WorldWideScience

Sample records for entropy-based gene ranking

  1. An ensemble rank learning approach for gene prioritization.

    Science.gov (United States)

    Lee, Po-Feng; Soo, Von-Wun

    2013-01-01

    Several different computational approaches have been developed to solve the gene prioritization problem. We intend to use the ensemble boosting learning techniques to combine variant computational approaches for gene prioritization in order to improve the overall performance. In particular we add a heuristic weighting function to the Rankboost algorithm according to: 1) the absolute ranks generated by the adopted methods for a certain gene, and 2) the ranking relationship between all gene-pairs from each prioritization result. We select 13 known prostate cancer genes in OMIM database as training set and protein coding gene data in HGNC database as test set. We adopt the leave-one-out strategy for the ensemble rank boosting learning. The experimental results show that our ensemble learning approach outperforms the four gene-prioritization methods in ToppGene suite in the ranking results of the 13 known genes in terms of mean average precision, ROC and AUC measures.

  2. Low-rank regularization for learning gene expression programs.

    Science.gov (United States)

    Ye, Guibo; Tang, Mengfan; Cai, Jian-Feng; Nie, Qing; Xie, Xiaohui

    2013-01-01

    Learning gene expression programs directly from a set of observations is challenging due to the complexity of gene regulation, high noise of experimental measurements, and insufficient number of experimental measurements. Imposing additional constraints with strong and biologically motivated regularizations is critical in developing reliable and effective algorithms for inferring gene expression programs. Here we propose a new form of regulation that constrains the number of independent connectivity patterns between regulators and targets, motivated by the modular design of gene regulatory programs and the belief that the total number of independent regulatory modules should be small. We formulate a multi-target linear regression framework to incorporate this type of regulation, in which the number of independent connectivity patterns is expressed as the rank of the connectivity matrix between regulators and targets. We then generalize the linear framework to nonlinear cases, and prove that the generalized low-rank regularization model is still convex. Efficient algorithms are derived to solve both the linear and nonlinear low-rank regularized problems. Finally, we test the algorithms on three gene expression datasets, and show that the low-rank regularization improves the accuracy of gene expression prediction in these three datasets.

  3. Ranking candidate genes in rat models of type 2 diabetes

    Directory of Open Access Journals (Sweden)

    Ståhl Fredrik

    2009-07-01

    Full Text Available Abstract Background Rat models are frequently used to find genomic regions that contribute to complex diseases, so called quantitative trait loci (QTLs. In general, the genomic regions found to be associated with a quantitative trait are rather large, covering hundreds of genes. To help selecting appropriate candidate genes from QTLs associated with type 2 diabetes models in rat, we have developed a web tool called Candidate Gene Capture (CGC, specifically adopted for this disorder. Methods CGC combines diabetes-related genomic regions in rat with rat/human homology data, textual descriptions of gene effects and an array of 789 keywords. Each keyword is assigned values that reflect its co-occurrence with 24 different reference terms describing sub-phenotypes of type 2 diabetes (for example "insulin resistance". The genes are then ranked based on the occurrences of keywords in the describing texts. Results CGC includes QTLs from type 2 diabetes models in rat. When comparing gene rankings from CGC based on one sub-phenotype, with manual gene ratings for four QTLs, very similar results were obtained. In total, 24 different sub-phenotypes are available as reference terms in the application and based on differences in gene ranking, they fall into separate clusters. Conclusion The very good agreement between the CGC gene ranking and the manual rating confirms that CGC is as a reliable tool for interpreting textual information. This, together with the possibility to select many different sub-phenotypes, makes CGC a versatile tool for finding candidate genes. CGC is publicly available at http://ratmap.org/CGC.

  4. Association between OPG, RANK and RANKL gene polymorphisms ...

    Indian Academy of Sciences (India)

    Association between OPG, RANK and RANKL gene polymorphisms and susceptibility to acute coronary syndrome in Korean population. Won-Seok Choe Hack-Lyoung Kim Jung-Kyu Han Young-Eun Choi Borami Seo Hyun-Jai Cho Han-Kwang Yang Kyu-Joo Park Jin-Shik Park Hun-Jun Park Pum-Joon Kim Sang-Hong ...

  5. Ranking differentially expressed genes from Affymetrix gene expression data: methods with reproducibility, sensitivity, and specificity

    OpenAIRE

    Shimizu Kentaro; Nakai Yuji; Kadota Koji

    2009-01-01

    Abstract Background To identify differentially expressed genes (DEGs) from microarray data, users of the Affymetrix GeneChip system need to select both a preprocessing algorithm to obtain expression-level measurements and a way of ranking genes to obtain the most plausible candidates. We recently recommended suitable combinations of a preprocessing algorithm and gene ranking method that can be used to identify DEGs with a higher level of sensitivity and specificity. However, in addition to th...

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

    Science.gov (United States)

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

    2005-09-21

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

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

    Directory of Open Access Journals (Sweden)

    Breitling Rainer

    2005-09-01

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

  8. 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.

  9. An Entropy-Based Position Projection Algorithm for Motif Discovery.

    Science.gov (United States)

    Zhang, Yipu; Wang, Ping; Yan, Maode

    2016-01-01

    Motif discovery problem is crucial for understanding the structure and function of gene expression. Over the past decades, many attempts using consensus and probability training model for motif finding are successful. However, the most existing motif discovery algorithms are still time-consuming or easily trapped in a local optimum. To overcome these shortcomings, in this paper, we propose an entropy-based position projection algorithm, called EPP, which designs a projection process to divide the dataset and explores the best local optimal solution. The experimental results on real DNA sequences, Tompa data, and ChIP-seq data show that EPP is advantageous in dealing with the motif discovery problem and outperforms current widely used algorithms.

  10. An Entropy-Based Position Projection Algorithm for Motif Discovery

    Directory of Open Access Journals (Sweden)

    Yipu Zhang

    2016-01-01

    Full Text Available Motif discovery problem is crucial for understanding the structure and function of gene expression. Over the past decades, many attempts using consensus and probability training model for motif finding are successful. However, the most existing motif discovery algorithms are still time-consuming or easily trapped in a local optimum. To overcome these shortcomings, in this paper, we propose an entropy-based position projection algorithm, called EPP, which designs a projection process to divide the dataset and explores the best local optimal solution. The experimental results on real DNA sequences, Tompa data, and ChIP-seq data show that EPP is advantageous in dealing with the motif discovery problem and outperforms current widely used algorithms.

  11. NDRC: A Disease-Causing Genes Prioritized Method Based on Network Diffusion and Rank Concordance.

    Science.gov (United States)

    Fang, Minghong; Hu, Xiaohua; Wang, Yan; Zhao, Junmin; Shen, Xianjun; He, Tingting

    2015-07-01

    Disease-causing genes prioritization is very important to understand disease mechanisms and biomedical applications, such as design of drugs. Previous studies have shown that promising candidate genes are mostly ranked according to their relatedness to known disease genes or closely related disease genes. Therefore, a dangling gene (isolated gene) with no edges in the network can not be effectively prioritized. These approaches tend to prioritize those genes that are highly connected in the PPI network while perform poorly when they are applied to loosely connected disease genes. To address these problems, we propose a new disease-causing genes prioritization method that based on network diffusion and rank concordance (NDRC). The method is evaluated by leave-one-out cross validation on 1931 diseases in which at least one gene is known to be involved, and it is able to rank the true causal gene first in 849 of all 2542 cases. The experimental results suggest that NDRC significantly outperforms other existing methods such as RWR, VAVIEN, DADA and PRINCE on identifying loosely connected disease genes and successfully put dangling genes as potential candidate disease genes. Furthermore, we apply NDRC method to study three representative diseases, Meckel syndrome 1, Protein C deficiency and Peroxisome biogenesis disorder 1A (Zellweger). Our study has also found that certain complex disease-causing genes can be divided into several modules that are closely associated with different disease phenotype.

  12. Entropy-based consensus clustering for patient stratification.

    Science.gov (United States)

    Liu, Hongfu; Zhao, Rui; Fang, Hongsheng; Cheng, Feixiong; Fu, Yun; Liu, Yang-Yu

    2017-09-01

    Patient stratification or disease subtyping is crucial for precision medicine and personalized treatment of complex diseases. The increasing availability of high-throughput molecular data provides a great opportunity for patient stratification. Many clustering methods have been employed to tackle this problem in a purely data-driven manner. Yet, existing methods leveraging high-throughput molecular data often suffers from various limitations, e.g. noise, data heterogeneity, high dimensionality or poor interpretability. Here we introduced an Entropy-based Consensus Clustering (ECC) method that overcomes those limitations all together. Our ECC method employs an entropy-based utility function to fuse many basic partitions to a consensus one that agrees with the basic ones as much as possible. Maximizing the utility function in ECC has a much more meaningful interpretation than any other consensus clustering methods. Moreover, we exactly map the complex utility maximization problem to the classic K -means clustering problem, which can then be efficiently solved with linear time and space complexity. Our ECC method can also naturally integrate multiple molecular data types measured from the same set of subjects, and easily handle missing values without any imputation. We applied ECC to 110 synthetic and 48 real datasets, including 35 cancer gene expression benchmark datasets and 13 cancer types with four molecular data types from The Cancer Genome Atlas. We found that ECC shows superior performance against existing clustering methods. Our results clearly demonstrate the power of ECC in clinically relevant patient stratification. The Matlab package is available at http://scholar.harvard.edu/yyl/ecc . yunfu@ece.neu.edu or yyl@channing.harvard.edu. Supplementary data are available at Bioinformatics online.

  13. Comparison of vocabularies, representations and ranking algorithms for gene prioritization by text mining.

    Science.gov (United States)

    Yu, Shi; Van Vooren, Steven; Tranchevent, Leon-Charles; De Moor, Bart; Moreau, Yves

    2008-08-15

    Computational gene prioritization methods are useful to help identify susceptibility genes potentially being involved in genetic disease. Recently, text mining techniques have been applied to extract prior knowledge from text-based genomic information sources and this knowledge can be used to improve the prioritization process. However, the effect of various vocabularies, representations and ranking algorithms on text mining for gene prioritization is still an issue that requires systematic and comparative studies. Therefore, a benchmark study about the vocabularies, representations and ranking algorithms in gene prioritization by text mining is discussed in this article. We investigated 5 different domain vocabularies, 2 text representation schemes and 27 linear ranking algorithms for disease gene prioritization by text mining. We indexed 288 177 MEDLINE titles and abstracts with the TXTGate text pro.ling system and adapted the benchmark dataset of the Endeavour gene prioritization system that consists of 618 disease-causing genes. Textual gene pro.les were created and their performance for prioritization were evaluated and discussed in a comparative manner. The results show that inverse document frequency-based representation of gene term vectors performs better than the term-frequency inverse document-frequency representation. The eVOC and MESH domain vocabularies perform better than Gene Ontology, Online Mendelian Inheritance in Man's and London Dysmorphology Database. The ranking algorithms based on 1-SVM, Standard Correlation and Ward linkage method provide the best performance. The MATLAB code of the algorithm and benchmark datasets are available by request. Supplementary data are available at Bioinformatics online.

  14. Network-Informed Gene Ranking Tackles Genetic Heterogeneity in Exome-Sequencing Studies of Monogenic Disease.

    Science.gov (United States)

    Dand, Nick; Schulz, Reiner; Weale, Michael E; Southgate, Laura; Oakey, Rebecca J; Simpson, Michael A; Schlitt, Thomas

    2015-12-01

    Genetic heterogeneity presents a significant challenge for the identification of monogenic disease genes. Whole-exome sequencing generates a large number of candidate disease-causing variants and typical analyses rely on deleterious variants being observed in the same gene across several unrelated affected individuals. This is less likely to occur for genetically heterogeneous diseases, making more advanced analysis methods necessary. To address this need, we present HetRank, a flexible gene-ranking method that incorporates interaction network data. We first show that different genes underlying the same monogenic disease are frequently connected in protein interaction networks. This motivates the central premise of HetRank: those genes carrying potentially pathogenic variants and whose network neighbors do so in other affected individuals are strong candidates for follow-up study. By simulating 1,000 exome sequencing studies (20,000 exomes in total), we model varying degrees of genetic heterogeneity and show that HetRank consistently prioritizes more disease-causing genes than existing analysis methods. We also demonstrate a proof-of-principle application of the method to prioritize genes causing Adams-Oliver syndrome, a genetically heterogeneous rare disease. An implementation of HetRank in R is available via the Website http://sourceforge.net/p/hetrank/. © 2015 The Authors. **Human Mutation published by Wiley Periodicals, Inc.

  15. Network‐Informed Gene Ranking Tackles Genetic Heterogeneity in Exome‐Sequencing Studies of Monogenic Disease

    Science.gov (United States)

    Schulz, Reiner; Weale, Michael E.; Southgate, Laura; Oakey, Rebecca J.; Simpson, Michael A.; Schlitt, Thomas

    2015-01-01

    ABSTRACT Genetic heterogeneity presents a significant challenge for the identification of monogenic disease genes. Whole‐exome sequencing generates a large number of candidate disease‐causing variants and typical analyses rely on deleterious variants being observed in the same gene across several unrelated affected individuals. This is less likely to occur for genetically heterogeneous diseases, making more advanced analysis methods necessary. To address this need, we present HetRank, a flexible gene‐ranking method that incorporates interaction network data. We first show that different genes underlying the same monogenic disease are frequently connected in protein interaction networks. This motivates the central premise of HetRank: those genes carrying potentially pathogenic variants and whose network neighbors do so in other affected individuals are strong candidates for follow‐up study. By simulating 1,000 exome sequencing studies (20,000 exomes in total), we model varying degrees of genetic heterogeneity and show that HetRank consistently prioritizes more disease‐causing genes than existing analysis methods. We also demonstrate a proof‐of‐principle application of the method to prioritize genes causing Adams‐Oliver syndrome, a genetically heterogeneous rare disease. An implementation of HetRank in R is available via the Website http://sourceforge.net/p/hetrank/. PMID:26394720

  16. Autonomous entropy-based intelligent experimental design

    Science.gov (United States)

    Malakar, Nabin Kumar

    2011-07-01

    The aim of this thesis is to explore the application of probability and information theory in experimental design, and to do so in a way that combines what we know about inference and inquiry in a comprehensive and consistent manner. Present day scientific frontiers involve data collection at an ever-increasing rate. This requires that we find a way to collect the most relevant data in an automated fashion. By following the logic of the scientific method, we couple an inference engine with an inquiry engine to automate the iterative process of scientific learning. The inference engine involves Bayesian machine learning techniques to estimate model parameters based upon both prior information and previously collected data, while the inquiry engine implements data-driven exploration. By choosing an experiment whose distribution of expected results has the maximum entropy, the inquiry engine selects the experiment that maximizes the expected information gain. The coupled inference and inquiry engines constitute an autonomous learning method for scientific exploration. We apply it to a robotic arm to demonstrate the efficacy of the method. Optimizing inquiry involves searching for an experiment that promises, on average, to be maximally informative. If the set of potential experiments is described by many parameters, the search involves a high-dimensional entropy space. In such cases, a brute force search method will be slow and computationally expensive. We develop an entropy-based search algorithm, called nested entropy sampling, to select the most informative experiment. This helps to reduce the number of computations necessary to find the optimal experiment. We also extended the method of maximizing entropy, and developed a method of maximizing joint entropy so that it could be used as a principle of collaboration between two robots. This is a major achievement of this thesis, as it allows the information-based collaboration between two robotic units towards a same

  17. Selection of long oligonucleotides for gene expression microarrays using weighted rank-sum strategy

    Directory of Open Access Journals (Sweden)

    Preiser Peter

    2007-09-01

    Full Text Available Abstract Background The design of long oligonucleotides for spotted DNA microarrays requires detailed attention to ensure their optimal performance in the hybridization process. The main challenge is to select an optimal oligonucleotide element that represents each genetic locus/gene in the genome and is unique, devoid of internal structures and repetitive sequences and its Tm is uniform with all other elements on the microarray. Currently, all of the publicly available programs for DNA long oligonucleotide microarray selection utilize various combinations of cutoffs in which each parameter (uniqueness, Tm, and secondary structure is evaluated and filtered individually. The use of the cutoffs can, however, lead to information loss and to selection of suboptimal oligonucleotides, especially for genomes with extreme distribution of the GC content, a large proportion of repetitive sequences or the presence of large gene families with highly homologous members. Results Here we present the program OligoRankPick which is using a weighted rank-based strategy to select microarray oligonucleotide elements via an integer weighted linear function. This approach optimizes the selection criteria (weight score for each gene individually, accommodating variable properties of the DNA sequence along the genome. The designed algorithm was tested using three microbial genomes Escherichia coli, Saccharomyces cerevisiae and the human malaria parasite species Plasmodium falciparum. In comparison to other published algorithms OligoRankPick provides significant improvements in oligonucleotide design for all three genomes with the most significant improvements observed in the microarray design for P. falciparum whose genome is characterized by large fluctuations of GC content, and abundant gene duplications. Conclusion OligoRankPick is an efficient tool for the design of long oligonucleotide DNA microarrays which does not rely on direct oligonucleotide exclusion by

  18. GOrilla: a tool for discovery and visualization of enriched GO terms in ranked gene lists

    Directory of Open Access Journals (Sweden)

    Steinfeld Israel

    2009-02-01

    Full Text Available Abstract Background Since the inception of the GO annotation project, a variety of tools have been developed that support exploring and searching the GO database. In particular, a variety of tools that perform GO enrichment analysis are currently available. Most of these tools require as input a target set of genes and a background set and seek enrichment in the target set compared to the background set. A few tools also exist that support analyzing ranked lists. The latter typically rely on simulations or on union-bound correction for assigning statistical significance to the results. Results GOrilla is a web-based application that identifies enriched GO terms in ranked lists of genes, without requiring the user to provide explicit target and background sets. This is particularly useful in many typical cases where genomic data may be naturally represented as a ranked list of genes (e.g. by level of expression or of differential expression. GOrilla employs a flexible threshold statistical approach to discover GO terms that are significantly enriched at the top of a ranked gene list. Building on a complete theoretical characterization of the underlying distribution, called mHG, GOrilla computes an exact p-value for the observed enrichment, taking threshold multiple testing into account without the need for simulations. This enables rigorous statistical analysis of thousand of genes and thousands of GO terms in order of seconds. The output of the enrichment analysis is visualized as a hierarchical structure, providing a clear view of the relations between enriched GO terms. Conclusion GOrilla is an efficient GO analysis tool with unique features that make a useful addition to the existing repertoire of GO enrichment tools. GOrilla's unique features and advantages over other threshold free enrichment tools include rigorous statistics, fast running time and an effective graphical representation. GOrilla is publicly available at: http://cbl-gorilla.cs.technion.ac.il

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

    Science.gov (United States)

    Mallik, Saurav; Maulik, Ujjwal

    2015-10-01

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

  20. Netter: re-ranking gene network inference predictions using structural network properties.

    Science.gov (United States)

    Ruyssinck, Joeri; Demeester, Piet; Dhaene, Tom; Saeys, Yvan

    2016-02-09

    Many algorithms have been developed to infer the topology of gene regulatory networks from gene expression data. These methods typically produce a ranking of links between genes with associated confidence scores, after which a certain threshold is chosen to produce the inferred topology. However, the structural properties of the predicted network do not resemble those typical for a gene regulatory network, as most algorithms only take into account connections found in the data and do not include known graph properties in their inference process. This lowers the prediction accuracy of these methods, limiting their usability in practice. We propose a post-processing algorithm which is applicable to any confidence ranking of regulatory interactions obtained from a network inference method which can use, inter alia, graphlets and several graph-invariant properties to re-rank the links into a more accurate prediction. To demonstrate the potential of our approach, we re-rank predictions of six different state-of-the-art algorithms using three simple network properties as optimization criteria and show that Netter can improve the predictions made on both artificially generated data as well as the DREAM4 and DREAM5 benchmarks. Additionally, the DREAM5 E.coli. community prediction inferred from real expression data is further improved. Furthermore, Netter compares favorably to other post-processing algorithms and is not restricted to correlation-like predictions. Lastly, we demonstrate that the performance increase is robust for a wide range of parameter settings. Netter is available at http://bioinformatics.intec.ugent.be. Network inference from high-throughput data is a long-standing challenge. In this work, we present Netter, which can further refine network predictions based on a set of user-defined graph properties. Netter is a flexible system which can be applied in unison with any method producing a ranking from omics data. It can be tailored to specific prior

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

    Directory of Open Access Journals (Sweden)

    Licamele Louis

    2010-03-01

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

  2. Effects of sample size on differential gene expression, rank order and prediction accuracy of a gene signature.

    Directory of Open Access Journals (Sweden)

    Cynthia Stretch

    Full Text Available Top differentially expressed gene lists are often inconsistent between studies and it has been suggested that small sample sizes contribute to lack of reproducibility and poor prediction accuracy in discriminative models. We considered sex differences (69♂, 65 ♀ in 134 human skeletal muscle biopsies using DNA microarray. The full dataset and subsamples (n = 10 (5 ♂, 5 ♀ to n = 120 (60 ♂, 60 ♀ thereof were used to assess the effect of sample size on the differential expression of single genes, gene rank order and prediction accuracy. Using our full dataset (n = 134, we identified 717 differentially expressed transcripts (p<0.0001 and we were able predict sex with ~90% accuracy, both within our dataset and on external datasets. Both p-values and rank order of top differentially expressed genes became more variable using smaller subsamples. For example, at n = 10 (5 ♂, 5 ♀, no gene was considered differentially expressed at p<0.0001 and prediction accuracy was ~50% (no better than chance. We found that sample size clearly affects microarray analysis results; small sample sizes result in unstable gene lists and poor prediction accuracy. We anticipate this will apply to other phenotypes, in addition to sex.

  3. A simple approach to ranking differentially expressed gene expression time courses through Gaussian process regression.

    Science.gov (United States)

    Kalaitzis, Alfredo A; Lawrence, Neil D

    2011-05-20

    The analysis of gene expression from time series underpins many biological studies. Two basic forms of analysis recur for data of this type: removing inactive (quiet) genes from the study and determining which genes are differentially expressed. Often these analysis stages are applied disregarding the fact that the data is drawn from a time series. In this paper we propose a simple model for accounting for the underlying temporal nature of the data based on a Gaussian process. We review Gaussian process (GP) regression for estimating the continuous trajectories underlying in gene expression time-series. We present a simple approach which can be used to filter quiet genes, or for the case of time series in the form of expression ratios, quantify differential expression. We assess via ROC curves the rankings produced by our regression framework and compare them to a recently proposed hierarchical Bayesian model for the analysis of gene expression time-series (BATS). We compare on both simulated and experimental data showing that the proposed approach considerably outperforms the current state of the art. Gaussian processes offer an attractive trade-off between efficiency and usability for the analysis of microarray time series. The Gaussian process framework offers a natural way of handling biological replicates and missing values and provides confidence intervals along the estimated curves of gene expression. Therefore, we believe Gaussian processes should be a standard tool in the analysis of gene expression time series.

  4. EasyGene – a prokaryotic gene finder that ranks ORFs by statistical significance

    DEFF Research Database (Denmark)

    Larsen, Thomas Schou; Krogh, Anders Stærmose

    2003-01-01

    annotated as genes.Results: In this paper, we present a new automated gene-finding method, EasyGene, which estimates the statistical significance of a predicted gene. The gene finder is based on a hidden Markov model (HMM) that is automatically estimated for a new genome. Using extensions of similarities...... is the expected number of ORFs in one megabase of random sequence at the same significance level or better, where the random sequence has the same statistics as the genome in the sense of a third order Markov chain.Conclusions: The result is a flexible gene finder whose overall performance matches or exceeds...

  5. An Entropy-Based Network Anomaly Detection Method

    Directory of Open Access Journals (Sweden)

    Przemysław Bereziński

    2015-04-01

    Full Text Available Data mining is an interdisciplinary subfield of computer science involving methods at the intersection of artificial intelligence, machine learning and statistics. One of the data mining tasks is anomaly detection which is the analysis of large quantities of data to identify items, events or observations which do not conform to an expected pattern. Anomaly detection is applicable in a variety of domains, e.g., fraud detection, fault detection, system health monitoring but this article focuses on application of anomaly detection in the field of network intrusion detection.The main goal of the article is to prove that an entropy-based approach is suitable to detect modern botnet-like malware based on anomalous patterns in network. This aim is achieved by realization of the following points: (i preparation of a concept of original entropy-based network anomaly detection method, (ii implementation of the method, (iii preparation of original dataset, (iv evaluation of the method.

  6. EasyGene – a prokaryotic gene finder that ranks ORFs by statistical significance

    Directory of Open Access Journals (Sweden)

    Larsen Thomas

    2003-06-01

    Full Text Available Abstract Background Contrary to other areas of sequence analysis, a measure of statistical significance of a putative gene has not been devised to help in discriminating real genes from the masses of random Open Reading Frames (ORFs in prokaryotic genomes. Therefore, many genomes have too many short ORFs annotated as genes. Results In this paper, we present a new automated gene-finding method, EasyGene, which estimates the statistical significance of a predicted gene. The gene finder is based on a hidden Markov model (HMM that is automatically estimated for a new genome. Using extensions of similarities in Swiss-Prot, a high quality training set of genes is automatically extracted from the genome and used to estimate the HMM. Putative genes are then scored with the HMM, and based on score and length of an ORF, the statistical significance is calculated. The measure of statistical significance for an ORF is the expected number of ORFs in one megabase of random sequence at the same significance level or better, where the random sequence has the same statistics as the genome in the sense of a third order Markov chain. Conclusions The result is a flexible gene finder whose overall performance matches or exceeds other methods. The entire pipeline of computer processing from the raw input of a genome or set of contigs to a list of putative genes with significance is automated, making it easy to apply EasyGene to newly sequenced organisms. EasyGene with pre-trained models can be accessed at http://www.cbs.dtu.dk/services/EasyGene.

  7. Enhanced gene ranking approaches using modified trace ratio algorithm for gene expression data

    Directory of Open Access Journals (Sweden)

    Shruti Mishra

    Full Text Available Microarray technology enables the understanding and investigation of gene expression levels by analyzing high dimensional datasets that contain few samples. Over time, microarray expression data have been collected for studying the underlying biological mechanisms of disease. One such application for understanding the mechanism is by constructing a gene regulatory network (GRN. One of the foremost key criteria for GRN discovery is gene selection. Choosing a generous set of genes for the structure of the network is highly desirable. For this role, two suitable methods were proposed for selection of appropriate genes. The first approach comprises a gene selection method called Information gain, where the dataset is reformed and fused with another distinct algorithm called Trace Ratio (TR. Our second method is the implementation of our projected modified TR algorithm, where the scoring base for finding weight matrices has been re-designed. Both the methods' efficiency was shown with different classifiers that include variants of the Artificial Neural Network classifier, such as Resilient Propagation, Quick Propagation, Back Propagation, Manhattan Propagation and Radial Basis Function Neural Network and also the Support Vector Machine (SVM classifier. In the study, it was confirmed that both of the proposed methods worked well and offered high accuracy with a lesser number of iterations as compared to the original Trace Ratio algorithm. Keywords: Gene regulatory network, Gene selection, Information gain, Trace ratio, Canonical correlation analysis, Classification

  8. PosMed: ranking genes and bioresources based on Semantic Web Association Study

    Science.gov (United States)

    Makita, Yuko; Kobayashi, Norio; Yoshida, Yuko; Doi, Koji; Mochizuki, Yoshiki; Nishikata, Koro; Matsushima, Akihiro; Takahashi, Satoshi; Ishii, Manabu; Takatsuki, Terue; Bhatia, Rinki; Khadbaatar, Zolzaya; Watabe, Hajime; Masuya, Hiroshi; Toyoda, Tetsuro

    2013-01-01

    Positional MEDLINE (PosMed; http://biolod.org/PosMed) is a powerful Semantic Web Association Study engine that ranks biomedical resources such as genes, metabolites, diseases and drugs, based on the statistical significance of associations between user-specified phenotypic keywords and resources connected directly or inferentially through a Semantic Web of biological databases such as MEDLINE, OMIM, pathways, co-expressions, molecular interactions and ontology terms. Since 2005, PosMed has long been used for in silico positional cloning studies to infer candidate disease-responsible genes existing within chromosomal intervals. PosMed is redesigned as a workbench to discover possible functional interpretations for numerous genetic variants found from exome sequencing of human disease samples. We also show that the association search engine enhances the value of mouse bioresources because most knockout mouse resources have no phenotypic annotation, but can be associated inferentially to phenotypes via genes and biomedical documents. For this purpose, we established text-mining rules to the biomedical documents by careful human curation work, and created a huge amount of correct linking between genes and documents. PosMed associates any phenotypic keyword to mouse resources with 20 public databases and four original data sets as of May 2013. PMID:23761449

  9. Deceiving entropy-based DoS detection

    Science.gov (United States)

    Özçelik, Ä.°lker; Brooks, Richard R.

    2014-06-01

    Denial of Service (DoS) attacks disable network services for legitimate users. A McAfee report shows that eight out of ten Critical Infrastructure Providers (CIPs) surveyed had a significant Distributed DoS (DDoS) attack in 2010.1 Researchers proposed many approaches for detecting these attacks in the past decade. Anomaly based DoS detection is the most common. In this approach, the detector uses statistical features; such as the entropy of incoming packet header fields like source IP addresses or protocol type. It calculates the observed statistical feature and triggers an alarm if an extreme deviation occurs. However, intrusion detection systems (IDS) using entropy based detection can be fooled by spoofing. An attacker can sniff the network to collect header field data of network packets coming from distributed nodes on the Internet and fuses them to calculate the entropy of normal background traffic. Then s/he can spoof attack packets to keep the entropy value in the expected range during the attack. In this study, we present a proof of concept entropy spoofing attack that deceives entropy based detection approaches. Our preliminary results show that spoofing attacks cause significant detection performance degradation.

  10. Relating quantum coherence and correlations with entropy-based measures.

    Science.gov (United States)

    Wang, Xiao-Li; Yue, Qiu-Ling; Yu, Chao-Hua; Gao, Fei; Qin, Su-Juan

    2017-09-21

    Quantum coherence and quantum correlations are important quantum resources for quantum computation and quantum information. In this paper, using entropy-based measures, we investigate the relationships between quantum correlated coherence, which is the coherence between subsystems, and two main kinds of quantum correlations as defined by quantum discord as well as quantum entanglement. In particular, we show that quantum discord and quantum entanglement can be well characterized by quantum correlated coherence. Moreover, we prove that the entanglement measure formulated by quantum correlated coherence is lower and upper bounded by the relative entropy of entanglement and the entanglement of formation, respectively, and equal to the relative entropy of entanglement for all the maximally correlated states.

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

    Science.gov (United States)

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

    2016-05-01

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

  12. Filtering and ranking techniques for automated selection of high-quality 16S rRNA gene sequences.

    Science.gov (United States)

    De Smet, Wim; De Loof, Karel; De Vos, Paul; Dawyndt, Peter; De Baets, Bernard

    2013-12-01

    StrainInfo has augmented its type strain and species/subspecies passports with a recommendation for a high-quality 16S rRNA gene sequence available from the public sequence databases. These recommendations are generated by an automated pipeline that collects all candidate 16S rRNA gene sequences for a prokaryotic type strain, filters out low-quality sequences and retains a high-quality sequence from the remaining pool. Due to thorough automation, recommendations can be renewed daily using the latest updates of the public sequence databases and the latest species descriptions. We discuss the quality criteria constructed to filter and rank available 16S rRNA gene sequences, and show how a partially ordered set (poset) ranking algorithm can be applied to solve the multi-criteria ranking problem of selecting the best candidate sequence. The proof of concept of the recommender system is validated by comparing the results of automated selection with an expert selection made in the All-Species Living Tree Project. Based on these validation results, the pipeline may reliably be applied for non-type strains and developed further for the automated selection of housekeeping genes. Copyright © 2013 Elsevier GmbH. All rights reserved.

  13. Entropy-Based Privacy against Profiling of User Mobility

    Directory of Open Access Journals (Sweden)

    Alicia Rodriguez-Carrion

    2015-06-01

    Full Text Available Location-based services (LBSs flood mobile phones nowadays, but their use poses an evident privacy risk. The locations accompanying the LBS queries can be exploited by the LBS provider to build the user profile of visited locations, which might disclose sensitive data, such as work or home locations. The classic concept of entropy is widely used to evaluate privacy in these scenarios, where the information is represented as a sequence of independent samples of categorized data. However, since the LBS queries might be sent very frequently, location profiles can be improved by adding temporal dependencies, thus becoming mobility profiles, where location samples are not independent anymore and might disclose the user’s mobility patterns. Since the time dimension is factored in, the classic entropy concept falls short of evaluating the real privacy level, which depends also on the time component. Therefore, we propose to extend the entropy-based privacy metric to the use of the entropy rate to evaluate mobility profiles. Then, two perturbative mechanisms are considered to preserve locations and mobility profiles under gradual utility constraints. We further use the proposed privacy metric and compare it to classic ones to evaluate both synthetic and real mobility profiles when the perturbative methods proposed are applied. The results prove the usefulness of the proposed metric for mobility profiles and the need for tailoring the perturbative methods to the features of mobility profiles in order to improve privacy without completely loosing utility.

  14. Entropy-based particle correspondence for shape populations.

    Science.gov (United States)

    Oguz, Ipek; Cates, Josh; Datar, Manasi; Paniagua, Beatriz; Fletcher, Thomas; Vachet, Clement; Styner, Martin; Whitaker, Ross

    2016-07-01

    Statistical shape analysis of anatomical structures plays an important role in many medical image analysis applications such as understanding the structural changes in anatomy in various stages of growth or disease. Establishing accurate correspondence across object populations is essential for such statistical shape analysis studies. In this paper, we present an entropy-based correspondence framework for computing point-based correspondence among populations of surfaces in a groupwise manner. This robust framework is parameterization-free and computationally efficient. We review the core principles of this method as well as various extensions to deal effectively with surfaces of complex geometry and application-driven correspondence metrics. We apply our method to synthetic and biological datasets to illustrate the concepts proposed and compare the performance of our framework to existing techniques. Through the numerous extensions and variations presented here, we create a very flexible framework that can effectively handle objects of various topologies, multi-object complexes, open surfaces, and objects of complex geometry such as high-curvature regions or extremely thin features.

  15. Google goes cancer: improving outcome prediction for cancer patients by network-based ranking of marker genes.

    Directory of Open Access Journals (Sweden)

    Christof Winter

    Full Text Available Predicting the clinical outcome of cancer patients based on the expression of marker genes in their tumors has received increasing interest in the past decade. Accurate predictors of outcome and response to therapy could be used to personalize and thereby improve therapy. However, state of the art methods used so far often found marker genes with limited prediction accuracy, limited reproducibility, and unclear biological relevance. To address this problem, we developed a novel computational approach to identify genes prognostic for outcome that couples gene expression measurements from primary tumor samples with a network of known relationships between the genes. Our approach ranks genes according to their prognostic relevance using both expression and network information in a manner similar to Google's PageRank. We applied this method to gene expression profiles which we obtained from 30 patients with pancreatic cancer, and identified seven candidate marker genes prognostic for outcome. Compared to genes found with state of the art methods, such as Pearson correlation of gene expression with survival time, we improve the prediction accuracy by up to 7%. Accuracies were assessed using support vector machine classifiers and Monte Carlo cross-validation. We then validated the prognostic value of our seven candidate markers using immunohistochemistry on an independent set of 412 pancreatic cancer samples. Notably, signatures derived from our candidate markers were independently predictive of outcome and superior to established clinical prognostic factors such as grade, tumor size, and nodal status. As the amount of genomic data of individual tumors grows rapidly, our algorithm meets the need for powerful computational approaches that are key to exploit these data for personalized cancer therapies in clinical practice.

  16. Entropy-based probabilistic fatigue damage prognosis and algorithmic performance comparison

    Data.gov (United States)

    National Aeronautics and Space Administration — In this paper, a maximum entropy-based general framework for probabilistic fatigue damage prognosis is investigated. The proposed methodology is based on an...

  17. Entropy-based Probabilistic Fatigue Damage Prognosis and Algorithmic Performance Comparison

    Data.gov (United States)

    National Aeronautics and Space Administration — In this paper, a maximum entropy-based general framework for probabilistic fatigue damage prognosis is investigated. The proposed methodology is based on an...

  18. Text mining effectively scores and ranks the literature for improving chemical-gene-disease curation at the comparative toxicogenomics database.

    Science.gov (United States)

    Davis, Allan Peter; Wiegers, Thomas C; Johnson, Robin J; Lay, Jean M; Lennon-Hopkins, Kelley; Saraceni-Richards, Cynthia; Sciaky, Daniela; Murphy, Cynthia Grondin; Mattingly, Carolyn J

    2013-01-01

    The Comparative Toxicogenomics Database (CTD; http://ctdbase.org/) is a public resource that curates interactions between environmental chemicals and gene products, and their relationships to diseases, as a means of understanding the effects of environmental chemicals on human health. CTD provides a triad of core information in the form of chemical-gene, chemical-disease, and gene-disease interactions that are manually curated from scientific articles. To increase the efficiency, productivity, and data coverage of manual curation, we have leveraged text mining to help rank and prioritize the triaged literature. Here, we describe our text-mining process that computes and assigns each article a document relevancy score (DRS), wherein a high DRS suggests that an article is more likely to be relevant for curation at CTD. We evaluated our process by first text mining a corpus of 14,904 articles triaged for seven heavy metals (cadmium, cobalt, copper, lead, manganese, mercury, and nickel). Based upon initial analysis, a representative subset corpus of 3,583 articles was then selected from the 14,094 articles and sent to five CTD biocurators for review. The resulting curation of these 3,583 articles was analyzed for a variety of parameters, including article relevancy, novel data content, interaction yield rate, mean average precision, and biological and toxicological interpretability. We show that for all measured parameters, the DRS is an effective indicator for scoring and improving the ranking of literature for the curation of chemical-gene-disease information at CTD. Here, we demonstrate how fully incorporating text mining-based DRS scoring into our curation pipeline enhances manual curation by prioritizing more relevant articles, thereby increasing data content, productivity, and efficiency.

  19. Text Mining Effectively Scores and Ranks the Literature for Improving Chemical-Gene-Disease Curation at the Comparative Toxicogenomics Database

    Science.gov (United States)

    Johnson, Robin J.; Lay, Jean M.; Lennon-Hopkins, Kelley; Saraceni-Richards, Cynthia; Sciaky, Daniela; Murphy, Cynthia Grondin; Mattingly, Carolyn J.

    2013-01-01

    The Comparative Toxicogenomics Database (CTD; http://ctdbase.org/) is a public resource that curates interactions between environmental chemicals and gene products, and their relationships to diseases, as a means of understanding the effects of environmental chemicals on human health. CTD provides a triad of core information in the form of chemical-gene, chemical-disease, and gene-disease interactions that are manually curated from scientific articles. To increase the efficiency, productivity, and data coverage of manual curation, we have leveraged text mining to help rank and prioritize the triaged literature. Here, we describe our text-mining process that computes and assigns each article a document relevancy score (DRS), wherein a high DRS suggests that an article is more likely to be relevant for curation at CTD. We evaluated our process by first text mining a corpus of 14,904 articles triaged for seven heavy metals (cadmium, cobalt, copper, lead, manganese, mercury, and nickel). Based upon initial analysis, a representative subset corpus of 3,583 articles was then selected from the 14,094 articles and sent to five CTD biocurators for review. The resulting curation of these 3,583 articles was analyzed for a variety of parameters, including article relevancy, novel data content, interaction yield rate, mean average precision, and biological and toxicological interpretability. We show that for all measured parameters, the DRS is an effective indicator for scoring and improving the ranking of literature for the curation of chemical-gene-disease information at CTD. Here, we demonstrate how fully incorporating text mining-based DRS scoring into our curation pipeline enhances manual curation by prioritizing more relevant articles, thereby increasing data content, productivity, and efficiency. PMID:23613709

  20. Tensor Rank

    OpenAIRE

    Erdtman, Elias; Jönsson, Carl

    2012-01-01

    This master's thesis addresses numerical methods of computing the typical ranks of tensors over the real numbers and explores some properties of tensors over finite fields. We present three numerical methods to compute typical tensor rank. Two of these have already been published and can be used to calculate the lowest typical ranks of tensors and an approximate percentage of how many tensors have the lowest typical ranks (for some tensor formats), respectively. The third method was developed...

  1. Phylogeny, historical biogeography, and taxonomic ranking of Parnassiinae (Lepidoptera, Papilionidae) based on morphology and seven genes.

    Science.gov (United States)

    Nazari, Vazrick; Zakharov, Evgueni V; Sperling, Felix A H

    2007-01-01

    We tested the taxonomic utility of morphology and seven mitochondrial or nuclear genes in a phylogenetic reconstruction of swallowtail butterflies in the subfamily Parnassiinae. Our data included 236 morphological characters and DNA sequences for seven genes that are commonly used to infer lepidopteran relationships (COI+COII, ND5, ND1, 16S, EF-1alpha, and wg; total 5775 bp). Nuclear genes performed best for inferring phylogenies, particularly at higher taxonomic levels, while there was substantial variation in performance among mitochondrial genes. Multiple analyses of molecular data (MP, ML and Bayesian) consistently produced a tree topology different from that obtained by morphology alone. Based on molecular evidence, sister-group relationships were confirmed between the genera Hypermnestra and Parnassius, as well as between Archon and Luehdorfia, while the monophyly of the subfamily was weakly supported. We recognize three tribes within Parnassiinae, with Archon and Luehdorfia forming the tribe Luehdorfiini Tutt, 1896 [stat. rev.]. Three fossil taxa were incorporated into a molecular clock analysis with biogeographic time constraints. Based on dispersal-vicariance (DIVA) analysis, the most recent common ancestor of Parnassiinae occurred in the Iranian Plateau and Central Asia to China. Early diversification of Parnassiinae took place at the same time that India collided into Eurasia, 65-42 million years ago.

  2. ENTVis: A Visual Analytic Tool for Entropy-Based Network Traffic Anomaly Detection.

    Science.gov (United States)

    Zhou, Fangfang; Huang, Wei; Zhao, Ying; Shi, Yang; Liang, Xing; Fan, Xiaoping

    2015-01-01

    Entropy-based traffic metrics have received substantial attention in network traffic anomaly detection because entropy can provide fine-grained metrics of traffic distribution characteristics. However, some practical issues--such as ambiguity, lack of detailed distribution information, and a large number of false positives--affect the application of entropy-based traffic anomaly detection. In this work, we introduce a visual analytic tool called ENTVis to help users understand entropy-based traffic metrics and achieve accurate traffic anomaly detection. ENTVis provides three coordinated views and rich interactions to support a coherent visual analysis on multiple perspectives: the timeline group view for perceiving situations and finding hints of anomalies, the Radviz view for clustering similar anomalies in a period, and the matrix view for understanding traffic distributions and diagnosing anomalies in detail. Several case studies have been performed to verify the usability and effectiveness of our method. A further evaluation was conducted via expert review.

  3. Ranking of disease gene associations from large corpora of scientific publications

    OpenAIRE

    ter Horst, Hendrik

    2015-01-01

    The extraction of disease-gene associations from biomedical publications is a widely inves- tigated field of research. In previous work, a frequent method was to implement natural language processing tools that use semantic information to find such associations. How- ever, most of these approaches are restricted to single documents. Retrieval systems that predict novel associations across various documents often lack the ability to deal with the huge amount of resulting candida...

  4. 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

  5. Multiscale Permutation Entropy Based Rolling Bearing Fault Diagnosis

    Directory of Open Access Journals (Sweden)

    Jinde Zheng

    2014-01-01

    Full Text Available A new rolling bearing fault diagnosis approach based on multiscale permutation entropy (MPE, Laplacian score (LS, and support vector machines (SVMs is proposed in this paper. Permutation entropy (PE was recently proposed and defined to measure the randomicity and detect dynamical changes of time series. However, for the complexity of mechanical systems, the randomicity and dynamic changes of the vibration signal will exist in different scales. Thus, the definition of MPE is introduced and employed to extract the nonlinear fault characteristics from the bearing vibration signal in different scales. Besides, the SVM is utilized to accomplish the fault feature classification to fulfill diagnostic procedure automatically. Meanwhile, in order to avoid a high dimension of features, the Laplacian score (LS is used to refine the feature vector by ranking the features according to their importance and correlations with the main fault information. Finally, the rolling bearing fault diagnosis method based on MPE, LS, and SVM is proposed and applied to the experimental data. The experimental data analysis results indicate that the proposed method could identify the fault categories effectively.

  6. A two-phase copula entropy-based multiobjective optimization approach to hydrometeorological gauge network design

    Science.gov (United States)

    Xu, Pengcheng; Wang, Dong; Singh, Vijay P.; Wang, Yuankun; Wu, Jichun; Wang, Lachun; Zou, Xinqing; Chen, Yuanfang; Chen, Xi; Liu, Jiufu; Zou, Ying; He, Ruimin

    2017-12-01

    Hydrometeorological data are needed for obtaining point and areal mean, quantifying the spatial variability of hydrometeorological variables, and calibration and verification of hydrometeorological models. Hydrometeorological networks are utilized to collect such data. Since data collection is expensive, it is essential to design an optimal network based on the minimal number of hydrometeorological stations in order to reduce costs. This study proposes a two-phase copula entropy- based multiobjective optimization approach that includes: (1) copula entropy-based directional information transfer (CDIT) for clustering the potential hydrometeorological gauges into several groups, and (2) multiobjective method for selecting the optimal combination of gauges for regionalized groups. Although entropy theory has been employed for network design before, the joint histogram method used for mutual information estimation has several limitations. The copula entropy-based mutual information (MI) estimation method is shown to be more effective for quantifying the uncertainty of redundant information than the joint histogram (JH) method. The effectiveness of this approach is verified by applying to one type of hydrometeorological gauge network, with the use of three model evaluation measures, including Nash-Sutcliffe Coefficient (NSC), arithmetic mean of the negative copula entropy (MNCE), and MNCE/NSC. Results indicate that the two-phase copula entropy-based multiobjective technique is capable of evaluating the performance of regional hydrometeorological networks and can enable decision makers to develop strategies for water resources management.

  7. An Entropy-Based Measure for Assessing Fuzziness in Logistic Regression

    Science.gov (United States)

    Weiss, Brandi A.; Dardick, William

    2016-01-01

    This article introduces an entropy-based measure of data-model fit that can be used to assess the quality of logistic regression models. Entropy has previously been used in mixture-modeling to quantify how well individuals are classified into latent classes. The current study proposes the use of entropy for logistic regression models to quantify…

  8. Assessment of OPG/RANK/RANKL gene expression levels in peripheral blood mononuclear cells (PBMC) after treatment with strontium ranelate and ibandronate in patients with postmenopausal osteoporosis.

    Science.gov (United States)

    Stuss, Michal; Rieske, Piotr; Cegłowska, Agnieszka; Stêpień-Kłos, Wioletta; Liberski, Paweł P; Brzeziańska, Ewa; Sewerynek, Ewa

    2013-05-01

    Recent research results have confirmed the high significance of the OPG/RANK/RANKL system in the development of bone diseases. The aim of the reported study was to assess gene expression levels of the OPG/RANK/RANKL system in peripheral blood mononuclear cells (PBMCs) after strontium ranelate (SR) and ibandronate administered to patients with postmenopausal osteoporosis. A total of 89 postmenopausal women, aged 51 to 85 years, patients of the Outpatient Clinic of Osteoporosis of the Military Teaching Hospital in Lodz, were enrolled into the study. The patients were randomly assigned to different medical therapies: ibandronate and SR. Patients of the control group received only calcium and vitamin D₃ supplements. Patient visits were repeated after 3 and 6 months. Measurements of serum alkaline phosphatase concentrations and of RNA expression in PBMCs as well as of total serum calcium and phosphate levels and of their 24-hour urine excretion rates were carried out in material, collected at baseline and after 3 and 6 months of the therapy. Densitometry of the left hip and of the lumbar spine was done at the baseline visit and after 6 months. The differences in gene expressions of RANKL and RANK were not significant during the study period and did not differ between the groups in a statistically significant manner. No OPG gene expression was observed in PBMCs of patients in any of the studied groups and at any time point. The tendency of correlation (P = .07) was observed between decreasing RANK gene expression and increasing bone mineral density in the patients treated with SR. Both ibandronate and SR do not seem to cause any significant changes in gene expression levels of OPG/RANK/RANKL in PBMCs during the first 6 months of treatment.

  9. Feature extraction and learning using context cue and Rényi entropy based mutual information

    DEFF Research Database (Denmark)

    Pan, Hong; Olsen, Søren Ingvor; Zhu, Yaping

    2015-01-01

    improving the robustness of CKD. For feature learning and reduction, we propose a novel codebook learning method, based on a Rényi quadratic entropy based mutual information measure called Cauchy-Schwarz Quadratic Mutual Information (CSQMI), to learn a compact and discriminative CKD codebook. Projecting......Feature extraction and learning play a critical role for visual perception tasks. We focus on improving the robustness of the kernel descriptors (KDES) by embedding context cues and further learning a compact and discriminative feature codebook for feature reduction using Rényi entropy based mutual...... information. In particular, for feature extraction, we develop a new set of kernel descriptors−Context Kernel Descriptors (CKD), which enhance the original KDES by embedding the spatial context into the descriptors. Context cues contained in the context kernel enforce some degree of spatial consistency, thus...

  10. Optimal Entropy-Based Cooperative Spectrum Sensing for Maritime Cognitive Radio Networks

    Directory of Open Access Journals (Sweden)

    Waleed Ejaz

    2013-11-01

    Full Text Available Maritime cognitive radio networks (MCRNs have recently been proposed for opportunistic utilization of the licensed band. Spectrum sensing is one of the key issues for the successful deployment of the MCRNs. The maritime environment is unique in terms of radio wave propagation over water, surface reflection and wave occlusions. In order to deal with the challenging maritime environment, we proposed an optimal entropy-based cooperative spectrum sensing. As the results of spectrum sensing are sensitive to the number of samples in an entropy-based local detection scheme, we first calculated the optimal number of samples. Next, a cooperative spectrum sensing scheme considering the conditions of the sea environment is proposed. Finally, the throughput optimization of the m-out-of-n rule is considered. Results revealed that although the existing schemes work well for the lower sea states, they fail to perform at higher sea states. Moreover, simulation results also indicated the robustness of the entropy-based scheme and the proposed cooperative spectrum sensing scheme at higher sea states in comparison with the traditional energy detector.

  11. Sequential rank agreement methods for comparison of ranked lists

    DEFF Research Database (Denmark)

    Ekstrøm, Claus Thorn; Gerds, Thomas Alexander; Jensen, Andreas Kryger

    2015-01-01

    The comparison of alternative rankings of a set of items is a general and prominent task in applied statistics. Predictor variables are ranked according to magnitude of association with an outcome, prediction models rank subjects according to the personalized risk of an event, and genetic studies...... are illustrated using gene rankings, and using data from two Danish ovarian cancer studies where we assess the within and between agreement of different statistical classification methods.......The comparison of alternative rankings of a set of items is a general and prominent task in applied statistics. Predictor variables are ranked according to magnitude of association with an outcome, prediction models rank subjects according to the personalized risk of an event, and genetic studies...

  12. ENTROPY-BASED FUZZY AHP SEBAGAI PENDUKUNG KEPUTUSAN PENEMPATAN BIDAN DI KOTA BANJARBARU

    Directory of Open Access Journals (Sweden)

    Siti Hatimah Rahmadaniah

    2016-04-01

    Full Text Available Banjarbaru City Health Office is a government agency that plays an important role in health development in Banjarbaru. Support system midwife placement in the Health Service Banjarbaru done by following the specified criteria. However, the system has not been run in accordance with these criteria, but every midwife who will be placed in primary and villages are given the freedom to choose from one health center placement options, and direct placement was decided on the option selected health centers midwives. Because of the ineffectiveness of the existing system at the Department of Health Banjarbaru it will be designed and built "Midwives Placement Decision Support Systems in Banjarbaru with Method Using Entropy-Based Fuzzy AHP (Analytical Hierarchy Process" to determine the placement of midwives in accordance with the criteria that have been determined. From the research and observations of the system that has been created, it can be seen that the Decision Support System Placement Midwives using Entropy-Based Fuzzy AHP is a decision that is in accordance with the number of midwives needed by each health center. Keywords : Decision Support System , Placement Midwives , Entropy Method. Dinas Kesehatan Kota Banjarbaru merupakan suatu instansi pemerintah yang berperan penting dalam pembangunan kesehatan di Kota Banjarbaru . Sistem pendukung penempatan bidan di Dinas Kesehatan Banjarbaru dilakukan dengan mengikuti kreteria yang sudah ditentukan. Akan tetapi sistem tersebut belum berjalan sesuai dengan kriteria tersebut melainkan setiap bidan yang akan ditempatkan dipuskesmas dan desa diberikan kebebasan untuk memilih dari salah satu puskesmas pilihan penempatan, dan langsung diputuskan penempatan pada puskesmas pilihan yang dipilih bidan. Oleh karena tidak berjalannya sistem yang sudah ada pada Dinas Kesehatan Banjarbaru maka akan dirancang dan dibangun “Sistem Pendukung Keputusan Penempatan Bidan di Kota Banjarbaru dengan Menggunakan Metode

  13. Polymorphisms in the RANK/RANKL Genes and Their Effect on Bone Specific Prognosis in Breast Cancer Patients

    Directory of Open Access Journals (Sweden)

    Alexander Hein

    2014-01-01

    Full Text Available The receptor activator of NF-κB (RANK pathway is involved in bone health as well as breast cancer (BC pathogenesis and progression. Whereas the therapeutic implication of this pathway is established for the treatment of osteoporosis and bone metastases, the application in adjuvant BC is currently investigated. As genetic variants in this pathway have been described to influence bone health, aim of this study was the prognostic relevance of genetic variants in RANK and RANKL. Single nucleotide polymorphisms in RANK(L (rs1054016/rs1805034/rs35211496 were genotyped and analyzed with regard to bone metastasis-free survival (BMFS, disease-free survival, and overall survival for a retrospective cohort of 1251 patients. Cox proportional hazard models were built to examine the prognostic influence in addition to commonly established prognostic factors. The SNP rs1054016 seems to influence BMFS. Patients with two minor alleles had a more favorable prognosis than patients with at least one common allele (HR 0.37 (95% CI: 0.17, 0.84, whereas other outcome parameters remained unaffected. rs1805034 and rs35211496 had no prognostic relevance. The effect of rs1054016(RANKL adds to the evidence that the RANK pathway plays a role in BC pathogenesis and progression with respect to BMFS, emphasizing the connection between BC and bone health.

  14. On the Entropy Based Associative Memory Model with Higher-Order Correlations

    Directory of Open Access Journals (Sweden)

    Masahiro Nakagawa

    2010-01-01

    Full Text Available In this paper, an entropy based associative memory model will be proposed and applied to memory retrievals with an orthogonal learning model so as to compare with the conventional model based on the quadratic Lyapunov functional to be minimized during the retrieval process. In the present approach, the updating dynamics will be constructed on the basis of the entropy minimization strategy which may be reduced asymptotically to the above-mentioned conventional dynamics as a special case ignoring the higher-order correlations. According to the introduction of the entropy functional, one may involve higer-order correlation effects between neurons in a self-contained manner without any heuristic coupling coefficients as in the conventional manner. In fact we shall show such higher order coupling tensors are to be uniquely determined in the framework of the entropy based approach. From numerical results, it will be found that the presently proposed novel approach realizes much larger memory capacity than that of the quadratic Lyapunov functional approach, e.g., associatron.

  15. An Integrated Dictionary-Learning Entropy-Based Medical Image Fusion Framework

    Directory of Open Access Journals (Sweden)

    Guanqiu Qi

    2017-10-01

    Full Text Available Image fusion is widely used in different areas and can integrate complementary and relevant information of source images captured by multiple sensors into a unitary synthetic image. Medical image fusion, as an important image fusion application, can extract the details of multiple images from different imaging modalities and combine them into an image that contains complete and non-redundant information for increasing the accuracy of medical diagnosis and assessment. The quality of the fused image directly affects medical diagnosis and assessment. However, existing solutions have some drawbacks in contrast, sharpness, brightness, blur and details. This paper proposes an integrated dictionary-learning and entropy-based medical image-fusion framework that consists of three steps. First, the input image information is decomposed into low-frequency and high-frequency components by using a Gaussian filter. Second, low-frequency components are fused by weighted average algorithm and high-frequency components are fused by the dictionary-learning based algorithm. In the dictionary-learning process of high-frequency components, an entropy-based algorithm is used for informative blocks selection. Third, the fused low-frequency and high-frequency components are combined to obtain the final fusion results. The results and analyses of comparative experiments demonstrate that the proposed medical image fusion framework has better performance than existing solutions.

  16. Toward optimal feature selection using ranking methods and classification algorithms

    Directory of Open Access Journals (Sweden)

    Novaković Jasmina

    2011-01-01

    Full Text Available We presented a comparison between several feature ranking methods used on two real datasets. We considered six ranking methods that can be divided into two broad categories: statistical and entropy-based. Four supervised learning algorithms are adopted to build models, namely, IB1, Naive Bayes, C4.5 decision tree and the RBF network. We showed that the selection of ranking methods could be important for classification accuracy. In our experiments, ranking methods with different supervised learning algorithms give quite different results for balanced accuracy. Our cases confirm that, in order to be sure that a subset of features giving the highest accuracy has been selected, the use of many different indices is recommended.

  17. Ranking and characterization of established BMI and lipid associated loci as candidates for gene-environment interactions

    DEFF Research Database (Denmark)

    Shungin, Dmitry; Deng, Wei Q; Varga, Tibor V

    2017-01-01

    Phenotypic variance heterogeneity across genotypes at a single nucleotide polymorphism (SNP) may reflect underlying gene-environment (G×E) or gene-gene interactions. We modeled variance heterogeneity for blood lipids and BMI in up to 44,211 participants and investigated relationships between...

  18. Entropy Based Analysis of DNS Query Traffic in the Campus Network

    Directory of Open Access Journals (Sweden)

    Dennis Arturo Ludeña Romaña

    2008-10-01

    Full Text Available We carried out the entropy based study on the DNS query traffic from the campus network in a university through January 1st, 2006 to March 31st, 2007. The results are summarized, as follows: (1 The source IP addresses- and query keyword-based entropies change symmetrically in the DNS query traffic from the outside of the campus network when detecting the spam bot activity on the campus network. On the other hand (2, the source IP addresses- and query keywordbased entropies change similarly each other when detecting big DNS query traffic caused by prescanning or distributed denial of service (DDoS attack from the campus network. Therefore, we can detect the spam bot and/or DDoS attack bot by only watching DNS query access traffic.

  19. Risk Contagion in Chinese Banking Industry: A Transfer Entropy-Based Analysis

    Directory of Open Access Journals (Sweden)

    Jianping Li

    2013-12-01

    Full Text Available What is the impact of a bank failure on the whole banking industry? To resolve this issue, the paper develops a transfer entropy-based method to determine the interbank exposure matrix between banks. This method constructs the interbank market structure by calculating the transfer entropy matrix using bank stock price sequences. This paper also evaluates the stability of Chinese banking system by simulating the risk contagion process. This paper contributes to the literature on interbank contagion mainly in two ways: it establishes a convincing connection between interbank market and transfer entropy, and exploits the market information (stock price rather than presumptions to determine the interbank exposure matrix. Second, the empirical analysis provides an in depth understanding of the stability of the current Chinese banking system.

  20. An entropy-based method for noise reduction of liquid chromatography-mass spectrometry data.

    Science.gov (United States)

    Li, Yunfei; Qu, Haibin; Cheng, Yiyu

    2008-03-31

    Entropy-based methods have been extensively used to measure the uncertainty information in a variety of fields. In this article, a novel information theory-based method for reducing noise of liquid chromatography-mass spectrometry (LC/MS) data was developed. The uncertainty existed in the LC/MS chromatograms was captured and evaluated by information entropy. By comparing the information entropy computationally derived from mass chromatograms, the good quality chromatograms and the noisy chromatograms can be distinguished. The proposed method was applied in processing LC/MS data of "Jing-Zhi-Guan-Xin" troche which is a well-known preparation of traditional Chinese medicine (TCM). The obtained result indicated that this method is beneficial to reduce noise of LC/MS data of complicated chemical samples, such as TCM.

  1. Entropy-based generation of supervised neural networks for classification of structured patterns.

    Science.gov (United States)

    Tsai, Hsien-Leing; Lee, Shie-Jue

    2004-03-01

    Sperduti and Starita proposed a new type of neural network which consists of generalized recursive neurons for classification of structures. In this paper, we propose an entropy-based approach for constructing such neural networks for classification of acyclic structured patterns. Given a classification problem, the architecture, i.e., the number of hidden layers and the number of neurons in each hidden layer, and all the values of the link weights associated with the corresponding neural network are automatically determined. Experimental results have shown that the networks constructed by our method can have a better performance, with respect to network size, learning speed, or recognition accuracy, than the networks obtained by other methods.

  2. An Entropy-Based Adaptive Hybrid Particle Swarm Optimization for Disassembly Line Balancing Problems

    Directory of Open Access Journals (Sweden)

    Shanli Xiao

    2017-11-01

    Full Text Available In order to improve the product disassembly efficiency, the disassembly line balancing problem (DLBP is transformed into a problem of searching for the optimum path in the directed and weighted graph by constructing the disassembly hierarchy information graph (DHIG. Then, combining the characteristic of the disassembly sequence, an entropy-based adaptive hybrid particle swarm optimization algorithm (AHPSO is presented. In this algorithm, entropy is introduced to measure the changing tendency of population diversity, and the dimension learning, crossover and mutation operator are used to increase the probability of producing feasible disassembly solutions (FDS. Performance of the proposed methodology is tested on the primary problem instances available in the literature, and the results are compared with other evolutionary algorithms. The results show that the proposed algorithm is efficient to solve the complex DLBP.

  3. Special Issue on Entropy-Based Applied Cryptography and Enhanced Security for Ubiquitous Computing

    Directory of Open Access Journals (Sweden)

    James (Jong Hyuk Park

    2016-09-01

    Full Text Available Entropy is a basic and important concept in information theory. It is also often used as a measure of the unpredictability of a cryptographic key in cryptography research areas. Ubiquitous computing (Ubi-comp has emerged rapidly as an exciting new paradigm. In this special issue, we mainly selected and discussed papers related with ore theories based on the graph theory to solve computational problems on cryptography and security, practical technologies; applications and services for Ubi-comp including secure encryption techniques, identity and authentication; credential cloning attacks and countermeasures; switching generator with resistance against the algebraic and side channel attacks; entropy-based network anomaly detection; applied cryptography using chaos function, information hiding and watermark, secret sharing, message authentication, detection and modeling of cyber attacks with Petri Nets, and quantum flows for secret key distribution, etc.

  4. Combined SPHARM-PDM and entropy-based particle systems shape analysis framework.

    Science.gov (United States)

    Paniagua, Beatriz; Bompard, Lucile; Cates, Josh; Whitaker, Ross; Datar, Manasi; Vachet, Clement; Styner, Martin

    2012-03-23

    The NA-MIC SPHARM-PDM Toolbox represents an automated set of tools for the computation of 3D structural statistical shape analysis. SPHARM-PDM solves the correspondence problem by defining a first order ellipsoid aligned, uniform spherical parameterization for each object with correspondence established at equivalently parameterized points. However, SPHARM correspondence has shown to be inadequate for some biological shapes that are not well described by a uniform spherical parameterization. Entropy-based particle systems compute correspondence by representing surfaces as discrete point sets that does not rely on any inherent parameterization. However, they are sensitive to initialization and have little ability to recover from initial errors. By combining both methodologies we compute reliable correspondences in topologically challenging biological shapes. Diverse subcortical structures cohorts were used, obtained from MR brain images. The SPHARM-PDM shape analysis toolbox was used to compute point based correspondent models that were then used as initializing particles for the entropy-based particle systems. The combined framework was implemented as a stand-alone Slicer3 module, which works as an end-to-end shape analysis module. The combined SPHARM-PDM-Particle framework has demonstrated to improve correspondence in the example dataset over the conventional SPHARM-PDM toolbox. The work presented in this paper demonstrates a two-sided improvement for the scientific community, being able to 1) find good correspondences among spherically topological shapes, that can be used in many morphometry studies 2) offer an end-to-end solution that will facilitate the access to shape analysis framework to users without computer expertise.

  5. Ranking and characterization of established BMI and lipid associated loci as candidates for gene-environment interactions

    DEFF Research Database (Denmark)

    Shungin, Dmitry; Deng, Wei Q; Varga, Tibor V

    2017-01-01

    Phenotypic variance heterogeneity across genotypes at a single nucleotide polymorphism (SNP) may reflect underlying gene-environment (G×E) or gene-gene interactions. We modeled variance heterogeneity for blood lipids and BMI in up to 44,211 participants and investigated relationships between vari...... (Pbinomial = 8.63×10-9 and 8.52×10-7 for SNP × smoking and SNP × physical activity, respectively). We conclude that some loci with strong marginal effects may be good candidates for G×E, and variance-based prioritization can be used to identify them....... variance effects (Pv), G×E interaction effects (with smoking and physical activity), and marginal genetic effects (Pm). Correlations between Pv and Pm were stronger for SNPs with established marginal effects (Spearman's ρ = 0.401 for triglycerides, and ρ = 0.236 for BMI) compared to all SNPs. When Pv...... and Pm were compared for all pruned SNPs, only BMI was statistically significant (Spearman's ρ = 0.010). Overall, SNPs with established marginal effects were overrepresented in the nominally significant part of the Pv distribution (Pbinomial

  6. Entropy-Based Model for Interpreting Life Systems in Traditional Chinese Medicine

    Directory of Open Access Journals (Sweden)

    Guo-lian Kang

    2008-01-01

    Full Text Available Traditional Chinese medicine (TCM treats qi as the core of the human life systems. Starting with a hypothetical correlation between TCM qi and the entropy theory, we address in this article a holistic model for evaluating and unveiling the rule of TCM life systems. Several new concepts such as acquired life entropy (ALE, acquired life entropy flow (ALEF and acquired life entropy production (ALEP are propounded to interpret TCM life systems. Using the entropy theory, mathematical models are established for ALE, ALEF and ALEP, which reflect the evolution of life systems. Some criteria are given on physiological activities and pathological changes of the body in different stages of life. Moreover, a real data-based simulation shows life entropies of the human body with different ages, Cold and Hot constitutions and in different seasons in North China are coincided with the manifestations of qi as well as the life evolution in TCM descriptions. Especially, based on the comparative and quantitative analysis, the entropy-based model can nicely describe the evolution of life entropies in Cold and Hot individuals thereby fitting the Yin–Yang theory in TCM. Thus, this work establishes a novel approach to interpret the fundamental principles in TCM, and provides an alternative understanding for the complex life systems.

  7. Entropy-Based Investigation on the Precipitation Variability over the Hexi Corridor in China

    Directory of Open Access Journals (Sweden)

    Liang Cheng

    2017-12-01

    Full Text Available The spatial and temporal variability of precipitation time series were investigated for the Hexi Corridor, in Northwest China, by analyzing the entropy information. The examinations were performed on monthly, seasonal, and annual timescales based on 29 meteorological stations for the period of 1961–2015. The apportionment entropy and intensity entropy were used to analyze the regional precipitation characteristics, including the intra-annual and decadal distribution of monthly and annual precipitation amounts, as well as the number of precipitation days within a year and a decade. The regions with high precipitation variability are found in the western part of the Hexi corridor and with less precipitation, and may have a high possibility of drought occurrence. The variability of the number of precipitation days decreased from the west to the east of the corridor. Higher variability, in terms of both of precipitation amount and intensity during crop-growing season, has been found in the recent decade. In addition, the correlation between entropy-based precipitation variability and the crop yield is also compared, and the crop yield in historical periods is found to be correlated with the precipitation intensity disorder index in the middle reaches of the Hexi corridor.

  8. A Weighted Belief Entropy-Based Uncertainty Measure for Multi-Sensor Data Fusion

    Science.gov (United States)

    Tang, Yongchuan; Zhou, Deyun; Xu, Shuai; He, Zichang

    2017-01-01

    In real applications, how to measure the uncertain degree of sensor reports before applying sensor data fusion is a big challenge. In this paper, in the frame of Dempster–Shafer evidence theory, a weighted belief entropy based on Deng entropy is proposed to quantify the uncertainty of uncertain information. The weight of the proposed belief entropy is based on the relative scale of a proposition with regard to the frame of discernment (FOD). Compared with some other uncertainty measures in Dempster–Shafer framework, the new measure focuses on the uncertain information represented by not only the mass function, but also the scale of the FOD, which means less information loss in information processing. After that, a new multi-sensor data fusion approach based on the weighted belief entropy is proposed. The rationality and superiority of the new multi-sensor data fusion method is verified according to an experiment on artificial data and an application on fault diagnosis of a motor rotor. PMID:28441736

  9. Entropy-based derivation of generalized distributions for hydrometeorological frequency analysis

    Science.gov (United States)

    Chen, Lu; Singh, Vijay P.

    2018-02-01

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

  10. Ranking and characterization of established BMI and lipid associated loci as candidates for gene-environment interactions.

    Directory of Open Access Journals (Sweden)

    Dmitry Shungin

    2017-06-01

    Full Text Available Phenotypic variance heterogeneity across genotypes at a single nucleotide polymorphism (SNP may reflect underlying gene-environment (G×E or gene-gene interactions. We modeled variance heterogeneity for blood lipids and BMI in up to 44,211 participants and investigated relationships between variance effects (Pv, G×E interaction effects (with smoking and physical activity, and marginal genetic effects (Pm. Correlations between Pv and Pm were stronger for SNPs with established marginal effects (Spearman's ρ = 0.401 for triglycerides, and ρ = 0.236 for BMI compared to all SNPs. When Pv and Pm were compared for all pruned SNPs, only BMI was statistically significant (Spearman's ρ = 0.010. Overall, SNPs with established marginal effects were overrepresented in the nominally significant part of the Pv distribution (Pbinomial <0.05. SNPs from the top 1% of the Pm distribution for BMI had more significant Pv values (PMann-Whitney = 1.46×10-5, and the odds ratio of SNPs with nominally significant (<0.05 Pm and Pv was 1.33 (95% CI: 1.12, 1.57 for BMI. Moreover, BMI SNPs with nominally significant G×E interaction P-values (Pint<0.05 were enriched with nominally significant Pv values (Pbinomial = 8.63×10-9 and 8.52×10-7 for SNP × smoking and SNP × physical activity, respectively. We conclude that some loci with strong marginal effects may be good candidates for G×E, and variance-based prioritization can be used to identify them.

  11. Measles Virus Nucleocapsid (MVNP) Gene Expression and RANK Receptor Signaling in Osteoclast Precursors, Osteoclast Inhibitors Peptide Therapy for Pagets Disease

    Science.gov (United States)

    2008-10-01

    cytoplas- mic inclusions. Immunocytochemical studies confirmed that MV and RSV nucleocapsid anti- genswere expressed in osteoclasts formed invitro in...multiple cloning site immediately upstream of the rabbit β-glo- bin sequences. The TRAP-p62P392L transgene was excised by XhoI digestion from the... digestion . The resulting DNA fragment (430 bp) encoding the com- plete coding sequence of OIP-1 was sub-cloned into the pKCR3R1-mTRAP gene promoter

  12. Ranking library materials

    OpenAIRE

    Lewandowski, Dirk

    2015-01-01

    Purpose: This paper discusses ranking factors suitable for library materials and shows that ranking in general is a complex process and that ranking for library materials requires a variety of techniques. Design/methodology/approach: The relevant literature is reviewed to provide a systematic overview of suitable ranking factors. The discussion is based on an overview of ranking factors used in Web search engines. Findings: While there are a wide variety of ranking factors appl...

  13. Application of Entropy-Based Metrics to Identify Emotional Distress from Electroencephalographic Recordings

    Directory of Open Access Journals (Sweden)

    Beatriz García-Martínez

    2016-06-01

    Full Text Available Recognition of emotions is still an unresolved challenge, which could be helpful to improve current human-machine interfaces. Recently, nonlinear analysis of some physiological signals has shown to play a more relevant role in this context than their traditional linear exploration. Thus, the present work introduces for the first time the application of three recent entropy-based metrics: sample entropy (SE, quadratic SE (QSE and distribution entropy (DE to discern between emotional states of calm and negative stress (also called distress. In the last few years, distress has received growing attention because it is a common negative factor in the modern lifestyle of people from developed countries and, moreover, it may lead to serious mental and physical health problems. Precisely, 279 segments of 32-channel electroencephalographic (EEG recordings from 32 subjects elicited to be calm or negatively stressed have been analyzed. Results provide that QSE is the first single metric presented to date with the ability to identify negative stress. Indeed, this metric has reported a discriminant ability of around 70%, which is only slightly lower than the one obtained by some previous works. Nonetheless, discriminant models from dozens or even hundreds of features have been previously obtained by using advanced classifiers to yield diagnostic accuracies about 80%. Moreover, in agreement with previous neuroanatomy findings, QSE has also revealed notable differences for all the brain regions in the neural activation triggered by the two considered emotions. Consequently, given these results, as well as easy interpretation of QSE, this work opens a new standpoint in the detection of emotional distress, which may gain new insights about the brain’s behavior under this negative emotion.

  14. 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 e...... eigenvalues and eigenvectors. We give a number of different applications to regression and time series analysis, and show how the reduced rank regression estimator can be derived as a Gaussian maximum likelihood estimator. We briefly mention asymptotic results......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...

  15. 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

  16. Toxicity ranking and toxic mode of action evaluation of commonly used agricultural adjuvants on the basis of bacterial gene expression profiles.

    Directory of Open Access Journals (Sweden)

    Ingrid Nobels

    Full Text Available The omnipresent group of pesticide adjuvants are often referred to as "inert" ingredients, a rather misleading term since consumers associate this term with "safe". The upcoming new EU regulation concerning the introduction of plant protection products on the market (EC1107/2009 includes for the first time the demand for information on the possible negative effects of not only the active ingredients but also the used adjuvants. This new regulation requires basic toxicological information that allows decisions on the use/ban or preference of use of available adjuvants. In this study we obtained toxicological relevant information through a multiple endpoint reporter assay for a broad selection of commonly used adjuvants including several solvents (e.g. isophorone and non-ionic surfactants (e.g. ethoxylated alcohols. The used assay allows the toxicity screening in a mechanistic way, with direct measurement of specific toxicological responses (e.g. oxidative stress, DNA damage, membrane damage and general cell lesions. The results show that the selected solvents are less toxic than the surfactants, suggesting that solvents may have a preference of use, but further research on more compounds is needed to confirm this observation. The gene expression profiles of the selected surfactants reveal that a phenol (ethoxylated tristyrylphenol and an organosilicone surfactant (ethoxylated trisiloxane show little or no inductions at EC(20 concentrations, making them preferred surfactants for use in different applications. The organosilicone surfactant shows little or no toxicity and good adjuvant properties. However, this study also illustrates possible genotoxicity (induction of the bacterial SOS response for several surfactants (POEA, AE, tri-EO, EO FA and EO NP and one solvent (gamma-butyrolactone. Although the number of compounds that were evaluated is rather limited (13, the results show that the used reporter assay is a promising tool to rank commonly

  17. 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.

  18. A Cross-Entropy-Based Admission Control Optimization Approach for Heterogeneous Virtual Machine Placement in Public Clouds

    Directory of Open Access Journals (Sweden)

    Li Pan

    2016-03-01

    Full Text Available Virtualization technologies make it possible for cloud providers to consolidate multiple IaaS provisions into a single server in the form of virtual machines (VMs. Additionally, in order to fulfill the divergent service requirements from multiple users, a cloud provider needs to offer several types of VM instances, which are associated with varying configurations and performance, as well as different prices. In such a heterogeneous virtual machine placement process, one significant problem faced by a cloud provider is how to optimally accept and place multiple VM service requests into its cloud data centers to achieve revenue maximization. To address this issue, in this paper, we first formulate such a revenue maximization problem during VM admission control as a multiple-dimensional knapsack problem, which is known to be NP-hard to solve. Then, we propose to use a cross-entropy-based optimization approach to address this revenue maximization problem, by obtaining a near-optimal eligible set for the provider to accept into its data centers, from the waiting VM service requests in the system. Finally, through extensive experiments and measurements in a simulated environment with the settings of VM instance classes derived from real-world cloud systems, we show that our proposed cross-entropy-based admission control optimization algorithm is efficient and effective in maximizing cloud providers’ revenue in a public cloud computing environment.

  19. An entropy-based improved k-top scoring pairs (TSP) method for ...

    African Journals Online (AJOL)

    We compared Ik-TSP classifiers with 5 different machine learning methods and the k-TSP method based on 3 different feature selection methods on 9 binary class gene expression datasets and 10 multi-class gene expression datasets involving human cancers. Experimental results showed that the Ik-TSP method had ...

  20. Maximum Waring ranks of monomials

    OpenAIRE

    Holmes, Erik; Plummer, Paul; Siegert, Jeremy; Teitler, Zach

    2013-01-01

    We show that monomials and sums of pairwise coprime monomials in four or more variables have Waring rank less than the generic rank, with a short list of exceptions. We asymptotically compare their ranks with the generic rank.

  1. 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.

  2. An entropy-based improved k-top scoring pairs (TSP) method for ...

    African Journals Online (AJOL)

    DR. NJ TONUKARI

    2012-06-05

    Jun 5, 2012 ... Engineering of the Ministry of Education, Changdhun 130012, People's Republic of China. 2Supercomputing Center ... disjoint top scoring pairs of genes as decision rules rather than only the highest pair and both ..... including C4.5 decision trees (DT), Naive Bayes (NB), k-nearest neighbor (k-NN), support ...

  3. Academic rankings: an approach to a Portuguese ranking

    OpenAIRE

    Bernardino, Pedro; Marques,Rui

    2009-01-01

    The academic rankings are a controversial subject in higher education. However, despite all the criticism, academic rankings are here to stay and more and more different stakeholders use rankings to obtain information about the institutions’ performance. The two most well-known rankings, The Times and the Shanghai Jiao Tong University rankings have different methodologies. The Times ranking is based on peer review, whereas the Shanghai ranking has only quantitative indicators and is mainly ba...

  4. Analysis of entropies based on empirical mode decomposition in amnesic mild cognitive impairment of diabetes mellitus

    Directory of Open Access Journals (Sweden)

    Dong Cui

    2015-09-01

    Full Text Available EEG characteristics that correlate with the cognitive functions are important in detecting mild cognitive impairment (MCI in T2DM. To investigate the complexity between aMCI group and age-matched non-aMCI control group in T2DM, six entropies combining empirical mode decomposition (EMD, including Approximate entropy (ApEn, Sample entropy (SaEn, Fuzzy entropy (FEn, Permutation entropy (PEn, Power spectrum entropy (PsEn and Wavelet entropy (WEn were used in the study. A feature extraction technique based on maximization of the area under the curve (AUC and a support vector machine (SVM were subsequently used to for features selection and classification. Finally, Pearson's linear correlation was employed to study associations between these entropies and cognitive functions. Compared to other entropies, FEn had a higher classification accuracy, sensitivity and specificity of 68%, 67.1% and 71.9%, respectively. Top 43 salient features achieved classification accuracy, sensitivity and specificity of 73.8%, 72.3% and 77.9%, respectively. P4, T4 and C4 were the highest ranking salient electrodes. Correlation analysis showed that FEn based on EMD was positively correlated to memory at electrodes F7, F8 and P4, and PsEn based on EMD was positively correlated to Montreal cognitive assessment (MoCA and memory at electrode T4. In sum, FEn based on EMD in right-temporal and occipital regions may be more suitable for early diagnosis of the MCI with T2DM.

  5. AKT1 as the PageRank hub gene is associated with melanoma and its functional annotation is highly related to the estrogen signaling pathway that may regulate the growth of melanoma.

    Science.gov (United States)

    Zhao, Jingjing; Zeng, Xue; Song, Ping; Wu, Xiaohong; Shi, Hongbo

    2016-10-01

    In order to detect the disease-associated genes and their gene interaction function and association with melanoma mechanisms, we identified a total of 1,310 differentially expressed genes (DEGs) from the Gene Expression Omnibus database GSE3189 with FDR 2 using the R package. After constructing the gene interaction network by STRING with the selected DEGs, we applied a statistical approach to identify the topological hub genes with PageRank score. Forty-four genes were identified in this network and AKT1 was selected as the most important hub gene. The AKT1 gene encodes a serine‑threonine protein kinase (AKT). High expression of AKT is involved in the resistance of cell apoptosis as well as adaptive resistance to treatment in melanoma. Our results indicated that AKT1 with a higher expression in melanoma showed enriched binding sites in the negative regulation of response to external stimulus, which enables cells to adapt to changes in external stimulation for survival. Another finding was that AKT regulated the lipid metabolic process and may be involved in melanoma progression and promotion of tumor growth through gene enrichment function analysis. Two highlighted pathways were detected in our study: i) the estrogen signaling pathway modulates the immune tolerance and resistance to cell apoptosis, which contributes to the growth of melanoma and ii) the RAP1 signaling pathway which regulates focal adhesion (FA) negative feedback to cell migration and invasion in melanoma. Our studies highlighted the top differentially expressed gene AKT1 and its correlation with the estrogen signaling and RAP1 signaling pathways to alter the proliferation and apoptosis of melanoma cells. Analysis of the enrichment functions of genes associated with melanoma will help us find the exact mechanism of melanoma and advance the full potential of newly targeted cancer therapy.

  6. 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...

  7. 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...

  8. 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.

  9. Asset ranking manager (ranking index of components)

    Energy Technology Data Exchange (ETDEWEB)

    Maloney, S.M.; Engle, A.M.; Morgan, T.A. [Applied Reliability, Maracor Software and Engineering (United States)

    2004-07-01

    The Ranking Index of Components (RIC) is an Asset Reliability Manager (ARM), which itself is a Web Enabled front end where plant database information fields from several disparate databases are combined. That information is used to create a specific weighted number (Ranking Index) relating to that components health and risk to the site. The higher the number, the higher priority that any work associated with that component receives. ARM provides site Engineering, Maintenance and Work Control personnel with a composite real time - (current condition) look at the components 'risk of not working' to the plant. Information is extracted from the existing Computerized Maintenance management System (CMMS) and specific site applications and processed nightly. ARM helps to ensure that the most important work is placed into the workweeks and the non value added work is either deferred, frequency changed or deleted. This information is on the web, updated each night, and available for all employees to use. This effort assists the work management specialist when allocating limited resources to the most important work. The use of this tool has maximized resource usage, performing the most critical work with available resources. The ARM numbers are valued inputs into work scoping for the workweek managers. System and Component Engineers are using ARM to identify the components that are at 'risk of failure' and therefore should be placed into the appropriate work week schedule.

  10. 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.

  11. 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.

  12. Ranking of Rankings: Benchmarking Twenty-Five Higher Education Ranking Systems in Europe

    Science.gov (United States)

    Stolz, Ingo; Hendel, Darwin D.; Horn, Aaron S.

    2010-01-01

    The purpose of this study is to evaluate the ranking practices of 25 European higher education ranking systems (HERSs). Ranking practices were assessed with 14 quantitative measures derived from the Berlin Principles on Ranking of Higher Education Institutions (BPs). HERSs were then ranked according to their degree of congruence with the BPs.…

  13. LCA*: an entropy-based measure for taxonomic assignment within assembled metagenomes.

    Science.gov (United States)

    Hanson, Niels W; Konwar, Kishori M; Hallam, Steven J

    2016-12-01

    A perennial problem in the analysis of environmental sequence information is the assignment of reads or assembled sequences, e.g. contigs or scaffolds, to discrete taxonomic bins. In the absence of reference genomes for most environmental microorganisms, the use of intrinsic nucleotide patterns and phylogenetic anchors can improve assembly-dependent binning needed for more accurate taxonomic and functional annotation in communities of microorganisms, and assist in identifying mobile genetic elements or lateral gene transfer events. Here, we present a statistic called LCA* inspired by Information and Voting theories that uses the NCBI Taxonomic Database hierarchy to assign taxonomy to contigs assembled from environmental sequence information. The LCA* algorithm identifies a sufficiently strong majority on the hierarchy while minimizing entropy changes to the observed taxonomic distribution resulting in improved statistical properties. Moreover, we apply results from the order-statistic literature to formulate a likelihood-ratio hypothesis test and P-value for testing the supremacy of the assigned LCA* taxonomy. Using simulated and real-world datasets, we empirically demonstrate that voting-based methods, majority vote and LCA*, in the presence of known reference annotations, are consistently more accurate in identifying contig taxonomy than the lowest common ancestor algorithm popularized by MEGAN, and that LCA* taxonomy strikes a balance between specificity and confidence to provide an estimate appropriate to the available information in the data. The LCA* has been implemented as a stand-alone Python library compatible with the MetaPathways pipeline; both of which are available on GitHub with installation instructions and use-cases (http://www.github.com/hallamlab/LCAStar/). shallam@mail.ubc.caSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

  14. From rankings to mission.

    Science.gov (United States)

    Kirch, Darrell G; Prescott, John E

    2013-08-01

    Since the 1980s, school ranking systems have been a topic of discussion among leaders of higher education. Various ranking systems are based on inadequate data that fail to illustrate the complex nature and special contributions of the institutions they purport to rank, including U.S. medical schools, each of which contributes uniquely to meeting national health care needs. A study by Tancredi and colleagues in this issue of Academic Medicine illustrates the limitations of rankings specific to primary care training programs. This commentary discusses, first, how each school's mission and strengths, as well as the impact it has on the community it serves, are distinct, and, second, how these schools, which are each unique, are poorly represented by overly subjective ranking methodologies. Because academic leaders need data that are more objective to guide institutional development, the Association of American Medical Colleges (AAMC) has been developing tools to provide valid data that are applicable to each medical school. Specifically, the AAMC's Medical School Admissions Requirements and its Missions Management Tool each provide a comprehensive assessment of medical schools that leaders are using to drive institutional capacity building. This commentary affirms the importance of mission while challenging the leaders of medical schools, teaching hospitals, and universities to use reliable data to continually improve the quality of their training programs to improve the health of all.

  15. Shannon Entropy-Based Wavelet Transform Method for Autonomous Coherent Structure Identification in Fluid Flow Field Data

    Directory of Open Access Journals (Sweden)

    Kartik V. Bulusu

    2015-09-01

    Full Text Available The coherent secondary flow structures (i.e., swirling motions in a curved artery model possess a variety of spatio-temporal morphologies and can be encoded over an infinitely-wide range of wavelet scales. Wavelet analysis was applied to the following vorticity fields: (i a numerically-generated system of Oseen-type vortices for which the theoretical solution is known, used for bench marking and evaluation of the technique; and (ii experimental two-dimensional, particle image velocimetry data. The mother wavelet, a two-dimensional Ricker wavelet, can be dilated to infinitely large or infinitesimally small scales. We approached the problem of coherent structure detection by means of continuous wavelet transform (CWT and decomposition (or Shannon entropy. The main conclusion of this study is that the encoding of coherent secondary flow structures can be achieved by an optimal number of binary digits (or bits corresponding to an optimal wavelet scale. The optimal wavelet-scale search was driven by a decomposition entropy-based algorithmic approach and led to a threshold-free coherent structure detection method. The method presented in this paper was successfully utilized in the detection of secondary flow structures in three clinically-relevant blood flow scenarios involving the curved artery model under a carotid artery-inspired, pulsatile inflow condition. These scenarios were: (i a clean curved artery; (ii stent-implanted curved artery; and (iii an idealized Type IV stent fracture within the curved artery.

  16. A comparison of non-symmetric entropy-based classification trees and support vector machine for cardiovascular risk stratification.

    Science.gov (United States)

    Singh, Anima; Guttag, John V

    2011-01-01

    Classification tree-based risk stratification models generate easily interpretable classification rules. This feature makes classification tree-based models appealing for use in a clinical setting, provided that they have comparable accuracy to other methods. In this paper, we present and evaluate the performance of a non-symmetric entropy-based classification tree algorithm. The algorithm is designed to accommodate class imbalance found in many medical datasets. We evaluate the performance of this algorithm, and compare it to that of SVM-based classifiers, when applied to 4219 non-ST elevation acute coronary syndrome patients. We generated SVM-based classifiers using three different strategies for handling class imbalance: cost-sensitive SVM learning, synthetic minority oversampling (SMOTE), and random majority undersampling. We used both linear and radial basis kernel-based SVMs. Our classification tree models outperformed SVM-based classifiers generated using each of the three techniques. On average, the classification tree models yielded a 14% improvement in G-score and a 21% improvement in F-score relative to the linear SVM classifiers with the best performance. Similarly, our classification tree models yielded a 12% improvement in G-score and a 21% improvement in the F-score over the best RBF kernel-based SVM classifiers.

  17. 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.

  18. 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.

  19. 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....

  20. 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.

  1. 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...

  2. 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 ...

  3. Inferring data-specific micro-RNA function through the joint ranking of micro-RNA and pathways from matched micro-RNA and gene expression data.

    Science.gov (United States)

    Patrick, Ellis; Buckley, Michael; Müller, Samuel; Lin, David M; Yang, Jean Y H

    2015-09-01

    In practice, identifying and interpreting the functional impacts of the regulatory relationships between micro-RNA and messenger-RNA is non-trivial. The sheer scale of possible micro-RNA and messenger-RNA interactions can make the interpretation of results difficult. We propose a supervised framework, pMim, built upon concepts of significance combination, for jointly ranking regulatory micro-RNA and their potential functional impacts with respect to a condition of interest. Here, pMim directly tests if a micro-RNA is differentially expressed and if its predicted targets, which lie in a common biological pathway, have changed in the opposite direction. We leverage the information within existing micro-RNA target and pathway databases to stabilize the estimation and annotation of micro-RNA regulation making our approach suitable for datasets with small sample sizes. In addition to outputting meaningful and interpretable results, we demonstrate in a variety of datasets that the micro-RNA identified by pMim, in comparison to simpler existing approaches, are also more concordant with what is described in the literature. This framework is implemented as an R function, pMim, in the package sydSeq available from http://www.ellispatrick.com/r-packages. jean.yang@sydney.edu.au Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  4. An Entropy-Based Kernel Learning Scheme toward Efficient Data Prediction in Cloud-Assisted Network Environments

    Directory of Open Access Journals (Sweden)

    Xiong Luo

    2016-07-01

    Full Text Available With the recent emergence of wireless sensor networks (WSNs in the cloud computing environment, it is now possible to monitor and gather physical information via lots of sensor nodes to meet the requirements of cloud services. Generally, those sensor nodes collect data and send data to sink node where end-users can query all the information and achieve cloud applications. Currently, one of the main disadvantages in the sensor nodes is that they are with limited physical performance relating to less memory for storage and less source of power. Therefore, in order to avoid such limitation, it is necessary to develop an efficient data prediction method in WSN. To serve this purpose, by reducing the redundant data transmission between sensor nodes and sink node while maintaining the required acceptable errors, this article proposes an entropy-based learning scheme for data prediction through the use of kernel least mean square (KLMS algorithm. The proposed scheme called E-KLMS develops a mechanism to maintain the predicted data synchronous at both sides. Specifically, the kernel-based method is able to adjust the coefficients adaptively in accordance with every input, which will achieve a better performance with smaller prediction errors, while employing information entropy to remove these data which may cause relatively large errors. E-KLMS can effectively solve the tradeoff problem between prediction accuracy and computational efforts while greatly simplifying the training structure compared with some other data prediction approaches. What’s more, the kernel-based method and entropy technique could ensure the prediction effect by both improving the accuracy and reducing errors. Experiments with some real data sets have been carried out to validate the efficiency and effectiveness of E-KLMS learning scheme, and the experiment results show advantages of the our method in prediction accuracy and computational time.

  5. An entropy-based input variable selection approach to identify equally informative subsets for data-driven hydrological models

    Science.gov (United States)

    Karakaya, Gulsah; Taormina, Riccardo; Galelli, Stefano; Damla Ahipasaoglu, Selin

    2015-04-01

    Input Variable Selection (IVS) is an essential step in hydrological modelling problems, since it allows determining the optimal subset of input variables from a large set of candidates to characterize a preselected output. Interestingly, most of the existing IVS algorithms select a single subset, or, at most, one subset of input variables for each cardinality level, thus overlooking the fact that, for a given cardinality, there can be several subsets with similar information content. In this study, we develop a novel IVS approach specifically conceived to account for this issue. The approach is based on the formulation of a four-objective optimization problem that aims at minimizing the number of selected variables and maximizing the prediction accuracy of a data-driven model, while optimizing two entropy-based measures of relevance and redundancy. The redundancy measure ensures that the cross-dependence between the variables in a subset is minimized, while the relevance measure guarantees that the information content of each subset is maximized. In addition to the capability of selecting equally informative subsets, the approach is characterized by two other properties, namely 1) the capability of handling nonlinear interactions between the candidate input variables and preselected output, and 2) computational efficiency. These properties are guaranteed by the adoption of Extreme Learning Machine and Borg MOEA as data-driven model and heuristic optimization procedure, respectively. The approach is demonstrated on a long-term streamflow prediction problem, with the input dataset including both hydro-meteorological variables and climate indices representing dominant modes of climate variability. Results show that the availability of several equally informative subsets allows 1) determining the relative importance of each candidate input, thus supporting the understanding of the underlying physical processes, and 2) finding a better trade-off between multiple

  6. A statistical approach towards the derivation of predictive gene sets for potency ranking of chemicals in the mouse embryonic stem cell test

    NARCIS (Netherlands)

    Schulpen, Sjors H W; Pennings, Jeroen L A; Tonk, Elisa C M; Piersma, Aldert H.

    2014-01-01

    The embryonic stem cell test (EST) is applied as a model system for detection of embryotoxicants. The application of transcriptomics allows a more detailed effect assessment compared to the morphological endpoint. Genes involved in cell differentiation, modulated by chemical exposures, may be useful

  7. Fractional cointegration rank estimation

    DEFF Research Database (Denmark)

    Lasak, Katarzyna; Velasco, Carlos

    We consider cointegration rank estimation for a p-dimensional Fractional Vector Error Correction Model. We propose a new two-step procedure which allows testing for further long-run equilibrium relations with possibly different persistence levels. The fi…rst step consists in estimating the parame......We consider cointegration rank estimation for a p-dimensional Fractional Vector Error Correction Model. We propose a new two-step procedure which allows testing for further long-run equilibrium relations with possibly different persistence levels. The fi…rst step consists in estimating...... to control for stochastic trend estimation effects from the first step. The critical values of the tests proposed depend only on the number of common trends under the null, p - r, and on the interval of the cointegration degrees b allowed, but not on the true cointegration degree b0. Hence, no additional...

  8. Can College Rankings Be Believed?

    Directory of Open Access Journals (Sweden)

    Meredith Davis

    Full Text Available The article summarizes literature on college and university rankings worldwide and the strategies used by various ranking organizations, including those of government and popular media. It traces the history of national and global rankings, indicators used by ranking systems, and the effect of rankings on academic programs and their institutions. Although ranking systems employ diverse criteria and most weight certain indicators over others, there is considerable skepticism that most actually measure educational quality. At the same time, students and their families increasingly consult these evaluations when making college decisions, and sponsors of faculty research consider reputation when forming academic partnerships. While there are serious concerns regarding the validity of ranking institutions when so little data can support differences between one institution and another, college rankings appear to be here to stay.

  9. Ranking Baltic States Researchers

    Directory of Open Access Journals (Sweden)

    Gyula Mester

    2017-10-01

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

  10. Sync-rank: Robust Ranking, Constrained Ranking and Rank Aggregation via Eigenvector and SDP Synchronization

    Science.gov (United States)

    2015-04-28

    eigenvector of the associated Laplacian matrix (i.e., the Fiedler vector) matches that of the variables. In other words, this approach (reminiscent of...S1), i.e., Dii = ∑n j=1Gi,j is the degree of node i in the measurement graph G. 3: Compute the Fiedler vector of S (eigenvector corresponding to the...smallest nonzero eigenvalue of LS). 4: Output the ranking induced by sorting the Fiedler vector of S, with the global ordering (increasing or decreasing

  11. 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/.

  12. Rankings from Fuzzy Pairwise Comparisons

    NARCIS (Netherlands)

    van den Broek, P.M.; Noppen, J.A.R.; Mohammadian, M.

    2006-01-01

    We propose a new method for deriving rankings from fuzzy pairwise comparisons. It is based on the observation that quantification of the uncertainty of the pairwise comparisons should be used to obtain a better crisp ranking, instead of a fuzzified version of the ranking obtained from crisp pairwise

  13. PageRank (II): Mathematics

    African Journals Online (AJOL)

    maths/stats

    INTRODUCTION. PageRank is Google's system for ranking web pages. A page with a higher PageRank is deemed more important and is more likely to be listed above a ... Felix U. Ogban, Department of Mathematics/Statistics and Computer Science, Faculty of Science, University of ..... probability, 2004, 41, (3): 721-734.

  14. 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…

  15. ENBFS+kNN: Hybrid ensemble classifier using entropy-based naïve Bayes with feature selection and k-nearest neighbor

    Science.gov (United States)

    Sainin, Mohd Shamrie; Alfred, Rayner; Ahmad, Faudziah

    2016-08-01

    A hybrid ensemble classifier which combines the entropy based naive Bayes (ENB) classifier strategy and k-nearest neighbor (k-NN) is examined. The classifiers are joined in light of the fact that naive Bayes gives prior estimations taking into account entropy while k-NN gives neighborhood estimate to model for a deferred characterization. While original NB utilizes the probabilities, this study utilizes the entropy as priors for class estimations. The result of the hybrid ensemble classifier demonstrates that by consolidating the classifiers, the proposed technique accomplishes promising execution on several benchmark datasets.

  16. 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.

  17. 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. PMID:28713181

  18. 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.

  19. 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).

  20. 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.

  1. 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.

  2. University Rankings in Critical Perspective

    Science.gov (United States)

    Pusser, Brian; Marginson, Simon

    2013-01-01

    This article addresses global postsecondary ranking systems by using critical-theoretical perspectives on power. This research suggests rankings are at once a useful lens for studying power in higher education and an important instrument for the exercise of power in service of dominant norms in global higher education. (Contains 1 table and 1…

  3. University Ranking as Social Exclusion

    Science.gov (United States)

    Amsler, Sarah S.; Bolsmann, Chris

    2012-01-01

    In this article we explore the dual role of global university rankings in the creation of a new, knowledge-identified, transnational capitalist class and in facilitating new forms of social exclusion. We examine how and why the practice of ranking universities has become widely defined by national and international organisations as an important…

  4. PageRank tracker: from ranking to tracking.

    Science.gov (United States)

    Gong, Chen; Fu, Keren; Loza, Artur; Wu, Qiang; Liu, Jia; Yang, Jie

    2014-06-01

    Video object tracking is widely used in many real-world applications, and it has been extensively studied for over two decades. However, tracking robustness is still an issue in most existing methods, due to the difficulties with adaptation to environmental or target changes. In order to improve adaptability, this paper formulates the tracking process as a ranking problem, and the PageRank algorithm, which is a well-known webpage ranking algorithm used by Google, is applied. Labeled and unlabeled samples in tracking application are analogous to query webpages and the webpages to be ranked, respectively. Therefore, determining the target is equivalent to finding the unlabeled sample that is the most associated with existing labeled set. We modify the conventional PageRank algorithm in three aspects for tracking application, including graph construction, PageRank vector acquisition and target filtering. Our simulations with the use of various challenging public-domain video sequences reveal that the proposed PageRank tracker outperforms mean-shift tracker, co-tracker, semiboosting and beyond semiboosting trackers in terms of accuracy, robustness and stability.

  5. Universal scaling in sports ranking

    Science.gov (United States)

    Deng, Weibing; Li, Wei; Cai, Xu; Bulou, Alain; Wang, Qiuping A.

    2012-09-01

    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.

  6. Universal scaling in sports ranking

    CERN Document Server

    Deng, Weibing; Cai, Xu; Bulou, Alain; Wang, Qiuping A

    2011-01-01

    Ranking is a ubiquitous phenomenon in the human society. By clicking the web pages of Forbes, you may find all kinds of rankings, such as world's most powerful people, world's richest people, top-paid tennis stars, and so on and so forth. Herewith, we study a specific kind, sports ranking systems in which players' scores and prize money are calculated based on their performances in attending various tournaments. A typical example is tennis. It is found that the distributions of both scores and prize money follow universal power laws, with exponents nearly identical for most sports fields. 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 will top 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 simul...

  7. 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.

  8. PageRank of integers

    Science.gov (United States)

    Frahm, K. M.; Chepelianskii, A. D.; Shepelyansky, D. L.

    2012-10-01

    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.

  9. Ranking in evolving complex networks

    Science.gov (United States)

    Liao, Hao; Mariani, Manuel Sebastian; Medo, Matúš; Zhang, Yi-Cheng; Zhou, Ming-Yang

    2017-05-01

    Complex networks have emerged as a simple yet powerful framework to represent and analyze a wide range of complex systems. The problem of ranking the nodes and the edges in complex networks is critical for a broad range of real-world problems because it affects how we access online information and products, how success and talent are evaluated in human activities, and how scarce resources are allocated by companies and policymakers, among others. This calls for a deep understanding of how existing ranking algorithms perform, and which are their possible biases that may impair their effectiveness. Many popular ranking algorithms (such as Google's PageRank) are static in nature and, as a consequence, they exhibit important shortcomings when applied to real networks that rapidly evolve in time. At the same time, recent advances in the understanding and modeling of evolving networks have enabled the development of a wide and diverse range of ranking algorithms that take the temporal dimension into account. The aim of this review is to survey the existing ranking algorithms, both static and time-aware, and their applications to evolving networks. We emphasize both the impact of network evolution on well-established static algorithms and the benefits from including the temporal dimension for tasks such as prediction of network traffic, prediction of future links, and identification of significant nodes.

  10. RANK and RANK ligand expression in primary human osteosarcoma

    Directory of Open Access Journals (Sweden)

    Daniel Branstetter

    2015-09-01

    Our results demonstrate RANKL expression was observed in the tumor element in 68% of human OS using IHC. However, the staining intensity was relatively low and only 37% (29/79 of samples exhibited≥10% RANKL positive tumor cells. RANK expression was not observed in OS tumor cells. In contrast, RANK expression was clearly observed in other cells within OS samples, including the myeloid osteoclast precursor compartment, osteoclasts and in giant osteoclast cells. The intensity and frequency of RANKL and RANK staining in OS samples were substantially less than that observed in GCTB samples. The observation that RANKL is expressed in OS cells themselves suggests that these tumors may mediate an osteoclastic response, and anti-RANKL therapy may potentially be protective against bone pathologies in OS. However, the absence of RANK expression in primary human OS cells suggests that any autocrine RANKL/RANK signaling in human OS tumor cells is not operative, and anti-RANKL therapy would not directly affect the tumor.

  11. Ranking structures and Rank-Rank Correlations of Countries. The FIFA and UEFA cases

    CERN Document Server

    Ausloos, Marcel; Gadomski, Adam; Vitanov, Nikolay K

    2014-01-01

    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.

  12. 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.

  13. University Ranking Systems; Criteria and Critiques

    OpenAIRE

    Saka, Yavuz; YAMAN, Süleyman

    2011-01-01

    The purpose of this paper is to explore international university ranking systems. As a compilation study this paper provides specific criteria that each ranking system uses and main critiques regarding these ranking systems. Since there are many ranking systems in this area of research, this study focused on only most cited and referred ranking systems. As there is no consensus in terms of the criteria that these systems use, this paper has no intention of identifying the best ranking system ...

  14. Ranking species in mutualistic networks.

    Science.gov (United States)

    Domínguez-García, Virginia; Muñoz, Miguel A

    2015-02-02

    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.

  15. 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...

  16. Rank distributions: Frequency vs. magnitude.

    Science.gov (United States)

    Velarde, Carlos; Robledo, Alberto

    2017-01-01

    We examine the relationship between two different types of ranked data, frequencies and magnitudes. We consider data that can be sorted out either way, through numbers of occurrences or size of the measures, as it is the case, say, of moon craters, earthquakes, billionaires, etc. We indicate that these two types of distributions are functional inverses of each other, and specify this link, first in terms of the assumed parent probability distribution that generates the data samples, and then in terms of an analog (deterministic) nonlinear iterated map that reproduces them. For the particular case of hyperbolic decay with rank the distributions are identical, that is, the classical Zipf plot, a pure power law. But their difference is largest when one displays logarithmic decay and its counterpart shows the inverse exponential decay, as it is the case of Benford law, or viceversa. For all intermediate decay rates generic differences appear not only between the power-law exponents for the midway rank decline but also for small and large rank. We extend the theoretical framework to include thermodynamic and statistical-mechanical concepts, such as entropies and configuration.

  17. Rankings Methodology Hurts Public Institutions

    Science.gov (United States)

    Van Der Werf, Martin

    2007-01-01

    In the 1980s, when the "U.S. News & World Report" rankings of colleges were based solely on reputation, the nation's public universities were well represented at the top. However, as soon as the magazine began including its "measures of excellence," statistics intended to define quality, public universities nearly disappeared from the top. As the…

  18. Let Us Rank Journalism Programs

    Science.gov (United States)

    Weber, Joseph

    2014-01-01

    Unlike law, business, and medical schools, as well as universities in general, journalism schools and journalism programs have rarely been ranked. Publishers such as "U.S. News & World Report," "Forbes," "Bloomberg Businessweek," and "Washington Monthly" do not pay them much mind. What is the best…

  19. 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.

  20. 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.

  1. The Globalization of College and University Rankings

    Science.gov (United States)

    Altbach, Philip G.

    2012-01-01

    In the era of globalization, accountability, and benchmarking, university rankings have achieved a kind of iconic status. The major ones--the Academic Ranking of World Universities (ARWU, or the "Shanghai rankings"), the QS (Quacquarelli Symonds Limited) World University Rankings, and the "Times Higher Education" World…

  2. Navigation and Self-Semantic Location of Drones in Indoor Environments by Combining the Visual Bug Algorithm and Entropy-Based Vision.

    Science.gov (United States)

    Maravall, Darío; de Lope, Javier; Fuentes, Juan P

    2017-01-01

    We introduce a hybrid algorithm for the self-semantic location and autonomous navigation of robots using entropy-based vision and visual topological maps. In visual topological maps the visual landmarks are considered as leave points for guiding the robot to reach a target point (robot homing) in indoor environments. These visual landmarks are defined from images of relevant objects or characteristic scenes in the environment. The entropy of an image is directly related to the presence of a unique object or the presence of several different objects inside it: the lower the entropy the higher the probability of containing a single object inside it and, conversely, the higher the entropy the higher the probability of containing several objects inside it. Consequently, we propose the use of the entropy of images captured by the robot not only for the landmark searching and detection but also for obstacle avoidance. If the detected object corresponds to a landmark, the robot uses the suggestions stored in the visual topological map to reach the next landmark or to finish the mission. Otherwise, the robot considers the object as an obstacle and starts a collision avoidance maneuver. In order to validate the proposal we have defined an experimental framework in which the visual bug algorithm is used by an Unmanned Aerial Vehicle (UAV) in typical indoor navigation tasks.

  3. Navigation and Self-Semantic Location of Drones in Indoor Environments by Combining the Visual Bug Algorithm and Entropy-Based Vision

    Directory of Open Access Journals (Sweden)

    Darío Maravall

    2017-08-01

    Full Text Available We introduce a hybrid algorithm for the self-semantic location and autonomous navigation of robots using entropy-based vision and visual topological maps. In visual topological maps the visual landmarks are considered as leave points for guiding the robot to reach a target point (robot homing in indoor environments. These visual landmarks are defined from images of relevant objects or characteristic scenes in the environment. The entropy of an image is directly related to the presence of a unique object or the presence of several different objects inside it: the lower the entropy the higher the probability of containing a single object inside it and, conversely, the higher the entropy the higher the probability of containing several objects inside it. Consequently, we propose the use of the entropy of images captured by the robot not only for the landmark searching and detection but also for obstacle avoidance. If the detected object corresponds to a landmark, the robot uses the suggestions stored in the visual topological map to reach the next landmark or to finish the mission. Otherwise, the robot considers the object as an obstacle and starts a collision avoidance maneuver. In order to validate the proposal we have defined an experimental framework in which the visual bug algorithm is used by an Unmanned Aerial Vehicle (UAV in typical indoor navigation tasks.

  4. 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.

  5. Validating rankings in soccer championships

    Directory of Open Access Journals (Sweden)

    Annibal Parracho Sant'Anna

    2012-08-01

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

  6. 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

  7. Combined Reduced-Rank Transform

    Directory of Open Access Journals (Sweden)

    Anatoli Torokhti

    2006-04-01

    Full Text Available We propose and justify a new approach to constructing optimal nonlinear transforms of random vectors. We show that the proposed transform improves such characteristics of {rank-reduced} transforms as compression ratio, accuracy of decompression and reduces required computational work. The proposed transform ${mathcal T}_p$ is presented in the form of a sum with $p$ terms where each term is interpreted as a particular rank-reduced transform. Moreover, terms in ${mathcal T}_p$ are represented as a combination of three operations ${mathcal F}_k$, ${mathcal Q}_k$ and ${oldsymbol{varphi}}_k$ with $k=1,ldots,p$. The prime idea is to determine ${mathcal F}_k$ separately, for each $k=1,ldots,p$, from an associated rank-constrained minimization problem similar to that used in the Karhunen--Lo`{e}ve transform. The operations ${mathcal Q}_k$ and ${oldsymbol{varphi}}_k$ are auxiliary for f/inding ${mathcal F}_k$. The contribution of each term in ${mathcal T}_p$ improves the entire transform performance. A corresponding unconstrained nonlinear optimal transform is also considered. Such a transform is important in its own right because it is treated as an optimal filter without signal compression. A rigorous analysis of errors associated with the proposed transforms is given.

  8. 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.

  9. 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.

  10. Entropy-based benchmarking methods

    NARCIS (Netherlands)

    Temurshoev, Umed

    2012-01-01

    We argue that benchmarking sign-volatile series should be based on the principle of movement and sign preservation, which states that a bench-marked series should reproduce the movement and signs in the original series. We show that the widely used variants of Denton (1971) method and the growth

  11. 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;…

  12. Methodology, Meaning and Usefulness of Rankings

    Science.gov (United States)

    Williams, Ross

    2008-01-01

    University rankings are having a profound effect on both higher education systems and individual universities. In this paper we outline these effects, discuss the desirable characteristics of a good ranking methodology and document existing practice, with an emphasis on the two main international rankings (Shanghai Jiao Tong and THES-QS). We take…

  13. Tool for Ranking Research Options

    Science.gov (United States)

    Ortiz, James N.; Scott, Kelly; Smith, Harold

    2005-01-01

    Tool for Research Enhancement Decision Support (TREDS) is a computer program developed to assist managers in ranking options for research aboard the International Space Station (ISS). It could likely also be adapted to perform similar decision-support functions in industrial and academic settings. TREDS provides a ranking of the options, based on a quantifiable assessment of all the relevant programmatic decision factors of benefit, cost, and risk. The computation of the benefit for each option is based on a figure of merit (FOM) for ISS research capacity that incorporates both quantitative and qualitative inputs. Qualitative inputs are gathered and partly quantified by use of the time-tested analytical hierarchical process and used to set weighting factors in the FOM corresponding to priorities determined by the cognizant decision maker(s). Then by use of algorithms developed specifically for this application, TREDS adjusts the projected benefit for each option on the basis of levels of technical implementation, cost, and schedule risk. Based partly on Excel spreadsheets, TREDS provides screens for entering cost, benefit, and risk information. Drop-down boxes are provided for entry of qualitative information. TREDS produces graphical output in multiple formats that can be tailored by users.

  14. Issue Management Risk Ranking Systems

    Energy Technology Data Exchange (ETDEWEB)

    Novack, Steven David; Marshall, Frances Mc Clellan; Stromberg, Howard Merion; Grant, Gary Michael

    1999-06-01

    Thousands of safety issues have been collected on-line at the Idaho National Engineering and Environmental Laboratory (INEEL) as part of the Issue Management Plan. However, there has been no established approach to prioritize collected and future issues. The authors developed a methodology, based on hazards assessment, to identify and risk rank over 5000 safety issues collected at INEEL. This approach required that it was easily applied and understandable for site adaptation and commensurate with the Integrated Safety Plan. High-risk issues were investigated and mitigative/preventive measures were suggested and ranked based on a cost-benefit scheme to provide risk-informed safety measures. This methodology was consistent with other integrated safety management goals and tasks providing a site-wide risk informed decision tool to reduce hazardous conditions and focus resources on high-risk safety issues. As part of the issue management plan, this methodology was incorporated at the issue collection level and training was provided to management to better familiarize decision-makers with concepts of safety and risk. This prioritization methodology and issue dissemination procedure will be discussed. Results of issue prioritization and training efforts will be summarized. Difficulties and advantages of the process will be reported. Development and incorporation of this process into INEELs lessons learned reporting and the site-wide integrated safety management program will be shown with an emphasis on establishing self reliance and ownership of safety issues.

  15. 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.

  16. Rank Modulation for Translocation Error Correction

    CERN Document Server

    Farnoud, Farzad; Milenkovic, Olgica

    2012-01-01

    We consider rank modulation codes for flash memories that allow for handling arbitrary charge drop errors. Unlike classical rank modulation codes used for correcting errors that manifest themselves as swaps of two adjacently ranked elements, the proposed \\emph{translocation rank codes} account for more general forms of errors that arise in storage systems. Translocations represent a natural extension of the notion of adjacent transpositions and as such may be analyzed using related concepts in combinatorics and rank modulation coding. Our results include tight bounds on the capacity of translocation rank codes, construction techniques for asymptotically good codes, as well as simple decoding methods for one class of structured codes. As part of our exposition, we also highlight the close connections between the new code family and permutations with short common subsequences, deletion and insertion error-correcting codes for permutations and permutation arrays.

  17. Dynamics of Ranking Processes in Complex Systems

    Science.gov (United States)

    Blumm, Nicholas; Ghoshal, Gourab; Forró, Zalán; Schich, Maximilian; Bianconi, Ginestra; Bouchaud, Jean-Philippe; Barabási, Albert-László

    2012-09-01

    The world is addicted to ranking: everything, from the reputation of scientists, journals, and universities to purchasing decisions is driven by measured or perceived differences between them. Here, we analyze empirical data capturing real time ranking in a number of systems, helping to identify the universal characteristics of ranking dynamics. We develop a continuum theory that not only predicts the stability of the ranking process, but shows that a noise-induced phase transition is at the heart of the observed differences in ranking regimes. The key parameters of the continuum theory can be explicitly measured from data, allowing us to predict and experimentally document the existence of three phases that govern ranking stability.

  18. 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.

  19. Ranking in Swiss system chess team tournaments

    OpenAIRE

    Csató, László

    2015-01-01

    The paper uses paired comparison-based scoring procedures for ranking the participants of a Swiss system chess team tournament. We present the main challenges of ranking in Swiss system, the features of individual and team competitions as well as the failures of official lexicographical orders. The tournament is represented as a ranking problem, our model is discussed with respect to the properties of the score, generalized row sum and least squares methods. The proposed procedure is illustra...

  20. A universal rank-size law

    CERN Document Server

    Ausloos, Marcel

    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.

  1. Methodology for ranking restoration options

    Energy Technology Data Exchange (ETDEWEB)

    Hedemann Jensen, Per

    1999-04-01

    The work described in this report has been performed as a part of the RESTRAT Project FI4P-CT95-0021a (PL 950128) co-funded by the Nuclear Fission Safety Programme of the European Commission. The RESTRAT project has the overall objective of developing generic methodologies for ranking restoration techniques as a function of contamination and site characteristics. The project includes analyses of existing remediation methodologies and contaminated sites, and is structured in the following steps: characterisation of relevant contaminated sites; identification and characterisation of relevant restoration techniques; assessment of the radiological impact; development and application of a selection methodology for restoration options; formulation of generic conclusions and development of a manual. The project is intended to apply to situations in which sites with nuclear installations have been contaminated with radioactive materials as a result of the operation of these installations. The areas considered for remedial measures include contaminated land areas, rivers and sediments in rivers, lakes, and sea areas. Five contaminated European sites have been studied. Various remedial measures have been envisaged with respect to the optimisation of the protection of the populations being exposed to the radionuclides at the sites. Cost-benefit analysis and multi-attribute utility analysis have been applied for optimisation. Health, economic and social attributes have been included and weighting factors for the different attributes have been determined by the use of scaling constants. (au)

  2. Ranking documents with a thesaurus.

    Science.gov (United States)

    Rada, R; Bicknell, E

    1989-09-01

    This article reports on exploratory experiments in evaluating and improving a thesaurus through studying its effect on retrieval. A formula called DISTANCE was developed to measure the conceptual distance between queries and documents encoded as sets of thesaurus terms. DISTANCE references MeSH (Medical Subject Headings) and assesses the degree of match between a MeSH-encoded query and document. The performance of DISTANCE on MeSH is compared to the performance of people in the assessment of conceptual distance between queries and documents, and is found to simulate with surprising accuracy the human performance. The power of the computer simulation stems both from the tendency of people to rely heavily on broader-than (BT) relations in making decisions about conceptual distance and from the thousands of accurate BT relations in MeSH. One source for discrepancy between the algorithms' measurement of closeness between query and document and people's measurement of closeness between query and document is occasional inconsistency in the BT relations. Our experiments with adding non-BT relations to MeSH showed how these non-BT non-BT relations to MeSH showed how these non-BT relations could improve document ranking, if DISTANCE were also appropriately revised to treat these relations differently from BT relations.

  3. 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....

  4. 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...

  5. Ranked Conservation Opportunity Areas for Region 7 (ECO_RES.RANKED_OAS)

    Data.gov (United States)

    U.S. Environmental Protection Agency — The RANKED_OAS are all the Conservation Opportunity Areas identified by MoRAP that have subsequently been ranked by patch size, landform representation, and the...

  6. 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.

  7. 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.

  8. 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

  9. 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

  10. Biplots in Reduced-Rank Regression

    NARCIS (Netherlands)

    Braak, ter C.J.F.; Looman, C.W.N.

    1994-01-01

    Regression problems with a number of related response variables are typically analyzed by separate multiple regressions. This paper shows how these regressions can be visualized jointly in a biplot based on reduced-rank regression. Reduced-rank regression combines multiple regression and principal

  11. 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…

  12. 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

  13. Generating and ranking of Dyck words

    CERN Document Server

    Kasa, Zoltan

    2010-01-01

    A new algorithm to generate all Dyck words is presented, which is used in ranking and unranking Dyck words. We emphasize the importance of using Dyck words in encoding objects related to Catalan numbers. As a consequence of formulas used in the ranking algorithm we can obtain a recursive formula for the nth Catalan number.

  14. Low-Pass Filtering Approach via Empirical Mode Decomposition Improves Short-Scale Entropy-Based Complexity Estimation of QT Interval Variability in Long QT Syndrome Type 1 Patients

    Directory of Open Access Journals (Sweden)

    Vlasta Bari

    2014-09-01

    Full Text Available Entropy-based complexity of cardiovascular variability at short time scales is largely dependent on the noise and/or action of neural circuits operating at high frequencies. This study proposes a technique for canceling fast variations from cardiovascular variability, thus limiting the effect of these overwhelming influences on entropy-based complexity. The low-pass filtering approach is based on the computation of the fastest intrinsic mode function via empirical mode decomposition (EMD and its subtraction from the original variability. Sample entropy was exploited to estimate complexity. The procedure was applied to heart period (HP and QT (interval from Q-wave onset to T-wave end variability derived from 24-hour Holter recordings in 14 non-mutation carriers (NMCs and 34 mutation carriers (MCs subdivided into 11 asymptomatic MCs (AMCs and 23 symptomatic MCs (SMCs. All individuals belonged to the same family developing long QT syndrome type 1 (LQT1 via KCNQ1-A341V mutation. We found that complexity indexes computed over EMD-filtered QT variability differentiated AMCs from NMCs and detected the effect of beta-blocker therapy, while complexity indexes calculated over EMD-filtered HP variability separated AMCs from SMCs. The EMD-based filtering method enhanced features of the cardiovascular control that otherwise would have remained hidden by the dominant presence of noise and/or fast physiological variations, thus improving classification in LQT1.

  15. University ranking methodologies. An interview with Ben Sowter about the Quacquarelli Symonds World University Ranking

    OpenAIRE

    Alberto Baccini; Antono Banfi; Giuseppe De Nicolao; Paola Galimberti

    2015-01-01

    University rankings represent a controversial issue in the debate about higher education policy. One of the best known university ranking is the Quacquarelli Symonds World University Rankings (QS), published annually since 2004 by Quacquarelli Symonds ltd, a company founded in 1990 and headquartered in London. QS provides a ranking based on a score calculated by weighting six different indicators. The 2015 edition, published in October 2015, introduced major methodological innovations and, as...

  16. 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)

  17. 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.

  18. Reliability of journal impact factor rankings

    Science.gov (United States)

    Greenwood, Darren C

    2007-01-01

    Background Journal impact factors and their ranks are used widely by journals, researchers, and research assessment exercises. Methods Based on citations to journals in research and experimental medicine in 2005, Bayesian Markov chain Monte Carlo methods were used to estimate the uncertainty associated with these journal performance indicators. Results Intervals representing plausible ranges of values for journal impact factor ranks indicated that most journals cannot be ranked with great precision. Only the top and bottom few journals could place any confidence in their rank position. Intervals were wider and overlapping for most journals. Conclusion Decisions placed on journal impact factors are potentially misleading where the uncertainty associated with the measure is ignored. This article proposes that caution should be exercised in the interpretation of journal impact factors and their ranks, and specifically that a measure of uncertainty should be routinely presented alongside the point estimate. PMID:18005435

  19. Reliability of journal impact factor rankings

    Directory of Open Access Journals (Sweden)

    Greenwood Darren C

    2007-11-01

    Full Text Available Abstract Background Journal impact factors and their ranks are used widely by journals, researchers, and research assessment exercises. Methods Based on citations to journals in research and experimental medicine in 2005, Bayesian Markov chain Monte Carlo methods were used to estimate the uncertainty associated with these journal performance indicators. Results Intervals representing plausible ranges of values for journal impact factor ranks indicated that most journals cannot be ranked with great precision. Only the top and bottom few journals could place any confidence in their rank position. Intervals were wider and overlapping for most journals. Conclusion Decisions placed on journal impact factors are potentially misleading where the uncertainty associated with the measure is ignored. This article proposes that caution should be exercised in the interpretation of journal impact factors and their ranks, and specifically that a measure of uncertainty should be routinely presented alongside the point estimate.

  20. Cointegration rank testing under conditional heteroskedasticity

    DEFF Research Database (Denmark)

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

    2010-01-01

    (martingale difference) innovations. We first demonstrate that the limiting null distributions of the rank statistics coincide with those derived by previous authors who assume either independent and identically distributed (i.i.d.) or (strict and covariance) stationary martingale difference innovations. We...... then propose wild bootstrap implementations of the cointegrating rank tests and demonstrate that the associated bootstrap rank statistics replicate the first-order asymptotic null distributions of the rank statistics. We show that the same is also true of the corresponding rank tests based on the i.......i.d. bootstrap of Swensen (2006, Econometrica 74, 1699-1714). The wild bootstrap, however, has the important property that, unlike the i.i.d. bootstrap, it preserves in the resampled data the pattern of heteroskedasticity present in the original shocks. Consistent with this, numerical evidence suggests that...

  1. 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.

  2. 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}.

  3. 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.

  4. University ranking methodologies. An interview with Ben Sowter about the Quacquarelli Symonds World University Ranking

    Directory of Open Access Journals (Sweden)

    Alberto Baccini

    2015-10-01

    Full Text Available University rankings represent a controversial issue in the debate about higher education policy. One of the best known university ranking is the Quacquarelli Symonds World University Rankings (QS, published annually since 2004 by Quacquarelli Symonds ltd, a company founded in 1990 and headquartered in London. QS provides a ranking based on a score calculated by weighting six different indicators. The 2015 edition, published in October 2015, introduced major methodological innovations and, as a consequence, many universities worldwide underwent major changes of their scores and ranks. Ben Sowter, head of division of intelligence unit of Quacquarelli Symonds, responds to 15 questions about the new QS methodology.

  5. On a common generalization of Shelah's 2-rank, dp-rank, and o-minimal dimension

    OpenAIRE

    Guingona, Vincent; Hill, Cameron Donnay

    2013-01-01

    In this paper, we build a dimension theory related to Shelah's 2-rank, dp-rank, and o-minimal dimension. We call this dimension op-dimension. We exhibit the notion of the n-multi-order property, generalizing the order property, and use this to create op-rank, which generalizes 2-rank. From this we build op-dimension. We show that op-dimension bounds dp-rank, that op-dimension is sub-additive, and op-dimension generalizes o-minimal dimension in o-minimal theories.

  6. Academic rankings: an approach to rank portuguese universities Rankings académicos: un abordaje para clasificar las universidades portuguesas Rankings acadêmicos: uma abordagem ao ranking das universidades portuguesas

    Directory of Open Access Journals (Sweden)

    Pedro Bernardino

    2010-03-01

    Full Text Available The academic rankings are a controversial subject in higher education. However, despite all the criticism, academic rankings are here to stay and more and more different stakeholders use rankings to obtain information about the institutions' performance. The two most well-known rankings, The Times and the Shanghai Jiao Tong University rankings have different methodologies. The Times ranking is based on peer review, whereas the Shanghai ranking has only quantitative indicators and is mainly based on research outputs. In Germany, the CHE ranking uses a different methodology from the traditional rankings, allowing the users to choose criteria and weights. The Portuguese higher education institutions are performing below their European peers, and the Government believes that an academic ranking could improve both performance and competitiveness between institutions. The purpose of this paper is to analyse the advantages and problems of academic rankings and provide guidance to a new Portuguese ranking.Los rankings académicos son un tema muy contradictorio en la enseñanza superior. Todavía, además de todas las críticas los rankings están para quedarse entre nosotros. Y cada vez más, diferentes stakeholders utilizan los rankings para obtener información sobre el desempeño de las instituciones. Dos de los rankings más conocidos, el The Times y el ranking de la universidad de Shangai Jiao Tong tienen métodos distintos. El The Times se basa en la opinión de expertos mientras el ranking de la universidad de Shangai presenta solamente indicadores cuantitativos y mayoritariamente basados en los resultados de actividades de investigación. En Alemania el ranking CHE usa un método distinto permitiendo al utilizador elegir los criterios y su importancia. Las instituciones de enseñanza superior portuguesas tienen un desempeño abajo de las europeas y el gobierno cree que un ranking académico podría contribuir para mejorar su desempeño y

  7. 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.

  8. Adiabatic Quantum Algorithm for Search Engine Ranking

    Science.gov (United States)

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

    2012-06-01

    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.

  9. Augmenting the Deliberative Method for Ranking Risks.

    Science.gov (United States)

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

    2016-01-01

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

  10. C/EBPα and PU.1 exhibit different responses to RANK signaling for osteoclastogenesis.

    Science.gov (United States)

    Jules, Joel; Chen, Wei; Li, Yi-Ping

    2017-10-11

    The transcription factors C/EBPα and PU.1 are upregulated by RANKL through activation of its receptor RANK during osteoclastogenesis and are critical for osteoclast differentiation. Herein we investigated the mechanisms underlying how C/EBPα and PU.1 regulate osteoclast differentiation in response to RANK signaling. We showed that C/EBPα or PU.1 overexpression could initiate osteoclastogenesis and upregulate the expressions of the osteoclast genes encoding the nuclear factor of activated T-cells, C1, cathepsin K, and tartrate-resistant acid phosphatase independently of RANKL. However, while PU.1 upregulated C/EBPα, C/EBPα could not upregulate PU.1. RANK has a unique cytoplasmic domain, 535IVVY538 motif, which is crucial for osteoclast differentiation. We demonstrated that mutational inactivation of RANK IVVY motif blocked osteoclast differentiation and significantly attenuated C/EBPα, but not PU.1, expression, indicating that RANK-IVVY-induced signaling is dispensable to PU.1 upregulation during osteoclastogenesis. However, C/EBPα or PU.1 overexpression failed to promote osteoclastogenesis in cells expressing mutated RANK IVVY motif. We noted that RANK-IVVY-motif inactivation significantly repressed osteoclast genes as compared with a vector control, suggesting that IVVY motif might also negatively regulate osteoclast inhibitors during osteoclastogenesis. Consistently, IVVY-motif inactivation triggered upregulation of RBP-J, a potent osteoclast inhibitor, during osteoclastogenesis. Notably, C/EBPα or PU.1 overexpression in cells expressing mutated RANK IVVY motif failed to control the deregulated RBP-J expression, resulting in repression of osteoclast genes. Accordingly, RBP-J silencing in the mutant cells rescued osteoclastogenesis with C/EBPα or PU.1 overexpression. In conclusion, we revealed that while PU.1 and C/EBPα are critical for osteoclastogenesis, they respond differently to RANKL-induced activation of RANK IVVY motif. Copyright © 2016

  11. 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...

  12. The exact probability distribution of the rank product statistics for replicated experiments.

    Science.gov (United States)

    Eisinga, Rob; Breitling, Rainer; Heskes, Tom

    2013-03-18

    The rank product method is a widely accepted technique for detecting differentially regulated genes in replicated microarray experiments. To approximate the sampling distribution of the rank product statistic, the original publication proposed a permutation approach, whereas recently an alternative approximation based on the continuous gamma distribution was suggested. However, both approximations are imperfect for estimating small tail probabilities. In this paper we relate the rank product statistic to number theory and provide a derivation of its exact probability distribution and the true tail probabilities. Copyright © 2013 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

  13. Block models and personalized PageRank

    National Research Council Canada - National Science Library

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

    2017-01-01

    ...? 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...

  14. 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.

  15. Ranking Forestry Investments With Parametric Linear Programming

    Science.gov (United States)

    Paul A. Murphy

    1976-01-01

    Parametric linear programming is introduced as a technique for ranking forestry investments under multiple constraints; it combines the advantages of simple tanking and linear programming as capital budgeting tools.

  16. Superfund Hazard Ranking System Training Course

    Science.gov (United States)

    The Hazard Ranking System (HRS) training course is a four and ½ day, intermediate-level course designed for personnel who are required to compile, draft, and review preliminary assessments (PAs), site inspections (SIs), and HRS documentation records/packag

  17. A cognitive model for aggregating people's rankings

    National Research Council Canada - National Science Library

    Lee, Michael D; Steyvers, Mark; Miller, Brent

    2014-01-01

    .... Applications of the model to 23 data sets, dealing with general knowledge and prediction tasks, show that the model performs well in producing an aggregate ranking that is often close to the ground...

  18. 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.

  19. Rank rigidity for CAT(0) cube complexes

    OpenAIRE

    Caprace, Pierre-Emmanuel; Sageev, Michah

    2010-01-01

    We prove that any group acting essentially without a fixed point at infinity on an irreducible finite-dimensional CAT(0) cube complex contains a rank one isometry. This implies that the Rank Rigidity Conjecture holds for CAT(0) cube complexes. We derive a number of other consequences for CAT(0) cube complexes, including a purely geometric proof of the Tits Alternative, an existence result for regular elements in (possibly non-uniform) lattices acting on cube complexes, and a characterization ...

  20. NUCLEAR POWER PLANTS SAFETY IMPROVEMENT PROJECTS RANKING

    OpenAIRE

    Григорян, Анна Сергеевна; Тигран Георгиевич ГРИГОРЯН; Квасневский, Евгений Анатольевич

    2013-01-01

    The ranking nuclear power plants safety improvement projects is the most important task for ensuring the efficiency of NPP project management office work. Total amount of projects in NPP portfolio may reach more than 400. Features of the nuclear power plants safety improvement projects ranking in NPP portfolio determine the choice of the decision verbal analysis as a method of decision-making, as it allows to quickly compare the number of alternatives that are not available at the time of con...

  1. 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...... the relevance and importance of music. The proposed method may support users with diverse needs when searching for music....

  2. 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.

  3. Hierarchical Rank Aggregation with Applications to Nanotoxicology.

    Science.gov (United States)

    Patel, Trina; Telesca, Donatello; Rallo, Robert; George, Saji; Xia, Tian; Nel, André E

    2013-06-01

    The development of high throughput screening (HTS) assays in the field of nanotoxicology provide new opportunities for the hazard assessment and ranking of engineered nanomaterials (ENMs). It is often necessary to rank lists of materials based on multiple risk assessment parameters, often aggregated across several measures of toxicity and possibly spanning an array of experimental platforms. Bayesian models coupled with the optimization of loss functions have been shown to provide an effective framework for conducting inference on ranks. In this article we present various loss-function-based ranking approaches for comparing ENM within experiments and toxicity parameters. Additionally, we propose a framework for the aggregation of ranks across different sources of evidence while allowing for differential weighting of this evidence based on its reliability and importance in risk ranking. We apply these methods to high throughput toxicity data on two human cell-lines, exposed to eight different nanomaterials, and measured in relation to four cytotoxicity outcomes. This article has supplementary material online.

  4. Retrieval with gene queries

    Directory of Open Access Journals (Sweden)

    Srinivasan Padmini

    2006-04-01

    Full Text Available Abstract Background Accuracy of document retrieval from MEDLINE for gene queries is crucially important for many applications in bioinformatics. We explore five information retrieval-based methods to rank documents retrieved by PubMed gene queries for the human genome. The aim is to rank relevant documents higher in the retrieved list. We address the special challenges faced due to ambiguity in gene nomenclature: gene terms that refer to multiple genes, gene terms that are also English words, and gene terms that have other biological meanings. Results Our two baseline ranking strategies are quite similar in performance. Two of our three LocusLink-based strategies offer significant improvements. These methods work very well even when there is ambiguity in the gene terms. Our best ranking strategy offers significant improvements on three different kinds of ambiguities over our two baseline strategies (improvements range from 15.9% to 17.7% and 11.7% to 13.3% depending on the baseline. For most genes the best ranking query is one that is built from the LocusLink (now Entrez Gene summary and product information along with the gene names and aliases. For others, the gene names and aliases suffice. We also present an approach that successfully predicts, for a given gene, which of these two ranking queries is more appropriate. Conclusion We explore the effect of different post-retrieval strategies on the ranking of documents returned by PubMed for human gene queries. We have successfully applied some of these strategies to improve the ranking of relevant documents in the retrieved sets. This holds true even when various kinds of ambiguity are encountered. We feel that it would be very useful to apply strategies like ours on PubMed search results as these are not ordered by relevance in any way. This is especially so for queries that retrieve a large number of documents.

  5. ARWU vs. Alternative ARWU Ranking: What are the Consequences for Lower Ranked Universities?

    Directory of Open Access Journals (Sweden)

    Milica Maričić

    2017-05-01

    Full Text Available The ARWU ranking has been a source of academic debate since its development in 2003, but the same does not account for the Alternative ARWU ranking. Namely, the Alternative ARWU ranking attempts to reduce the influence of the prestigious indicators Alumni and Award which are based on the number of received Nobel Prizes and Fields Medals by alumni or university staff. However, the consequences of the reduction of the two indicators have not been scrutinized in detail. Therefore, we propose a statistical approach to the comparison of the two rankings and an in-depth analysis of the Alternative ARWU groups. The obtained results, which are based on the official data, can provide new insights into the nature of the Alternative ARWU ranking. The presented approach might initiate further research on the Alternative ARWU ranking and on the impact of university ranking’s list length. JEL Classification: C10, C38, I23

  6. Efficient Top-k Search for PageRank

    National Research Council Canada - National Science Library

    Fujiwara, Yasuhiro; Nakatsuji, Makoto; Shiokawa, Hiroaki; Mishima, Takeshi; Onizuka, Makoto

    2015-01-01

      In AI communities, many applications utilize PageRank. To obtain high PageRank score nodes, the original approach iteratively computes the PageRank score of each node until convergence from the whole graph...

  7. 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.

  8. 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.

  9. Mining Functional Modules in Heterogeneous Biological Networks Using Multiplex PageRank Approach.

    Science.gov (United States)

    Li, Jun; Zhao, Patrick X

    2016-01-01

    Identification of functional modules/sub-networks in large-scale biological networks is one of the important research challenges in current bioinformatics and systems biology. Approaches have been developed to identify functional modules in single-class biological networks; however, methods for systematically and interactively mining multiple classes of heterogeneous biological networks are lacking. In this paper, we present a novel algorithm (called mPageRank) that utilizes the Multiplex PageRank approach to mine functional modules from two classes of biological networks. We demonstrate the capabilities of our approach by successfully mining functional biological modules through integrating expression-based gene-gene association networks and protein-protein interaction networks. We first compared the performance of our method with that of other methods using simulated data. We then applied our method to identify the cell division cycle related functional module and plant signaling defense-related functional module in the model plant Arabidopsis thaliana. Our results demonstrated that the mPageRank method is effective for mining sub-networks in both expression-based gene-gene association networks and protein-protein interaction networks, and has the potential to be adapted for the discovery of functional modules/sub-networks in other heterogeneous biological networks. The mPageRank executable program, source code, the datasets and results of the presented two case studies are publicly and freely available at http://plantgrn.noble.org/MPageRank/.

  10. Ranking Fuzzy Numbers and Its Application to Products Attributes Preferences

    OpenAIRE

    Abdullah, Lazim; Fauzee, Nor Nashrah Ahmad

    2011-01-01

    Ranking is one of the widely used methods in fuzzy decision making environment. The recent ranking fuzzy numbers proposed by Wang and Li is claimed to be the improved version in ranking. However, the method was never been simplified and tested in real life application. This paper presents a four-step computation of ranking fuzzy numbers and its application in ranking attributes of selected chocolate products. The four steps algorithm was formulated to rank fuzzy numbers and followed by a tes...

  11. 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.

  12. A network-based dynamical ranking system

    CERN Document Server

    Motegi, Shun

    2012-01-01

    Ranking players or teams in sports is of practical interests. From the viewpoint of networks, a ranking system is equivalent a centrality measure for sports networks, whereby a directed link represents the result of a single game. Previously proposed network-based ranking systems are derived from static networks, i.e., aggregation of the results of games over time. However, the score (i.e., strength) of a player, for example, depends on time. Defeating a renowned player in the peak performance is intuitively more rewarding than defeating the same player in other periods. To account for this factor, we propose a dynamic variant of such a network-based ranking system and apply it to professional men's tennis data. Our ranking system, also interpreted as a centrality measure for directed temporal networks, has two parameters. One parameter represents the exponential decay rate of the past score, and the other parameter controls the effect of indirect wins on the score. We derive a set of linear online update equ...

  13. 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.

  14. A Cognitive Model for Aggregating People's Rankings

    Science.gov (United States)

    Lee, Michael D.; Steyvers, Mark; Miller, Brent

    2014-01-01

    We develop a cognitive modeling approach, motivated by classic theories of knowledge representation and judgment from psychology, for combining people's rankings of items. The model makes simple assumptions about how individual differences in knowledge lead to observed ranking data in behavioral tasks. We implement the cognitive model as a Bayesian graphical model, and use computational sampling to infer an aggregate ranking and measures of the individual expertise. Applications of the model to 23 data sets, dealing with general knowledge and prediction tasks, show that the model performs well in producing an aggregate ranking that is often close to the ground truth and, as in the “wisdom of the crowd” effect, usually performs better than most of individuals. We also present some evidence that the model outperforms the traditional statistical Borda count method, and that the model is able to infer people's relative expertise surprisingly well without knowing the ground truth. We discuss the advantages of the cognitive modeling approach to combining ranking data, and in wisdom of the crowd research generally, as well as highlighting a number of potential directions for future model development. PMID:24816733

  15. A Review of Outcomes of Seven World University Ranking Systems

    National Research Council Canada - National Science Library

    Mahmood Khosrowjerdi; Neda Zeraatkar

    2012-01-01

    There are many national and international ranking systems rank the universities and higher education institutions of the world, nationally or internationally, based on the same or different criteria...

  16. Gene

    Data.gov (United States)

    U.S. Department of Health & Human Services — Gene integrates information from a wide range of species. A record may include nomenclature, Reference Sequences (RefSeqs), maps, pathways, variations, phenotypes,...

  17. Ranking schools on external knowledge tests results

    Directory of Open Access Journals (Sweden)

    Gašper Cankar

    2007-01-01

    Full Text Available The paper discusses the use of external knowledge test results for school ranking and the implicit effect of such ranking. A question of validity is raised and a review of research literature and main known problems are presented. In many western countries publication of school results is a common practice and a similar trend can be observed in Slovenia. Experiences of other countries help to predict positive and negative aspects of such publication. Results of external knowledge tests produce very limited information about school quality—if we use other sources of information our ranking of schools can be very different. Nevertheless, external knowledge tests can yield useful information. If we want to improve quality in schools, we must allow schools to use this information themselves and improve from within. Broad public scrutiny is unnecessary and problematic—it moves the focus of school efforts from real improvement of quality to mere improvement of the school public image.

  18. Resolution of ranking hierarchies in directed networks

    Science.gov (United States)

    Barucca, Paolo; Lillo, Fabrizio

    2018-01-01

    Identifying hierarchies and rankings of nodes in directed graphs is fundamental in many applications such as social network analysis, biology, economics, and finance. A recently proposed method identifies the hierarchy by finding the ordered partition of nodes which minimises a score function, termed agony. This function penalises the links violating the hierarchy in a way depending on the strength of the violation. To investigate the resolution of ranking hierarchies we introduce an ensemble of random graphs, the Ranked Stochastic Block Model. We find that agony may fail to identify hierarchies when the structure is not strong enough and the size of the classes is small with respect to the whole network. We analytically characterise the resolution threshold and we show that an iterated version of agony can partly overcome this resolution limit. PMID:29394278

  19. 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...

  20. 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; ...

  1. Adaptive distributional extensions to DFR ranking

    DEFF Research Database (Denmark)

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

    2016-01-01

    Divergence From Randomness (DFR) ranking models assume that informative terms are distributed in a corpus differently than non-informative terms. Different statistical models (e.g. Poisson, geometric) are used to model the distribution of non-informative terms, producing different DFR models....... An informative term is then detected by measuring the divergence of its distribution from the distribution of non-informative terms. However, there is little empirical evidence that the distributions of non-informative terms used in DFR actually fit current datasets. Practically this risks providing a poor...... separation between informative and non-informative terms, thus compromising the discriminative power of the ranking model. We present a novel extension to DFR, which first detects the best-fitting distribution of non-informative terms in a collection, and then adapts the ranking computation to this best...

  2. 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.

  3. Pulling Rank: A Plan to Help Students with College Choice in an Age of Rankings

    Science.gov (United States)

    Thacker, Lloyd

    2008-01-01

    Colleges and universities are "ranksteering"--driving under the influence of popular college rankings systems like "U.S. News and World Report's" Best Colleges. This article examines the criticisms of college rankings and describes how a group of education leaders is honing a plan to end the tyranny of the ratings game and better help students and…

  4. 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.

  5. Discovery of DNA methylation markers in cervical cancer using relaxation ranking

    Directory of Open Access Journals (Sweden)

    van Criekinge Wim

    2008-11-01

    Full Text Available Abstract Background To discover cancer specific DNA methylation markers, large-scale screening methods are widely used. The pharmacological unmasking expression microarray approach is an elegant method to enrich for genes that are silenced and re-expressed during functional reversal of DNA methylation upon treatment with demethylation agents. However, such experiments are performed in in vitro (cancer cell lines, mostly with poor relevance when extrapolating to primary cancers. To overcome this problem, we incorporated data from primary cancer samples in the experimental design. A strategy to combine and rank data from these different data sources is essential to minimize the experimental work in the validation steps. Aim To apply a new relaxation ranking algorithm to enrich DNA methylation markers in cervical cancer. Results The application of a new sorting methodology allowed us to sort high-throughput microarray data from both cervical cancer cell lines and primary cervical cancer samples. The performance of the sorting was analyzed in silico. Pathway and gene ontology analysis was performed on the top-selection and gives a strong indication that the ranking methodology is able to enrich towards genes that might be methylated. Terms like regulation of progression through cell cycle, positive regulation of programmed cell death as well as organ development and embryonic development are overrepresented. Combined with the highly enriched number of imprinted and X-chromosome located genes, and increased prevalence of known methylation markers selected from cervical (the highest-ranking known gene is CCNA1 as well as from other cancer types, the use of the ranking algorithm seems to be powerful in enriching towards methylated genes. Verification of the DNA methylation state of the 10 highest-ranking genes revealed that 7/9 (78% gene promoters showed DNA methylation in cervical carcinomas. Of these 7 genes, 3 (SST, HTRA3 and NPTX1 are not

  6. Ranking Entities in Networks via Lefschetz Duality

    DEFF Research Database (Denmark)

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

    2014-01-01

    In the theory of communication it is essential that agents are able to exchange information. This fact is closely related to the study of connected spaces in topology. A communication network may be modelled as a topological space such that agents can communicate if and only if they belong...... 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...

  7. Compressed Sensing with Rank Deficient Dictionaries

    DEFF Research Database (Denmark)

    Hansen, Thomas Lundgaard; Johansen, Daniel Højrup; Jørgensen, Peter Bjørn

    2012-01-01

    In compressed sensing it is generally assumed that the dictionary matrix constitutes a (possibly overcomplete) basis of the signal space. In this paper we consider dictionaries that do not span the signal space, i.e. rank deficient dictionaries. We show that in this case the signal-to-noise ratio...... (SNR) in the compressed samples can be increased by selecting the rows of the measurement matrix from the column space of the dictionary. As an example application of compressed sensing with a rank deficient dictionary, we present a case study of compressed sensing applied to the Coarse Acquisition (C...

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

    Directory of Open Access Journals (Sweden)

    LI Lan-yin

    2017-04-01

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

  9. Association between OPG, RANK and RANKL gene polymorphisms ...

    Indian Academy of Sciences (India)

    2009) and MMP-9 production. (Sandberg et al. 2006). .... rupture. RANKL promoted vascular smooth muscle cell. (VSMC) calcification via induction of the bone morphogenic protein (BMP) (Panizo et al. 2009). RANKL was highly. 88 ... Bunimov N., Smith J. E., Gosselin D. and Laneuville O. 2007. Translational regulation of ...

  10. SOUTH AFRICAN ARMY RANKS AND INSIGNIA

    African Journals Online (AJOL)

    major, cap- tain, lieutenant;. Other Ranks : Warrant officer, staff sergeant, sergeant, corporal, lance-cor- poral, private.' We apparently had no need for second lieuten- ants at that time, and they were introduced only .... Army warrant officers can also hold the cmmon serv- ice posts of Sergeant-Major of Special Forces.

  11. Kinesiology Faculty Citations across Academic Rank

    Science.gov (United States)

    Knudson, Duane

    2015-01-01

    Citations to research reports are used as a measure for the influence of a scholar's research line when seeking promotion, grants, and awards. The current study documented the distributions of citations to kinesiology scholars of various academic ranks. Google Scholar Citations was searched for user profiles using five research interest areas…

  12. Biomechanics Scholar Citations across Academic Ranks

    Directory of Open Access Journals (Sweden)

    Knudson Duane

    2015-11-01

    Full Text Available Study aim: citations to the publications of a scholar have been used as a measure of the quality or influence of their research record. A world-wide descriptive study of the citations to the publications of biomechanics scholars of various academic ranks was conducted.

  13. Ranking Workplace Competencies: Student and Graduate Perceptions.

    Science.gov (United States)

    Rainsbury, Elizabeth; Hodges, Dave; Burchell, Noel; Lay, Mark

    2002-01-01

    New Zealand business students and graduates made similar rankings of the five most important workplace competencies: computer literacy, customer service orientation, teamwork and cooperation, self-confidence, and willingness to learn. Graduates placed greater importance on most of the 24 competencies, resulting in a statistically significant…

  14. Subject Gateway Sites and Search Engine Ranking.

    Science.gov (United States)

    Thelwall, Mike

    2002-01-01

    Discusses subject gateway sites and commercial search engines for the Web and presents an explanation of Google's PageRank algorithm. The principle question addressed is the conditions under which a gateway site will increase the likelihood that a target page is found in search engines. (LRW)

  15. Ranking related entities: components and analyses

    NARCIS (Netherlands)

    Bron, M.; Balog, K.; de Rijke, M.

    2010-01-01

    Related entity finding is the task of returning a ranked list of homepages of relevant entities of a specified type that need to engage in a given relationship with a given source entity. We propose a framework for addressing this task and perform a detailed analysis of four core components;

  16. Low-rank coal oil agglomeration

    Science.gov (United States)

    Knudson, C.L.; Timpe, R.C.

    1991-07-16

    A low-rank coal oil agglomeration process is described. High mineral content, a high ash content subbituminous coals are effectively agglomerated with a bridging oil which is partially water soluble and capable of entering the pore structure, and is usually coal-derived.

  17. An evaluation and critique of current rankings

    NARCIS (Netherlands)

    Federkeil, Gero; Westerheijden, Donald F.; van Vught, Franciscus A.; Ziegele, Frank

    2012-01-01

    This chapter raises the question of whether university league tables deliver relevant information to one of their key target groups – students. It examines the inherent biases and weaknesses in the methodologies of the major rankings and argues that the concentration on a single indicator of

  18. World University Ranking Methodologies: Stability and Variability

    Science.gov (United States)

    Fidler, Brian; Parsons, Christine

    2008-01-01

    There has been a steady growth in the number of national university league tables over the last 25 years. By contrast, "World University Rankings" are a more recent development and have received little serious academic scrutiny in peer-reviewed publications. Few researchers have evaluated the sources of data and the statistical…

  19. Alternative Class Ranks Using Z-Scores

    Science.gov (United States)

    Brown, Philip H.; Van Niel, Nicholas

    2012-01-01

    Grades at US colleges and universities have increased precipitously over the last 50 years, suggesting that their signalling power has become attenuated. Moreover, average grades have risen disproportionately in some departments, implying that weak students in departments with high grades may obtain better class ranks than strong students in…

  20. Statistical inference of Minimum Rank Factor Analysis

    NARCIS (Netherlands)

    Shapiro, A; Ten Berge, JMF

    For any given number of factors, Minimum Rank Factor Analysis yields optimal communalities for an observed covariance matrix in the sense that the unexplained common variance with that number of factors is minimized, subject to the constraint that both the diagonal matrix of unique variances and the

  1. City Life: Rankings (Livability) versus Perceptions (Satisfaction)

    Science.gov (United States)

    Okulicz-Kozaryn, Adam

    2013-01-01

    I investigate the relationship between the popular Mercer city ranking (livability) and survey data (satisfactions). Livability aims to capture "objective" quality of life such as infrastructure. Survey items capture "subjective" quality of life such as satisfaction with city. The relationship between objective measures of quality of life and…

  2. Matrices with high completely positive semidefinite rank

    NARCIS (Netherlands)

    de Laat, David; Gribling, Sander; Laurent, Monique

    2017-01-01

    A real symmetric matrix M is completely positive semidefinite if it admits a Gram representation by (Hermitian) positive semidefinite matrices of any size d. The smallest such d is called the (complex) completely positive semidefinite rank of M , and it is an open question whether there exists an

  3. Ranking health between countries in international comparisons

    DEFF Research Database (Denmark)

    Brønnum-Hansen, Henrik

    2014-01-01

    Cross-national comparisons and ranking of summary measures of population health sometimes give rise to inconsistent and diverging conclusions. In order to minimise confusion, international comparative studies ought to be based on well-harmonised data with common standards of definitions...

  4. Comparing survival curves using rank tests

    NARCIS (Netherlands)

    Albers, Willem/Wim

    1990-01-01

    Survival times of patients can be compared using rank tests in various experimental setups, including the two-sample case and the case of paired data. Attention is focussed on two frequently occurring complications in medical applications: censoring and tail alternatives. A review is given of the

  5. Smooth rank one perturbations of selfadjoint operators

    NARCIS (Netherlands)

    Hassi, Seppo; Snoo, H.S.V. de; Willemsma, A.D.I.

    Let A be a selfadjoint operator in a Hilbert space aleph with inner product [.,.]. The rank one perturbations of A have the form A+tau [.,omega]omega, tau epsilon R, for some element omega epsilon aleph. In this paper we consider smooth perturbations, i.e. we consider omega epsilon dom \\A\\(k/2) for

  6. Primate Innovation: Sex, Age and Social Rank

    NARCIS (Netherlands)

    Reader, S.M.; Laland, K.N.

    2001-01-01

    Analysis of an exhaustive survey of primate behavior collated from the published literature revealed significant variation in rates of innovation among individuals of different sex, age and social rank. We searched approximately 1,000 articles in four primatology journals, together with other

  7. An algorithm for ranking assignments using reoptimization

    DEFF Research Database (Denmark)

    Pedersen, Christian Roed; Nielsen, Lars Relund; Andersen, Kim Allan

    2008-01-01

    We consider the problem of ranking assignments according to cost in the classical linear assignment problem. An algorithm partitioning the set of possible assignments, as suggested by Murty, is presented where, for each partition, the optimal assignment is calculated using a new reoptimization...... technique. Computational results for the new algorithm are presented...

  8. Ouderdom, omvang en citatiescores: rankings nader bekeken

    NARCIS (Netherlands)

    van Rooij, Jules

    2017-01-01

    By comparing the Top-300 lists of four global university rankings (ARWU, THE, QS, Leiden), three hypotheses are tested: 1) position correlates with size in the ARWU more than in the THE and QS; 2) given their strong dependency on reputation scores, position will be correlated more with a

  9. 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...

  10. 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

  11. 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

  12. World University Rankings: Take with a Large Pinch of Salt

    Science.gov (United States)

    Cheng, Soh Kay

    2011-01-01

    Equating the unequal is misleading, and this happens consistently in comparing rankings from different university ranking systems, as the NUT saga shows. This article illustrates the problem by analyzing the 2011 rankings of the top 100 universities in the AWUR, QSWUR and THEWUR ranking results. It also discusses the reasons why the rankings…

  13. Generalized Reduced Rank Tests using the Singular Value Decomposition

    NARCIS (Netherlands)

    Kleibergen, F.R.; Paap, R.

    2006-01-01

    We propose a novel statistic to test the rank of a matrix. The rank statistic overcomes deficiencies of existing rank statistics, like: a Kronecker covariance matrix for the canonical correlation rank statistic of Anderson [Annals of Mathematical Statistics (1951), 22, 327-351] sensitivity to the

  14. Some upper and lower bounds on PSD-rank

    NARCIS (Netherlands)

    T. J. Lee (Troy); Z. Wei (Zhaohui); R. M. de Wolf (Ronald)

    2014-01-01

    textabstractPositive semidefinite rank (PSD-rank) is a relatively new quantity with applications to combinatorial optimization and communication complexity. We first study several basic properties of PSD-rank, and then develop new techniques for showing lower bounds on the PSD-rank. All of these

  15. Some upper and lower bounds on PSD-rank

    NARCIS (Netherlands)

    Lee, T.; Wei, Z.; de Wolf, R.

    Positive semidefinite rank (PSD-rank) is a relatively new complexity measure on matrices, with applications to combinatorial optimization and communication complexity. We first study several basic properties of PSD-rank, and then develop new techniques for showing lower bounds on the PSD-rank. All

  16. Biology of RANK, RANKL, and osteoprotegerin

    Science.gov (United States)

    Boyce, Brendan F; Xing, Lianping

    2007-01-01

    The discovery of the receptor activator of nuclear factor-κB ligand (RANKL)/RANK/osteoprotegerin (OPG) system and its role in the regulation of bone resorption exemplifies how both serendipity and a logic-based approach can identify factors that regulate cell function. Before this discovery in the mid to late 1990s, it had long been recognized that osteoclast formation was regulated by factors expressed by osteoblast/stromal cells, but it had not been anticipated that members of the tumor necrosis factor superfamily of ligands and receptors would be involved or that the factors involved would have extensive functions beyond bone remodeling. RANKL/RANK signaling regulates the formation of multinucleated osteoclasts from their precursors as well as their activation and survival in normal bone remodeling and in a variety of pathologic conditions. OPG protects the skeleton from excessive bone resorption by binding to RANKL and preventing it from binding to its receptor, RANK. Thus, RANKL/OPG ratio is an important determinant of bone mass and skeletal integrity. Genetic studies in mice indicate that RANKL/RANK signaling is also required for lymph node formation and mammary gland lactational hyperplasia, and that OPG also protects arteries from medial calcification. Thus, these tumor necrosis factor superfamily members have important functions outside bone. Although our understanding of the mechanisms whereby they regulate osteoclast formation has advanced rapidly during the past 10 years, many questions remain about their roles in health and disease. Here we review our current understanding of the role of the RANKL/RANK/OPG system in bone and other tissues. PMID:17634140

  17. The Signature of Maternal Social Rank in Placenta Deoxyribonucleic Acid Methylation Profiles in Rhesus Monkeys.

    Science.gov (United States)

    Massart, Renaud; Suderman, Matthew J; Nemoda, Zsofia; Sutti, Sheila; Ruggiero, Angela M; Dettmer, Amanda M; Suomi, Stephen J; Szyf, Moshe

    2017-05-01

    The effects of social status on human health can be modeled in captive cohorts of nonhuman primates. This study shows that maternal social rank is associated with broad changes in DNA methylation in placentae of rhesus monkeys (N = 10). Differentially methylated genes between social ranks are enriched in signaling pathways playing major roles in placenta physiology. Moreover, the authors found significant overlaps with genes whose expression was previously associated with social rank in adult rhesus monkeys (Tung et al., 2012) and whose methylation was associated with perinatal stress in newborn humans and rhesus monkeys (Nieratschker et al., 2014). These results are consistent with the hypothesis that system-wide epigenetic changes in multiple tissues are involved in long-term adaptations to the social environment. © 2016 The Authors. Child Development © 2016 Society for Research in Child Development, Inc.

  18. Opg, Rank, and Rankl in tooth development: co-ordination of odontogenesis and osteogenesis.

    Science.gov (United States)

    Ohazama, A; Courtney, J-M; Sharpe, P T

    2004-03-01

    Osteoprotegerin (OPG), receptor activator of nuclear factor-kappaB (RANK), and RANK ligand (RANKL) are mediators of various cellular interactions, including bone metabolism. We analyzed expression of these three genes during murine odontogenesis from epithelial thickening to cytodifferentiation stages. Opg showed expression in the thickening and bud epithelium. Expression of Opg and Rank was observed in both the internal and the external enamel epithelium as well as in the dental papilla mesenchyme. Although Rankl expression was not detected in tooth epithelium or mesenchyme, it was expressed in pre-osteogenic mesenchymal cells close to developing tooth germs. All three genes were detected in developing dentary bone at P0. The addition of exogenous OPG to explant cultures of tooth primordia produced a delay in tooth development that resulted in reduced mineralization. We propose that the spatiotemporal expression of these molecules in early tooth and bone primordia cells has a role in co-ordinating bone and tooth development.

  19. Ranked Conservation Opportunity Areas for Region 7 (ECO_RES.RANKED_OAS)

    Science.gov (United States)

    The RANKED_OAS are all the Conservation Opportunity Areas identified by MoRAP that have subsequently been ranked by patch size, landform representation, and the targeted land cover class (highest rank for conservation management = 1 [LFRANK_NOR]). The OAs designate areas with potential for forest or grassland conservation because they are areas of natural or semi-natural land cover that are at least 75 meters away from roads and away from patch edges. The OAs were modeled by creating distance grids using the National Land Cover Database and the Census Bureau's TIGER roads files.

  20. UNIVERSITY RANKINGS BY COST OF LIVING ADJUSTED FACULTY COMPENSATION

    OpenAIRE

    Terrance Jalbert; Mercedes Jalbert; Karla Hayashi

    2010-01-01

    In this paper we rank 574 universities based on compensation paid to their faculty. The analysis examines universities both on a raw basis and on a cost of living adjusted basis. Rankings based on salary data and benefit data are presented. In addition rankings based on total compensation are presented. Separate rankings are provided for universities offering different degrees. The results indicate that rankings of universities based on raw and cost of living adjusted data are markedly differ...

  1. Kriging for Simulation Metamodeling: Experimental Design, Reduced Rank Kriging, and Omni-Rank Kriging

    Science.gov (United States)

    Hosking, Michael Robert

    This dissertation improves an analyst's use of simulation by offering improvements in the utilization of kriging metamodels. There are three main contributions. First an analysis is performed of what comprises good experimental designs for practical (non-toy) problems when using a kriging metamodel. Second is an explanation and demonstration of how reduced rank decompositions can improve the performance of kriging, now referred to as reduced rank kriging. Third is the development of an extension of reduced rank kriging which solves an open question regarding the usage of reduced rank kriging in practice. This extension is called omni-rank kriging. Finally these results are demonstrated on two case studies. The first contribution focuses on experimental design. Sequential designs are generally known to be more efficient than "one shot" designs. However, sequential designs require some sort of pilot design from which the sequential stage can be based. We seek to find good initial designs for these pilot studies, as well as designs which will be effective if there is no following sequential stage. We test a wide variety of designs over a small set of test-bed problems. Our findings indicate that analysts should take advantage of any prior information they have about their problem's shape and/or their goals in metamodeling. In the event of a total lack of information we find that Latin hypercube designs are robust default choices. Our work is most distinguished by its attention to the higher levels of dimensionality. The second contribution introduces and explains an alternative method for kriging when there is noise in the data, which we call reduced rank kriging. Reduced rank kriging is based on using a reduced rank decomposition which artificially smoothes the kriging weights similar to a nugget effect. Our primary focus will be showing how the reduced rank decomposition propagates through kriging empirically. In addition, we show further evidence for our

  2. Pulling Rank: Military Rank Affects Hormone Levels and Fairness in an Allocation Experiment

    Directory of Open Access Journals (Sweden)

    Benjamin Siart

    2016-11-01

    Full Text Available Status within social hierarchies has great effects on the lives of socially organized mammals. Its effects on human behavior and related physiology however is relatively little studied. The present study investigated the impact of military rank on fairness and behavior in relation to salivary cortisol (C and testosterone (T levels in male soldiers. For this purpose 180 members of the Austrian Armed Forces belonging to two distinct rank groups participated in two variations of a computer-based guard duty allocation experiment. The rank groups were 1 warrant officers (High Rank, HR and 2 enlisted men (Low Rank, LR. One soldier from each rank group participated in every experiment. At the beginning of the experiment, one participant was assigned to start standing guard and the other participant at rest. The participant who started at rest could choose if and when to relieve his fellow soldier and therefore had control over the experiment. In order to trigger perception of unfair behavior, an additional experiment was conducted which was manipulated by the experimenter. In the manipulated version both soldiers started in the standing guard position and were never relieved, believing that their opponent was at rest, not relieving them. Our aim was to test whether unfair behavior causes a physiological reaction. Saliva samples for hormone analysis were collected at regular intervals throughout the experiment.We found that in the un-manipulated setup high-ranking soldiers spent less time standing guard than lower ranking individuals. Rank was a significant predictor for C but not for T levels during the experiment. C levels in the HR group were higher than in LR group. C levels were also elevated in the manipulated experiment compared to the un-manipulated experiment, especially in LR. We assume that the elevated C levels in HR were caused by HR feeling their status challenged by the situation of having to negotiate with an individual of lower military

  3. Pulling Rank: Military Rank Affects Hormone Levels and Fairness in an Allocation Experiment.

    Science.gov (United States)

    Siart, Benjamin; Pflüger, Lena S; Wallner, Bernard

    2016-01-01

    Status within social hierarchies has great effects on the lives of socially organized mammals. Its effects on human behavior and related physiology, however, is relatively little studied. The present study investigated the impact of military rank on fairness and behavior in relation to salivary cortisol (C) and testosterone (T) levels in male soldiers. For this purpose 180 members of the Austrian Armed Forces belonging to two distinct rank groups participated in two variations of a computer-based guard duty allocation experiment. The rank groups were (1) warrant officers (high rank, HR) and (2) enlisted men (low rank, LR). One soldier from each rank group participated in every experiment. At the beginning of the experiment, one participant was assigned to start standing guard and the other participant at rest. The participant who started at rest could choose if and when to relieve his fellow soldier and therefore had control over the experiment. In order to trigger perception of unfair behavior, an additional experiment was conducted which was manipulated by the experimenter. In the manipulated version both soldiers started in the standing guard position and were never relieved, believing that their opponent was at rest, not relieving them. Our aim was to test whether unfair behavior causes a physiological reaction. Saliva samples for hormone analysis were collected at regular intervals throughout the experiment. We found that in the un-manipulated setup high-ranking soldiers spent less time standing guard than lower ranking individuals. Rank was a significant predictor for C but not for T levels during the experiment. C levels in the HR group were higher than in the LR group. C levels were also elevated in the manipulated experiment compared to the un-manipulated experiment, especially in LR. We assume that the elevated C levels in HR were caused by HR feeling their status challenged by the situation of having to negotiate with an individual of lower military rank

  4. Social Bookmarking Induced Active Page Ranking

    Science.gov (United States)

    Takahashi, Tsubasa; Kitagawa, Hiroyuki; Watanabe, Keita

    Social bookmarking services have recently made it possible for us to register and share our own bookmarks on the web and are attracting attention. The services let us get structured data: (URL, Username, Timestamp, Tag Set). And these data represent user interest in web pages. The number of bookmarks is a barometer of web page value. Some web pages have many bookmarks, but most of those bookmarks may have been posted far in the past. Therefore, even if a web page has many bookmarks, their value is not guaranteed. If most of the bookmarks are very old, the page may be obsolete. In this paper, by focusing on the timestamp sequence of social bookmarkings on web pages, we model their activation levels representing current values. Further, we improve our previously proposed ranking method for web search by introducing the activation level concept. Finally, through experiments, we show effectiveness of the proposed ranking method.

  5. Regression Estimator Using Double Ranked Set Sampling

    Directory of Open Access Journals (Sweden)

    Hani M. Samawi

    2002-06-01

    Full Text Available The performance of a regression estimator based on the double ranked set sample (DRSS scheme, introduced by Al-Saleh and Al-Kadiri (2000, is investigated when the mean of the auxiliary variable X is unknown. Our primary analysis and simulation indicates that using the DRSS regression estimator for estimating the population mean substantially increases relative efficiency compared to using regression estimator based on simple random sampling (SRS or ranked set sampling (RSS (Yu and Lam, 1997 regression estimator.  Moreover, the regression estimator using DRSS is also more efficient than the naïve estimators of the population mean using SRS, RSS (when the correlation coefficient is at least 0.4 and DRSS for high correlation coefficient (at least 0.91. The theory is illustrated using a real data set of trees.

  6. 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.

  7. 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......-Yau surfaces. We find, for example, that U is "positive" (i.e., nearly affine) and either finite-type or non-acyclic (in the cluster sense) if and only if the monodromy of the tropicalization of U is one of Kodaira's matrices for the monodromy of an ellpitic fibration. In the positive cases, we also describe...... the action of the cluster modular group on the tropicalization of U....

  8. Deep Impact: Unintended consequences of journal rank

    CERN Document Server

    Brembs, Björn

    2013-01-01

    Much has been said about the increasing bureaucracy in science, stifling innovation, hampering the creativity of researchers and incentivizing misconduct, even outright fraud. Many anecdotes have been recounted, observations described and conclusions drawn about the negative impact of impact assessment on scientists and science. However, few of these accounts have drawn their conclusions from data, and those that have typically relied on a few studies. In this review, we present the most recent and pertinent data on the consequences that our current scholarly communication system has had on various measures of scientific quality (such as utility/citations, methodological soundness, expert ratings and retractions). These data confirm previous suspicions: using journal rank as an assessment tool is bad scientific practice. Moreover, the data lead us to argue that any journal rank (not only the currently-favored Impact Factor) would have this negative impact. Therefore, we suggest that abandoning journals altoge...

  9. Probabilistic Low-Rank Multitask Learning.

    Science.gov (United States)

    Kong, Yu; Shao, Ming; Li, Kang; Fu, Yun

    2017-01-04

    In this paper, we consider the problem of learning multiple related tasks simultaneously with the goal of improving the generalization performance of individual tasks. The key challenge is to effectively exploit the shared information across multiple tasks as well as preserve the discriminative information for each individual task. To address this, we propose a novel probabilistic model for multitask learning (MTL) that can automatically balance between low-rank and sparsity constraints. The former assumes a low-rank structure of the underlying predictive hypothesis space to explicitly capture the relationship of different tasks and the latter learns the incoherent sparse patterns private to each task. We derive and perform inference via variational Bayesian methods. Experimental results on both regression and classification tasks on real-world applications demonstrate the effectiveness of the proposed method in dealing with the MTL problems.

  10. Ranking agility factors affecting hospitals in Iran

    OpenAIRE

    M. Abdi Talarposht; GH. Mahmodi; MA. Jahani

    2017-01-01

    Background: Agility is an effective response to the changing and unpredictable environment and using these changes as opportunities for organizational improvement. Objective: The aim of the present study was to rank the factors affecting agile supply chain of hospitals of Iran. Methods: This applied study was conducted by cross sectional-descriptive method at some point of 2015 for one year. The research population included managers, administrators, faculty members and experts were sele...

  11. Ranking images based on aesthetic qualities.

    OpenAIRE

    Gaur, Aarushi

    2015-01-01

    The qualitative assessment of image content and aesthetic impression is affected by various image attributes and relations between the attributes. Modelling of such assessments in the form of objective rankings and learning image representations based on them is not a straightforward problem. The criteria can be varied with different levels of complexity for various applications. A highly-complex problem could involve a large number of interrelated attributes and features alongside varied rul...

  12. Homological characterisation of Lambda-ranks

    OpenAIRE

    Howson, Susan

    1999-01-01

    If G is a pro-p, p-adic, Lie group and if $\\Lambda(G)$ denotes the Iwasawa algebra of G then we present a formula for determining the $\\Lambda(G)$-rank of a finitely generated $\\Lambda(G)$-module. This is given in terms of the G homology groups of the module. We explore some consequences of this for the structure of $\\Lambda(G)$-modules.

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

    DEFF Research Database (Denmark)

    Meho, Lokman I.; Sonnenwald, Diane H.

    2000-01-01

    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......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...

  14. 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 (Rxy ) is the maximum likelihood estimator of the Pearson correlation (ρxy ) 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 ρxy 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.

  15. Higher-rank fields and currents

    Energy Technology Data Exchange (ETDEWEB)

    Gelfond, O.A. [Institute of System Research of Russian Academy of Sciences,Nakhimovsky prospect 36-1, 117218, Moscow (Russian Federation); I.E.Tamm Department of Theoretical Physics, Lebedev Physical Institute,Leninsky prospect 53, 119991, Moscow (Russian Federation); Vasiliev, M.A. [I.E.Tamm Department of Theoretical Physics, Lebedev Physical Institute,Leninsky prospect 53, 119991, Moscow (Russian Federation)

    2016-10-13

    Sp(2M) invariant field equations in the space M{sub M} with symmetric matrix coordinates are classified. Analogous results are obtained for Minkowski-like subspaces of M{sub M} which include usual 4d Minkowski space as a particular case. The constructed equations are associated with the tensor products of the Fock (singleton) representation of Sp(2M) of any rank r. The infinite set of higher-spin conserved currents multilinear in rank-one fields in M{sub M} is found. The associated conserved charges are supported by (rM−((r(r−1))/2))-dimensional differential forms in M{sub M}, that are closed by virtue of the rank-2r field equations. The cohomology groups H{sup p}(σ{sub −}{sup r}) with all p and r, which determine the form of appropriate gauge fields and their field equations, are found both for M{sub M} and for its Minkowski-like subspace.

  16. Association between Metabolic Syndrome and Job Rank.

    Science.gov (United States)

    Mehrdad, Ramin; Pouryaghoub, Gholamreza; Moradi, Mahboubeh

    2018-01-01

    The occupation of the people can influence the development of metabolic syndrome. To determine the association between metabolic syndrome and its determinants with the job rank in workers of a large car factory in Iran. 3989 male workers at a large car manufacturing company were invited to participate in this cross-sectional study. Demographic and anthropometric data of the participants, including age, height, weight, and abdominal circumference were measured. Blood samples were taken to measure lipid profile and blood glucose level. Metabolic syndrome was diagnosed in each participant based on ATPIII 2001 criteria. The workers were categorized based on their job rank into 3 groups of (1) office workers, (2) workers with physical exertion, and (3) workers with chemical exposure. The study characteristics, particularly the frequency of metabolic syndrome and its determinants were compared among the study groups. The prevalence of metabolic syndrome in our study was 7.7% (95% CI 6.9 to 8.5). HDL levels were significantly lower in those who had chemical exposure (p=0.045). Diastolic blood pressure was significantly higher in those who had mechanical exertion (p=0.026). The frequency of metabolic syndrome in the office workers, workers with physical exertion, and workers with chemical exposure was 7.3%, 7.9%, and 7.8%, respectively (p=0.836). Seemingly, there is no association between metabolic syndrome and job rank.

  17. [Ranke and modern surgery in Groningen].

    Science.gov (United States)

    van Gijn, Jan; Gijselhart, Joost P

    2012-01-01

    Hans Rudolph Ranke (1849-1887) studied medicine in Halle, located in the eastern part of Germany, where he also trained as a surgeon under Richard von Volkmann (1830-1889), during which time he became familiar with the new antiseptic technique that had been introduced by Joseph Lister (1827-1912). In 1878 he was appointed head of the department of surgery in Groningen, the Netherlands, where his predecessor had been chronically indisposed and developments were flagging. Within a few months, Ranke had introduced disinfection by using carbolic acid both before and during operations. For the disinfection of wound dressings, he replaced carbolic acid with thymol as this was less pungent and foul-smelling. The rate of postoperative infections dropped to a minimum despite the inadequate housing and living conditions of the patients with infectious diseases. In 1887, at the age of 37, Ranke died after a brief illness - possibly glomerulonephritis - only eight years after he had assumed office. A street in the city of Groningen near its present-day University Medical Centre has been named after him.

  18. Ranking agility factors affecting hospitals in Iran

    Directory of Open Access Journals (Sweden)

    M. Abdi Talarposht

    2017-04-01

    Full Text Available Background: Agility is an effective response to the changing and unpredictable environment and using these changes as opportunities for organizational improvement. Objective: The aim of the present study was to rank the factors affecting agile supply chain of hospitals of Iran. Methods: This applied study was conducted by cross sectional-descriptive method at some point of 2015 for one year. The research population included managers, administrators, faculty members and experts were selected hospitals. A total of 260 people were selected as sample from the health centers. The construct validity of the questionnaire was approved by confirmatory factor analysis test and its reliability was approved by Cronbach's alpha (α=0.97. All data were analyzed by Kolmogorov-Smirnov, Chi-square and Friedman tests. Findings: The development of staff skills, the use of information technology, the integration of processes, appropriate planning, and customer satisfaction and product quality had a significant impact on the agility of public hospitals of Iran (P<0.001. New product introductions had earned the highest ranking and the development of staff skills earned the lowest ranking. Conclusion: The new product introduction, market responsiveness and sensitivity, reduce costs, and the integration of organizational processes, ratings better to have acquired agility hospitals in Iran. Therefore, planners and officials of hospitals have to, through the promotion quality and variety of services customer-oriented, providing a basis for investing in the hospital and etc to apply for agility supply chain public hospitals of Iran.

  19. Ranking Fuzzy Numbers and Its Application to Products Attributes Preferences

    OpenAIRE

    Lazim Abdullah; Nor Nashrah Ahmad Fauzee

    2011-01-01

    Ranking is one of the widely used methods in fuzzy decision making environment. The recent ranking fuzzy numbers proposed by Wang and Li is claimed to be the improved version in ranking. However, the method was never been simplified and tested in real life application. This paper presents a four-step computation of ranking fuzzy numbers and its application in ranking attributes of selected chocolate products.  The four steps algorithm was formulated to rank fuzzy numbers and followed by a tes...

  20. 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

  1. OPG/RANKL/RANK cytokine system in renal osteodystrophy

    Directory of Open Access Journals (Sweden)

    Ivica Avberšek-Lužnik

    2007-11-01

    Full Text Available Background: Renal osteodystrophy is one of the most common complications affecting patients with endstage renal disease treated with hemodialysis (HD. The action of calciotropic hormones in renal osteodystrophy is regulated by the OPG/RANKL/RANK system. Its function is modulated by interleukines, calcitriol and parathyroid hormone (PTH.The aim of our study was to confirm that this system is involved in the pathogenesis of renal osteodystrophy and supports the mechanism of PTH action on bone.Methods: 106 HD patients (mean age 60 years and 50 healthy volunteers (mean age 64 years were enrolled in the study. In serum samples of patients and controls we determined concentrations of OPG, RANKL, tartarat resistant acid phosphatase 5b (TRAP 5b, serum Cterminal telopeptide cross-links of type I collagen (CTx, bone specific alkaline phosphatase (BALP, osteocalcin (OC and parathyroid hormone (PTH. We compared serum measurements of HD patients and controls and assessed the correlation of OPG and RANKL with bone markers. The most frequent OPG promotor gene polymorphisms were also determined. SPSS 12.1 for Windows was used for statistical analysis.Results: Median OPG concentrations were approximately three times higher in HD patients (0.804 µg/l than in healthy volunteers (0.272 µg/l. Mean serum RANKL concentrations were 1.66- fold higher in HD patients (1.36 pmol/l than in controls (0.82 pmol/l. Serum RANKL levels significantly differed between patients with and without calcitriol therapy (p = 0.001. After dividing HD patients into tertiles according to PTH, we observed significantly higher OPG values in the lower and RANKL in the upper tertile (p < 0.001. OPG did not correlate with bone resorption markers. Only weak correlation of bone formation markers with osteocalcin was noted. In contrast to OPG, RANKL correlated well with PTH, OC and CTX. OPG promoter gene polymorphisms (149 T → C, 163 A → G, 950 T → C do not influence OPG expression and

  2. 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.

  3. 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.

  4. On the Nonnegative Rank of Euclidean Distance Matrices.

    Science.gov (United States)

    Lin, Matthew M; Chu, Moody T

    2010-09-01

    The Euclidean distance matrix for n distinct points in ℝ r is generically of rank r + 2. It is shown in this paper via a geometric argument that its nonnegative rank for the case r = 1 is generically n.

  5. Global Low-Rank Image Restoration With Gaussian Mixture Model.

    Science.gov (United States)

    Zhang, Sibo; Jiao, Licheng; Liu, Fang; Wang, Shuang

    2017-06-27

    Low-rank restoration has recently attracted a lot of attention in the research of computer vision. Empirical studies show that exploring the low-rank property of the patch groups can lead to superior restoration performance, however, there is limited achievement on the global low-rank restoration because the rank minimization at image level is too strong for the natural images which seldom match the low-rank condition. In this paper, we describe a flexible global low-rank restoration model which introduces the local statistical properties into the rank minimization. The proposed model can effectively recover the latent global low-rank structure via nuclear norm, as well as the fine details via Gaussian mixture model. An alternating scheme is developed to estimate the Gaussian parameters and the restored image, and it shows excellent convergence and stability. Besides, experiments on image and video sequence datasets show the effectiveness of the proposed method in image inpainting problems.

  6. 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...

  7. Implicit Block Diagonal Low-Rank Representation.

    Science.gov (United States)

    Xie, Xingyu; Guo, Xianglin; Liu, Guangcan; Wang, Jun

    2017-10-17

    While current block diagonal constrained subspace clustering methods are performed explicitly on the original data space, in practice it is often more desirable to embed the block diagonal prior into the reproducing kernel Hilbert feature space by kernelization techniques, as the underlying data structure in reality is usually nonlinear. However, it is still unknown how to carry out the embedding and kernelization in the models with block diagonal constraints. In this work, we shall take a step in this direction. First, we establish a novel model termed Implicit Block Diagonal Low-Rank Representation (IBDLR), by incorporating the implicit feature representation and block diagonal prior into the prevalent Low-Rank Representation (LRR) method. Second, mostly important, we show that the model in IBDLR could be kernelized by making use of a smoothed dual representation and the specifics of a proximal gradient based optimization algorithm. Finally, we provide some theoretical analyses for the convergence of our optimization algorithm. Comprehensive experiments on synthetic and realworld datasets demonstrate the superiorities of our IBDLR over state-of-the-art methods.While current block diagonal constrained subspace clustering methods are performed explicitly on the original data space, in practice it is often more desirable to embed the block diagonal prior into the reproducing kernel Hilbert feature space by kernelization techniques, as the underlying data structure in reality is usually nonlinear. However, it is still unknown how to carry out the embedding and kernelization in the models with block diagonal constraints. In this work, we shall take a step in this direction. First, we establish a novel model termed Implicit Block Diagonal Low-Rank Representation (IBDLR), by incorporating the implicit feature representation and block diagonal prior into the prevalent Low-Rank Representation (LRR) method. Second, mostly important, we show that the model in IBDLR could be

  8. Tecer sobe no ranking da Capes

    Directory of Open Access Journals (Sweden)

    José Aparecido

    2013-11-01

    Full Text Available Surpresa ainda maior foi verificar que prosseguimos no rumo da consolidação, crescendo no ranking – chegando a B3 em alguns campos, como pode ser visto no portal de buscas do Qualis Capes http://qualis.capes.gov.br/webqualis/principal.seamhttp://qualis.capes.gov, que apresenta nossa classificação abaixo:   B3 ADMINISTRAÇÃO, CIÊNCIAS CONTÁBEIS E TURISMO B4 CIÊNCIAS SOCIAIS APLICADAS I B4 EDUCAÇÃO B4 INTERDISCIPLINAR B5 DIREITO B5 HISTÓRIA C CIÊNCIA DA COMPUTAÇÃO

  9. On Stein's unbiased risk estimate for reduced rank estimators

    DEFF Research Database (Denmark)

    Hansen, Niels Richard

    2018-01-01

    Stein's unbiased risk estimate (SURE) is considered for matrix valued observables with low rank means. It is shown that SURE is applicable to a class of spectral function estimators including the reduced rank estimator.......Stein's unbiased risk estimate (SURE) is considered for matrix valued observables with low rank means. It is shown that SURE is applicable to a class of spectral function estimators including the reduced rank estimator....

  10. A study of serial ranks via random graphs

    OpenAIRE

    Haeusler, Erich; Mason, David M.; Turova, Tatyana S.

    2000-01-01

    Serial ranks have long been used as the basis for nonparametric tests of independence in time series analysis. We shall study the underlying graph structure of serial ranks. This will lead us to a basic martingale which will allow us to construct a weighted approximation to a serial rank process. To show the applicability of this approximation, we will use it to prove two very general central limit theorems for Wald-Wolfowitz-type serial rank statistics.

  11. Do PageRank-based author rankings outperform simple citation counts?

    CERN Document Server

    Fiala, Dalibor; Žitnik, Slavko; Bajec, Marko

    2015-01-01

    The basic indicators of a researcher's productivity and impact are still the number of publications and their citation counts. These metrics are clear, straightforward, and easy to obtain. When a ranking of scholars is needed, for instance in grant, award, or promotion procedures, their use is the fastest and cheapest way of prioritizing some scientists over others. However, due to their nature, there is a danger of oversimplifying scientific achievements. Therefore, many other indicators have been proposed including the usage of the PageRank algorithm known for the ranking of webpages and its modifications suited to citation networks. Nevertheless, this recursive method is computationally expensive and even if it has the advantage of favouring prestige over popularity, its application should be well justified, particularly when compared to the standard citation counts. In this study, we analyze three large datasets of computer science papers in the categories of artificial intelligence, software engineering,...

  12. an investigation into n investigation into index ranking technique for ...

    African Journals Online (AJOL)

    eobe

    The study shows that the utility of the ranking technique may be limited by em. Therefore users of the technique for ranking fuzzy numbers have to maker, risk attitude, critical path, total float ranking s usually faced with a ully managing projects. The th project management is vities in the project have the activity times in the.

  13. Variation in rank abundance replicate samples and impact of clustering

    NARCIS (Netherlands)

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

    2005-01-01

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

  14. 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

  15. 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…

  16. University Rankings 2.0: New Frontiers in Institutional Comparisons

    Science.gov (United States)

    Usher, Alex

    2009-01-01

    The number of university rankings systems in use around the world has increased dramatically over the last decade. As they have spread, they have mutated; no longer are ranking systems simply clones of the original ranking systems such as "US News" and "World Report". A number of different types of "mutation" have occurred, so that there are now…

  17. Ranking Scholarly Publishers in Political Science: An Alternative Approach

    Science.gov (United States)

    Garand, James C.; Giles, Micheal W.

    2011-01-01

    Previous research has documented how political scientists evaluate and rank scholarly journals, but the evaluation and ranking of scholarly book publishers has drawn less attention. In this article, we use data from a survey of 603 American political scientists to generate a ranking of scholarly publishers in political science. We used open-ended…

  18. 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…

  19. Cardinal priority ranking based decision making for economic ...

    African Journals Online (AJOL)

    To access the indifference band, interaction with the decision maker is obtained via cardinal priority ranking (CPR) of the objectives. The cardinal priority ranking is constructed in the functional space and then transformed into the decision space, so the cardinal priority ranking of objectives relate the decision maker's ...

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

    African Journals Online (AJOL)

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

  1. Calibrating Canadian Universities: Rankings for Sale Once Again

    Science.gov (United States)

    Cramer, Kenneth M.; Page, Stewart

    2007-01-01

    A summary and update on recent research by the authors and others concerning rankings of Canadian universities is presented. Some specific data are reported in regard to the 2005 and 2006 ranking data published by "Maclean's" magazine. Some criticisms and difficulties with the use of rank-based data are outlined with regard to the issues…

  2. Higher Education Ranking and Leagues Tables: Lessons Learned from Benchmarking

    Science.gov (United States)

    Proulx, Roland

    2007-01-01

    The paper intends to contribute to the debate on ranking and league tables by adopting a critical approach to ranking methodologies from the point of view of a university benchmarking exercise. The absence of a strict benchmarking exercise in the ranking process has been, in the opinion of the author, one of the major problems encountered in the…

  3. Synthesis of Partial Rankings of Points of Interest Using Crowdsourcing

    DEFF Research Database (Denmark)

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

    2015-01-01

    to the query keywords and the query location. A key challenge in being able to make progress on the design of ranking functions is to be able to assess the quality of the results returned by ranking functions. We propose a model that synthesizes a ranking of points of interest from answers to crowdsourced...

  4. Fuzzy Multicriteria Ranking of Aluminium Coating Methods

    Science.gov (United States)

    Batzias, A. F.

    2007-12-01

    This work deals with multicriteria ranking of aluminium coating methods. The alternatives used are: sulfuric acid anodization, A1; oxalic acid anodization, A2; chromic acid anodization, A3; phosphoric acid anodization, A4; integral color anodizing, A5; chemical conversion coating, A6; electrostatic powder deposition, A7. The criteria used are: cost of production, f1; environmental friendliness of production process, f2; appearance (texture), f3; reflectivity, f4; response to coloring, f5; corrosion resistance, f6; abrasion resistance, f7; fatigue resistance, f8. Five experts coming from relevant industrial units set grades to the criteria vector and the preference matrix according to a properly modified Delphi method. Sensitivity analysis of the ranked first alternative A1 against the `second best', which was A3 at low and A7 at high resolution levels proved that the solution is robust. The dependence of anodized products quality on upstream processes is presented and the impact of energy price increase on industrial cost is discussed.

  5. Rank order scaling of pictorial depth.

    Science.gov (United States)

    van Doorn, Andrea; Koenderink, Jan; Wagemans, Johan

    2011-01-01

    We address the topic of "pictorial depth" in cases of pictures that are unlike photographic renderings. The most basic measure of "depth" is no doubt that of depth order. We establish depth order through the pairwise depth-comparison method, involving all pairs from a set of 49 fiducial points. The pictorial space for this study was evoked by a capriccio (imaginary landscape) by Francesco Guardi (1712-1793). In such a drawing pictorial space is suggested by the artist through a small set of conventional depth cues. As a result typical Western observers tend to agree largely in their visual awareness when looking at such art. We rank depths for locations that are not on a single surface and far apart in pictorial space. We find that observers resolve about 40 distinct depth layers and agree largely in this. From a previous experiment we have metrical data for the same observers. The rank correlations between the results are high. Perhaps surprisingly, we find no correlation between the number of distinct depth layers and the total metrical depth range. Thus, the relation between subjective magnitude and discrimination threshold fails to hold for pictorial depth.

  6. Condensing biomedical journal texts through paragraph ranking.

    Science.gov (United States)

    Chiang, Jung-Hsien; Liu, Heng-Hui; Huang, Yi-Ting

    2011-04-15

    The growing availability of full-text scientific articles raises the important issue of how to most efficiently digest full-text content. Although article titles and abstracts provide accurate and concise information on an article's contents, their brevity inevitably entails the loss of detail. Full-text articles provide those details, but require more time to read. The primary goal of this study is to combine the advantages of concise abstracts and detail-rich full-texts to ease the burden of reading. We retrieved abstract-related paragraphs from full-text articles through shared keywords between the abstract and paragraphs from the main text. Significant paragraphs were then recommended by applying a proposed paragraph ranking approach. Finally, the user was provided with a condensed text consisting of these significant paragraphs, allowing the user to save time from perusing the whole article. We compared the performance of the proposed approach with a keyword counting approach and a PageRank-like approach. Evaluation was conducted in two aspects: the importance of each retrieved paragraph and the information coverage of a set of retrieved paragraphs. In both evaluations, the proposed approach outperformed the other approaches. jchiang@mail.ncku.edu.tw.

  7. Rank hypocrisies the insult of the REF

    CERN Document Server

    Sayer, Derek

    2015-01-01

    "The REF is right out of Havel's and Kundera's Eastern Europe: a state-administered exercise to rank academic research like hotel chains dependent on the active collaboration of the UK professoriate. In crystalline text steeped in cold rage, Sayer takes aim at the REF's central claim, that it is a legitimate process of expert peer review. He critiques university and national-level REF processes against actual practices of scholarly review as found in academic journals, university presses, and North American tenure procedures. His analysis is damning. If the REF fails as scholarly review, how can academics and universities continue to participate? And how can government use its rankings as a basis for public policy?" - Tarak Barkawi, Reader in the Department of International Relations, London School of Economics "Many academics across the world have come to see the REF as an arrogant attempt to raise national research standards that has resulted in a variety of self-inflicted wounds to UK higher education. Der...

  8. Entropy-based financial asset pricing.

    Directory of Open Access Journals (Sweden)

    Mihály Ormos

    Full Text Available We investigate entropy as a financial risk measure. Entropy explains the equity premium of securities and portfolios in a simpler way and, at the same time, with higher explanatory power than the beta parameter of the capital asset pricing model. For asset pricing we define the continuous entropy as an alternative measure of risk. Our results show that entropy decreases in the function of the number of securities involved in a portfolio in a similar way to the standard deviation, and that efficient portfolios are situated on a hyperbola in the expected return-entropy system. For empirical investigation we use daily returns of 150 randomly selected securities for a period of 27 years. Our regression results show that entropy has a higher explanatory power for the expected return than the capital asset pricing model beta. Furthermore we show the time varying behavior of the beta along with entropy.

  9. Entropy-based financial asset pricing.

    Science.gov (United States)

    Ormos, Mihály; Zibriczky, Dávid

    2014-01-01

    We investigate entropy as a financial risk measure. Entropy explains the equity premium of securities and portfolios in a simpler way and, at the same time, with higher explanatory power than the beta parameter of the capital asset pricing model. For asset pricing we define the continuous entropy as an alternative measure of risk. Our results show that entropy decreases in the function of the number of securities involved in a portfolio in a similar way to the standard deviation, and that efficient portfolios are situated on a hyperbola in the expected return-entropy system. For empirical investigation we use daily returns of 150 randomly selected securities for a period of 27 years. Our regression results show that entropy has a higher explanatory power for the expected return than the capital asset pricing model beta. Furthermore we show the time varying behavior of the beta along with entropy.

  10. An Entropy-Based Damage Characterization

    Directory of Open Access Journals (Sweden)

    Mehdi Amiri

    2014-12-01

    Full Text Available This paper presents a scientific basis for the description of the causes of damage within an irreversible thermodynamic framework and the effects of damage as observable variables that signify degradation of structural integrity. The approach relies on the fundamentals of irreversible thermodynamics and specifically the notion of entropy generation as a measure of degradation and damage. We first review the state-of-the-art advances in entropic treatment of damage followed by a discussion on generalization of the entropic concept to damage characterization that may offers a better definition of damage metric commonly used for structural integrity assessment. In general, this approach provides the opportunity to described reliability and risk of structures in terms of fundamental science concepts. Over the years, many studies have focused on materials damage assessment by determining physics-based cause and affect relationships, the goal of this paper is to put this work in perspective and encourage future work of materials damage based on the entropy concept.

  11. Entropy based fingerprint for local crystalline order

    Science.gov (United States)

    Piaggi, Pablo M.; Parrinello, Michele

    2017-09-01

    We introduce a new fingerprint that allows distinguishing between liquid-like and solid-like atomic environments. This fingerprint is based on an approximate expression for the entropy projected on individual atoms. When combined with local enthalpy, this fingerprint acquires an even finer resolution and it is capable of discriminating between different crystal structures.

  12. Entropy-based adaptive attitude estimation

    Science.gov (United States)

    Kiani, Maryam; Barzegar, Aylin; Pourtakdoust, Seid H.

    2018-03-01

    Gaussian approximation filters have increasingly been developed to enhance the accuracy of attitude estimation in space missions. The effective employment of these algorithms demands accurate knowledge of system dynamics and measurement models, as well as their noise characteristics, which are usually unavailable or unreliable. An innovation-based adaptive filtering approach has been adopted as a solution to this problem; however, it exhibits two major challenges, namely appropriate window size selection and guaranteed assurance of positive definiteness for the estimated noise covariance matrices. The current work presents two novel techniques based on relative entropy and confidence level concepts in order to address the abovementioned drawbacks. The proposed adaptation techniques are applied to two nonlinear state estimation algorithms of the extended Kalman filter and cubature Kalman filter for attitude estimation of a low earth orbit satellite equipped with three-axis magnetometers and Sun sensors. The effectiveness of the proposed adaptation scheme is demonstrated by means of comprehensive sensitivity analysis on the system and environmental parameters by using extensive independent Monte Carlo simulations.

  13. The Entropy-Based Quantum Metric

    Directory of Open Access Journals (Sweden)

    Roger Balian

    2014-07-01

    Full Text Available The von Neumann entropy S( D ^ generates in the space of quantum density matrices  D ^ the Riemannian metric ds2 = −d2S( D ^ , which is physically founded and which characterises the amount of quantum information lost by mixing  D ^ and  D ^ + d D ^ . A rich geometric structure is thereby implemented in quantum mechanics. It includes a canonical mapping between the spaces of states and of observables, which involves the Legendre transform of S( D ^ . The Kubo scalar product is recovered within the space of observables. Applications are given to equilibrium and non equilibrium quantum statistical mechanics. There the formalism is specialised to the relevant space of observables and to the associated reduced states issued from the maximum entropy criterion, which result from the exact states through an orthogonal projection. Von Neumann’s entropy specialises into a relevant entropy. Comparison is made with other metrics. The Riemannian properties of the metric ds2 = −d2S( D ^ are derived. The curvature arises from the non-Abelian nature of quantum mechanics; its general expression and its explicit form for q-bits are given, as well as geodesics.

  14. RANK-ligand (RANKL) expression in young breast cancer patients and during pregnancy.

    Science.gov (United States)

    Azim, Hatem A; Peccatori, Fedro A; Brohée, Sylvain; Branstetter, Daniel; Loi, Sherene; Viale, Giuseppe; Piccart, Martine; Dougall, William C; Pruneri, Giancarlo; Sotiriou, Christos

    2015-02-21

    RANKL is important in mammary gland development during pregnancy and mediates the initiation and progression of progesterone-induced breast cancer. No clinical data are available on the effect of pregnancy on RANK/RANKL expression in young breast cancer patients. We used our previously published dataset of 65 pregnant and 130 matched young breast cancer patients with full clinical, pathological, and survival information. 85% of patients had available transcriptomic data as well. RANK/RANKL expression by immunohistochemistry using H-score on the primary tumor and adjacent normal tissue was performed. We examined the difference in expression of RANK/RANKL between pregnant and non-pregnant patients and their association with clinicopathological features and prognosis. We also evaluated genes and pathways associated with RANK/RANKL expression on primary tumors. RANKL but not RANK expression was more prevalent in the pregnant group, both on the tumor and adjacent normal tissue, independent of other clinicopathological factors (both P Pregnancy increases RANKL expression both in normal breast and primary tumors. These results could guide further development of RANKL-targeted therapy.

  15. Partial Kernelization for Rank Aggregation: Theory and Experiments

    Science.gov (United States)

    Betzler, Nadja; Bredereck, Robert; Niedermeier, Rolf

    Rank Aggregation is important in many areas ranging from web search over databases to bioinformatics. The underlying decision problem Kemeny Score is NP-complete even in case of four input rankings to be aggregated into a "median ranking". We study efficient polynomial-time data reduction rules that allow us to find optimal median rankings. On the theoretical side, we improve a result for a "partial problem kernel" from quadratic to linear size. On the practical side, we provide encouraging experimental results with data based on web search and sport competitions, e.g., computing optimal median rankings for real-world instances with more than 100 candidates within milliseconds.

  16. Ranking de universidades chilenas: un análisis multivariado

    Directory of Open Access Journals (Sweden)

    Firinguetti Limone, Luis

    2015-06-01

    Full Text Available In this work a ranking of Chilean universities on the basis of publicly available information is developed. This ranking takes into account the multivariate character of these institutions. Also, it is noted that the results are consistent with those of a well-known international ranking that uses a different set of data, as well as with several multivariate analyses of the data considered in this study.En este trabajo se elabora un ranking de las universidades chilenas en base a información pública disponible. Dicho ranking toma en cuenta el carácter multivariado de estas instituciones. Además, se ha comprobado que los resultados del ranking son consistentes con un conocido ranking internacional construido a partir de un conjunto diferente de datos y con varios análisis multivariados realizados de la información tratada en este estudio.

  17. EU Country Rankings' Sensitivity to the Choice of Welfare Indicators

    DEFF Research Database (Denmark)

    Hussain, M. Azhar

    2016-01-01

    are particularly volatile for countries in the middle of the ranking distribution, while countries with either high or low welfare generally have lower volatility. A multidimensional poverty index has the highest correlation with the latent welfare measure. It is concluded that the observed rankings do not tell......Ranking of countries with respect to some welfare measure is highly popular and takes places with high frequency. Ranking of a country can change over time given the same welfare measure is applied. Rankings can also change depending on which welfare measure is applied in a given year. To what...... extent do we see ranking changes and which existing welfare measures best captures an unobserved, yet existing, notion of welfare in society? To investigate this we apply seven welfare indicators for fifteen EU countries covering the years from 2005 until 2011. The results indicate that rankings...

  18. 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.

  19. Asynchronous Gossip for Averaging and Spectral Ranking

    Science.gov (United States)

    Borkar, Vivek S.; Makhijani, Rahul; Sundaresan, Rajesh

    2014-08-01

    We consider two variants of the classical gossip algorithm. The first variant is a version of asynchronous stochastic approximation. We highlight a fundamental difficulty associated with the classical asynchronous gossip scheme, viz., that it may not converge to a desired average, and suggest an alternative scheme based on reinforcement learning that has guaranteed convergence to the desired average. We then discuss a potential application to a wireless network setting with simultaneous link activation constraints. The second variant is a gossip algorithm for distributed computation of the Perron-Frobenius eigenvector of a nonnegative matrix. While the first variant draws upon a reinforcement learning algorithm for an average cost controlled Markov decision problem, the second variant draws upon a reinforcement learning algorithm for risk-sensitive control. We then discuss potential applications of the second variant to ranking schemes, reputation networks, and principal component analysis.

  20. Ranking Visualizations of Correlation Using Weber's Law.

    Science.gov (United States)

    Harrison, Lane; Yang, Fumeng; Franconeri, Steven; Chang, Remco

    2014-12-01

    Despite years of research yielding systems and guidelines to aid visualization design, practitioners still face the challenge of identifying the best visualization for a given dataset and task. One promising approach to circumvent this problem is to leverage perceptual laws to quantitatively evaluate the effectiveness of a visualization design. Following previously established methodologies, we conduct a large scale (n=1687) crowdsourced experiment to investigate whether the perception of correlation in nine commonly used visualizations can be modeled using Weber's law. The results of this experiment contribute to our understanding of information visualization by establishing that: (1) for all tested visualizations, the precision of correlation judgment could be modeled by Weber's law, (2) correlation judgment precision showed striking variation between negatively and positively correlated data, and (3) Weber models provide a concise means to quantify, compare, and rank the perceptual precision afforded by a visualization.

  1. Motif discovery in ranked lists of sequences

    DEFF Research Database (Denmark)

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

    2016-01-01

    . These features make Regmex well suited for a range of biological sequence analysis problems related to motif discovery, exemplified by microRNA seed enrichment, but also including enrichment problems involving complex motifs and combinations of motifs. We demonstrate a number of usage scenarios that take......Motif analysis has long been an important method to characterize biological functionality and the current growth of sequencing-based genomics experiments further extends its potential. These diverse experiments often generate sequence lists ranked by some functional property. There is therefore...... a growing need for motif analysis methods that can exploit this coupled data structure and be tailored for specific biological questions. Here, we present an exploratory motif analysis tool, Regmex (REGular expression Motif EXplorer), which offers several methods to evaluate the correlation of motifs...

  2. Ranking different factors influencing flight delay

    Directory of Open Access Journals (Sweden)

    Meysam Kazemi Asfe

    2014-07-01

    Full Text Available Flight interruption is one of the most important issues in today’s airline industry. Every year, most airlines spend significant amount of money to compensate flight delays. Therefore, it is important to detect important factors influencing on flight delays. This paper presents an empirical investigation to determine important factors on this issue. The study also asks some decision makers to make pairwise comparison and ranks various factors using the art of analytical hierarchy process. The study determines that technical defects and delayed entry were among the most important factors to blame for flight delays. In addition, announcing the postponement, replacement aircraft and path replacement are among the most important decisions facing managers in the aviation industry during the disruption of the flight.

  3. Identification of Top-ranked Proteins within a Directional Protein Interaction Network using the PageRank Algorithm: Applications in Humans and Plants.

    Science.gov (United States)

    Li, Xiu-Qing; Xing, Tim; Du, Donglei

    2016-01-01

    Somatic mutation of signal transduction genes or key nodes of the cellular protein network can cause severe diseases in humans but can sometimes genetically improve plants, likely because growth is determinate in animals but indeterminate in plants. This article reviews protein networks; human protein ranking; the mitogen-activated protein kinase (MAPK) and insulin (phospho- inositide 3kinase [PI3K]/phosphatase and tensin homolog [PTEN]/protein kinase B [AKT]) signaling pathways; human diseases caused by somatic mutations to the PI3K/PTEN/ AKT pathway; use of the MAPK pathway in plant molecular breeding; and protein domain evolution. Casitas B-lineage lymphoma (CBL), PTEN, MAPK1 and PIK3CA are among PIK3CA the top-ranked proteins in directional rankings. Eight proteins (ACVR1, CDC42, RAC1, RAF1, RHOA, TGFBR1, TRAF2, and TRAF6) are ranked in the top 50 key players in both signal emission and signal reception and in interaction with many other proteins. Top-ranked proteins likely have major impacts on the network function. Such proteins are targets for drug discovery, because their mutations are implicated in various cancers and overgrowth syndromes. Appropriately managing food intake may help reduce the growth of tumors or malformation of tissues. The role of the protein kinase C/ fatty acid synthase pathway in fat deposition in PTEN/PI3K patients should be investigated. Both the MAPK and insulin signaling pathways exist in plants, and MAPK pathway engineering can improve plant tolerance to biotic and abiotic stresses such as salinity.

  4. Image Registration based on Low Rank Matrix: Rank-Regularized SSD.

    Science.gov (United States)

    Ghaffari, Aboozar; Fatemizadeh, Emad

    2017-08-25

    Similarity measure is a main core of image registration algorithms. Spatially varying intensity distortion is an important challenge which affects the performance of similarity measures. Correlation among pixels is the main characteristic of this distortion. Similarity measures such as sum-of-squareddifferences (SSD) and mutual information (MI) ignore this correlation; Hence, perfect registration cannot be achieved in the presence of this distortion. In this paper, we model this correlation with the aid of the low rank matrix theory. Based on this model, we compensate this distortion analytically and introduce Rank-Regularized SSD (RRSSD). This new similarity measure is a modified SSD based on singular values of difference image in mono-modal imaging. In fact, image registration and distortion correction are performed simultaneously in the proposed model. Based on our experiments, the RRSSD similarity measure achieves clinically acceptable registration results, and outperforms other state-of-the-art similarity measures such as the well-known method of residual complexity.

  5. RANK ligand as a potential target for breast cancer prevention in BRCA1-mutation carriers.

    Science.gov (United States)

    Nolan, Emma; Vaillant, François; Branstetter, Daniel; Pal, Bhupinder; Giner, Göknur; Whitehead, Lachlan; Lok, Sheau W; Mann, Gregory B; Rohrbach, Kathy; Huang, Li-Ya; Soriano, Rosalia; Smyth, Gordon K; Dougall, William C; Visvader, Jane E; Lindeman, Geoffrey J

    2016-08-01

    Individuals who have mutations in the breast-cancer-susceptibility gene BRCA1 (hereafter referred to as BRCA1-mutation carriers) frequently undergo prophylactic mastectomy to minimize their risk of breast cancer. The identification of an effective prevention therapy therefore remains a 'holy grail' for the field. Precancerous BRCA1(mut/+) tissue harbors an aberrant population of luminal progenitor cells, and deregulated progesterone signaling has been implicated in BRCA1-associated oncogenesis. Coupled with the findings that tumor necrosis factor superfamily member 11 (TNFSF11; also known as RANKL) is a key paracrine effector of progesterone signaling and that RANKL and its receptor TNFRSF11A (also known as RANK) contribute to mammary tumorigenesis, we investigated a role for this pathway in the pre-neoplastic phase of BRCA1-mutation carriers. We identified two subsets of luminal progenitors (RANK(+) and RANK(-)) in histologically normal tissue of BRCA1-mutation carriers and showed that RANK(+) cells are highly proliferative, have grossly aberrant DNA repair and bear a molecular signature similar to that of basal-like breast cancer. These data suggest that RANK(+) and not RANK(-) progenitors are a key target population in these women. Inhibition of RANKL signaling by treatment with denosumab in three-dimensional breast organoids derived from pre-neoplastic BRCA1(mut/+) tissue attenuated progesterone-induced proliferation. Notably, proliferation was markedly reduced in breast biopsies from BRCA1-mutation carriers who were treated with denosumab. Furthermore, inhibition of RANKL in a Brca1-deficient mouse model substantially curtailed mammary tumorigenesis. Taken together, these findings identify a targetable pathway in a putative cell-of-origin population in BRCA1-mutation carriers and implicate RANKL blockade as a promising strategy in the prevention of breast cancer.

  6. Rankings matter: nurse graduates from higher-ranked institutions have higher productivity.

    Science.gov (United States)

    Yakusheva, Olga; Weiss, Marianne

    2017-02-13

    Increasing demand for baccalaureate-prepared nurses has led to rapid growth in the number of baccalaureate-granting programs, and to concerns about educational quality and potential effects on productivity of the graduating nursing workforce. We examined the association of individual productivity of a baccalaureate-prepared nurse with the ranking of the degree-granting institution. For a sample of 691 nurses from general medical-surgical units at a large magnet urban hospital between 6/1/2011-12/31/2011, we conducted multivariate regression analysis of nurse productivity on the ranking of the degree-granting institution, adjusted for age, hospital tenure, gender, and unit-specific effects. Nurse productivity was coded as "top"/"average"/"bottom" based on a computation of individual nurse value-added to patient outcomes. Ranking of the baccalaureate-granting institution was derived from the US News and World Report Best Colleges Rankings' categorization of the nurse's institution as the "first tier" or the "second tier", with diploma or associate degree as the reference category. Relative to diploma or associate degree nurses, nurses who had attended first-tier universities had three-times the odds of being in the top productivity category (OR = 3.18, p productivity (OR = 1.73, p = 0.11). Being in the bottom productivity category was not associated with having a baccalaureate degree or the quality tier. The productivity boost from a nursing baccalaureate degree depends on the quality of the educational institution. Recognizing differences in educational outcomes, initiatives to build a baccalaureate-educated nursing workforce should be accompanied by improved access to high-quality educational institutions.

  7. 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.

  8. Improving the Incoherence of a Learned Dictionary via Rank Shrinkage.

    Science.gov (United States)

    Ubaru, Shashanka; Seghouane, Abd-Krim; Saad, Yousef

    2017-01-01

    This letter considers the problem of dictionary learning for sparse signal representation whose atoms have low mutual coherence. To learn such dictionaries, at each step, we first update the dictionary using the method of optimal directions (MOD) and then apply a dictionary rank shrinkage step to decrease its mutual coherence. In the rank shrinkage step, we first compute a rank 1 decomposition of the column-normalized least squares estimate of the dictionary obtained from the MOD step. We then shrink the rank of this learned dictionary by transforming the problem of reducing the rank to a nonnegative garrotte estimation problem and solving it using a path-wise coordinate descent approach. We establish theoretical results that show that the rank shrinkage step included will reduce the coherence of the dictionary, which is further validated by experimental results. Numerical experiments illustrating the performance of the proposed algorithm in comparison to various other well-known dictionary learning algorithms are also presented.

  9. LogDet Rank Minimization with Application to Subspace Clustering.

    Science.gov (United States)

    Kang, Zhao; Peng, Chong; Cheng, Jie; Cheng, Qiang

    2015-01-01

    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.

  10. RANK/RANK-L/OPG in Patients with Bone Metastases Treated with Anticancer Agents and Zoledronic Acid: A Prospective Study

    Directory of Open Access Journals (Sweden)

    Laura Mercatali

    2013-05-01

    Full Text Available Patients with solid cancer frequently develop bone metastases (BM. Zoledronic acid (Zometa®, ZA, routinely used to treat patients with BM, acts on osteoclasts and also has antitumor properties. We aimed to assess the effect of ZA over time in novel bone turnover markers (RANK/receptor activator of nuclear factor-k B ligand (RANK-L/ Osteoprotegerin (OPG and to correlate these with serum N-terminal telopeptide (NTX. The study prospectively evaluated levels of RANK, RANK-L and OPG transcripts by real-time PCR and NTX expression by ELISA in the peripheral blood of 49 consecutive patients with advanced breast, lung or prostate cancer. All patients received the standard ZA schedule and were monitored for 12 months. Median baseline values of RANK, RANK-L and OPG were 78.28 (range 7.34–620.64, 319.06 (21.42–1884.41 and 1.52 (0.10–58.02, respectively. At 12 months, the median RANK-L value had decreased by 22% with respect to the baseline, whereas median OPG levels had increased by about 96%. Consequently, the RANK-L/OPG ratio decreased by 56% from the baseline. Median serum NTX levels decreased over the 12-month period, reaching statistical significance (p < 0.0001. Our results would seem to indicate that ZA modulates RANK, RANK-L and OPG expression, thus decreasing osteoclast activity.

  11. 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.

  12. Photo Aesthetics Ranking Network with Attributes and Content Adaptation

    OpenAIRE

    Kong, Shu; Shen, Xiaohui; Lin, Zhe; Mech, Radomir; Fowlkes, Charless

    2016-01-01

    Real-world applications could benefit from the ability to automatically generate a fine-grained ranking of photo aesthetics. However, previous methods for image aesthetics analysis have primarily focused on the coarse, binary categorization of images into high- or low-aesthetic categories. In this work, we propose to learn a deep convolutional neural network to rank photo aesthetics in which the relative ranking of photo aesthetics are directly modeled in the loss function. Our model incorpor...

  13. A Review of Ranking Models in Data Envelopment Analysis

    OpenAIRE

    Hosseinzadeh Lotfi, F.; Jahanshahloo, G.R.; M. Khodabakhshi; Rostamy-Malkhlifeh, M.; Moghaddas, Z.; Vaez-Ghasemi, M.

    2013-01-01

    In the course of improving various abilities of data envelopment analysis (DEA) models, many investigations have been carried out for ranking decision-making units (DMUs). This is an important issue both in theory and practice. There exist a variety of papers which apply different ranking methods to a real data set. Here the ranking methods are divided into seven groups. As each of the existing methods can be viewed from different aspects, it is possible that somewhat these groups have an ove...

  14. International ranking systems for universities and institutions: a critical appraisal

    Science.gov (United States)

    Ioannidis, John PA; Patsopoulos, Nikolaos A; Kavvoura, Fotini K; Tatsioni, Athina; Evangelou, Evangelos; Kouri, Ioanna; Contopoulos-Ioannidis, Despina G; Liberopoulos, George

    2007-01-01

    Background Ranking of universities and institutions has attracted wide attention recently. Several systems have been proposed that attempt to rank academic institutions worldwide. Methods We review the two most publicly visible ranking systems, the Shanghai Jiao Tong University 'Academic Ranking of World Universities' and the Times Higher Education Supplement 'World University Rankings' and also briefly review other ranking systems that use different criteria. We assess the construct validity for educational and research excellence and the measurement validity of each of the proposed ranking criteria, and try to identify generic challenges in international ranking of universities and institutions. Results None of the reviewed criteria for international ranking seems to have very good construct validity for both educational and research excellence, and most don't have very good construct validity even for just one of these two aspects of excellence. Measurement error for many items is also considerable or is not possible to determine due to lack of publication of the relevant data and methodology details. The concordance between the 2006 rankings by Shanghai and Times is modest at best, with only 133 universities shared in their top 200 lists. The examination of the existing international ranking systems suggests that generic challenges include adjustment for institutional size, definition of institutions, implications of average measurements of excellence versus measurements of extremes, adjustments for scientific field, time frame of measurement and allocation of credit for excellence. Conclusion Naïve lists of international institutional rankings that do not address these fundamental challenges with transparent methods are misleading and should be abandoned. We make some suggestions on how focused and standardized evaluations of excellence could be improved and placed in proper context. PMID:17961208

  15. Asian top universities in six world university ranking systems

    OpenAIRE

    Mahmood Khosrowjerdi; Zahra Seif Kashani

    2013-01-01

    There are a variety of ranking systems for universities throughout the different continents of the world. The majority of the world ranking systems have paid special attention toward evaluation of universities and higher education institutions at the national and international level. This paper tries to study the similarities and status of top Asian universities in the list of top 200 universities by these world ranking systems. Findings show that there are some parallelisms among the...

  16. International ranking systems for universities and institutions: a critical appraisal

    Directory of Open Access Journals (Sweden)

    Tatsioni Athina

    2007-10-01

    Full Text Available Abstract Background Ranking of universities and institutions has attracted wide attention recently. Several systems have been proposed that attempt to rank academic institutions worldwide. Methods We review the two most publicly visible ranking systems, the Shanghai Jiao Tong University 'Academic Ranking of World Universities' and the Times Higher Education Supplement 'World University Rankings' and also briefly review other ranking systems that use different criteria. We assess the construct validity for educational and research excellence and the measurement validity of each of the proposed ranking criteria, and try to identify generic challenges in international ranking of universities and institutions. Results None of the reviewed criteria for international ranking seems to have very good construct validity for both educational and research excellence, and most don't have very good construct validity even for just one of these two aspects of excellence. Measurement error for many items is also considerable or is not possible to determine due to lack of publication of the relevant data and methodology details. The concordance between the 2006 rankings by Shanghai and Times is modest at best, with only 133 universities shared in their top 200 lists. The examination of the existing international ranking systems suggests that generic challenges include adjustment for institutional size, definition of institutions, implications of average measurements of excellence versus measurements of extremes, adjustments for scientific field, time frame of measurement and allocation of credit for excellence. Conclusion Naïve lists of international institutional rankings that do not address these fundamental challenges with transparent methods are misleading and should be abandoned. We make some suggestions on how focused and standardized evaluations of excellence could be improved and placed in proper context.

  17. Ranking agricultural, environmental and natural resource economics journals: A note

    OpenAIRE

    Halkos, George; Tzeremes, Nickolaos

    2012-01-01

    This paper by applying Data Envelopment Analysis (DEA) ranks for the first time Economics journals in the field of Agricultural, Environmental and Natural Resource. Specifically, by using one composite input and one composite output the paper ranks 32 journals. In addition for the first time three different quality ranking reports have been incorporated to the DEA modelling problem in order to classify the journals into four categories (‘A’ to ‘D’). The results reveal that the journals with t...

  18. 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.

  19. Diffusion of scientific credits and the ranking of scientists

    OpenAIRE

    Radicchi, Filippo; Fortunato, Santo; Markines, Benjamin; Vespignani, Alessandro

    2009-01-01

    Recently, the abundance of digital data enabled the implementation of graph based ranking algorithms that provide system level analysis for ranking publications and authors. Here we take advantage of the entire Physical Review publication archive (1893-2006) to construct authors' networks where weighted edges, as measured from opportunely normalized citation counts, define a proxy for the mechanism of scientific credit transfer. On this network we define a ranking method based on a diffusion ...

  20. Social ranking effects on tooth-brushing behaviour

    OpenAIRE

    Maltby, John; Paterson, Kevin; Day, Liz; Jones, Ceri; Kinnear, Hayley; Buchanan, Heather

    2016-01-01

    Objective: A tooth-brushing social rank hypothesis is tested suggesting tooth-brushing duration is influenced when individuals position their behaviour in a rank when comparing their behaviour with other individuals.\\ud Design: Study 1 used a correlation design, Study 2 used a semi-experimental design, and Study 3 used a randomized intervention design to examine the tooth-brushing social rank hypothesis in terms of self-reported attitudes, cognitions, and behaviour towards tooth-brushing dura...

  1. A scale for ranking volcanoes by risk

    Science.gov (United States)

    Scandone, Roberto; Bartolini, Stefania; Martí, Joan

    2016-01-01

    We propose a simple volcanic risk coefficient (VRC) useful for comparing the degree of risk arising from different volcanoes, which may be used by civil protection agencies and volcano observatories to rapidly allocate limited resources even without a detailed knowledge of each volcano. Volcanic risk coefficient is given by the sum of the volcanic explosivity index (VEI) of the maximum expected eruption from the volcano, the logarithm of the eruption rate, and the logarithm of the population that may be affected by the maximum expected eruption. We show how to apply the method to rank the risk using as examples the volcanoes of Italy and in the Canary Islands. Moreover, we demonstrate that the maximum theoretical volcanic risk coefficient is 17 and pertains to the large caldera-forming volcanoes like Toba or Yellowstone that may affect the life of the entire planet. We develop also a simple plugin for a dedicated Quantum Geographic Information System (QGIS) software to graphically display the VRC of different volcanoes in a region.

  2. Relevancy Ranking of Satellite Dataset Search Results

    Science.gov (United States)

    Lynnes, Christopher; Quinn, Patrick; Norton, James

    2017-01-01

    As the Variety of Earth science datasets increases, science researchers find it more challenging to discover and select the datasets that best fit their needs. The most common way of search providers to address this problem is to rank the datasets returned for a query by their likely relevance to the user. Large web page search engines typically use text matching supplemented with reverse link counts, semantic annotations and user intent modeling. However, this produces uneven results when applied to dataset metadata records simply externalized as a web page. Fortunately, data and search provides have decades of experience in serving data user communities, allowing them to form heuristics that leverage the structure in the metadata together with knowledge about the user community. Some of these heuristics include specific ways of matching the user input to the essential measurements in the dataset and determining overlaps of time range and spatial areas. Heuristics based on the novelty of the datasets can prioritize later, better versions of data over similar predecessors. And knowledge of how different user types and communities use data can be brought to bear in cases where characteristics of the user (discipline, expertise) or their intent (applications, research) can be divined. The Earth Observing System Data and Information System has begun implementing some of these heuristics in the relevancy algorithm of its Common Metadata Repository search engine.

  3. Multirelational Social Recommendations via Multigraph Ranking.

    Science.gov (United States)

    Mao, Mingsong; Lu, Jie; Zhang, Guangquan; Zhang, Jinlong

    2017-12-01

    Recommender systems aim to identify relevant items for particular users in large-scale online applications. The historical rating data of users is a valuable input resource for many recommendation models such as collaborative filtering (CF), but these models are known to suffer from the rating sparsity problem when the users or items under consideration have insufficient rating records. With the continued growth of online social networks, the increased user-to-user relationships are reported to be helpful and can alleviate the CF rating sparsity problem. Although researchers have developed a range of social network-based recommender systems, there is no unified model to handle multirelational social networks. To address this challenge, this paper represents different user relationships in a multigraph and develops a multigraph ranking model to identify and recommend the nearest neighbors of particular users in high-order environments. We conduct empirical experiments on two real-world datasets: 1) Epinions and 2) Last.fm, and the comprehensive comparison with other approaches demonstrates that our model improves recommendation performance in terms of both recommendation coverage and accuracy, especially when the rating data are sparse.

  4. Grades and Ranking: When Tenure Affects Assessment

    Directory of Open Access Journals (Sweden)

    Jean Filetti

    2010-10-01

    Full Text Available This article examines how a faculty member's status-'either tenured or tenure-track-'might affect the grades assigned to students in a writing class. We begin with a brief review of the research surrounding faculty to student assessment practices and follow with specific controversies regarding faculty motivation pertaining to grading practices. We interpret the grade distributions of tenured and tenure-track faculty members teaching a sophomore-level writing course in an English Department at a small, public liberal arts university in Virginia, examine the relationship between grade distributions and faculty rank, and conclude that tenure-track faculty grade more leniently than their tenured colleagues, primarily in the number of - A- grades assigned. The results of this study suggest that tenured professors tend to award fewer - As- than tenure-track professors. We posit that at universities where emphasis is placed upon teaching, two specific patterns emerge: reciprocity may be an unspoken agreement between some faculty and students with regard to the exchange of good grades for good evaluations, or with experience comes rigor.

  5. Improving CBIR Systems Using Automated Ranking

    Directory of Open Access Journals (Sweden)

    B. D. Reljin

    2012-11-01

    Full Text Available The most common way of searching images on the Internet and in private collections is based on a similarity measuring of a series of text words that are assigned to each image with users query series. This method imposes strong constraints (the number of words to describe the image, the time necessary to thoroughly describe the subjective experience of images, the level of details in the picture, language barrier, etc., and is therefore very inefficient. Modern researches in this area are focused on the contentbased searching images (CBIR. In this way, all described disadvantages are overcome and the quality of searching results is improved. This paper presents a solution for CBIR systems where the search procedure is enhanced using sophisticated extraction and ranking of extracted images. The searching procedure is based on extraction and preprocessing of a large number of low level image features. Thus, when the user defines a query image, the proposed algorithm based on artificial intelligence, shows to the user a group of images which are most similar to a query image by content. The proposed algorithm is iterative, so the user can direct the searching procedure to an expected outcome and get a set of images that are more similar to the query one.

  6. Gene-Centric Genomewide Association Study via Entropy

    Science.gov (United States)

    Cui, Yuehua; Kang, Guolian; Sun, Kelian; Qian, Minping; Romero, Roberto; Fu, Wenjiang

    2008-01-01

    Genes are the functional units in most organisms. Compared to genetic variants located outside genes, genic variants are more likely to affect disease risk. The development of the human HapMap project provides an unprecedented opportunity for genetic association studies at the genomewide level for elucidating disease etiology. Currently, most association studies at the single-nucleotide polymorphism (SNP) or the haplotype level rely on the linkage information between SNP markers and disease variants, with which association findings are difficult to replicate. Moreover, variants in genes might not be sufficiently covered by currently available methods. In this article, we present a gene-centric approach via entropy statistics for a genomewide association study to identify disease genes. The new entropy-based approach considers genic variants within one gene simultaneously and is developed on the basis of a joint genotype distribution among genetic variants for an association test. A grouping algorithm based on a penalized entropy measure is proposed to reduce the dimension of the test statistic. Type I error rates and power of the entropy test are evaluated through extensive simulation studies. The results indicate that the entropy test has stable power under different disease models with a reasonable sample size. Compared to single SNP-based analysis, the gene-centric approach has greater power, especially when there is more than one disease variant in a gene. As the genomewide genic SNPs become available, our entropy-based gene-centric approach would provide a robust and computationally efficient way for gene-based genomewide association study. PMID:18458106

  7. 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.

  8. 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.

  9. 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.

  10. 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

  11. 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.

  12. 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.

  13. A Modification on the Hesitant Fuzzy Set Lexicographical Ranking Method

    Directory of Open Access Journals (Sweden)

    Xiaodi Liu

    2016-12-01

    Full Text Available Recently, a novel hesitant fuzzy set (HFS ranking technique based on the idea of lexicographical ordering is proposed and an example is presented to demonstrate that the proposed ranking method is invariant with multiple occurrences of any element of a hesitant fuzzy element (HFE. In this paper, we show by examples that the HFS lexicographical ordering method is sometimes invalid, and a modified ranking method is presented. In comparison with the HFS lexicographical ordering method, the modified ranking method is more reasonable in more general cases.

  14. 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.

  15. Severe language effect in university rankings: particularly Germany and France are wronged in citation-based rankings.

    Science.gov (United States)

    van Raan, Anthony F J; van Leeuwen, Thed N; Visser, Martijn S

    2011-08-01

    We applied a set of standard bibliometric indicators to monitor the scientific state-of-arte of 500 universities worldwide and constructed a ranking on the basis of these indicators (Leiden Ranking 2010). We find a dramatic and hitherto largely underestimated language effect in the bibliometric, citation-based measurements of research performance when comparing the ranking based on all Web of Science (WoS) covered publications and on only English WoS covered publications, particularly for Germany and France.

  16. Effect of Doximity Residency Rankings on Residency Applicants’ Program Choices

    Directory of Open Access Journals (Sweden)

    Aimee M. Rolston

    2015-11-01

    Full Text Available Introduction: Choosing a residency program is a stressful and important decision. Doximity released residency program rankings by specialty in September 2014. This study sought to investigate the impact of those rankings on residency application choices made by fourth year medical students. Methods: A 12-item survey was administered in October 2014 to fourth year medical students at three schools. Students indicated their specialty, awareness of and perceived accuracy of the rankings, and the rankings’ impact on the programs to which they chose to apply. Descriptive statistics were reported for all students and those applying to Emergency Medicine (EM. Results: A total of 461 (75.8% students responded, with 425 applying in one of the 20 Doximity ranked specialties. Of the 425, 247 (58% were aware of the rankings and 177 looked at them. On a 1-100 scale (100=very accurate, students reported a mean ranking accuracy rating of 56.7 (SD 20.3. Forty-five percent of students who looked at the rankings modified the number of programs to which they applied. The majority added programs. Of the 47 students applying to EM, 18 looked at the rankings and 33% changed their application list with most adding programs. Conclusion: The Doximity rankings had real effects on students applying to residencies as almost half of students who looked at the rankings modified their program list. Additionally, students found the rankings to be moderately accurate. Graduating students might benefit from emphasis on more objective characterization of programs to assess in light of their own interests and personal/career goals

  17. Stratification of co-evolving genomic groups using ranked phylogenetic profiles

    Directory of Open Access Journals (Sweden)

    Tsoka Sophia

    2009-10-01

    Full Text Available Abstract Background Previous methods of detecting the taxonomic origins of arbitrary sequence collections, with a significant impact to genome analysis and in particular metagenomics, have primarily focused on compositional features of genomes. The evolutionary patterns of phylogenetic distribution of genes or proteins, represented by phylogenetic profiles, provide an alternative approach for the detection of taxonomic origins, but typically suffer from low accuracy. Herein, we present rank-BLAST, a novel approach for the assignment of protein sequences into genomic groups of the same taxonomic origin, based on the ranking order of phylogenetic profiles of target genes or proteins across the reference database. Results The rank-BLAST approach is validated by computing the phylogenetic profiles of all sequences for five distinct microbial species of varying degrees of phylogenetic proximity, against a reference database of 243 fully sequenced genomes. The approach - a combination of sequence searches, statistical estimation and clustering - analyses the degree of sequence divergence between sets of protein sequences and allows the classification of protein sequences according to the species of origin with high accuracy, allowing taxonomic classification of 64% of the proteins studied. In most cases, a main cluster is detected, representing the corresponding species. Secondary, functionally distinct and species-specific clusters exhibit different patterns of phylogenetic distribution, thus flagging gene groups of interest. Detailed analyses of such cases are provided as examples. Conclusion Our results indicate that the rank-BLAST approach can capture the taxonomic origins of sequence collections in an accurate and efficient manner. The approach can be useful both for the analysis of genome evolution and the detection of species groups in metagenomics samples.

  18. Ranking production units according to marginal efficiency contribution

    DEFF Research Database (Denmark)

    Ghiyasi, Mojtaba; Hougaard, Jens Leth

    League tables associated with various forms of service activities from schools to hospitals illustrate the public need for ranking institutions by their productive performance. We present a new method for ranking production units which is based on each units marginal contribution to the technical...

  19. WISER ranking of the African national libraries' websites | Gupta ...

    African Journals Online (AJOL)

    Data collection has been done with the help of Google search engine and Check Page Rank tool. This study highlighted the fact that the ranking based on web impact factor was not much reliable and it is biased towards the small number of webpages and in-links. In the present study WISER, a combined web indicator was ...

  20. 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

  1. 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...

  2. The Ranking Phenomenon and the Experience of Academics in Taiwan

    Science.gov (United States)

    Lo, William Yat Wai

    2014-01-01

    The primary aim of the paper is to examine how global university rankings have influenced the higher education sector in Taiwan from the perspective of academics. A qualitative case study method was used to examine how university ranking influenced the Taiwanese higher education at institutional and individual levels, respectively, thereby…

  3. Relying on topic subsets for system ranking estimation

    NARCIS (Netherlands)

    Hauff, C.; Hiemstra, Djoerd; de Jong, Franciska M.G.; Azzopardi, Leif

    2009-01-01

    Ranking a number of retrieval systems according to their retrieval effectiveness without relying on costly relevance judgments was first explored by Soboroff et al [6]. Over the years, a number of alternative approaches have been proposed. We perform a comprehensive analysis of system ranking

  4. Who Should Rank Our Journals...And Based on What?

    Science.gov (United States)

    Cherkowski, Sabre; Currie, Russell; Hilton, Sandy

    2012-01-01

    Purpose: This study aims to establish the use of active scholar assessment (ASA) in the field of education leadership as a new methodology in ranking administration and leadership journals. The secondary purpose of this study is to respond to the paucity of research on journal ranking in educational administration and leadership.…

  5. A Comparative Analysis of Higher Education Ranking Systems in Europe

    Science.gov (United States)

    Hendel, Darwin D.; Stolz, Ingo

    2008-01-01

    According to Altbach in 2004, "everyone wants a world-class university". Corresponding developmental efforts undertaken by higher education institutions are very often referenced to improvements in ranking results. Surprisingly, there is relatively little analysis of variations in higher education ranking systems across countries…

  6. International University Ranking Systems and the Idea of University Excellence

    Science.gov (United States)

    Taylor, Paul; Braddock, Richard

    2007-01-01

    We look at some of the theoretical and methodological issues underlying international university ranking systems and, in particular, their conceptual connection with the idea of excellence. We then turn to a critical examination of the two best-known international university ranking systems--the "Times Higher Education Supplement (THES)" World…

  7. How Do European Pharmacy Students Rank Competences for Practice?

    NARCIS (Netherlands)

    Atkinson, Jeffrey; De Paepe, Kristien; Sánchez Pozo, Antonio; Rekkas, Dimitrios; Volmer, Daisy; Hirvonen, Jouni; Bozic, Borut; Skowron, Agnieska; Mircioiu, Constantin; Marcincal, Annie; Koster, Andries; Wilson, Keith; van Schravendijk, Chris; Hočevar, Sandra

    2016-01-01

    European students (n = 370), academics (n = 241) and community pharmacists (n = 258) ranked 13 clusters of 68 personal and patient care competences for pharmacy practice. The results show that ranking profiles for all three groups as a rule were similar. This was especially true of the comparison

  8. The Distribution of the Sum of Signed Ranks

    Science.gov (United States)

    Albright, Brian

    2012-01-01

    We describe the calculation of the distribution of the sum of signed ranks and develop an exact recursive algorithm for the distribution as well as an approximation of the distribution using the normal. The results have applications to the non-parametric Wilcoxon signed-rank test.

  9. Online learning to rank for information retrieval: SIGIR 2016 tutorial

    NARCIS (Netherlands)

    Grotov, A.; de Rijke, M.

    2016-01-01

    During the past 10--15 years offline learning to rank has had a tremendous influence on information retrieval, both scientifically and in practice. Recently, as the limitations of offline learning to rank for information retrieval have become apparent, there is increased attention for online

  10. A generative language modeling approach for ranking entities

    NARCIS (Netherlands)

    Weerkamp, W.; Balog, K.; Meij, E.

    2009-01-01

    We describe our participation in the INEX 2008 Entity Ranking track. We develop a generative language modeling approach for the entity ranking and list completion tasks. Our framework comprises the following components: (i) entity and (ii) query language models, (iii) entity prior, (iv) the

  11. Estimating Independent Locally Shifted Random Utility Models for Ranking Data

    Science.gov (United States)

    Lam, Kar Yin; Koning, Alex J.; Franses, Philip Hans

    2011-01-01

    We consider the estimation of probabilistic ranking models in the context of conjoint experiments. By using approximate rather than exact ranking probabilities, we avoided the computation of high-dimensional integrals. We extended the approximation technique proposed by Henery (1981) in the context of the Thurstone-Mosteller-Daniels model to any…

  12. A Global Comparison of Business Journal Ranking Systems

    Science.gov (United States)

    Alexander, Jennifer K.; Scherer, Robert F.; Lecoutre, Marc

    2007-01-01

    The authors compared business journal ranking systems from 6 countries. Results revealed a low degree of agreement among the systems, and a low to moderate relationship between pairs of systems. In addition, the French and United Kingdom ranking systems were different from each other and from the systems in Australia, Germany, Hong Kong, and the…

  13. 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.

  14. Combining Document-and Paragraph-Based Entity Ranking

    NARCIS (Netherlands)

    Rode, H.; Serdyukov, Pavel; Hiemstra, Djoerd

    2008-01-01

    We study entity ranking on the INEX entity track and pro- pose a simple graph-based ranking approach that enables to combine scores on document and paragraph level. The com- bined approach improves the retrieval results not only on the INEX testset, but similarly on TREC’s expert finding task.

  15. University Rankings: How Well Do They Measure Library Service Quality?

    Science.gov (United States)

    Jackson, Brian

    2015-01-01

    University rankings play an increasingly large role in shaping the goals of academic institutions and departments, while removing universities themselves from the evaluation process. This study compares the library-related results of two university ranking publications with scores on the LibQUAL+™ survey to identify if library service quality--as…

  16. What Parameters Do Students Value in Business School Rankings?

    Science.gov (United States)

    Mårtensson, Pär; Richtnér, Anders

    2015-01-01

    The starting point of this paper is the question: Which issues do students think are important when choosing a higher education institution, and how are they related to the factors taken into consideration in ranking institutions? The aim is to identify and rank the parameters students perceive as important when choosing their place of education.…

  17. Positioning Open Access Journals in a LIS Journal Ranking

    Science.gov (United States)

    Xia, Jingfeng

    2012-01-01

    This research uses the h-index to rank the quality of library and information science journals between 2004 and 2008. Selected open access (OA) journals are included in the ranking to assess current OA development in support of scholarly communication. It is found that OA journals have gained momentum supporting high-quality research and…

  18. Information Theoretic Bounds for Low-Rank Matrix Completion

    CERN Document Server

    Vishwanath, Sriram

    2010-01-01

    This paper studies the low-rank matrix completion problem from an information theoretic perspective. The completion problem is rephrased as a communication problem of an (uncoded) low-rank matrix source over an erasure channel. The paper then uses achievability and converse arguments to present order-wise optimal bounds for the completion problem.

  19. Balancing exploration and exploitation in learning to rank online

    NARCIS (Netherlands)

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

    2011-01-01

    As retrieval systems become more complex, learning to rank approaches are being developed to automatically tune their parameters. Using online learning to rank approaches, retrieval systems can learn directly from implicit feedback, while they are running. In such an online setting, algorithms need

  20. On the classification of complex vector bundles of stable rank

    Indian Academy of Sciences (India)

    According to previous observations, this would imply (under the above torsion conditions) a classification of all rank r complex vector bundles on X, for stable rank r ≥ n/2. A few partial answers to this question are known. For instance, a classical result of. Wu asserts that any couple of cohomology classes (c1,c2) ∈ H2(X, ...

  1. Economic Research at National Liberal Arts Colleges: School Rankings.

    Science.gov (United States)

    Hartley, James E.; Robinson, Michael D.

    1997-01-01

    Presents a comprehensive ranking of all national liberal arts colleges based on publications cataloged by the "Journal of Economic Literature" (JEL) from 1989-1994. Concludes that, although economics research is important at the highest ranked colleges, it remains a secondary consideration at the rest. Briefly discusses previous rankings…

  2. Rank range test for equality of dispersion | Odiase | Journal of ...

    African Journals Online (AJOL)

    This paper exploits the computational simplicity of the range of a set of data to formulate a twosample scale test called the Rank Range test. The performance of the test statistic is compared with other tests of scale. The exact distribution of the Rank Range test statistic is generated empirically through the unconditional ...

  3. Social ranking effects on tooth-brushing behaviour.

    Science.gov (United States)

    Maltby, John; Paterson, Kevin; Day, Liz; Jones, Ceri; Kinnear, Hayley; Buchanan, Heather

    2016-05-01

    A tooth-brushing social rank hypothesis is tested suggesting tooth-brushing duration is influenced when individuals position their behaviour in a rank when comparing their behaviour with other individuals. Study 1 used a correlation design, Study 2 used a semi-experimental design, and Study 3 used a randomized intervention design to examine the tooth-brushing social rank hypothesis in terms of self-reported attitudes, cognitions, and behaviour towards tooth-brushing duration. Study 1 surveyed participants to examine whether the perceived health benefits of tooth-brushing duration could be predicted from the ranking of each person's tooth-brushing duration. Study 2 tested whether manipulating the rank position of the tooth-brushing duration influenced participant-perceived health benefits of tooth-brushing duration. Study 3 used a longitudinal intervention method to examine whether messages relating to the rank positions of tooth-brushing durations causally influenced the self-report tooth-brushing duration. Study 1 demonstrates that perceptions of the health benefits from tooth-brushing duration are predicted by the perceptions of how that behaviour ranks in comparison to other people's behaviour. Study 2 demonstrates that the perceptions of the health benefits of tooth-brushing duration can be manipulated experimentally by changing the ranked position of a person's tooth-brushing duration. Study 3 experimentally demonstrates the possibility of increasing the length of time for which individuals clean their teeth by focusing on how they rank among their peers in terms of tooth-brushing duration. The effectiveness of interventions using social-ranking methods relative to those that emphasize comparisons made against group averages or normative guidelines are discussed. What is already known on this subject? Individual make judgements based on social rank information. Social rank information has been shown to influence positive health behaviours such as exercise

  4. PageRank model of opinion formation on social networks

    Science.gov (United States)

    Kandiah, Vivek; Shepelyansky, Dima L.

    2012-11-01

    We propose the PageRank model of opinion formation and investigate its rich properties on real directed networks of the Universities of Cambridge and Oxford, LiveJournal, and Twitter. In this model, the opinion formation of linked electors is weighted with their PageRank probability. Such a probability is used by the Google search engine for ranking of web pages. We find that the society elite, corresponding to the top PageRank nodes, can impose its opinion on a significant fraction of the society. However, for a homogeneous distribution of two opinions, there exists a bistability range of opinions which depends on a conformist parameter characterizing the opinion formation. We find that the LiveJournal and Twitter networks have a stronger tendency to a totalitarian opinion formation than the university networks. We also analyze the Sznajd model generalized for scale-free networks with the weighted PageRank vote of electors.

  5. 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.

  6. Rankings Scientists, Journals and Countries using h-Index

    Directory of Open Access Journals (Sweden)

    Gyula Mester

    2016-01-01

    Full Text Available Indexes in scientometrics are based on citations. However, in contrast to the journal impact factor, which gives only the ranking of the scientific journals, ordered by impact factor, indexes in scientometrics are suitable for ranking of scientists, scientific journals and countries. In this paper the h-index, h5-index, the World ranking the top of 25 Highly Cited Researchers (h > 100 and the ranking of 25 scientists in Hungarian Institutions according to their Google Scholar Citations public profiles are considered. These indexes (h5-index are applied for making of the list of top 20 publications (journals and proceedings in the field of Robotics. The World ranking is done of the best 50 countries according to h-index in year 2014. Data are obtained from the portal Scimago.

  7. 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.

  8. Rank Protein Immunolabeling during Bone-Implant Interface Healing Process

    Directory of Open Access Journals (Sweden)

    Francisley Ávila Souza

    2010-01-01

    Full Text Available The purpose of this paper was to evaluate the expression of RANK protein during bone-healing process around machined surface implants. Twenty male Wistar rats, 90 days old, after having had a 2 mm diameter and 6 mm long implant inserted in their right tibias, were evaluated at 7, 14, 21, and 42 days after healing. After obtaining the histological samples, slides were subjected to RANK immunostaining reaction. Results were quantitatively evaluated. Results. Immunolabeling analysis showed expressions of RANK in osteoclast and osteoblast lineage cells. The statistical analysis showed an increase in the expression of RANK in osteoblasts at 7 postoperative days and a gradual decrease during the chronology of the healing process demonstrated by mild cellular activity in the final stage (P<.05. Conclusion. RANK immunolabeling was observed especially in osteoclast and osteoblast cells in primary bone during the initial periods of bone-healing/implant interface.

  9. Rank Protein Immunolabeling during Bone-Implant Interface Healing Process

    Science.gov (United States)

    Ávila Souza, Francisley; Pereira Queiroz, Thallita; Rodrigues Luvizuto, Eloá; Nishioka, Renato Sussumu; Garcia-JR, Idelmo Rangel; de Carvalho, Paulo Sérgio Perri; Okamoto, Roberta

    2010-01-01

    The purpose of this paper was to evaluate the expression of RANK protein during bone-healing process around machined surface implants. Twenty male Wistar rats, 90 days old, after having had a 2 mm diameter and 6 mm long implant inserted in their right tibias, were evaluated at 7, 14, 21, and 42 days after healing. After obtaining the histological samples, slides were subjected to RANK immunostaining reaction. Results were quantitatively evaluated. Results. Immunolabeling analysis showed expressions of RANK in osteoclast and osteoblast lineage cells. The statistical analysis showed an increase in the expression of RANK in osteoblasts at 7 postoperative days and a gradual decrease during the chronology of the healing process demonstrated by mild cellular activity in the final stage (P < .05). Conclusion. RANK immunolabeling was observed especially in osteoclast and osteoblast cells in primary bone during the initial periods of bone-healing/implant interface. PMID:20706673

  10. Beyond Zipf's Law: The Lavalette Rank Function and its Properties

    CERN Document Server

    Fontanelli, Oscar; Yang, Yaning; Cocho, Germinal; Li, Wentian

    2016-01-01

    Although Zipf's law is widespread in natural and social data, one often encounters situations where one or both ends of the ranked data deviate from the power-law function. Previously we proposed the Beta rank function to improve the fitting of data which does not follow a perfect Zipf's law. Here we show that when the two parameters in the Beta rank function have the same value, the Lavalette rank function, the probability density function can be derived analytically. We also show both computationally and analytically that Lavalette distribution is approximately equal, though not identical, to the lognormal distribution. We illustrate the utility of Lavalette rank function in several datasets. We also address three analysis issues on the statistical testing of Lavalette fitting function, comparison between Zipf's law and lognormal distribution through Lavalette function, and comparison between lognormal distribution and Lavalette distribution.

  11. VisualRank: applying PageRank to large-scale image search.

    Science.gov (United States)

    Jing, Yushi; Baluja, Shumeet

    2008-11-01

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

  12. 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 different disciplines, and this perceived difference could have implications for promotion and tenure decisions.

  13. The Times Higher Education Supplement and Quacquarelli Symonds (THES - QS) World University Rankings: New Developments in Ranking Methodology

    Science.gov (United States)

    Sowter, Ben

    2008-01-01

    This paper presents key new developments in the THES - QS World University Rankings in 2007, related to enhancements to the "Peer Review", "Data Collection" and "Statistical Aggregation" utilised in this ranking as well as discussing the decision to utilise Full-Time Equivalent (FTE) figures for personnel statistics. Indicator correlation is also…

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

    NARCIS (Netherlands)

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

    2015-01-01

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

  15. RANK (TNFRSF11A Is Epigenetically Inactivated and Induces Apoptosis in Gliomas

    Directory of Open Access Journals (Sweden)

    Anna von dem Knesebeck

    2012-06-01

    Full Text Available Alterations of DNA methylation play an important role in gliomas. In a genome-wide screen, we identified a CpG-rich fragment within the 5′ region of the tumor necrosis factor receptor superfamily, member 11A gene (TNFRSF11A that showed de novo methylation in gliomas. TNFRSF11A, also known as receptor activator of NF-κB (RANK, activates several signaling pathways, such as NF-κB, JNK, ERK, p38α, and Akt/PKB. Using pyrosequencing, we detected RANK/TNFRSF11A promoter methylation in 8 (57.1% of 14 diffuse astrocytomas, 17 (77.3% of 22 anaplastic astrocytomas, 101 (84.2% of 120 glioblastomas, 6 (100% of 6 glioma cell lines, and 7 (100% of 7 glioma stem cell-enriched glioblastoma primary cultures but not in four normal white matter tissue samples. Treatment of glioma cell lines with the demethylating agent 5-aza-2′-deoxycytidine significantly reduced the methylation level and resulted in increased RANK/TNFRSF11A mRNA expression. Overexpression of RANK/TNFRSF11A in glioblastoma cell lines leads to a significant reduction in focus formation and elevated apoptotic activity after flow cytometric analysis. Reporter assay studies of transfected glioma cells supported these results by showing the activation of signaling pathways associated with regulation of apoptosis. We conclude that RANK/TNFRSF11A is a novel and frequent target for de novo methylation in gliomas, which affects apoptotic activity and focus formation thereby contributing to the molecular pathogenesis of gliomas.

  16. Highlighting Entanglement of Cultures via Ranking of Multilingual Wikipedia Articles

    Science.gov (United States)

    Eom, Young-Ho; Shepelyansky, Dima L.

    2013-01-01

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

  17. SRS: Site ranking system for hazardous chemical and radioactive waste

    Energy Technology Data Exchange (ETDEWEB)

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

    1988-05-01

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

  18. Highlighting entanglement of cultures via ranking of multilingual Wikipedia articles.

    Directory of Open Access Journals (Sweden)

    Young-Ho Eom

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

  19. Highlighting entanglement of cultures via ranking of multilingual Wikipedia articles.

    Science.gov (United States)

    Eom, Young-Ho; Shepelyansky, Dima L

    2013-01-01

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

  20. RANK/RANKL/OPG pathway: genetic associations with stress fracture period prevalence in elite athletes.

    Science.gov (United States)

    Varley, Ian; Hughes, David C; Greeves, Julie P; Stellingwerff, Trent; Ranson, Craig; Fraser, William D; Sale, Craig

    2015-02-01

    The RANK/RANKL/OPG signalling pathway is important in the regulation of bone turnover, with single nucleotide polymorphisms (SNPs) in genes within this pathway associated with bone phenotypic adaptations. To determine whether four SNPs associated with genes in the RANK/RANKL/OPG signalling pathway were associated with stress fracture injury in elite athletes. Radiologically confirmed stress fracture history was reported in 518 elite athletes, forming the Stress Fracture Elite Athlete (SFEA) cohort. Data were analysed for the whole group and were sub-stratified into male and cases of multiple stress fracture groups. Genotypes were determined using proprietary fluorescence-based competitive allele-specific PCR assays. SNPs rs3018362 (RANK) and rs1021188 (RANKL) were associated with stress fracture injury (Pstress fracture group and 2.8% of the non-stress fracture group were homozygote for the rare allele of rs1021188. Allele frequency, heterozygotes and homozygotes for the rare allele of rs3018362 were associated with stress fracture period prevalence (Pstress fracture whilst 2.5% of the non-stress fracture group were homozygous. In cases of multiple stress fractures, homozygotes for the rare allele of rs1021188 and individuals possessing at least one copy of the rare allele of rs4355801 (OPG) were shown to be associated with stress fracture injury (Pstress fracture injury. The association of rs3018362 (RANK) and rs1021188 (RANKL) with stress fracture injury susceptibility supports their role in the maintenance of bone health and offers potential targets for therapeutic interventions. Copyright © 2014 Elsevier Inc. All rights reserved.

  1. Ranking the dermatology programs based on measurements of academic achievement.

    Science.gov (United States)

    Wu, Jashin J; Ramirez, Claudia C; Alonso, Carol A; Berman, Brian; Tyring, Stephen K

    2007-07-13

    The only dermatology rankings in the past were based on National Institutes of Health (NIH) funding and journal citations. To determine the highest ranking academic dermatology programs based on 5 outcome measures and on an overall ranking scale. To the best of our knowledge, this is the first report to rank the dermatology programs on 4 of the following outcome measures of academic achievement and with an overall ranking. We collected extensive 2001 to 2004 data ranging from total publications to grant funding on 107 U.S. dermatology programs and their full-time faculty. Data from part-time and volunteer faculty were not used. Publications in 2001 to 2004; NIH funding in 2004; Dermatology Foundation grants in 2001 to 2004; faculty lectures in 2004 delivered at national conferences; number of full-time faculty members who were on the editorial boards of the top 3 U.S. dermatology journals and the top 4 subspecialty journals We used the 5 outcome measures to tabulate the highest ranking programs in each category. Using a weighted ranking system, we also tabulated the overall top 30 dermatology programs based on these 5 outcome measures. We were not able to determine the total amount of NIH funding in dollars of the dermatology divisions. The impact factors of the journal in which these publications appeared was not factored into our calculations. Since faculty members may collaborate on the same publication, some publications may have been double-counted. In descending order, the 5 highest ranked academic programs are the University of Pennsylvania; University of California, San Francisco; Yale-New Haven Medical Center; New York University; and University of Michigan. This ranking system may allow residents and faculty to improve the academic achievements at their respective programs.

  2. An Efficient PageRank Approach for Urban Traffic Optimization

    Directory of Open Access Journals (Sweden)

    Florin Pop

    2012-01-01

    to determine optimal decisions for each traffic light, based on the solution given by Larry Page for page ranking in Web environment (Page et al. (1999. Our approach is similar with work presented by Sheng-Chung et al. (2009 and Yousef et al. (2010. We consider that the traffic lights are controlled by servers and a score for each road is computed based on efficient PageRank approach and is used in cost function to determine optimal decisions. We demonstrate that the cumulative contribution of each car in the traffic respects the main constrain of PageRank approach, preserving all the properties of matrix consider in our model.

  3. The art of living in Otto Rank's Will Therapy.

    Science.gov (United States)

    Wadlington, Will

    2012-12-01

    Otto Rank's approach to psychotherapy, developed after his separation from Freud, encourages living life fully in spite of death and limitation. In his emphasis on the here and now, new experience in the therapeutic relationship, and collaboration and creativity in the therapy process, Rank was ahead of his time. As a theorist of personality and of creativity, his work is well known, but his influence on the practices of humanistic, existential, and post-psychoanalytic relational therapists is largely unacknowledged. Rank's creative legacy is an approach to psychotherapy that calls forth artistry and collaboration between therapist and client.

  4. Who's #1? The Science of Rating and Ranking

    CERN Document Server

    Langville, Amy N

    2012-01-01

    A website's ranking on Google can spell the difference between success and failure for a new business. NCAA football ratings determine which schools get to play for the big money in postseason bowl games. Product ratings influence everything from the clothes we wear to the movies we select on Netflix. Ratings and rankings are everywhere, but how exactly do they work? Who's #1? offers an engaging and accessible account of how scientific rating and ranking methods are created and applied to a variety of uses. Amy Langville and Carl Meyer provide the first comprehensive overview of the mathemat

  5. Reduced rank adaptive filtering in impulsive noise environments

    KAUST Repository

    Soury, Hamza

    2014-11-01

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

  6. Google's pagerank and beyond the science of search engine rankings

    CERN Document Server

    Langville, Amy N

    2006-01-01

    Why doesn't your home page appear on the first page of search results, even when you query your own name? How do other Web pages always appear at the top? What creates these powerful rankings? And how? The first book ever about the science of Web page rankings, Google's PageRank and Beyond supplies the answers to these and other questions and more. The book serves two very different audiences: the curious science reader and the technical computational reader. The chapters build in mathematical sophistication, so that the first five are accessible to the general academic reader. While other cha

  7. Ranking stability and super-stable nodes in complex networks.

    Science.gov (United States)

    Ghoshal, Gourab; Barabási, Albert-László

    2011-07-19

    Pagerank, a network-based diffusion algorithm, has emerged as the leading method to rank web content, ecological species and even scientists. Despite its wide use, it remains unknown how the structure of the network on which it operates affects its performance. Here we show that for random networks the ranking provided by pagerank is sensitive to perturbations in the network topology, making it unreliable for incomplete or noisy systems. In contrast, in scale-free networks we predict analytically the emergence of super-stable nodes whose ranking is exceptionally stable to perturbations. We calculate the dependence of the number of super-stable nodes on network characteristics and demonstrate their presence in real networks, in agreement with the analytical predictions. These results not only deepen our understanding of the interplay between network topology and dynamical processes but also have implications in all areas where ranking has a role, from science to marketing.

  8. 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.

  9. Topic Evolutionary Tweet Stream Clustering Algorithm and TCV Rank Summarization

    National Research Council Canada - National Science Library

    K.Selvaraj; S.Balaji

    2015-01-01

    ... and more. our proposed work consists three components tweet stream clustering to cluster tweet using k-means cluster algorithm and second tweet cluster vector technique to generate rank summarization using...

  10. Ranking online quality and reputation via the user activity

    Science.gov (United States)

    Liu, Xiao-Lu; Guo, Qiang; Hou, Lei; Cheng, Can; Liu, Jian-Guo

    2015-10-01

    How to design an accurate algorithm for ranking the object quality and user reputation is of importance for online rating systems. In this paper we present an improved iterative algorithm for online ranking object quality and user reputation in terms of the user degree (IRUA), where the user's reputation is measured by his/her rating vector, the corresponding objects' quality vector and the user degree. The experimental results for the empirical networks show that the AUC values of the IRUA algorithm can reach 0.9065 and 0.8705 in Movielens and Netflix data sets, respectively, which is better than the results generated by the traditional iterative ranking methods. Meanwhile, the results for the synthetic networks indicate that user degree should be considered in real rating systems due to users' rating behaviors. Moreover, we find that enhancing or reducing the influences of the large-degree users could produce more accurate reputation ranking lists.

  11. The system of world golf ranking among amateur players - WAGR

    Directory of Open Access Journals (Sweden)

    Tereshchuk M.V.

    2014-11-01

    Full Text Available Purpose: justify the particular rating-WAGR and determine its value. Material: More than 40 references, including analysis of 8 protocols of Ukraine competition in golf. Results: The features and significance of the world rankings in golf among amateur players. Displaying ranking tournaments in accordance with the system of WAGR and justified the use of the conversion of the results to determine the specific places the player in the rankings. In Ukraine, held six WAGR-Tournament, the first tournament was held in 2011. Today in the world ranking of amateur players is one player from the Ukraine. Conclusions: It was found that the top-WAGR determines the level of development of the national golf federations and influence in the international arena. For the selection of athletes for the summer Youth Olympic Games is used world-rated golf amateur players (WAGR among boys and girls.

  12. Weighted Discriminative Dictionary Learning based on Low-rank Representation

    Science.gov (United States)

    Chang, Heyou; Zheng, Hao

    2017-01-01

    Low-rank representation has been widely used in the field of pattern classification, especially when both training and testing images are corrupted with large noise. Dictionary plays an important role in low-rank representation. With respect to the semantic dictionary, the optimal representation matrix should be block-diagonal. However, traditional low-rank representation based dictionary learning methods cannot effectively exploit the discriminative information between data and dictionary. To address this problem, this paper proposed weighted discriminative dictionary learning based on low-rank representation, where a weighted representation regularization term is constructed. The regularization associates label information of both training samples and dictionary atoms, and encourages to generate a discriminative representation with class-wise block-diagonal structure, which can further improve the classification performance where both training and testing images are corrupted with large noise. Experimental results demonstrate advantages of the proposed method over the state-of-the-art methods.

  13. Universality in the tail of musical note rank distribution

    Science.gov (United States)

    Beltrán del Río, M.; Cocho, G.; Naumis, G. G.

    2008-09-01

    Although power laws have been used to fit rank distributions in many different contexts, they usually fail at the tails. Languages as sequences of symbols have been a popular subject for ranking distributions, and for this purpose, music can be treated as such. Here we show that more than 1800 musical compositions are very well fitted by the first kind two parameter beta distribution, which arises in the ranking of multiplicative stochastic processes. The parameters a and b are obtained for classical, jazz and rock music, revealing interesting features. Specially, we have obtained a clear trend in the values of the parameters for major and minor tonal modes. Finally, we discuss the distribution of notes for each octave and its connection with the ranking of the notes.

  14. INTEL: Intel based systems move up in supercomputing ranks

    CERN Document Server

    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).

  15. Rank on emotional intelligence, unlearning and self-leadership.

    Science.gov (United States)

    Kramer, Robert

    2012-12-01

    Propelled from the inner circle after publishing The Trauma of Birth (1924), Otto Rank jettisoned Freud's science of knowing because it denied the intelligence of the emotions. Transforming therapy from knowing to being-in-relationship, Rank invented modern object-relations theory, which advocates continual learning, unlearning and relearning: that is, cutting the chains that bind us to the past. Separating, no matter how anxiety-provoking, from outworn phases of life, including previously taken-for-granted ideologies and internalized others, is essential for self-leadership. In 1926, Rank coined the terms "here-and-now" and "pre-Oedipal." By 1926, Rank had formulated a model of "creative willing"-self-leadership infused with the intelligence of the emotions-as the optimal way of being-in-relationship with others.

  16. Bootstrap determination of the cointegration rank in heteroskedastic VAR models

    DEFF Research Database (Denmark)

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

    2014-01-01

    In a recent paper Cavaliere et al. (2012) develop bootstrap implementations of the (pseudo-) likelihood ratio (PLR) co-integration rank test and associated sequential rank determination procedure of Johansen (1996). The bootstrap samples are constructed using the restricted parameter estimates...... show that the bootstrap PLR tests are asymptotically correctly sized and, moreover, that the probability that the associated bootstrap sequential procedures select a rank smaller than the true rank converges to zero. This result is shown to hold for both the i.i.d. and wild bootstrap variants under...... conditional heteroskedasticity but only for the latter under unconditional heteroskedasticity. Monte Carlo evidence is reported which suggests that the bootstrap approach of Cavaliere et al. (2012) significantly improves upon the finite sample performance of corresponding procedures based on either...

  17. A network-based dynamical ranking system for competitive sports

    Science.gov (United States)

    Motegi, Shun; Masuda, Naoki

    2012-12-01

    From the viewpoint of networks, a ranking system for players or teams in sports is equivalent to a centrality measure for sports networks, whereby a directed link represents the result of a single game. Previously proposed network-based ranking systems are derived from static networks, i.e., aggregation of the results of games over time. However, the score of a player (or team) fluctuates over time. Defeating a renowned player in the peak performance is intuitively more rewarding than defeating the same player in other periods. To account for this factor, we propose a dynamic variant of such a network-based ranking system and apply it to professional men's tennis data. We derive a set of linear online update equations for the score of each player. The proposed ranking system predicts the outcome of the future games with a higher accuracy than the static counterparts.

  18. A network-based dynamical ranking system for competitive sports

    National Research Council Canada - National Science Library

    Motegi, Shun; Masuda, Naoki

    2012-01-01

    From the viewpoint of networks, a ranking system for players or teams in sports is equivalent to a centrality measure for sports networks, whereby a directed link represents the result of a single game...

  19. A network-based dynamical ranking system for competitive sports.

    Science.gov (United States)

    Motegi, Shun; Masuda, Naoki

    2012-01-01

    From the viewpoint of networks, a ranking system for players or teams in sports is equivalent to a centrality measure for sports networks, whereby a directed link represents the result of a single game. Previously proposed network-based ranking systems are derived from static networks, i.e., aggregation of the results of games over time. However, the score of a player (or team) fluctuates over time. Defeating a renowned player in the peak performance is intuitively more rewarding than defeating the same player in other periods. To account for this factor, we propose a dynamic variant of such a network-based ranking system and apply it to professional men's tennis data. We derive a set of linear online update equations for the score of each player. The proposed ranking system predicts the outcome of the future games with a higher accuracy than the static counterparts.

  20. Superfund Hazard Ranking System Training Course: Table of Contents

    Science.gov (United States)

    The Hazard Ranking System (HRS) training course is a four and ½ day, intermediate-level course designed for personnel who are required to compile, draft, and review preliminary assessments (PAs), site inspections (SIs), and HRS documentation records/packag

  1. The THES University Rankings: Are They Really World Class?

    Directory of Open Access Journals (Sweden)

    Richard Holmes

    2006-06-01

    Full Text Available The Times Higher Education Supplement (THES international ranking of universities, published in 2004 and 2005, has received a great deal of attention throughout the world, nowhere more so than in East and Southeast Asia. This paper looks at the rankings and concludes that they are deficient in several respects. The sampling procedure is not explained and is very probably seriously biased, the weighting of the various components is not justified, inappropriate measures of teaching quality are used, the assessment of research achievement is biased against the humanities and social sciences, the classification of institutions is inconsistent, there are striking and implausible changes in the rankings between 2004 and 2005 and they are based in one crucial respect on regional rather than international comparisons. It is recommended that these rankings should not be the basis for the development and assessment of national and institutional policies

  2. RUSSIAN UNIVERSITIES IN THE LOOP OF THE WORLD EDUCATION RANKINGS

    Directory of Open Access Journals (Sweden)

    Inozemtseva Ekaterina Sergeevna

    2013-02-01

    Full Text Available Purpose: a research on different sociological and economic aspects of world education rankings (THE, ARWU, QS, evaluation of their role and impact on the world education market’s main consumers (i.e. students and academic staff as a subject to discussion in terms of the customers’ preferences and choice motivators. Methodology: general scientific research tools were applied throughout the research: analysis, synthesis, deduction. Results: world ranking approach and methodology was assessed, defined and systemized, a unique general ranking of the countries was developed and performed (based on the researched body – the US ranked #1, Russia #30, expert recommendations for Russian universities have been developed and concluded. Practical implications: the main statements could be used within learning courses on the internationalization of higher education and applied in sociological and economic research dedicated to macroeconomic problems and issues analysis.

  3. RUSSIAN UNIVERSITIES IN THE LOOP OF THE WORLD EDUCATION RANKINGS

    Directory of Open Access Journals (Sweden)

    Екатерина Сергеевна Иноземцева

    2013-04-01

    Full Text Available Purpose: a research on different sociological and economic aspects of world education rankings (THE, ARWU, QS, evaluation of their role and impact on the world education market’s main consumers (i.e. students and academic staff as a subject to discussion in terms of the customers’ preferences and choice motivators.  Methodology: general scientific research tools were applied throughout the research: analysis, synthesis, deduction.Results: world ranking approach and methodology was assessed, defined and systemized, a unique general ranking of the countries was developed and performed (based on the researched body – the US ranked #1, Russia #30, expert recommendations for Russian universities have been developed and concluded.Practical implications: the main statements could be used within learning courses on the internationalization of higher education and applied in sociological and economic research dedicated to macroeconomic problems and issues analysis.DOI: http://dx.doi.org/10.12731/2218-7405-2013-2-18

  4. The Rank-Ferenczi relationship, as seen from France.

    Science.gov (United States)

    Lugrin, Yves

    2012-12-01

    Seen from France, where Rank's "American" work is not well known, the Rank-Ferenczi relationship does not allow to state that the two learned colleagues were the best friends. Rank met Ferenczi in 1908, but their most valuable and fruitful working relationship is limited to the 1922-1924 time period. Their working relationship must be read in light of the unique transference links of each to Freud, and in light of the tormented history of the analytic movement, especially after the First World War. The sensible reader will not forget that after the fast extinction of their short collaboration they continued their own works in their own ways, Otto Rank in Paris and in America and Sándor Ferenczi in Budapest. No more friends, nor enemies, but both, in a different style, brave and creative analysts.

  5. Results of the Universidad Nacional de Colombia's Research Groups ranking

    National Research Council Canada - National Science Library

    Andrés Pavas

    2016-01-01

    ... of the national scientic production. In previous editorial notes of Ingeniera e Investigacin (Narvez, 2014; Pavas, 2015), a revision of the research groups ranking in the Universidad Nacional de Colombia UN was presented for the last two years...

  6. Locating Leaks with TrustRank Algorithm Support

    National Research Council Canada - National Science Library

    Luísa Ribeiro; Joaquim Sousa; Alfeu Sa Marques; Nuno E Simões

    2015-01-01

      This paper presents a methodology to quantify and to locate leaks. The original contribution is the use of a tool based on the TrustRank algorithm for the selection of nodes for pressure monitoring...

  7. Hearing Office Average Processing Time Ranking Report, February 2016

    Data.gov (United States)

    Social Security Administration — A ranking of ODAR hearing offices by the average number of hearings dispositions per ALJ per day. The average shown will be a combined average for all ALJs working...

  8. Personalized Profile Based Search Interface With Ranked and Clustered Display

    National Research Council Canada - National Science Library

    Kumar, Sachin; Oztekin, B. U; Ertoz, Levent; Singhal, Saurabh; Han, Euihong; Kumar, Vipin

    2001-01-01

    We have developed an experimental meta-search engine, which takes the snippets from traditional search engines and presents them to the user either in the form of clusters, indices or re-ranked list...

  9. Ranking industries using a hybrid of DEA-TOPSIS

    Directory of Open Access Journals (Sweden)

    Amir Mehdiabadi

    2013-10-01

    Full Text Available Ranking industry normally helps find hot sectors and attract potential investors to invest in appropriate plans. Ranking various industries is also a multiple criteria decision making problem. In this paper, we present an empirical investigation to rank different industries using the art of data envelopment analysis (DEA. The inputs of our proposed DEA model include capital, employment and importance coefficient and outputs are exports, ecological effects and added value. In addition, exports, value added and environmental investment are used as outputs of DEA method. Since the results of DEA may consider more than one efficient unit, so we implement Technique for Order Preference by Similarity to Ideal Solution (TOPSIS technique to rank efficient units. In our case study, there were 15 different sectors from various industries and the implementation of DEA technique recommends 8 efficient units. The implementation of TOPSIS among these efficient units has suggested that Chemical industry could be considered as the most attracting industry for investment.

  10. Hearing Office Dispositions Per ALJ Per Day Rate Ranking Report

    Data.gov (United States)

    Social Security Administration — A ranking of ODAR hearing offices by the average number of hearings dispositions per ALJ per day. The average shown will be a combined average for all ALJs working...

  11. Analysis of convergence performance of neural networks ranking algorithm.

    Science.gov (United States)

    Zhang, Yongquan; Cao, Feilong

    2012-10-01

    The ranking problem is to learn a real-valued function which gives rise to a ranking over an instance space, which has gained much attention in machine learning in recent years. This article gives analysis of the convergence performance of neural networks ranking algorithm by means of the given samples and approximation property of neural networks. The upper bounds of convergence rate provided by our results can be considerably tight and independent of the dimension of input space when the target function satisfies some smooth condition. The obtained results imply that neural networks are able to adapt to ranking function in the instance space. Hence the obtained results are able to circumvent the curse of dimensionality on some smooth condition. Crown Copyright © 2012. Published by Elsevier Ltd. All rights reserved.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2001-10-01

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

  13. 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

  14. 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

  15. Student Practices, Learning, and Attitudes When Using Computerized Ranking Tasks

    Science.gov (United States)

    Lee, Kevin M.; Prather, E. E.; Collaboration of Astronomy Teaching Scholars CATS

    2011-01-01

    Ranking Tasks are a novel type of conceptual exercise based on a technique called rule assessment. Ranking Tasks present students with a series of four to eight icons that describe slightly different variations of a basic physical situation. Students are then asked to identify the order, or ranking, of the various situations based on some physical outcome or result. The structure of Ranking Tasks makes it difficult for students to rely strictly on memorized answers and mechanical substitution of formulae. In addition, by changing the presentation of the different scenarios (e.g., photographs, line diagrams, graphs, tables, etc.) we find that Ranking Tasks require students to develop mental schema that are more flexible and robust. Ranking tasks may be implemented on the computer which requires students to order the icons through drag-and-drop. Computer implementation allows the incorporation of background material, grading with feedback, and providing additional similar versions of the task through randomization so that students can build expertise through practice. This poster will summarize the results of a study of student usage of computerized ranking tasks. We will investigate 1) student practices (How do they make use of these tools?), 2) knowledge and skill building (Do student scores improve with iteration and are there diminishing returns?), and 3) student attitudes toward using computerized Ranking Tasks (Do they like using them?). This material is based upon work supported by the National Science Foundation under Grant No. 0715517, a CCLI Phase III Grant for the Collaboration of Astronomy Teaching Scholars (CATS). Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.

  16. Tensor rank is not multiplicative under the tensor product

    DEFF Research Database (Denmark)

    Christandl, Matthias; Jensen, Asger Kjærulff; Zuiddam, Jeroen

    2018-01-01

    The tensor rank of a tensor t is the smallest number r such that t can be decomposed as a sum of r simple tensors. Let s be a k-tensor and let t be an ℓ-tensor. The tensor product of s and t is a (k+ℓ)-tensor. Tensor rank is sub-multiplicative under the tensor product. We revisit the connection b...

  17. Image Retrieval and Re-Ranking Techniques - A Survey

    OpenAIRE

    Mayuri D. Joshi; Revati M. Deshmukh; Kalashree N.Hemke; Ashwini Bhake; Rakhi Wajgi

    2014-01-01

    There is a huge amount of research work focusing on the searching, retrieval and re-ranking of images in the image database. The diverse and scattered work in this domain needs to be collected and organized for easy and quick reference. Relating to the above context, this paper gives a brief overview of various image retrieval and re-ranking techniques. Starting with the introduction to existing system the paper proceeds through the core architecture of image harvesti...

  18. LET THE STUDENTS DECIDE: A PERSONALISED RANKING OF TURKISH UNIVERSITIES

    OpenAIRE

    MUTLUTÜRK, Meltem Emine

    2016-01-01

    Choosing a university from a vast range of choices is a major decision in every student’s life. There are various amounts of university ranking systems that mostly use academic indicators such as number of citations, number of publications and doctorate students in their ranking model, but other indicators such as socio-cultural and physical structure of the university also factor into their decision, especially when choosing between universities of the same league. In this paper, the multi-c...

  19. Ranking and Mapping the Contributions by Overseas Chinese Strategy Scholars

    DEFF Research Database (Denmark)

    Li, Weiwen; Li, Peter Ping; Shu, Cheng

    2015-01-01

    The authors comment on an article by H. Jiao and colleagues regarding development of a ranking of overseas Chines strategy scholars in terms of their contributions to the strategy research. Topics include selection of 24 business journals ranked by the University of Texas at Dallas...... for their research; identifying authors who had published articles in periodicals such as "Management and Organization Review;" and development of a coding protocol and discussing coding procedure.....

  20. Top coalitions, common rankings, and semistrict core stability

    OpenAIRE

    Dinko Dimitrov

    2006-01-01

    The top coalition property of Banerjee et al. (2001) and the common ranking property of Farrell and Scotchmer (1988) are sufficient conditions for core stability in hedonic games. We introduce the semistrict core as a stronger stability concept than the core, and show that the top coalition property guarantees the existence of semistrictly core stable coalition structures. Moreover, for each game satisfying the common ranking property, the core and the semistrict core coincide.

  1. 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....

  2. Ranking independent timber investments by alternative investment criteria

    Science.gov (United States)

    Thomas J. Mills; Gary E. Dixon

    1982-01-01

    A sample of 231 independent timber investments were ranked by internal rate of return, present net worth per acre and the benefit cost ratio—the last two discounted by 3, 6.4. 7.5. and 10 percent—to determine if the different criteria had a practical influence on timber investment ranking. The samples in this study were drawn from a group of timber investments...

  3. International infant mortality rankings: A look behind the numbers

    OpenAIRE

    Liu, Korbin; Moon, Marilyn; Sulvetta, Margaret; Chawla, Juhi

    1992-01-01

    The very unfavorable infant mortality ranking of the United States in international comparisons is often used to question the quality of health care there. Infant mortality rates, however, implicitly capture a complicated story, measuring much more than differences in health care across countries. This article examines reasons behind international infant mortality rate rankings, including variations in the measurement of vital events, and differences in risk factors across countries. Its goal...

  4. 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…

  5. A new mutually reinforcing network node and link ranking algorithm.

    Science.gov (United States)

    Wang, Zhenghua; Dueñas-Osorio, Leonardo; Padgett, Jamie E

    2015-10-23

    This study proposes a novel Normalized Wide network Ranking algorithm (NWRank) that has the advantage of ranking nodes and links of a network simultaneously. This algorithm combines the mutual reinforcement feature of Hypertext Induced Topic Selection (HITS) and the weight normalization feature of PageRank. Relative weights are assigned to links based on the degree of the adjacent neighbors and the Betweenness Centrality instead of assigning the same weight to every link as assumed in PageRank. Numerical experiment results show that NWRank performs consistently better than HITS, PageRank, eigenvector centrality, and edge betweenness from the perspective of network connectivity and approximate network flow, which is also supported by comparisons with the expensive N-1 benchmark removal criteria based on network efficiency. Furthermore, it can avoid some problems, such as the Tightly Knit Community effect, which exists in HITS. NWRank provides a new inexpensive way to rank nodes and links of a network, which has practical applications, particularly to prioritize resource allocation for upgrade of hierarchical and distributed networks, as well as to support decision making in the design of networks, where node and link importance depend on a balance of local and global integrity.

  6. A Review of Ranking Models in Data Envelopment Analysis

    Directory of Open Access Journals (Sweden)

    F. Hosseinzadeh Lotfi

    2013-01-01

    Full Text Available In the course of improving various abilities of data envelopment analysis (DEA models, many investigations have been carried out for ranking decision-making units (DMUs. This is an important issue both in theory and practice. There exist a variety of papers which apply different ranking methods to a real data set. Here the ranking methods are divided into seven groups. As each of the existing methods can be viewed from different aspects, it is possible that somewhat these groups have an overlapping with the others. The first group conducts the evaluation by a cross-efficiency matrix where the units are self- and peer-evaluated. In the second one, the ranking units are based on the optimal weights obtained from multiplier model of DEA technique. In the third group, super-efficiency methods are dealt with which are based on the idea of excluding the unit under evaluation and analyzing the changes of frontier. The fourth group involves methods based on benchmarking, which adopts the idea of being a useful target for the inefficient units. The fourth group uses the multivariate statistical techniques, usually applied after conducting the DEA classification. The fifth research area ranks inefficient units through proportional measures of inefficiency. The sixth approach involves multiple-criteria decision methodologies with the DEA technique. In the last group, some different methods of ranking units are mentioned.

  7. 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.

  8. A new mutually reinforcing network node and link ranking algorithm

    Science.gov (United States)

    Wang, Zhenghua; Dueñas-Osorio, Leonardo; Padgett, Jamie E.

    2015-10-01

    This study proposes a novel Normalized Wide network Ranking algorithm (NWRank) that has the advantage of ranking nodes and links of a network simultaneously. This algorithm combines the mutual reinforcement feature of Hypertext Induced Topic Selection (HITS) and the weight normalization feature of PageRank. Relative weights are assigned to links based on the degree of the adjacent neighbors and the Betweenness Centrality instead of assigning the same weight to every link as assumed in PageRank. Numerical experiment results show that NWRank performs consistently better than HITS, PageRank, eigenvector centrality, and edge betweenness from the perspective of network connectivity and approximate network flow, which is also supported by comparisons with the expensive N-1 benchmark removal criteria based on network efficiency. Furthermore, it can avoid some problems, such as the Tightly Knit Community effect, which exists in HITS. NWRank provides a new inexpensive way to rank nodes and links of a network, which has practical applications, particularly to prioritize resource allocation for upgrade of hierarchical and distributed networks, as well as to support decision making in the design of networks, where node and link importance depend on a balance of local and global integrity.

  9. UNIVERSITY RANKING IMPROVING TOOLS IN MODERN INFORMATION EDUCATIONAL ENVIRONMENT

    Directory of Open Access Journals (Sweden)

    M. Bilous

    2015-03-01

    Full Text Available Ranking criteria of national and international levels are the instruments of university ranking increasing. Ratings provide a balanced measure of quality in higher educational institutions. Determining the level of university research influences the position of the university in various rankings. We can separate the main aggregates that are considered when ranking international higher education institutions. The results of university ranking allows the identification of its strengths and weaknesses in order to develop strategies for success and excellence based on the achievements of other universities at the regional, national and international levels. In article, we can see strengths, weaknesses, opportunities, and threats of Kherson State University (SWOT-analysis. The main goals of Kherson State University are self-promotion in the media space, raising the prestige of KSU and integration with the world science community, development of an effective technological corridor: «School - University – Labor» market, increasing the number of students, improving the ranking of academic staff in scientometric databases, and gaining international recognition.

  10. Aggregate Interview Method of ranking orthopedic applicants predicts future performance.

    Science.gov (United States)

    Geissler, Jacqueline; VanHeest, Ann; Tatman, Penny; Gioe, Terence

    2013-07-01

    This article evaluates and describes a process of ranking orthopedic applicants using what the authors term the Aggregate Interview Method. The authors hypothesized that higher-ranking applicants using this method at their institution would perform better than those ranked lower using multiple measures of resident performance. A retrospective review of 115 orthopedic residents was performed at the authors' institution. Residents were grouped into 3 categories by matching rank numbers: 1-5, 6-14, and 15 or higher. Each rank group was compared with resident performance as measured by faculty evaluations, the Orthopaedic In-Training Examination (OITE), and American Board of Orthopaedic Surgery (ABOS) test results. Residents ranked 1-5 scored significantly better on patient care, behavior, and overall competence by faculty evaluation (Porthopedic resident candidates who scored highly on the Accreditation Council for Graduate Medical Education resident core competencies as measured by faculty evaluations, performed above the national average on the OITE, and passed the ABOS part 1 examination at rates exceeding the national average. Copyright 2013, SLACK Incorporated.

  11. 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...

  12. On the Rank of Cutting-Plane Proof Systems

    Science.gov (United States)

    Pokutta, Sebastian; Schulz, Andreas S.

    We introduce a natural abstraction of propositional proof systems that are based on cutting planes. This new class of proof systems includes well-known operators such as Gomory-Chvátal cuts, lift-and-project cuts, Sherali-Adams cuts (for a fixed hierarchy level d), and split cuts. The rank of such a proof system corresponds to the number of rounds needed to show the nonexistence of integral solutions. We exhibit a family of polytopes without integral points contained in the n-dimensional 0/1-cube that has rank Ω(n/logn) for any proof system in our class. In fact, we show that whenever a specific cutting-plane based proof system has (maximal) rank n on a particular family of instances, then any cutting-plane proof system in our class has rank Ω(n/logn) for this family. This shows that the rank complexity of worst-case instances is intrinsic to the problem, and does not depend on specific cutting-plane proof systems, except for log factors. We also construct a new cutting-plane proof system that has worst-case rank O(n/logn) for any polytope without integral points, implying that the universal lower bound is essentially tight.

  13. 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.

  14. RANK/RANKL/OPG signaling pathways in necrotic jaw bone from bisphosphonate-treated subjects

    Directory of Open Access Journals (Sweden)

    C. Di Nisio

    2015-02-01

    Full Text Available Osteonecrosis of the jaw (ONJ is a chronic complication affecting long-term bisphosphonate-treated subjects, recognized by non-healing exposed bone in the maxillofacial region. The pathophysiological mechanism underlying ONJ has not been fully elucidated. The aim of the present study was to investigate the role of RANK/RANKL/OPG signaling pathway and, in parallel, to evaluate angiogenic and matrix mineralization processes in jaw bone necrotic samples obtained from bisphosphonate-treated subjects with established ONJ. Necrotic bone samples and native bone samples were processed for Light and Field Emission in Lens Scanning Electron Microscope (FEISEM analyses, for Real-Time RT-PCR to evaluate the gene expression of TNFRSF11A (RANK, TNFSF11 (RANKL, and TNFSF11B (OPG and for immunohistochemical analyses of VEGF and BSP expression. Morphological analyses performed by Light microscope and FEISEM show empty osteocytic lacunae and alteration of lamellar organization with degradation of the mineralized bone matrix in necrotic bone samples. A significant increase in TNFRSF11A, TNFSF11, TRAF6 and NFAT2 gene expression, and a reduction of TNFSF11B gene transcription level compared is also showed in necrotic bone compared to control samples. No significant difference of VEGF expression is evidenced, while lower BSP expression in necrotic bone compared to healthy samples is found. Even if the pathogenesis of bisphosphonate-associated ONJ remains unknown, a link between oral pathogens and its development seems to exist. We suppose lipopolysaccharide produced by bacteria colonizing and infecting necrotic bone and the surrounding viable area could trigger RANK/RANKL/OPG signaling pathway and, in this context, osteoclasts activation could be considered as a protective strategy carried out by the host bone tissue to delimitate the necrotic area and to counteract infection.

  15. Modeling Gene Networks in Saccharomyces cerevisiae Based on Gene Expression Profiles.

    Science.gov (United States)

    Zhang, Yulin; Lv, Kebo; Wang, Shudong; Su, Jionglong; Meng, Dazhi

    2015-01-01

    Detailed and innovative analysis of gene regulatory network structures may reveal novel insights to biological mechanisms. Here we study how gene regulatory network in Saccharomyces cerevisiae can differ under aerobic and anaerobic conditions. To achieve this, we discretized the gene expression profiles and calculated the self-entropy of down- and upregulation of gene expression as well as joint entropy. Based on these quantities the uncertainty coefficient was calculated for each gene triplet, following which, separate gene logic networks were constructed for the aerobic and anaerobic conditions. Four structural parameters such as average degree, average clustering coefficient, average shortest path, and average betweenness were used to compare the structure of the corresponding aerobic and anaerobic logic networks. Five genes were identified to be putative key components of the two energy metabolisms. Furthermore, community analysis using the Newman fast algorithm revealed two significant communities for the aerobic but only one for the anaerobic network. David Gene Functional Classification suggests that, under aerobic conditions, one such community reflects the cell cycle and cell replication, while the other one is linked to the mitochondrial respiratory chain function.

  16. RANKL/RANK/MMP-1 molecular triad contributes to the metastatic phenotype of breast and prostate cancer cells in vitro.

    Directory of Open Access Journals (Sweden)

    Sandra Casimiro

    Full Text Available The osteolytic nature of bone metastasis results from a tumor-driven increased bone resorption. Bone remodeling is orchestrated by the molecular triad RANK-RANKL-OPG. This process is dysregulated in bone metastases, mostly via induction of RANKL by tumor-derived factors. These factors increase expression of RANKL, which induce osteoclast formation, function, and survival, thereby increasing bone resorption. RANK is unexpectedly expressed by cancer cells, and the activation of RANKL-RANK pathway correlates with an increased invasive phenotype. To investigate the interaction between RANK expression in human breast and prostate cancer cells and their pro-metastatic phenotype we analyzed the activation of RANKL-RANK pathway and its effects on cell migration, invasion, gene expression in vitro, and osteolysis-inducing ability in vivo. RANKL activates kinase signaling pathways, stimulates cell migration, increases cell invasion, and up-regulates MMP-1 expression. In vivo, MMP-1 knockdown resulted in smaller x-ray osteolytic lesions and osteoclastogenesis, and decreased tumor burden. Therefore, RANKL inhibition in bone metastatic disease may decrease the levels of the osteoclastogenesis inducer MMP-1, contributing to a better clinical outcome.

  17. ConformRank: A conformity-based rank for finding top-k influential users

    Science.gov (United States)

    Wang, Qiyao; Jin, Yuehui; Cheng, Shiduan; Yang, Tan

    2017-05-01

    Finding influential users is a hot topic in social networks. For example, advertisers identify influential users to make a successful campaign. Retweeters forward messages from original users, who originally publish messages. This action is referred to as retweeting. Retweeting behaviors generate influence. Original users have influence on retweeters. Whether retweeters keep the same sentiment as original users is taken into consideration in this study. Influence is calculated based on conformity from emotional perspective after retweeting. A conformity-based algorithm, called ConformRank, is proposed to find top-k influential users, who make the most users keep the same sentiment after retweeting messages. Emotional conformity is introduced to denote how users conform to original users from the emotional perspective. Conforming weights are introduced to denote how two users keep the same sentiment after retweeting messages. Emotional conformity is applied for users and conforming weights are used for relations. Experiments were conducted on Sina Weibo. Experimental results show that users have larger influence when they publish positive messages.

  18. Podium: Ranking Data Using Mixed-Initiative Visual Analytics.

    Science.gov (United States)

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

    2017-08-29

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

  19. Second order analysis of two-stage rank tests for the one-sample problem

    NARCIS (Netherlands)

    Albers, Willem/Wim

    1991-01-01

    In this paper we present a rank analogue to Stein's two-stage procedure. We analyze its behavior to second order using existing asymptotic expansions for fixed sample size rank tests and recent results on combinations of independent rank statistics.

  20. A ranking system for reference libraries of DNA barcodes: application to marine fish species from Portugal.

    Science.gov (United States)

    Costa, Filipe O; Landi, Monica; Martins, Rogelia; Costa, Maria H; Costa, Maria E; Carneiro, Miguel; Alves, Maria J; Steinke, Dirk; Carvalho, Gary R

    2012-01-01

    The increasing availability of reference libraries of DNA barcodes (RLDB) offers the opportunity to the screen the level of consistency in DNA barcode data among libraries, in order to detect possible disagreements generated from taxonomic uncertainty or operational shortcomings. We propose a ranking system to attribute a confidence level to species identifications associated with DNA barcode records from a RLDB. Here we apply the proposed ranking system to a newly generated RLDB for marine fish of Portugal. Specimens (n = 659) representing 102 marine fish species were collected along the continental shelf of Portugal, morphologically identified and archived in a museum collection. Samples were sequenced at the barcode region of the cytochrome oxidase subunit I gene (COI-5P). Resultant DNA barcodes had average intra-specific and inter-specific Kimura-2-parameter distances (0.32% and 8.84%, respectively) within the range usually observed for marine fishes. All specimens were ranked in five different levels (A-E), according to the reliability of the match between their species identification and the respective diagnostic DNA barcodes. Grades A to E were attributed upon submission of individual specimen sequences to BOLD-IDS and inspection of the clustering pattern in the NJ tree generated. Overall, our study resulted in 73.5% of unambiguous species IDs (grade A), 7.8% taxonomically congruent barcode clusters within our dataset, but awaiting external confirmation (grade B), and 18.7% of species identifications with lower levels of reliability (grades C/E). We highlight the importance of implementing a system to rank barcode records in RLDB, in order to flag taxa in need of taxonomic revision, or reduce ambiguities of discordant data. With increasing DNA barcode records publicly available, this cross-validation system would provide a metric of relative accuracy of barcodes, while enabling the continuous revision and annotation required in taxonomic work.

  1. Assessment of University Rankings in the frame of measuring university performance

    OpenAIRE

    Vancauwenbergh, Sadia; Poelmans, Hanne

    2016-01-01

    Since the first publication of the Shanghai ranking, the number of university rankings has been vastly growing. Over the years, this has resulted in wide variety of rankings ranging in their scope, underlying methodologies and indicators used. As university rankings receive extensive media attention, it is crucial that ranking results are interpreted correctly. All too often hasty conclusions are drawn without considering the exact meaning of a particular ranking result. However, this is beco...

  2. A Hybrid Distance-Based Ideal-Seeking Consensus Ranking Model

    OpenAIRE

    Tavana, Madjid; LoPinto, Frank; Smither, James W.

    2007-01-01

    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 differe...

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. Utilization of low rank coal and agricultural by-products

    Energy Technology Data Exchange (ETDEWEB)

    Ekinci, E.; Yardim, M.F.; Petrova, B.; Budinova, T.; Petrov, N. [Istanbul Technical University, Maslak-Istanbul (Turkey). Department of Chemical Engineering

    2007-07-01

    The present investigation deals with alternative utilization processes to convert low rank coal and agricultural by products into solid, liquid and gaseous products for a more efficient exploitation of these materials. Low rank coals and different agricultural by-products were subjected to different thermochemical treatments. The composition and physico-chemical properties of liquid products obtained from agricultural by-products were investigated. The identified compounds are predominantly oxygen derivatives of phenol, dihydroxybenzenes, guaiacol, syringol, vanilin, veratrol, furan and acids. Liquids from low rank coals contain higher quality of aromatic compounds predominantly mono- and bicyclic. The amount of oxygen containing structures is high as well. By thermo-chemical treatment of liquid products from agricultural by-products, low rank coals and their mixtures with H{sub 2}SO{sub 4} carbon adsorbents with very low ash and sulfur content are obtained. Using different activation reagents large scale carbon adsorbents are prepared from agricultural by-products and coals. The results of the investigations open-up possibilities for utilization of low rank coals and agricultural by-products. 18 refs., 5 figs., 7 tabs.

  8. Fast Estimation of Approximate Matrix Ranks Using Spectral Densities.

    Science.gov (United States)

    Ubaru, Shashanka; Saad, Yousef; Seghouane, Abd-Krim

    2017-05-01

    Many machine learning and data-related applications require the knowledge of approximate ranks of large data matrices at hand. This letter presents two computationally inexpensive techniques to estimate the approximate ranks of such matrices. These techniques exploit approximate spectral densities, popular in physics, which are probability density distributions that measure the likelihood of finding eigenvalues of the matrix at a given point on the real line. Integrating the spectral density over an interval gives the eigenvalue count of the matrix in that interval. Therefore, the rank can be approximated by integrating the spectral density over a carefully selected interval. Two different approaches are discussed to estimate the approximate rank, one based on Chebyshev polynomials and the other based on the Lanczos algorithm. In order to obtain the appropriate interval, it is necessary to locate a gap between the eigenvalues that correspond to noise and the relevant eigenvalues that contribute to the matrix rank. A method for locating this gap and selecting the interval of integration is proposed based on the plot of the spectral density. Numerical experiments illustrate the performance of these techniques on matrices from typical applications.

  9. A document clustering and ranking system for exploring MEDLINE citations.

    Science.gov (United States)

    Lin, Yongjing; Li, Wenyuan; Chen, Keke; Liu, Ying

    2007-01-01

    A major problem faced in biomedical informatics involves how best to present information retrieval results. When a single query retrieves many results, simply showing them as a long list often provides poor overview. With a goal of presenting users with reduced sets of relevant citations, this study developed an approach that retrieved and organized MEDLINE citations into different topical groups and prioritized important citations in each group. A text mining system framework for automatic document clustering and ranking organized MEDLINE citations following simple PubMed queries. The system grouped the retrieved citations, ranked the citations in each cluster, and generated a set of keywords and MeSH terms to describe the common theme of each cluster. Several possible ranking functions were compared, including citation count per year (CCPY), citation count (CC), and journal impact factor (JIF). We evaluated this framework by identifying as "important" those articles selected by the Surgical Oncology Society. Our results showed that CCPY outperforms CC and JIF, i.e., CCPY better ranked important articles than did the others. Furthermore, our text clustering and knowledge extraction strategy grouped the retrieval results into informative clusters as revealed by the keywords and MeSH terms extracted from the documents in each cluster. The text mining system studied effectively integrated text clustering, text summarization, and text ranking and organized MEDLINE retrieval results into different topical groups.

  10. Auto insurance fraud detection using unsupervised spectral ranking for anomaly

    Directory of Open Access Journals (Sweden)

    Ke Nian

    2016-03-01

    Full Text Available For many data mining problems, obtaining labels is costly and time consuming, if not practically infeasible. In addition, unlabeled data often includes categorical or ordinal features which, compared with numerical features, can present additional challenges. We propose a new unsupervised spectral ranking method for anomaly (SRA. We illustrate that the spectral optimization in SRA can be viewed as a relaxation of an unsupervised SVM problem. We demonstrate that the first non-principal eigenvector of a Laplacian matrix is linked to a bi-class classification strength measure which can be used to rank anomalies. Using the first non-principal eigenvector of the Laplacian matrix directly, the proposed SRA generates an anomaly ranking either with respect to the majority class or with respect to two main patterns. The choice of the ranking reference can be made based on whether the cardinality of the smaller class (positive or negative is sufficiently large. Using an auto insurance claim data set but ignoring labels when generating ranking, we show that our proposed SRA significantly surpasses existing outlier-based fraud detection methods. Finally we demonstrate that, while proposed SRA yields good performance for a few similarity measures for the auto insurance claim data, notably ones based on the Hamming distance, choosing appropriate similarity measures for a fraud detection problem remains crucial.

  11. 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.

  12. Intergenerational Educational Rank Mobility in 20th Century United States

    DEFF Research Database (Denmark)

    Karlson, Kristian Bernt

    2015-01-01

    in the overall schooling distribution both over time and among population groups defined by race and gender.METHODS & DATA: To analyze educational rank mobility, I use quantile transition matrices known from studies on intergenerational income mobility. However, because schooling distributions are quite lumpy......BACKGROUND: Studies of educational mobility in the United States report widespread persistence in the association between parental and offspring schooling over most of the 20th century. Despite this apparent persistency, many other studies report substantial improvements in the educational...... performance of historically disadvantaged groups. To reconcile these diverging trends, I propose examining educational mobility in terms of percentile ranks in the respective schooling distributions of parents and offspring. Using a novel estimator of educational rank, I compare patterns of mobility...

  13. An Improved Approach to the PageRank Problems

    Directory of Open Access Journals (Sweden)

    Yue Xie

    2013-01-01

    Full Text Available We introduce a partition of the web pages particularly suited to the PageRank problems in which the web link graph has a nested block structure. Based on the partition of the web pages, dangling nodes, common nodes, and general nodes, the hyperlink matrix can be reordered to be a more simple block structure. Then based on the parallel computation method, we propose an algorithm for the PageRank problems. In this algorithm, the dimension of the linear system becomes smaller, and the vector for general nodes in each block can be calculated separately in every iteration. Numerical experiments show that this approach speeds up the computation of PageRank.

  14. Publication Anxiety, Quality, and Journal Rankings: Researcher Views

    Directory of Open Access Journals (Sweden)

    Darryl Coulthard

    2016-10-01

    Full Text Available Journal ranking systems are increasingly used to measure research performance of academics and universities. A growing number of academic commentators have voiced concerns of possible undesirable outcomes such as increased publication anxiety and an increase in safe and conforming research, but there have been few empirical studies on the possible effects. To address this gap, we surveyed Information Systems (IS academics who published in one of three key IS conferences in 2013, to gather their views of the effects of journal ranking systems. Overall, we found that the concerns in the literature were strongly reflected in the views of those surveyed. Academics believe the system has greatly increased their publication anxiety. While most believed that the quality of published research had improved, researchers believe the ranking systems inhibit innovative, risky research, and encourages safe, conforming, mainstream research.

  15. THE USE OF RANKING SAMPLING METHOD WITHIN MARKETING RESEARCH

    Directory of Open Access Journals (Sweden)

    CODRUŢA DURA

    2011-01-01

    Full Text Available Marketing and statistical literature available to practitioners provides a wide range of sampling methods that can be implemented in the context of marketing research. Ranking sampling method is based on taking apart the general population into several strata, namely into several subdivisions which are relatively homogenous regarding a certain characteristic. In fact, the sample will be composed by selecting, from each stratum, a certain number of components (which can be proportional or non-proportional to the size of the stratum until the pre-established volume of the sample is reached. Using ranking sampling within marketing research requires the determination of some relevant statistical indicators - average, dispersion, sampling error etc. To that end, the paper contains a case study which illustrates the actual approach used in order to apply the ranking sample method within a marketing research made by a company which provides Internet connection services, on a particular category of customers – small and medium enterprises.

  16. Fuzzy logic and its application in football team ranking.

    Science.gov (United States)

    Zeng, Wenyi; Li, Junhong

    2014-01-01

    Fuzzy set theory and fuzzy logic are a highly suitable and applicable basis for developing knowledge-based systems in physical education for tasks such as the selection for athletes, the evaluation for different training approaches, the team ranking, and the real-time monitoring of sports data. In this paper, we use fuzzy set theory and apply fuzzy clustering analysis in football team ranking. Based on some certain rules, we propose four parameters to calculate fuzzy similar matrix, obtain fuzzy equivalence matrix and the ranking result for our numerical example, T 7, T 3, T 1, T 9, T 10, T 8, T 11, T 12, T 2, T 6, T 5, T 4, and investigate four parameters sensitivity analysis. The study shows that our fuzzy logic method is reliable and stable when the parameters change in certain range.

  17. Using Bibliographic Knowledge for Ranking in Scientific Publication Databases

    CERN Document Server

    Vesely, Martin; Le Meur, Jean-Yves

    2008-01-01

    Document ranking for scientific publications involves a variety of specialized resources (e.g. author or citation indexes) that are usually difficult to use within standard general purpose search engines that usually operate on large-scale heterogeneous document collections for which the required specialized resources are not always available for all the documents present in the collections. Integrating such resources into specialized information retrieval engines is therefore important to cope with community-specific user expectations that strongly influence the perception of relevance within the considered community. In this perspective, this paper extends the notion of ranking with various methods exploiting different types of bibliographic knowledge that represent a crucial resource for measuring the relevance of scientific publications. In our work, we experimentally evaluated the adequacy of two such ranking methods (one based on freshness, i.e. the publication date, and the other on a novel index, the ...

  18. A new DEA approach to rank alternatives in MCDA

    Directory of Open Access Journals (Sweden)

    Majid Darehmiraki

    2013-04-01

    Full Text Available One of the principal subjects in multiple criteria decision analysis is ranking alternatives. Here, we present a new method to rank alternatives by using data envelopment analysis. In this paper, one ranking method is proposed based on applying an artificial alternative called aggregate alternative. The method is based on the fact that one efficient alternative with a better performance has stronger effects on the group of other alternatives. That means its deletion forces the remaining alternatives to get smaller efficiency. The described idea in this paper is inspired of Lotfi and et al. (2011. One feature of the proposed method is that it does not need to determine the weight of the prior. Two examples are used to illustrate how the proposed method works in actual practices, and the results are compared with those obtained from the TOPSIS method.

  19. International Conference on Robust Rank-Based and Nonparametric Methods

    CERN Document Server

    McKean, Joseph

    2016-01-01

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

  20. Ranking influential nodes in complex networks with structural holes

    Science.gov (United States)

    Hu, Ping; Mei, Ting

    2018-01-01

    Ranking influential nodes in complex networks is of great theoretical and practical significance to ensure the safe operations of networks. In view of the important role structural hole nodes usually play in information spreading in complex networks, we propose a novel ranking method of influential nodes using structural holes called E-Burt method, which can be applied to weighted networks. This method fully takes into account the total connectivity strengths of the node in its local scope, the number of the connecting edges and the distributions of the total connectivity strengths on its connecting edges. The simulation results on the susceptible-infectious-recovered (SIR) dynamics suggest that the proposed E-Burt method can rank influential nodes more effectively and accurately in complex networks.

  1. Joint Sport Classification of Ukraine and ranking standards in powerlifting

    Directory of Open Access Journals (Sweden)

    Stetsenko A.I.

    2010-01-01

    Full Text Available Realization of motion potential of a human happens more often in the process of his competitive activity. Criteria for the assessment of such activity's success are sport trophies (medals, cups, certificates, diplomas and correspondence of competitive results to sport ranks and categories. Joint sport classification of Ukraine is an important regulatory enactment of the physical education and sports sphere of country's life activity, that's why requirements and regulations of sport ranks and categories conferment require scientific-pragmatic approach. Performance of powerlifters, who are divided into weight categories, has progressive and advanced character. These and other factories complicate solving of the problem according the definition of logical algorithm of the table forming of ranking standards.

  2. Ranking Technology Forecasting Journals by Using Data Envelopment Analysis

    Directory of Open Access Journals (Sweden)

    Jasna Petković

    2015-05-01

    Full Text Available The goal of this paper is to present the ranking of the journals in the field of technology forecasting (TF through the application of the Data Envelopment Analysis - DEA. Over the past four decades, we have witnessed a rapid development in the field of technology forecasting. This development, both in theory and in practice, has been fuelled by the increase in complexity, even greater competition, and rapid changes in the business environment. Back in the past, little attention was paid to the importance and conceptual development in the field of TF, which caused numerous overlaps of the forms of TF development and its influence. The changes that have resulted in the emergence of information technology and modern manufacturing technology have actually increased the need for application of technology forecasting, as well as for explosive growth in scientific and engineering literature worldwide. The paper shows the ranking of 39 journals in the field of TF over the period from 1999 to 2011 through the application of the Data Envelopment Analysis, as well as through analyzing trend changes in publishing professional publications in the field of technology forecasting. Also pointed out are the shortcomings ofprevious methods of ranking journals by using impact factors, as one of the most important indicators of the quality of journals, as well as the possibilities of applying indicators obtained by using other methodologies. The results of such method of ranking should point out to publishing trends to the researchers engaged in this field, and direct them to journals in which they could present the results of their research. The aim of this research is to show that more than one criterion must be taken in order to create the rank of a journal from a specific area. In this way we get a more realistic ranking of leading journals from the observed area, since other necessary elements that contribute to the importance of a journal for a relevant

  3. LANL environmental restoration site ranking system: System description. Final report

    Energy Technology Data Exchange (ETDEWEB)

    Merkhofer, L.; Kann, A.; Voth, M. [Applied Decision Analysis, Inc., Menlo Park, CA (United States)

    1992-10-13

    The basic structure of the LANL Environmental Restoration (ER) Site Ranking System and its use are described in this document. A related document, Instructions for Generating Inputs for the LANL ER Site Ranking System, contains detailed descriptions of the methods by which necessary inputs for the system will be generated. LANL has long recognized the need to provide a consistent basis for comparing the risks and other adverse consequences associated with the various waste problems at the Lab. The LANL ER Site Ranking System is being developed to help address this need. The specific purpose of the system is to help improve, defend, and explain prioritization decisions at the Potential Release Site (PRS) and Operable Unit (OU) level. The precise relationship of the Site Ranking System to the planning and overall budget processes is yet to be determined, as the system is still evolving. Generally speaking, the Site Ranking System will be used as a decision aid. That is, the system will be used to aid in the planning and budgetary decision-making process. It will never be used alone to make decisions. Like all models, the system can provide only a partial and approximate accounting of the factors important to budget and planning decisions. Decision makers at LANL will have to consider factors outside of the formal system when making final choices. Some of these other factors are regulatory requirements, DOE policy, and public concern. The main value of the site ranking system, therefore, is not the precise numbers it generates, but rather the general insights it provides.

  4. Prevalence of polymorphisms in OPG, RANKL and RANK as potential markers for Charcot arthropathy development.

    Science.gov (United States)

    Bruhn-Olszewska, Bożena; Korzon-Burakowska, Anna; Węgrzyn, Grzegorz; Jakóbkiewicz-Banecka, Joanna

    2017-03-29

    Charcot arthropathy is one of the most serious complications of diabetic foot syndrome that leads to amputation of the affected limb. Since there is no cure for Charcot arthropathy, early diagnosis and implementation preventive care are the best available treatment. However, diagnosis is hindered by obscure clinical picture of the disease and lack of molecular markers for its early detection. Results of recent research suggest that OPG-RANKL-RANK axis regulating bone metabolism can be associated with Charcot arthropathy and that SNPs in OPG gene are associated with the disease. Here we report the results of comprehensive analysis of ten SNPs in OPG, RANKL and RANK genes in 260 subjects divided into diabetes, neuropathy and Charcot arthropathy groups. Besides genotype analysis we performed linkage disequilibrium and hierarchical clustering to obtain information about correlation between SNPs. Our results show that OPG 245T/G (rs3134069) and OPG 1217C/T (rs3102734) polymorphisms co-occur in patients with Charcot arthropathy (r2 = 0.99). Moreover, hierarchical clustering revealed a characteristic profile of all SNPs in Charcot arthropathy and neuropathy, which is distinct from control group. Our results suggest that analysis of multiple SNPs can be used as potential marker of Charcot arthropathy and provide insight into possible molecular mechanisms of its development.

  5. PageRank model of opinion formation on Ulam networks

    Science.gov (United States)

    Chakhmakhchyan, L.; Shepelyansky, D.

    2013-12-01

    We consider a PageRank model of opinion formation on Ulam networks, generated by the intermittency map and the typical Chirikov map. The Ulam networks generated by these maps have certain similarities with such scale-free networks as the World Wide Web (WWW), showing an algebraic decay of the PageRank probability. We find that the opinion formation process on Ulam networks has certain similarities but also distinct features comparing to the WWW. We attribute these distinctions to internal differences in network structure of the Ulam and WWW networks. We also analyze the process of opinion formation in the frame of generalized Sznajd model which protects opinion of small communities.

  6. Enhancing Invenio Digital Library With An External Relevance Ranking Engine

    CERN Document Server

    Glauner, Patrick Oliver

    Invenio is a comprehensive web-based free digital library software suite originally developed at CERN. In order to improve its information retrieval and word similarity ranking capabilities, the goal of this thesis is to enhance Invenio by bridging it with modern external information retrieval systems. In the first part a comparison of various information retrieval systems such as Solr and Xapian is made. In the second part a system-independent bridge for word similarity ranking is designed and implemented. Subsequently, Solr and Xapian are integrated in Invenio via adapters to the bridge. In the third part scalability tests are performed. Finally, a future outlook is briefly discussed.

  7. Ranking Performance Measures in Multi-Task Agencies

    DEFF Research Database (Denmark)

    Christensen, Peter Ove; Sabac, Florin; Tian, Joyce

    2010-01-01

    We derive sufficient conditions for ranking performance evaluation systems in multi-task agency models (using both optimal and linear contracts) in terms of a second-order stochastic dominance (SSD) condition on the likelihood ratios. The SSD condition can be replaced by a variance-covariance mat......We derive sufficient conditions for ranking performance evaluation systems in multi-task agency models (using both optimal and linear contracts) in terms of a second-order stochastic dominance (SSD) condition on the likelihood ratios. The SSD condition can be replaced by a variance...

  8. Adaptive Game Level Creation through Rank-based Interactive Evolution

    DEFF Research Database (Denmark)

    Liapis, Antonios; Martínez, Héctor Pérez; Togelius, Julian

    2013-01-01

    This paper introduces Rank-based Interactive Evolution (RIE) which is an alternative to interactive evolution driven by computational models of user preferences to generate personalized content. In RIE, the computational models are adapted to the preferences of users which, in turn, are used...... as fitness functions for the optimization of the generated content. The preference models are built via ranking-based preference learning, while the content is generated via evolutionary search. The proposed method is evaluated on the creation of strategy game maps, and its performance is tested using...

  9. Low-rank and sparse modeling for visual analysis

    CERN Document Server

    Fu, Yun

    2014-01-01

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

  10. 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

  11. MacWilliams Identity for Codes with the Rank Metric

    Directory of Open Access Journals (Sweden)

    Zhiyuan Yan

    2008-05-01

    Full Text Available The MacWilliams identity, which relates the weight distribution of a code to the weight distribution of its dual code, is useful in determining the weight distribution of codes. In this paper, we derive the MacWilliams identity for linear codes with the rank metric, and our identity has a different form than that by Delsarte. Using our MacWilliams identity, we also derive related identities for rank metric codes. These identities parallel the binomial and power moment identities derived for codes with the Hamming metric.

  12. MacWilliams Identity for Codes with the Rank Metric

    Directory of Open Access Journals (Sweden)

    Gadouleau Maximilien

    2008-01-01

    Full Text Available Abstract The MacWilliams identity, which relates the weight distribution of a code to the weight distribution of its dual code, is useful in determining the weight distribution of codes. In this paper, we derive the MacWilliams identity for linear codes with the rank metric, and our identity has a different form than that by Delsarte. Using our MacWilliams identity, we also derive related identities for rank metric codes. These identities parallel the binomial and power moment identities derived for codes with the Hamming metric.

  13. Ranking transitive chemical-disease inferences using local network topology in the comparative toxicogenomics database.

    Science.gov (United States)

    King, Benjamin L; Davis, Allan Peter; Rosenstein, Michael C; Wiegers, Thomas C; Mattingly, Carolyn J

    2012-01-01

    Exposure to chemicals in the environment is believed to play a critical role in the etiology of many human diseases. To enhance understanding about environmental effects on human health, the Comparative Toxicogenomics Database (CTD; http://ctdbase.org) provides unique curated data that enable development of novel hypotheses about the relationships between chemicals and diseases. CTD biocurators read the literature and curate direct relationships between chemicals-genes, genes-diseases, and chemicals-diseases. These direct relationships are then computationally integrated to create additional inferred relationships; for example, a direct chemical-gene statement can be combined with a direct gene-disease statement to generate a chemical-disease inference (inferred via the shared gene). In CTD, the number of inferences has increased exponentially as the number of direct chemical, gene and disease interactions has grown. To help users navigate and prioritize these inferences for hypothesis development, we implemented a statistic to score and rank them based on the topology of the local network consisting of the chemical, disease and each of the genes used to make an inference. In this network, chemicals, diseases and genes are nodes connected by edges representing the curated interactions. Like other biological networks, node connectivity is an important consideration when evaluating the CTD network, as the connectivity of nodes follows the power-law distribution. Topological methods reduce the influence of highly connected nodes that are present in biological networks. We evaluated published methods that used local network topology to determine the reliability of protein-protein interactions derived from high-throughput assays. We developed a new metric that combines and weights two of these methods and uniquely takes into account the number of common neighbors and the connectivity of each entity involved. We present several CTD inferences as case studies to

  14. Ranking transitive chemical-disease inferences using local network topology in the comparative toxicogenomics database.

    Directory of Open Access Journals (Sweden)

    Benjamin L King

    Full Text Available Exposure to chemicals in the environment is believed to play a critical role in the etiology of many human diseases. To enhance understanding about environmental effects on human health, the Comparative Toxicogenomics Database (CTD; http://ctdbase.org provides unique curated data that enable development of novel hypotheses about the relationships between chemicals and diseases. CTD biocurators read the literature and curate direct relationships between chemicals-genes, genes-diseases, and chemicals-diseases. These direct relationships are then computationally integrated to create additional inferred relationships; for example, a direct chemical-gene statement can be combined with a direct gene-disease statement to generate a chemical-disease inference (inferred via the shared gene. In CTD, the number of inferences has increased exponentially as the number of direct chemical, gene and disease interactions has grown. To help users navigate and prioritize these inferences for hypothesis development, we implemented a statistic to score and rank them based on the topology of the local network consisting of the chemical, disease and each of the genes used to make an inference. In this network, chemicals, diseases and genes are nodes connected by edges representing the curated interactions. Like other biological networks, node connectivity is an important consideration when evaluating the CTD network, as the connectivity of nodes follows the power-law distribution. Topological methods reduce the influence of highly connected nodes that are present in biological networks. We evaluated published methods that used local network topology to determine the reliability of protein-protein interactions derived from high-throughput assays. We developed a new metric that combines and weights two of these methods and uniquely takes into account the number of common neighbors and the connectivity of each entity involved. We present several CTD inferences as case

  15. Zipf rank approach and cross-country convergence of incomes

    Science.gov (United States)

    Shao, Jia; Ivanov, Plamen Ch.; Urošević, Branko; Stanley, H. Eugene; Podobnik, Boris

    2011-05-01

    We employ a concept popular in physics —the Zipf rank approach— in order to estimate the number of years that EU members would need in order to achieve "convergence" of their per capita incomes. Assuming that trends in the past twenty years continue to hold in the future, we find that after t≈30 years both developing and developed EU countries indexed by i will have comparable values of their per capita gross domestic product {\\cal G}_{i,t} . Besides the traditional Zipf rank approach we also propose a weighted Zipf rank method. In contrast to the EU block, on the world level the Zipf rank approach shows that, between 1960 and 2009, cross-country income differences increased over time. For a brief period during the 2007-2008 global economic crisis, at world level the {\\cal G}_{i,t} of richer countries declined more rapidly than the {\\cal G}_{i,t} of poorer countries, in contrast to EU where the {\\cal G}_{i,t} of developing EU countries declined faster than the {\\cal G}_{i,t} of developed EU countries, indicating that the recession interrupted the convergence between EU members. We propose a simple model of GDP evolution that accounts for the scaling we observe in the data.

  16. On the Schwartz space isomorphism theorem for rank one ...

    Indian Academy of Sciences (India)

    Abstract. In this paper we give a simpler proof of the Lp-Schwartz space isomorphism. (0 < p ≤ 2) under the Fourier transform for the class of functions of left δ-type on a. Riemannian symmetric space of rank one. Our treatment rests on Anker's [2] proof of the corresponding result in the case of left K-invariant functions on X.

  17. Systematic Weighting and Ranking: Cutting the Gordian Knot.

    Science.gov (United States)

    Davis, Charles H.; McKim, Geoffrey W.

    1999-01-01

    Describes SWEAR (Systematic Weighting and Ranking), a powers-of-two algorithm that can be used for searching the World Wide Web or any large database that automatically creates discrete, well-defined result sets and displays them in decreasing order of likely relevance. Also discusses fuzzy sets. (Author/LRW)

  18. 10 CFR 455.131 - State ranking of grant applications.

    Science.gov (United States)

    2010-01-01

    ... energy conservation potential, on a savings percentage basis, of the building as determined in the energy... basis, several buildings may be ranked as a single building if the application proposes a single energy... State Plan; (3) The types of energy sources to which conversion is proposed, including renewable energy...

  19. 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.

  20. First rank symptoms: concepts and diagnostic utility | Saddichha ...

    African Journals Online (AJOL)

    First Rank Symptoms (FRS) were first defined by Schneider as diagnostic of schizophrenia. Since then, there has been an immense debate on their diagnostic and prognostic utility. This review attempts to understand the concepts of FRS as depicted over the years and the diagnostic and prognostic implications of FRS in ...