parameter without performing validation. Thereby, RefMed achieves a high learning accuracy in real time without performing a validation process. RefMed is accessible at http://dm.postech.ac.kr/refmed. RefMed is the first multi-level relevance feedback system for PubMed, which achieves a high accuracy with less feedback. It effectively learns an accurate relevance function from the user's feedback and efficiently processes the function to return relevant articles in real time.

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…

Canine length in wild male baboons: maturation, aging and social dominance rank.

Directory of Open Access Journals (Sweden)

Jordi Galbany

Full Text Available Canines represent an essential component of the dentition for any heterodont mammal. In primates, like many other mammals, canines are frequently used as weapons. Hence, tooth size and wear may have significant implications for fighting ability, and consequently for social dominance rank, reproductive success, and fitness. We evaluated sources of variance in canine growth and length in a well-studied wild primate population because of the potential importance of canines for male reproductive success in many primates. Specifically, we measured maxillary canine length in 80 wild male baboons (aged 5.04-20.45 years from the Amboseli ecosystem in southern Kenya, and examined its relationship with maturation, age, and social dominance rank. In our analysis of maturation, we compared food-enhanced baboons (those that fed part time at a refuse pit associated with a tourist lodge with wild-feeding males, and found that food-enhanced males achieved long canines earlier than wild-feeding males. Among adult males, canine length decreased with age because of tooth wear. We found some evidence that, after controlling for age, longer canines were associated with higher adult dominance rank (accounting for 9% of the variance in rank, but only among relatively high-ranking males. This result supports the idea that social rank, and thus reproductive success and fitness, may depend in part on fighting ability mediated by canine size.

HPGMG 1.0: A Benchmark for Ranking High Performance Computing Systems

Energy Technology Data Exchange (ETDEWEB)

Adams, Mark; Brown, Jed; Shalf, John; Straalen, Brian Van; Strohmaier, Erich; Williams, Sam

2014-05-05

This document provides an overview of the benchmark ? HPGMG ? for ranking large scale general purpose computers for use on the Top500 list [8]. We provide a rationale for the need for a replacement for the current metric HPL, some background of the Top500 list and the challenges of developing such a metric; we discuss our design philosophy and methodology, and an overview of the specification of the benchmark. The primary documentation with maintained details on the specification can be found at hpgmg.org and the Wiki and benchmark code itself can be found in the repository https://bitbucket.org/hpgmg/hpgmg.

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.

High-Throughput Screening and Quantitative Chemical Ranking for Sodium-Iodide Symporter Inhibitors in ToxCast Phase I Chemical Library.

Science.gov (United States)

Wang, Jun; Hallinger, Daniel R; Murr, Ashley S; Buckalew, Angela R; Simmons, Steven O; Laws, Susan C; Stoker, Tammy E

2018-05-01

Thyroid uptake of iodide via the sodium-iodide symporter (NIS) is the first step in the biosynthesis of thyroid hormones that are critical for health and development in humans and wildlife. Despite having long been a known target of endocrine disrupting chemicals such as perchlorate, information regarding NIS inhibition activity is still unavailable for the vast majority of environmental chemicals. This study applied a previously validated high-throughput approach to screen for NIS inhibitors in the ToxCast phase I library, representing 293 important environmental chemicals. Here 310 blinded samples were screened in a tiered-approach using an initial single-concentration (100 μM) radioactive-iodide uptake (RAIU) assay, followed by 169 samples further evaluated in multi-concentration (0.001 μM-100 μM) testing in parallel RAIU and cell viability assays. A novel chemical ranking system that incorporates multi-concentration RAIU and cytotoxicity responses was also developed as a standardized method for chemical prioritization in current and future screenings. Representative chemical responses and thyroid effects of high-ranking chemicals are further discussed. This study significantly expands current knowledge of NIS inhibition potential in environmental chemicals and provides critical support to U.S. EPA's Endocrine Disruptor Screening Program (EDSP) initiative to expand coverage of thyroid molecular targets, as well as the development of thyroid adverse outcome pathways (AOPs).

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.

Life history in male mandrills (Mandrillus sphinx): physical development, dominance rank, and group association.

Science.gov (United States)

Setchell, Joanna M; Wickings, E Jean; Knapp, Leslie A

2006-12-01

We assess life history from birth to death in male mandrills (Mandrillus sphinx) living in a semifree-ranging colony in Gabon, using data collected for 82 males that attained at least the age of puberty, including 33 that reached adulthood and 25 that died, yielding data for their entire lifespan. We describe patterns of mortality and injuries, dominance rank, group association, growth and stature, and secondary sexual character expression across the male lifespan. We examine relationships among these variables and investigate potential influences on male life history, including differences in the social environment (maternal rank and group demography) and early development, with the aim of identifying characteristics of successful males. Sons of higher-ranking females were more likely to survive to adulthood than sons of low-ranking females. Adolescent males varied consistently in the rate at which they developed, and this variation was related to a male's own dominance rank. Males with fewer peers and sons of higher-ranking and heavier mothers also matured faster. However, maternal variables were not significantly related to dominance rank during adolescence, the age at which males attained adult dominance rank, or whether a male became alpha male. Among adult males, behavior and morphological development were related to a male's own dominance rank, and sons of high-ranking females were larger than sons of low-ranking females. Alpha males were always the most social, and the most brightly colored males, but were not necessarily the largest males present. Finally, alpha male tenure was related to group demography, with larger numbers of rival adult males and maturing adolescent males reducing the time a male spent as alpha male. Tenure did not appear to be related to characteristics of the alpha male himself. 2006 Wiley-Liss, Inc.

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.

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…

High Ki-67 score is indicative of a greater benefit from adjuvant chemotherapy when added to endocrine therapy in luminal B HER2 negative and node-positive breast cancer.

Science.gov (United States)

Criscitiello, Carmen; Disalvatore, Davide; De Laurentiis, Michele; Gelao, Lucia; Fumagalli, Luca; Locatelli, Marzia; Bagnardi, Vincenzo; Rotmensz, Nicole; Esposito, Angela; Minchella, Ida; De Placido, Sabino; Santangelo, Michele; Viale, Giuseppe; Goldhirsch, Aron; Curigliano, Giuseppe

2014-02-01

The indication of adjuvant chemotherapy for patients with highly proliferative estrogen receptor-positive breast cancer is controversial. We analyzed the predictive value of Ki67 for the efficacy of adjuvant chemotherapy in patients with estrogen receptor-positive, node-positive breast cancer. We identified 1241 patients with Luminal B early stage breast cancer with 1-3 axillary positive nodes who underwent surgery between 1995 and 2005 at the European Institute of Oncology and received adjuvant hormonotherapy and/or chemotherapy. Differences in the distribution of characteristics according to treatment were evaluated by the Chi-square test. To evaluate the effect of adding chemotherapy to hormonotherapy, the propensity score method was used to match patients' characteristics minimizing bias related to the non-random assignment of treatment. The probability of receiving chemotherapy was significantly associated with age, tumor grade, degree of hormone responsiveness, tumor size and peripheral vascular invasion. The propensity score distribution was statistically different between the two treatment groups (p chemotherapy group (log-rank test p-value 0.663). The 5-year DFS percentages were 84.6% (95% CI, 81.0-87.6%) in the hormonotherapy group and 84.2% (95% CI, 81.3-86.7%) in the hormonotherapy/chemotherapy group (log-rank test p-value 0.388). However, when analyzing the 5-year DFS by Ki-67 distribution, Subpopulation Treatment Effect Pattern Plot (STEPP) analysis showed a beneficial effect of chemotherapy in patients with highly proliferative tumor (Ki-67 ≥ 32%). The interaction between Ki-67 and treatment was statistically significant (p = 0.027). Ki67 expression identifies a subset of patients with Luminal B and node-positive breast cancer who could benefit from addition of adjuvant chemotherapy to hormonotherapy. Dichotomy was observed for Ki67 at 32% level. Copyright © 2013 Elsevier Ltd. All rights reserved.

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.

Robust Tracking with Discriminative Ranking Middle-Level Patches

Directory of Open Access Journals (Sweden)

Hong Liu

2014-04-01

Full Text Available The appearance model has been shown to be essential for robust visual tracking since it is the basic criterion to locating targets in video sequences. Though existing tracking-by-detection algorithms have shown to be greatly promising, they still suffer from the drift problem, which is caused by updating appearance models. In this paper, we propose a new appearance model composed of ranking middle-level patches to capture more object distinctiveness than traditional tracking-by-detection models. Targets and backgrounds are represented by both low-level bottom-up features and high-level top-down patches, which can compensate each other. Bottom-up features are defined at the pixel level, and each feature gets its discrimination score through selective feature attention mechanism. In top-down feature extraction, rectangular patches are ranked according to their bottom-up discrimination scores, by which all of them are clustered into irregular patches, named ranking middle-level patches. In addition, at the stage of classifier training, the online random forests algorithm is specially refined to reduce drifting problems. Experiments on challenging public datasets and our test videos demonstrate that our approach can effectively prevent the tracker drifting problem and obtain competitive performance in visual tracking.

The Influence of Wealth, Transparency, and Democracy on the Number of Top Ranked Universities

Science.gov (United States)

Jabnoun, Naceur

2015-01-01

Purpose: This paper aims to explore the influence of wealth, transparency and democracy on the number of universities per million people ranked among the top 300 and 500. The highly ranked universities in the world tend to be concentrated in a few countries. Design/Methodology/Approach: ANOVA was used to test the differences between the two groups…

Diagnosing and ranking retinopathy disease level using diabetic fundus image recuperation approach.

Science.gov (United States)

Somasundaram, K; Rajendran, P Alli

2015-01-01

Retinal fundus images are widely used in diagnosing different types of eye diseases. The existing methods such as Feature Based Macular Edema Detection (FMED) and Optimally Adjusted Morphological Operator (OAMO) effectively detected the presence of exudation in fundus images and identified the true positive ratio of exudates detection, respectively. These mechanically detected exudates did not include more detailed feature selection technique to the system for detection of diabetic retinopathy. To categorize the exudates, Diabetic Fundus Image Recuperation (DFIR) method based on sliding window approach is developed in this work to select the features of optic cup in digital retinal fundus images. The DFIR feature selection uses collection of sliding windows with varying range to obtain the features based on the histogram value using Group Sparsity Nonoverlapping Function. Using support vector model in the second phase, the DFIR method based on Spiral Basis Function effectively ranks the diabetic retinopathy disease level. The ranking of disease level on each candidate set provides a much promising result for developing practically automated and assisted diabetic retinopathy diagnosis system. Experimental work on digital fundus images using the DFIR method performs research on the factors such as sensitivity, ranking efficiency, and feature selection time.

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

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

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

Science.gov (United States)

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

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.

Multicriteria ranking of workplaces regarding working conditions in a mining company.

Science.gov (United States)

Bogdanović, Dejan; Stanković, Vladimir; Urošević, Snežana; Stojanović, Miloš

2016-12-01

Ranking of workplaces with respect to working conditions is very significant for each company. It indicates the positions where employees are most exposed to adverse effects resulting from the working environment, which endangers their health. This article presents the results obtained for 12 different production workplaces in the copper mining and smelting complex RTB Bor - 'Veliki Krivelj' open pit, based on six parameters measured regularly which defined the following working environment conditions: air temperature, light, noise, dustiness, chemical hazards and vibrations. The ranking of workplaces has been performed by PROMETHEE/GAIA. Additional optimization of workplaces is done by PROMETHEE V with the given limits related to maximum permitted values for working environment parameters. The obtained results indicate that the most difficult workplace is on the excavation location (excavator operator). This method can be successfully used for solving similar kinds of problems, in order to improve working conditions.

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.

BridgeRank: A novel fast centrality measure based on local structure of the network

Science.gov (United States)

Salavati, Chiman; Abdollahpouri, Alireza; Manbari, Zhaleh

2018-04-01

Ranking nodes in complex networks have become an important task in many application domains. In a complex network, influential nodes are those that have the most spreading ability. Thus, identifying influential nodes based on their spreading ability is a fundamental task in different applications such as viral marketing. One of the most important centrality measures to ranking nodes is closeness centrality which is efficient but suffers from high computational complexity O(n3) . This paper tries to improve closeness centrality by utilizing the local structure of nodes and presents a new ranking algorithm, called BridgeRank centrality. The proposed method computes local centrality value for each node. For this purpose, at first, communities are detected and the relationship between communities is completely ignored. Then, by applying a centrality in each community, only one best critical node from each community is extracted. Finally, the nodes are ranked based on computing the sum of the shortest path length of nodes to obtained critical nodes. We have also modified the proposed method by weighting the original BridgeRank and selecting several nodes from each community based on the density of that community. Our method can find the best nodes with high spread ability and low time complexity, which make it applicable to large-scale networks. To evaluate the performance of the proposed method, we use the SIR diffusion model. Finally, experiments on real and artificial networks show that our method is able to identify influential nodes so efficiently, and achieves better performance compared to other recent methods.

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

Science.gov (United States)

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

2017-01-01

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

Ranking of Palliative Care Development in the Countries of the European Union.

Science.gov (United States)

Woitha, Kathrin; Garralda, Eduardo; Martin-Moreno, Jose María; Clark, David; Centeno, Carlos

2016-09-01

There is growing interest in monitoring palliative care (PC) development internationally. One aspect of this is the ranking of such development for comparative purposes. To generate a ranking classification and to compare scores for PC development in the countries of the European Union, 2007 and 2013. PC "development" in this study is understood as a combination of the existence of relevant services in a country ("resources") plus the capacity to develop further resources in the future ("vitality"). "Resources" comprise indicators of three types of PC services per population (inpatient palliative care units and inpatient hospices, hospital support teams, and home care teams). "Vitality" of PC is estimated by numerical scores for the existence of a national association, a directory of services, physician accreditation, attendances at a key European conference and volume of publications on PC development. The leading country (by raw score) is then considered as the reference point against which all other countries are measured. Different weightings are applied to resources (75%) and vitality (25%). From this, an overall ranking is constructed. The U.K. achieved the highest level of development (86% of the maximum possible score), followed by Belgium and overall The Netherlands (81%), and Sweden (80%). In the resources domain, Luxembourg, the U.K., and Belgium were leading. The top countries in vitality were Germany and the U.K. In comparison to 2007, The Netherlands, Malta, and Portugal showed the biggest improvements, whereas the positions of Spain, France, and Greece deteriorated. The ranking method permitted a comparison of palliative care development between countries and shows changes over time. Recommendations for improving the ranking include improvements to the methodology and greater explanation of the levels and changes it reveals. Copyright © 2016 Universidad Navarra. Published by Elsevier Inc. All rights reserved.

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....

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.

A review of studies on information systems and SMEs in high ranked IS journals (2000-2014

Directory of Open Access Journals (Sweden)

Craig M. Parker

2015-10-01

Full Text Available This paper identifies novel approaches to future small and medium enterprise (SME research from a review of articles, and then introduces the papers in this AJIS special section which evidence these approaches. More specifically, the paper makes an important contribution by reviewing 61 articles in high ranked IS journals (2000-2014 and introducing three new facets which are used to analyse research on SME adoption/use of IS (units of analysis, SME sizes and SME types not considered in previous literature review studies. These facets provide the basis for proposing various future research opportunities. The editorial then introduces the four papers in this special section covering the research theme on SMEs, and highlights the contributions they make using the three facets.

The highest-ranking rooster has priority to announce the break of dawn

OpenAIRE

Shimmura, Tsuyoshi; Ohashi, Shosei; Yoshimura, Takashi

2015-01-01

The ?cock-a-doodle-doo? crowing of roosters, which symbolizes the break of dawn in many cultures, is controlled by the circadian clock. When one rooster announces the break of dawn, others in the vicinity immediately follow. Chickens are highly social animals, and they develop a linear and fixed hierarchy in small groups. We found that when chickens were housed in small groups, the top-ranking rooster determined the timing of predawn crowing. Specifically, the top-ranking rooster always start...

The Homogeneity of Social Selection in Accessing Higher Ranked Universities

DEFF Research Database (Denmark)

Munk, Martin David; Baklanov, Nikita

2018-01-01

This paper demonstrates the persistence of social selectivity throughout the educational ladder, with evident social reproduction at the top. By jointly modelling multiple choices of high school, university, field of study, and institutional rank of university using a multinomial transition model...

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.

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

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.

Strategy Precedes Operational Effectiveness: Aligning High Graduation Rankings with Competitive Graduation Grade Point Averages

Science.gov (United States)

Apprey, Maurice; Bassett, Kimberley C.; Preston-Grimes, Patrice; Lewis, Dion W.; Wood, Beverly

2014-01-01

Two pivotal and interconnected claims are addressed in this article. First, strategy precedes program effectiveness. Second, graduation rates and rankings are insufficient in any account of academic progress for African American students. In this article, graduation is regarded as the floor and not the ceiling, as it were. The ideal situation in…

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.

Hazard Ranking Methodology for Assessing Health Impacts of Unconventional Natural Gas Development and Production: The Maryland Case Study.

Directory of Open Access Journals (Sweden)

Meleah D Boyle

Full Text Available The recent growth of unconventional natural gas development and production (UNGDP has outpaced research on the potential health impacts associated with the process. The Maryland Marcellus Shale Public Health Study was conducted to inform the Maryland Marcellus Shale Safe Drilling Initiative Advisory Commission, State legislators and the Governor about potential public health impacts associated with UNGDP so they could make an informed decision that considers the health and well-being of Marylanders. In this paper, we describe an impact assessment and hazard ranking methodology we used to assess the potential public health impacts for eight hazards associated with the UNGDP process. The hazard ranking included seven metrics: 1 presence of vulnerable populations (e.g. children under the age of 5, individuals over the age of 65, surface owners, 2 duration of exposure, 3 frequency of exposure, 4 likelihood of health effects, 5 magnitude/severity of health effects, 6 geographic extent, and 7 effectiveness of setbacks. Overall public health concern was determined by a color-coded ranking system (low, moderately high, and high that was generated based on the overall sum of the scores for each hazard. We provide three illustrative examples of applying our methodology for air quality and health care infrastructure which were ranked as high concern and for water quality which was ranked moderately high concern. The hazard ranking was a valuable tool that allowed us to systematically evaluate each of the hazards and provide recommendations to minimize the hazards.

Ranked retrieval of Computational Biology models.

Science.gov (United States)

Henkel, Ron; Endler, Lukas; Peters, Andre; Le Novère, Nicolas; Waltemath, Dagmar

2010-08-11

The study of biological systems demands computational support. If targeting a biological problem, the reuse of existing computational models can save time and effort. Deciding for potentially suitable models, however, becomes more challenging with the increasing number of computational models available, and even more when considering the models' growing complexity. Firstly, among a set of potential model candidates it is difficult to decide for the model that best suits ones needs. Secondly, it is hard to grasp the nature of an unknown model listed in a search result set, and to judge how well it fits for the particular problem one has in mind. Here we present an improved search approach for computational models of biological processes. It is based on existing retrieval and ranking methods from Information Retrieval. The approach incorporates annotations suggested by MIRIAM, and additional meta-information. It is now part of the search engine of BioModels Database, a standard repository for computational models. The introduced concept and implementation are, to our knowledge, the first application of Information Retrieval techniques on model search in Computational Systems Biology. Using the example of BioModels Database, it was shown that the approach is feasible and extends the current possibilities to search for relevant models. The advantages of our system over existing solutions are that we incorporate a rich set of meta-information, and that we provide the user with a relevance ranking of the models found for a query. Better search capabilities in model databases are expected to have a positive effect on the reuse of existing models.

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

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.

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

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...

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; ...

Abundances of polycyclic aromatic hydrocarbons (PAHs) in 14 chinese and american coals and their relation to coal rank and weathering

Science.gov (United States)

Wang, R.; Liu, Gaisheng; Zhang, Jiahua; Chou, C.-L.; Liu, J.

2010-01-01

The abundances of 16 polycyclic aromatic hydrocarbons (PAHs) on the priority list of the United States Environmental Protection Agency (U.S. EPA) have been determined in 14 Chinese and American coals. The ranks of the samples range from lignite, bituminous coal, anthracite, to natural coke. Soxhlet extraction was conducted on each coal for 48 h. The extract was analyzed on a gas chromatograph-mass spectrometer (GC-MS). The results show that the total PAH content ranged from 0.31 to 57.6 ??g/g of coal (on a dry basis). It varied with coal rank and is highest in the maturity range of bituminous coal rank. High-molecular-weight (HMW) PAHs are predominant in low-rank coals, but low-molecular-weight (LMW) PAHs are predominant in high-rank coals. The low-sulfur coals have a higher PAH content than high-sulfur coals. It may be explained by an increasing connection between disulfide bonds and PAHs in high-sulfur coal. In addition, it leads us to conclude that the PAH content of coals may be related to the depositional environment. ?? 2010 American Chemical Society.

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.

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

A gender-based comparison of academic rank and scholarly productivity in academic neurological surgery.

Science.gov (United States)

Tomei, Krystal L; Nahass, Meghan M; Husain, Qasim; Agarwal, Nitin; Patel, Smruti K; Svider, Peter F; Eloy, Jean Anderson; Liu, James K

2014-07-01

The number of women pursuing training opportunities in neurological surgery has increased, although they are still underrepresented at senior positions relative to junior academic ranks. Research productivity is an important component of the academic advancement process. We sought to use the h-index, a bibliometric previously analyzed among neurological surgeons, to evaluate whether there are gender differences in academic rank and research productivity among academic neurological surgeons. The h-index was calculated for 1052 academic neurological surgeons from 84 institutions, and organized by gender and academic rank. Overall men had statistically higher research productivity (mean 13.3) than their female colleagues (mean 9.5), as measured by the h-index, in the overall sample (p0.05) in h-index at the assistant professor (mean 7.2 male, 6.3 female), associate professor (11.2 male, 10.8 female), and professor (20.0 male, 18.0 female) levels based on gender. There was insufficient data to determine significance at the chairperson rank, as there was only one female chairperson. Although overall gender differences in scholarly productivity were detected, these differences did not reach statistical significance upon controlling for academic rank. Women were grossly underrepresented at the level of chairpersons in this sample of 1052 academic neurological surgeons, likely a result of the low proportion of females in this specialty. Future studies may be needed to investigate gender-specific research trends for neurosurgical residents, a cohort that in recent years has seen increased representation by women. Copyright © 2013 Elsevier Ltd. All rights reserved.

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.

[Computerized ranking test in three French universities: Staff experience and students' feedback].

Science.gov (United States)

Roux, D; Meyer, G; Cymbalista, F; Bouaziz, J-D; Falgarone, G; Tesniere, A; Gervais, J; Cariou, A; Peffault de Latour, R; Marat, M; Moenaert, E; Guebli, T; Rodriguez, O; Lefort, A; Dreyfuss, D; Hajage, D; Ricard, J-D

2016-03-01

The year 2016 will be pivotal for the evaluation of French medical students with the introduction of the first computerized National Ranking Test (ECNi). The SIDES, online electronic system for medical student evaluation, was created for this purpose. All the universities have already organized faculty exams but few a joint computerized ranking test at several universities simultaneously. We report our experience on the organization of a mock ECNi by universities Paris Descartes, Paris Diderot and Paris 13. Docimological, administrative and technical working groups were created to organize this ECNi. Students in their fifth year of medical studies, who will be the first students to sit for the official ECNi in 2016, were invited to attend this mock exam that represented more than 50% of what will be proposed in 2016. A final electronic questionnaire allowed a docimological and organizational evaluation by students. An analysis of ratings and rankings and their distribution on a 1000-point scale were performed. Sixty-four percent of enrolled students (i.e., 654) attended the three half-day exams. No difference in total score and ranking between the three universities was observed. Students' feedback was extremely positive. Normalized over 1000 points, 99% of students were scored on 300 points only. Progressive clinical cases were the most discriminating test. The organization of a mock ECNi involving multiple universities was a docimological and technical success but required an important administrative, technical and teaching investment. Copyright © 2016 Société nationale française de médecine interne (SNFMI). Published by Elsevier SAS. All rights reserved.

High current precision long pulse electron beam position monitor

CERN Document Server

Nelson, S D; Fessenden, T J; Holmes, C

2000-01-01

Precision high current long pulse electron beam position monitoring has typically experienced problems with high Q sensors, sensors damped to the point of lack of precision, or sensors that interact substantially with any beam halo thus obscuring the desired signal. As part of the effort to develop a multi-axis electron beam transport system using transverse electromagnetic stripline kicker technology, it is necessary to precisely determine the position and extent of long high energy beams for accurate beam position control (6 - 40 MeV, 1 - 4 kA, 2 μs beam pulse, sub millimeter beam position accuracy.) The kicker positioning system utilizes shot-to-shot adjustments for reduction of relatively slow (< 20 MHz) motion of the beam centroid. The electron beams passing through the diagnostic systems have the potential for large halo effects that tend to corrupt position measurements.

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.)

Class Attendance and Students' Evaluations of Teaching: Do No-Shows Bias Course Ratings and Rankings?

Science.gov (United States)

Wolbring, Tobias

2012-01-01

Background: Many university departments use students' evaluations of teaching (SET) to compare and rank courses. However, absenteeism from class is often nonrandom and, therefore, SET for different courses might not be comparable. Objective: The present study aims to answer two questions. Are SET positively biased due to absenteeism? Do…

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…

Diagnosing and Ranking Retinopathy Disease Level Using Diabetic Fundus Image Recuperation Approach

Directory of Open Access Journals (Sweden)

K. Somasundaram

2015-01-01

Full Text Available Retinal fundus images are widely used in diagnosing different types of eye diseases. The existing methods such as Feature Based Macular Edema Detection (FMED and Optimally Adjusted Morphological Operator (OAMO effectively detected the presence of exudation in fundus images and identified the true positive ratio of exudates detection, respectively. These mechanically detected exudates did not include more detailed feature selection technique to the system for detection of diabetic retinopathy. To categorize the exudates, Diabetic Fundus Image Recuperation (DFIR method based on sliding window approach is developed in this work to select the features of optic cup in digital retinal fundus images. The DFIR feature selection uses collection of sliding windows with varying range to obtain the features based on the histogram value using Group Sparsity Nonoverlapping Function. Using support vector model in the second phase, the DFIR method based on Spiral Basis Function effectively ranks the diabetic retinopathy disease level. The ranking of disease level on each candidate set provides a much promising result for developing practically automated and assisted diabetic retinopathy diagnosis system. Experimental work on digital fundus images using the DFIR method performs research on the factors such as sensitivity, ranking efficiency, and feature selection time.

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....

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.

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

Change in ranking order of prescribing patterns by age and sex standardization of the practice population--audit may be misleading

DEFF Research Database (Denmark)

Olesen, Frede; Vedsted, Peter; Nielsen, Jørgen Nørskov

1996-01-01

OBJECTIVE: To demonstrate whether standardization of practice populations by age and sex changes the internal prescription ranking order of a group of practices. DESIGN: Data on the prescribing of cardiovascular drugs in a group of practices were obtained from a county-based database. Information...... on the age, sex, and numbers of patients per practice was also obtained. The direct standardization method was used to adjust practice populations for age and sex. SETTING: The town of Randers, Aarhus County, Denmark. SUBJECTS: 35 practices, 41 GPs. MAIN OUTCOME MEASURES: Ranking of the 35 practices...... of the practices. Only four practices did not change ranking position, while four moved more than ten places. The slope between highest and lowest ranked practice did not diminish after standardization. CONCLUSION: Care should be taken when comparing peer prescribing patterns from crude utilization data, and we...

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...

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

Computing Principal Eigenvectors of Large Web Graphs: Algorithms and Accelerations Related to PageRank and HITS

Science.gov (United States)

Nagasinghe, Iranga

2010-01-01

This thesis investigates and develops a few acceleration techniques for the search engine algorithms used in PageRank and HITS computations. PageRank and HITS methods are two highly successful applications of modern Linear Algebra in computer science and engineering. They constitute the essential technologies accounted for the immense growth and…

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.

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…

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.

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.

On the dimension of subspaces with bounded Schmidt rank

International Nuclear Information System (INIS)

Cubitt, Toby; Montanaro, Ashley; Winter, Andreas

2008-01-01

We consider the question of how large a subspace of a given bipartite quantum system can be when the subspace contains only highly entangled states. This is motivated in part by results of Hayden et al. [e-print arXiv:quant-ph/0407049; Commun. Math. Phys., 265, 95 (2006)], which show that in large dxd-dimensional systems there exist random subspaces of dimension almost d 2 , all of whose states have entropy of entanglement at least log d-O(1). It is also a generalization of results on the dimension of completely entangled subspaces, which have connections with the construction of unextendible product bases. Here we take as entanglement measure the Schmidt rank, and determine, for every pair of local dimensions d A and d B , and every r, the largest dimension of a subspace consisting only of entangled states of Schmidt rank r or larger. This exact answer is a significant improvement on the best bounds that can be obtained using the random subspace techniques in Hayden et al. We also determine the converse: the largest dimension of a subspace with an upper bound on the Schmidt rank. Finally, we discuss the question of subspaces containing only states with Schmidt equal to r

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.

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.

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.

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)

High voltage disconnect switch position monitoring

Energy Technology Data Exchange (ETDEWEB)

Crampton, S W

1983-08-01

Unreliable position indication on high-voltage (HV) disconnect switches can result in equipment damage worth many times the cost of a disconnect switch. The benefits and limitations of a number of possible methods of reliably monitoring HV disconnect switches are assessed. Several methods of powering active devices at HV are noted. It is concluded that the most reliable way of monitoring switch position at reasonable cost would use a passive hermetically-sealed blade-position sensor located at HV, with a fibre-optic link between HV and ground. Separate sensors would be used for open and closed position indication. For maximum reliability the fibre-optic link would continue into the relay building. A passive magnetically actuated fibre-optic sensor has been built which demonstrates the feasibility of the concept. The sensor monitors blade position relative to the jaws in three dimensions with high resolution. A design for an improved passive magneto-optic sensor has significantly lower optical losses, allowing a single fibre-optic loop and 3 sensors to monitor closure of all phases of a disconnect switch. A similar loop would monitor switch opening. The improved sensor has a solid copper housing to provide greater immunity to fault currents, and to protect it from the environment and from physical damage. Two methods of providing a protected path for fibre-optics passing from HV to ground are proposed, one using a hollow porcelain switch-support insulator and the other using an additional small-diameter polymer insulator with optical fibres imbedded in its fibreglass core. A number of improvements are recommended which can be made to existing switches to increase their reliability. 16 refs., 13 figs., 1 tab.

Screening and ranking Alberta oil pools for CO{sub 2} flooding and sequestration

Energy Technology Data Exchange (ETDEWEB)

Shaw, J.C. [Adams Pearson Associates Inc., Calgary, AB (Canada); Bachu, S. [Alberta Energy and Utilities Board, Calgary, AB (Canada)

2001-06-01

This paper presented the results of a technical screening program using Excel VBA to successfully screen and rank a very large number of oil pools for enhanced oil recovery using carbon dioxide (CO{sub 2}) flooding. A total of 6 ranking parameters were used, including API gravity of oil, residual oil saturation, ratio between reservoir pressure and minimum miscibility pressure, reservoir temperature, net pay thickness and porosity. The screening program provided a technical ranking of approximately 8,800 Alberta pools in less than 2 minutes. After compilation of the Alberta oil pools, it was determined that most of the deep carbonate oil pools are excellent candidates for CO{sub 2} miscible flooding. Other Devonian carbonate pools were also ranked as having high potential for the process. An environmental benefit of CO{sub 2} miscible flooding process is that carbon sequestration has the potential to reduce anthropogenic carbon dioxide emissions from reaching the atmosphere. Ongoing studies are currently addressing CO{sub 2} capture and transportation, making EOR technology viable for maintaining light oil production in western Canada. 11 refs., 7 tabs., 1 fig.

Man-Made Object Extraction from Remote Sensing Imagery by Graph-Based Manifold Ranking

Science.gov (United States)