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Sample records for rank percentile method

  1. A Comparison of Three Conditional Growth Percentile Methods: Student Growth Percentiles, Percentile Rank Residuals, and a Matching Method

    ERIC Educational Resources Information Center

    Wyse, Adam E.; Seo, Dong Gi

    2014-01-01

    This article provides a brief overview and comparison of three conditional growth percentile methods; student growth percentiles, percentile rank residuals, and a nonparametric matching method. These approaches seek to describe student growth in terms of the relative percentile ranking of a student in relationship to students that had the same…

  2. Tutorial: Calculating Percentile Rank and Percentile Norms Using SPSS

    ERIC Educational Resources Information Center

    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…

  3. Percentile Ranking and Citation Impact of a Large Cohort of NHLBI-funded Cardiovascular R01 Grants

    PubMed Central

    Danthi, Narasimhan; Wu, Colin O.; Shi, Peibei; Lauer, Michael

    2014-01-01

    Rationale Funding decisions for cardiovascular R01 grant applications at NHLBI largely hinge on percentile rankings. It is not known whether this approach enables the highest impact science. Objective To conduct an observational analysis of percentile rankings and bibliometric outcomes for a contemporary set of funded NHLBI cardiovascular R01 grants. Methods and results We identified 1492 investigator-initiated de novo R01 grant applications that were funded between 2001 and 2008, and followed their progress for linked publications and citations to those publications. Our co-primary endpoints were citations received per million dollars of funding, citations obtained within 2-years of publication, and 2-year citations for each grant’s maximally cited paper. In 7654 grant-years of funding that generated $3004 million of total NIH awards, the portfolio yielded 16,793 publications that appeared between 2001 and 2012 (median per grant 8, 25th and 75th percentiles 4 and 14, range 0 – 123), which received 2,224,255 citations (median per grant 1048, 25th and 75th percentiles 492 and 1,932, range 0 – 16,295). We found no association between percentile ranking and citation metrics; the absence of association persisted even after accounting for calendar time, grant duration, number of grants acknowledged per paper, number of authors per paper, early investigator status, human versus non-human focus, and institutional funding. An exploratory machine-learning analysis suggested that grants with the very best percentile rankings did yield more maximally cited papers. Conclusions In a large cohort of NHLBI-funded cardiovascular R01 grants, we were unable to find a monotonic association between better percentile ranking and higher scientific impact as assessed by citation metrics. PMID:24406983

  4. Standard Errors of Equating for the Percentile Rank-Based Equipercentile Equating with Log-Linear Presmoothing

    ERIC Educational Resources Information Center

    Wang, Tianyou

    2009-01-01

    Holland and colleagues derived a formula for analytical standard error of equating using the delta-method for the kernel equating method. Extending their derivation, this article derives an analytical standard error of equating procedure for the conventional percentile rank-based equipercentile equating with log-linear smoothing. This procedure is…

  5. Recurrent fuzzy ranking methods

    NASA Astrophysics Data System (ADS)

    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.

  6. Attempt for percentile analysis of food colorants with photoacoustic method

    NASA Astrophysics Data System (ADS)

    Coelho, T. M.; Vidotti, E. C.; Rollemberg, M. C. E.; Baesso, M. L.; Bento, A. C.

    2005-06-01

    In this work the photoacoustic (PAS) method is applied in polyester-type polyurethane foam (PUF) doped with food colorants. Aiming to resolve binary mixtures of synthetic colorants such as Sunset Yellow, Tartrazine, Brilliant Blue and Amaranth, a single spectroscopic method is described. Based upon individual spectra, a Gaussian deconvolution is used and the fraction of each colorant is found.

  7. Statewide Analysis of the Drainage-Area Ratio Method for 34 Streamflow Percentile Ranges in Texas

    USGS Publications Warehouse

    Asquith, William H.; Roussel, Meghan C.; Vrabel, Joseph

    2006-01-01

    The drainage-area ratio method commonly is used to estimate streamflow for sites where no streamflow data are available using data from one or more nearby streamflow-gaging stations. The method is intuitive and straightforward to implement and is in widespread use by analysts and managers of surface-water resources. The method equates the ratio of streamflow at two stream locations to the ratio of the respective drainage areas. In practice, unity often is assumed as the exponent on the drainage-area ratio, and unity also is assumed as a multiplicative bias correction. These two assumptions are evaluated in this investigation through statewide analysis of daily mean streamflow in Texas. The investigation was made by the U.S. Geological Survey in cooperation with the Texas Commission on Environmental Quality. More than 7.8 million values of daily mean streamflow for 712 U.S. Geological Survey streamflow-gaging stations in Texas were analyzed. To account for the influence of streamflow probability on the drainage-area ratio method, 34 percentile ranges were considered. The 34 ranges are the 4 quartiles (0-25, 25-50, 50-75, and 75-100 percent), the 5 intervals of the lower tail of the streamflow distribution (0-1, 1-2, 2-3, 3-4, and 4-5 percent), the 20 quintiles of the 4 quartiles (0-5, 5-10, 10-15, 15-20, 20-25, 25-30, 30-35, 35-40, 40-45, 45-50, 50-55, 55-60, 60-65, 65-70, 70-75, 75-80, 80-85, 85-90, 90-95, and 95-100 percent), and the 5 intervals of the upper tail of the streamflow distribution (95-96, 96-97, 97-98, 98-99 and 99-100 percent). For each of the 253,116 (712X711/2) unique pairings of stations and for each of the 34 percentile ranges, the concurrent daily mean streamflow values available for the two stations provided for station-pair application of the drainage-area ratio method. For each station pair, specific statistical summarization (median, mean, and standard deviation) of both the exponent and bias-correction components of the drainage-area ratio

  8. Association of percentile ranking with citation impact and productivity in a large cohort of de novo NIMH-funded R01 grants.

    PubMed

    Doyle, J M; Quinn, K; Bodenstein, Y A; Wu, C O; Danthi, N; Lauer, M S

    2015-09-01

    Previous reports from National Institutes of Health and National Science Foundation have suggested that peer review scores of funded grants bear no association with grant citation impact and productivity. This lack of association, if true, may be particularly concerning during times of increasing competition for increasingly limited funds. We analyzed the citation impact and productivity for 1755 de novo investigator-initiated R01 grants funded for at least 2 years by National Institute of Mental Health between 2000 and 2009. Consistent with previous reports, we found no association between grant percentile ranking and subsequent productivity and citation impact, even after accounting for subject categories, years of publication, duration and amounts of funding, as well as a number of investigator-specific measures. Prior investigator funding and academic productivity were moderately strong predictors of grant citation impact. PMID:26033238

  9. A Rational Method for Ranking Engineering Programs.

    ERIC Educational Resources Information Center

    Glower, Donald D.

    1980-01-01

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

  10. Augmenting the Deliberative Method for Ranking Risks.

    PubMed

    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. PMID:26224206

  11. Fuzzy Multicriteria Ranking of Aluminium Coating Methods

    NASA Astrophysics Data System (ADS)

    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.

  12. Image Quality Ranking Method for Microscopy.

    PubMed

    Koho, Sami; Fazeli, Elnaz; Eriksson, John E; Hänninen, Pekka E

    2016-01-01

    Automated analysis of microscope images is necessitated by the increased need for high-resolution follow up of events in time. Manually finding the right images to be analyzed, or eliminated from data analysis are common day-to-day problems in microscopy research today, and the constantly growing size of image datasets does not help the matter. We propose a simple method and a software tool for sorting images within a dataset, according to their relative quality. We demonstrate the applicability of our method in finding good quality images in a STED microscope sample preparation optimization image dataset. The results are validated by comparisons to subjective opinion scores, as well as five state-of-the-art blind image quality assessment methods. We also show how our method can be applied to eliminate useless out-of-focus images in a High-Content-Screening experiment. We further evaluate the ability of our image quality ranking method to detect out-of-focus images, by extensive simulations, and by comparing its performance against previously published, well-established microscopy autofocus metrics. PMID:27364703

  13. Image Quality Ranking Method for Microscopy

    PubMed Central

    Koho, Sami; Fazeli, Elnaz; Eriksson, John E.; Hänninen, Pekka E.

    2016-01-01

    Automated analysis of microscope images is necessitated by the increased need for high-resolution follow up of events in time. Manually finding the right images to be analyzed, or eliminated from data analysis are common day-to-day problems in microscopy research today, and the constantly growing size of image datasets does not help the matter. We propose a simple method and a software tool for sorting images within a dataset, according to their relative quality. We demonstrate the applicability of our method in finding good quality images in a STED microscope sample preparation optimization image dataset. The results are validated by comparisons to subjective opinion scores, as well as five state-of-the-art blind image quality assessment methods. We also show how our method can be applied to eliminate useless out-of-focus images in a High-Content-Screening experiment. We further evaluate the ability of our image quality ranking method to detect out-of-focus images, by extensive simulations, and by comparing its performance against previously published, well-established microscopy autofocus metrics. PMID:27364703

  14. Image Quality Ranking Method for Microscopy

    NASA Astrophysics Data System (ADS)

    Koho, Sami; Fazeli, Elnaz; Eriksson, John E.; Hänninen, Pekka E.

    2016-07-01

    Automated analysis of microscope images is necessitated by the increased need for high-resolution follow up of events in time. Manually finding the right images to be analyzed, or eliminated from data analysis are common day-to-day problems in microscopy research today, and the constantly growing size of image datasets does not help the matter. We propose a simple method and a software tool for sorting images within a dataset, according to their relative quality. We demonstrate the applicability of our method in finding good quality images in a STED microscope sample preparation optimization image dataset. The results are validated by comparisons to subjective opinion scores, as well as five state-of-the-art blind image quality assessment methods. We also show how our method can be applied to eliminate useless out-of-focus images in a High-Content-Screening experiment. We further evaluate the ability of our image quality ranking method to detect out-of-focus images, by extensive simulations, and by comparing its performance against previously published, well-established microscopy autofocus metrics.

  15. A Ranking Method for Evaluating Constructed Responses

    ERIC Educational Resources Information Center

    Attali, Yigal

    2014-01-01

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

  16. Application of Radial Basis Function Methods in the Development of a 95th Percentile Male Seated FEA Model.

    PubMed

    Vavalle, Nicholas A; Schoell, Samantha L; Weaver, Ashley A; Stitzel, Joel D; Gayzik, F Scott

    2014-11-01

    Human body finite element models (FEMs) are a valuable tool in the study of injury biomechanics. However, the traditional model development process can be time-consuming. Scaling and morphing an existing FEM is an attractive alternative for generating morphologically distinct models for further study. The objective of this work is to use a radial basis function to morph the Global Human Body Models Consortium (GHBMC) average male model (M50) to the body habitus of a 95th percentile male (M95) and to perform validation tests on the resulting model. The GHBMC M50 model (v. 4.3) was created using anthropometric and imaging data from a living subject representing a 50th percentile male. A similar dataset was collected from a 95th percentile male (22,067 total images) and was used in the morphing process. Homologous landmarks on the reference (M50) and target (M95) geometries, with the existing FE node locations (M50 model), were inputs to the morphing algorithm. The radial basis function was applied to morph the FE model. The model represented a mass of 103.3 kg and contained 2.2 million elements with 1.3 million nodes. Simulations of the M95 in seven loading scenarios were presented ranging from a chest pendulum impact to a lateral sled test. The morphed model matched anthropometric data to within a rootmean square difference of 4.4% while maintaining element quality commensurate to the M50 model and matching other anatomical ranges and targets. The simulation validation data matched experimental data well in most cases. PMID:26192960

  17. Can Percentiles Replace Raw Scores in the Statistical Analysis of Test Data?

    ERIC Educational Resources Information Center

    Zimmerman, Donald W.; Zumbo, Bruno D.

    2005-01-01

    Educational and psychological testing textbooks typically warn of the inappropriateness of performing arithmetic operations and statistical analysis on percentiles instead of raw scores. This seems inconsistent with the well-established finding that transforming scores to ranks and using nonparametric methods often improves the validity and power…

  18. Bayes method for low rank tensor estimation

    NASA Astrophysics Data System (ADS)

    Suzuki, Taiji; Kanagawa, Heishiro

    2016-03-01

    We investigate the statistical convergence rate of a Bayesian low-rank tensor estimator, and construct a Bayesian nonlinear tensor estimator. The problem setting is the regression problem where the regression coefficient forms a tensor structure. This problem setting occurs in many practical applications, such as collaborative filtering, multi-task learning, and spatio-temporal data analysis. The convergence rate of the Bayes tensor estimator is analyzed in terms of both in-sample and out-of-sample predictive accuracies. It is shown that a fast learning rate is achieved without any strong convexity of the observation. Moreover, we extend the tensor estimator to a nonlinear function estimator so that we estimate a function that is a tensor product of several functions.

  19. Alternative Statistical Frameworks for Student Growth Percentile Estimation

    ERIC Educational Resources Information Center

    Lockwood, J. R.; Castellano, Katherine E.

    2015-01-01

    This article suggests two alternative statistical approaches for estimating student growth percentiles (SGP). The first is to estimate percentile ranks of current test scores conditional on past test scores directly, by modeling the conditional cumulative distribution functions, rather than indirectly through quantile regressions. This would…

  20. Diagrammatic perturbation methods in networks and sports ranking combinatorics

    NASA Astrophysics Data System (ADS)

    Park, Juyong

    2010-04-01

    Analytic and computational tools developed in statistical physics are being increasingly applied to the study of complex networks. Here we present recent developments in the diagrammatic perturbation methods for the exponential random graph models, and apply them to the combinatoric problem of determining the ranking of nodes in directed networks that represent pairwise competitions.

  1. Network Selection: A Method for Ranked Lists Selection

    PubMed Central

    Figini, Silvia

    2012-01-01

    We consider the problem of finding the set of rankings that best represents a given group of orderings on the same collection of elements (preference lists). This problem arises from social choice and voting theory, in which each voter gives a preference on a set of alternatives, and a system outputs a single preference order based on the observed voters’ preferences. In this paper, we observe that, if the given set of preference lists is not homogeneous, a unique true underling ranking might not exist. Moreover only the lists that share the highest amount of information should be aggregated, and thus multiple rankings might provide a more feasible solution to the problem. In this light, we propose Network Selection, an algorithm that, given a heterogeneous group of rankings, first discovers the different communities of homogeneous rankings and then combines only the rank orderings belonging to the same community into a single final ordering. Our novel approach is inspired by graph theory; indeed our set of lists can be loosely read as the nodes of a network. As a consequence, only the lists populating the same community in the network would then be aggregated. In order to highlight the strength of our proposal, we show an application both on simulated and on two real datasets, namely a financial and a biological dataset. Experimental results on simulated data show that Network Selection can significantly outperform existing related methods. The other way around, the empirical evidence achieved on real financial data reveals that Network Selection is also able to select the most relevant variables in data mining predictive models, providing a clear superiority in terms of predictive power of the models built. Furthermore, we show the potentiality of our proposal in the bioinformatics field, providing an application to a biological microarray dataset. PMID:22937075

  2. The Consistency and Ranking Method Based on Comparison Linguistic Variable

    NASA Astrophysics Data System (ADS)

    Zhao, Qisheng; Wei, Fajie; Zhou, Shenghan

    The study developed a consistency approximation and ranking method based on the comparison Linguistic variable. The method constructs the consistency fuzzy complementary judgment matrix by using the judgment matrix of linguistic variable. The judgment matrix is defined by the fuzzy set or vague set of comparison linguistic variable. The method obtains the VPIS and VNIS based on TOPSIS method. And the relative similar approach degrees with the distance between alternatives and VPIS or VNIS are defined. Then the study analyzes the impact on quality of evaluation which caused by evaluation method, index weight and appraiser. Finally, the improving methods were discussed, and an example is presented to illustrate the proposed method.

  3. The use of the percentile method for searching empirical relationships between compression strength (UCS), Point Load (Is50) and Schmidt Hammer (RL) Indices

    NASA Astrophysics Data System (ADS)

    Bruno, Giovanni; Bobbo, Luigi; Vessia, Giovanna

    2014-05-01

    Is50 and RL indices are commonly used to indirectly estimate the compression strength of a rocky deposit by in situ and in laboratory devices. The widespread use of Point load and Schmidt hammer tests is due to the simplicity and the speediness of the execution of these tests. Their indices can be related to the UCS by means of the ordinary least square regression analyses. Several researchers suggest to take into account the lithology to build high correlated empirical expressions (R2 >0.8) to draw UCS from Is50 or RL values. Nevertheless, the lower and upper bounds of the UCS ranges of values that can be estimated by means of the two indirect indices are not clearly defined yet. Aydin (2009) stated that the Schmidt hammer test shall be used to assess the compression resistance of rocks characterized by UCS>12-20 MPa. On the other hand, the Point load measures can be performed on weak rocks but upper bound values for UCS are not suggested. In this paper, the empirical relationships between UCS, RL and Is50 are searched by means of the percentile method (Bruno et al. 2013). This method is based on looking for the best regression function, between measured data of UCS and one of the indirect indices, drawn from a subset sample of the couples of measures that are the percentile values. These values are taken from the original dataset of both measures by calculating the cumulative function. No hypothesis on the probability distribution of the sample is needed and the procedure shows to be robust with respect to odd values or outliers. In this study, the carbonate sedimentary rocks are investigated. According to the rock mass classification of Dobereiner and De Freitas (1986), the UCS values for the studied rocks range between 'extremely weak' to 'strong'. For the analyzed data, UCS varies between 1,18-270,70 MPa. Thus, through the percentile method the best empirical relationships UCS-Is50 and UCS-RL are plotted. Relationships between Is50 and RL are drawn, too

  4. Applications of fuzzy ranking methods to risk-management decisions

    NASA Astrophysics Data System (ADS)

    Mitchell, Harold A.; Carter, James C., III

    1993-12-01

    The Department of Energy is making significant improvements to its nuclear facilities as a result of more stringent regulation, internal audits, and recommendations from external review groups. A large backlog of upgrades has resulted. Currently, a prioritization method is being utilized which relies on a matrix of potential consequence and probability of occurrence. The attributes of the potential consequences considered include likelihood, exposure, public health and safety, environmental impact, site personnel safety, public relations, legal liability, and business loss. This paper describes an improved method which utilizes fuzzy multiple attribute decision methods to rank proposed improvement projects.

  5. Risk-based methods applicable to ranking conceptual designs

    SciTech Connect

    Breeding, R.J.; Ortiz, K.; Ringland, J.T.; Lim, J.J.

    1993-11-01

    In Ginichi Taguchi`s latest book on quality engineering, an emphasis is placed on robust design processes in which quality engineering techniques are brought ``upstream,`` that is, they are utilized as early as possible, preferably in the conceptual design stage. This approach was used in a study of possible future safety system designs for weapons. As an experiment, a method was developed for using probabilistic risk analysis (PRA) techniques to rank conceptual designs for performance against a safety metric for ultimate incorporation into a Pugh matrix evaluation. This represents a high-level UW application of PRA methods to weapons. As with most conceptual designs, details of the implementation were not yet developed; many of the components had never been built, let alone tested. Therefore, our application of risk assessment methods was forced to be at such a high level that the entire evaluation could be performed on a spreadsheet. Nonetheless, the method produced numerical estimates of safety in a manner that was consistent, reproducible, and scrutable. The results enabled us to rank designs to identify areas where returns on research efforts would be the greatest. The numerical estimates were calibrated against what is achievable by current weapon safety systems. The use of expert judgement is inescapable, but these judgements are explicit and the method is easily implemented on an spreadsheet computer program.

  6. Punching Wholes into Parts, or Beating the Percentile Averages.

    ERIC Educational Resources Information Center

    Carwile, Nancy R.

    1990-01-01

    Presents a facetious, ingenious resolution to the percentile dilemma concerning above- and below-average test scores. If schools enrolled the same number of pigs as students and tested both groups, the pigs would fill up the bottom half and all children would rank in the top 50 percent. However, some wrinkles need to be ironed out! (MLH)

  7. Consistent linguistic fuzzy preference relations method with ranking fuzzy numbers

    NASA Astrophysics Data System (ADS)

    Ridzuan, Siti Amnah Mohd; Mohamad, Daud; Kamis, Nor Hanimah

    2014-12-01

    Multi-Criteria Decision Making (MCDM) methods have been developed to help decision makers in selecting the best criteria or alternatives from the options given. One of the well known methods in MCDM is the Consistent Fuzzy Preference Relation (CFPR) method, essentially utilizes a pairwise comparison approach. This method was later improved to cater subjectivity in the data by using fuzzy set, known as the Consistent Linguistic Fuzzy Preference Relations (CLFPR). The CLFPR method uses the additive transitivity property in the evaluation of pairwise comparison matrices. However, the calculation involved is lengthy and cumbersome. To overcome this problem, a method of defuzzification was introduced by researchers. Nevertheless, the defuzzification process has a major setback where some information may lose due to the simplification process. In this paper, we propose a method of CLFPR that preserves the fuzzy numbers form throughout the process. In obtaining the desired ordering result, a method of ranking fuzzy numbers is utilized in the procedure. This improved procedure for CLFPR is implemented to a case study to verify its effectiveness. This method is useful for solving decision making problems and can be applied to many areas of applications.

  8. Method and apparatus for second-rank tensor generation

    NASA Technical Reports Server (NTRS)

    Liu, Hua-Kuang (Inventor)

    1991-01-01

    A method and apparatus are disclosed for generation of second-rank tensors using a photorefractive crystal to perform the outer-product between two vectors via four-wave mixing, thereby taking 2n input data to a control n squared output data points. Two orthogonal amplitude modulated coherent vector beams x and y are expanded and then parallel sides of the photorefractive crystal in exact opposition. A beamsplitter is used to direct a coherent pumping beam onto the crystal at an appropriate angle so as to produce a conjugate beam that is the matrix product of the vector beam that propagates in the exact opposite direction from the pumping beam. The conjugate beam thus separated is the tensor output xy (sup T).

  9. An efficient community detection method based on rank centrality

    NASA Astrophysics Data System (ADS)

    Jiang, Yawen; Jia, Caiyan; Yu, Jian

    2013-05-01

    Community detection is a very important problem in social network analysis. Classical clustering approach, K-means, has been shown to be very efficient to detect communities in networks. However, K-means is quite sensitive to the initial centroids or seeds, especially when it is used to detect communities. To solve this problem, in this study, we propose an efficient algorithm K-rank, which selects the top-K nodes with the highest rank centrality as the initial seeds, and updates these seeds by using an iterative technique like K-means. Then we extend K-rank to partition directed, weighted networks, and to detect overlapping communities. The empirical study on synthetic and real networks show that K-rank is robust and better than the state-of-the-art algorithms including K-means, BGLL, LPA, infomap and OSLOM.

  10. Methods for evaluating and ranking transportation energy conservation programs

    NASA Astrophysics Data System (ADS)

    Santone, L. C.

    1981-04-01

    The energy conservation programs are assessed in terms of petroleum savings, incremental costs to consumers probability of technical and market success, and external impacts due to environmental, economic, and social factors. Three ranking functions and a policy matrix are used to evaluate the programs. The net present value measure which computes the present worth of petroleum savings less the present worth of costs is modified by dividing by the present value of DOE funding to obtain a net present value per program dollar. The comprehensive ranking function takes external impacts into account. Procedures are described for making computations of the ranking functions and the attributes that require computation. Computations are made for the electric vehicle, Stirling engine, gas turbine, and MPG mileage guide program.

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

    PubMed

    Tian, Yuling; Zhang, Hongxian

    2016-01-01

    For the purposes of information retrieval, users must find highly relevant documents from within a system (and often a quite large one comprised of many individual documents) based on input query. Ranking the documents according to their relevance within the system to meet user needs is a challenging endeavor, and a hot research topic-there already exist several rank-learning methods based on machine learning techniques which can generate ranking functions automatically. This paper proposes a parallel B cell algorithm, RankBCA, for rank learning which utilizes a clonal selection mechanism based on biological immunity. The novel algorithm is compared with traditional rank-learning algorithms through experimentation and shown to outperform the others in respect to accuracy, learning time, and convergence rate; taken together, the experimental results show that the proposed algorithm indeed effectively and rapidly identifies optimal ranking functions. PMID:27487242

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

    PubMed Central

    Tian, Yuling; Zhang, Hongxian

    2016-01-01

    For the purposes of information retrieval, users must find highly relevant documents from within a system (and often a quite large one comprised of many individual documents) based on input query. Ranking the documents according to their relevance within the system to meet user needs is a challenging endeavor, and a hot research topic–there already exist several rank-learning methods based on machine learning techniques which can generate ranking functions automatically. This paper proposes a parallel B cell algorithm, RankBCA, for rank learning which utilizes a clonal selection mechanism based on biological immunity. The novel algorithm is compared with traditional rank-learning algorithms through experimentation and shown to outperform the others in respect to accuracy, learning time, and convergence rate; taken together, the experimental results show that the proposed algorithm indeed effectively and rapidly identifies optimal ranking functions. PMID:27487242

  13. Stabilized thermally beneficiated low rank coal and method of manufacture

    SciTech Connect

    Viall, A.J.; Richards, J.M.

    2000-07-18

    A process is described for reducing the spontaneous combustion tendencies of thermally beneficiated low rank coals employing heat, air or an oxygen containing gas followed by an optional moisture addition. Specific reaction conditions are supplied along with knowledge of equipment types that may be employed on a commercial scale to complete the process.

  14. Stabilized thermally beneficiated low rank coal and method of manufacture

    DOEpatents

    Viall, Arthur J.; Richards, Jeff M.

    2000-01-01

    A process for reducing the spontaneous combustion tendencies of thermally beneficiated low rank coals employing heat, air or an oxygen containing gas followed by an optional moisture addition. Specific reaction conditions are supplied along with knowledge of equipment types that may be employed on a commercial scale to complete the process.

  15. Stabilized thermally beneficiated low rank coal and method of manufacture

    DOEpatents

    Viall, A.J.; Richards, J.M.

    1999-01-26

    A process is described for reducing the spontaneous combustion tendencies of thermally beneficiated low rank coals employing heat, air or an oxygen containing gas followed by an optional moisture addition. Specific reaction conditions are supplied along with knowledge of equipment types that may be employed on a commercial scale to complete the process. 3 figs.

  16. Stabilized thermally beneficiated low rank coal and method of manufacture

    DOEpatents

    Viall, Arthur J.; Richards, Jeff M.

    1999-01-01

    A process for reducing the spontaneous combustion tendencies of thermally beneficiated low rank coals employing heat, air or an oxygen containing gas followed by an optional moisture addition. Specific reaction conditions are supplied along with knowledge of equipment types that may be employed on a commercial scale to complete the process.

  17. Efficient implementation of minimal polynomial and reduced rank extrapolation methods

    NASA Technical Reports Server (NTRS)

    Sidi, Avram

    1990-01-01

    The minimal polynomial extrapolation (MPE) and reduced rank extrapolation (RRE) are two effective techniques that have been used in accelerating the convergence of vector sequences, such as those that are obtained from iterative solution of linear and nonlinear systems of equation. Their definitions involve some linear least squares problems, and this causes difficulties in their numerical implementation. Timewise efficient and numerically stable implementations for MPE and RRE are developed. A computer program written in FORTRAN 77 is also appended and applied to some model problems.

  18. Dynamic Contrast-Enhanced MRI of Cervical Cancers: Temporal Percentile Screening of Contrast Enhancement Identifies Parameters for Prediction of Chemoradioresistance

    SciTech Connect

    Andersen, Erlend K.F.; Hole, Knut Hakon; Lund, Kjersti V.; Sundfor, Kolbein; Kristensen, Gunnar B.; Lyng, Heidi; Malinen, Eirik

    2012-03-01

    Purpose: To systematically screen the tumor contrast enhancement of locally advanced cervical cancers to assess the prognostic value of two descriptive parameters derived from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). Methods and Materials: This study included a prospectively collected cohort of 81 patients who underwent DCE-MRI with gadopentetate dimeglumine before chemoradiotherapy. The following descriptive DCE-MRI parameters were extracted voxel by voxel and presented as histograms for each time point in the dynamic series: normalized relative signal increase (nRSI) and normalized area under the curve (nAUC). The first to 100th percentiles of the histograms were included in a log-rank survival test, resulting in p value and relative risk maps of all percentile-time intervals for each DCE-MRI parameter. The maps were used to evaluate the robustness of the individual percentile-time pairs and to construct prognostic parameters. Clinical endpoints were locoregional control and progression-free survival. The study was approved by the institutional ethics committee. Results: The p value maps of nRSI and nAUC showed a large continuous region of percentile-time pairs that were significantly associated with locoregional control (p < 0.05). These parameters had prognostic impact independent of tumor stage, volume, and lymph node status on multivariate analysis. Only a small percentile-time interval of nRSI was associated with progression-free survival. Conclusions: The percentile-time screening identified DCE-MRI parameters that predict long-term locoregional control after chemoradiotherapy of cervical cancer.

  19. Solutions of interval type-2 fuzzy polynomials using a new ranking method

    NASA Astrophysics Data System (ADS)

    Rahman, Nurhakimah Ab.; Abdullah, Lazim; Ghani, Ahmad Termimi Ab.; Ahmad, Noor'Ani

    2015-10-01

    A few years ago, a ranking method have been introduced in the fuzzy polynomial equations. Concept of the ranking method is proposed to find actual roots of fuzzy polynomials (if exists). Fuzzy polynomials are transformed to system of crisp polynomials, performed by using ranking method based on three parameters namely, Value, Ambiguity and Fuzziness. However, it was found that solutions based on these three parameters are quite inefficient to produce answers. Therefore in this study a new ranking method have been developed with the aim to overcome the inherent weakness. The new ranking method which have four parameters are then applied in the interval type-2 fuzzy polynomials, covering the interval type-2 of fuzzy polynomial equation, dual fuzzy polynomial equations and system of fuzzy polynomials. The efficiency of the new ranking method then numerically considered in the triangular fuzzy numbers and the trapezoidal fuzzy numbers. Finally, the approximate solutions produced from the numerical examples indicate that the new ranking method successfully produced actual roots for the interval type-2 fuzzy polynomials.

  20. Establishing percentiles for junior tennis players based on physical fitness testing results.

    PubMed

    Roetert, E P; Piorkowski, P A; Woods, R B; Brown, S W

    1995-01-01

    An important aspect of this study was the establishment of a data base. A broad data base allows for data on certain parameters to be greatly expanded and will also enhance the use and interpretation of statistical methods. A longitudinal study of these variables may also assist in monitoring the players' progress over a period of time, and can provide a useful supplement to subjective coaching appraisals. The means and standard deviation for each test were calculated according to the USTA age and gender groups, that is, 12s, 14s, and 16s for each separate gender. Additionally, the mean and standard deviations for the ages, heights, and weights of each grouping were also calculated. Once the means and standard deviations were calculated, percentile tables were developed for each of the USTA groupings (by age and gender). The percentiles for each USTA test are presented in Appendix 1. A percentile is defined as the point on the distribution below which a given percentage of the scores is found. Percentiles can provide a norm-referenced interpretation of an individual score within a distribution that often consists of scores from a comparable group of individuals. Using the USTA protocol, players and coaches now have a set of normative data by which individual player's fitness scores may be compared with participants of the USTA Area Training Centers (See appendix 1). From the test results, coaches and players can determine which fitness areas need to be improved for athletes on an individual basis. Specific training programs can then be designed based on an athlete's fitness testing results. Proper interpretation of the USTA fitness testing data base results can lead to an easy way to determine the relative position of a given fitness score in the distribution, recognizing weaker areas for the purpose of injury prevention and performance enhancement. Each player can be given a profile detailing their percentile rank relative to other area training center

  1. Group-based ranking method for online rating systems with spamming attacks

    NASA Astrophysics Data System (ADS)

    Gao, Jian; Dong, Yu-Wei; Shang, Ming-Sheng; Cai, Shi-Min; Zhou, Tao

    2015-04-01

    The ranking problem has attracted much attention in real systems. How to design a robust ranking method is especially significant for online rating systems under the threat of spamming attacks. By building reputation systems for users, many well-performed ranking methods have been applied to address this issue. In this letter, we propose a group-based ranking method that evaluates users' reputations based on their grouping behaviors. More specifically, users are assigned with high reputation scores if they always fall into large rating groups. Results on three real data sets indicate that the present method is more accurate and robust than the correlation-based method in the presence of spamming attacks.

  2. Solving the interval type-2 fuzzy polynomial equation using the ranking method

    NASA Astrophysics Data System (ADS)

    Rahman, Nurhakimah Ab.; Abdullah, Lazim

    2014-07-01

    Polynomial equations with trapezoidal and triangular fuzzy numbers have attracted some interest among researchers in mathematics, engineering and social sciences. There are some methods that have been developed in order to solve these equations. In this study we are interested in introducing the interval type-2 fuzzy polynomial equation and solving it using the ranking method of fuzzy numbers. The ranking method concept was firstly proposed to find real roots of fuzzy polynomial equation. Therefore, the ranking method is applied to find real roots of the interval type-2 fuzzy polynomial equation. We transform the interval type-2 fuzzy polynomial equation to a system of crisp interval type-2 fuzzy polynomial equation. This transformation is performed using the ranking method of fuzzy numbers based on three parameters, namely value, ambiguity and fuzziness. Finally, we illustrate our approach by numerical example.

  3. Methods of computing vocabulary size for the two-parameter rank distribution

    NASA Technical Reports Server (NTRS)

    Edmundson, H. P.; Fostel, G.; Tung, I.; Underwood, W.

    1972-01-01

    A summation method is described for computing the vocabulary size for given parameter values in the 1- and 2-parameter rank distributions. Two methods of determining the asymptotes for the family of 2-parameter rank-distribution curves are also described. Tables are computed and graphs are drawn relating paris of parameter values to the vocabulary size. The partial product formula for the Riemann zeta function is investigated as an approximation to the partial sum formula for the Riemann zeta function. An error bound is established that indicates that the partial product should not be used to approximate the partial sum in calculating the vocabulary size for the 2-parameter rank distribution.

  4. Percentile curves for skinfold thickness for Canadian children and youth

    PubMed Central

    Ashley-Martin, Jillian; Maguire, Bryan; Hamilton, David C.

    2016-01-01

    Background. Skinfold thickness (SFT) measurements are a reliable and feasible method for assessing body fat in children but their use and interpretation is hindered by the scarcity of reference values in representative populations of children. The objective of the present study was to develop age- and sex-specific percentile curves for five SFT measures (biceps, triceps, subscapular, suprailiac, medial calf) in a representative population of Canadian children and youth. Methods. We analyzed data from 3,938 children and adolescents between 6 and 19 years of age who participated in the Canadian Health Measures Survey cycles 1 (2007/2009) and 2 (2009/2011). Standardized procedures were used to measure SFT. Age- and sex-specific centiles for SFT were calculated using the GAMLSS method. Results. Percentile curves were materially different in absolute value and shape for boys and girls. Percentile girls in girls steadily increased with age whereas percentile curves in boys were characterized by a pubertal centered peak. Conclusions. The current study has presented for the first time percentile curves for five SFT measures in a representative sample of Canadian children and youth. PMID:27547554

  5. Percentile curves for skinfold thickness for Canadian children and youth.

    PubMed

    Kuhle, Stefan; Ashley-Martin, Jillian; Maguire, Bryan; Hamilton, David C

    2016-01-01

    Background. Skinfold thickness (SFT) measurements are a reliable and feasible method for assessing body fat in children but their use and interpretation is hindered by the scarcity of reference values in representative populations of children. The objective of the present study was to develop age- and sex-specific percentile curves for five SFT measures (biceps, triceps, subscapular, suprailiac, medial calf) in a representative population of Canadian children and youth. Methods. We analyzed data from 3,938 children and adolescents between 6 and 19 years of age who participated in the Canadian Health Measures Survey cycles 1 (2007/2009) and 2 (2009/2011). Standardized procedures were used to measure SFT. Age- and sex-specific centiles for SFT were calculated using the GAMLSS method. Results. Percentile curves were materially different in absolute value and shape for boys and girls. Percentile girls in girls steadily increased with age whereas percentile curves in boys were characterized by a pubertal centered peak. Conclusions. The current study has presented for the first time percentile curves for five SFT measures in a representative sample of Canadian children and youth. PMID:27547554

  6. Systematic comparison of hedonic ranking and rating methods demonstrates few practical differences.

    PubMed

    Kozak, Marcin; Cliff, Margaret A

    2013-08-01

    Hedonic ranking is one of the commonly used methods to evaluate consumer preferences. Some authors suggest that it is the best methodology for discriminating among products, while others recommend hedonic rating. These mixed findings suggest the statistical outcome(s) are dependent on the experimental conditions or a user's expectation of "what is" and "what is not" desirable for evaluating consumer preferences. Therefore, sensory and industry professionals may be uncertain or confused regarding the appropriate application of hedonic tests. This paper would like to put this controversy to rest, by evaluating 3 data sets (3 yogurts, 79 consumers; 6 yogurts, 109 consumers; 4 apple cultivars, 70 consumers) collected using the same consumers and by calculating nontied ranks from hedonic scores. Consumer responses were evaluated by comparing bivariate associations between the methods (nontied ranks, tied ranks, hedonic rating scores) using trellis displays, determining the number of consumers with discrepancies in their responses between the methods, and comparing mean values using conventional statistical analyses. Spearman's rank correlations (0.33-0.84) revealed significant differences between the methods for all products, whether or not means separation tests differentiated the products. The work illustrated the inherent biases associated with hedonic ranking and recommended alternate hedonic methodologies. PMID:23815796

  7. Simultaneous denoising and reconstruction of 5D seismic data via damped rank-reduction method

    NASA Astrophysics Data System (ADS)

    Chen, Yangkang; Zhang, Dong; Jin, Zhaoyu; Chen, Xiaohong; Zu, Shaohuan; Huang, Weilin; Gan, Shuwei

    2016-06-01

    The Cadzow rank-reduction method can be effectively utilized in simultaneously denoising and reconstructing 5D seismic data that depends on four spatial dimensions. The classic version of Cadzow rank-reduction method arranges the 4D spatial data into a level-four block Hankel/Toeplitz matrix and then applies truncated singular value decomposition (TSVD) for rank-reduction. When the observed data is extremely noisy, which is often the feature of real seismic data, traditional TSVD cannot be adequate for attenuating the noise and reconstructing the signals. The reconstructed data tends to contain a significant amount of residual noise using the traditional TSVD method, which can be explained by the fact that the reconstructed data space is a mixture of both signal subspace and noise subspace. In order to better decompose the block Hankel matrix into signal and noise components, we introduced a damping operator into the traditional TSVD formula, which we call the damped rank-reduction method. The damped rank-reduction method can obtain a perfect reconstruction performance even when the observed data has extremely low signal-to-noise ratio (SNR). The feasibility of the improved 5D seismic data reconstruction method was validated via both 5D synthetic and field data examples. We presented comprehensive analysis of the data examples and obtained valuable experience and guidelines in better utilizing the proposed method in practice. Since the proposed method is convenient to implement and can achieve immediate improvement, we suggest its wide application in the industry.

  8. Simultaneous denoising and reconstruction of 5-D seismic data via damped rank-reduction method

    NASA Astrophysics Data System (ADS)

    Chen, Yangkang; Zhang, Dong; Jin, Zhaoyu; Chen, Xiaohong; Zu, Shaohuan; Huang, Weilin; Gan, Shuwei

    2016-09-01

    The Cadzow rank-reduction method can be effectively utilized in simultaneously denoising and reconstructing 5-D seismic data that depend on four spatial dimensions. The classic version of Cadzow rank-reduction method arranges the 4-D spatial data into a level-four block Hankel/Toeplitz matrix and then applies truncated singular value decomposition (TSVD) for rank reduction. When the observed data are extremely noisy, which is often the feature of real seismic data, traditional TSVD cannot be adequate for attenuating the noise and reconstructing the signals. The reconstructed data tend to contain a significant amount of residual noise using the traditional TSVD method, which can be explained by the fact that the reconstructed data space is a mixture of both signal subspace and noise subspace. In order to better decompose the block Hankel matrix into signal and noise components, we introduced a damping operator into the traditional TSVD formula, which we call the damped rank-reduction method. The damped rank-reduction method can obtain a perfect reconstruction performance even when the observed data have extremely low signal-to-noise ratio. The feasibility of the improved 5-D seismic data reconstruction method was validated via both 5-D synthetic and field data examples. We presented comprehensive analysis of the data examples and obtained valuable experience and guidelines in better utilizing the proposed method in practice. Since the proposed method is convenient to implement and can achieve immediate improvement, we suggest its wide application in the industry.

  9. Low-Rank Incremental Methods for Computing Dominant Singular Subspaces

    SciTech Connect

    Baker, Christopher G; Gallivan, Dr. Kyle A; Van Dooren, Dr. Paul

    2012-01-01

    Computing the singular values and vectors of a matrix is a crucial kernel in numerous scientific and industrial applications. As such, numerous methods have been proposed to handle this problem in a computationally efficient way. This paper considers a family of methods for incrementally computing the dominant SVD of a large matrix A. Specifically, we describe a unification of a number of previously disparate methods for approximating the dominant SVD via a single pass through A. We tie the behavior of these methods to that of a class of optimization-based iterative eigensolvers on A'*A. An iterative procedure is proposed which allows the computation of an accurate dominant SVD via multiple passes through A. We present an analysis of the convergence of this iteration, and provide empirical demonstration of the proposed method on both synthetic and benchmark data.

  10. Solving fuzzy polynomial equation and the dual fuzzy polynomial equation using the ranking method

    NASA Astrophysics Data System (ADS)

    Rahman, Nurhakimah Ab.; Abdullah, Lazim

    2014-06-01

    Fuzzy polynomials with trapezoidal and triangular fuzzy numbers have attracted interest among some researchers. Many studies have been done by researchers to obtain real roots of fuzzy polynomials. As a result, there are many numerical methods involved in obtaining the real roots of fuzzy polynomials. In this study, we will present the solution to the fuzzy polynomial equation and dual fuzzy polynomial equation using the ranking method of fuzzy numbers and subsequently transforming fuzzy polynomials to crisp polynomials. This transformation is performed using the ranking method based on three parameters, namely Value, Ambiguity and Fuzziness. Finally, we illustrate our approach with two numerical examples for fuzzy polynomial equation and dual fuzzy polynomial equation.

  11. Percentile Curves for Anthropometric Measures for Canadian Children and Youth

    PubMed Central

    Kuhle, Stefan; Maguire, Bryan; Ata, Nicole; Hamilton, David

    2015-01-01

    Body mass index (BMI) is commonly used to assess a child's weight status but it does not provide information about the distribution of body fat. Since the disease risks associated with obesity are related to the amount and distribution of body fat, measures that assess visceral or subcutaneous fat, such as waist circumference (WC), waist-to-height ratio (WHtR), or skinfolds thickness may be more suitable. The objective of this study was to develop percentile curves for BMI, WC, WHtR, and sum of 5 skinfolds (SF5) in a representative sample of Canadian children and youth. The analysis used data from 4115 children and adolescents between 6 and 19 years of age that participated in the Canadian Health Measures Survey Cycles 1 (2007/2009) and 2 (2009/2011). BMI, WC, WHtR, and SF5 were measured using standardized procedures. Age- and sex-specific centiles were calculated using the LMS method and the percentiles that intersect the adult cutpoints for BMI, WC, and WHtR at age 18 years were determined. Percentile curves for all measures showed an upward shift compared to curves from the pre-obesity epidemic era. The adult cutoffs for overweight and obesity corresponded to the 72nd and 91st percentile, respectively, for both sexes. The current study has presented for the first time percentile curves for BMI, WC, WHtR, and SF5 in a representative sample of Canadian children and youth. The percentile curves presented are meant to be descriptive rather than prescriptive as associations with cardiovascular disease markers or outcomes were not assessed. PMID:26176769

  12. Application of model-free methods for analysis of combustion kinetics of coals with different ranks

    SciTech Connect

    Sis, H

    2009-07-01

    Model-free kinetic approaches were employed to investigate the combustion kinetics of coals with different ranks, namely, lignite, bituminous coal, and anthracite. The experimental data were provided under non-isothermal conditions at different heating rates in the range of 2-25C min{sup -1}. The activation energy values were estimated by two model-free methods, that is, Ozawa-Flynn-Wall and Kissinger-Akahira-Sunose methods. Slightly higher activation energy values were obtained by Ozawa-Flynn-Wall method at a wide range of conversion extent. Variation of activation energy was found to be comparably more significant for lower rank lignite (between 44.82 and 287.56 kJ mol{sup -1}) while less significant for higher rank bituminous coal (between 101.97 and 155.64 kJ mol{sup -1}) and anthracite (between 106.04 and 160.31 kJ mol{sup -1}).

  13. A Recursive Partitioning Method for the Prediction of Preference Rankings Based Upon Kemeny Distances.

    PubMed

    D'Ambrosio, Antonio; Heiser, Willem J

    2016-09-01

    Preference rankings usually depend on the characteristics of both the individuals judging a set of objects and the objects being judged. This topic has been handled in the literature with log-linear representations of the generalized Bradley-Terry model and, recently, with distance-based tree models for rankings. A limitation of these approaches is that they only work with full rankings or with a pre-specified pattern governing the presence of ties, and/or they are based on quite strict distributional assumptions. To overcome these limitations, we propose a new prediction tree method for ranking data that is totally distribution-free. It combines Kemeny's axiomatic approach to define a unique distance between rankings with the CART approach to find a stable prediction tree. Furthermore, our method is not limited by any particular design of the pattern of ties. The method is evaluated in an extensive full-factorial Monte Carlo study with a new simulation design. PMID:27370072

  14. Methods for evaluating and ranking transportation energy conservation programs. Final report

    SciTech Connect

    Not Available

    1981-04-30

    Methods for comparative evaluations of the Office of Transportation programs designed to help achieve significant reductions in the consumption of petroleum by different forms of transportation while maintaining public, commercial, and industrial mobility are described. Assessments of the programs in terms of petroleum savings, incremental costs to consumers of the technologies and activities, probability of technical and market success, and external impacts due to environmental, economic, and social factors are inputs to the evaluation methodologies presented. The methods described for evaluating the programs on a comparative basis are three ranking functions and a policy matrix listing important attributes of the programs and the technologies and activities with which they are concerned and include the traditional net present value measure which computes the present worth of petroleum savings less the present worth of costs. This is modified by dividing by the present value of DOE funding to obtain a net present value per program dollar, which is the second ranking function. The third ranking function is broader in that it takes external impacts into account and is known as the comprehensive ranking function. Procedures are described for making computations of the ranking functions and the attributes that require computation. Computations are made for the electric vehicle, Stirling engine, gas turbine, and MPG mileage guide program. (MCW)

  15. On Efficient Feature Ranking Methods for High-Throughput Data Analysis.

    PubMed

    Liao, Bo; Jiang, Yan; Liang, Wei; Peng, Lihong; Peng, Li; Hanyurwimfura, Damien; Li, Zejun; Chen, Min

    2015-01-01

    Efficient mining of high-throughput data has become one of the popular themes in the big data era. Existing biology-related feature ranking methods mainly focus on statistical and annotation information. In this study, two efficient feature ranking methods are presented. Multi-target regression and graph embedding are incorporated in an optimization framework, and feature ranking is achieved by introducing structured sparsity norm. Unlike existing methods, the presented methods have two advantages: (1) the feature subset simultaneously account for global margin information as well as locality manifold information. Consequently, both global and locality information are considered. (2) Features are selected by batch rather than individually in the algorithm framework. Thus, the interactions between features are considered and the optimal feature subset can be guaranteed. In addition, this study presents a theoretical justification. Empirical experiments demonstrate the effectiveness and efficiency of the two algorithms in comparison with some state-of-the-art feature ranking methods through a set of real-world gene expression data sets. PMID:26684461

  16. Effects of Different Methods of Weighting Subscores on the Composite-Score Ranking of Examinees.

    ERIC Educational Resources Information Center

    Modu, Christopher C.

    The effects of applying different methods of determining different sets of subscore weights on the composite score ranking of examinees were investigated. Four sets of subscore weights were applied to each of three examination results. The scores were from Advanced Placement (AP) Examinations in History of Art, Spanish Language, and Chemistry. One…

  17. [RANK INDICES METHOD AND ITS USE FOR THE COMPARATIVE ANALYSIS OF POPULATION HEALTH].

    PubMed

    Bolshakov, A M; Krutko, V N; Smirnova, T M; Chankov, S V

    2016-01-01

    There is presented a calculation method aimed to elevate the informative value of the integral indices of the social and hygienic monitoringfor purposes of comparative analysis. The method of rank indices is based on the ranking of monitoring objects on the values of primary indices on the base of which there are calculated the integral such indices as, for example, life expectancy. There are presented results of the use of this method for the comparative analysis of mortality rate in WHO Member States for the period of 1990-2011. There were revealed specialfeatures of mortality trends which cannot be detected when using only mortality rates or the life expectancy. In particular, for Russia there was shown that, in spite of the downward trend in child and adolescent mortality rate observed in the last decade, the country's world rankings for these indices fail to achieve the level of 1990. This means that the competitiveness of the country, sharply declined in the 90's, was not restored until now. There are described some features of the use of the method of rank indices for the analysis of indices of the environment state, public health and its socio-economic determinants. PMID:27266035

  18. A method for integrating and ranking the evidence for biochemical pathways by mining reactions from text

    PubMed Central

    Miwa, Makoto; Ohta, Tomoko; Rak, Rafal; Rowley, Andrew; Kell, Douglas B.; Pyysalo, Sampo; Ananiadou, Sophia

    2013-01-01

    Motivation: To create, verify and maintain pathway models, curators must discover and assess knowledge distributed over the vast body of biological literature. Methods supporting these tasks must understand both the pathway model representations and the natural language in the literature. These methods should identify and order documents by relevance to any given pathway reaction. No existing system has addressed all aspects of this challenge. Method: We present novel methods for associating pathway model reactions with relevant publications. Our approach extracts the reactions directly from the models and then turns them into queries for three text mining-based MEDLINE literature search systems. These queries are executed, and the resulting documents are combined and ranked according to their relevance to the reactions of interest. We manually annotate document-reaction pairs with the relevance of the document to the reaction and use this annotation to study several ranking methods, using various heuristic and machine-learning approaches. Results: Our evaluation shows that the annotated document-reaction pairs can be used to create a rule-based document ranking system, and that machine learning can be used to rank documents by their relevance to pathway reactions. We find that a Support Vector Machine-based system outperforms several baselines and matches the performance of the rule-based system. The success of the query extraction and ranking methods are used to update our existing pathway search system, PathText. Availability: An online demonstration of PathText 2 and the annotated corpus are available for research purposes at http://www.nactem.ac.uk/pathtext2/. Contact: makoto.miwa@manchester.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online. PMID:23813008

  19. Urinary iodine percentile ranges in the United States

    PubMed Central

    Soldin, Offie Porat; Soldin, Steven J.; Pezzullo, John C.

    2013-01-01

    Background The status of iodine nutrition of a population can be determined by measurement of urinary iodine concentrations since it is thought to indicate dietary iodine intake. Normally, these results are compared to population-based criteria, since there are no reference ranges for urinary iodine. Objective To determine the percentile ranges for urinary iodide (UI) concentrations in normal individuals in the United States. Materials and methods The third National Health and Nutrition Examination Survey (NHANES III) (1988–1994) database of the civilian, non-institutionalized, iodine-sufficient US population was used. The 2.5th to 97.5th percentile ranges for urinary iodine and for urinary iodine per gram creatinine ratio (UI/Cr) (μg/g) were calculated for females and males, 6–89 years of age, each stratified by age groups. Results and conclusions We calculated the percentile ranges for urinary iodine. After exclusions of subjects with goiter or thyroid disease, the study sample included 21,530 subjects; 10,439 males and 11,091 females. For women of childbearing age (14–44 years), urinary iodine concentration 2.5th to 97.5th percentiles are 1.8–65 μg/dl or 36–539 μg/g creatinine. For pregnant women, the ranges are 4.2–55 μg/dl or 33–535 μg/g creatinine. PMID:12559616

  20. Methods for contingency screening and ranking for voltage stability analysis of power systems

    SciTech Connect

    Ejebe, G.C.; Irisarri, G.D.; Mokhtari, S.; Obadina, O.; Ristanovic, P.; Tong, J.

    1996-02-01

    The comparison of performance of four methods for contingency screening and ranking for voltage stability analysis is presented. Three of the methods are existing methods, while a new method is proposed. The performance of all the methods is carried out by comparing with full solutions using a continuation power flow. It is shown that the newly proposed method has the best performance in terms of accuracy and computation time. All the methods are evaluated using a 234-bus system. Additional results using the best performing method are included for a 901-bus power system.

  1. Methods for contingency screening and ranking for voltage stability analysis of power systems

    SciTech Connect

    Ejebe, G.C.; Irisarri, G.D.; Mokhtari, S.; Obadina, O.; Ristanovic, P.; Tong, J.

    1995-12-31

    The comparison of performance of four methods for contingency screening and ranking for voltage stability analysis is presented. Three of the methods are existing methods, while a new method is proposed. The performance of all the methods is carried out by comparing with full solutions using a continuation power flow. It is shown that the newly proposed method has the best performance in terms of accuracy and computation time. All the methods are evaluated using a 234-bus system. Additional results using the best performing method are included for a 901-bus power system.

  2. Supervised descent method with low rank and sparsity constraints for robust face alignment

    NASA Astrophysics Data System (ADS)

    Sun, Yubao; Hu, Bin; Deng, Jiankang; Li, Xing

    2015-03-01

    Supervised Descent Method (SDM) learns the descent directions of nonlinear least square objective in a supervised manner, which has been efficiently used for face alignment. However, SDM still may fail in the cases of partial occlusions and serious pose variations. To deal with this issue, we present a new method for robust face alignment by utilizing the low rank prior of human face and enforcing sparse structure of the descent directions. Our approach consists of low rank face frontalization and sparse descent steps. Firstly, in terms of the low rank prior of face image, we recover such a low-rank face from its deformed image and the associated deformation despite significant distortion and corruption. Alignment of the recovered frontal face image is more simple and effective. Then, we propose a sparsity regularized supervised descent model by enforcing the sparse structure of the descent directions under the l1constraint, which makes the model more effective in computation and robust to partial occlusion. Extensive results on several benchmarks demonstrate that the proposed method is robust to facial occlusions and pose variations

  3. Promoted combustion of nine structural metals in high-pressure gaseous oxygen - A comparison of ranking methods

    NASA Technical Reports Server (NTRS)

    Steinberg, Theodore A.; Rucker, Michelle A.; Beeson, Harold D.

    1989-01-01

    The 316, 321, 440C, and 17-4 PH stainless steels, as well as Inconel 600, Inconel 718, Waspaloy, Monel 400, and Al 2219, have been evaluated for relative nonflammability in a high-pressure oxygen environment with a view to the comparative advantages of four different flammability-ranking methods. The effects of changes in test pressure, sample diameter, promoter type, and sample configuration on ranking method results are evaluated; ranking methods employing velocity as the primary ranking criterion are limited by diameter effects, while those which use extinguishing pressure are nonselective for metals with similar flammabilities.

  4. An Activity for Learning to Find Percentiles

    ERIC Educational Resources Information Center

    Cox, Richard G.

    2016-01-01

    This classroom activity is designed to help students practice calculating percentiles. The approach of the activity involves physical sorting and full classroom participation in each calculation. The design encourages a more engaged approach than simply having students make a calculation with numbers on a paper.

  5. Efficient completion for corrupted low-rank images via alternating direction method

    NASA Astrophysics Data System (ADS)

    Li, Wei; Zhao, Lei; Xu, Duanqing; Lu, Dongming

    2014-05-01

    We propose an efficient and easy-to-implement method to settle the inpainting problem for low-rank images following the recent studies about low-rank matrix completion. In general, our method has three steps: first, corresponding to the three channels of RGB color space, an incomplete image is split into three incomplete matrices; second, each matrix is restored by solving a convex problem derived from the nuclear norm relaxation; at last, the three recovered matrices are merged to produce the final output. During the process, in order to efficiently solve the nuclear norm minimization problem, we employ the alternating direction method. Except for the basic image inpainting problem, we also enable our method to handle cases where corrupted images not only have missing values but also have noisy entries. Our experiments show that our method outperforms the existing inpainting techniques both quantitatively and qualitatively. We also demonstrate that our method is capable of processing many other situations, including block-wise low-rank image completion, large-scale image restoration, and object removal.

  6. Prioritizing sewer rehabilitation projects using AHP-PROMETHEE II ranking method.

    PubMed

    Kessili, Abdelhak; Benmamar, Saadia

    2016-01-01

    The aim of this paper is to develop a methodology for the prioritization of sewer rehabilitation projects for Algiers (Algeria) sewer networks to support the National Sanitation Office in its challenge to make decisions on prioritization of sewer rehabilitation projects. The methodology applies multiple-criteria decision making. The study includes 47 projects (collectors) and 12 criteria to evaluate them. These criteria represent the different issues considered in the prioritization of the projects, which are structural, hydraulic, environmental, financial, social and technical. The analytic hierarchy process (AHP) is used to determine weights of the criteria and the Preference Ranking Organization Method for Enrichment Evaluations (PROMETHEE II) method is used to obtain the final ranking of the projects. The model was verified using the sewer data of Algiers. The results have shown that the method can be used for prioritizing sewer rehabilitation projects. PMID:26819383

  7. NIH peer review percentile scores are poorly predictive of grant productivity

    PubMed Central

    Fang, Ferric C; Bowen, Anthony; Casadevall, Arturo

    2016-01-01

    Peer review is widely used to assess grant applications so that the highest ranked applications can be funded. A number of studies have questioned the ability of peer review panels to predict the productivity of applications, but a recent analysis of grants funded by the National Institutes of Health (NIH) in the US found that the percentile scores awarded by peer review panels correlated with productivity as measured by citations of grant-supported publications. Here, based on a re-analysis of these data for the 102,740 funded grants with percentile scores of 20 or better, we report that these percentile scores are a poor discriminator of productivity. This underscores the limitations of peer review as a means of assessing grant applications in an era when typical success rates are often as low as about 10%. DOI: http://dx.doi.org/10.7554/eLife.13323.001 PMID:26880623

  8. NIH peer review percentile scores are poorly predictive of grant productivity.

    PubMed

    Fang, Ferric C; Bowen, Anthony; Casadevall, Arturo

    2016-01-01

    Peer review is widely used to assess grant applications so that the highest ranked applications can be funded. A number of studies have questioned the ability of peer review panels to predict the productivity of applications, but a recent analysis of grants funded by the National Institutes of Health (NIH) in the US found that the percentile scores awarded by peer review panels correlated with productivity as measured by citations of grant-supported publications. Here, based on a re-analysis of these data for the 102,740 funded grants with percentile scores of 20 or better, we report that these percentile scores are a poor discriminator of productivity. This underscores the limitations of peer review as a means of assessing grant applications in an era when typical success rates are often as low as about 10%. PMID:26880623

  9. Percentile growth charts for biomedical studies using a porcine model.

    PubMed

    Corson, A M; Laws, J; Laws, A; Litten, J C; Lean, I J; Clarke, L

    2008-12-01

    Increasing rates of obesity and heart disease are compromising quality of life for a growing number of people. There is much research linking adult disease with the growth and development both in utero and during the first year of life. The pig is an ideal model for studying the origins of developmental programming. The objective of this paper was to construct percentile growth curves for the pig for use in biomedical studies. The body weight (BW) of pigs was recorded from birth to 150 days of age and their crown-to-rump length was measured over the neonatal period to enable the ponderal index (PI; kg/m3) to be calculated. Data were normalised and percentile curves were constructed using Cole's lambda-mu-sigma (LMS) method for BW and PI. The construction of these percentile charts for use in biomedical research will allow a more detailed and precise tracking of growth and development of individual pigs under experimental conditions. PMID:22444086

  10. Low-rank Quasi-Newton updates for Robust Jacobian lagging in Newton methods

    SciTech Connect

    Brown, J.; Brune, P.

    2013-07-01

    Newton-Krylov methods are standard tools for solving nonlinear problems. A common approach is to 'lag' the Jacobian when assembly or preconditioner setup is computationally expensive, in exchange for some degradation in the convergence rate and robustness. We show that this degradation may be partially mitigated by using the lagged Jacobian as an initial operator in a quasi-Newton method, which applies unassembled low-rank updates to the Jacobian until the next full reassembly. We demonstrate the effectiveness of this technique on problems in glaciology and elasticity. (authors)

  11. Feature selection for splice site prediction: A new method using EDA-based feature ranking

    PubMed Central

    Saeys, Yvan; Degroeve, Sven; Aeyels, Dirk; Rouzé, Pierre; Van de Peer, Yves

    2004-01-01

    Background The identification of relevant biological features in large and complex datasets is an important step towards gaining insight in the processes underlying the data. Other advantages of feature selection include the ability of the classification system to attain good or even better solutions using a restricted subset of features, and a faster classification. Thus, robust methods for fast feature selection are of key importance in extracting knowledge from complex biological data. Results In this paper we present a novel method for feature subset selection applied to splice site prediction, based on estimation of distribution algorithms, a more general framework of genetic algorithms. From the estimated distribution of the algorithm, a feature ranking is derived. Afterwards this ranking is used to iteratively discard features. We apply this technique to the problem of splice site prediction, and show how it can be used to gain insight into the underlying biological process of splicing. Conclusion We show that this technique proves to be more robust than the traditional use of estimation of distribution algorithms for feature selection: instead of returning a single best subset of features (as they normally do) this method provides a dynamical view of the feature selection process, like the traditional sequential wrapper methods. However, the method is faster than the traditional techniques, and scales better to datasets described by a large number of features. PMID:15154966

  12. The Typicality Ranking Task: A New Method to Derive Typicality Judgments from Children

    PubMed Central

    Ameel, Eef; Storms, Gert

    2016-01-01

    An alternative method for deriving typicality judgments, applicable in young children that are not familiar with numerical values yet, is introduced, allowing researchers to study gradedness at younger ages in concept development. Contrary to the long tradition of using rating-based procedures to derive typicality judgments, we propose a method that is based on typicality ranking rather than rating, in which items are gradually sorted according to their typicality, and that requires a minimum of linguistic knowledge. The validity of the method is investigated and the method is compared to the traditional typicality rating measurement in a large empirical study with eight different semantic concepts. The results show that the typicality ranking task can be used to assess children’s category knowledge and to evaluate how this knowledge evolves over time. Contrary to earlier held assumptions in studies on typicality in young children, our results also show that preference is not so much a confounding variable to be avoided, but that both variables are often significantly correlated in older children and even in adults. PMID:27322371

  13. Development of a percentile based three-dimensional model of the buttocks in computer system

    NASA Astrophysics Data System (ADS)

    Wang, Lijing; He, Xueli; Li, Hongpeng

    2016-04-01

    There are diverse products related to human buttocks, which need to be designed, manufactured and evaluated with 3D buttock model. The 3D buttock model used in present research field is just simple approximate model similar to human buttocks. The 3D buttock percentile model is highly desired in the ergonomics design and evaluation for these products. So far, there is no research on the percentile sizing system of human 3D buttock model. So the purpose of this paper is to develop a new method for building three-dimensional buttock percentile model in computer system. After scanning the 3D shape of buttocks, the cloud data of 3D points is imported into the reverse engineering software (Geomagic) for the reconstructing of the buttock surface model. Five characteristic dimensions of the buttock are measured through mark-points after models being imported into engineering software CATIA. A series of space points are obtained by the intersecting of the cutting slices and 3D buttock surface model, and then are ordered based on the sequence number of the horizontal and vertical slices. The 1st, 5th, 50th, 95th, 99th percentile values of the five dimensions and the spatial coordinate values of the space points are obtained, and used to reconstruct percentile buttock models. This research proposes a establishing method of percentile sizing system of buttock 3D model based on the percentile values of the ischial tuberosities diameter, the distances from margin to ischial tuberosity and the space coordinates value of coordinate points, for establishing the Nth percentile 3D buttock model and every special buttock types model. The proposed method also serves as a useful guidance for the other 3D percentile models establishment for other part in human body with characteristic points.

  14. Development of a percentile based three-dimensional model of the buttocks in computer system

    NASA Astrophysics Data System (ADS)

    Wang, Lijing; He, Xueli; Li, Hongpeng

    2016-05-01

    There are diverse products related to human buttocks, which need to be designed, manufactured and evaluated with 3D buttock model. The 3D buttock model used in present research field is just simple approximate model similar to human buttocks. The 3D buttock percentile model is highly desired in the ergonomics design and evaluation for these products. So far, there is no research on the percentile sizing system of human 3D buttock model. So the purpose of this paper is to develop a new method for building three-dimensional buttock percentile model in computer system. After scanning the 3D shape of buttocks, the cloud data of 3D points is imported into the reverse engineering software (Geomagic) for the reconstructing of the buttock surface model. Five characteristic dimensions of the buttock are measured through mark-points after models being imported into engineering software CATIA. A series of space points are obtained by the intersecting of the cutting slices and 3D buttock surface model, and then are ordered based on the sequence number of the horizontal and vertical slices. The 1st, 5th, 50th, 95th, 99th percentile values of the five dimensions and the spatial coordinate values of the space points are obtained, and used to reconstruct percentile buttock models. This research proposes a establishing method of percentile sizing system of buttock 3D model based on the percentile values of the ischial tuberosities diameter, the distances from margin to ischial tuberosity and the space coordinates value of coordinate points, for establishing the Nth percentile 3D buttock model and every special buttock types model. The proposed method also serves as a useful guidance for the other 3D percentile models establishment for other part in human body with characteristic points.

  15. Analysis of extreme top event frequency percentiles based on fast probability integration

    SciTech Connect

    Staple, B.; Haskin, F.E.

    1993-10-01

    In risk assessments, a primary objective is to determine the frequency with which a collection of initiating and basic events, E{sub e} leads to some undesired top event, T. Uncertainties in the occurrence rates, x{sub t}, assigned to the initiating and basic events cause uncertainty in the top event frequency, z{sub T}. The quantification of the uncertainty in z{sub T} is an essential part of risk assessment called uncertainty analysis. In the past, it has been difficult to evaluate the extreme percentiles of output variables like z{sub T}. Analytic methods such as the method of moments do not provide estimates of output percentiles and the Monte Carlo (MC) method can be used to estimate extreme output percentiles only by resorting to large sample sizes. A promising altemative to these methods is the fast probability integration (FPI) methods. These methods approximate the integrals of multi-variate functions, representing percentiles of interest, without recourse to multi-dimensional numerical integration. FPI methods give precise results and have been demonstrated to be more efficient than MC methods for estimating extreme output percentiles. FPI allows the analyst to choose extreme percentiles of interest and perform sensitivity analyses in those regions. Such analyses can provide valuable insights as to the events driving the top event frequency response in extreme probability regions. In this paper, FPI methods are adapted a) to precisely estimate extreme top event frequency percentiles and b) to allow the quantification of sensitivity measures at these extreme percentiles. In addition, the relative precision and efficiency of alternative methods for treating lognormally distributed inputs is investigated. The methodology is applied to the top event frequency expression for the dominant accident sequence from a risk assessment of Grand Gulf nuclear power plant.

  16. A Novel Hepatocellular Carcinoma Image Classification Method Based on Voting Ranking Random Forests

    PubMed Central

    Xia, Bingbing; Jiang, Huiyan; Liu, Huiling; Yi, Dehui

    2016-01-01

    This paper proposed a novel voting ranking random forests (VRRF) method for solving hepatocellular carcinoma (HCC) image classification problem. Firstly, in preprocessing stage, this paper used bilateral filtering for hematoxylin-eosin (HE) pathological images. Next, this paper segmented the bilateral filtering processed image and got three different kinds of images, which include single binary cell image, single minimum exterior rectangle cell image, and single cell image with a size of n⁎n. After that, this paper defined atypia features which include auxiliary circularity, amendment circularity, and cell symmetry. Besides, this paper extracted some shape features, fractal dimension features, and several gray features like Local Binary Patterns (LBP) feature, Gray Level Cooccurrence Matrix (GLCM) feature, and Tamura features. Finally, this paper proposed a HCC image classification model based on random forests and further optimized the model by voting ranking method. The experiment results showed that the proposed features combined with VRRF method have a good performance in HCC image classification problem. PMID:27293477

  17. Comparison of Krylov subspace methods on the PageRank problem

    NASA Astrophysics Data System (ADS)

    Del Corso, Gianna M.; Gulli, Antonio; Romani, Francesco

    2007-12-01

    PageRank algorithm plays a very important role in search engine technology and consists in the computation of the eigenvector corresponding to the eigenvalue one of a matrix whose size is now in the billions. The problem incorporates a parameter [alpha] that determines the difficulty of the problem. In this paper, the effectiveness of stationary and nonstationary methods are compared on some portion of real web matrices for different choices of [alpha]. We see that stationary methods are very reliable and more competitive when the problem is well conditioned, that is for small values of [alpha]. However, for large values of the parameter [alpha] the problem becomes more difficult and methods such as preconditioned BiCGStab or restarted preconditioned GMRES become competitive with stationary methods in terms of Mflops count as well as in number of iterations necessary to reach convergence.

  18. Hypothesis Testing of Population Percentiles via the Wald Test with Bootstrap Variance Estimates

    PubMed Central

    Johnson, William D.; Romer, Jacob E.

    2016-01-01

    Testing the equality of percentiles (quantiles) between populations is an effective method for robust, nonparametric comparison, especially when the distributions are asymmetric or irregularly shaped. Unlike global nonparametric tests for homogeneity such as the Kolmogorv-Smirnov test, testing the equality of a set of percentiles (i.e., a percentile profile) yields an estimate of the location and extent of the differences between the populations along the entire domain. The Wald test using bootstrap estimates of variance of the order statistics provides a unified method for hypothesis testing of functions of the population percentiles. Simulation studies are conducted to show performance of the method under various scenarios and to give suggestions on its use. Several examples are given to illustrate some useful applications to real data. PMID:27034909

  19. Multi-dimensional evaluation and ranking of coastal areas using GIS and multiple criteria choice methods.

    PubMed

    Kitsiou, Dimitra; Coccossis, Harry; Karydis, Michael

    2002-02-01

    Coastal ecosystems are increasingly threatened by short-sighted management policies that focus on human activities rather than the systems that sustain them. The early assessment of the impacts of human activities on the quality of the environment in coastal areas is important for decision-making, particularly in cases of environment/development conflicts, such as environmental degradation and saturation in tourist areas. In the present study, a methodology was developed for the multi-dimensional evaluation and ranking of coastal areas using a set of criteria and based on the combination of multiple criteria choice methods and Geographical Information Systems (GIS). The northeastern part of the island of Rhodes in the Aegean Sea, Greece was the case study area. A distinction in sub-areas was performed and they were ranked according to socio-economic and environmental parameters. The robustness of the proposed methodology was assessed using different configurations of the initial criteria and reapplication of the process. The advantages and disadvantages, as well as the usefulness of this methodology for comparing the status of coastal areas and evaluating their potential for further development based on various criteria, is further discussed. PMID:11846155

  20. mtDNA analysis of 174 Eurasian populations using a new iterative rank correlation method.

    PubMed

    Juhász, Zoltán; Fehér, Tibor; Németh, Endre; Pamjav, Horolma

    2016-02-01

    In this study, we analyse 27-dimensional mtDNA haplogroup distributions of 174 Eurasian, North-African and American populations, including numerous ancient data as well. The main contribution of this work was the description of the haplogroup distribution of recent and ancient populations as compounds of certain hypothetic ancient core populations immediately or indirectly determining the migration processes in Eurasia for a long time. To identify these core populations, we developed a new iterative algorithm determining clusters of the 27 mtDNA haplogroups studied having strong rank correlation among each other within a definite subset of the populations. Based on this study, the current Eurasian populations can be considered as compounds of three early core populations regarding to maternal lineages. We wanted to show that a simultaneous analysis of ancient and recent data using a new iterative rank correlation algorithm and the weighted SOC learning technique may reveal the most important and deterministic migration processes in the past. This technique allowed us to determine geographically, historically and linguistically well-interpretable clusters of our dataset having a very specific, hardly classifiable structure. The method was validated using a 2-dimensional stepping stone model. PMID:26142878

  1. Probability Elicitation Under Severe Time Pressure: A Rank-Based Method.

    PubMed

    Jaspersen, Johannes G; Montibeller, Gilberto

    2015-07-01

    Probability elicitation protocols are used to assess and incorporate subjective probabilities in risk and decision analysis. While most of these protocols use methods that have focused on the precision of the elicited probabilities, the speed of the elicitation process has often been neglected. However, speed is also important, particularly when experts need to examine a large number of events on a recurrent basis. Furthermore, most existing elicitation methods are numerical in nature, but there are various reasons why an expert would refuse to give such precise ratio-scale estimates, even if highly numerate. This may occur, for instance, when there is lack of sufficient hard evidence, when assessing very uncertain events (such as emergent threats), or when dealing with politicized topics (such as terrorism or disease outbreaks). In this article, we adopt an ordinal ranking approach from multicriteria decision analysis to provide a fast and nonnumerical probability elicitation process. Probabilities are subsequently approximated from the ranking by an algorithm based on the principle of maximum entropy, a rule compatible with the ordinal information provided by the expert. The method can elicit probabilities for a wide range of different event types, including new ways of eliciting probabilities for stochastically independent events and low-probability events. We use a Monte Carlo simulation to test the accuracy of the approximated probabilities and try the method in practice, applying it to a real-world risk analysis recently conducted for DEFRA (the U.K. Department for the Environment, Farming and Rural Affairs): the prioritization of animal health threats. PMID:25850859

  2. SITE RANK

    EPA Science Inventory

    Site rank is formulated for ranking the relative hazard of contamination sources and vulnerability of drinking water wells. Site rank can be used with a variety of groundwater flow and transport models.

  3. Analysis of performance measures with single channel fuzzy queues under two class by using ranking method

    NASA Astrophysics Data System (ADS)

    Mueen, Zeina; Ramli, Razamin; Zaibidi, Nerda Zura

    2016-08-01

    In this paper, we propose a procedure to find different performance measurements under crisp value terms for new single fuzzy queue FM/F(H1,H2)/1 with two classes, where arrival rate and service rates are all fuzzy numbers which are represented by triangular and trapezoidal fuzzy numbers. The basic idea is to obtain exact crisp values from the fuzzy value, which is more realistic in the practical queueing system. This is done by adopting left and right ranking method to remove the fuzziness before computing the performance measurements using conventional queueing theory. The main advantage of this approach is its simplicity in application, giving exact real data around fuzzy values. This approach can also be used in all types of queueing systems by taking two types of symmetrical linear membership functions. Numerical illustration is solved in this article to obtain two groups of crisp values in the queueing system under consideration.

  4. Reference Genes Selection for Quantitative Real-Time PCR Using RankAggreg Method in Different Tissues of Capra hircus

    PubMed Central

    Najafpanah, Mohammad Javad; Sadeghi, Mostafa; Bakhtiarizadeh, Mohammad Reza

    2013-01-01

    Identification of reference genes with stable levels of gene expression is an important prerequisite for obtaining reliable results in analysis of gene expression data using quantitative real time PCR (RT-qPCR). Since the underlying assumption of reference genes is that expressed at the exact same level in all sample types, in this study, we evaluated the expression stability of nine most commonly used endogenous controls (GAPDH, ACTB, 18S rRNA, RPS18, HSP-90, ALAS, HMBS, ACAC, and B2M) in four different tissues of the domestic goat, Capra hircus, including liver, visceral, subcutaneous fat and longissimus muscles, across different experimental treatments (a standard diet prepared using the NRC computer software as control and the same diet plus one mg chromium/day). We used six different software programs for ranking of reference genes and found that individual rankings of the genes differed among them. Additionally, there was a significant difference in ranking patterns of the studied genes among different tissues. A rank aggregation method was applied to combine the ranking lists of the six programs to a consensus ranking. Our results revealed that HSP-90 was nearly always among the two most stable genes in all studied tissues. Therefore, it is recommended for accurate normalization of RT-qPCR data in goats, while GAPDH, ACTB, and RPS18 showed the most varied expressions and should be avoided as reference genes. PMID:24358246

  5. A finite field method for calculating molecular polarizability tensors for arbitrary multipole rank.

    PubMed

    Elking, Dennis M; Perera, Lalith; Duke, Robert; Darden, Thomas; Pedersen, Lee G

    2011-11-30

    A finite field method for calculating spherical tensor molecular polarizability tensors α(lm;l'm') = ∂Δ(lm)/∂ϕ(l'm')* by numerical derivatives of induced molecular multipole Δ(lm) with respect to gradients of electrostatic potential ϕ(l'm')* is described for arbitrary multipole ranks l and l'. Interconversion formulae for transforming multipole moments and polarizability tensors between spherical and traceless Cartesian tensor conventions are derived. As an example, molecular polarizability tensors up to the hexadecapole-hexadecapole level are calculated for water using the following ab initio methods: Hartree-Fock (HF), Becke three-parameter Lee-Yang-Parr exchange-correlation functional (B3LYP), Møller-Plesset perturbation theory up to second order (MP2), and Coupled Cluster theory with single and double excitations (CCSD). In addition, intermolecular electrostatic and polarization energies calculated by molecular multipoles and polarizability tensors are compared with ab initio reference values calculated by the Reduced Variation Space method for several randomly oriented small molecule dimers separated by a large distance. It is discussed how higher order molecular polarizability tensors can be used as a tool for testing and developing new polarization models for future force fields. PMID:21915883

  6. A communication-avoiding, hybrid-parallel, rank-revealing orthogonalization method.

    SciTech Connect

    Hoemmen, Mark

    2010-11-01

    Orthogonalization consumes much of the run time of many iterative methods for solving sparse linear systems and eigenvalue problems. Commonly used algorithms, such as variants of Gram-Schmidt or Householder QR, have performance dominated by communication. Here, 'communication' includes both data movement between the CPU and memory, and messages between processors in parallel. Our Tall Skinny QR (TSQR) family of algorithms requires asymptotically fewer messages between processors and data movement between CPU and memory than typical orthogonalization methods, yet achieves the same accuracy as Householder QR factorization. Furthermore, in block orthogonalizations, TSQR is faster and more accurate than existing approaches for orthogonalizing the vectors within each block ('normalization'). TSQR's rank-revealing capability also makes it useful for detecting deflation in block iterative methods, for which existing approaches sacrifice performance, accuracy, or both. We have implemented a version of TSQR that exploits both distributed-memory and shared-memory parallelism, and supports real and complex arithmetic. Our implementation is optimized for the case of orthogonalizing a small number (5-20) of very long vectors. The shared-memory parallel component uses Intel's Threading Building Blocks, though its modular design supports other shared-memory programming models as well, including computation on the GPU. Our implementation achieves speedups of 2 times or more over competing orthogonalizations. It is available now in the development branch of the Trilinos software package, and will be included in the 10.8 release.

  7. A Spatial Overlay Ranking Method for a Geospatial Search of Text Objects

    USGS Publications Warehouse

    Lanfear, Kenneth J.

    2006-01-01

    Earth-science researchers need the capability to find relevant information by location and topic. Conventional geographic techniques that simply check whether polygons intersect can efficiently achieve a high recall on location, but can not achieve precision for ranking results in likely order of importance to the reader. A spatial overlay ranking based upon how well an object's footprint matches the search area provides a more effective way to spatially search a collection of reports, and avoids many of the problems associated with an 'in/out' (True/False) boolean search. Moreover, spatial overlay ranking appears to work well even when spatial extent is defined only by a simple bounding box.

  8. A Finite Field Method for Calculating Molecular Polarizability Tensors for Arbitrary Multipole Rank

    PubMed Central

    Elking, Dennis M.; Perera, Lalith; Duke, Robert; Darden, Thomas; Pedersen, Lee G.

    2011-01-01

    A finite field method for calculating spherical tensor molecular polarizability tensors αlm;l′m′ = ∂Δlm/∂ϕl′m′* by numerical derivatives of induced molecular multipole Δlm with respect to gradients of electrostatic potential ϕl′m′* is described for arbitrary multipole ranks l and l′. Inter-conversion formulae for transforming multipole moments and polarizability tensors between spherical and traceless Cartesian tensor conventions are derived. As an example, molecular polarizability tensors up to the hexadecapole-hexadecapole level are calculated for water at the HF, B3LYP, MP2, and CCSD levels. In addition, inter-molecular electrostatic and polarization energies calculated by molecular multipoles and polarizability tensors are compared to ab initio reference values calculated by the Reduced Variation Space (RVS) method for several randomly oriented small molecule dimers separated by a large distance. It is discussed how higher order molecular polarizability tensors can be used as a tool for testing and developing new polarization models for future force fields. PMID:21915883

  9. A Z-number-based decision making procedure with ranking fuzzy numbers method

    NASA Astrophysics Data System (ADS)

    Mohamad, Daud; Shaharani, Saidatull Akma; Kamis, Nor Hanimah

    2014-12-01

    The theory of fuzzy set has been in the limelight of various applications in decision making problems due to its usefulness in portraying human perception and subjectivity. Generally, the evaluation in the decision making process is represented in the form of linguistic terms and the calculation is performed using fuzzy numbers. In 2011, Zadeh has extended this concept by presenting the idea of Z-number, a 2-tuple fuzzy numbers that describes the restriction and the reliability of the evaluation. The element of reliability in the evaluation is essential as it will affect the final result. Since this concept can still be considered as new, available methods that incorporate reliability for solving decision making problems is still scarce. In this paper, a decision making procedure based on Z-numbers is proposed. Due to the limitation of its basic properties, Z-numbers will be first transformed to fuzzy numbers for simpler calculations. A method of ranking fuzzy number is later used to prioritize the alternatives. A risk analysis problem is presented to illustrate the effectiveness of this proposed procedure.

  10. Global adaptive rank truncated product method for gene-set analysis in association studies.

    PubMed

    Vilor-Tejedor, Natalia; Calle, M Luz

    2014-08-01

    Gene set analysis (GSA) aims to assess the overall association of a set of genetic variants with a phenotype and has the potential to detect subtle effects of variants in a gene or a pathway that might be missed when assessed individually. We present a new implementation of the Adaptive Rank Truncated Product method (ARTP) for analyzing the association of a set of Single Nucleotide Polymorphisms (SNPs) in a gene or pathway. The new implementation, referred to as globalARTP, improves the original one by allowing the different SNPs in the set to have different modes of inheritance. We perform a simulation study for exploring the power of the proposed methodology in a set of scenarios with different numbers of causal SNPs with different effect sizes. Moreover, we show the advantage of using the gene set approach in the context of an Alzheimer's disease case-control study where we explore the endocytosis pathway. The new method is implemented in the R function globalARTP of the globalGSA package available at http://cran.r-project.org. PMID:25082012

  11. Reduced-rank approximations to the far-field transform in the gridded fast multipole method

    NASA Astrophysics Data System (ADS)

    Hesford, Andrew J.; Waag, Robert C.

    2011-05-01

    The fast multipole method (FMM) has been shown to have a reduced computational dependence on the size of finest-level groups of elements when the elements are positioned on a regular grid and FFT convolution is used to represent neighboring interactions. However, transformations between plane-wave expansions used for FMM interactions and pressure distributions used for neighboring interactions remain significant contributors to the cost of FMM computations when finest-level groups are large. The transformation operators, which are forward and inverse Fourier transforms with the wave space confined to the unit sphere, are smooth and well approximated using reduced-rank decompositions that further reduce the computational dependence of the FMM on finest-level group size. The adaptive cross approximation (ACA) is selected to represent the forward and adjoint far-field transformation operators required by the FMM. However, the actual error of the ACA is found to be greater than that predicted using traditional estimates, and the ACA generally performs worse than the approximation resulting from a truncated singular-value decomposition (SVD). To overcome these issues while avoiding the cost of a full-scale SVD, the ACA is employed with more stringent accuracy demands and recompressed using a reduced, truncated SVD. The results show a greatly reduced approximation error that performs comparably to the full-scale truncated SVD without degrading the asymptotic computational efficiency associated with ACA matrix assembly.

  12. RAMPART (TM): Risk Assessment Method-Property Analysis and Ranking Tool v.4.0

    SciTech Connect

    2007-09-30

    RAMPART{trademark}, Risk Assessment Method-property Analysis and Ranking Tool, is a new type of computer software package for the assessment of risk to buildings. RAMPART{trademark} has been developed by Sandia National Laboratories (SNL) for the U.S. General Services Administration (GSA). RAMPART {trademark} has been designed and developed to be a risk-based decision support tool that requires no risk analysis expertise on the part of the user. The RAMPART{trademark} user interface elicits information from the user about the building. The RAMPART{trademark} expert system is a set of rules that embodies GSA corporate knowledge and SNL's risk assessment experience. The RAMPART{trademark} database contains both data entered by the user during a building analysis session and large sets of natural hazard and crime data. RAMPART{trademark} algorithms use these data to assess the risk associated with a given building in the face of certain hazards. Risks arising from five natural hazards (earthquake, hurricane, winter storm, tornado and flood); crime (inside and outside the building); fire and terrorism are calculated. These hazards may cause losses of various kinds. RAMPART{trademark} considers death, injury, loss of mission, loss of property, loss of contents, loss of building use, and first-responder loss. The results of each analysis are presented graphically on the screen and in a written report.

  13. RAMPART (TM): Risk Assessment Method-Property Analysis and Ranking Tool v.4.0

    Energy Science and Technology Software Center (ESTSC)

    2007-09-30

    RAMPART{trademark}, Risk Assessment Method-property Analysis and Ranking Tool, is a new type of computer software package for the assessment of risk to buildings. RAMPART{trademark} has been developed by Sandia National Laboratories (SNL) for the U.S. General Services Administration (GSA). RAMPART {trademark} has been designed and developed to be a risk-based decision support tool that requires no risk analysis expertise on the part of the user. The RAMPART{trademark} user interface elicits information from the user aboutmore » the building. The RAMPART{trademark} expert system is a set of rules that embodies GSA corporate knowledge and SNL's risk assessment experience. The RAMPART{trademark} database contains both data entered by the user during a building analysis session and large sets of natural hazard and crime data. RAMPART{trademark} algorithms use these data to assess the risk associated with a given building in the face of certain hazards. Risks arising from five natural hazards (earthquake, hurricane, winter storm, tornado and flood); crime (inside and outside the building); fire and terrorism are calculated. These hazards may cause losses of various kinds. RAMPART{trademark} considers death, injury, loss of mission, loss of property, loss of contents, loss of building use, and first-responder loss. The results of each analysis are presented graphically on the screen and in a written report.« less

  14. A value and ambiguity-based ranking method of trapezoidal intuitionistic fuzzy numbers and application to decision making.

    PubMed

    Zeng, Xiang-tian; Li, Deng-feng; Yu, Gao-feng

    2014-01-01

    The aim of this paper is to develop a method for ranking trapezoidal intuitionistic fuzzy numbers (TrIFNs) in the process of decision making in the intuitionistic fuzzy environment. Firstly, the concept of TrIFNs is introduced. Arithmetic operations and cut sets over TrIFNs are investigated. Then, the values and ambiguities of the membership degree and the nonmembership degree for TrIFNs are defined as well as the value-index and ambiguity-index. Finally, a value and ambiguity-based ranking method is developed and applied to solve multiattribute decision making problems in which the ratings of alternatives on attributes are expressed using TrIFNs. A numerical example is examined to demonstrate the implementation process and applicability of the method proposed in this paper. Furthermore, comparison analysis of the proposed method is conducted to show its advantages over other similar methods. PMID:25147854

  15. Lanczos-based Low-Rank Correction Method for Solving the Dyson Equation in Inhomogenous Dynamical Mean-Field Theory

    NASA Astrophysics Data System (ADS)

    Carrier, Pierre; Tang, Jok M.; Saad, Yousef; Freericks, James K.

    Inhomogeneous dynamical mean-field theory has been employed to solve many interesting strongly interacting problems from transport in multilayered devices to the properties of ultracold atoms in a trap. The main computational step, especially for large systems, is the problem of calculating the inverse of a large sparse matrix to solve Dyson's equation and determine the local Green's function at each lattice site from the corresponding local self-energy. We present a new e_cient algorithm, the Lanczos-based low-rank algorithm, for the calculation of the inverse of a large sparse matrix which yields this local (imaginary time) Green's function. The Lanczos-based low-rank algorithm is based on a domain decomposition viewpoint, but avoids explicit calculation of Schur complements and relies instead on low-rank matrix approximations derived from the Lanczos algorithm, for solving the Dyson equation. We report at least a 25-fold improvement of performance compared to explicit decomposition (such as sparse LU) of the matrix inverse. We also report that scaling relative to matrix sizes, of the low-rank correction method on the one hand and domain decomposition methods on the other, are comparable.

  16. Davidon-Broyden rank-one minimization methods in Hilbert space with application to optimal control problems

    NASA Technical Reports Server (NTRS)

    Straeter, T. A.

    1972-01-01

    The Davidon-Broyden class of rank one, quasi-Newton minimization methods is extended from Euclidean spaces to infinite-dimensional, real Hilbert spaces. For several techniques of choosing the step size, conditions are found which assure convergence of the associated iterates to the location of the minimum of a positive definite quadratic functional. For those techniques, convergence is achieved without the problem of the computation of a one-dimensional minimum at each iteration. The application of this class of minimization methods for the direct computation of the solution of an optimal control problem is outlined. The performance of various members of the class are compared by solving a sample optimal control problem. Finally, the sample problem is solved by other known gradient methods, and the results are compared with those obtained with the rank one quasi-Newton methods.

  17. Rank Dynamics

    NASA Astrophysics Data System (ADS)

    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

  18. Combinatoric Models of Information Retrieval Ranking Methods and Performance Measures for Weakly-Ordered Document Collections

    ERIC Educational Resources Information Center

    Church, Lewis

    2010-01-01

    This dissertation answers three research questions: (1) What are the characteristics of a combinatoric measure, based on the Average Search Length (ASL), that performs the same as a probabilistic version of the ASL?; (2) Does the combinatoric ASL measure produce the same performance result as the one that is obtained by ranking a collection of…

  19. Semantic descriptor ranking: a quantitative method for evaluating qualitative verbal reports of visual cognition in the laboratory or the clinic

    PubMed Central

    Maestri, Matthew; Odel, Jeffrey; Hegdé, Jay

    2014-01-01

    For scientific, clinical, and machine learning purposes alike, it is desirable to quantify the verbal reports of high-level visual percepts. Methods to do this simply do not exist at present. Here we propose a novel methodological principle to help fill this gap, and provide empirical evidence designed to serve as the initial “proof” of this principle. In the proposed method, subjects view images of real-world scenes and describe, in their own words, what they saw. The verbal description is independently evaluated by several evaluators. Each evaluator assigns a rank score to the subject’s description of each visual object in each image using a novel ranking principle, which takes advantage of the well-known fact that semantic descriptions of real life objects and scenes can usually be rank-ordered. Thus, for instance, “animal,” “dog,” and “retriever” can be regarded as increasingly finer-level, and therefore higher ranking, descriptions of a given object. These numeric scores can preserve the richness of the original verbal description, and can be subsequently evaluated using conventional statistical procedures. We describe an exemplar implementation of this method and empirical data that show its feasibility. With appropriate future standardization and validation, this novel method can serve as an important tool to help quantify the subjective experience of the visual world. In addition to being a novel, potentially powerful testing tool, our method also represents, to our knowledge, the only available method for numerically representing verbal accounts of real-world experience. Given that its minimal requirements, i.e., a verbal description and the ground truth that elicited the description, our method has a wide variety of potential real-world applications. PMID:24624102

  20. Estimation of a monotone percentile residual life function under random censorship.

    PubMed

    Franco-Pereira, Alba M; de Uña-Álvarez, Jacobo

    2013-01-01

    In this paper, we introduce a new estimator of a percentile residual life function with censored data under a monotonicity constraint. Specifically, it is assumed that the percentile residual life is a decreasing function. This assumption is useful when estimating the percentile residual life of units, which degenerate with age. We establish a law of the iterated logarithm for the proposed estimator, and its n-equivalence to the unrestricted estimator. The asymptotic normal distribution of the estimator and its strong approximation to a Gaussian process are also established. We investigate the finite sample performance of the monotone estimator in an extensive simulation study. Finally, data from a clinical trial in primary biliary cirrhosis of the liver are analyzed with the proposed methods. One of the conclusions of our work is that the restricted estimator may be much more efficient than the unrestricted one. PMID:23225621

  1. A Comparison of Growth Percentile and Value-Added Models of Teacher Performance. Working Paper #39

    ERIC Educational Resources Information Center

    Guarino, Cassandra M.; Reckase, Mark D.; Stacy, Brian W.; Wooldridge, Jeffrey M.

    2014-01-01

    School districts and state departments of education frequently must choose between a variety of methods to estimating teacher quality. This paper examines under what circumstances the decision between estimators of teacher quality is important. We examine estimates derived from student growth percentile measures and estimates derived from commonly…

  2. Questioning the method and utility of ranking drug harms in drug policy.

    PubMed

    Rolles, Stephen; Measham, Fiona

    2011-07-01

    In a 2010 Lancet paper Nutt et al. propose a model for evaluating and ranking drug harms, building on earlier work by incorporating multi criteria decision analysis. It is argued that problems arise in modelling drug harms using rankable single figure indices when determinants of harm reflect pharmacology translated through a complex prism of social and behavioural variables, in turn influenced by a range of policy environments. The delphic methodolgy used is highly vulnerable to subjective judgements and even the more robust measures, such as drug related death and dependence, can be understood as socially constructed. The failure of the model to dissaggregate drug use harms from those related to the policy environment is also highlighted. Beyond these methodological challenges the utility of single figure index harm rankings is questioned, specifically their role in increasingly redundant legal frameworks utilising a harm-based hierarchy of punitive sanctions. If analysis is to include the capacity to capture the complexity relating to drug using behaviours and environments; specific personal and social risks for particular using populations; and the broader socio-cultural context to contemporary intoxication, there will need to be acceptance that analysis of the various harm vectors must remain separate - the complexity of such analysis is not something that can or should be over generalised to suit political discourse or outdated legal frameworks. PMID:21652195

  3. Birthweight percentiles for twin birth neonates by gestational age in China.

    PubMed

    Zhang, Bin; Cao, Zhongqiang; Zhang, Yiming; Yao, Cong; Xiong, Chao; Zhang, Yaqi; Wang, Youjie; Zhou, Aifen

    2016-01-01

    Localized birthweight references for gestational ages serve as an essential tool in accurate evaluation of atypical birth outcomes. Such references for twin births are currently not available in China. The aim of this study was to construct up-to-data sex specific birth weight references by gestational ages for twin births in China. We conducted a population-based analysis on the data of 22,507 eligible living twin infants with births dated between 8/01/2006 and 8/31/2015 from all 95 hospitals within the Wuhan area. Gestational ages in complete weeks were determined using a combination of last-menstrual-period based (LMP) estimation and ultrasound examination. Smoothed percentile curves were created by the Lambda Mu Sigma (LMS) method. Reference of the 3(rd), 10(th), 25(th), 50(th), 75(th), 90(th), 97(th) percentiles birth weight by sex and gestational age were made using 11,861 male and 10,646 female twin newborns with gestational age 26-42 weeks. Separate birthweight percentiles curves for male and female twins were constructed. In summary, our study firstly presents percentile curves of birthweight by gestational age for Chinese twin neonates. Further research is required for the validation and implementation of twin birthweight curves into clinical practice. PMID:27506479

  4. Birthweight percentiles for twin birth neonates by gestational age in China

    PubMed Central

    Zhang, Bin; Cao, Zhongqiang; Zhang, Yiming; Yao, Cong; Xiong, Chao; Zhang, Yaqi; Wang, Youjie; Zhou, Aifen

    2016-01-01

    Localized birthweight references for gestational ages serve as an essential tool in accurate evaluation of atypical birth outcomes. Such references for twin births are currently not available in China. The aim of this study was to construct up-to-data sex specific birth weight references by gestational ages for twin births in China. We conducted a population-based analysis on the data of 22,507 eligible living twin infants with births dated between 8/01/2006 and 8/31/2015 from all 95 hospitals within the Wuhan area. Gestational ages in complete weeks were determined using a combination of last-menstrual-period based (LMP) estimation and ultrasound examination. Smoothed percentile curves were created by the Lambda Mu Sigma (LMS) method. Reference of the 3rd, 10th, 25th, 50th, 75th, 90th, 97th percentiles birth weight by sex and gestational age were made using 11,861 male and 10,646 female twin newborns with gestational age 26–42 weeks. Separate birthweight percentiles curves for male and female twins were constructed. In summary, our study firstly presents percentile curves of birthweight by gestational age for Chinese twin neonates. Further research is required for the validation and implementation of twin birthweight curves into clinical practice. PMID:27506479

  5. Bootstrap rank-ordered conditional mutual information (broCMI): A nonlinear input variable selection method for water resources modeling

    NASA Astrophysics Data System (ADS)

    Quilty, John; Adamowski, Jan; Khalil, Bahaa; Rathinasamy, Maheswaran

    2016-03-01

    The input variable selection problem has recently garnered much interest in the time series modeling community, especially within water resources applications, demonstrating that information theoretic (nonlinear)-based input variable selection algorithms such as partial mutual information (PMI) selection (PMIS) provide an improved representation of the modeled process when compared to linear alternatives such as partial correlation input selection (PCIS). PMIS is a popular algorithm for water resources modeling problems considering nonlinear input variable selection; however, this method requires the specification of two nonlinear regression models, each with parametric settings that greatly influence the selected input variables. Other attempts to develop input variable selection methods using conditional mutual information (CMI) (an analog to PMI) have been formulated under different parametric pretenses such as k nearest-neighbor (KNN) statistics or kernel density estimates (KDE). In this paper, we introduce a new input variable selection method based on CMI that uses a nonparametric multivariate continuous probability estimator based on Edgeworth approximations (EA). We improve the EA method by considering the uncertainty in the input variable selection procedure by introducing a bootstrap resampling procedure that uses rank statistics to order the selected input sets; we name our proposed method bootstrap rank-ordered CMI (broCMI). We demonstrate the superior performance of broCMI when compared to CMI-based alternatives (EA, KDE, and KNN), PMIS, and PCIS input variable selection algorithms on a set of seven synthetic test problems and a real-world urban water demand (UWD) forecasting experiment in Ottawa, Canada.

  6. How to Rank Journals

    PubMed Central

    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. PMID:26930052

  7. How to Rank Journals.

    PubMed

    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. PMID:26930052

  8. Sum of ranking differences (SRD) to ensemble multivariate calibration model merits for tuning parameter selection and comparing calibration methods.

    PubMed

    Kalivas, John H; Héberger, Károly; Andries, Erik

    2015-04-15

    Most multivariate calibration methods require selection of tuning parameters, such as partial least squares (PLS) or the Tikhonov regularization variant ridge regression (RR). Tuning parameter values determine the direction and magnitude of respective model vectors thereby setting the resultant predication abilities of the model vectors. Simultaneously, tuning parameter values establish the corresponding bias/variance and the underlying selectivity/sensitivity tradeoffs. Selection of the final tuning parameter is often accomplished through some form of cross-validation and the resultant root mean square error of cross-validation (RMSECV) values are evaluated. However, selection of a "good" tuning parameter with this one model evaluation merit is almost impossible. Including additional model merits assists tuning parameter selection to provide better balanced models as well as allowing for a reasonable comparison between calibration methods. Using multiple merits requires decisions to be made on how to combine and weight the merits into an information criterion. An abundance of options are possible. Presented in this paper is the sum of ranking differences (SRD) to ensemble a collection of model evaluation merits varying across tuning parameters. It is shown that the SRD consensus ranking of model tuning parameters allows automatic selection of the final model, or a collection of models if so desired. Essentially, the user's preference for the degree of balance between bias and variance ultimately decides the merits used in SRD and hence, the tuning parameter values ranked lowest by SRD for automatic selection. The SRD process is also shown to allow simultaneous comparison of different calibration methods for a particular data set in conjunction with tuning parameter selection. Because SRD evaluates consistency across multiple merits, decisions on how to combine and weight merits are avoided. To demonstrate the utility of SRD, a near infrared spectral data set and a

  9. Examining the Reliability of Student Growth Percentiles Using Multidimensional IRT

    ERIC Educational Resources Information Center

    Monroe, Scott; Cai, Li

    2015-01-01

    Student growth percentiles (SGPs, Betebenner, 2009) are used to locate a student's current score in a conditional distribution based on the student's past scores. Currently, following Betebenner (2009), quantile regression (QR) is most often used operationally to estimate the SGPs. Alternatively, multidimensional item response theory (MIRT) may…

  10. Method and algorithm of ranking boiler plants at block electric power stations by the criterion of operation reliability and profitability

    NASA Astrophysics Data System (ADS)

    Farhadzadeh, E. M.; Muradaliyev, A. Z.; Farzaliyev, Y. Z.

    2015-10-01

    A method and an algorithm of ranking of boiler installations based on their technical and economic indicators are proposed. One of the basic conditions for ranking is the independence of technical and economic indicators. The assessment of their interrelation was carried out with respect to the correlation rate. The analysis of calculation data has shown that the interrelation stability with respect to the value and sign persists only for those indicators that have an evident relationship between each other. One of the calculation steps is the normalization of quantitative estimates of technical and economic indicators, which makes it possible to eliminate differences in dimensions and indicator units. The analysis of the known methods of normalization has allowed one to recommend the relative deviation from the average value as a normalized value and to use the arithmetic mean of the normalized values of independent indicators of each boiler installation as an integrated index of performance reliability and profitability. The fundamental differences from the existing approach to assess the "weak components" of a boiler installation and the quality of monitoring of its operating regimes are that the given approach takes into account the reliability and profitability of the operation of all other analogous boiler installations of an electric power station; it also implements competing elements with respect to the quality of control among the operating personnel of separate boiler installations and is aimed at encouraging an increased quality of maintenance and repairs.

  11. A novel homogenization method for phase field approaches based on partial rank-one relaxation

    NASA Astrophysics Data System (ADS)

    Mosler, J.; Shchyglo, O.; Montazer Hojjat, H.

    2014-08-01

    This paper deals with the analysis of homogenization assumptions within phase field theories in a finite strain setting. Such homogenization assumptions define the average bulk's energy within the diffusive interface region where more than one phase co-exist. From a physical point of view, a correct computation of these energies is essential, since they define the driving force of material interfaces between different phases. The three homogenization assumptions considered in this paper are: (a) Voigt/Taylor model, (b) Reuss/Sachs model, and (c) Khachaturyan model. It is shown that these assumptions indeed share some similarities and sometimes lead to the same results. However, they are not equivalent. Only two of them allow the computation of the individual energies of the co-existing phases even within the aforementioned diffusive interface region: the Voigt/Taylor and the Reuss/Sachs model. Such a localization of the averaged energy is important in order to determine and to subsequently interpret the driving force at the interface. Since the Voigt/Taylor and the Reuss/Sachs model are known to be relatively restrictive in terms of kinematics (Voigt/Taylor) and linear momentum (Reuss/Sachs), a novel homogenization approach is advocated. Within a variational setting based on (incremental) energy minimization, the results predicted by the novel approach are bounded by those corresponding to the Voigt/Taylor and the Reuss/Sachs model. The new approach fulfills equilibrium at material interfaces (continuity of the stress vector) and it is kinematically compatible. In sharp contrast to existing approaches, it naturally defines the mismatch energy at incoherent material interfaces. From a mathematical point of view, it can be interpreted as a partial rank-one convexification.

  12. Ecological vulnerability in wildlife: application of a species-ranking method to food chains and habitats.

    PubMed

    De Lange, Hendrika J; Lahr, Joost; Van der Pol, Joost J C; Faber, Jack H

    2010-12-01

    Nature development in The Netherlands is often planned on contaminated soils or sediments. This contamination may present a risk for wildlife species desired at those nature development sites and must be assessed by specific risk assessment methods. In a previous study, we developed a method to predict ecological vulnerability in wildlife species by using autecological data and expert judgment; in the current study, this method is further extended to assess ecological vulnerability of food chains and terrestrial and aquatic habitats typical for The Netherlands. The method is applied to six chemicals: Cd, Cu, Zn, dichlorodiphenyltrichloroethane, chlorpyrifos, and ivermectin. The results indicate that species in different food chains differ in vulnerability, with earthworm-based food chains the most vulnerable. Within and between food chains, vulnerability varied with habitat, particularly at low trophic levels. The concept of habitat vulnerability was applied to a case study of four different habitat types in floodplains contaminated with cadmium and zinc along the river Dommel, The Netherlands. The alder floodplain forest habitat contained the most vulnerable species. The differences among habitats were significant for Cd. We further conclude that the method has good potential for application in mapping of habitat vulnerability. PMID:20973107

  13. Estimated monthly percentile discharges at ungaged sites in the Upper Yellowstone River Basin in Montana

    USGS Publications Warehouse

    Parrett, Charles; Hull, J.A.

    1986-01-01

    Once-monthly streamflow measurements were used to estimate selected percentile discharges on flow-duration curves of monthly mean discharge for 40 ungaged stream sites in the upper Yellowstone River basin in Montana. The estimation technique was a modification of the concurrent-discharge method previously described and used by H.C. Riggs to estimate annual mean discharge. The modified technique is based on the relationship of various mean seasonal discharges to the required discharges on the flow-duration curves. The mean seasonal discharges are estimated from the monthly streamflow measurements, and the percentile discharges are calculated from regression equations. The regression equations, developed from streamflow record at nine gaging stations, indicated a significant log-linear relationship between mean seasonal discharge and various percentile discharges. The technique was tested at two discontinued streamflow-gaging stations; the differences between estimated monthly discharges and those determined from the discharge record ranged from -31 to +27 percent at one site and from -14 to +85 percent at the other. The estimates at one site were unbiased, and the estimates at the other site were consistently larger than the recorded values. Based on the test results, the probable average error of the technique was + or - 30 percent for the 21 sites measured during the first year of the program and + or - 50 percent for the 19 sites measured during the second year. (USGS)

  14. Percentile Distributions of Birth Weight according to Gestational Ages in Korea (2010-2012)

    PubMed Central

    2016-01-01

    The Pediatric Growth Chart (2007) is used as a standard reference to evaluate weight and height percentiles of Korean children and adolescents. Although several previous studies provided a useful reference range of newborn birth weight (BW) by gestational age (GA), the BW reference analyzed by sex and plurality is not currently available. Therefore, we aimed to establish a national reference range of neonatal BW percentiles considering GA, sex, and plurality of newborns in Korea. The raw data of all newborns (470,171 in 2010, 471,265 in 2011, and 484,550 in 2012) were analyzed. Using the Korean Statistical Information Service data (2010–2012), smoothed percentile curves (3rd–97th) by GA were created using the lambda-mu-sigma method after exclusion and the data were distinguished by all live births, singleton births, and multiple births. In the entire cohort, male newborns were heavier than female newborns and singletons were heavier than twins. As GA increased, the difference in BW between singleton and multiples increased. Compared to the previous data published 10 years ago in Korea, the BW of newborns 22–23 gestational weeks old was increased, whereas that of others was smaller. Other countries' data were also compared and showed differences in BW of both singleton and multiple newborns. We expect this updated data to be utilized as a reference to improve clinical assessments of newborn growth. PMID:27247504

  15. Percentile Distributions of Birth Weight according to Gestational Ages in Korea (2010-2012).

    PubMed

    Lee, Jin Kyoung; Jang, Hye Lim; Kang, Byung Ho; Lee, Kyung-Suk; Choi, Yong-Sung; Shim, Kye Shik; Lim, Jae Woo; Bae, Chong-Woo; Chung, Sung-Hoon

    2016-06-01

    The Pediatric Growth Chart (2007) is used as a standard reference to evaluate weight and height percentiles of Korean children and adolescents. Although several previous studies provided a useful reference range of newborn birth weight (BW) by gestational age (GA), the BW reference analyzed by sex and plurality is not currently available. Therefore, we aimed to establish a national reference range of neonatal BW percentiles considering GA, sex, and plurality of newborns in Korea. The raw data of all newborns (470,171 in 2010, 471,265 in 2011, and 484,550 in 2012) were analyzed. Using the Korean Statistical Information Service data (2010-2012), smoothed percentile curves (3(rd)-97(th)) by GA were created using the lambda-mu-sigma method after exclusion and the data were distinguished by all live births, singleton births, and multiple births. In the entire cohort, male newborns were heavier than female newborns and singletons were heavier than twins. As GA increased, the difference in BW between singleton and multiples increased. Compared to the previous data published 10 years ago in Korea, the BW of newborns 22-23 gestational weeks old was increased, whereas that of others was smaller. Other countries' data were also compared and showed differences in BW of both singleton and multiple newborns. We expect this updated data to be utilized as a reference to improve clinical assessments of newborn growth. PMID:27247504

  16. Bayes and empirical Bayes methods for reduced rank regression models in matched case-control studies

    PubMed Central

    Zhou, Qin; Lan, Qing; Rothman, Nathaniel; Langseth, Hilde; Engel, Lawrence S.

    2015-01-01

    Summary Matched case-control studies are popular designs used in epidemiology for assessing the effects of exposures on binary traits. Modern studies increasingly enjoy the ability to examine a large number of exposures in a comprehensive manner. However, several risk factors often tend to be related in a non-trivial way, undermining efforts to identify the risk factors using standard analytic methods due to inflated type I errors and possible masking of effects. Epidemiologists often use data reduction techniques by grouping the prognostic factors using a thematic approach, with themes deriving from biological considerations. We propose shrinkage type estimators based on Bayesian penalization methods to estimate the effects of the risk factors using these themes. The properties of the estimators are examined using extensive simulations. The methodology is illustrated using data from a matched case-control study of polychlorinflated biphenyls in relation to the etiology of non-Hodgkin’s lymphoma. PMID:26575519

  17. Bayes and empirical Bayes methods for reduced rank regression models in matched case-control studies.

    PubMed

    Satagopan, Jaya M; Sen, Ananda; Zhou, Qin; Lan, Qing; Rothman, Nathaniel; Langseth, Hilde; Engel, Lawrence S

    2016-06-01

    Matched case-control studies are popular designs used in epidemiology for assessing the effects of exposures on binary traits. Modern studies increasingly enjoy the ability to examine a large number of exposures in a comprehensive manner. However, several risk factors often tend to be related in a nontrivial way, undermining efforts to identify the risk factors using standard analytic methods due to inflated type-I errors and possible masking of effects. Epidemiologists often use data reduction techniques by grouping the prognostic factors using a thematic approach, with themes deriving from biological considerations. We propose shrinkage-type estimators based on Bayesian penalization methods to estimate the effects of the risk factors using these themes. The properties of the estimators are examined using extensive simulations. The methodology is illustrated using data from a matched case-control study of polychlorinated biphenyls in relation to the etiology of non-Hodgkin's lymphoma. PMID:26575519

  18. A Chemical Risk Ranking and Scoring Method for the Selection of Harmful Substances to be Specially Controlled in Occupational Environments

    PubMed Central

    Shin, Saemi; Moon, Hyung-Il; Lee, Kwon Seob; Hong, Mun Ki; Byeon, Sang-Hoon

    2014-01-01

    This study aimed to devise a method for prioritizing hazardous chemicals for further regulatory action. To accomplish this objective, we chose appropriate indicators and algorithms. Nine indicators from the Globally Harmonized System of Classification and Labeling of Chemicals were used to identify categories to which the authors assigned numerical scores. Exposure indicators included handling volume, distribution, and exposure level. To test the method devised by this study, sixty-two harmful substances controlled by the Occupational Safety and Health Act in Korea, including acrylamide, acrylonitrile, and styrene were ranked using this proposed method. The correlation coefficients between total score and each indicator ranged from 0.160 to 0.641, and those between total score and hazard indicators ranged from 0.603 to 0.641. The latter were higher than the correlation coefficients between total score and exposure indicators, which ranged from 0.160 to 0.421. Correlations between individual indicators were low (−0.240 to 0.376), except for those between handling volume and distribution (0.613), suggesting that each indicator was not strongly correlated. The low correlations between each indicator mean that the indicators and independent and were well chosen for prioritizing harmful chemicals. This method proposed by this study can improve the cost efficiency of chemical management as utilized in occupational regulatory systems. PMID:25419874

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

    PubMed

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

    2013-12-01

    In this paper, we show a new technique to analyze families of rankings. In particular, we focus on sports rankings and, more precisely, on soccer leagues. We consider that two teams compete when they change their relative positions in consecutive rankings. This allows to define a graph by linking teams that compete. We show how to use some structural properties of this competitivity graph to measure to what extend the teams in a league compete. These structural properties are the mean degree, the mean strength, and the clustering coefficient. We give a generalization of the Kendall's correlation coefficient to more than two rankings. We also show how to make a dynamic analysis of a league and how to compare different leagues. We apply this technique to analyze the four major European soccer leagues: Bundesliga, Italian Lega, Spanish Liga, and Premier League. We compare our results with the classical analysis of sport ranking based on measures of competitive balance. PMID:24387553

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

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

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

  1. The oxygen sensitivity/compatibility ranking of several materials by different test methods

    NASA Technical Reports Server (NTRS)

    Lockhart, Billy J.; Bryan, Coleman J.; Hampton, Michael D.

    1989-01-01

    Eleven materials were evaluated for oxygen compatibility using the following test methods: heat of combustion (ASTM D 2015), liquid oxygen impact (ASTM D 2512), pneumatic impact (ASTM G 74), gaseous mechanical impact (ASTM G 86), autogenous ignition temperature by pressurized differential scanning calorimeter, and the determination of the 50 percent reaction level in liquid oxygen using silicon carbide as a reaction enhancer. The eleven materials evaluated were: Teflon TFE, Vespel SP-21, Krytox 240AC, Viton PLV5010B, Fluorel E2160, Kel F 81, Fluorogold, Fluorogreen E-600, Rulon A, Garlock 8573, nylon 6/6.

  2. MRPrimer: a MapReduce-based method for the thorough design of valid and ranked primers for PCR

    PubMed Central

    Kim, Hyerin; Kang, NaNa; Chon, Kang-Wook; Kim, Seonho; Lee, NaHye; Koo, JaeHyung; Kim, Min-Soo

    2015-01-01

    Primer design is a fundamental technique that is widely used for polymerase chain reaction (PCR). Although many methods have been proposed for primer design, they require a great deal of manual effort to generate feasible and valid primers, including homology tests on off-target sequences using BLAST-like tools. That approach is inconvenient for many target sequences of quantitative PCR (qPCR) due to considering the same stringent and allele-invariant constraints. To address this issue, we propose an entirely new method called MRPrimer that can design all feasible and valid primer pairs existing in a DNA database at once, while simultaneously checking a multitude of filtering constraints and validating primer specificity. Furthermore, MRPrimer suggests the best primer pair for each target sequence, based on a ranking method. Through qPCR analysis using 343 primer pairs and the corresponding sequencing and comparative analyses, we showed that the primer pairs designed by MRPrimer are very stable and effective for qPCR. In addition, MRPrimer is computationally efficient and scalable and therefore useful for quickly constructing an entire collection of feasible and valid primers for frequently updated databases like RefSeq. Furthermore, we suggest that MRPrimer can be utilized conveniently for experiments requiring primer design, especially real-time qPCR. PMID:26109350

  3. Rasch analysis for the evaluation of rank of student response time in multiple choice examinations.

    PubMed

    Thompson, James J; Yang, Tong; Chauvin, Sheila W

    2013-01-01

    The availability of computerized testing has broadened the scope of person assessment beyond the usual accuracy-ability domain to include response time analyses. Because there are contexts in which speed is important, e.g. medical practice, it is important to develop tools by which individuals can be evaluated for speed. In this paper, the ability of Rasch measurement to convert ordinal nonparametric rankings of speed to measures is examined and compared to similar measures derived from parametric analysis of response times (pace) and semi-parametric logarithmic time-scaling procedures. Assuming that similar spans of the measures were used, non-parametric methods of raw ranking or percentile-ranking of persons by questions gave statistically acceptable person estimates of speed virtually identical to the parametric or semi-parametric methods. Because no assumptions were made about the underlying time distributions with ranking, generality of conclusions was enhanced. The main drawbacks of the non-parametric ranking procedures were the lack of information on question duration and the overall assignment by the model of variance to the person by question interaction. PMID:24064578

  4. Network tuned multiple rank aggregation and applications to gene ranking

    PubMed Central

    2015-01-01

    With the development of various high throughput technologies and analysis methods, researchers can study different aspects of a biological phenomenon simultaneously or one aspect repeatedly with different experimental techniques and analysis methods. The output from each study is a rank list of components of interest. Aggregation of the rank lists of components, such as proteins, genes and single nucleotide variants (SNV), produced by these experiments has been proven to be helpful in both filtering the noise and bringing forth a more complete understanding of the biological problems. Current available rank aggregation methods do not consider the network information that has been observed to provide vital contributions in many data integration studies. We developed network tuned rank aggregation methods incorporating network information and demonstrated its superior performance over aggregation methods without network information. The methods are tested on predicting the Gene Ontology function of yeast proteins. We validate the methods using combinations of three gene expression data sets and three protein interaction networks as well as an integrated network by combining the three networks. Results show that the aggregated rank lists are more meaningful if protein interaction network is incorporated. Among the methods compared, CGI_RRA and CGI_Endeavour, which integrate rank lists with networks using CGI [1] followed by rank aggregation using either robust rank aggregation (RRA) [2] or Endeavour [3] perform the best. Finally, we use the methods to locate target genes of transcription factors. PMID:25708095

  5. Binorm-a fortran subroutine to calculate the percentiles of a standardized binormal distribution

    USGS Publications Warehouse

    McCammon, R.B.

    1977-01-01

    BINORM is a FORTRAN subroutine for calculating the percentiles of a standardized binormal distribution. By using a linear transformation, the percentiles of a binormal distribution can be obtained. The percentiles of a binormal distribution are useful for plotting purposes, for establishing confidence intervals, and for sampling from a mixed population that consists of two normal distributions. ?? 1977.

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

    NASA Astrophysics Data System (ADS)

    Shams, Bita; Haratizadeh, Saman

    2016-09-01

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

  7. When Does Rank(ABC)= Rank(AB) + Rank(BC) - Rank(B) Hold?

    ERIC Educational Resources Information Center

    Tian, Yongge; Styan, George P. H.

    2002-01-01

    The well-known Frobenius rank inequality established by Frobenius in 1911 states that the rank of the product ABC of three matrices satisfies the inequality rank(ABC) [greater than or equal]rank(AB) + rank(BC) - rank(B) A new necessary and sufficient condition for equality to hold is presented and then some interesting consequences and…

  8. Ensemble hydrological prediction of streamflow percentile at ungauged basins in Pakistan

    NASA Astrophysics Data System (ADS)

    Waseem, Muhammad; Ajmal, Muhammad; Kim, Tae-Woong

    2015-06-01

    Streamflow records with sufficient spatial and temporal coverage at the site of interest are usually scarce in Pakistan. As an alternative, various regional methods have been frequently adopted to derive hydrological information, which in essence attempt to transfer hydrological information from gauged to ungauged catchments. In this study, a new concept of ensemble hydrological prediction (EHP) was introduced which is an improved regional method for hydrological prediction at ungauged sites. It was mainly based on the performance weights (triple-connection weights (TCW)) derived from Nash Sutcliffe efficiency (NSE) and hydrological variable (here percentiles) calculated from three traditional regional transfer methods (RTMs) with suitable modification (i.e., three-step drainage area ratio (DAR) method, inverse distance weighting (IDW) method, and three-step regional regression analysis (RRA)). The overall results indicated that the proposed EHP method was robust for estimating hydrological percentiles at ungauged sites as compared to traditional individual RTMs. The comparative study based on NSE, percent bias (PBIAS) and the relative error (RE) as performance criteria resulted that the EHP is a constructive alternative for hydrological prediction of ungauged basins.

  9. Ranking of causes lead to road accidents using a new linguistic variable in interval type-2 fuzzy entropy weight of a decision making method

    NASA Astrophysics Data System (ADS)

    Zamri, Nurnadiah; Abdullah, Lazim

    2014-07-01

    A linguistic data is a variable whose value is naturally language phase in dealing with too complex situation to be described properly in conventional quantitative expressions. However, all the past researchers on linguistic variables used positive fuzzy numbers in expressing meaning of symbolic word. It seems that positive and negative numbers were never put concurrently in defining linguistic variables. Accordingly, we intend to construct a new positive and negative linguistic variable in interval type-2 fuzzy entropy weight for interval type-2 fuzzy TOPSIS (IT2 FTOPSIS). This paper uses a new linguistic variable in interval type-2 fuzzy entropy weight to capture the problems on reducing number of road accidents due to all the previously mentioned methods had no discussion about ranking of factors associated with road accidents. Specifically the objective of this paper is to establish rankings of the selected factors associated with road accidents using a new positive and negative linguistic variable and interval type-2 fuzzy entropy weight in interval type-2 fuzzy TOPSIS. This new method is hoped can produce an optimal preference ranking of alternatives in accordance with a set of criterion wise ranking in selection of causes that lead to road accidents. The proposed method produces actionable results that laid the decision-making process. Besides, it does not require a complicated computation procedure and will be beneficial to decision analysis.

  10. Physical Fitness Percentiles of German Children Aged 9–12 Years: Findings from a Longitudinal Study

    PubMed Central

    Golle, Kathleen; Muehlbauer, Thomas; Wick, Ditmar; Granacher, Urs

    2015-01-01

    Background Generating percentile values is helpful for the identification of children with specific fitness characteristics (i.e., low or high fitness level) to set appropriate fitness goals (i.e., fitness/health promotion and/or long-term youth athlete development). Thus, the aim of this longitudinal study was to assess physical fitness development in healthy children aged 9–12 years and to compute sex- and age-specific percentile values. Methods Two-hundred and forty children (88 girls, 152 boys) participated in this study and were tested for their physical fitness. Physical fitness was assessed using the 50-m sprint test (i.e., speed), the 1-kg ball push test, the triple hop test (i.e., upper- and lower- extremity muscular power), the stand-and-reach test (i.e., flexibility), the star run test (i.e., agility), and the 9-min run test (i.e., endurance). Age- and sex-specific percentile values (i.e., P10 to P90) were generated using the Lambda, Mu, and Sigma method. Adjusted (for change in body weight, height, and baseline performance) age- and sex-differences as well as the interactions thereof were expressed by calculating effect sizes (Cohen’s d). Results Significant main effects of Age were detected for all physical fitness tests (d = 0.40–1.34), whereas significant main effects of Sex were found for upper-extremity muscular power (d = 0.55), flexibility (d = 0.81), agility (d = 0.44), and endurance (d = 0.32) only. Further, significant Sex by Age interactions were observed for upper-extremity muscular power (d = 0.36), flexibility (d = 0.61), and agility (d = 0.27) in favor of girls. Both, linear and curvilinear shaped curves were found for percentile values across the fitness tests. Accelerated (curvilinear) improvements were observed for upper-extremity muscular power (boys: 10–11 yrs; girls: 9–11 yrs), agility (boys: 9–10 yrs; girls: 9–11 yrs), and endurance (boys: 9–10 yrs; girls: 9–10 yrs). Tabulated percentiles for the 9-min run test

  11. Pay for Percentile. NBER Working Paper No. 17194

    ERIC Educational Resources Information Center

    Barlevy, Gadi; Neal, Derek

    2011-01-01

    We analyze an incentive pay scheme for educators that links educator compensation to the ranks of their students within appropriately defined comparison sets, and we show that under certain conditions this scheme induces teachers to allocate socially optimal levels of effort to all students. Moreover, because this scheme employs only ordinal…

  12. Beyond Low Rank + Sparse: Multiscale Low Rank Matrix Decomposition

    NASA Astrophysics Data System (ADS)

    Ong, Frank; Lustig, Michael

    2016-06-01

    Low rank methods allow us to capture globally correlated components within matrices. The recent low rank + sparse decomposition further enables us to extract sparse entries along with the globally correlated components. In this paper, we present a natural generalization and consider the decomposition of matrices into components of multiple scales. Such decomposition is well motivated in practice as data matrices often exhibit local correlations in multiple scales. Concretely, we propose a multi-scale low rank modeling that represents a data matrix as a sum of block-wise low rank matrices with increasing scales of block sizes. We then consider the inverse problem of decomposing the data matrix into its multi-scale low rank components and approach the problem via a convex formulation. Theoretically, we show that under an incoherence condition, the convex program recovers the multi-scale low rank components exactly. Practically, we provide guidance on selecting the regularization parameters and incorporate cycle spinning to reduce blocking artifacts. Experimentally, we show that the multi-scale low rank decomposition provides a more intuitive decomposition than conventional low rank methods and demonstrate its effectiveness in four applications, including illumination normalization for face images, motion separation for surveillance videos, multi-scale modeling of the dynamic contrast enhanced magnetic resonance imaging and collaborative filtering exploiting age information.

  13. A Novel Multi-Sensor Environmental Perception Method Using Low-Rank Representation and a Particle Filter for Vehicle Reversing Safety.

    PubMed

    Zhang, Zutao; Li, Yanjun; Wang, Fubing; Meng, Guanjun; Salman, Waleed; Saleem, Layth; Zhang, Xiaoliang; Wang, Chunbai; Hu, Guangdi; Liu, Yugang

    2016-01-01

    Environmental perception and information processing are two key steps of active safety for vehicle reversing. Single-sensor environmental perception cannot meet the need for vehicle reversing safety due to its low reliability. In this paper, we present a novel multi-sensor environmental perception method using low-rank representation and a particle filter for vehicle reversing safety. The proposed system consists of four main steps, namely multi-sensor environmental perception, information fusion, target recognition and tracking using low-rank representation and a particle filter, and vehicle reversing speed control modules. First of all, the multi-sensor environmental perception module, based on a binocular-camera system and ultrasonic range finders, obtains the distance data for obstacles behind the vehicle when the vehicle is reversing. Secondly, the information fusion algorithm using an adaptive Kalman filter is used to process the data obtained with the multi-sensor environmental perception module, which greatly improves the robustness of the sensors. Then the framework of a particle filter and low-rank representation is used to track the main obstacles. The low-rank representation is used to optimize an objective particle template that has the smallest L-1 norm. Finally, the electronic throttle opening and automatic braking is under control of the proposed vehicle reversing control strategy prior to any potential collisions, making the reversing control safer and more reliable. The final system simulation and practical testing results demonstrate the validity of the proposed multi-sensor environmental perception method using low-rank representation and a particle filter for vehicle reversing safety. PMID:27294931

  14. A Novel Multi-Sensor Environmental Perception Method Using Low-Rank Representation and a Particle Filter for Vehicle Reversing Safety

    PubMed Central

    Zhang, Zutao; Li, Yanjun; Wang, Fubing; Meng, Guanjun; Salman, Waleed; Saleem, Layth; Zhang, Xiaoliang; Wang, Chunbai; Hu, Guangdi; Liu, Yugang

    2016-01-01

    Environmental perception and information processing are two key steps of active safety for vehicle reversing. Single-sensor environmental perception cannot meet the need for vehicle reversing safety due to its low reliability. In this paper, we present a novel multi-sensor environmental perception method using low-rank representation and a particle filter for vehicle reversing safety. The proposed system consists of four main steps, namely multi-sensor environmental perception, information fusion, target recognition and tracking using low-rank representation and a particle filter, and vehicle reversing speed control modules. First of all, the multi-sensor environmental perception module, based on a binocular-camera system and ultrasonic range finders, obtains the distance data for obstacles behind the vehicle when the vehicle is reversing. Secondly, the information fusion algorithm using an adaptive Kalman filter is used to process the data obtained with the multi-sensor environmental perception module, which greatly improves the robustness of the sensors. Then the framework of a particle filter and low-rank representation is used to track the main obstacles. The low-rank representation is used to optimize an objective particle template that has the smallest L-1 norm. Finally, the electronic throttle opening and automatic braking is under control of the proposed vehicle reversing control strategy prior to any potential collisions, making the reversing control safer and more reliable. The final system simulation and practical testing results demonstrate the validity of the proposed multi-sensor environmental perception method using low-rank representation and a particle filter for vehicle reversing safety. PMID:27294931

  15. Efficient Evaluation of Ranking Procedures when the Number of Units is Large, With Application to SNP Identification

    PubMed Central

    Louis, Thomas A.; Ruczinski, Ingo

    2009-01-01

    Summary Simulation-based assessment is a popular and frequently necessary approach to evaluation of statistical procedures. Sometimes overlooked is the ability to take advantage of underlying mathematical relations and we focus on this aspect. We show how to take advantage of large-sample theory when conducting a simulation using the analysis of genomic data as a motivating example. The approach uses convergence results to provide an approximation to smaller-sample results, results that are available only by simulation. We consider evaluating and comparing a variety of ranking-based methods for identifying the most highly associated SNPs in a genome-wide association study, derive integral equation representations of the pre-posterior distribution of percentiles produced by three ranking methods, and provide examples comparing performance. These results are of interest in their own right and set the framework for a more extensive set of comparisons. PMID:20131327

  16. Percentile-based Empirical Distribution Function Estimates for Performance Evaluation of Healthcare Providers

    PubMed Central

    Paddock, Susan M.; Louis, Thomas A.

    2010-01-01

    Summary Hierarchical models are widely-used to characterize the performance of individual healthcare providers. However, little attention has been devoted to system-wide performance evaluations, the goals of which include identifying extreme (e.g., top 10%) provider performance and developing statistical benchmarks to define high-quality care. Obtaining optimal estimates of these quantities requires estimating the empirical distribution function (EDF) of provider-specific parameters that generate the dataset under consideration. However, the difficulty of obtaining uncertainty bounds for a square-error loss minimizing EDF estimate has hindered its use in system-wide performance evaluations. We therefore develop and study a percentile-based EDF estimate for univariate provider-specific parameters. We compute order statistics of samples drawn from the posterior distribution of provider-specific parameters to obtain relevant uncertainty assessments of an EDF estimate and its features, such as thresholds and percentiles. We apply our method to data from the Medicare End Stage Renal Disease (ESRD) Program, a health insurance program for people with irreversible kidney failure. We highlight the risk of misclassifying providers as exceptionally good or poor performers when uncertainty in statistical benchmark estimates is ignored. Given the high stakes of performance evaluations, statistical benchmarks should be accompanied by precision estimates. PMID:21918583

  17. Waist Circumferences of Chilean Students: Comparison of the CDC-2012 Standard and Proposed Percentile Curves

    PubMed Central

    Gómez-Campos, Rossana; Lee Andruske, Cinthya; Hespanhol, Jefferson; Sulla Torres, Jose; Arruda, Miguel; Luarte-Rocha, Cristian; Cossio-Bolaños, Marco Antonio

    2015-01-01

    The measurement of waist circumference (WC) is considered to be an important means to control overweight and obesity in children and adolescents. The objectives of the study were to (a) compare the WC measurements of Chilean students with the international CDC-2012 standard and other international standards, and (b) propose a specific measurement value for the WC of Chilean students based on age and sex. A total of 3892 students (6 to 18 years old) were assessed. Weight, height, body mass index (BMI), and WC were measured. WC was compared with the CDC-2012 international standard. Percentiles were constructed based on the LMS method. Chilean males had a greater WC during infancy. Subsequently, in late adolescence, males showed values lower than those of the international standards. Chilean females demonstrated values similar to the standards until the age of 12. Subsequently, females showed lower values. The 85th and 95th percentiles were adopted as cutoff points for evaluating overweight and obesity based on age and sex. The WC of Chilean students differs from the CDC-2012 curves. The regional norms proposed are a means to identify children and adolescents with a high risk of suffering from overweight and obesity disorders. PMID:26184250

  18. Waist Circumferences of Chilean Students: Comparison of the CDC-2012 Standard and Proposed Percentile Curves.

    PubMed

    Gómez-Campos, Rossana; Andruske, Cinthya Lee; Hespanhol, Jefferson; Torres, Jose Sulla; Arruda, Miguel; Luarte-Rocha, Cristian; Cossio-Bolaños, Marco Antonio

    2015-07-01

    The measurement of waist circumference (WC) is considered to be an important means to control overweight and obesity in children and adolescents. The objectives of the study were to (a) compare the WC measurements of Chilean students with the international CDC-2012 standard and other international standards, and (b) propose a specific measurement value for the WC of Chilean students based on age and sex. A total of 3892 students (6 to 18 years old) were assessed. Weight, height, body mass index (BMI), and WC were measured. WC was compared with the CDC-2012 international standard. Percentiles were constructed based on the LMS method. Chilean males had a greater WC during infancy. Subsequently, in late adolescence, males showed values lower than those of the international standards. Chilean females demonstrated values similar to the standards until the age of 12. Subsequently, females showed lower values. The 85th and 95th percentiles were adopted as cutoff points for evaluating overweight and obesity based on age and sex. The WC of Chilean students differs from the CDC-2012 curves. The regional norms proposed are a means to identify children and adolescents with a high risk of suffering from overweight and obesity disorders. PMID:26184250

  19. Ranking of refrigerants.

    PubMed

    Restrepo, Guillermo; Weckert, Monika; Brüggemann, Rainer; Gerstmann, Silke; Frank, Hartmut

    2008-04-15

    Environmental ranking of refrigerants is of need in many instances. The aim is to assess the relative environmental hazard posed by 40 refrigerants, including those used in the past, those presently used, and some proposed substitutes. Ranking is based upon ozone depletion potential, global warming potential, and atmospheric lifetime and is achieved by applying the Hasse diagram technique, a mathematical method that allows us to assess order relationships of chemicals. The refrigerants are divided into 13 classes, of which the chlorofluorocarbons, hydrofluorocarbons, hydrochlorofluorocarbons, hydrofluoroethers, and hydrocarbons contain the largest number of single substances. The dominance degree, a method for measuring order relationships among classes, is discussed and applied to the 13 refrigerant classes. The results show that some hydrofluoroethers are as problematic as the hydrofluorocarbons. Hydrocarbons and ammonia are the least problematic refrigerants with respect to the three environmental properties. PMID:18497145

  20. Forecasting Urban Water Demand via Machine Learning Methods Coupled with a Bootstrap Rank-Ordered Conditional Mutual Information Input Variable Selection Method

    NASA Astrophysics Data System (ADS)

    Adamowski, J. F.; Quilty, J.; Khalil, B.; Rathinasamy, M.

    2014-12-01

    This paper explores forecasting short-term urban water demand (UWD) (using only historical records) through a variety of machine learning techniques coupled with a novel input variable selection (IVS) procedure. The proposed IVS technique termed, bootstrap rank-ordered conditional mutual information for real-valued signals (brCMIr), is multivariate, nonlinear, nonparametric, and probabilistic. The brCMIr method was tested in a case study using water demand time series for two urban water supply system pressure zones in Ottawa, Canada to select the most important historical records for use with each machine learning technique in order to generate forecasts of average and peak UWD for the respective pressure zones at lead times of 1, 3, and 7 days ahead. All lead time forecasts are computed using Artificial Neural Networks (ANN) as the base model, and are compared with Least Squares Support Vector Regression (LSSVR), as well as a novel machine learning method for UWD forecasting: the Extreme Learning Machine (ELM). Results from one-way analysis of variance (ANOVA) and Tukey Honesty Significance Difference (HSD) tests indicate that the LSSVR and ELM models are the best machine learning techniques to pair with brCMIr. However, ELM has significant computational advantages over LSSVR (and ANN) and provides a new and promising technique to explore in UWD forecasting.

  1. Impact of Doximity Residency Rankings on Emergency Medicine Applicant Rank Lists

    PubMed Central

    Peterson, William J.; Hopson, Laura R.; Khandelwal, Sorabh; White, Melissa; Gallahue, Fiona E.; Burkhardt, John; Rolston, Aimee M.; Santen, Sally A.

    2016-01-01

    Introduction This study investigates the impact of the Doximity rankings on the rank list choices made by residency applicants in emergency medicine (EM). Methods We sent an 11-item survey by email to all students who applied to EM residency programs at four different institutions representing diverse geographical regions. Students were asked questions about their perception of Doximity rankings and how it may have impacted their rank list decisions. Results Response rate was 58% of 1,372 opened electronic surveys. This study found that a majority of medical students applying to residency in EM were aware of the Doximity rankings prior to submitting rank lists (67%). One-quarter of these applicants changed the number of programs and ranks of those programs when completing their rank list based on the Doximity rankings (26%). Though the absolute number of programs changed on the rank lists was small, the results demonstrate that the EM Doximity rankings impact applicant decision-making in ranking residency programs. Conclusion While applicants do not find the Doximity rankings to be important compared to other factors in the application process, the Doximity rankings result in a small change in residency applicant ranking behavior. This unvalidated ranking, based principally on reputational data rather than objective outcome criteria, thus has the potential to be detrimental to students, programs, and the public. We feel it important for specialties to develop consensus around measurable training outcomes and provide freely accessible metrics for candidate education. PMID:27330670

  2. Quantifying aflatoxins in peanuts using fluorescence spectroscopy coupled with multi-way methods: Resurrecting second-order advantage in excitation-emission matrices with rank overlap problem

    NASA Astrophysics Data System (ADS)

    Sajjadi, S. Maryam; Abdollahi, Hamid; Rahmanian, Reza; Bagheri, Leila

    2016-03-01

    A rapid, simple and inexpensive method using fluorescence spectroscopy coupled with multi-way methods for the determination of aflatoxins B1 and B2 in peanuts has been developed. In this method, aflatoxins are extracted with a mixture of water and methanol (90:10), and then monitored by fluorescence spectroscopy producing EEMs. Although the combination of EEMs and multi-way methods is commonly used to determine analytes in complex chemical systems with unknown interference(s), rank overlap problem in excitation and emission profiles may restrain the application of this strategy. If there is rank overlap in one mode, there are several three-way algorithms such as PARAFAC under some constraints that can resolve this kind of data successfully. However, the analysis of EEM data is impossible when some species have rank overlap in both modes because the information of the data matrix is equivalent to a zero-order data for that species, which is the case in our study. Aflatoxins B1 and B2 have the same shape of spectral profiles in both excitation and emission modes and we propose creating a third order data for each sample using solvent as a new additional selectivity mode. This third order data, in turn, converted to the second order data by augmentation, a fact which resurrects the second order advantage in original EEMs. The three-way data is constructed by stacking augmented data in the third way, and then analyzed by two powerful second order calibration methods (BLLS-RBL and PARAFAC) to quantify the analytes in four kinds of peanut samples. The results of both methods are in good agreement and reasonable recoveries are obtained.

  3. Quantifying aflatoxins in peanuts using fluorescence spectroscopy coupled with multi-way methods: Resurrecting second-order advantage in excitation-emission matrices with rank overlap problem.

    PubMed

    Sajjadi, S Maryam; Abdollahi, Hamid; Rahmanian, Reza; Bagheri, Leila

    2016-03-01

    A rapid, simple and inexpensive method using fluorescence spectroscopy coupled with multi-way methods for the determination of aflatoxins B1 and B2 in peanuts has been developed. In this method, aflatoxins are extracted with a mixture of water and methanol (90:10), and then monitored by fluorescence spectroscopy producing EEMs. Although the combination of EEMs and multi-way methods is commonly used to determine analytes in complex chemical systems with unknown interference(s), rank overlap problem in excitation and emission profiles may restrain the application of this strategy. If there is rank overlap in one mode, there are several three-way algorithms such as PARAFAC under some constraints that can resolve this kind of data successfully. However, the analysis of EEM data is impossible when some species have rank overlap in both modes because the information of the data matrix is equivalent to a zero-order data for that species, which is the case in our study. Aflatoxins B1 and B2 have the same shape of spectral profiles in both excitation and emission modes and we propose creating a third order data for each sample using solvent as a new additional selectivity mode. This third order data, in turn, converted to the second order data by augmentation, a fact which resurrects the second order advantage in original EEMs. The three-way data is constructed by stacking augmented data in the third way, and then analyzed by two powerful second order calibration methods (BLLS-RBL and PARAFAC) to quantify the analytes in four kinds of peanut samples. The results of both methods are in good agreement and reasonable recoveries are obtained. PMID:26650793

  4. Colorado Growth Model--Brief Report: Student Growth Percentiles and FRL Status. Accountability & Data Analysis Unit

    ERIC Educational Resources Information Center

    Colorado Department of Education, 2013

    2013-01-01

    This report examines the relationship between socioeconomic status, as defined by a free-and-reduced lunch proxy variable, and student growth percentiles by elementary, middle, and high school grade levels for math, reading, and writing. Comparisons were made between median growth percentiles for each educational level by free and reduced lunch…

  5. A simple surrogate test method to rank the wear performance of prospective ceramic materials under hip prosthesis edge-loading conditions.

    PubMed

    Sanders, Anthony P; Brannon, Rebecca M

    2014-02-01

    This research has developed a novel test method for evaluating the wear resistance of ceramic materials under severe contact stresses simulating edge loading in prosthetic hip bearings. Simply shaped test specimens - a cylinder and a spheroid - were designed as surrogates for an edge-loaded, head/liner implant pair. Equivalency of the simpler specimens was assured in the sense that their theoretical contact dimensions and pressures were identical, according to Hertzian contact theory, to those of the head/liner pair. The surrogates were fabricated in three ceramic materials: Al2 O3 , zirconia-toughened alumina (ZTA), and ZrO2 . They were mated in three different material pairs and reciprocated under a 200 N normal contact force for 1000-2000 cycles, which created small (<1 mm(2) ) wear scars. The three material pairs were ranked by their wear resistance, quantified by the volume of abraded material measured using an interferometer. Similar tests were performed on edge-loaded hip implants in the same material pairs. The surrogates replicated the wear rankings of their full-scale implant counterparts and mimicked their friction force trends. The results show that a proxy test using simple test specimens can validly rank the wear performance of ceramic materials under severe, edge-loading contact stresses, while replicating the beginning stage of edge-loading wear. This simple wear test is therefore potentially useful for screening and ranking new, prospective materials early in their development, to produce optimized candidates for more complicated full-scale hip simulator wear tests. PMID:23996812

  6. Hasse diagram as a green analytical metrics tool: ranking of methods for benzo[a]pyrene determination in sediments.

    PubMed

    Bigus, Paulina; Tsakovski, Stefan; Simeonov, Vasil; Namieśnik, Jacek; Tobiszewski, Marek

    2016-05-01

    This study presents an application of the Hasse diagram technique (HDT) as the assessment tool to select the most appropriate analytical procedures according to their greenness or the best analytical performance. The dataset consists of analytical procedures for benzo[a]pyrene determination in sediment samples, which were described by 11 variables concerning their greenness and analytical performance. Two analyses with the HDT were performed-the first one with metrological variables and the second one with "green" variables as input data. Both HDT analyses ranked different analytical procedures as the most valuable, suggesting that green analytical chemistry is not in accordance with metrology when benzo[a]pyrene in sediment samples is determined. The HDT can be used as a good decision support tool to choose the proper analytical procedure concerning green analytical chemistry principles and analytical performance merits. PMID:27038058

  7. TripleRank: Ranking Semantic Web Data by Tensor Decomposition

    NASA Astrophysics Data System (ADS)

    Franz, Thomas; Schultz, Antje; Sizov, Sergej; Staab, Steffen

    The Semantic Web fosters novel applications targeting a more efficient and satisfying exploitation of the data available on the web, e.g. faceted browsing of linked open data. Large amounts and high diversity of knowledge in the Semantic Web pose the challenging question of appropriate relevance ranking for producing fine-grained and rich descriptions of the available data, e.g. to guide the user along most promising knowledge aspects. Existing methods for graph-based authority ranking lack support for fine-grained latent coherence between resources and predicates (i.e. support for link semantics in the linked data model). In this paper, we present TripleRank, a novel approach for faceted authority ranking in the context of RDF knowledge bases. TripleRank captures the additional latent semantics of Semantic Web data by means of statistical methods in order to produce richer descriptions of the available data. We model the Semantic Web by a 3-dimensional tensor that enables the seamless representation of arbitrary semantic links. For the analysis of that model, we apply the PARAFAC decomposition, which can be seen as a multi-modal counterpart to Web authority ranking with HITS. The result are groupings of resources and predicates that characterize their authority and navigational (hub) properties with respect to identified topics. We have applied TripleRank to multiple data sets from the linked open data community and gathered encouraging feedback in a user evaluation where TripleRank results have been exploited in a faceted browsing scenario.

  8. A Method for the Design and Development of Medical or Health Care Information Websites to Optimize Search Engine Results Page Rankings on Google

    PubMed Central

    Cummins, Niamh Maria; Hannigan, Ailish; Shannon, Bill; Dunne, Colum; Cullen, Walter

    2013-01-01

    Background The Internet is a widely used source of information for patients searching for medical/health care information. While many studies have assessed existing medical/health care information on the Internet, relatively few have examined methods for design and delivery of such websites, particularly those aimed at the general public. Objective This study describes a method of evaluating material for new medical/health care websites, or for assessing those already in existence, which is correlated with higher rankings on Google's Search Engine Results Pages (SERPs). Methods A website quality assessment (WQA) tool was developed using criteria related to the quality of the information to be contained in the website in addition to an assessment of the readability of the text. This was retrospectively applied to assess existing websites that provide information about generic medicines. The reproducibility of the WQA tool and its predictive validity were assessed in this study. Results The WQA tool demonstrated very high reproducibility (intraclass correlation coefficient=0.95) between 2 independent users. A moderate to strong correlation was found between WQA scores and rankings on Google SERPs. Analogous correlations were seen between rankings and readability of websites as determined by Flesch Reading Ease and Flesch-Kincaid Grade Level scores. Conclusions The use of the WQA tool developed in this study is recommended as part of the design phase of a medical or health care information provision website, along with assessment of readability of the material to be used. This may ensure that the website performs better on Google searches. The tool can also be used retrospectively to make improvements to existing websites, thus, potentially enabling better Google search result positions without incurring the costs associated with Search Engine Optimization (SEO) professionals or paid promotion. PMID:23981848

  9. Large-scale linear rankSVM.

    PubMed

    Lee, Ching-Pei; Lin, Chih-Jen

    2014-04-01

    Linear rankSVM is one of the widely used methods for learning to rank. Although its performance may be inferior to nonlinear methods such as kernel rankSVM and gradient boosting decision trees, linear rankSVM is useful to quickly produce a baseline model. Furthermore, following its recent development for classification, linear rankSVM may give competitive performance for large and sparse data. A great deal of works have studied linear rankSVM. The focus is on the computational efficiency when the number of preference pairs is large. In this letter, we systematically study existing works, discuss their advantages and disadvantages, and propose an efficient algorithm. We discuss different implementation issues and extensions with detailed experiments. Finally, we develop a robust linear rankSVM tool for public use. PMID:24479776

  10. An Analytic Hierarchy Process-based Method to Rank the Critical Success Factors of Implementing a Pharmacy Barcode System.

    PubMed

    Alharthi, Hana; Sultana, Nahid; Al-Amoudi, Amjaad; Basudan, Afrah

    2015-01-01

    Pharmacy barcode scanning is used to reduce errors during the medication dispensing process. However, this technology has rarely been used in hospital pharmacies in Saudi Arabia. This article describes the barriers to successful implementation of a barcode scanning system in Saudi Arabia. A literature review was conducted to identify the relevant critical success factors (CSFs) for a successful dispensing barcode system implementation. Twenty-eight pharmacists from a local hospital in Saudi Arabia were interviewed to obtain their perception of these CSFs. In this study, planning (process flow issues and training requirements), resistance (fear of change, communication issues, and negative perceptions about technology), and technology (software, hardware, and vendor support) were identified as the main barriers. The analytic hierarchy process (AHP), one of the most widely used tools for decision making in the presence of multiple criteria, was used to compare and rank these identified CSFs. The results of this study suggest that resistance barriers have a greater impact than planning and technology barriers. In particular, fear of change is the most critical factor, and training is the least critical factor. PMID:26807079

  11. An Analytic Hierarchy Process–based Method to Rank the Critical Success Factors of Implementing a Pharmacy Barcode System

    PubMed Central

    Alharthi, Hana; Sultana, Nahid; Al-amoudi, Amjaad; Basudan, Afrah

    2015-01-01

    Pharmacy barcode scanning is used to reduce errors during the medication dispensing process. However, this technology has rarely been used in hospital pharmacies in Saudi Arabia. This article describes the barriers to successful implementation of a barcode scanning system in Saudi Arabia. A literature review was conducted to identify the relevant critical success factors (CSFs) for a successful dispensing barcode system implementation. Twenty-eight pharmacists from a local hospital in Saudi Arabia were interviewed to obtain their perception of these CSFs. In this study, planning (process flow issues and training requirements), resistance (fear of change, communication issues, and negative perceptions about technology), and technology (software, hardware, and vendor support) were identified as the main barriers. The analytic hierarchy process (AHP), one of the most widely used tools for decision making in the presence of multiple criteria, was used to compare and rank these identified CSFs. The results of this study suggest that resistance barriers have a greater impact than planning and technology barriers. In particular, fear of change is the most critical factor, and training is the least critical factor. PMID:26807079

  12. Rank products: a simple, yet powerful, new method to detect differentially regulated genes in replicated microarray experiments.

    PubMed

    Breitling, Rainer; Armengaud, Patrick; Amtmann, Anna; Herzyk, Pawel

    2004-08-27

    One of the main objectives in the analysis of microarray experiments is the identification of genes that are differentially expressed under two experimental conditions. This task is complicated by the noisiness of the data and the large number of genes that are examined simultaneously. Here, we present a novel technique for identifying differentially expressed genes that does not originate from a sophisticated statistical model but rather from an analysis of biological reasoning. The new technique, which is based on calculating rank products (RP) from replicate experiments, is fast and simple. At the same time, it provides a straightforward and statistically stringent way to determine the significance level for each gene and allows for the flexible control of the false-detection rate and familywise error rate in the multiple testing situation of a microarray experiment. We use the RP technique on three biological data sets and show that in each case it performs more reliably and consistently than the non-parametric t-test variant implemented in Tusher et al.'s significance analysis of microarrays (SAM). We also show that the RP results are reliable in highly noisy data. An analysis of the physiological function of the identified genes indicates that the RP approach is powerful for identifying biologically relevant expression changes. In addition, using RP can lead to a sharp reduction in the number of replicate experiments needed to obtain reproducible results. PMID:15327980

  13. Playing the Rankings Game.

    ERIC Educational Resources Information Center

    Machung, Anne

    1998-01-01

    The "U.S. News and World Report" rankings of colleges do not affect institutions equally; the schools impacted most are those that have the most to lose because they benefit from, even rely on, the rankings for prestige and visibility. The magazine relies on the rankings for substantial sales revenues, and has garnered considerable power within…

  14. Order-Theoretical Ranking.

    ERIC Educational Resources Information Center

    Carpineto, Claudio; Romano, Giovanni

    2000-01-01

    Presents an approach to document ranking that explicitly addresses the word mismatch problem between a query and a document by exploiting interdocument similarity information, based on the theory of concept lattices. Compares information retrieval using concept lattice-based ranking (CLR) to BMR (best-match ranking) and HCR (hierarchical…

  15. Using a Spreadsheet to Compute the Maximum Wind Sector 99.5th Percentile X/Q Value in Accordance with DOE-STD-3009-2014.

    PubMed

    Vickers, Linda

    2016-05-01

    The U.S. Department of Energy Standard 3009-2014 requires one of two methods to determine the simple Gaussian relative concentration (X/Q) of pollutant at plume centerline downwind to a receptor for a 2-h exposure duration from a ground-level release (i.e., less than 10 m height) which are (1) the 99.5th percentile X/Q for the directionally-dependent method and (2) the 95th percentile X/Q for the directionally-independent method. This paper describes how to determine the simple Gaussian 99.5th percentile X/Q for the directionally-dependent method using an electronic spreadsheet. Refer to a previous paper to determine the simple Gaussian 95th percentile X/Q for the directionally-independent method using an electronic spreadsheet (Vickers 2015). The method described herein is simple, quick, accurate, and transparent because all of the data, calculations, and results are visible for validation and verification. PMID:27023153

  16. Shaping in the 21st century: Moving percentile schedules into applied settings

    PubMed Central

    Galbicka, Gregory

    1994-01-01

    The present paper provides a primer on percentile reinforcement schedules, which have been used for two decades to study response differentiation and shaping in the laboratory. Arranged in applied settings, percentile procedures could be used to specify response criteria, standardizing treatment across subjects, trainers, and times to provide a more consistent training environment while maintaining the sensitivity to the individual's repertoire that is the hallmark of shaping. Percentile schedules are also valuable tools in analyzing the variables of which responding is a function, both inside and outside the laboratory. Finally, by formalizing the rules of shaping, percentile schedules provide a useful heuristic of the processes involved in shaping behavior, even for those situations that may not easily permit their implementation. As such, they may help further sensitize trainers and researchers alike to variables of critical importance in behavior change. ImagesFigure 6 PMID:16795849

  17. Comparison of daily percentiles of streamflow and rainfall to investigate stream aquifer connectivity

    NASA Astrophysics Data System (ADS)

    Brodie, Ross S.; Hostetler, Stephen; Slatter, Emily

    2008-01-01

    SummaryA frequency analysis approach was used to investigate the hydraulic connectivity between streams and aquifers, by comparing daily percentiles of streamflow and rainfall. Three Australian streams were examined - a dominantly gaining stream (Wilsons River, NSW), a dominantly gaining stream modified by significant water extraction (Ovens River, Victoria) and a dominantly losing stream (Mooki River, NSW). For the gaining stream examples, a lag is observed between the seasonal peak in the low-flow percentile curves and the seasonal peak in the daily rainfall percentile curve. Cross-correlation was used to calculate the time-shift that provides the best fit between the streamflow and rainfall percentile curves. There is a good correlation ( r2 > 0.8) between the reference rainfall percentile curve and the shifted streamflow percentile curves for gaining streams. The lags evident between the rainfall and streamflow percentile curves represent the processes of first replenishing catchment storages (such as soil moisture and groundwater) and subsequent release to the stream. This is largely a function of catchment hydrogeology as well as climate, notably the magnitude and regularity of rainfall events. Catchment size is not a controlling factor. Analysis of these lags provides insights into the dynamics of groundwater recharge, storage and release. Changes in the lag times over the flow percentiles can reflect changes in the dominant catchment storage contributing to streamflow. For the Wilsons River, the contribution from a groundwater system with longer flow paths increases at lower flow percentiles. This can be critical when protecting minimum streamflows, as near-stream groundwater flow may not be the only determining factor. The impact of water extraction can be recognised in this analysis. For the Ovens River, streamflow deficits relative to the rainfall percentile curve correspond to the summer period of high irrigation demand. Such a deficit was also observed

  18. Quantum anonymous ranking

    NASA Astrophysics Data System (ADS)

    Huang, Wei; Wen, Qiao-Yan; Liu, Bin; Su, Qi; Qin, Su-Juan; Gao, Fei

    2014-03-01

    Anonymous ranking is a kind of privacy-preserving ranking whereby each of the involved participants can correctly and anonymously get the rankings of his data. It can be utilized to solve many practical problems, such as anonymously ranking the students' exam scores. We investigate the issue of how quantum mechanics can be of use in maintaining the anonymity of the participants in multiparty ranking and present a series of quantum anonymous multiparty, multidata ranking protocols. In each of these protocols, a participant can get the correct rankings of his data and nobody else can match the identity to his data. Furthermore, the security of these protocols with respect to different kinds of attacks is proved.

  19. Ranking species in mutualistic networks.

    PubMed

    Domínguez-García, Virginia; Muñoz, Miguel A

    2015-01-01

    Understanding the architectural subtleties of ecological networks, believed to confer them enhanced stability and robustness, is a subject of outmost relevance. Mutualistic interactions have been profusely studied and their corresponding bipartite networks, such as plant-pollinator networks, have been reported to exhibit a characteristic "nested" structure. Assessing the importance of any given species in mutualistic networks is a key task when evaluating extinction risks and possible cascade effects. Inspired in a recently introduced algorithm--similar in spirit to Google's PageRank but with a built-in non-linearity--here we propose a method which--by exploiting their nested architecture--allows us to derive a sound ranking of species importance in mutualistic networks. This method clearly outperforms other existing ranking schemes and can become very useful for ecosystem management and biodiversity preservation, where decisions on what aspects of ecosystems to explicitly protect need to be made. PMID:25640575

  20. Ranking species in mutualistic networks

    NASA Astrophysics Data System (ADS)

    Domínguez-García, Virginia; Muñoz, Miguel A.

    2015-02-01

    Understanding the architectural subtleties of ecological networks, believed to confer them enhanced stability and robustness, is a subject of outmost relevance. Mutualistic interactions have been profusely studied and their corresponding bipartite networks, such as plant-pollinator networks, have been reported to exhibit a characteristic ``nested'' structure. Assessing the importance of any given species in mutualistic networks is a key task when evaluating extinction risks and possible cascade effects. Inspired in a recently introduced algorithm -similar in spirit to Google's PageRank but with a built-in non-linearity- here we propose a method which -by exploiting their nested architecture- allows us to derive a sound ranking of species importance in mutualistic networks. This method clearly outperforms other existing ranking schemes and can become very useful for ecosystem management and biodiversity preservation, where decisions on what aspects of ecosystems to explicitly protect need to be made.

  1. Ranking species in mutualistic networks

    PubMed Central

    Domínguez-García, Virginia; Muñoz, Miguel A.

    2015-01-01

    Understanding the architectural subtleties of ecological networks, believed to confer them enhanced stability and robustness, is a subject of outmost relevance. Mutualistic interactions have been profusely studied and their corresponding bipartite networks, such as plant-pollinator networks, have been reported to exhibit a characteristic “nested” structure. Assessing the importance of any given species in mutualistic networks is a key task when evaluating extinction risks and possible cascade effects. Inspired in a recently introduced algorithm –similar in spirit to Google's PageRank but with a built-in non-linearity– here we propose a method which –by exploiting their nested architecture– allows us to derive a sound ranking of species importance in mutualistic networks. This method clearly outperforms other existing ranking schemes and can become very useful for ecosystem management and biodiversity preservation, where decisions on what aspects of ecosystems to explicitly protect need to be made. PMID:25640575

  2. A New Method for Navigating Optimal Direction for Pulling Ligand from Binding Pocket: Application to Ranking Binding Affinity by Steered Molecular Dynamics.

    PubMed

    Vuong, Quan Van; Nguyen, Tin Trung; Li, Mai Suan

    2015-12-28

    In this paper we present a new method for finding the optimal path for pulling a ligand from the binding pocket using steered molecular dynamics (SMD). Scoring function is defined as the steric hindrance caused by a receptor to ligand movement. Then the optimal path corresponds to the minimum of this scoring function. We call the new method MSH (Minimal Steric Hindrance). Contrary to existing navigation methods, our approach takes into account the geometry of the ligand while other methods including CAVER only consider the ligand as a sphere with a given radius. Using three different target + receptor sets, we have shown that the rupture force Fmax and nonequilibrium work Wpull obtained based on the MSH method show a much higher correlation with experimental data on binding free energies compared to CAVER. Furthermore, Wpull was found to be a better indicator for binding affinity than Fmax. Thus, the new MSH method is a reliable tool for obtaining the best direction for ligand exiting from the binding site. Its combination with the standard SMD technique can provide reasonable results for ranking binding affinities using Wpull as a scoring function. PMID:26595261

  3. Ranking chemicals based on chronic toxicity data.

    PubMed

    De Rosa, C T; Stara, J F; Durkin, P R

    1985-12-01

    During the past 3 years, EPA's ECAO/Cincinnati has developed a method to rank chemicals based on chronic toxicity data. This ranking system reflects two primary attributes of every chemical: the minimum effective dose and the type of effect elicited at that dose. The purpose for developing this chronic toxicity ranking system was to provide the EPA with the technical background required to adjust the RQs of hazardous substances designated in Section 101(14) of CERCLA or "Superfund." This approach may have applications to other areas of interest to the EPA and other regulatory agencies where ranking of chemicals based on chronic toxicity is desired. PMID:3843499

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

    PubMed

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

    2016-03-01

    In 2003, the Uganda Ministry of Health introduced the district league table for district health system performance assessment. The league table presents district performance against a number of input, process and output indicators and a composite index to rank districts. This study explores the use of hierarchical cluster analysis for analysing and presenting district health systems performance data and compares this approach with the use of the league table in Uganda. Ministry of Health and district plans and reports, and published documents were used to provide information on the development and utilization of the Uganda district league table. Quantitative data were accessed from the Ministry of Health databases. Statistical analysis using SPSS version 20 and hierarchical cluster analysis, utilizing Wards' method was used. The hierarchical cluster analysis was conducted on the basis of seven clusters determined for each year from 2003 to 2010, ranging from a cluster of good through moderate-to-poor performers. The characteristics and membership of clusters varied from year to year and were determined by the identity and magnitude of performance of the individual variables. Criticisms of the league table include: perceived unfairness, as it did not take into consideration district peculiarities; and being oversummarized and not adequately informative. Clustering organizes the many data points into clusters of similar entities according to an agreed set of indicators and can provide the beginning point for identifying factors behind the observed performance of districts. Although league table ranking emphasize summation and external control, clustering has the potential to encourage a formative, learning approach. More research is required to shed more light on factors behind observed performance of the different clusters. Other countries especially low-income countries that share many similarities with Uganda can learn from these experiences. PMID:26024882

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

    PubMed Central

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

    2016-01-01

    In 2003, the Uganda Ministry of Health introduced the district league table for district health system performance assessment. The league table presents district performance against a number of input, process and output indicators and a composite index to rank districts. This study explores the use of hierarchical cluster analysis for analysing and presenting district health systems performance data and compares this approach with the use of the league table in Uganda. Ministry of Health and district plans and reports, and published documents were used to provide information on the development and utilization of the Uganda district league table. Quantitative data were accessed from the Ministry of Health databases. Statistical analysis using SPSS version 20 and hierarchical cluster analysis, utilizing Wards’ method was used. The hierarchical cluster analysis was conducted on the basis of seven clusters determined for each year from 2003 to 2010, ranging from a cluster of good through moderate-to-poor performers. The characteristics and membership of clusters varied from year to year and were determined by the identity and magnitude of performance of the individual variables. Criticisms of the league table include: perceived unfairness, as it did not take into consideration district peculiarities; and being oversummarized and not adequately informative. Clustering organizes the many data points into clusters of similar entities according to an agreed set of indicators and can provide the beginning point for identifying factors behind the observed performance of districts. Although league table ranking emphasize summation and external control, clustering has the potential to encourage a formative, learning approach. More research is required to shed more light on factors behind observed performance of the different clusters. Other countries especially low-income countries that share many similarities with Uganda can learn from these experiences. PMID:26024882

  6. Low-Rank Preserving Projections.

    PubMed

    Lu, Yuwu; Lai, Zhihui; Xu, Yong; Li, Xuelong; Zhang, David; Yuan, Chun

    2016-08-01

    As one of the most popular dimensionality reduction techniques, locality preserving projections (LPP) has been widely used in computer vision and pattern recognition. However, in practical applications, data is always corrupted by noises. For the corrupted data, samples from the same class may not be distributed in the nearest area, thus LPP may lose its effectiveness. In this paper, it is assumed that data is grossly corrupted and the noise matrix is sparse. Based on these assumptions, we propose a novel dimensionality reduction method, named low-rank preserving projections (LRPP) for image classification. LRPP learns a low-rank weight matrix by projecting the data on a low-dimensional subspace. We use the L21 norm as a sparse constraint on the noise matrix and the nuclear norm as a low-rank constraint on the weight matrix. LRPP keeps the global structure of the data during the dimensionality reduction procedure and the learned low rank weight matrix can reduce the disturbance of noises in the data. LRPP can learn a robust subspace from the corrupted data. To verify the performance of LRPP in image dimensionality reduction and classification, we compare LRPP with the state-of-the-art dimensionality reduction methods. The experimental results show the effectiveness and the feasibility of the proposed method with encouraging results. PMID:26277014

  7. On Rank and Nullity

    ERIC Educational Resources Information Center

    Dobbs, David E.

    2012-01-01

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

  8. Hitting the Rankings Jackpot

    ERIC Educational Resources Information Center

    Chapman, David W.

    2008-01-01

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

  9. Memory Efficient Ranking.

    ERIC Educational Resources Information Center

    Moffat, Alistair; And Others

    1994-01-01

    Describes an approximate document ranking process that uses a compact array of in-memory, low-precision approximations for document length. Combined with another rule for reducing the memory required by partial similarity accumulators, the approximation heuristic allows the ranking of large document collections using less than one byte of memory…

  10. Re-Ranking Model Based on Document Clusters.

    ERIC Educational Resources Information Center

    Lee, Kyung-Soon; Park, Young-Chan; Choi, Key-Sun

    2001-01-01

    Describes a model of an information retrieval system that is based on a document re-ranking method, using document clusters. Retrieves documents based on the inverted file method, then analyzes the retrieved documents using document clusters and re-ranks them. Shows significant improvements over the method based on similarity search ranking alone.…

  11. A Ranking Approach to Genomic Selection

    PubMed Central

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

    2015-01-01

    Background Genomic selection (GS) is a recent selective breeding method which uses predictive models based on whole-genome molecular markers. Until now, existing studies formulated GS as the problem of modeling an individual’s breeding value for a particular trait of interest, i.e., as a regression problem. To assess predictive accuracy of the model, the Pearson correlation between observed and predicted trait values was used. Contributions In this paper, we propose to formulate GS as the problem of ranking individuals according to their breeding value. Our proposed framework allows us to employ machine learning methods for ranking which had previously not been considered in the GS literature. To assess ranking accuracy of a model, we introduce a new measure originating from the information retrieval literature called normalized discounted cumulative gain (NDCG). NDCG rewards more strongly models which assign a high rank to individuals with high breeding value. Therefore, NDCG reflects a prerequisite objective in selective breeding: accurate selection of individuals with high breeding value. Results We conducted a comparison of 10 existing regression methods and 3 new ranking methods on 6 datasets, consisting of 4 plant species and 25 traits. Our experimental results suggest that tree-based ensemble methods including McRank, Random Forests and Gradient Boosting Regression Trees achieve excellent ranking accuracy. RKHS regression and RankSVM also achieve good accuracy when used with an RBF kernel. Traditional regression methods such as Bayesian lasso, wBSR and BayesC were found less suitable for ranking. Pearson correlation was found to correlate poorly with NDCG. Our study suggests two important messages. First, ranking methods are a promising research direction in GS. Second, NDCG can be a useful evaluation measure for GS. PMID:26068103

  12. Investigation of oxidation and tautomerization of a recently synthesized Schiff base in micellar media using multivariate curve resolution alternative least squares and rank annihilation factor analysis methods.

    PubMed

    Afkhami, Abbas; Khajavi, Farzad; Khanmohammadi, Hamid

    2009-08-11

    The oxidation of the recently synthesized Schiff base 3,6-bis((2-aminoethyl-5-Br-salicyliden)thio)pyridazine (PABST) with hydrogen peroxide was investigated using spectrophotometric studies. The reaction rate order and observed rate constant of the oxidation reaction was obtained in the mixture of N,N-dimethylformamide (DMF):water (30:70, v/v) at pH 10 using multivariate cure resolution alternative least squares (MCR-ALS) method and rank annihilation factor analysis (RAFA). The effective parameters on the oxidation rate constant such as percents of DMF, the effect of transition metals like Cu(2+), Zn(2+), Mn(2+) and Hg(2+) and the presence of surfactants were investigated. The keto-enol equilibria in DMF:water (30:70, v/v) solution at pH 7.6 was also investigated in the presence of surfactants. At concentrations above critical micelle concentration (cmc) of cationic surfactant cetyltrimethylammonium bromide (CTAB), the keto form was the predominant species, while at concentrations above cmc of anionic surfactant sodium dodecyl sulfate (SDS), the enol form was the predominant species. The kinetic reaction order and the rate constant of tautomerization in micellar medium were obtained using MCR-ALS and RAFA. The results obtained by both the methods were in a good agreement with each other. Also the effect of different volume percents of DMF on the rate constant of tautomerization was investigated. The neutral surfactant (Triton X-100) had no effect on tautomerization equilibrium. PMID:19591704

  13. Rasch analysis of rank-ordered data.

    PubMed

    Linacre, John M

    2006-01-01

    Theoretical and practical aspects of several methods for the construction of linear measures from rank-ordered data are presented. The final partial-rankings of 356 professional golfers participating in 47 stroke-play tournaments are used for illustration. The methods include decomposing the rankings into independent paired comparisons without ties, into dependent paired comparisons without ties and into independent paired comparisons with ties. A further method, which is easier to implement, entails modeling each tournament as a partial-credit item in which the rank of each golfer is treated as the observation of a category on a partial-credit rating scale. For the golf data, the partial-credit method yields measures with greater face validity than the paired comparison methods. The methods are implemented with the computer programs FACETS and WINSTEPS. PMID:16385155

  14. Problems with Percentiles: Student Growth Scores in New York's Teacher Evaluation System

    ERIC Educational Resources Information Center

    Patrick, Drew

    2016-01-01

    New York State has used the Growth Model for Educator Evaluation ratings since the 2011-2012 school year. Since that time, student growth percentiles have been used as the basis for teacher and principal ratings. While a great deal has been written about the use of student test scores to measures educator effectiveness, less attention has been…

  15. Percentile Norms for the AAHPER Cooperative Physical Education Tests. Research Report.

    ERIC Educational Resources Information Center

    Moodie, Allan G.

    Percentile scores for Vancouver students in grades 9, 10, 11 and 12 on the AAHPER Cooperative Physical Education Tests are presented. Two of the six forms of the tests were used in these administrations. Every form consists of 60 multiple-choice questions to be completed in 40 minutes. A single score, based on the number of questions answered…

  16. Age-specific percentile-based reference curve of serum procalcitonin concentrations in Japanese preterm infants.

    PubMed

    Fukuzumi, Noriko; Osawa, Kayo; Sato, Itsuko; Iwatani, Sota; Ishino, Ruri; Hayashi, Nobuhide; Iijima, Kazumoto; Saegusa, Jun; Morioka, Ichiro

    2016-01-01

    Procalcitonin (PCT) levels are elevated early after birth in newborn infants; however, the physiological features and reference of serum PCT concentrations have not been fully studied in preterm infants. The aims of the current study were to establish an age-specific percentile-based reference curve of serum PCT concentrations in preterm infants and determine the features. The PCT concentration peaked in infants at 1 day old and decreased thereafter. At 1 day old, serum PCT concentrations in preterm infants <34 weeks' gestational age were higher than those in late preterm infants between 34 and 36 weeks' gestational age or term infants ≥37 weeks' gestational age. Although the 50-percentile value in late preterm and term infants reached the adult normal level (0.1 ng/mL) at 5 days old, it did not in preterm infants. It took 9 weeks for preterm infants to reach it. Serum PCT concentrations at onset in late-onset infected preterm infants were over the 95-percentile value. We showed that the physiological feature in preterm infants was significantly different from that in late preterm infants, even in those <37 weeks' gestational age. To detect late-onset bacterial infection and sepsis, an age-specific percentile-based reference curve may be useful in preterm infants. PMID:27033746

  17. Age-specific percentile-based reference curve of serum procalcitonin concentrations in Japanese preterm infants

    PubMed Central

    Fukuzumi, Noriko; Osawa, Kayo; Sato, Itsuko; Iwatani, Sota; Ishino, Ruri; Hayashi, Nobuhide; Iijima, Kazumoto; Saegusa, Jun; Morioka, Ichiro

    2016-01-01

    Procalcitonin (PCT) levels are elevated early after birth in newborn infants; however, the physiological features and reference of serum PCT concentrations have not been fully studied in preterm infants. The aims of the current study were to establish an age-specific percentile-based reference curve of serum PCT concentrations in preterm infants and determine the features. The PCT concentration peaked in infants at 1 day old and decreased thereafter. At 1 day old, serum PCT concentrations in preterm infants <34 weeks’ gestational age were higher than those in late preterm infants between 34 and 36 weeks’ gestational age or term infants ≥37 weeks’ gestational age. Although the 50-percentile value in late preterm and term infants reached the adult normal level (0.1 ng/mL) at 5 days old, it did not in preterm infants. It took 9 weeks for preterm infants to reach it. Serum PCT concentrations at onset in late-onset infected preterm infants were over the 95-percentile value. We showed that the physiological feature in preterm infants was significantly different from that in late preterm infants, even in those <37 weeks’ gestational age. To detect late-onset bacterial infection and sepsis, an age-specific percentile-based reference curve may be useful in preterm infants. PMID:27033746

  18. AGE AND GENDER SPECIFIC BMI PERCENTILES ARE LIMITED FOR TRACKING THE CHILDHOOD OBESITY EPIDEMIC

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Purpose: To evaluate pediatric nutrition and physical activity interventions a reliable and feasible way of tracking change in body status is needed. Historically, body mass index (BMI) has been used in adults. BMI percentiles or Z scores, which are theoretically age and gender adjusted, have been...

  19. Student Growth Percentiles Based on MIRT: Implications of Calibrated Projection. CRESST Report 842

    ERIC Educational Resources Information Center

    Monroe, Scott; Cai, Li; Choi, Kilchan

    2014-01-01

    This research concerns a new proposal for calculating student growth percentiles (SGP, Betebenner, 2009). In Betebenner (2009), quantile regression (QR) is used to estimate the SGPs. However, measurement error in the score estimates, which always exists in practice, leads to bias in the QR-­based estimates (Shang, 2012). One way to address this…

  20. Risk for nonalcoholic fatty liver disease in Hispanic Youth with BMI > or = 95th percentile

    Technology Transfer Automated Retrieval System (TEKTRAN)

    To characterize children at risk for nonalcoholic fatty liver disease (NAFLD) and to explore possible mechanisms underlying the development of NAFLD in Hispanic youth with a body mass index > or =95th percentile. Hispanic nonoverweight (n = 475) and overweight (n = 517) children, ages 4 to 19 y, wer...

  1. User Guide for the 2014-15 Teacher Median Student Growth Percentile Report

    ERIC Educational Resources Information Center

    New Jersey Department of Education, 2016

    2016-01-01

    On March 22, 2016, the New Jersey Department of Education ("the Department") published a broadcast memo sharing secure district access to 2014-15 median Student Growth Percentile (mSGP) data for all qualifying teachers. These data describe student growth from the last school year, and comprise 10% of qualifying teachers' 2014-15…

  2. Using Percentile Schedules to Increase Eye Contact in Children with Fragile X Syndrome

    ERIC Educational Resources Information Center

    Hall, Scott S.; Maynes, Natalee P.; Reiss, Allan L.

    2009-01-01

    Aversion to eye contact is a common behavior of individuals diagnosed with Fragile X syndrome (FXS); however, no studies to date have attempted to increase eye-contact duration in these individuals. In this study, we employed a percentile reinforcement schedule with and without overcorrection to shape eye-contact duration of 6 boys with FXS.…

  3. PhyloPythiaS+: a self-training method for the rapid reconstruction of low-ranking taxonomic bins from metagenomes.

    PubMed

    Gregor, Ivan; Dröge, Johannes; Schirmer, Melanie; Quince, Christopher; McHardy, Alice C

    2016-01-01

    Background. Metagenomics is an approach for characterizing environmental microbial communities in situ, it allows their functional and taxonomic characterization and to recover sequences from uncultured taxa. This is often achieved by a combination of sequence assembly and binning, where sequences are grouped into 'bins' representing taxa of the underlying microbial community. Assignment to low-ranking taxonomic bins is an important challenge for binning methods as is scalability to Gb-sized datasets generated with deep sequencing techniques. One of the best available methods for species bins recovery from deep-branching phyla is the expert-trained PhyloPythiaS package, where a human expert decides on the taxa to incorporate in the model and identifies 'training' sequences based on marker genes directly from the sample. Due to the manual effort involved, this approach does not scale to multiple metagenome samples and requires substantial expertise, which researchers who are new to the area do not have. Results. We have developed PhyloPythiaS+, a successor to our PhyloPythia(S) software. The new (+) component performs the work previously done by the human expert. PhyloPythiaS+ also includes a new k-mer counting algorithm, which accelerated the simultaneous counting of 4-6-mers used for taxonomic binning 100-fold and reduced the overall execution time of the software by a factor of three. Our software allows to analyze Gb-sized metagenomes with inexpensive hardware, and to recover species or genera-level bins with low error rates in a fully automated fashion. PhyloPythiaS+ was compared to MEGAN, taxator-tk, Kraken and the generic PhyloPythiaS model. The results showed that PhyloPythiaS+ performs especially well for samples originating from novel environments in comparison to the other methods. Availability. PhyloPythiaS+ in a virtual machine is available for installation under Windows, Unix systems or OS X on: https://github.com/algbioi/ppsp/wiki. PMID:26870609

  4. Ranking scientific publications: the effect of nonlinearity

    NASA Astrophysics Data System (ADS)

    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.

  5. Ranking scientific publications: the effect of nonlinearity

    PubMed Central

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

    2014-01-01

    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. PMID:25322852

  6. Multiplex PageRank.

    PubMed

    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. PMID:24205186

  7. Ranking Refinement via Relevance Feedback in Geographic Information Retrieval

    NASA Astrophysics Data System (ADS)

    Villatoro-Tello, Esaú; Villaseñor-Pineda, Luis; Montes-Y-Gómez, Manuel

    Recent evaluation results from Geographic Information Retrieval (GIR) indicate that current information retrieval methods are effective to retrieve relevant documents for geographic queries, but they have severe difficulties to generate a pertinent ranking of them. Motivated by these results in this paper we present a novel re-ranking method, which employs information obtained through a relevance feedback process to perform a ranking refinement. Performed experiments show that the proposed method allows to improve the generated ranking from a traditional IR machine, as well as results from traditional re-ranking strategies such as query expansion via relevance feedback.

  8. Relationships between walking and percentiles of adiposity inolder and younger men

    SciTech Connect

    Williams, Paul T.

    2005-06-01

    To assess the relationship of weekly walking distance to percentiles of adiposity in elders (age {ge} 75 years), seniors (55 {le} age <75 years), middle-age men (35 {le} age <55 years), and younger men (18 {le} age <35 years old). Cross-sectional analyses of baseline questionnaires from 7,082 male participants of the National Walkers Health Study. The walkers BMIs were inversely and significantly associated with walking distance (kg/m{sup 2} per km/wk) in elders (slope {+-} SE: -0.032 {+-} 0.008), seniors (-0.045 {+-} 0.005), and middle-aged men (-0.037 {+-} 0.007), as were their waist circumferences (-0.091 {+-} 0.025, -0.045 {+-} 0.005, and -0.091 {+-} 0.015 cm per km/wk, respectively), and these slopes remained significant when adjusted statistically for reported weekly servings of meat, fish, fruit, and alcohol. The declines in BMI associated with walking distance were greater at the higher than lower percentiles of the BMI distribution. Specifically, compared to the decline at the 10th BMI percentile, the decline in BMI at the 90th percentile was 5.1-fold greater in elders, 5.9-fold greater in seniors, and 6.7-fold greater in middle-age men. The declines in waist circumference associated with walking distance were also greater among men with broader waistlines. Exercise-induced weight loss (or self-selection) causes an inverse relationship between adiposity and walking distance in men 35 and older that is substantially greater among fatter men.

  9. Trend estimates of AERONET-observed and model-simulated AOT percentiles between 1993 and 2013

    NASA Astrophysics Data System (ADS)

    Yoon, Jongmin; Pozzer, Andrea; Chang, Dong Yeong; Lelieveld, Jos

    2016-04-01

    Recent Aerosol Optical thickness (AOT) trend studies used monthly or annual arithmetic means that discard details of the generally right-skewed AOT distributions. Potentially, such results can be biased by extreme values (including outliers). This study additionally uses percentiles (i.e., the lowest 5%, 25%, 50%, 75% and 95% of the monthly cumulative distributions fitted to Aerosol Robotic Network (AERONET)-observed and ECHAM/MESSy Atmospheric Chemistry (EMAC)-model simulated AOTs) that are less affected by outliers caused by measurement error, cloud contamination and occasional extreme aerosol events. Since the limited statistical representativeness of monthly percentiles and means can lead to bias, this study adopts the number of observations as a weighting factor, which improves the statistical robustness of trend estimates. By analyzing the aerosol composition of AERONET-observed and EMAC-simulated AOTs in selected regions of interest, we distinguish the dominant aerosol types and investigate the causes of regional AOT trends. The simulated and observed trends are generally consistent with a high correlation coefficient (R = 0.89) and small bias (slope±2σ = 0.75 ± 0.19). A significant decrease in EMAC-decomposed AOTs by water-soluble compounds and black carbon is found over the USA and the EU due to environmental regulation. In particular, a clear reversal in the AERONET AOT trend percentiles is found over the USA, probably related to the AOT diurnal cycle and the frequency of wildfires.

  10. PhyloPythiaS+: a self-training method for the rapid reconstruction of low-ranking taxonomic bins from metagenomes

    PubMed Central

    Gregor, Ivan; Dröge, Johannes; Schirmer, Melanie; Quince, Christopher

    2016-01-01

    Background. Metagenomics is an approach for characterizing environmental microbial communities in situ, it allows their functional and taxonomic characterization and to recover sequences from uncultured taxa. This is often achieved by a combination of sequence assembly and binning, where sequences are grouped into ‘bins’ representing taxa of the underlying microbial community. Assignment to low-ranking taxonomic bins is an important challenge for binning methods as is scalability to Gb-sized datasets generated with deep sequencing techniques. One of the best available methods for species bins recovery from deep-branching phyla is the expert-trained PhyloPythiaS package, where a human expert decides on the taxa to incorporate in the model and identifies ‘training’ sequences based on marker genes directly from the sample. Due to the manual effort involved, this approach does not scale to multiple metagenome samples and requires substantial expertise, which researchers who are new to the area do not have. Results. We have developed PhyloPythiaS+, a successor to our PhyloPythia(S) software. The new (+) component performs the work previously done by the human expert. PhyloPythiaS+ also includes a new k-mer counting algorithm, which accelerated the simultaneous counting of 4–6-mers used for taxonomic binning 100-fold and reduced the overall execution time of the software by a factor of three. Our software allows to analyze Gb-sized metagenomes with inexpensive hardware, and to recover species or genera-level bins with low error rates in a fully automated fashion. PhyloPythiaS+ was compared to MEGAN, taxator-tk, Kraken and the generic PhyloPythiaS model. The results showed that PhyloPythiaS+ performs especially well for samples originating from novel environments in comparison to the other methods. Availability. PhyloPythiaS+ in a virtual machine is available for installation under Windows, Unix systems or OS X on: https://github.com/algbioi/ppsp/wiki. PMID

  11. Selection Methods for Undergraduate Admissions in Australia. Does the Australian Predominate Entry Scheme the Australian Tertiary Admissions Rank (ATAR) Have a Future?

    ERIC Educational Resources Information Center

    Blyth, Kathryn

    2014-01-01

    This article considers the Australian entry score system, the Australian Tertiary Admissions Rank (ATAR), and its usage as a selection mechanism for undergraduate places in Australian higher education institutions and asks whether its role as the main selection criterion will continue with the introduction of demand driven funding in 2012.…

  12. Quantum navigation and ranking in complex networks.

    PubMed

    Sánchez-Burillo, Eduardo; Duch, Jordi; Gómez-Gardeñes, Jesús; Zueco, David

    2012-01-01

    Complex networks are formal frameworks capturing the interdependencies between the elements of large systems and databases. This formalism allows to use network navigation methods to rank the importance that each constituent has on the global organization of the system. A key example is Pagerank navigation which is at the core of the most used search engine of the World Wide Web. Inspired in this classical algorithm, we define a quantum navigation method providing a unique ranking of the elements of a network. We analyze the convergence of quantum navigation to the stationary rank of networks and show that quantumness decreases the number of navigation steps before convergence. In addition, we show that quantum navigation allows to solve degeneracies found in classical ranks. By implementing the quantum algorithm in real networks, we confirm these improvements and show that quantum coherence unveils new hierarchical features about the global organization of complex systems. PMID:22930671

  13. Quantum Navigation and Ranking in Complex Networks

    PubMed Central

    Sánchez-Burillo, Eduardo; Duch, Jordi; Gómez-Gardeñes, Jesús; Zueco, David

    2012-01-01

    Complex networks are formal frameworks capturing the interdependencies between the elements of large systems and databases. This formalism allows to use network navigation methods to rank the importance that each constituent has on the global organization of the system. A key example is Pagerank navigation which is at the core of the most used search engine of the World Wide Web. Inspired in this classical algorithm, we define a quantum navigation method providing a unique ranking of the elements of a network. We analyze the convergence of quantum navigation to the stationary rank of networks and show that quantumness decreases the number of navigation steps before convergence. In addition, we show that quantum navigation allows to solve degeneracies found in classical ranks. By implementing the quantum algorithm in real networks, we confirm these improvements and show that quantum coherence unveils new hierarchical features about the global organization of complex systems. PMID:22930671

  14. RANKING INDOOR AIR TOXICS

    EPA Science Inventory

    The basis of the ranking is 10 monitoring studies chosen to represent "typical" concentrations of the pollutants found indoors. The studies were conducted in the United States during the last 15 years, and mainly focused on concentrations of pollutants in homes, schools, and off...

  15. Responses to the Rankings.

    ERIC Educational Resources Information Center

    Change, 1992

    1992-01-01

    Ten higher education professionals and one college senior comment on the "U.S. News and World Report" rankings of doctoral programs in six liberal arts disciplines. The authors' response to one set of comments and the comments of an executive editor from the magazine are also included. (MSE)

  16. Outflanking the Rankings Industry

    ERIC Educational Resources Information Center

    McGuire, Patricia

    2007-01-01

    In this article, the author argues that American higher education is allowing itself to be held hostage by the rankings industry, which can lead institutions to consider actions harmful to the public interest and encourage the public's infatuation with celebrity at the expense of substance. Instead of sitting quietly by during the upcoming ratings…

  17. College Rankings. ERIC Digest.

    ERIC Educational Resources Information Center

    Holub, Tamara

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

  18. Diversifying customer review rankings.

    PubMed

    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. PMID:25795511

  19. Ranking Adverse Drug Reactions With Crowdsourcing

    PubMed Central

    Gottlieb, Assaf; Hoehndorf, Robert; Dumontier, Michel

    2015-01-01

    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. PMID:25800813

  20. The role of entropy in word ranking

    NASA Astrophysics Data System (ADS)

    Mehri, Ali; Darooneh, Amir H.

    2011-09-01

    Entropy as a measure of complexity in the systems has been applied for ranking the words in the human written texts. We introduce a novel approach to evaluate accuracy for retrieved indices. We also have an illustrative comparison between proposed entropic metrics and some other methods in extracting the keywords. It seems that, some of the discussed metrics apply similar features for word ranking in the text. This work recommend the entropy as a systematic measure in text mining.

  1. A note on rank reduction in sparse multivariate regression

    PubMed Central

    Chen, Kun; Chan, Kung-Sik

    2016-01-01

    A reduced-rank regression with sparse singular value decomposition (RSSVD) approach was proposed by Chen et al. for conducting variable selection in a reduced-rank model. To jointly model the multivariate response, the method efficiently constructs a prespecified number of latent variables as some sparse linear combinations of the predictors. Here, we generalize the method to also perform rank reduction, and enable its usage in reduced-rank vector autoregressive (VAR) modeling to perform automatic rank determination and order selection. We show that in the context of stationary time-series data, the generalized approach correctly identifies both the model rank and the sparse dependence structure between the multivariate response and the predictors, with probability one asymptotically. We demonstrate the efficacy of the proposed method by simulations and analyzing a macro-economical multivariate time series using a reduced-rank VAR model. PMID:26997938

  2. Let your users do the ranking.

    SciTech Connect

    Spomer, Judith E.

    2010-12-01

    Ranking search results is a thorny issue for enterprise search. Search engines rank results using a variety of sophisticated algorithms, but users still complain that search can't ever seem to find anything useful or relevant! The challenge is to provide results that are ranked according to the users' definition of relevancy. Sandia National Laboratories has enhanced its commercial search engine to discover user preferences, re-ranking results accordingly. Immediate positive impact was achieved by modeling historical data consisting of user queries and subsequent result clicks. New data is incorporated into the model daily. An important benefit is that results improve naturally and automatically over time as a function of user actions. This session presents the method employed, how it was integrated with the search engine,metrics illustrating the subsequent improvement to the users' search experience, and plans for implementation with Sandia's FAST for SharePoint 2010 search engine.

  3. A COMPARISON OF STUDENTS SCORING ABOVE THE EIGHTIETH PERCENTILE OR BELOW THE TWENTIETH PERCENTILE ON EITHER THE SCHOOL AND COLLEGE ABILITY TEST OR THE WATSON-GLASER TEST OF CRITICAL THINKING.

    ERIC Educational Resources Information Center

    CURRY, JOHN

    IN ORDER TO ESTABLISH THE FEASIBILITY OF A CUT-OFF SCORE FOR ENTRANCE INTO TEACHER EDUCATION PROGRAMS AT NORTH TEXAS STATE UNIVERSITY, SCORES OF 1,346 STUDENTS WHO EITHER PLACED ABOVE THE 80TH PERCENTILE (N-672) OR BELOW THE 20TH PERCENTILE (N-674) ON EITHER THE SCHOOL AND COLLEGE ABILITY TEST OR THE WATSON-GLASER TEST OF CRITICAL THINKING WERE…

  4. University Rankings and Social Science

    ERIC Educational Resources Information Center

    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…

  5. Hierarchical Rank Aggregation with Applications to Nanotoxicology

    PubMed Central

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

    2014-01-01

    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. PMID:24839387

  6. Ranking and Sequencing Model

    Energy Science and Technology Software Center (ESTSC)

    2009-08-13

    This database application (commonly called the Supermodel) provides a repository for managing critical facility/project information, allows the user to subjectively an objectively assess key criteria , quantify project risks, develop ROM cost estimates, determine facility/project end states, ultimately performing risk-based modeling to rank facilities/project based on risk, sequencing project schedules and provides an optimized recommended sequencing/scheduling of these projects which maximize the S&M cost savings to perform closure projects which benefit all stakeholders.

  7. Ordinal Distance Metric Learning for Image Ranking.

    PubMed

    Li, Changsheng; Liu, Qingshan; Liu, Jing; Lu, Hanqing

    2015-07-01

    Recently, distance metric learning (DML) has attracted much attention in image retrieval, but most previous methods only work for image classification and clustering tasks. In this brief, we focus on designing ordinal DML algorithms for image ranking tasks, by which the rank levels among the images can be well measured. We first present a linear ordinal Mahalanobis DML model that tries to preserve both the local geometry information and the ordinal relationship of the data. Then, we develop a nonlinear DML method by kernelizing the above model, considering of real-world image data with nonlinear structures. To further improve the ranking performance, we finally derive a multiple kernel DML approach inspired by the idea of multiple-kernel learning that performs different kernel operators on different kinds of image features. Extensive experiments on four benchmarks demonstrate the power of the proposed algorithms against some related state-of-the-art methods. PMID:25163071

  8. Texture classification by local rank correlation

    NASA Technical Reports Server (NTRS)

    Harwood, D.; Subbarao, M.; Davis, L. S.

    1985-01-01

    A new approach to texture classification based on local rank correlation is proposed here. Its performance is compared with Laws' method which uses local convolution with feature masks. In the experiments, texture samples are classified based on their distribution of local statistics, either rank correlations or convolutions. The new method achieves generally optimal classification rates. It appears to be more robust because local order statistics are unaffected by local sample differences due to monotonic shifts of texture gray values and are less sensitive to noise.

  9. State disparities in time trends of adolescent body mass index percentile and weight-related behaviors in the United States.

    PubMed

    Taber, Daniel R; Stevens, June; Poole, Charles; Maciejewski, Matthew L; Evenson, Kelly R; Ward, Dianne S

    2012-02-01

    Evidence is conflicting as to whether youth obesity prevalence has reached a plateau in the United States overall. Trends vary by state, and experts recommend exploring whether trends in weight-related behaviors are associated with changes in weight status trends. Thus, our objective was to estimate between-state variation in time trends of adolescent body mass index (BMI) percentile and weight-related behaviors from 2001 to 2007. A time series design combined cross-sectional Youth Risk Behavior Survey data from 272,044 adolescents in 29 states from 2001 to 2007. Self-reported height, weight, sports participation, physical education, television viewing, and daily consumption of 100% fruit juice, milk, and fruits and vegetables were collected. Linear mixed models estimated state variance in time trends of behaviors and BMI percentile. Across states, BMI percentile trends were consistent despite differences in behavioral trends. Boys experienced a modest linear increase in BMI percentile (ß = 0.18, 95% CI: 0.07, 0.30); girls experienced a non-linear increase, as the rate of increase declined over time from 1.02 units in 2001-2002 (95% CI: 0.68, 1.36) to 0.23 units in 2006-2007 (95% CI: -0.09, 0.56). States in which BMI percentile decreased experienced a greater decrease in TV viewing than states where BMI percentile increased. Otherwise, states with disparate BMI percentile trends did not differ with respect to behaviors. Future research should explore the role of other behaviors (e.g., soda consumption), measurement units (e.g., portion size), and societal trends (e.g., urban sprawl) on state and national adiposity trends. PMID:21773818

  10. Risk ranking by perception

    SciTech Connect

    Osei, E.K.; Amoh, G.E.A.; Schandorf, C.

    1997-02-01

    The study of people`s perception and acceptability of risk is important in understanding the public reaction to technology and its environmental and health impact. The perception of risk depends on several factors, including early experiences, education, controllability of the risk, the type of consequence, and the type of person(s) who makes the judgment. This paper reviews some of the main factors influencing people`s perception and acceptability of risk. Knowledge about which factors influence the perception of risk may enhance the understanding of different points of view brought into risk controversies, improve risk communication, and facilitate policy making. Results from a risk ranking by perception survey Conducted in Ghana are also presented. 18 refs., 8 figs., 1 tab.

  11. The Privileges of Rank

    PubMed Central

    MacLean, Alair

    2010-01-01

    This article examines the effects of peacetime cold war military service on the life course according to four potentially overlapping theories that state that military service (1) was a disruption, (2) was a positive turning point, (3) allowed veterans to accumulate advantage, and (4) was an agent of social reproduction. The article argues that the extent to which the effect of military service on veterans' lives corresponds with one or another of the preceding theories depends on historical shifts in three dimensions: conscription, conflict, and benefits. Military service during the peacetime draft era of the late 1950s had a neutral effect on the socioeconomic attainment of enlisted veterans. However, it had a positive effect on veterans who served as officers, which partly stemmed from status reproduction and selection. Yet net of pre-service and educational differences by rank, officers in this peacetime draft era were still able to accumulate advantage. PMID:20842210

  12. Development of a Three-Dimensional Finite Element Chest Model for the 5(th) Percentile Female.

    PubMed

    Kimpara, Hideyuki; Lee, Jong B; Yang, King H; King, Albert I; Iwamoto, Masami; Watanabe, Isao; Miki, Kazuo

    2005-11-01

    Several three-dimensional (3D) finite element (FE) models of the human body have been developed to elucidate injury mechanisms due to automotive crashes. However, these models are mainly focused on 50(th) percentile male. As a first step towards a better understanding of injury biomechanics in the small female, a 3D FE model of a 5(th) percentile female human chest (FEM-5F) has been developed and validated against experimental data obtained from two sets of frontal impact, one set of lateral impact, two sets of oblique impact and a series of ballistic impacts. Two previous FE models, a small female Total HUman Model for Safety (THUMS-AF05) occupant version 1.0Beta (Kimpara et al. 2002) and the Wayne State University Human Thoracic Model (WSUHTM, Wang 1995 and Shah et al. 2001) were integrated and modified for this model development. The model incorporated not only geometrical gender differences, such as location of the internal organs and structure of the bony skeleton, but also the biomechanical differences of the ribs due to gender. It includes a detailed description of the sternum, ribs, costal cartilage, thoracic spine, skin, superficial muscles, intercostal muscles, heart, lung, diaphragm, major blood vessels and simplified abdominal internal organs and has been validated against a series of six cadaveric experiments on the small female reported by Nahum et al. (1970), Kroell et al. (1974), Viano (1989), Talantikite et al. (1998) and Wilhelm (2003). Results predicted by the model were well-matched to these experimental data for a range of impact speeds and impactor masses. More research is needed in order to increase the accuracy of predicting rib fractures so that the mechanisms responsible for small female injury can be more clearly defined. PMID:17096277

  13. Low-rank coal research

    SciTech Connect

    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).

  14. Wikipedia ranking of world universities

    NASA Astrophysics Data System (ADS)

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

    2016-03-01

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

  15. MRI Contrasts in High Rank Rotating Frames

    PubMed Central

    Liimatainen, Timo; Hakkarainen, Hanne; Mangia, Silvia; Huttunen, Janne M.J.; Storino, Christine; Idiyatullin, Djaudat; Sorce, Dennis; Garwood, Michael; Michaeli, Shalom

    2014-01-01

    Purpose MRI relaxation measurements are performed in the presence of a fictitious magnetic field in the recently described technique known as RAFF (Relaxation Along a Fictitious Field). This method operates in the 2nd rotating frame (rank n = 2) by utilizing a non-adiabatic sweep of the radiofrequency effective field to generate the fictitious magnetic field. In the present study, the RAFF method is extended for generating MRI contrasts in rotating frames of ranks 1 ≤ n ≤ 5. The developed method is entitled RAFF in rotating frame of rank n (RAFFn). Methods RAFFn pulses were designed to generate fictitious fields that allow locking of magnetization in rotating frames of rank n. Contrast generated with RAFFn was studied using Bloch-McConnell formalism together with experiments on human and rat brains. Results Tolerance to B0 and B1 inhomogeneities and reduced specific absorption rate with increasing n in RAFFn were demonstrated. Simulations of exchange-induced relaxations revealed enhanced sensitivity of RAFFn to slow exchange. Consistent with such feature, an increased grey/white matter contrast was observed in human and rat brain as n increased. Conclusion RAFFn is a robust and safe rotating frame relaxation method to access slow molecular motions in vivo. PMID:24523028

  16. A low rank approach to automatic differentiation.

    SciTech Connect

    Abdel-Khalik, H. S.; Hovland, P. D.; Lyons, A.; Stover, T. E.; Utke, J.; Mathematics and Computer Science; North Carolina State Univ.; Univ. of Chicago

    2008-01-01

    This manuscript introduces a new approach for increasing the efficiency of automatic differentiation (AD) computations for estimating the first order derivatives comprising the Jacobian matrix of a complex large-scale computational model. The objective is to approximate the entire Jacobian matrix with minimized computational and storage resources. This is achieved by finding low rank approximations to a Jacobian matrix via the Efficient Subspace Method (ESM). Low rank Jacobian matrices arise in many of today's important scientific and engineering problems, e.g. nuclear reactor calculations, weather climate modeling, geophysical applications, etc. A low rank approximation replaces the original Jacobian matrix J (whose size is dictated by the size of the input and output data streams) with matrices of much smaller dimensions (determined by the numerical rank of the Jacobian matrix). This process reveals the rank of the Jacobian matrix and can be obtained by ESM via a series of r randomized matrix-vector products of the form: Jq, and J{sup T} {omega} which can be evaluated by the AD forward and reverse modes, respectively.

  17. Ranking nodes in growing networks: When PageRank fails

    NASA Astrophysics Data System (ADS)

    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.

  18. Hazard Ranking System evaluation of CERCLA (Comprehensive Environmental Response, Compensation, and Liability Act) inactive waste sites at Hanford: Volume 1, Evaluation methods and results

    SciTech Connect

    Stenner, R.D.; Cramer, K.H.; Higley, K.A.; Jette, S.J.; Lamar, D.A.; McLaughlin, T.J.; Sherwood, D.R.; Van Houten, N.C.

    1988-10-01

    The purpose of this report is to formally document the individual site Hazard Ranking System (HRS) evaluations conducted as part of the preliminary assessment/site inspection (PA/SI) activities at the US Department of Energy (DOE) Hanford Site. These activities were carried out pursuant to the DOE orders that describe the Comprehensive Environmental Response, Compensation, and Liability Act (CERCLA) Program addressing the cleanup of inactive waste sites. These orders incorporate the US Environmental Protection Agency methodology, which is based on the Superfund Amendments and Reauthorization Act of 1986 (SARA). The methodology includes six parts: PA/SI, remedial investigation/feasibility study, record of decision, design and implementation of remedial action, operation and monitoring, and verification monitoring. Volume 1 of this report discusses the CERCLA inactive waste-site evaluation process, assumptions, and results of the HRS methodology employed. Volume 2 presents the data on the individual CERCLA engineered-facility sites at Hanford, as contained in the Hanford Inactive Site Surveillance (HISS) Data Base. Volume 3 presents the data on the individual CERCLA unplanned-release sites at Hanford, as contained in the HISS Data Base. 34 refs., 43 figs., 47 tabs.

  19. A method to assess the ranking importance of uncertainties of residual and dissolution trapping of CO2 on a large-scale storage site

    NASA Astrophysics Data System (ADS)

    Audigane, P.; Rohmer, J.; Manceau, J. C.

    2014-12-01

    The long term fate of mobile CO2 remaining after the injection period is a crucial issue for regulators and operators. There are needs to evaluate properly the amount of gas free to migrate and to estimate the fluid movements at long time scales. Often the difficulty is to manage the computational time to assess the large time and dimension scale of the problem. The second limitation is the large level of uncertainty associated to the computation prediction. A variance-based global sensitivity analysis is proposed to assess the importance ranking of uncertainty sources, with regards to the behavior of the mobile CO2 during the post-injection period. We consider three output parameters which characterize the location and the quantity of mobile CO2, considering residual and dissolution trapping. To circumvent both (i) the large number of computationally intensive reservoir-scale flow simulations and (ii) the different nature of uncertainties whether linked to parameters (continuous variables) or to modeling assumptions (scenario-like variables) we propose to use advanced meta-modeling techniques of ACOSSO-type. The feasibility of the approach is demonstrated using a potential site for CO2 storage in the Paris basin (France), for which the amount, nature and quality of the data available at disposal and the associated uncertainties can be seen as representative to those of a storage project at the post-screening stage. A special attention has been paid to confront the results of the sensitivity analysis with the physical interpretation of the processes.

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

    NASA Astrophysics Data System (ADS)

    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

  1. Obsession with Rankings Goes Global

    ERIC Educational Resources Information Center

    Labi, Aisha

    2008-01-01

    A Chinese list of the world's top universities would seem an unlikely concern for French politicians. But this year, France's legislature took aim at the annual rankings produced by Shanghai Jiao Tong University, which claims to list the 500 best universities in the world. The highest-ranked French entry, Universite Pierre et Marie Curie, comes in…

  2. Technical Pitfalls in University Rankings

    ERIC Educational Resources Information Center

    Bougnol, Marie-Laure; Dulá, Jose H.

    2015-01-01

    Academicians, experts, and other stakeholders have contributed extensively to the literature on university rankings also known as "league tables". Often the tone is critical usually focused on the subjective aspects of the process; e.g., the list of the universities' attributes used in the rankings, their respective weights, and the size…

  3. University Rankings in Critical Perspective

    ERIC Educational Resources Information Center

    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…

  4. University Ranking as Social Exclusion

    ERIC Educational Resources Information Center

    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…

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

    ERIC Educational Resources Information Center

    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…

  6. Chemical comminution and deashing of low-rank coals

    DOEpatents

    Quigley, David R.

    1992-01-01

    A method of chemically comminuting a low-rank coal while at the same time increasing the heating value of the coal. A strong alkali solution is added to a low-rank coal to solubilize the carbonaceous portion of the coal, leaving behind the noncarbonaceous mineral matter portion. The solubilized coal is precipitated from solution by a multivalent cation, preferably calcium.

  7. Chemical comminution and deashing of low-rank coals

    DOEpatents

    Quigley, David R.

    1992-12-01

    A method of chemically comminuting a low-rank coal while at the same time increasing the heating value of the coal. A strong alkali solution is added to a low-rank coal to solubilize the carbonaceous portion of the coal, leaving behind the noncarbonaceous mineral matter portion. The solubilized coal is precipitated from solution by a multivalent cation, preferably calcium.

  8. Likelihoods for fixed rank nomination networks.

    PubMed

    Hoff, Peter; Fosdick, Bailey; Volfovsky, Alex; Stovel, Katherine

    2013-12-01

    Many studies that gather social network data use survey methods that lead to censored, missing, or otherwise incomplete information. For example, the popular fixed rank nomination (FRN) scheme, often used in studies of schools and businesses, asks study participants to nominate and rank at most a small number of contacts or friends, leaving the existence of other relations uncertain. However, most statistical models are formulated in terms of completely observed binary networks. Statistical analyses of FRN data with such models ignore the censored and ranked nature of the data and could potentially result in misleading statistical inference. To investigate this possibility, we compare Bayesian parameter estimates obtained from a likelihood for complete binary networks with those obtained from likelihoods that are derived from the FRN scheme, and therefore accommodate the ranked and censored nature of the data. We show analytically and via simulation that the binary likelihood can provide misleading inference, particularly for certain model parameters that relate network ties to characteristics of individuals and pairs of individuals. We also compare these different likelihoods in a data analysis of several adolescent social networks. For some of these networks, the parameter estimates from the binary and FRN likelihoods lead to different conclusions, indicating the importance of analyzing FRN data with a method that accounts for the FRN survey design. PMID:25110586

  9. StructRank: a new approach for ligand-based virtual screening.

    PubMed

    Rathke, Fabian; Hansen, Katja; Brefeld, Ulf; Müller, Klaus-Robert

    2011-01-24

    Screening large libraries of chemical compounds against a biological target, typically a receptor or an enzyme, is a crucial step in the process of drug discovery. Virtual screening (VS) can be seen as a ranking problem which prefers as many actives as possible at the top of the ranking. As a standard, current Quantitative Structure-Activity Relationship (QSAR) models apply regression methods to predict the level of activity for each molecule and then sort them to establish the ranking. In this paper, we propose a top-k ranking algorithm (StructRank) based on Support Vector Machines to solve the early recognition problem directly. Empirically, we show that our ranking approach outperforms not only regression methods but another ranking approach recently proposed for QSAR ranking, RankSVM, in terms of actives found. PMID:21166393

  10. Universal scaling in sports ranking

    NASA Astrophysics Data System (ADS)

    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.

  11. A theory of measuring, electing, and ranking

    PubMed Central

    Balinski, Michel; Laraki, Rida

    2007-01-01

    The impossibility theorems that abound in the theory of social choice show that there can be no satisfactory method for electing and ranking in the context of the traditional, 700-year-old model. A more realistic model, whose antecedents may be traced to Laplace and Galton, leads to a new theory that avoids all impossibilities with a simple and eminently practical method, “the majority judgement.” It has already been tested. PMID:17496140

  12. Analysis of the Stability of Teacher-Level Growth Scores from the Student Growth Percentile Model. REL 2016-104

    ERIC Educational Resources Information Center

    Lash, Andrea; Makkonen, Reino; Tran, Loan; Huang, Min

    2016-01-01

    This study, undertaken at the request of the Nevada Department of Education, examined the stability over years of teacher-level growth scores from the Student Growth Percentile (SGP) model, which many states and districts have selected as a measure of effectiveness in their teacher evaluation systems. The authors conducted a generalizability study…

  13. Validation of the 5th and 95th Percentile Hybrid III Anthropomorphic Test Device Finite Element Model

    NASA Technical Reports Server (NTRS)

    Lawrence, C.; Somers, J. T.; Baldwin, M. A.; Wells, J. A.; Newby, N.; Currie, N. J.

    2014-01-01

    NASA spacecraft design requirements for occupant protection are a combination of the Brinkley criteria and injury metrics extracted from anthropomorphic test devices (ATD's). For the ATD injury metrics, the requirements specify the use of the 5th percentile female Hybrid III and the 95th percentile male Hybrid III. Furthermore, each of these ATD's is required to be fitted with an articulating pelvis and a straight spine. The articulating pelvis is necessary for the ATD to fit into spacecraft seats, while the straight spine is required as injury metrics for vertical accelerations are better defined for this configuration. The requirements require that physical testing be performed with both ATD's to demonstrate compliance. Before compliance testing can be conducted, extensive modeling and simulation are required to determine appropriate test conditions, simulate conditions not feasible for testing, and assess design features to better ensure compliance testing is successful. While finite element (FE) models are currently available for many of the physical ATD's, currently there are no complete models for either the 5th percentile female or the 95th percentile male Hybrid III with a straight spine and articulating pelvis. The purpose of this work is to assess the accuracy of the existing Livermore Software Technology Corporation's FE models of the 5th and 95th percentile ATD's. To perform this assessment, a series of tests will be performed at Wright Patterson Air Force Research Lab using their horizontal impact accelerator sled test facility. The ATD's will be placed in the Orion seat with a modified-advanced-crew-escape-system (MACES) pressure suit and helmet, and driven with loadings similar to what is expected for the actual Orion vehicle during landing, launch abort, and chute deployment. Test data will be compared to analytical predictions and modelling uncertainty factors will be determined for each injury metric. Additionally, the test data will be used to

  14. The Association of Weight Percentile and Motor Vehicle Crash Injury Among 3 to 8 Year Old Children

    PubMed Central

    Zonfrillo, Mark R.; Nelson, Kyle A.; Durbin, Dennis R.; Kallan, Michael J.

    2010-01-01

    The use of age-appropriate child restraint systems significantly reduces injury and death associated with motor vehicle crashes (MVCs). Pediatric obesity has become a global epidemic. Although recent evidence suggests a possible association between pediatric obesity and MVC-related injury, there are potential misclassifications of body mass index from under-estimated height in younger children. Given this limitation, age- and sex-specific weight percentiles can be used as a proxy of weight status. The specific aim of this study was to determine the association between weight percentile and the risk of significant injury for children 3–8 years in MVCs. This was a cross-sectional study of children aged 3–8 years in MVCs in 16 US states, with data collected via insurance claims records and a telephone survey from 12/1/98–11/30/07. Parent-reported injuries with an abbreviated Injury Scale (AIS) score of 2+ indicated a clinically significant injury. Age- and sex-specific weight percentiles were calculated using pediatric norms. The study sample included 9,327 children aged 3–8 years (weighted to represent 157,878 children), of which 0.96% sustained clinically significant injuries. There was no association between weight percentiles and overall injury when adjusting for restraint type (p=0.71). However, increasing weight percentiles were associated with lower extremity injuries at a level that approached significance (p=0.053). Further research is necessary to describe mechanisms for weight-related differences in injury risk. Parents should continue to properly restrain their children in accordance with published guidelines. PMID:21050602

  15. Influence Analysis of Ranking Data.

    ERIC Educational Resources Information Center

    Poon, Wai-Yin; Chan, Wai

    2002-01-01

    Developed diagnostic measures to identify observations in Thurstonian models for ranking data that unduly influence parameter estimates obtained by the partition maximum likelihood approach of W. Chan and P. Bender (1998). (SLD)

  16. RANK and RANK ligand expression in primary human osteosarcoma.

    PubMed

    Branstetter, Daniel; Rohrbach, Kathy; Huang, Li-Ya; Soriano, Rosalia; Tometsko, Mark; Blake, Michelle; Jacob, Allison P; Dougall, William C

    2015-09-01

    Receptor activator of nuclear factor kappa-B ligand (RANKL) is an essential mediator of osteoclast formation, function and survival. In patients with solid tumor metastasis to the bone, targeting the bone microenvironment by inhibition of RANKL using denosumab, a fully human monoclonal antibody (mAb) specific to RANKL, has been demonstrated to prevent tumor-induced osteolysis and subsequent skeletal complications. Recently, a prominent functional role for the RANKL pathway has emerged in the primary bone tumor giant cell tumor of bone (GCTB). Expression of both RANKL and RANK is extremely high in GCTB tumors and denosumab treatment was associated with tumor regression and reduced tumor-associated bone lysis in GCTB patients. In order to address the potential role of the RANKL pathway in another primary bone tumor, this study assessed human RANKL and RANK expression in human primary osteosarcoma (OS) using specific mAbs, validated and optimized for immunohistochemistry (IHC) or flow cytometry. 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

  17. Reduced-Rank Adaptive Filtering Using Krylov Subspace

    NASA Astrophysics Data System (ADS)

    Burykh, Sergueï; Abed-Meraim, Karim

    2003-12-01

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

  18. Energy and environmental research emphasizing low-rank coal--Task 4.4: Development of supercritical fluid extraction methods for the quantitation of sulfur forms in coal

    SciTech Connect

    Timpe, R.C.

    1995-04-01

    Current analytical methods are inadequate for accurately measuring sulfur forms in coal. This task was concerned with developing methods to quantitate and identify major sulfur forms in coal based on direct measurement (as opposed to present techniques based on indirect measurement and difference values). The focus was on the forms that were least understood and for which the analytical methods have been the poorest, i.e., organic and elemental sulfur. Improved measurement techniques for sulfatic and pyritic sulfur also need to be developed. A secondary goal was to understand the interconversion of sulfur forms in coal during thermal processing. This task had as its focus the development of selective extraction methods that will allow the direct measurement of sulfur content in each form. Therefore, selective extraction methods were needed for the major sulfur forms in coal, including elemental, pyritic, sulfatic, and organic sulfur. This study was a continuation of that of previous analytical method development for sulfur forms in coal which resulted in the successful isolation and quantitation of elemental and sulfatic sulfur. Super- and subcritical extractions with methanol or water with and without additives were investigated in an attempt to develop methods for pyritic and organic sulfur forms analysis in coal. Based on these studies, a sequential extraction scheme that is capable of selectively determining elemental, sulfatic, pyritic and two forms of organic sulfur is presented here.

  19. Social Bookmarking Induced Active Page Ranking

    NASA Astrophysics Data System (ADS)

    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.

  20. Bayesian Inference of Natural Rankings in Incomplete Competition Networks

    PubMed Central

    Park, Juyong; Yook, Soon-Hyung

    2014-01-01

    Competition between a complex system's constituents and a corresponding reward mechanism based on it have profound influence on the functioning, stability, and evolution of the system. But determining the dominance hierarchy or ranking among the constituent parts from the strongest to the weakest – essential in determining reward and penalty – is frequently an ambiguous task due to the incomplete (partially filled) nature of competition networks. Here we introduce the “Natural Ranking,” an unambiguous ranking method applicable to a round robin tournament, and formulate an analytical model based on the Bayesian formula for inferring the expected mean and error of the natural ranking of nodes from an incomplete network. We investigate its potential and uses in resolving important issues of ranking by applying it to real-world competition networks. PMID:25163528

  1. Ranking nodes in growing networks: When PageRank fails

    PubMed Central

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

    2015-01-01

    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. PMID:26553630

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

    NASA Astrophysics Data System (ADS)

    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.

  3. A cautionary note on the rank product statistic.

    PubMed

    Koziol, James A

    2016-06-01

    The rank product method introduced by Breitling R et al. [2004, FEBS Letters 573, 83-92] has rapidly generated popularity in practical settings, in particular, detecting differential expression of genes in microarray experiments. The purpose of this note is to point out a particular property of the rank product method, namely, its differential sensitivity to over- and underexpression. It turns out that overexpression is less likely to be detected than underexpression with the rank product statistic. We have conducted both empirical and exact power studies that demonstrate this phenomenon, and summarize these findings in this note. PMID:27160968

  4. Compressive Sensing via Nonlocal Smoothed Rank Function.

    PubMed

    Fan, Ya-Ru; Huang, Ting-Zhu; Liu, Jun; Zhao, Xi-Le

    2016-01-01

    Compressive sensing (CS) theory asserts that we can reconstruct signals and images with only a small number of samples or measurements. Recent works exploiting the nonlocal similarity have led to better results in various CS studies. To better exploit the nonlocal similarity, in this paper, we propose a non-convex smoothed rank function based model for CS image reconstruction. We also propose an efficient alternating minimization method to solve the proposed model, which reduces a difficult and coupled problem to two tractable subproblems. Experimental results have shown that the proposed method performs better than several existing state-of-the-art CS methods for image reconstruction. PMID:27583683

  5. Percentile Values for Running Sprint Field Tests in Children Ages 6-17 Years: Influence of Weight Status

    ERIC Educational Resources Information Center

    Castro-Pinero, Jose; Gonzalez-Montesinos, Jose Luis; Keating, Xiaofen D.; Mora, Jesus; Sjostrom, Michael; Ruiz, Jonatan R.

    2010-01-01

    The aim of this study was to provide percentile values for six different sprint tests in 2,708 Spanish children (1,234 girls) ages 6-17.9 years. We also examined the influence of weight status on sprint performance across age groups, with a focus on underweight and obese groups. We used the 20-m, 30-m, and 50-m running sprint standing start and…

  6. Relevance Preserving Projection and Ranking for Web Image Search Reranking.

    PubMed

    Ji, Zhong; Pang, Yanwei; Li, Xuelong

    2015-11-01

    An image search reranking (ISR) technique aims at refining text-based search results by mining images' visual content. Feature extraction and ranking function design are two key steps in ISR. Inspired by the idea of hypersphere in one-class classification, this paper proposes a feature extraction algorithm named hypersphere-based relevance preserving projection (HRPP) and a ranking function called hypersphere-based rank (H-Rank). Specifically, an HRPP is a spectral embedding algorithm to transform an original high-dimensional feature space into an intrinsically low-dimensional hypersphere space by preserving the manifold structure and a relevance relationship among the images. An H-Rank is a simple but effective ranking algorithm to sort the images by their distances to the hypersphere center. Moreover, to capture the user's intent with minimum human interaction, a reversed k-nearest neighbor (KNN) algorithm is proposed, which harvests enough pseudorelevant images by requiring that the user gives only one click on the initially searched images. The HRPP method with reversed KNN is named one-click-based HRPP (OC-HRPP). Finally, an OC-HRPP algorithm and the H-Rank algorithm form a new ISR method, H-reranking. Extensive experimental results on three large real-world data sets show that the proposed algorithms are effective. Moreover, the fact that only one relevant image is required to be labeled makes it has a strong practical significance. PMID:26011885

  7. Rank in Class and College Admission

    ERIC Educational Resources Information Center

    Walker, Karen

    2010-01-01

    Traditionally class rankings have been used by high schools to determine valedictorians and salutatorians. These rankings have also been used by colleges to make admission decisions and for awarding scholarships. While there is no direct link between college rank and college admission, there is evidence that not using class rank can reduce stress…

  8. The Globalization of College and University Rankings

    ERIC Educational Resources Information Center

    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 University Rankings…

  9. Using Microsoft Excel to compute the 5% overall site X/Q value and the 95th percentile of the distribution of doses to the nearest maximally exposed offsite individual (MEOI).

    PubMed

    Vickers, Linda D

    2010-05-01

    This paper describes the method using Microsoft Excel (Microsoft Corporation One Microsoft Way Redmond, WA 98052-6399) to compute the 5% overall site X/Q value and the 95th percentile of the distribution of doses to the nearest maximally exposed offsite individual (MEOI) in accordance with guidance from DOE-STD-3009-1994 and U.S. NRC Regulatory Guide 1.145-1982. The accurate determination of the 5% overall site X/Q value is the most important factor in the computation of the 95th percentile of the distribution of doses to the nearest MEOI. This method should be used to validate software codes that compute the X/Q. The 95th percentile of the distribution of doses to the nearest MEOI must be compared to the U.S. DOE Evaluation Guide of 25 rem to determine the relative severity of hazard to the public from a postulated, unmitigated design basis accident that involves an offsite release of radioactive material. PMID:20386192

  10. Time evolution of Wikipedia network ranking

    NASA Astrophysics Data System (ADS)

    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.

  11. On Rank Driven Dynamical Systems

    NASA Astrophysics Data System (ADS)

    Veerman, J. J. P.; Prieto, F. J.

    2014-08-01

    We investigate a class of models related to the Bak-Sneppen (BS) model, initially proposed to study evolution. The BS model is extremely simple and yet captures some forms of "complex behavior" such as self-organized criticality that is often observed in physical and biological systems. In this model, random fitnesses in are associated to agents located at the vertices of a graph . Their fitnesses are ranked from worst (0) to best (1). At every time-step the agent with the worst fitness and some others with a priori given rank probabilities are replaced by new agents with random fitnesses. We consider two cases: The exogenous case where the new fitnesses are taken from an a priori fixed distribution, and the endogenous case where the new fitnesses are taken from the current distribution as it evolves. We approximate the dynamics by making a simplifying independence assumption. We use Order Statistics and Dynamical Systems to define a rank-driven dynamical system that approximates the evolution of the distribution of the fitnesses in these rank-driven models, as well as in the BS model. For this simplified model we can find the limiting marginal distribution as a function of the initial conditions. Agreement with experimental results of the BS model is excellent.

  12. Querying and Ranking XML Documents.

    ERIC Educational Resources Information Center

    Schlieder, Torsten; Meuss, Holger

    2002-01-01

    Discussion of XML, information retrieval, precision, and recall focuses on a retrieval technique that adopts the similarity measure of the vector space model, incorporates the document structure, and supports structured queries. Topics include a query model based on tree matching; structured queries and term-based ranking; and term frequency and…

  13. Let Us Rank Journalism Programs

    ERIC Educational Resources Information Center

    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…

  14. RELATIVE POTENCY RANKING FOR CHLOROPHENOLS

    EPA Science Inventory

    Recently the National Center for Environmental Assessment-Cincinnati completed a feasibility study for developing a toxicity related relative potency ranking scheme for chlorophenols. In this study it was concluded that a large data base exists pertaining to the relative toxicity...

  15. Graph ranking for exploratory gene data analysis

    PubMed Central

    2009-01-01

    Background Microarray technology has made it possible to simultaneously monitor the expression levels of thousands of genes in a single experiment. However, the large number of genes greatly increases the challenges of analyzing, comprehending and interpreting the resulting mass of data. Selecting a subset of important genes is inevitable to address the challenge. Gene selection has been investigated extensively over the last decade. Most selection procedures, however, are not sufficient for accurate inference of underlying biology, because biological significance does not necessarily have to be statistically significant. Additional biological knowledge needs to be integrated into the gene selection procedure. Results We propose a general framework for gene ranking. We construct a bipartite graph from the Gene Ontology (GO) and gene expression data. The graph describes the relationship between genes and their associated molecular functions. Under a species condition, edge weights of the graph are assigned to be gene expression level. Such a graph provides a mathematical means to represent both species-independent and species-dependent biological information. We also develop a new ranking algorithm to analyze the weighted graph via a kernelized spatial depth (KSD) approach. Consequently, the importance of gene and molecular function can be simultaneously ranked by a real-valued measure, KSD, which incorporates the global and local structure of the graph. Over-expressed and under-regulated genes also can be separately ranked. Conclusion The gene-function bigraph integrates molecular function annotations into gene expression data. The relevance of genes is described in the graph (through a common function). The proposed method provides an exploratory framework for gene data analysis. PMID:19811684

  16. Simple approach for ranking structure determining residues

    PubMed Central

    Luna-Martínez, Oscar D.; Vidal-Limón, Abraham; Villalba-Velázquez, Miryam I.; Sánchez-Alcalá, Rosalba; Garduño-Juárez, Ramón; Uversky, Vladimir N.

    2016-01-01

    Mutating residues has been a common task in order to study structural properties of the protein of interest. Here, we propose and validate a simple method that allows the identification of structural determinants; i.e., residues essential for preservation of the stability of global structure, regardless of the protein topology. This method evaluates all of the residues in a 3D structure of a given globular protein by ranking them according to their connectivity and movement restrictions without topology constraints. Our results matched up with sequence-based predictors that look up for intrinsically disordered segments, suggesting that protein disorder can also be described with the proposed methodology. PMID:27366642

  17. Simple approach for ranking structure determining residues.

    PubMed

    Luna-Martínez, Oscar D; Vidal-Limón, Abraham; Villalba-Velázquez, Miryam I; Sánchez-Alcalá, Rosalba; Garduño-Juárez, Ramón; Uversky, Vladimir N; Becerril, Baltazar

    2016-01-01

    Mutating residues has been a common task in order to study structural properties of the protein of interest. Here, we propose and validate a simple method that allows the identification of structural determinants; i.e., residues essential for preservation of the stability of global structure, regardless of the protein topology. This method evaluates all of the residues in a 3D structure of a given globular protein by ranking them according to their connectivity and movement restrictions without topology constraints. Our results matched up with sequence-based predictors that look up for intrinsically disordered segments, suggesting that protein disorder can also be described with the proposed methodology. PMID:27366642

  18. Community exposures to airborne agricultural pesticides in California: ranking of inhalation risks.

    PubMed

    Lee, Sharon; McLaughlin, Robert; Harnly, Martha; Gunier, Robert; Kreutzer, Richard

    2002-12-01

    We assessed inhalation risks to California communities from airborne agricultural pesticides by probability distribution analysis using ambient air data provided by the California Air Resources Board and the California Department of Pesticide Regulation. The pesticides evaluated include chloropicrin, chlorothalonil, chlorpyrifos, S,S,S-tributyl phosphorotrithioate, diazinon, 1,3-dichloropropene, dichlorvos (naled breakdown product), endosulfan, eptam, methidathion, methyl bromide, methyl isothiocyanate (MITC; metam sodium breakdown product), molinate, propargite, and simazine. Risks were estimated for the median and 75th and 95th percentiles of probability (50, 25, and 5% of the exposed populations). Exposure estimates greater than or equal to noncancer reference values occurred for 50% of the exposed populations (adults and children) for MITC subchronic and chronic exposures, methyl bromide subchronic exposures (year 2000 monitoring), and 1,3-dichloropropene subchronic exposures (1990 monitoring). Short-term chlorpyrifos exposure estimates exceeded the acute reference value for 50% of children (not adults) in the exposed population. Noncancer risks were uniformly higher for children due to a proportionately greater inhalation rate-to-body weight ratio compared to adults and other factors. Target health effects of potential concern for these exposures include neurologic effects (methyl bromide and chlorpyrifos) and respiratory effects (1,3-dichloropropene and MITC). The lowest noncancer risks occurred for simazine and chlorothalonil. Lifetime cancer risks of one-in-a-million or greater were estimated for 50% of the exposed population for 1,3-dichloropropene (1990 monitoring) and 25% of the exposed populations for methidathion and molinate. Pesticide vapor pressure was found to be a better predictor of inhalation risk compared to other methods of ranking pesticides as potential toxic air contaminants. PMID:12460795

  19. Community exposures to airborne agricultural pesticides in California: ranking of inhalation risks.

    PubMed Central

    Lee, Sharon; McLaughlin, Robert; Harnly, Martha; Gunier, Robert; Kreutzer, Richard

    2002-01-01

    We assessed inhalation risks to California communities from airborne agricultural pesticides by probability distribution analysis using ambient air data provided by the California Air Resources Board and the California Department of Pesticide Regulation. The pesticides evaluated include chloropicrin, chlorothalonil, chlorpyrifos, S,S,S-tributyl phosphorotrithioate, diazinon, 1,3-dichloropropene, dichlorvos (naled breakdown product), endosulfan, eptam, methidathion, methyl bromide, methyl isothiocyanate (MITC; metam sodium breakdown product), molinate, propargite, and simazine. Risks were estimated for the median and 75th and 95th percentiles of probability (50, 25, and 5% of the exposed populations). Exposure estimates greater than or equal to noncancer reference values occurred for 50% of the exposed populations (adults and children) for MITC subchronic and chronic exposures, methyl bromide subchronic exposures (year 2000 monitoring), and 1,3-dichloropropene subchronic exposures (1990 monitoring). Short-term chlorpyrifos exposure estimates exceeded the acute reference value for 50% of children (not adults) in the exposed population. Noncancer risks were uniformly higher for children due to a proportionately greater inhalation rate-to-body weight ratio compared to adults and other factors. Target health effects of potential concern for these exposures include neurologic effects (methyl bromide and chlorpyrifos) and respiratory effects (1,3-dichloropropene and MITC). The lowest noncancer risks occurred for simazine and chlorothalonil. Lifetime cancer risks of one-in-a-million or greater were estimated for 50% of the exposed population for 1,3-dichloropropene (1990 monitoring) and 25% of the exposed populations for methidathion and molinate. Pesticide vapor pressure was found to be a better predictor of inhalation risk compared to other methods of ranking pesticides as potential toxic air contaminants. PMID:12460795

  20. Inconsistent year-to-year fluctuations limit the conclusiveness of global higher education rankings for university management.

    PubMed

    Sorz, Johannes; Wallner, Bernard; Seidler, Horst; Fieder, Martin

    2015-01-01

    Backround. University rankings are getting very high international media attention, this holds particularly true for the Times Higher Education Ranking (THE) and the Shanghai Jiao Tong University's Academic Ranking of World Universities Ranking (ARWU). We therefore aimed to investigate how reliable the rankings are, especially for universities with lower ranking positions, that often show inconclusive year-to-year fluctuations in their rank, and if these rankings are thus a suitable basis for management purposes. Methods. We used the public available data from the web pages of the THE and the ARWU ranking to analyze the dynamics of change in score and ranking position from year to year, and we investigated possible causes for inconsistent fluctuations in the rankings by the means of regression analyses. Results. Regression analyses of results from the THE and ARWU from 2010-2014 show inconsistent fluctuations in the rank and score for universities with lower rank positions (below position 50) which lead to inconsistent "up and downs" in the total results, especially in the THE and to a lesser extent also in the ARWU. In both rankings, the mean year-to-year fluctuation of universities in groups of 50 universities aggregated by descending rank increases from less than 10% in the group of the 50 highest ranked universities to up to 60% in the group of the lowest ranked universities. Furthermore, year-to-year results do not correspond in THES- and ARWU-Rankings for universities below rank 50. Discussion. We conclude that the observed fluctuations in the THE do not correspond to actual university performance and ranking results are thus of limited conclusiveness for the university management of universities below a rank of 50. While the ARWU rankings seems more robust against inconsistent fluctuations, its year to year changes in the scores are very small, so essential changes from year to year could not be expected. Furthermore, year-to-year results do not correspond

  1. Inconsistent year-to-year fluctuations limit the conclusiveness of global higher education rankings for university management

    PubMed Central

    Sorz, Johannes; Wallner, Bernard; Seidler, Horst

    2015-01-01

    Backround. University rankings are getting very high international media attention, this holds particularly true for the Times Higher Education Ranking (THE) and the Shanghai Jiao Tong University’s Academic Ranking of World Universities Ranking (ARWU). We therefore aimed to investigate how reliable the rankings are, especially for universities with lower ranking positions, that often show inconclusive year-to-year fluctuations in their rank, and if these rankings are thus a suitable basis for management purposes. Methods. We used the public available data from the web pages of the THE and the ARWU ranking to analyze the dynamics of change in score and ranking position from year to year, and we investigated possible causes for inconsistent fluctuations in the rankings by the means of regression analyses. Results. Regression analyses of results from the THE and ARWU from 2010–2014 show inconsistent fluctuations in the rank and score for universities with lower rank positions (below position 50) which lead to inconsistent “up and downs” in the total results, especially in the THE and to a lesser extent also in the ARWU. In both rankings, the mean year-to-year fluctuation of universities in groups of 50 universities aggregated by descending rank increases from less than 10% in the group of the 50 highest ranked universities to up to 60% in the group of the lowest ranked universities. Furthermore, year-to-year results do not correspond in THES- and ARWU-Rankings for universities below rank 50. Discussion. We conclude that the observed fluctuations in the THE do not correspond to actual university performance and ranking results are thus of limited conclusiveness for the university management of universities below a rank of 50. While the ARWU rankings seems more robust against inconsistent fluctuations, its year to year changes in the scores are very small, so essential changes from year to year could not be expected. Furthermore, year-to-year results do not

  2. Bayesian CP Factorization of Incomplete Tensors with Automatic Rank Determination.

    PubMed

    Zhao, Qibin; Zhang, Liqing; Cichocki, Andrzej

    2015-09-01

    CANDECOMP/PARAFAC (CP) tensor factorization of incomplete data is a powerful technique for tensor completion through explicitly capturing the multilinear latent factors. The existing CP algorithms require the tensor rank to be manually specified, however, the determination of tensor rank remains a challenging problem especially for CP rank . In addition, existing approaches do not take into account uncertainty information of latent factors, as well as missing entries. To address these issues, we formulate CP factorization using a hierarchical probabilistic model and employ a fully Bayesian treatment by incorporating a sparsity-inducing prior over multiple latent factors and the appropriate hyperpriors over all hyperparameters, resulting in automatic rank determination. To learn the model, we develop an efficient deterministic Bayesian inference algorithm, which scales linearly with data size. Our method is characterized as a tuning parameter-free approach, which can effectively infer underlying multilinear factors with a low-rank constraint, while also providing predictive distributions over missing entries. Extensive simulations on synthetic data illustrate the intrinsic capability of our method to recover the ground-truth of CP rank and prevent the overfitting problem, even when a large amount of entries are missing. Moreover, the results from real-world applications, including image inpainting and facial image synthesis, demonstrate that our method outperforms state-of-the-art approaches for both tensor factorization and tensor completion in terms of predictive performance. PMID:26353124

  3. Upgrading method of low-rank coal

    SciTech Connect

    Yokoyama, H.; Kuge, T.; Nakamura, Y.; Nogita, Sh.

    1984-07-24

    A coal is finely pulverized. The finely pulverized coal is subjected to dry distillation. A tar obtained by the dry distillation is added to an aqueous slurry together with the dry-distilled coal to effect the submerged granulation.

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

    PubMed Central

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

    2014-01-01

    Feature rankings are often used for supervised dimension reduction especially when discriminating power of each feature is of interest, dimensionality of dataset is extremely high, or computational power is limited to perform more complicated methods. In practice, it is recommended to start dimension reduction via simple methods such as feature rankings before applying more complex approaches. Single Variable Classifier (SVC) ranking is a feature ranking based on the predictive performance of a classifier built using only a single feature. While benefiting from capabilities of classifiers, this ranking method is not as computationally intensive as wrappers. In this paper, we report the results of an extensive study on the bias and stability of such feature ranking method. We study whether the classifiers influence the SVC rankings or the discriminative power of features themselves has a dominant impact on the final rankings. We show the common intuition of using the same classifier for feature ranking and final classification does not always result in the best prediction performance. We then study if heterogeneous classifiers ensemble approaches provide more unbiased rankings and if they improve final classification performance. Furthermore, we calculate an empirical prediction performance loss for using the same classifier in SVC feature ranking and final classification from the optimal choices. PMID:25177107

  5. Factors affecting quality of dried low-rank coals

    SciTech Connect

    Karthikeyan, M.; Kuma, J.V.M.; Hoe, C.S.; Ngo, D.L.Y.

    2007-07-01

    The chemical and physical properties of coal are strongly affected by the upgrading process employed. For high-moisture coals, upgrading involves thermal dehydration to improve the calorific value of the coal on mass basis. This study evaluates the feasibility of upgrading a low-rank/grade coal using the oven drying method. The objective of this research work is to study the drying characteristics of low-rank coals and to understand the factors affecting the quality of dried low-rank coals. This article describes laboratory experiments conducted on the characterization of the low-rank coals before and after the drying process. The results on drying kinetics, re-absorption of coal samples, and proximate analysis of coal samples before and after drying are discussed. It was found that the upgrading process produced coal with better heating value and combustion characteristics than those of the raw coal samples.

  6. Ranking online quality and reputation via the user activity

    NASA Astrophysics Data System (ADS)

    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.

  7. Seasonal to decadal forcing of high water level percentiles in the German Bight throughout the last century

    NASA Astrophysics Data System (ADS)

    Dangendorf, Sönke; Mudersbach, Christoph; Jensen, Jürgen; Anette, Ganske; Heinrich, Hartmut

    2013-05-01

    For the purpose of coastal planning and management, especially under changing climatic conditions, enhanced knowledge about the evolution of extreme sea levels in the past, present, and future is required. This paper presents statistical analyses of high seasonal water level percentiles of 13 tide gauges in the German Bight, spanning over a period of up to 109 years throughout the twentieth and twenty-first centuries. Seasonal and annual high percentile time series of water levels were investigated in comparison to the mean sea level (MSL) for changes on seasonal, inter-annual, and decadal timescales. While throughout the first half of the twentieth century extreme water levels generally followed changes in MSL, during the second half of the century, linear extreme sea level trends exceeded those in MSL in the order of 9-64 cm per century. The largest, although insignificant, contribution to the magnitude of these trends occurs in the winter season (January to March), while smaller but, due to the generally lower atmospheric variability, significant changes are observed during spring (April to June). The observed multi-decadal trends are generally in good agreement with multi-decadal trends in the corresponding percentiles of local zonal surface winds. Only small parts of the trends remain unexplained. It is suggested that these remaining trends result from modifications in the local tidal regime. For the aspects of coastal planning, the findings clarify that in the German Bight, in addition to changes in MSL, potential changes in storminess and in the tidal regime significantly contribute to the development of extreme water levels. Since these factors have influenced the characteristic of extremes throughout the recent past, they also have to be taken into account when estimating design water levels for, e.g., dikes (in a warming climate) under changing greenhouse gas emissions.

  8. Twisted Yangians of small rank

    NASA Astrophysics Data System (ADS)

    Guay, Nicolas; Regelskis, Vidas; Wendlandt, Curtis

    2016-04-01

    We study quantized enveloping algebras called twisted Yangians associated with the symmetric pairs of types CI, BDI, and DIII (in Cartan's classification) when the rank is small. We establish isomorphisms between these twisted Yangians and the well known Olshanskii's twisted Yangians of types AI and AII, and also with the Molev-Ragoucy reflection algebras associated with symmetric pairs of type AIII. We also construct isomorphisms with twisted Yangians in Drinfeld's original presentation.

  9. Procedure for determining the distribution ranking index

    SciTech Connect

    Latino, M.A.

    1996-12-31

    The Distribution Ranking Index (DRI) has been developed as a simple but effective means to indicate the inherent, acute hazards of a material that might be released in a transportation accident. Utilizing existing Dow resources and procedures, it is one of the methods used for prioritization of chemicals in Dow`s distribution related process risk management effort. Seven individual hazard indexes are considered for a material. The values range from 1 to 4 with 4 representing the most severe hazard. The highest value from any hazard index determines the overall DRI. 3 refs., 1 fig., 8 tabs.

  10. Anaerobic bioprocessing of low rank coals

    SciTech Connect

    Jain, M.K.; Narayan, R.; Han, O.

    1991-01-01

    The overall goal of this project is to find biological methods to remove carboxylic functionalities from low rank coals under ambient conditions and to assess the properties of these modified coals towards coal liquefaction. The main objectives for this quarter were: (1) enrichment of anaerobic microbial consortia in a coal fed chemostat, (2) characterization of biocoal products and examination of liquefaction potential, (3) isolation of decarboxylating organisms and evaluation of the isolated organisms for decarboxylation. The project began on September 12, 1990. 3 figs., 7 tabs.

  11. Krylov subspace algorithms for computing GeneRank for the analysis of microarray data mining.

    PubMed

    Wu, Gang; Zhang, Ying; Wei, Yimin

    2010-04-01

    GeneRank is a new engine technology for the analysis of microarray experiments. It combines gene expression information with a network structure derived from gene notations or expression profile correlations. Using matrix decomposition techniques, we first give a matrix analysis of the GeneRank model. We reformulate the GeneRank vector as a linear combination of three parts in the general case when the matrix in question is non-diagonalizable. We then propose two Krylov subspace methods for computing GeneRank. Numerical experiments show that, when the GeneRank problem is very large, the new algorithms are appropriate choices. PMID:20426695

  12. Robust Generalized Low Rank Approximations of Matrices

    PubMed Central

    Shi, Jiarong; Yang, Wei; Zheng, Xiuyun

    2015-01-01

    In recent years, the intrinsic low rank structure of some datasets has been extensively exploited to reduce dimensionality, remove noise and complete the missing entries. As a well-known technique for dimensionality reduction and data compression, Generalized Low Rank Approximations of Matrices (GLRAM) claims its superiority on computation time and compression ratio over the SVD. However, GLRAM is very sensitive to sparse large noise or outliers and its robust version does not have been explored or solved yet. To address this problem, this paper proposes a robust method for GLRAM, named Robust GLRAM (RGLRAM). We first formulate RGLRAM as an l1-norm optimization problem which minimizes the l1-norm of the approximation errors. Secondly, we apply the technique of Augmented Lagrange Multipliers (ALM) to solve this l1-norm minimization problem and derive a corresponding iterative scheme. Then the weak convergence of the proposed algorithm is discussed under mild conditions. Next, we investigate a special case of RGLRAM and extend RGLRAM to a general tensor case. Finally, the extensive experiments on synthetic data show that it is possible for RGLRAM to exactly recover both the low rank and the sparse components while it may be difficult for previous state-of-the-art algorithms. We also discuss three issues on RGLRAM: the sensitivity to initialization, the generalization ability and the relationship between the running time and the size/number of matrices. Moreover, the experimental results on images of faces with large corruptions illustrate that RGLRAM obtains the best denoising and compression performance than other methods. PMID:26367116

  13. Caipirini: using gene sets to rank literature

    PubMed Central

    2012-01-01

    Background Keeping up-to-date with bioscience literature is becoming increasingly challenging. Several recent methods help meet this challenge by allowing literature search to be launched based on lists of abstracts that the user judges to be 'interesting'. Some methods go further by allowing the user to provide a second input set of 'uninteresting' abstracts; these two input sets are then used to search and rank literature by relevance. In this work we present the service 'Caipirini' (http://caipirini.org) that also allows two input sets, but takes the novel approach of allowing ranking of literature based on one or more sets of genes. Results To evaluate the usefulness of Caipirini, we used two test cases, one related to the human cell cycle, and a second related to disease defense mechanisms in Arabidopsis thaliana. In both cases, the new method achieved high precision in finding literature related to the biological mechanisms underlying the input data sets. Conclusions To our knowledge Caipirini is the first service enabling literature search directly based on biological relevance to gene sets; thus, Caipirini gives the research community a new way to unlock hidden knowledge from gene sets derived via high-throughput experiments. PMID:22297131

  14. Ranking Reputation and Quality in Online Rating Systems

    PubMed Central

    Liao, Hao; Zeng, An; Xiao, Rui; Ren, Zhuo-Ming; Chen, Duan-Bing; Zhang, Yi-Cheng

    2014-01-01

    How to design an accurate and robust ranking algorithm is a fundamental problem with wide applications in many real systems. It is especially significant in online rating systems due to the existence of some spammers. In the literature, many well-performed iterative ranking methods have been proposed. These methods can effectively recognize the unreliable users and reduce their weight in judging the quality of objects, and finally lead to a more accurate evaluation of the online products. In this paper, we design an iterative ranking method with high performance in both accuracy and robustness. More specifically, a reputation redistribution process is introduced to enhance the influence of highly reputed users and two penalty factors enable the algorithm resistance to malicious behaviors. Validation of our method is performed in both artificial and real user-object bipartite networks. PMID:24819119

  15. Ranking reputation and quality in online rating systems.

    PubMed

    Liao, Hao; Zeng, An; Xiao, Rui; Ren, Zhuo-Ming; Chen, Duan-Bing; Zhang, Yi-Cheng

    2014-01-01

    How to design an accurate and robust ranking algorithm is a fundamental problem with wide applications in many real systems. It is especially significant in online rating systems due to the existence of some spammers. In the literature, many well-performed iterative ranking methods have been proposed. These methods can effectively recognize the unreliable users and reduce their weight in judging the quality of objects, and finally lead to a more accurate evaluation of the online products. In this paper, we design an iterative ranking method with high performance in both accuracy and robustness. More specifically, a reputation redistribution process is introduced to enhance the influence of highly reputed users and two penalty factors enable the algorithm resistance to malicious behaviors. Validation of our method is performed in both artificial and real user-object bipartite networks. PMID:24819119

  16. Class Rank Weighs Down True Learning

    ERIC Educational Resources Information Center

    Guskey, Thomas R.

    2014-01-01

    The process of determining class rank does not help students achieve more or reach higher levels of proficiency. Evidence indicates ranking students may diminish students' motivation. High school educators argue that they are compelled to rank-order graduating students because selective colleges and universities require information about…

  17. 14 CFR 1214.1105 - Final ranking.

    Code of Federal Regulations, 2013 CFR

    2013-01-01

    ... 14 Aeronautics and Space 5 2013-01-01 2013-01-01 false Final ranking. 1214.1105 Section 1214.1105 Aeronautics and Space NATIONAL AERONAUTICS AND SPACE ADMINISTRATION SPACE FLIGHT NASA Astronaut Candidate Recruitment and Selection Program § 1214.1105 Final ranking. Final rankings will be based on a combination...

  18. 14 CFR 1214.1105 - Final ranking.

    Code of Federal Regulations, 2011 CFR

    2011-01-01

    ... 14 Aeronautics and Space 5 2011-01-01 2010-01-01 true Final ranking. 1214.1105 Section 1214.1105 Aeronautics and Space NATIONAL AERONAUTICS AND SPACE ADMINISTRATION SPACE FLIGHT NASA Astronaut Candidate Recruitment and Selection Program § 1214.1105 Final ranking. Final rankings will be based on a combination...

  19. 14 CFR 1214.1105 - Final ranking.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... 14 Aeronautics and Space 5 2010-01-01 2010-01-01 false Final ranking. 1214.1105 Section 1214.1105 Aeronautics and Space NATIONAL AERONAUTICS AND SPACE ADMINISTRATION SPACE FLIGHT NASA Astronaut Candidate Recruitment and Selection Program § 1214.1105 Final ranking. Final rankings will be based on a combination...

  20. 14 CFR 1214.1105 - Final ranking.

    Code of Federal Regulations, 2012 CFR

    2012-01-01

    ... 14 Aeronautics and Space 5 2012-01-01 2012-01-01 false Final ranking. 1214.1105 Section 1214.1105 Aeronautics and Space NATIONAL AERONAUTICS AND SPACE ADMINISTRATION SPACE FLIGHT NASA Astronaut Candidate Recruitment and Selection Program § 1214.1105 Final ranking. Final rankings will be based on a combination...

  1. A Comprehensive Analysis of Marketing Journal Rankings

    ERIC Educational Resources Information Center

    Steward, Michelle D.; Lewis, Bruce R.

    2010-01-01

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

  2. The Academic Ranking of World Universities

    ERIC Educational Resources Information Center

    Liu, Nian Cai; Cheng, Ying

    2005-01-01

    Shanghai Jiao Tong University has published on the Internet an Academic Ranking of World Universities that has attracted worldwide attention. Institutions are ranked according to academic or research performance and ranking indicators include major international awards, highly cited researchers in important fields, articles published in selected…

  3. The Privilege of Ranking: Google Plays Ball.

    ERIC Educational Resources Information Center

    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;…

  4. LogDet Rank Minimization with Application to Subspace Clustering.

    PubMed

    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. PMID:26229527

  5. An iterative searching and ranking algorithm for prioritising pharmacogenomics genes.

    PubMed

    Xu, Rong; Wang, Quanqiu

    2013-01-01

    Pharmacogenomics (PGx) studies are to identify genetic variants that may affect drug efficacy and toxicity. A machine understandable drug-gene relationship knowledge is important for many computational PGx studies and for personalised medicine. A comprehensive and accurate PGx-specific gene lexicon is important for automatic drug-gene relationship extraction from the scientific literature, rich knowledge source for PGx studies. In this study, we present a bootstrapping learning technique to rank 33,310 human genes with respect to their relevance to drug response. The algorithm uses only one seed PGx gene to iteratively extract and rank co-occurred genes using 20 million MEDLINE abstracts. Our ranking method is able to accurately rank PGx-specific genes highly among all human genes. Compared to randomly ranked genes (precision: 0.032, recall: 0.013, F1: 0.018), the algorithm has achieved significantly better performance (precision: 0.861, recall: 0.548, F1: 0.662) in ranking the top 2.5% of genes. PMID:23428471

  6. Learning to rank image tags with limited training examples.

    PubMed

    Songhe Feng; Zheyun Feng; Rong Jin

    2015-04-01

    With an increasing number of images that are available in social media, image annotation has emerged as an important research topic due to its application in image matching and retrieval. Most studies cast image annotation into a multilabel classification problem. The main shortcoming of this approach is that it requires a large number of training images with clean and complete annotations in order to learn a reliable model for tag prediction. We address this limitation by developing a novel approach that combines the strength of tag ranking with the power of matrix recovery. Instead of having to make a binary decision for each tag, our approach ranks tags in the descending order of their relevance to the given image, significantly simplifying the problem. In addition, the proposed method aggregates the prediction models for different tags into a matrix, and casts tag ranking into a matrix recovery problem. It introduces the matrix trace norm to explicitly control the model complexity, so that a reliable prediction model can be learned for tag ranking even when the tag space is large and the number of training images is limited. Experiments on multiple well-known image data sets demonstrate the effectiveness of the proposed framework for tag ranking compared with the state-of-the-art approaches for image annotation and tag ranking. PMID:25622318

  7. Query Specific Rank Fusion for Image Retrieval.

    PubMed

    Zhang, Shaoting; Yang, Ming; Cour, Timothee; Yu, Kai; Metaxas, Dimitris N

    2015-04-01

    Recently two lines of image retrieval algorithms demonstrate excellent scalability: 1) local features indexed by a vocabulary tree, and 2) holistic features indexed by compact hashing codes. Although both of them are able to search visually similar images effectively, their retrieval precision may vary dramatically among queries. Therefore, combining these two types of methods is expected to further enhance the retrieval precision. However, the feature characteristics and the algorithmic procedures of these methods are dramatically different, which is very challenging for the feature-level fusion. This motivates us to investigate how to fuse the ordered retrieval sets, i.e., the ranks of images, given by multiple retrieval methods, to boost the retrieval precision without sacrificing their scalability. In this paper, we model retrieval ranks as graphs of candidate images and propose a graph-based query specific fusion approach, where multiple graphs are merged and reranked by conducting a link analysis on a fused graph. The retrieval quality of an individual method is measured on-the-fly by assessing the consistency of the top candidates' nearest neighborhoods. Hence, it is capable of adaptively integrating the strengths of the retrieval methods using local or holistic features for different query images. This proposed method does not need any supervision, has few parameters, and is easy to implement. Extensive and thorough experiments have been conducted on four public datasets, i.e., the UKbench, Corel-5K, Holidays and the large-scale San Francisco Landmarks datasets. Our proposed method has achieved very competitive performance, including state-of-the-art results on several data sets, e.g., the N-S score 3.83 for UKbench. PMID:26353295

  8. Rank-Driven Markov Processes

    NASA Astrophysics Data System (ADS)

    Grinfeld, Michael; Knight, Philip A.; Wade, Andrew R.

    2012-01-01

    We study a class of Markovian systems of N elements taking values in [0,1] that evolve in discrete time t via randomized replacement rules based on the ranks of the elements. These rank-driven processes are inspired by variants of the Bak-Sneppen model of evolution, in which the system represents an evolutionary `fitness landscape' and which is famous as a simple model displaying self-organized criticality. Our main results are concerned with long-time large- N asymptotics for the general model in which, at each time step, K randomly chosen elements are discarded and replaced by independent U[0,1] variables, where the ranks of the elements to be replaced are chosen, independently at each time step, according to a distribution κ N on {1,2,…, N} K . Our main results are that, under appropriate conditions on κ N , the system exhibits threshold behavior at s ∗∈[0,1], where s ∗ is a function of κ N , and the marginal distribution of a randomly selected element converges to U[ s ∗,1] as t→∞ and N→∞. Of this class of models, results in the literature have previously been given for special cases only, namely the `mean-field' or `random neighbor' Bak-Sneppen model. Our proofs avoid the heuristic arguments of some of the previous work and use Foster-Lyapunov ideas. Our results extend existing results and establish their natural, more general context. We derive some more specialized results for the particular case where K=2. One of our technical tools is a result on convergence of stationary distributions for families of uniformly ergodic Markov chains on increasing state-spaces, which may be of independent interest.

  9. Two-dimensional ranking of Wikipedia articles

    NASA Astrophysics Data System (ADS)

    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.

  10. Tool for Ranking Research Options

    NASA Technical Reports Server (NTRS)

    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.

  11. The Role of Student Growth Percentiles in Monitoring Learning and Predicting Learning Outcomes

    ERIC Educational Resources Information Center

    Seo, Daeryong; McGrane, Joshua; Taherbhai, Husein

    2015-01-01

    Most formative assessments rely on the performance status of a student at a particular time point. However, such a method does not provide any information on the "propensity" of the student to achieve a predetermined target score or whether the student is performing as per the expectations from identical students with the same history of…

  12. Rank order scaling of pictorial depth

    PubMed Central

    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. PMID:23145256

  13. Ranking Biomedical Annotations with Annotator's Semantic Relevancy

    PubMed Central

    2014-01-01

    Biomedical annotation is a common and affective artifact for researchers to discuss, show opinion, and share discoveries. It becomes increasing popular in many online research communities, and implies much useful information. Ranking biomedical annotations is a critical problem for data user to efficiently get information. As the annotator's knowledge about the annotated entity normally determines quality of the annotations, we evaluate the knowledge, that is, semantic relationship between them, in two ways. The first is extracting relational information from credible websites by mining association rules between an annotator and a biomedical entity. The second way is frequent pattern mining from historical annotations, which reveals common features of biomedical entities that an annotator can annotate with high quality. We propose a weighted and concept-extended RDF model to represent an annotator, a biomedical entity, and their background attributes and merge information from the two ways as the context of an annotator. Based on that, we present a method to rank the annotations by evaluating their correctness according to user's vote and the semantic relevancy between the annotator and the annotated entity. The experimental results show that the approach is applicable and efficient even when data set is large. PMID:24899918

  14. Ranking biomedical annotations with annotator's semantic relevancy.

    PubMed

    Wu, Aihua

    2014-01-01

    Biomedical annotation is a common and affective artifact for researchers to discuss, show opinion, and share discoveries. It becomes increasing popular in many online research communities, and implies much useful information. Ranking biomedical annotations is a critical problem for data user to efficiently get information. As the annotator's knowledge about the annotated entity normally determines quality of the annotations, we evaluate the knowledge, that is, semantic relationship between them, in two ways. The first is extracting relational information from credible websites by mining association rules between an annotator and a biomedical entity. The second way is frequent pattern mining from historical annotations, which reveals common features of biomedical entities that an annotator can annotate with high quality. We propose a weighted and concept-extended RDF model to represent an annotator, a biomedical entity, and their background attributes and merge information from the two ways as the context of an annotator. Based on that, we present a method to rank the annotations by evaluating their correctness according to user's vote and the semantic relevancy between the annotator and the annotated entity. The experimental results show that the approach is applicable and efficient even when data set is large. PMID:24899918

  15. Knowledge-guided gene ranking by coordinative component analysis

    PubMed Central

    2010-01-01

    Background In cancer, gene networks and pathways often exhibit dynamic behavior, particularly during the process of carcinogenesis. Thus, it is important to prioritize those genes that are strongly associated with the functionality of a network. Traditional statistical methods are often inept to identify biologically relevant member genes, motivating researchers to incorporate biological knowledge into gene ranking methods. However, current integration strategies are often heuristic and fail to incorporate fully the true interplay between biological knowledge and gene expression data. Results To improve knowledge-guided gene ranking, we propose a novel method called coordinative component analysis (COCA) in this paper. COCA explicitly captures those genes within a specific biological context that are likely to be expressed in a coordinative manner. Formulated as an optimization problem to maximize the coordinative effort, COCA is designed to first extract the coordinative components based on a partial guidance from knowledge genes and then rank the genes according to their participation strengths. An embedded bootstrapping procedure is implemented to improve statistical robustness of the solutions. COCA was initially tested on simulation data and then on published gene expression microarray data to demonstrate its improved performance as compared to traditional statistical methods. Finally, the COCA approach has been applied to stem cell data to identify biologically relevant genes in signaling pathways. As a result, the COCA approach uncovers novel pathway members that may shed light into the pathway deregulation in cancers. Conclusion We have developed a new integrative strategy to combine biological knowledge and microarray data for gene ranking. The method utilizes knowledge genes for a guidance to first extract coordinative components, and then rank the genes according to their contribution related to a network or pathway. The experimental results show that

  16. Standing adult human phantoms based on 10th, 50th and 90th mass and height percentiles of male and female Caucasian populations

    NASA Astrophysics Data System (ADS)

    Cassola, V. F.; Milian, F. M.; Kramer, R.; de Oliveira Lira, C. A. B.; Khoury, H. J.

    2011-07-01

    Computational anthropomorphic human phantoms are useful tools developed for the calculation of absorbed or equivalent dose to radiosensitive organs and tissues of the human body. The problem is, however, that, strictly speaking, the results can be applied only to a person who has the same anatomy as the phantom, while for a person with different body mass and/or standing height the data could be wrong. In order to improve this situation for many areas in radiological protection, this study developed 18 anthropometric standing adult human phantoms, nine models per gender, as a function of the 10th, 50th and 90th mass and height percentiles of Caucasian populations. The anthropometric target parameters for body mass, standing height and other body measures were extracted from PeopleSize, a well-known software package used in the area of ergonomics. The phantoms were developed based on the assumption of a constant body-mass index for a given mass percentile and for different heights. For a given height, increase or decrease of body mass was considered to reflect mainly the change of subcutaneous adipose tissue mass, i.e. that organ masses were not changed. Organ mass scaling as a function of height was based on information extracted from autopsy data. The methods used here were compared with those used in other studies, anatomically as well as dosimetrically. For external exposure, the results show that equivalent dose decreases with increasing body mass for organs and tissues located below the subcutaneous adipose tissue layer, such as liver, colon, stomach, etc, while for organs located at the surface, such as breasts, testes and skin, the equivalent dose increases or remains constant with increasing body mass due to weak attenuation and more scatter radiation caused by the increasing adipose tissue mass. Changes of standing height have little influence on the equivalent dose to organs and tissues from external exposure. Specific absorbed fractions (SAFs) have also

  17. Relations Among Some Low-Rank Subspace Recovery Models.

    PubMed

    Zhang, Hongyang; Lin, Zhouchen; Zhang, Chao; Gao, Junbin

    2015-09-01

    Recovering intrinsic low-dimensional subspaces from data distributed on them is a key preprocessing step to many applications. In recent years, a lot of work has modeled subspace recovery as low-rank minimization problems. We find that some representative models, such as robust principal component analysis (R-PCA), robust low-rank representation (R-LRR), and robust latent low-rank representation (R-LatLRR), are actually deeply connected. More specifically, we discover that once a solution to one of the models is obtained, we can obtain the solutions to other models in closed-form formulations. Since R-PCA is the simplest, our discovery makes it the center of low-rank subspace recovery models. Our work has two important implications. First, R-PCA has a solid theoretical foundation. Under certain conditions, we could find globally optimal solutions to these low-rank models at an overwhelming probability, although these models are nonconvex. Second, we can obtain significantly faster algorithms for these models by solving R-PCA first. The computation cost can be further cut by applying low-complexity randomized algorithms, for example, our novel l2,1 filtering algorithm, to R-PCA. Although for the moment the formal proof of our l2,1 filtering algorithm is not yet available, experiments verify the advantages of our algorithm over other state-of-the-art methods based on the alternating direction method. PMID:26161818

  18. Sparse Contextual Activation for Efficient Visual Re-Ranking.

    PubMed

    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. PMID:26742133

  19. On the computation of the rank of block bidiagonal Toeplitz matrices

    NASA Astrophysics Data System (ADS)

    Triantafyllou, Dimitrios; Mitrouli, Marilena

    2009-05-01

    In the present paper we study the computation of the rank of a block bidiagonal Toeplitz (BBT) sequence of matrices. We propose matrix-based, numerical and symbolical, updating and direct methods, computing the rank of BBT matrices and comparing them with classical procedures. The methods deploy the special form of the BBT sequence, significantly reducing the required flops and leading to fast and efficient algorithms. The numerical implementation of the algorithms computes the numerical rank in contrast with the symbolical implementation, which guarantees the computation of the exact rank of the matrix. The combination of numerical and symbolical operations suggests a new approach in software mathematical computations denoted as hybrid computations.

  20. Cross ranking of cities and regions: population versus income

    NASA Astrophysics Data System (ADS)

    Cerqueti, Roy; Ausloos, Marcel

    2015-07-01

    This paper explores the relationship between the inner economical structure of communities and their population distribution through a rank-rank analysis of official data, along statistical physics ideas within two techniques. The data is taken on Italian cities. The analysis is performed both at a global (national) and at a more local (regional) level in order to distinguish ‘macro’ and ‘micro’ aspects. First, the rank-size rule is found not to be a standard power law, as in many other studies, but a doubly decreasing power law. Next, the Kendall τ and the Spearman ρ rank correlation coefficients which measure pair concordance and the correlation between fluctuations in two rankings, respectively,—as a correlation function does in thermodynamics, are calculated for finding rank correlation (if any) between demography and wealth. Results show non only global disparities for the whole (country) set, but also (regional) disparities, when comparing the number of cities in regions, the number of inhabitants in cities and that in regions, as well as when comparing the aggregated tax income of the cities and that of regions. Different outliers are pointed out and justified. Interestingly, two classes of cities in the country and two classes of regions in the country are found. ‘Common sense’ social, political, and economic considerations sustain the findings. More importantly, the methods show that they allow to distinguish communities, very clearly, when specific criteria are numerically sound. A specific modeling for the findings is presented, i.e. for the doubly decreasing power law and the two phase system, based on statistics theory, e.g. urn filling. The model ideas can be expected to hold when similar rank relationship features are observed in fields. It is emphasized that the analysis makes more sense than one through a Pearson Π value-value correlation analysis

  1. Birth Weight Ratio as an Alternative to Birth Weight Percentile to Express Infant Weight in Research and Clinical Practice: A Nationwide Cohort Study

    PubMed Central

    Kazemier, Brenda M.; Schuit, Ewoud; Mol, Ben Willem J.; Pajkrt, Eva; Ganzevoort, Wessel

    2014-01-01

    Objective. To compare birth weight ratio and birth weight percentile to express infant weight when assessing pregnancy outcome. Study Design. We performed a national cohort study. Birth weight ratio was calculated as the observed birth weight divided by the median birth weight for gestational age. The discriminative ability of birth weight ratio and birth weight percentile to identify infants at risk of perinatal death (fetal death and neonatal death) or adverse pregnancy outcome (perinatal death + severe neonatal morbidity) was compared using the area under the curve. Outcomes were expressed stratified by gestational age at delivery separate for birth weight ratio and birth weight percentile. Results. We studied 1,299,244 pregnant women, with an overall perinatal death rate of 0.62%. Birth weight ratio and birth weight percentile have equivalent overall discriminative performance for perinatal death and adverse perinatal outcome. In late preterm infants (33+0–36+6 weeks), birth weight ratio has better discriminative ability than birth weight percentile for perinatal death (0.68 versus 0.63, P  0.01) or adverse pregnancy outcome (0.67 versus 0.60, P < 0.001). Conclusion. Birth weight ratio is a potentially valuable instrument to identify infants at risk of perinatal death and adverse pregnancy outcome and provides several advantages for use in research and clinical practice. Moreover, it allows comparison of groups with different average birth weights. PMID:25197283

  2. The Stability of Rankings Derived from Composite Indicators: Analysis of the "IL Sole 24 Ore" Quality of Life Report

    ERIC Educational Resources Information Center

    Lun, G.; Holzer, D.; Tappeiner, G.; Tappeiner, U.

    2006-01-01

    The calculation of composite indicators and the derivation of respective rankings is a common method used to benchmark countries or regions. However, although the statistical robustness of these rankings is often criticised, they often still spark off heated political debate. Here, we assess the sensitivity of the province ranking published by the…

  3. [How to rank if you must? Reflections on the book of Amy N. Langville and Carl D. Meyer].

    PubMed

    Schubert, András

    2015-08-01

    More than ever, our life is permeated by rankings. This is true also in the world of scientific research. The responsibility of the producers of such rankings is significant, since their results may influence decisions determining human fates and careers. The reviewed book - in a rather special area of ranking only - exemplifies how a set of methodologies can be systematically compiled, and how various methods can be combined into comprehensive, multidimensional rating and ranking systems. PMID:26234311

  4. Decision Tree Modeling for Ranking Data

    NASA Astrophysics Data System (ADS)

    Yu, Philip L. H.; Wan, Wai Ming; Lee, Paul H.

    Ranking/preference data arises from many applications in marketing, psychology, and politics. We establish a new decision tree model for the analysis of ranking data by adopting the concept of classification and regression tree. The existing splitting criteria are modified in a way that allows them to precisely measure the impurity of a set of ranking data. Two types of impurity measures for ranking data are introduced, namelyg-wise and top-k measures. Theoretical results show that the new measures exhibit properties of impurity functions. In model assessment, the area under the ROC curve (AUC) is applied to evaluate the tree performance. Experiments are carried out to investigate the predictive performance of the tree model for complete and partially ranked data and promising results are obtained. Finally, a real-world application of the proposed methodology to analyze a set of political rankings data is presented.

  5. Error analysis of stochastic gradient descent ranking.

    PubMed

    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. PMID:24083315

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

    NASA Astrophysics Data System (ADS)

    Hüllermeier, Eyke; Fürnkranz, Johannes

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

  7. Ultrasonic ranking of toughness of tungsten carbide

    NASA Technical Reports Server (NTRS)

    Vary, A.; Hull, D. R.

    1983-01-01

    The feasibility of using ultrasonic attenuation measurements to rank tungsten carbide alloys according to their fracture toughness was demonstrated. Six samples of cobalt-cemented tungsten carbide (WC-Co) were examined. These varied in cobalt content from approximately 2 to 16 weight percent. The toughness generally increased with increasing cobalt content. Toughness was first determined by the Palmqvist and short rod fracture toughness tests. Subsequently, ultrasonic attenuation measurements were correlated with both these mechanical test methods. It is shown that there is a strong increase in ultrasonic attenuation corresponding to increased toughness of the WC-Co alloys. A correlation between attenuation and toughness exists for a wide range of ultrasonic frequencies. However, the best correlation for the WC-Co alloys occurs when the attenuation coefficient measured in the vicinity of 100 megahertz is compared with toughness as determined by the Palmqvist technique.

  8. Scalable ranked retrieval using document images

    NASA Astrophysics Data System (ADS)

    Jain, Rajiv; Oard, Douglas W.; Doermann, David

    2013-12-01

    Despite the explosion of text on the Internet, hard copy documents that have been scanned as images still play a significant role for some tasks. The best method to perform ranked retrieval on a large corpus of document images, however, remains an open research question. The most common approach has been to perform text retrieval using terms generated by optical character recognition. This paper, by contrast, examines whether a scalable segmentation-free image retrieval algorithm, which matches sub-images containing text or graphical objects, can provide additional benefit in satisfying a user's information needs on a large, real world dataset. Results on 7 million scanned pages from the CDIP v1.0 test collection show that content based image retrieval finds a substantial number of documents that text retrieval misses, and that when used as a basis for relevance feedback can yield improvements in retrieval effectiveness.

  9. Anaerobic bioprocessing of low-rank coals

    SciTech Connect

    Jain, M.K.; Narayan, R.; Han, O.

    1992-07-14

    We are seeking to find biological methods to remove carboxylic functionalities from low-rank coals and to assess the properties of the modified coal towards coal liquefaction. The main objectives for this quarter were : continuation of microbial consortia development and maintenance, evaluation of commercial decarboxylase, decarboxylation of lignite, demineralized Wyodak coal and model polymer, and characterization of biotreated coals. Specifically we report that two batch fermentor systems were completed and three other fermentors under optimum conditions for coal decarboxylation are in progress; that inhibition of growth of methanogens in the batch fermentor system enhanced the carbon dioxide production; that adapted microbial consortium produced more gas from lignite than Wyodak subbituminous coal; that phenylalanine decarboxylase exhibited insignificant coal decarboxylation activity; that two different microbial consortia developed on coal seem to be effective in decarboxylation of a polymer containing free carboxylic groups; and that CHN analyses of additional biotreated coals reconfirm increase in H/C ratio by 3--6%.

  10. Anaerobic processing of low-rank coals

    SciTech Connect

    Jain, M.K.; Narayan, R.; Han, O.

    1992-01-01

    The overall goal of this project is to find biological methods to remove carboxylic functionalities from low-rank coals and to assess the properties of the modified coal towards coal liquefaction. The main objectives for this quarter were: (i) continuation of microbial consortia maintenance and completion of coal decarboxylation using batch reactor system, (ii) decarboxylation of model polymer, (iii) characterization of biotreated coals, and (iv) microautoclave liquefaction of the botreated coal. Progress is reported on the thermogravimetric analysis of coal biotreated in the absence of methanogens and under 5% hydrogen gas exhibits increased volatile carbon to fixed carbon ratio; that the microbial consortia developed on coal are being adapted to two different model polymers containing free carboxylic groups to examine decarboxylation ability of consortium; completion of experiments to decarboxylate two model polymers, polyacrylic acid and polymethyl methacrylate, have been completed; that the biotreated coal showed increase in THF-solubles.

  11. Bayesian nonparametric models for ranked set sampling.

    PubMed

    Gemayel, Nader; Stasny, Elizabeth A; Wolfe, Douglas A

    2015-04-01

    Ranked set sampling (RSS) is a data collection technique that combines measurement with judgment ranking for statistical inference. This paper lays out a formal and natural Bayesian framework for RSS that is analogous to its frequentist justification, and that does not require the assumption of perfect ranking or use of any imperfect ranking models. Prior beliefs about the judgment order statistic distributions and their interdependence are embodied by a nonparametric prior distribution. Posterior inference is carried out by means of Markov chain Monte Carlo techniques, and yields estimators of the judgment order statistic distributions (and of functionals of those distributions). PMID:25326663

  12. Email user ranking based on email networks

    NASA Astrophysics Data System (ADS)

    Tran, Quang Anh; Vu, Minh Tuan; Frater, Michael; Jiang, Frank

    2012-09-01

    In this paper, four spam-filtering approaches based on the mail networks: Clustering, Extended Clustering Coefficient, PageRank Algorithm and Weighted PageRank Algorithm are analyzed. We also propose a couple of fully worked-out datasets against which the experimental comparisons with the respect to the accuracy of email user ranking and spam filtering are conducted. The results indicate that PageRank algorithm and Extended Clustering Coefficient approaches are better than others. The rate of true detection is over 99.5% while the failed alarm remains below 0.5%.

  13. Combustion behavior of low rank coal water slurries

    SciTech Connect

    Yavuz, R.; Kuecuekbayrak, S.; Williams, A.

    1996-12-31

    Coal water slurries have been developed over the last 15 years as an alternative to fuel oil mainly in industry and power station boilers. Observing of droplet lifetime reveals details of the mechanism of the slurry combustion. In the present investigation, single droplet combustion of lignite water slurries using different Turkish lignites were experimentally studied by using single droplet combustion technique. The technique is based on thermometric method. Results of combustion behavior of low rank coal water slurries were compared with that of high rank coal water slurries which were found in the literature.

  14. Ranked Tag Recommendation Systems Based on Logistic Regression

    NASA Astrophysics Data System (ADS)

    Quevedo, J. R.; Montañés, E.; Ranilla, J.; Díaz, I.

    This work proposes an approach to tag recommendation based on a logistic regression based system. The goal of the method is to support users of current social network systems by providing a rank of new meaningful tags for a resource. This system provides a ranked tag set and it feeds on different posts depending on the resource for which the user requests the recommendation. The performance of this approach is tested according to several evaluation measures, one of them proposed in this paper (F_1^+). The experiments show that this learning system outperforms certain benchmark recommenders.

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

    PubMed

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

    2016-04-01

    Graph-based ranking has been extensively studied and frequently applied in many applications, such as webpage ranking. It aims at mining potentially valuable information from the raw graph-structured data. Recently, with the proliferation of rich heterogeneous information (e.g., node/edge features and prior knowledge) available in many real-world graphs, how to effectively and efficiently leverage all information to improve the ranking performance becomes a new challenging problem. Previous methods only utilize part of such information and attempt to rank graph nodes according to link-based methods, of which the ranking performances are severely affected by several well-known issues, e.g., over-fitting or high computational complexity, especially when the scale of graph is very large. In this paper, we address the large-scale graph-based ranking problem and focus on how to effectively exploit rich heterogeneous information of the graph to improve the ranking performance. Specifically, we propose an innovative and effective semi-supervised PageRank (SSP) approach to parameterize the derived information within a unified semi-supervised learning framework (SSLF-GR), then simultaneously optimize the parameters and the ranking scores of graph nodes. Experiments on the real-world large-scale graphs demonstrate that our method significantly outperforms the algorithms that consider such graph information only partially. PMID:25879981

  16. Fuzzy Logic and Its Application in Football Team Ranking

    PubMed Central

    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, T7, T3, T1, T9, T10, T8, T11, T12, T2, T6, T5, T4, 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. PMID:25032227

  17. A network-based ranking system for US college football

    NASA Astrophysics Data System (ADS)

    Park, Juyong; Newman, M. E. J.

    2005-10-01

    American college football faces a conflict created by the desire to stage national championship games between the best teams of a season when there is no conventional play-off system for deciding which those teams are. Instead, ranking of teams is based on their records of wins and losses during the season, but each team plays only a small fraction of eligible opponents, making the system underdetermined or contradictory or both. It is an interesting challenge to create a ranking system that at once is mathematically well founded, gives results in general accord with received wisdom concerning the relative strengths of the teams, and is based upon intuitive principles, allowing it to be accepted readily by fans and experts alike. Here we introduce a one-parameter ranking method that satisfies all of these requirements and is based on a network representation of college football schedules.

  18. Analysis of Duplicated Multiple-Samples Rank Data Using the Mack-Skillings Test.

    PubMed

    Carabante, Kennet Mariano; Alonso-Marenco, Jose Ramon; Chokumnoyporn, Napapan; Sriwattana, Sujinda; Prinyawiwatkul, Witoon

    2016-07-01

    Appropriate analysis for duplicated multiple-samples rank data is needed. This study compared analysis of duplicated rank preference data using the Friedman versus Mack-Skillings tests. Panelists (n = 125) ranked twice 2 orange juice sets: different-samples set (100%, 70%, vs. 40% juice) and similar-samples set (100%, 95%, vs. 90%). These 2 sample sets were designed to get contrasting differences in preference. For each sample set, rank sum data were obtained from (1) averaged rank data of each panelist from the 2 replications (n = 125), (2) rank data of all panelists from each of the 2 separate replications (n = 125 each), (3) jointed rank data of all panelists from the 2 replications (n = 125), and (4) rank data of all panelists pooled from the 2 replications (n = 250); rank data (1), (2), and (4) were separately analyzed by the Friedman test, although those from (3) by the Mack-Skillings test. The effect of sample sizes (n = 10 to 125) was evaluated. For the similar-samples set, higher variations in rank data from the 2 replications were observed; therefore, results of the main effects were more inconsistent among methods and sample sizes. Regardless of analysis methods, the larger the sample size, the higher the χ(2) value, the lower the P-value (testing H0 : all samples are not different). Analyzing rank data (2) separately by replication yielded inconsistent conclusions across sample sizes, hence this method is not recommended. The Mack-Skillings test was more sensitive than the Friedman test. Furthermore, it takes into account within-panelist variations and is more appropriate for analyzing duplicated rank data. PMID:27240170

  19. Multiview saliency detection based on improved multimanifold ranking

    NASA Astrophysics Data System (ADS)

    Shi, Yanjiao; Yi, Yugen; Zhang, Ke; Kong, Jun; Zhang, Ming; Wang, Jianzhong

    2014-11-01

    As an important problem in computer vision, saliency detection is essential for image segmentation, super-resolution, object recognition, and so on. We propose a saliency detection method for images. Instead of using contrast between salient regions and their surrounding areas, both cues from salient and nonsalient regions are considered in our study. Based on these cues, an improved multimanifold ranking algorithm is proposed. In our algorithm, features from multiple views are utilized and the different contributions of these multiview features are taken into account. Moreover, an iterative updating optimization scheme is explored to solve the objective function, during which the feature fusion is performed. After two-stage ranking by the improved multimanifold ranking algorithm, each image patch can be assigned a ranking score, which determines the final saliency. The proposed method is evaluated on four public datasets and is compared with the state-of-the-art methods. Experimental results indicate that the proposed method outperforms existing schemes both in qualitative and quantitative comparisons.

  20. Ranked Retrieval with Semantic Networks and Vector Spaces.

    ERIC Educational Resources Information Center

    Kulyukin, Vladimir A.; Settle, Amber

    2001-01-01

    Discussion of semantic networks and ranked retrieval focuses on two models, the semantic network model with spreading activation and the vector space model with dot product. Suggests a formal method to analyze the two models in terms of their relative performance in the same universe of objects. (Author/LRW)

  1. Mining Feedback in Ranking and Recommendation Systems

    ERIC Educational Resources Information Center

    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…

  2. Public Perception of Cancer Survival Rankings

    ERIC Educational Resources Information Center

    Jensen, Jakob D.; Scherr, Courtney L.; Brown, Natasha; Jones, Christina; Christy, Katheryn

    2013-01-01

    Past research has observed that certain subgroups (e.g., individuals who are overweight/obese) have inaccurate estimates of survival rates for particular cancers (e.g., colon cancer). However, no study has examined whether the lay public can accurately rank cancer survival rates in comparison with one another (i.e., rank cancers from most deadly…

  3. A Different Approach to University Rankings

    ERIC Educational Resources Information Center

    Tofallis, Chris

    2012-01-01

    Educationalists are well able to find fault with rankings on numerous grounds and may reject them outright. However, given that they are here to stay, we could also try to improve them wherever possible. All currently published university rankings combine various measures to produce an overall score using an additive approach. The individual…

  4. Rankings and the Global Reputation Race

    ERIC Educational Resources Information Center

    Hazelkorn, Ellen

    2014-01-01

    This chapter delves into the growing influence and impact of rankings on higher education, as a lens through which to view how the race for reputation and status is changing the higher education landscape, both globally and nationally. The author considers the extent to which rankings are driving policy choices and institutional decisions and the…

  5. College Rankings: History, Criticism and Reform

    ERIC Educational Resources Information Center

    Myers, Luke; Robe, Jonathan

    2009-01-01

    Today, college quality rankings in news magazines and guidebooks are a big business with tangible impacts on the operation of higher education institutions. The college rankings published annually by "U.S. News and World Report" ("U.S. News") are so influential that Don Hossler of Indiana University derisively claims that higher education is the…

  6. The Rankings Game: Who's Playing Whom?

    ERIC Educational Resources Information Center

    Burness, John F.

    2008-01-01

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

  7. Ranked retrieval of Computational Biology models

    PubMed Central

    2010-01-01

    Background The study of biological systems demands computational support. If targeting a biological problem, the reuse of existing computational models can save time and effort. Deciding for potentially suitable models, however, becomes more challenging with the increasing number of computational models available, and even more when considering the models' growing complexity. Firstly, among a set of potential model candidates it is difficult to decide for the model that best suits ones needs. Secondly, it is hard to grasp the nature of an unknown model listed in a search result set, and to judge how well it fits for the particular problem one has in mind. Results Here we present an improved search approach for computational models of biological processes. It is based on existing retrieval and ranking methods from Information Retrieval. The approach incorporates annotations suggested by MIRIAM, and additional meta-information. It is now part of the search engine of BioModels Database, a standard repository for computational models. Conclusions The introduced concept and implementation are, to our knowledge, the first application of Information Retrieval techniques on model search in Computational Systems Biology. Using the example of BioModels Database, it was shown that the approach is feasible and extends the current possibilities to search for relevant models. The advantages of our system over existing solutions are that we incorporate a rich set of meta-information, and that we provide the user with a relevance ranking of the models found for a query. Better search capabilities in model databases are expected to have a positive effect on the reuse of existing models. PMID:20701772

  8. Universal emergence of PageRank

    NASA Astrophysics Data System (ADS)

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

    2011-11-01

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

  9. A Social Rank Explanation of How Money Influences Health

    PubMed Central

    2014-01-01

    Objective: Financial resources are a potent determinant of health, yet it remains unclear why this is the case. We aimed to identify whether the frequently observed association between absolute levels of monetary resources and health may occur because money acts an indirect proxy for a person’s social rank. Method: To address this question we examined over 230,000 observations on 40,400 adults drawn from two representative national panel studies; the British Household Panel Survey and the English Longitudinal Study of Ageing. We identified each person’s absolute income/wealth and their objective ranked position of income/wealth within a social reference-group. Absolute and rank income/wealth variables were then used to predict a series of self-reported and objectively recorded health outcomes in cross-sectional and longitudinal analyses. Results: As anticipated, those with higher levels of absolute income/wealth were found to have better health than others, after adjustment for age, gender, education, marital status, and labor force status. When evaluated simultaneously the ranked position of income/wealth but not absolute income/wealth predicted all health outcomes examined including: objective measures of allostatic load and obesity, the presence of long-standing illness, and ratings of health, physical functioning, role limitations, and pain. The health benefits of high rank were consistent in cross-sectional and longitudinal analyses and did not depend on the reference-group used to rank participants. Conclusions: This is the first study to demonstrate that social position rather than material conditions may explain the impact of money on human health. PMID:25133843

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

    SciTech Connect

    Merkhofer, L.; Kann, A.; Voth, M.

    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.

  11. Dosimetric impacts of microgravity: an analysis of 5th, 50th and 95th percentile male and female astronauts

    NASA Astrophysics Data System (ADS)

    Bahadori, Amir A.; Van Baalen, Mary; Shavers, Mark R.; Semones, Edward J.; Bolch, Wesley E.

    2012-02-01

    Computational phantoms serve an important role in organ dosimetry and risk assessment performed at the National Aeronautics and Space Administration (NASA). A previous study investigated the impact on organ dose equivalents and effective doses from the use of the University of Florida hybrid adult male (UFHADM) and adult female (UFHADF) phantoms at differing height and weight percentiles versus those given by the two existing NASA phantoms, the computerized anatomical man (CAM) and female (CAF) (Bahadori et al 2011 Phys. Med. Biol. 56 1671-94). In the present study, the UFHADM and UFHADF phantoms of different body sizes were further altered to incorporate the effects of microgravity. Body self-shielding distributions are generated using the voxel-based ray tracer (VoBRaT), and the results are combined with depth dose data from the NASA codes BRYNTRN and HZETRN to yield organ dose equivalents and their rates for a variety of space radiation environments. It is found that while organ dose equivalents are indeed altered by the physiological effects of microgravity, the magnitude of the change in overall risk (indicated by the effective dose) is minimal for the spectra and simplified shielding configurations considered. The results also indicate, however, that UFHADM and UFHADF could be useful in designing dose reduction strategies through optimized positioning of an astronaut during encounters with solar particle events.

  12. Tan's Epsilon-Determinant and Ranks of Matrices over Semirings

    PubMed Central

    Mohindru, Preeti; Pereira, Rajesh

    2015-01-01

    We use the ϵ-determinant introduced by Ya-Jia Tan to define a family of ranks of matrices over certain semirings. We show that these ranks generalize some known rank functions over semirings such as the determinantal rank. We also show that this family of ranks satisfies the rank-sum and Sylvester inequalities. We classify all bijective linear maps which preserve these ranks.

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  14. Research Productivity in Top-Ranked Schools in Psychology and Social Work: Research Cultures Do Matter!

    ERIC Educational Resources Information Center

    Holosko, Michael J.; Barner, John R.

    2016-01-01

    Objectives: We sought the answer to one major research question--Does psychology have a more defined culture of research than social work? Methods: Using "U.S. News and World Report" 2012 and 2013 rankings, we compared psychology faculty (N = 969) from their 25 top ranked programs with a controlled sample of social work faculty (N = 970)…

  15. World University Ranking Systems: An Alternative Approach Using Partial Least Squares Path Modelling

    ERIC Educational Resources Information Center

    Jajo, Nethal K.; Harrison, Jen

    2014-01-01

    University rankings are key drivers in national and institutional strategic planning. The increase in the number of university ranking systems and the diversity of methods and indicators used by these systems necessitate the development of an index that can measure a university's performance in all these systems at once. This article presents…

  16. Clinical Psychology Ph.D. Program Rankings: Evaluating Eminence on Faculty Publications and Citations

    ERIC Educational Resources Information Center

    Matson, Johnny L.; Malone, Carrie J.; Gonzalez, Melissa L.; McClure, David R.; Laud, Rinita B.; Minshawi, Noha F.

    2005-01-01

    Program rankings and their visibility have taken on greater and greater significance. Rarely is the accuracy of these rankings, which are typically based on a small subset of university faculty impressions, questioned. This paper presents a more comprehensive survey method based on quantifiable measures of faculty publications and citations. The…

  17. Low-Rank Total Variation for Image Super-Resolution

    PubMed Central

    Shi, Feng; Cheng, Jian; Wang, Li; Yap, Pew-Thian; Shen, Dinggang

    2014-01-01

    Most natural images can be approximated using their low-rank components. This fact has been successfully exploited in recent advancements of matrix completion algorithms for image recovery. However, a major limitation of low-rank matrix completion algorithms is that they cannot recover the case where a whole row or column is missing. The missing row or column will be simply filled as an arbitrary combination of other rows or columns with known values. This precludes the application of matrix completion to problems such as super-resolution (SR) where missing values in many rows and columns need to be recovered in the process of up-sampling a low-resolution image. Moreover, low-rank regularization considers information globally from the whole image and does not take proper consideration of local spatial consistency. Accordingly, we propose in this paper a solution to the SR problem via simultaneous (global) low-rank and (local) total variation (TV) regularization. We solve the respective cost function using the alternating direction method of multipliers (ADMM). Experiments on MR images of adults and pediatric subjects demonstrate that the proposed method enhances the details of the recovered high-resolution images, and outperforms the nearest-neighbor interpolation, cubic interpolation, non-local means, and TV-based up-sampling. PMID:24505661

  18. Ranking the spreading ability of nodes in network core

    NASA Astrophysics Data System (ADS)

    Tong, Xiao-Lei; Liu, Jian-Guo; Wang, Jiang-Pan; Guo, Qiang; Ni, Jing

    2015-11-01

    Ranking nodes by their spreading ability in complex networks is of vital significance to better understand the network structure and more efficiently spread information. The k-shell decomposition method could identify the most influential nodes, namely network core, with the same ks values regardless to their different spreading influence. In this paper, we present an improved method based on the k-shell decomposition method and closeness centrality (CC) to rank the node spreading influence of the network core. Experiment results on the data from the scientific collaboration network and U.S. aviation network show that the accuracy of the presented method could be increased by 31% and 45% than the one obtained by the degree k, 32% and 31% than the one by the betweenness.

  19. Percentile Distributions of Median Nitrite Plus Nitrate as Nitrogen, Total Nitrogen, and Total Phosphorus Concentrations in Oklahoma Streams, 1973-2001

    USGS Publications Warehouse

    Haggard, Brian E.; Masoner, Jason R.; Becker, Carol J.

    2003-01-01

    Nutrients are one of the primary causes of water-quality impairments in streams, lakes, reservoirs, and estuaries in the United States. The U.S. Environmental Protection Agency has developed regional-based nutrient criteria using ecoregions to protect streams in the United States from impairment. However, nutrient criteria were based on nutrient concentrations measured in large aggregated nutrient ecoregions with little relevance to local environmental conditions in states. The Oklahoma Water Resources Board is using a dichotomous process known as Use Support Assessment Protocols to define nutrient criteria in Oklahoma streams. The Oklahoma Water Resources Board is modifying the Use Support Assessment Protocols to reflect nutrient informa-tion and environmental characteristics relevant to Oklahoma streams, while considering nutrient information grouped by geographic regions based on level III ecoregions and state boundaries. Percentile distributions of median nitrite plus nitrate as nitrogen, total nitrogen, and total phosphorous concentrations were calculated from 563 sites in Oklahoma and 4 sites in Arkansas near the Oklahoma and Arkansas border to facilitate development of nutrient criteria for Oklahoma streams. Sites were grouped into four geographic regions and were categorized into eight stream categories by stream slope and stream order. The 50th percentiles of median nitrite plus nitrate as nitrogen, total nitrogen, and total phosphorus concentrations were greater in the Ozark Highland ecoregion and were less in the Ouachita Mountains ecoregion when compared to other geographic areas used to group sites. The 50th percentiles of median concentrations of nitrite plus nitrate as nitrogen, total nitrogen, and total phosphorus were least in first, second, and third order streams. The 50th percentiles of median nitrite plus nitrate as nitrogen, total nitrogen and total phosphorus concentrations in the Ozark Highland and Ouachita Mountains ecoregions were least in

  20. Adiabatic Quantum Algorithm for Search Engine Ranking

    NASA Astrophysics Data System (ADS)

    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.

  1. Ranking Competitors Using Degree-Neutralized Random Walks

    PubMed Central

    Shin, Seungkyu; Ahnert, Sebastian E.; Park, Juyong

    2014-01-01

    Competition is ubiquitous in many complex biological, social, and technological systems, playing an integral role in the evolutionary dynamics of the systems. It is often useful to determine the dominance hierarchy or the rankings of the components of the system that compete for survival and success based on the outcomes of the competitions between them. Here we propose a ranking method based on the random walk on the network representing the competitors as nodes and competitions as directed edges with asymmetric weights. We use the edge weights and node degrees to define the gradient on each edge that guides the random walker towards the weaker (or the stronger) node, which enables us to interpret the steady-state occupancy as the measure of the node's weakness (or strength) that is free of unwarranted degree-induced bias. We apply our method to two real-world competition networks and explore the issues of ranking stabilization and prediction accuracy, finding that our method outperforms other methods including the baseline win–loss differential method in sparse networks. PMID:25517977

  2. Low-rank coal oil agglomeration

    DOEpatents

    Knudson, Curtis L.; Timpe, Ronald C.

    1991-01-01

    A low-rank coal oil agglomeration process. 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 usually coal derived.

  3. Rank distributions: a panoramic macroscopic outlook.

    PubMed

    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. PMID:24580176

  4. Rank distributions: A panoramic macroscopic outlook

    NASA Astrophysics Data System (ADS)

    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.

  5. RANK as a therapeutic target in cancer.

    PubMed

    González-Suárez, Eva; Sanz-Moreno, Adrián

    2016-06-01

    The RANK signaling pathway has emerged as a new target in breast cancer as receptor activator of nuclear factor κB ligand (RANKL) and its receptor RANK mediate the pro-tumorigenic role of progesterone in the mammary gland. Thousands of cancer patients worldwide are already taking RANKL inhibitors for the management of bone metastasis, given the relevance of this pathway in osteoclastogenesis and bone resorption. RANK signaling also has multiple divergent effects in immunity and inflammation, both in the generation of active immune responses and in the induction of tolerance: it is required for lymph node organogenesis, thymic medullary epithelial development and self-tolerance, and regulates activation of several immune cells and inflammatory processes. The RANK pathway interferes with mammary epithelial differentiation and mediates the major proliferative response of mammary epithelium to progesterone and progesterone-driven expansion of mammary stem cells; it also controls hair follicle and epidermal stem cell homeostasis, pointing to RANK as a key regulator of epithelial stemness. Here we revisit the main functions of RANK signaling in bone remodeling, immune cells and epithelial differentiation. We also discuss the mechanistic evidence that supports its pleiotropic effects on cancer: from bone metastasis to immune and cancer-cell-dependent effects. PMID:26749530

  6. An Efficient Web Page Ranking for Semantic Web

    NASA Astrophysics Data System (ADS)

    Chahal, P.; Singh, M.; Kumar, S.

    2014-01-01

    With the enormous amount of information presented on the web, the retrieval of relevant information has become a serious problem and is also the topic of research for last few years. The most common tools to retrieve information from web are search engines like Google. The Search engines are usually based on keyword searching and indexing of web pages. This approach is not very efficient as the result-set of web pages obtained include large irrelevant pages. Sometimes even the entire result-set may contain lot of irrelevant pages for the user. The next generation of search engines must address this problem. Recently, many semantic web search engines have been developed like Ontolook, Swoogle, which help in searching meaningful documents presented on semantic web. In this process the ranking of the retrieved web pages is very crucial. Some attempts have been made in ranking of semantic web pages but still the ranking of these semantic web documents is neither satisfactory and nor up to the user's expectations. In this paper we have proposed a semantic web based document ranking scheme that relies not only on the keywords but also on the conceptual instances present between the keywords. As a result only the relevant page will be on the top of the result-set of searched web pages. We explore all relevant relations between the keywords exploring the user's intention and then calculate the fraction of these relations on each web page to determine their relevance. We have found that this ranking technique gives better results than those by the prevailing methods.

  7. A scale for ranking volcanoes by risk

    NASA Astrophysics Data System (ADS)

    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.

  8. The ranks of Indonesian and Japanese industrial sectors

    NASA Astrophysics Data System (ADS)

    Zuhdi, Ubaidillah

    2016-07-01

    The purpose of this study is to determine the ranks of Indonesian and Japanese industrial sectors from the economic point of view. The analysis period of this study is 2005. This study employs one of the well-known analysis tools in the economic topic, the Input-Output (IO) analysis. More specifically, this study uses the analysis methods in the IO analysis, backward and forward linkages, in order to achieve the purpose. The results of calculations show that the orders of the ranks depend on the method used. Nevertheless, from the results, one can say that the manufacturing industry was a leading sector in the Indonesian economy on the analysis period. On the other hand, for the Japanese case, the sector which had the beneficial effects in the Japanese economy on the analysis period was the transport.

  9. Poisson statistics of PageRank probabilities of Twitter and Wikipedia networks

    NASA Astrophysics Data System (ADS)

    Frahm, Klaus M.; Shepelyansky, Dima L.

    2014-04-01

    We use the methods of quantum chaos and Random Matrix Theory for analysis of statistical fluctuations of PageRank probabilities in directed networks. In this approach the effective energy levels are given by a logarithm of PageRank probability at a given node. After the standard energy level unfolding procedure we establish that the nearest spacing distribution of PageRank probabilities is described by the Poisson law typical for integrable quantum systems. Our studies are done for the Twitter network and three networks of Wikipedia editions in English, French and German. We argue that due to absence of level repulsion the PageRank order of nearby nodes can be easily interchanged. The obtained Poisson law implies that the nearby PageRank probabilities fluctuate as random independent variables.

  10. siRNA Knock-Down of RANK Signaling to Control Osteoclast-Mediated Bone Resorption

    PubMed Central

    Wang, Yuwei; Grainger, David W.

    2010-01-01

    Purpose To demonstrate the ability of small interfering (si)RNA targeting the cell receptor, RANK, to control osteoclast function in cultures of both primary and secondary osteoclasts and their precursor cells. Methods siRNA targeting RANK was transfected into both RAW264.7 and primary bone marrow cell cultures. RANK knock-down by siRNA and functional inhibition were assessed in both mature osteoclast and their precursor cell cultures. RANK mRNA message and protein expression after the transfections were analyzed by PCR and Western blot, respectively. Off-target effects were assessed. The inhibition of osteoclast formation was evaluated using tartrate-resistant acid phosphatase (TRAP) assay, and subsequent bone resorption was determined by resorption pit assay. Results Both osteoclasts and osteoclast precursors can be targeted by siRNA in serum-containing media. Delivery of siRNA targeting RANK to both RAW 264.7 and primary bone marrow cell cultures produces short term repression of RANK expression without off-targeting effects, and significantly inhibits both osteoclast formation and bone resorption. Moreover, data support successful RANK knock-down by siRNA specifically in mature osteoclast cultures. Conclusions RANK is demonstrated to be an attractive target for siRNA control of osteoclast activity, with utility for development of new therapeutics for low bone mass pathologies or osteoporosis. PMID:20333451

  11. Detect2Rank: Combining Object Detectors Using Learning to Rank.

    PubMed

    Karaoglu, Sezer; Yang Liu; Gevers, Theo

    2016-01-01

    Object detection is an important research area in the field of computer vision. Many detection algorithms have been proposed. However, each object detector relies on specific assumptions of the object appearance and imaging conditions. As a consequence, no algorithm can be considered universal. With the large variety of object detectors, the subsequent question is how to select and combine them. In this paper, we propose a framework to learn how to combine object detectors. The proposed method uses (single) detectors like Deformable Part Models, Color Names and Ensemble of Exemplar-SVMs, and exploits their correlation by high-level contextual features to yield a combined detection list. Experiments on the PASCAL VOC07 and VOC10 data sets show that the proposed method significantly outperforms single object detectors, DPM (8.4%), CN (6.8%) and EES (17.0%) on VOC07 and DPM (6.5%), CN (5.5%) and EES (16.2%) on VOC10. We show with an experiment that there are no constraints on the type of the detector. The proposed method outperforms (2.4%) the state-of-the-art object detector (RCNN) on VOC07 when Regions with Convolutional Neural Network is combined with other detectors used in this paper. PMID:26571528

  12. Comparing and ranking hospitals based on outcome: results from The Netherlands Stroke Survey

    PubMed Central

    Steyerberg, E.W.; Eijkemans, M.J.C.; Dippel, D.W.J.; Scholte Op Reimer, W.J.M.; Van Houwelingen, H.C.

    2010-01-01

    Background: Measuring quality of care and ranking hospitals with outcome measures poses two major methodological challenges: case-mix adjustment and variation that exists by chance. Aim: To compare methods for comparing and ranking hospitals that considers these. Methods: The Netherlands Stroke Survey was conducted in 10 hospitals in the Netherlands, between October 2002 and May 2003, with prospective and consecutive enrolment of patients with acute brain ischaemia. Poor outcome was defined as death or disability after 1 year (modified Rankin scale of ⩾3). We calculated fixed and random hospital effects on poor outcome, unadjusted and adjusted for patient characteristics. We compared the hospitals using the expected rank, a novel statistical measure incorporating the magnitude and the uncertainty of differences in outcome. Results: At 1 year after stroke, 268 of the total 505 patients (53%) had a poor outcome. There were substantial differences in outcome between hospitals in unadjusted analysis (χ2 = 48, 9 df, P < 0.0001). Adjustment for 12 confounders led to halving of the χ2 (χ2 = 24). The same pattern was observed in random effects analysis. Estimated performance of individual hospitals changed considerably between unadjusted and adjusted analysis. Further changes were seen with random effect estimation, especially for smaller hospitals. Ordering by expected rank led to shrinkage of the original ranks of 1–10 towards the median rank of 5.5 and to a different order of the hospitals, compared to ranking based on fixed effects. Conclusion: In comparing and ranking hospitals, case-mix-adjusted random effect estimates and the expected ranks are more robust alternatives to traditional fixed effect estimates and simple rankings. PMID:20008321

  13. A ranking efficiency unit by restrictions using DEA models

    NASA Astrophysics Data System (ADS)

    Arsad, Roslah; Abdullah, Mohammad Nasir; Alias, Suriana

    2014-12-01

    In this paper, a comparison regarding the efficiency shares of listed companies in Bursa Malaysia was made, through the application of estimation method of Data Envelopment Analysis (DEA). In this study, DEA is used to measure efficiency shares of listed companies in Bursa Malaysia in terms of the financial performance. It is believed that only good financial performer will give a good return to the investors in the long run. The main objectives were to compute the relative efficiency scores of the shares in Bursa Malaysia and rank the shares based on Balance Index with regard to relative efficiency. The methods of analysis using Alirezaee and Afsharian's model were employed to this study; where the originality of Charnes, Cooper and Rhode model (CCR) with assumption of constant return to scale (CRS) still holds. This method of ranking relative efficiency of decision making units (DMUs) was value-added by using Balance Index. From the result, the companies that were recommended for investors based on ranking were NATWIDE, YTL and MUDA. These companies were the top three efficient companies with good performance in 2011 whereas in 2012 the top three companies were NATWIDE, MUDA and BERNAS.

  14. Sparse/Low Rank Constrained Reconstruction for Dynamic PET Imaging

    PubMed Central

    Yu, Xingjian; Chen, Shuhang; Hu, Zhenghui; Liu, Meng; Chen, Yunmei; Shi, Pengcheng; Liu, Huafeng

    2015-01-01

    In dynamic Positron Emission Tomography (PET), an estimate of the radio activity concentration is obtained from a series of frames of sinogram data taken at ranging in duration from 10 seconds to minutes under some criteria. So far, all the well-known reconstruction algorithms require known data statistical properties. It limits the speed of data acquisition, besides, it is unable to afford the separated information about the structure and the variation of shape and rate of metabolism which play a major role in improving the visualization of contrast for some requirement of the diagnosing in application. This paper presents a novel low rank-based activity map reconstruction scheme from emission sinograms of dynamic PET, termed as SLCR representing Sparse/Low Rank Constrained Reconstruction for Dynamic PET Imaging. In this method, the stationary background is formulated as a low rank component while variations between successive frames are abstracted to the sparse. The resulting nuclear norm and l1 norm related minimization problem can also be efficiently solved by many recently developed numerical methods. In this paper, the linearized alternating direction method is applied. The effectiveness of the proposed scheme is illustrated on three data sets. PMID:26540274

  15. Laplacian Regularized Low-Rank Representation and Its Applications.

    PubMed

    Yin, Ming; Gao, Junbin; Lin, Zhouchen

    2016-03-01

    Low-rank representation (LRR) has recently attracted a great deal of attention due to its pleasing efficacy in exploring low-dimensional subspace structures embedded in data. For a given set of observed data corrupted with sparse errors, LRR aims at learning a lowest-rank representation of all data jointly. LRR has broad applications in pattern recognition, computer vision and signal processing. In the real world, data often reside on low-dimensional manifolds embedded in a high-dimensional ambient space. However, the LRR method does not take into account the non-linear geometric structures within data, thus the locality and similarity information among data may be missing in the learning process. To improve LRR in this regard, we propose a general Laplacian regularized low-rank representation framework for data representation where a hypergraph Laplacian regularizer can be readily introduced into, i.e., a Non-negative Sparse Hyper-Laplacian regularized LRR model (NSHLRR). By taking advantage of the graph regularizer, our proposed method not only can represent the global low-dimensional structures, but also capture the intrinsic non-linear geometric information in data. The extensive experimental results on image clustering, semi-supervised image classification and dimensionality reduction tasks demonstrate the effectiveness of the proposed method. PMID:27046494

  16. Manifold Ranking-Based Matrix Factorization for Saliency Detection.

    PubMed

    Tao, Dapeng; Cheng, Jun; Song, Mingli; Lin, Xu

    2016-06-01

    Saliency detection is used to identify the most important and informative area in a scene, and it is widely used in various vision tasks, including image quality assessment, image matching, and object recognition. Manifold ranking (MR) has been used to great effect for the saliency detection, since it not only incorporates the local spatial information but also utilizes the labeling information from background queries. However, MR completely ignores the feature information extracted from each superpixel. In this paper, we propose an MR-based matrix factorization (MRMF) method to overcome this limitation. MRMF models the ranking problem in the matrix factorization framework and embeds query sample labels in the coefficients. By incorporating spatial information and embedding labels, MRMF enforces similar saliency values on neighboring superpixels and ranks superpixels according to the learned coefficients. We prove that the MRMF has good generalizability, and develops an efficient optimization algorithm based on the Nesterov method. Experiments using popular benchmark data sets illustrate the promise of MRMF compared with the other state-of-the-art saliency detection methods. PMID:26277008

  17. Rank-1 accelerated illumination recovery in scanning diffractive imaging by transparency estimation.

    SciTech Connect

    Wu, Hau-Tieng

    2014-08-07

    Illumination retrieval in scanning diffractive imaging a.k.a. ptychography is challenging when the specimen is weakly scattering or surrounded by empty space. We describe a rank-1 acceleration method for weakly scattering or piecewise smooth specimens.

  18. Multi-energy CT based on a prior rank, intensity and sparsity model (PRISM)

    PubMed Central

    Gao, Hao; Yu, Hengyong; Osher, Stanley; Wang, Ge

    2011-01-01

    We propose a compressive sensing approach for multi-energy computed tomography (CT), namely the prior rank, intensity and sparsity model (PRISM). To further compress the multi-energy image for allowing the reconstruction with fewer CT data and less radiation dose, the PRISM models a multi-energy image as the superposition of a low-rank matrix and a sparse matrix (with row dimension in space and column dimension in energy), where the low-rank matrix corresponds to the stationary background over energy that has a low matrix rank, and the sparse matrix represents the rest of distinct spectral features that are often sparse. Distinct from previous methods, the PRISM utilizes the generalized rank, e.g., the matrix rank of tight-frame transform of a multi-energy image, which offers a way to characterize the multi-level and multi-filtered image coherence across the energy spectrum. Besides, the energy-dependent intensity information can be incorporated into the PRISM in terms of the spectral curves for base materials, with which the restoration of the multi-energy image becomes the reconstruction of the energy-independent material composition matrix. In other words, the PRISM utilizes prior knowledge on the generalized rank and sparsity of a multi-energy image, and intensity/spectral characteristics of base materials. Furthermore, we develop an accurate and fast split Bregman method for the PRISM and demonstrate the superior performance of the PRISM relative to several competing methods in simulations. PMID:22223929

  19. Multi-energy CT based on a prior rank, intensity and sparsity model (PRISM).

    PubMed

    Gao, Hao; Yu, Hengyong; Osher, Stanley; Wang, Ge

    2011-11-01

    We propose a compressive sensing approach for multi-energy computed tomography (CT), namely the prior rank, intensity and sparsity model (PRISM). To further compress the multi-energy image for allowing the reconstruction with fewer CT data and less radiation dose, the PRISM models a multi-energy image as the superposition of a low-rank matrix and a sparse matrix (with row dimension in space and column dimension in energy), where the low-rank matrix corresponds to the stationary background over energy that has a low matrix rank, and the sparse matrix represents the rest of distinct spectral features that are often sparse. Distinct from previous methods, the PRISM utilizes the generalized rank, e.g., the matrix rank of tight-frame transform of a multi-energy image, which offers a way to characterize the multi-level and multi-filtered image coherence across the energy spectrum. Besides, the energy-dependent intensity information can be incorporated into the PRISM in terms of the spectral curves for base materials, with which the restoration of the multi-energy image becomes the reconstruction of the energy-independent material composition matrix. In other words, the PRISM utilizes prior knowledge on the generalized rank and sparsity of a multi-energy image, and intensity/spectral characteristics of base materials. Furthermore, we develop an accurate and fast split Bregman method for the PRISM and demonstrate the superior performance of the PRISM relative to several competing methods in simulations. PMID:22223929

  20. Spectral thresholding quantum tomography for low rank states

    NASA Astrophysics Data System (ADS)

    Butucea, Cristina; Guţă, Mădălin; Kypraios, Theodore

    2015-11-01

    The estimation of high dimensional quantum states is an important statistical problem arising in current quantum technology applications. A key example is the tomography of multiple ions states, employed in the validation of state preparation in ion trap experiments (Häffner et al 2005 Nature 438 643). Since full tomography becomes unfeasible even for a small number of ions, there is a need to investigate lower dimensional statistical models which capture prior information about the state, and to devise estimation methods tailored to such models. In this paper we propose several new methods aimed at the efficient estimation of low rank states and analyse their performance for multiple ions tomography. All methods consist in first computing the least squares estimator, followed by its truncation to an appropriately chosen smaller rank. The latter is done by setting eigenvalues below a certain ‘noise level’ to zero, while keeping the rest unchanged, or normalizing them appropriately. We show that (up to logarithmic factors in the space dimension) the mean square error of the resulting estimators scales as r\\cdot d/N where r is the rank, d={2}k is the dimension of the Hilbert space, and N is the number of quantum samples. Furthermore we establish a lower bound for the asymptotic minimax risk which shows that the above scaling is optimal. The performance of the estimators is analysed in an extensive simulations study, with emphasis on the dependence on the state rank, and the number of measurement repetitions. We find that all estimators perform significantly better than the least squares, with the ‘physical estimator’ (which is a bona fide density matrix) slightly outperforming the other estimators.

  1. Groundwater contaminant plume ranking. [UMTRA Project

    SciTech Connect

    Not Available

    1988-08-01

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

  2. Deep impact: unintended consequences of journal rank.

    PubMed

    Brembs, Björn; Button, Katherine; Munafò, Marcus

    2013-01-01

    Most researchers acknowledge an intrinsic hierarchy in the scholarly journals ("journal rank") that they submit their work to, and adjust not only their submission but also their reading strategies accordingly. On the other hand, much has been written about the negative effects of institutionalizing journal rank as an impact measure. So far, contributions to the debate concerning the limitations of journal rank as a scientific impact assessment tool have either lacked data, or relied on only a few studies. In this review, we present the most recent and pertinent data on the consequences of our current scholarly communication system with respect to various measures of scientific quality (such as utility/citations, methodological soundness, expert ratings or retractions). These data corroborate previous hypotheses: 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 altogether, in favor of a library-based scholarly communication system, will ultimately be necessary. This new system will use modern information technology to vastly improve the filter, sort and discovery functions of the current journal system. PMID:23805088

  3. Diversity rankings among bacterial lineages in soil.

    PubMed

    Youssef, Noha H; Elshahed, Mostafa S

    2009-03-01

    We used rarefaction curve analysis and diversity ordering-based approaches to rank the 11 most frequently encountered bacterial lineages in soil according to diversity in 5 previously reported 16S rRNA gene clone libraries derived from agricultural, undisturbed tall grass prairie and forest soils (n=26,140, 28 328, 31 818, 13 001 and 53 533). The Planctomycetes, Firmicutes and the delta-Proteobacteria were consistently ranked among the most diverse lineages in all data sets, whereas the Verrucomicrobia, Gemmatimonadetes and beta-Proteobacteria were consistently ranked among the least diverse. On the other hand, the rankings of alpha-Proteobacteria, Acidobacteria, Actinobacteria, Bacteroidetes and Chloroflexi varied widely in different soil clone libraries. In general, lineages exhibiting largest differences in diversity rankings also exhibited the largest difference in relative abundance in the data sets examined. Within these lineages, a positive correlation between relative abundance and diversity was observed within the Acidobacteria, Actinobacteria and Chloroflexi, and a negative diversity-abundance correlation was observed within the Bacteroidetes. The ecological and evolutionary implications of these results are discussed. PMID:18987677

  4. Enhancing collaborative filtering by user interest expansion via personalized ranking.

    PubMed

    Liu, Qi; Chen, Enhong; Xiong, Hui; Ding, Chris H Q; Chen, Jian

    2012-02-01

    Recommender systems suggest a few items from many possible choices to the users by understanding their past behaviors. In these systems, the user behaviors are influenced by the hidden interests of the users. Learning to leverage the information about user interests is often critical for making better recommendations. However, existing collaborative-filtering-based recommender systems are usually focused on exploiting the information about the user's interaction with the systems; the information about latent user interests is largely underexplored. To that end, inspired by the topic models, in this paper, we propose a novel collaborative-filtering-based recommender system by user interest expansion via personalized ranking, named iExpand. The goal is to build an item-oriented model-based collaborative-filtering framework. The iExpand method introduces a three-layer, user-interests-item, representation scheme, which leads to more accurate ranking recommendation results with less computation cost and helps the understanding of the interactions among users, items, and user interests. Moreover, iExpand strategically deals with many issues that exist in traditional collaborative-filtering approaches, such as the overspecialization problem and the cold-start problem. Finally, we evaluate iExpand on three benchmark data sets, and experimental results show that iExpand can lead to better ranking performance than state-of-the-art methods with a significant margin. PMID:21880572

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

    PubMed

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

    2016-02-01

    Phylogenetic analysis of extinction threat is an emerging tool in the field of conservation. However, there are problems with the methods and data as commonly used. Phylogenetic sampling usually extends to the level of family or genus, but International Union for Conservation of Nature (IUCN) rankings are available only for individual species, and, although different species within a taxonomic group may have the same IUCN rank, the species may have been ranked as such for different reasons. Therefore, IUCN rank may not reflect evolutionary history and thus may not be appropriate for use in a phylogenetic context. To be used appropriately, threat-risk data should reflect the cause of extinction threat rather than the IUCN threat ranking. In a case study of the toad genus Incilius, with phylogenetic sampling at the species level (so that the resolution of the phylogeny matches character data from the IUCN Red List), we analyzed causes of decline and IUCN threat rankings by calculating metrics of phylogenetic signal (such as Fritz and Purvis' D). We also analyzed the extent to which cause of decline and threat ranking overlap by calculating phylogenetic correlation between these 2 types of character data. Incilius species varied greatly in both threat ranking and cause of decline; this variability would be lost at a coarser taxonomic resolution. We found far more phylogenetic signal, likely correlated with evolutionary history, for causes of decline than for IUCN threat ranking. Individual causes of decline and IUCN threat rankings were largely uncorrelated on the phylogeny. Our results demonstrate the importance of character selection and taxonomic resolution when extinction threat is analyzed in a phylogenetic context. PMID:26243724

  6. Adjoints and Low-rank Covariance Representation

    NASA Technical Reports Server (NTRS)

    Tippett, Michael K.; Cohn, Stephen E.

    2000-01-01

    Quantitative measures of the uncertainty of Earth System estimates can be as important as the estimates themselves. Second moments of estimation errors are described by the covariance matrix, whose direct calculation is impractical when the number of degrees of freedom of the system state is large. Ensemble and reduced-state approaches to prediction and data assimilation replace full estimation error covariance matrices by low-rank approximations. The appropriateness of such approximations depends on the spectrum of the full error covariance matrix, whose calculation is also often impractical. Here we examine the situation where the error covariance is a linear transformation of a forcing error covariance. We use operator norms and adjoints to relate the appropriateness of low-rank representations to the conditioning of this transformation. The analysis is used to investigate low-rank representations of the steady-state response to random forcing of an idealized discrete-time dynamical system.

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

    PubMed Central

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

    2005-01-01

    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. PMID:16176585

  8. Supervised feature ranking using a genetic algorithm optimized artificial neural network.

    PubMed

    Lin, Thy-Hou; Chiu, Shih-Hau; Tsai, Keng-Chang

    2006-01-01

    A genetic algorithm optimized artificial neural network GNW has been designed to rank features for two diversified multivariate data sets. The dimensions of these data sets are 85x24 and 62x25 for 24 or 25 molecular descriptors being computed for 85 matrix metalloproteinase-1 inhibitors or 62 hepatitis C virus NS3 protease inhibitors, respectively. Each molecular descriptor computed is treated as a feature and input into an input layer node of the artificial neural network. To optimize the artificial neural network by the genetic algorithm, each interconnected weight between input and hidden or between hidden and output layer nodes is binary encoded as a 16 bits string in a chromosome, and the chromosome is evolved by crossover and mutation operations. Each input layer node and its associated weights of the trained GNW are systematically omitted once (the self-depleted weights), and the corresponding weight adjustments due to the omission are computed to keep the overall network behavior unchanged. The primary feature ranking index defined as the sum of self-depleted weights and the corresponding weight adjustments computed is found capable of separating good from bad features for some artificial data sets of known feature rankings tested. The final feature indexes used to rank the data sets are computed as a sum of the weighted frequency of each feature being ranked in a particular rank for each data set being partitioned into numerous clusters. The two data sets are also clustered by a standard K-means method and trained by a support vector machine (SVM) for feature ranking using the computed F-scores as feature ranking index. It is found that GNW outperforms the SVM method on three artificial as well as the matrix metalloproteinase-1 inhibitor data sets studied. A clear-cut separation of good from bad features is offered by the GNW but not by the SVM method for a feature pool of known feature ranking. PMID:16859292

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

    ERIC Educational Resources Information Center

    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…

  10. Nominal versus Attained Weights in Universitas 21 Ranking

    ERIC Educational Resources Information Center

    Soh, Kaycheng

    2014-01-01

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

  11. 5 CFR 451.304 - Payment of Rank Awards.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... Presidential Rank Awards § 451.304 Payment of Rank Awards. (a) Receipt of the Distinguished rank by an SES.... 5376 or 5382, or any award paid under 5 U.S.C. 5384. (b) Receipt of the Meritorious rank by an...

  12. 5 CFR 451.302 - Ranks for senior career employees.

    Code of Federal Regulations, 2014 CFR

    2014-01-01

    ... 5 Administrative Personnel 1 2014-01-01 2014-01-01 false Ranks for senior career employees. 451.302 Section 451.302 Administrative Personnel OFFICE OF PERSONNEL MANAGEMENT CIVIL SERVICE REGULATIONS AWARDS Presidential Rank Awards § 451.302 Ranks for senior career employees. (a) The circumstances under which the President may award the rank...

  13. Predicting accurate probabilities with a ranking loss

    PubMed Central

    Menon, Aditya Krishna; Jiang, Xiaoqian J; Vembu, Shankar; Elkan, Charles; Ohno-Machado, Lucila

    2013-01-01

    In many real-world applications of machine learning classifiers, it is essential to predict the probability of an example belonging to a particular class. This paper proposes a simple technique for predicting probabilities based on optimizing a ranking loss, followed by isotonic regression. This semi-parametric technique offers both good ranking and regression performance, and models a richer set of probability distributions than statistical workhorses such as logistic regression. We provide experimental results that show the effectiveness of this technique on real-world applications of probability prediction. PMID:25285328

  14. Preference Learning and Ranking by Pairwise Comparison

    NASA Astrophysics Data System (ADS)

    Fürnkranz, Johannes; Hüllermeier, Eyke

    This chapter provides an overview of recent work on preference learning and ranking via pairwise classification. The learning by pairwise comparison (LPC) paradigm is the natural machine learning counterpart to the relational approach to preference modeling and decision making. From a machine learning point of view, LPC is especially appealing as it decomposes a possibly complex prediction problem into a certain number of learning problems of the simplest type, namely binary classification. We explain how to approach different preference learning problems, such as label and instance ranking, within the framework of LPC. We primarily focus on methodological aspects, but also address theoretical questions as well as algorithmic and complexity issues.

  15. Ranking Silent Nodes in Information Networks: A Quantitative Approach and Applications

    NASA Astrophysics Data System (ADS)

    Interdonato, Roberto; Tagarelli, Andrea

    This paper overviews recent research findings concerning a new challenging problem in information networks, namely identifying and ranking silent nodes. We present three case studies which show how silent nodes' behavior maps to different situations in computer networks, online social networks, and online collaboration networks, and we discuss major benefits in identifying and ranking silent nodes in such networks. We also provide an overview of our proposed approach, which relies on a new eigenvector- centrality graph-based ranking method built on a silent-oriented network model.

  16. An Overview of Low-Rank Matrix Recovery From Incomplete Observations

    NASA Astrophysics Data System (ADS)

    Davenport, Mark A.; Romberg, Justin

    2016-06-01

    Low-rank matrices play a fundamental role in modeling and computational methods for signal processing and machine learning. In many applications where low-rank matrices arise, these matrices cannot be fully sampled or directly observed, and one encounters the problem of recovering the matrix given only incomplete and indirect observations. This paper provides an overview of modern techniques for exploiting low-rank structure to perform matrix recovery in these settings, providing a survey of recent advances in this rapidly-developing field. Specific attention is paid to the algorithms most commonly used in practice, the existing theoretical guarantees for these algorithms, and representative practical applications of these techniques.

  17. DrugE-Rank: improving drug–target interaction prediction of new candidate drugs or targets by ensemble learning to rank

    PubMed Central

    Yuan, Qingjun; Gao, Junning; Wu, Dongliang; Zhang, Shihua; Mamitsuka, Hiroshi; Zhu, Shanfeng

    2016-01-01

    Motivation: Identifying drug–target interactions is an important task in drug discovery. To reduce heavy time and financial cost in experimental way, many computational approaches have been proposed. Although these approaches have used many different principles, their performance is far from satisfactory, especially in predicting drug–target interactions of new candidate drugs or targets. Methods: Approaches based on machine learning for this problem can be divided into two types: feature-based and similarity-based methods. Learning to rank is the most powerful technique in the feature-based methods. Similarity-based methods are well accepted, due to their idea of connecting the chemical and genomic spaces, represented by drug and target similarities, respectively. We propose a new method, DrugE-Rank, to improve the prediction performance by nicely combining the advantages of the two different types of methods. That is, DrugE-Rank uses LTR, for which multiple well-known similarity-based methods can be used as components of ensemble learning. Results: The performance of DrugE-Rank is thoroughly examined by three main experiments using data from DrugBank: (i) cross-validation on FDA (US Food and Drug Administration) approved drugs before March 2014; (ii) independent test on FDA approved drugs after March 2014; and (iii) independent test on FDA experimental drugs. Experimental results show that DrugE-Rank outperforms competing methods significantly, especially achieving more than 30% improvement in Area under Prediction Recall curve for FDA approved new drugs and FDA experimental drugs. Availability: http://datamining-iip.fudan.edu.cn/service/DrugE-Rank Contact: zhusf@fudan.edu.cn Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27307615

  18. Review of rank-based procedures for multicenter clinical trials.

    PubMed

    Rashid, M Mushfiqur; McKean, Joseph W; Kloke, John D

    2013-01-01

    This article reviews nonparametric alternatives to the mixed model normal theory analysis for the analyses of multicenter clinical trials. Under a mixed model, the traditional analysis is based on maximum likelihood theory under normal errors. This analysis, though, is not robust to outliers. Robust, rank-based, Wilcoxon-type procedures are reviewed for a multicenter clinical trial for the mixed model but without the assumption of normality. These procedures retain the high efficiency of Wilcoxon methods for simple location problems and are based on a fitting criterion which is robust to outliers in response space. A simple weighting scheme can be employed so that the procedures are robust to outliers in factor (design) space as well as response space. These rank-based analyses offer a complete analysis, including estimation of fixed effects and their standard errors, and tests of linear hypotheses. Both rank-based estimates of contrasts and individual treatment effects are reviewed. We illustrate the analyses using real data from a clinical trial. PMID:24138428

  19. Rank-based algorithms for anlaysis of microarrays

    NASA Astrophysics Data System (ADS)

    Liu, Wei-min; Mei, Rui; Bartell, Daniel M.; Di, Xiaojun; Webster, Teresa A.; Ryder, Tom

    2001-06-01

    Analysis of microarray data often involves extracting information from raw intensities of spots of cells and making certain calls. Rank-based algorithms are powerful tools to provide probability values of hypothesis tests, especially when the distribution of the intensities is unknown. For our current gene expression arrays, a gene is detected by a set of probe pairs consisting of perfect match and mismatch cells. The one-sided upper-tail Wilcoxon's signed rank test is used in our algorithms for absolute calls (whether a gene is detected or not), as well as comparative calls (whether a gene is increasing or decreasing or no significant change in a sample compared with another sample). We also test the possibility to use only perfect match cells to make calls. This paper focuses on absolute calls. We have developed error analysis methods and software tools that allow us to compare the accuracy of the calls in the presence or absence of mismatch cells at different target concentrations. The usage of nonparametric rank-based tests is not limited to absolute and comparative calls of gene expression chips. They can also be applied to other oligonucleotide microarrays for genotyping and mutation detection, as well as spotted arrays.

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

    PubMed Central

    Geoffroy, Véronique; Pizot, Cécile; Redin, Claire; Piton, Amélie; Vasli, Nasim; Stoetzel, Corinne; Blavier, André; Laporte, Jocelyn

    2015-01-01

    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/. PMID:25780760

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

    PubMed

    Geoffroy, Véronique; Pizot, Cécile; Redin, Claire; Piton, Amélie; Vasli, Nasim; Stoetzel, Corinne; Blavier, André; Laporte, Jocelyn; Muller, Jean

    2015-01-01

    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/. PMID:25780760

  2. To Overcome HITS Rank Similarity Confliction of Web Pages using Weight Calculation and Rank Improvement

    NASA Astrophysics Data System (ADS)

    Nath, Rajender; Kumar, Naresh

    2011-12-01

    Search Engine gives an ordered list of web search results in response to a user query, wherein the important pages are usually displayed at the top with less important ones afterwards. It may be possible that the user may have to look for many screen results to get the required documents. In literatures, many page ranking algorithms has been given to find the page rank of a page. For example PageRank is considered in this work. This algorithm treats all the links equally when distributing rank scores. That's why this algorithm some time gives equal importance to all the pages. But in real this can not be happen because, if two pages have same rank then how we can judge which page is more important then other. So this paper proposes another idea to organize the search results and describe which page is more important when confliction of same rank is produced by the PageRank. So that the user can get more relevant and important results easily and in a short span of time.

  3. A Ranking Procedure by Incomplete Pairwise Comparisons Using Information Entropy and Dempster-Shafer Evidence Theory

    PubMed Central

    Pan, Dongbo; Lu, Xi; Liu, Juan; Deng, Yong

    2014-01-01

    Decision-making, as a way to discover the preference of ranking, has been used in various fields. However, owing to the uncertainty in group decision-making, how to rank alternatives by incomplete pairwise comparisons has become an open issue. In this paper, an improved method is proposed for ranking of alternatives by incomplete pairwise comparisons using Dempster-Shafer evidence theory and information entropy. Firstly, taking the probability assignment of the chosen preference into consideration, the comparison of alternatives to each group is addressed. Experiments verified that the information entropy of the data itself can determine the different weight of each group's choices objectively. Numerical examples in group decision-making environments are used to test the effectiveness of the proposed method. Moreover, the divergence of ranking mechanism is analyzed briefly in conclusion section. PMID:25250393

  4. A ranking procedure by incomplete pairwise comparisons using information entropy and Dempster-Shafer evidence theory.

    PubMed

    Pan, Dongbo; Lu, Xi; Liu, Juan; Deng, Yong

    2014-01-01

    Decision-making, as a way to discover the preference of ranking, has been used in various fields. However, owing to the uncertainty in group decision-making, how to rank alternatives by incomplete pairwise comparisons has become an open issue. In this paper, an improved method is proposed for ranking of alternatives by incomplete pairwise comparisons using Dempster-Shafer evidence theory and information entropy. Firstly, taking the probability assignment of the chosen preference into consideration, the comparison of alternatives to each group is addressed. Experiments verified that the information entropy of the data itself can determine the different weight of each group's choices objectively. Numerical examples in group decision-making environments are used to test the effectiveness of the proposed method. Moreover, the divergence of ranking mechanism is analyzed briefly in conclusion section. PMID:25250393

  5. Human Resource Managers Rank Their Pressure Points.

    ERIC Educational Resources Information Center

    Herring, Jack

    1983-01-01

    A survey of 700 top-level human resource executives that elicited 309 responses revealed the highest priority ranking of 24 human resource issues to be: productivity improvement, controlling costs of employee benefits, compensation planning and administration, employee communications, upgrading management training development programs,…

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

    ERIC Educational Resources Information Center

    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…

  7. Kinesiology Faculty Citations across Academic Rank

    ERIC Educational Resources Information Center

    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…

  8. Alternative Class Ranks Using Z-Scores

    ERIC Educational Resources Information Center

    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…

  9. Deep impact: unintended consequences of journal rank

    PubMed Central

    Brembs, Björn; Button, Katherine; Munafò, Marcus

    2013-01-01

    Most researchers acknowledge an intrinsic hierarchy in the scholarly journals (“journal rank”) that they submit their work to, and adjust not only their submission but also their reading strategies accordingly. On the other hand, much has been written about the negative effects of institutionalizing journal rank as an impact measure. So far, contributions to the debate concerning the limitations of journal rank as a scientific impact assessment tool have either lacked data, or relied on only a few studies. In this review, we present the most recent and pertinent data on the consequences of our current scholarly communication system with respect to various measures of scientific quality (such as utility/citations, methodological soundness, expert ratings or retractions). These data corroborate previous hypotheses: 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 altogether, in favor of a library-based scholarly communication system, will ultimately be necessary. This new system will use modern information technology to vastly improve the filter, sort and discovery functions of the current journal system. PMID:23805088

  10. Spanish Universities and the "Ranking 2005" Initiative

    ERIC Educational Resources Information Center

    De Miguel, Jesus M.; Vaquera, Elizabeth; Sanchez, Jara D.

    2005-01-01

    This article assesses the quality of the Spanish higher education system, focusing mainly on the methodological challenges that the existence of public and private universities represents in the calculation of global higher education rankings. Researchers from the University of Barcelona and the University of Pennsylvania calculated the first…

  11. Efficiently Ranking Hyphotheses in Machine Learning

    NASA Technical Reports Server (NTRS)

    Chien, Steve

    1997-01-01

    This paper considers the problem of learning the ranking of a set of alternatives based upon incomplete information (e.g. a limited number of observations). At each decision cycle, the system can output a complete ordering on the hypotheses or decide to gather additional information (e.g. observation) at some cost.

  12. An Application of Sylvester's Rank Inequality

    ERIC Educational Resources Information Center

    Kung, Sidney H.

    2011-01-01

    Using two well known criteria for the diagonalizability of a square matrix plus an extended form of Sylvester's Rank Inequality, the author presents a new condition for the diagonalization of a real matrix from which one can obtain the eigenvectors by simply multiplying some associated matrices without solving a linear system of simultaneous…

  13. Ranks, Rates, and Numbers--and Confusion

    ERIC Educational Resources Information Center

    Bracey, Gerald W.

    2008-01-01

    The United States may be the most rank-crazy country in the world, but the world is catching up. The author cites the Organization for Economic and Cooperating and Development (OECD). When the International Association for the Evaluation of Educational Achievement (IEA) started its international studies--the First International Mathematics Study…

  14. Ranking Workplace Competencies: Student and Graduate Perceptions.

    ERIC Educational Resources Information Center

    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…

  15. Low-rank coal oil agglomeration

    DOEpatents

    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.

  16. Suppression pheromone and cockroach rank formation

    NASA Astrophysics Data System (ADS)

    Kou, Rong; Chang, Huan-Wen; Chen, Shu-Chun; Ho, Hsiao-Yung

    2009-06-01

    Although agonistic behaviors in the male lobster cockroach ( Nauphoeta cinerea) are well known, the formation of an unstable hierarchy has long been a puzzle. In this study, we investigate how the unstable dominance hierarchy in N. cinerea is maintained via a pheromone signaling system. In agonistic interactions, aggressive posture (AP) is an important behavioral index of aggression. This study showed that, during the formation of a governing hierarchy, thousands of nanograms of 3-hydroxy-2-butanone (3H-2B) were released by the AP-adopting dominant in the first encounter fight, then during the early domination period and that this release of 3H-2B was related to rank maintenance, but not to rank establishment. For rank maintenance, 3H-2B functioned as a suppression pheromone, which suppressed the fighting capability of rivals and kept them in a submissive state. During the period of rank maintenance, as the dominant male gradually decreased his 3H-2B release, the fighting ability of the subordinate gradually developed, as shown by the increasing odds of a subordinate adopting an AP (OSAP). The OSAP was negatively correlated with the amount of 3H-2B released by the dominant and positively correlated with the number of domination days. The same OSAP could be achieved earlier by reducing the amount of 3H-2B released by the dominant indicates that whether the subordinate adopts an offensive strategy depends on what the dominant is doing.

  17. Partial transfer entropy on rank vectors

    NASA Astrophysics Data System (ADS)

    Kugiumtzis, D.

    2013-06-01

    For the evaluation of information flow in bivariate time series, information measures have been employed, such as the transfer entropy (TE), the symbolic transfer entropy (STE), defined similarly to TE but on the ranks of the components of the reconstructed vectors, and the transfer entropy on rank vectors (TERV), similar to STE but forming the ranks for the future samples of the response system with regard to the current reconstructed vector. Here we extend TERV for multivariate time series, and account for the presence of confounding variables, called partial transfer entropy on ranks (PTERV). We investigate the asymptotic properties of PTERV, and also partial STE (PSTE), construct parametric significance tests under approximations with Gaussian and gamma null distributions, and show that the parametric tests cannot achieve the power of the randomization test using time-shifted surrogates. Using simulations on known coupled dynamical systems and applying parametric and randomization significance tests, we show that PTERV performs better than PSTE but worse than the partial transfer entropy (PTE). However, PTERV, unlike PTE, is robust to the presence of drifts in the time series and it is also not affected by the level of detrending.

  18. Subject Gateway Sites and Search Engine Ranking.

    ERIC Educational Resources Information Center

    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)

  19. World University Ranking Methodologies: Stability and Variability

    ERIC Educational Resources Information Center

    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 approaches used.…

  20. Chapel Hill, Berkeley Head Graduate Rankings.

    ERIC Educational Resources Information Center

    Chemical and Engineering News, 1983

    1983-01-01

    Provides lists ranking the 25 largest producers of bachelor's, certified bachelor's, master's, and doctoral graduates in chemistry. University of North Carolina (Chapel Hill) is the nation's largest producer of bachelor's degree chemistry graduates while the University of California (Berkeley) is the largest producer of Ph.D. chemistry graduates.…

  1. Applying Technology Ranking and Systems Engineering in Advanced Life Support

    NASA Technical Reports Server (NTRS)

    Jones, Harry; Luna, Bernadette (Technical Monitor)

    2000-01-01

    According to the Advanced Life Support (ALS) Program Plan, the Systems Modeling and Analysis Project (SMAP) has two important tasks: 1) prioritizing investments in ALS Research and Technology Development (R&TD), and 2) guiding the evolution of ALS systems. Investments could be prioritized simply by independently ranking different technologies, but we should also consider a technology's impact on system design. Guiding future ALS systems will require SMAP to consider many aspects of systems engineering. R&TD investments can be prioritized using familiar methods for ranking technology. The first step is gathering data on technology performance, safety, readiness level, and cost. Then the technologies are ranked using metrics or by decision analysis using net present economic value. The R&TD portfolio can be optimized to provide the maximum expected payoff in the face of uncertain future events. But more is needed. The optimum ALS system can not be designed simply by selecting the best technology for each predefined subsystem. Incorporating a new technology, such as food plants, can change the specifications of other subsystems, such as air regeneration. Systems must be designed top-down starting from system objectives, not bottom-up from selected technologies. The familiar top-down systems engineering process includes defining mission objectives, mission design, system specification, technology analysis, preliminary design, and detail design. Technology selection is only one part of systems analysis and engineering, and it is strongly related to the subsystem definitions. ALS systems should be designed using top-down systems engineering. R&TD technology selection should consider how the technology affects ALS system design. Technology ranking is useful but it is only a small part of systems engineering.

  2. Enhanced low-rank + sparsity decomposition for speckle reduction in optical coherence tomography

    NASA Astrophysics Data System (ADS)

    Kopriva, Ivica; Shi, Fei; Chen, Xinjian

    2016-07-01

    Speckle artifacts can strongly hamper quantitative analysis of optical coherence tomography (OCT), which is necessary to provide assessment of ocular disorders associated with vision loss. Here, we introduce a method for speckle reduction, which leverages from low-rank + sparsity decomposition (LRpSD) of the logarithm of intensity OCT images. In particular, we combine nonconvex regularization-based low-rank approximation of an original OCT image with a sparsity term that incorporates the speckle. State-of-the-art methods for LRpSD require a priori knowledge of a rank and approximate it with nuclear norm, which is not an accurate rank indicator. As opposed to that, the proposed method provides more accurate approximation of a rank through the use of nonconvex regularization that induces sparse approximation of singular values. Furthermore, a rank value is not required to be known a priori. This, in turn, yields an automatic and computationally more efficient method for speckle reduction, which yields the OCT image with improved contrast-to-noise ratio, contrast and edge fidelity. The source code will be available at www.mipav.net/English/research/research.html.

  3. Optimal Ranking Regime analysis of TreeFlow dendrohydrological reconstructions

    NASA Astrophysics Data System (ADS)

    Mauget, S. A.

    2015-03-01

    The Optimal Ranking Regime (ORR) method was used to identify 6-100 year time windows containing significant ranking sequences in 55 western US streamflow reconstructions, and reconstructions of the level of the Great Salt Lake and San Francisco Bay salinity during 1500-2007. The method's ability to identify optimally significant and non-overlapping runs of low and high rankings allows it to re-express a reconstruction time series as a simplified sequence of regime segments marking intra- to multi-decadal (IMD) periods of low or high streamflow, lake level, or salinity. Those ORR sequences, referred to here as Z lines, can be plotted to identify consistent regime patterns in the analysis of numerous reconstructions. The Z lines for the 57 reconstructions evaluated here show a common pattern of IMD cycles of drought and pluvial periods during the late 16th and 17th centuries, a relatively dormant period during the 18th century, and the reappearance of alternating dry and wet IMD periods during the 19th and early 20th centuries. Although this pattern suggests the possibility of similarly active and inactive oceanic modes in the North Pacific and North Atlantic, such centennial-scale patterns are not evident in the ORR analyses of reconstructed Pacific Decadal Oscillation (PDO), El Niño-Southern Oscillation, and North Atlantic seas-surface temperature variation. But given the inconsistency in the analyses of four PDO reconstructions the possible role of centennial-scale oceanic mechanisms is uncertain. In future research the ORR method might be applied to climate reconstructions around the Pacific Basin to try to resolve this uncertainty. Given its ability to compare regime patterns in climate reconstructions derived using different methods and proxies, the method may also be used in future research to evaluate long-term regional temperature reconstructions.

  4. Optimal ranking regime analysis of TreeFlow dendrohydrological reconstructions

    NASA Astrophysics Data System (ADS)

    Mauget, S. A.

    2015-08-01

    The optimal ranking regime (ORR) method was used to identify 6-100-year time windows containing significant ranking sequences in 55 western US streamflow reconstructions, and reconstructions of the level of the Great Salt Lake and San Francisco Bay salinity during 1500-2007. The method's ability to identify optimally significant and non-overlapping runs of low- and high-rankings allows it to re-express a reconstruction time series as a simplified sequence of regime segments marking intra- to multi-decadal (IMD) periods of low or high streamflow, lake level, and salinity. Those ORR sequences, referred to here as Z-lines, can be plotted to identify consistent regime patterns in the analysis of numerous reconstructions. The Z-lines for the 57 reconstructions evaluated here show a common pattern of IMD cycles of drought and pluvial periods during the late 16th and 17th centuries, a relatively dormant period during the 18th century, and the reappearance of alternating dry and wet IMD periods during the 19th and early 20th centuries. Although this pattern suggests the possibility of similarly active and inactive oceanic modes in the North Pacific and North Atlantic, such centennial-scale patterns are not evident in the ORR analyses of reconstructed Pacific Decadal Oscillation (PDO), El Niño-Southern Oscillation, and North Atlantic sea-surface temperature variation. However, given the inconsistency in the analyses of four PDO reconstructions, the possible role of centennial-scale oceanic mechanisms is uncertain. In future research the ORR method might be applied to climate reconstructions around the Pacific Basin to try to resolve this uncertainty. Given its ability to compare regime patterns in climate reconstructions derived using different methods and proxies, the method may also be used in future research to evaluate long-term regional temperature reconstructions.

  5. Salient Band Selection for Hyperspectral Image Classification via Manifold Ranking.

    PubMed

    Wang, Qi; Lin, Jianzhe; Yuan, Yuan

    2016-06-01

    Saliency detection has been a hot topic in recent years, and many efforts have been devoted in this area. Unfortunately, the results of saliency detection can hardly be utilized in general applications. The primary reason, we think, is unspecific definition of salient objects, which makes that the previously published methods cannot extend to practical applications. To solve this problem, we claim that saliency should be defined in a context and the salient band selection in hyperspectral image (HSI) is introduced as an example. Unfortunately, the traditional salient band selection methods suffer from the problem of inappropriate measurement of band difference. To tackle this problem, we propose to eliminate the drawbacks of traditional salient band selection methods by manifold ranking. It puts the band vectors in the more accurate manifold space and treats the saliency problem from a novel ranking perspective, which is considered to be the main contributions of this paper. To justify the effectiveness of the proposed method, experiments are conducted on three HSIs, and our method is compared with the six existing competitors. Results show that the proposed method is very effective and can achieve the best performance among the competitors. PMID:27008675

  6. Modified Hazard Ranking System/Hazard Ranking System for sites with mixed radioactive and hazardous wastes: Software documentation

    SciTech Connect

    Stenner, R.D.; Peloquin, R.A.; Hawley, K.A.

    1986-11-01

    The mHRS/HRS software package was developed by the Pacific Northwest Laboratory (PNL) under contract with the Department of Energy (DOE) to provide a uniform method for DOE facilities to use in performing their Conservation Environmental Response Compensation and Liability Act (CERCLA) Phase I Modified Hazard Ranking System or Hazard Ranking System evaluations. The program is designed to remove the tedium and potential for error associated with the performing of hand calculations and the interpreting of information on tables and in reference books when performing an evaluation. The software package is designed to operate on a microcomputer (IBM PC, PC/XT, or PC/AT, or a compatible system) using either a dual floppy disk drive or a hard disk storage system. It is written in the dBASE III language and operates using the dBASE III system. Although the mHRS/HRS software package was developed for use at DOE facilities, it has direct applicability to the performing of CERCLA Phase I evaluations for any facility contaminated by hazardous waste. The software can perform evaluations using either the modified hazard ranking system methodology developed by DOE/PNL, the hazard ranking system methodology developed by EPA/MITRE Corp., or a combination of the two. This document is a companion manual to the mHRS/HRS user manual. It is intended for the programmer who must maintain the software package and for those interested in the computer implementation. This manual documents the system logic, computer programs, and data files that comprise the package. Hardware and software implementation requirements are discussed. In addition, hand calculations of three sample situations (problems) with associated computer runs used for the verification of program calculations are included.

  7. Mining User Dwell Time for Personalized Web Search Re-Ranking

    SciTech Connect

    Xu, Songhua; Jiang, Hao; Lau, Francis

    2011-01-01

    We propose a personalized re-ranking algorithm through mining user dwell times derived from a user's previously online reading or browsing activities. We acquire document level user dwell times via a customized web browser, from which we then infer conceptword level user dwell times in order to understand a user's personal interest. According to the estimated concept word level user dwell times, our algorithm can estimate a user's potential dwell time over a new document, based on which personalized webpage re-ranking can be carried out. We compare the rankings produced by our algorithm with rankings generated by popular commercial search engines and a recently proposed personalized ranking algorithm. The results clearly show the superiority of our method. In this paper, we propose a new personalized webpage ranking algorithmthrough mining dwell times of a user. We introduce a quantitative model to derive concept word level user dwell times from the observed document level user dwell times. Once we have inferred a user's interest over the set of concept words the user has encountered in previous readings, we can then predict the user's potential dwell time over a new document. Such predicted user dwell time allows us to carry out personalized webpage re-ranking. To explore the effectiveness of our algorithm, we measured the performance of our algorithm under two conditions - one with a relatively limited amount of user dwell time data and the other with a doubled amount. Both evaluation cases put our algorithm for generating personalized webpage rankings to satisfy a user's personal preference ahead of those by Google, Yahoo!, and Bing, as well as a recent personalized webpage ranking algorithm.

  8. Is the 90th Percentile Adequate? The Optimal Waist Circumference Cutoff Points for Predicting Cardiovascular Risks in 124,643 15-Year-Old Taiwanese Adolescents

    PubMed Central

    Ho, ChinYu; Chen, Hsin-Jen; Huang, Nicole; Yeh, Jade Chienyu; deFerranti, Sarah

    2016-01-01

    Adolescent obesity has increased to alarming proportions globally. However, few studies have investigated the optimal waist circumference (WC) of Asian adolescents. This study sought to establish the optimal WC cutoff points that identify a cluster of cardiovascular risk factors (CVRFs) among 15-year-old ethnically Chinese adolescents. This study was a regional population-based study on the CVRFs among adolescents who enrolled in all the senior high schools in Taipei City, Taiwan, between 2011 and 2014. Four cross-sectional health examinations of first-year senior high school (grade 10) students were conducted from September to December of each year. A total of 124,643 adolescents aged 15 (boys: 63,654; girls: 60,989) were recruited. Participants who had at least three of five CVRFs were classified as the high-risk group. We used receiver-operating characteristic curves and the area under the curve (AUC) to determine the optimal WC cutoff points and the accuracy of WC in predicting high cardiovascular risk. WC was a good predictor for high cardiovascular risk for both boys (AUC: 0.845, 95% confidence interval [CI]: 0.833–0.857) and girls (AUC: 0.763, 95% CI: 0.731–0.795). The optimal WC cutoff points were ≥78.9 cm for boys (77th percentile) and ≥70.7 cm for girls (77th percentile). Adolescents with normal weight and an abnormal WC were more likely to be in the high cardiovascular risk group (odds ratio: 3.70, 95% CI: 2.65–5.17) compared to their peers with normal weight and normal WC. The optimal WC cutoff point of 15-year-old Taiwanese adolescents for identifying CVRFs should be the 77th percentile; the 90th percentile of the WC might be inadequate. The high WC criteria can help health professionals identify higher proportion of the adolescents with cardiovascular risks and refer them for further evaluations and interventions. Adolescents’ height, weight and WC should be measured as a standard practice in routine health checkups. PMID:27389572

  9. Is the 90th Percentile Adequate? The Optimal Waist Circumference Cutoff Points for Predicting Cardiovascular Risks in 124,643 15-Year-Old Taiwanese Adolescents.

    PubMed

    Lee, Jason Jiunshiou; Ho, ChinYu; Chen, Hsin-Jen; Huang, Nicole; Yeh, Jade Chienyu; deFerranti, Sarah

    2016-01-01

    Adolescent obesity has increased to alarming proportions globally. However, few studies have investigated the optimal waist circumference (WC) of Asian adolescents. This study sought to establish the optimal WC cutoff points that identify a cluster of cardiovascular risk factors (CVRFs) among 15-year-old ethnically Chinese adolescents. This study was a regional population-based study on the CVRFs among adolescents who enrolled in all the senior high schools in Taipei City, Taiwan, between 2011 and 2014. Four cross-sectional health examinations of first-year senior high school (grade 10) students were conducted from September to December of each year. A total of 124,643 adolescents aged 15 (boys: 63,654; girls: 60,989) were recruited. Participants who had at least three of five CVRFs were classified as the high-risk group. We used receiver-operating characteristic curves and the area under the curve (AUC) to determine the optimal WC cutoff points and the accuracy of WC in predicting high cardiovascular risk. WC was a good predictor for high cardiovascular risk for both boys (AUC: 0.845, 95% confidence interval [CI]: 0.833-0.857) and girls (AUC: 0.763, 95% CI: 0.731-0.795). The optimal WC cutoff points were ≥78.9 cm for boys (77th percentile) and ≥70.7 cm for girls (77th percentile). Adolescents with normal weight and an abnormal WC were more likely to be in the high cardiovascular risk group (odds ratio: 3.70, 95% CI: 2.65-5.17) compared to their peers with normal weight and normal WC. The optimal WC cutoff point of 15-year-old Taiwanese adolescents for identifying CVRFs should be the 77th percentile; the 90th percentile of the WC might be inadequate. The high WC criteria can help health professionals identify higher proportion of the adolescents with cardiovascular risks and refer them for further evaluations and interventions. Adolescents' height, weight and WC should be measured as a standard practice in routine health checkups. PMID:27389572

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

    PubMed Central

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

    2014-01-01

    Objectives Many studies based on microRNA (miRNA) expression profiles showed a new aspect of cancer classification. Because one characteristic of miRNA expression data is the high dimensionality, feature selection methods have been used to facilitate dimensionality reduction. The feature selection methods have one shortcoming thus far: they just consider the problem of where feature to class is 1:1 or n:1. However, because one miRNA may influence more than one type of cancer, human miRNA is considered to be ranked low in traditional feature selection methods and are removed most of the time. In view of the limitation of the miRNA number, low-ranking miRNAs are also important to cancer classification. Methods We considered both high- and low-ranking features to cover all problems (1:1, n:1, 1:n, and m:n) in cancer classification. First, we used the correlation-based feature selection method to select the high-ranking miRNAs, and chose the support vector machine, Bayes network, decision tree, k-nearest-neighbor, and logistic classifier to construct cancer classification. Then, we chose Chi-square test, information gain, gain ratio, and Pearson's correlation feature selection methods to build the m:n feature subset, and used the selected miRNAs to determine cancer classification. Results The low-ranking miRNA expression profiles achieved higher classification accuracy compared with just using high-ranking miRNAs in traditional feature selection methods. Conclusion Our results demonstrate that the m:n feature subset made a positive impression of low-ranking miRNAs in cancer classification. PMID:25389514

  11. Combining partially ranked data in plant breeding and biology: I. Rank aggregating methods.

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Combining heterogeneous data from plant breeding trials into a single dataset can be challenging, especially if observations have been performed only on partially overlapping sets of accessions, or if evaluations were done with different rating scales. In the present work we propose combining such d...

  12. SU (n) symmetry breaking by rank three and rank two antisymmetric tensor scalars

    NASA Astrophysics Data System (ADS)

    Adler, Stephen L.

    2015-05-01

    We study SU (n) symmetry breaking by rank three and rank two antisymmetric tensor fields. Using tensor analysis, we derive branching rules for the adjoint and antisymmetric tensor representations, and explain why for general SU (n) one finds the same U (1) generator mismatch that we noted earlier in special cases. We then compute the masses of the various scalar fields in the branching expansion, in terms of parameters of the general renormalizable potential for the antisymmetric tensor fields.

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

    ERIC Educational Resources Information Center

    Nagasinghe, Iranga

    2010-01-01

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

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

    ERIC Educational Resources Information Center

    Hou, Mingjun; Fan, Peihua; Liu, Heng

    2014-01-01

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

  15. Adaptive low-rank approximation and denoised Monte Carlo approach for high-dimensional Lindblad equations

    NASA Astrophysics Data System (ADS)

    Le Bris, C.; Rouchon, P.; Roussel, J.

    2015-12-01

    We present a twofold contribution to the numerical simulation of Lindblad equations. First, an adaptive numerical approach to approximate Lindblad equations using low-rank dynamics is described: a deterministic low-rank approximation of the density operator is computed, and its rank is adjusted dynamically, using an on-the-fly estimator of the error committed when reducing the dimension. On the other hand, when the intrinsic dimension of the Lindblad equation is too high to allow for such a deterministic approximation, we combine classical ensemble averages of quantum Monte Carlo trajectories and a denoising technique. Specifically, a variance reduction method based on the consideration of a low-rank dynamics as a control variate is developed. Numerical tests for quantum collapse and revivals show the efficiency of each approach, along with the complementarity of the two approaches.

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

    PubMed Central

    Hudmon, Karen Suchanek; Sowinski, Kevin M.; Corelli, Robin L.

    2016-01-01

    Objective. To characterize the educational background and academic rank of faculty members in US schools of pharmacy, estimate the extent to which they are employed by institutions where they received previous training, and determine whether differences in degree origin and rank exist between faculty members in established (≤1995) vs newer programs. Methods. A cross-sectional study was conducted using the American Association of Colleges of Pharmacy (AACP) faculty database and demographic information from the public domain. Results. Among 5516 faculty members, 50.3% held two or more types of degrees. Established schools had a higher median number of faculty members and a higher mean faculty rank than did newer schools. Conclusion. The difference in mean faculty rank highlights the shortage of experienced faculty members in newer schools. Future research efforts should investigate educational attainment in correlation to other faculty and school characteristics and prospectively track and report trends related to pharmacy faculty members composition. PMID:27293228

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

    PubMed

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

    2016-05-25

    Objective. To characterize the educational background and academic rank of faculty members in US schools of pharmacy, estimate the extent to which they are employed by institutions where they received previous training, and determine whether differences in degree origin and rank exist between faculty members in established (≤1995) vs newer programs. Methods. A cross-sectional study was conducted using the American Association of Colleges of Pharmacy (AACP) faculty database and demographic information from the public domain. Results. Among 5516 faculty members, 50.3% held two or more types of degrees. Established schools had a higher median number of faculty members and a higher mean faculty rank than did newer schools. Conclusion. The difference in mean faculty rank highlights the shortage of experienced faculty members in newer schools. Future research efforts should investigate educational attainment in correlation to other faculty and school characteristics and prospectively track and report trends related to pharmacy faculty members composition. PMID:27293228

  18. Evaluation of the adequacy of interval model of control systems ranked configurations

    NASA Astrophysics Data System (ADS)

    Wójcik, Waldemar; Bykov, Mykola M.; Raimy, A.; Yesmakhanova, Laura; Smailova, Saule

    2015-12-01

    The paper describes a new approach to presenting of the information about the control system states and processing of this information for the control decision-making. The ranks between distances of system states but not these distances are important information for implementation of procedures to identifying states and optimization of the system in this approach. The concept of rank configurations and special binary codes for their encoding are introduced. Different models of ranked configurations for defining the characteristics of these codes are presented. The interval model of ranked configurations to determine the completeness of such codes and a method and algorithm for evaluation of its adequacy are designed. The results of the algorithm performance are presented.

  19. Rank-dependant factorization of entanglement evolution

    NASA Astrophysics Data System (ADS)

    Siomau, Michael

    2016-05-01

    The description of the entanglement evolution of a complex quantum system can be significantly simplified due to the symmetries of the initial state and the quantum channels, which simultaneously affect parts of the system. Using concurrence as the entanglement measure, we study the entanglement evolution of few qubit systems, when each of the qubits is affected by a local unital channel independently on the others. We found that for low-rank density matrices of the final quantum state, such complex entanglement dynamics can be completely described by a combination of independent factors representing the evolution of entanglement of the initial state, when just one of the qubits is affected by a local channel. We suggest necessary conditions for the rank of the density matrices to represent the entanglement evolution through the factors. Our finding is supported with analytical examples and numerical simulations.

  20. National rankings as a means of evaluating medical school library programs: a comparative study.

    PubMed

    Matheson, N W; Grefsheim, S F

    1981-07-01

    A comparative study was undertaken to assess the reasons for the low rankings received by George Washington University Medical Center library in the Annual Statistics for Medical School Libraries in the United States and Canada. Although internal studies showed the library was successfully satisfying user needs and meeting its primary objectives, the rankings, which include the traditional measures of quality used by accrediting bodies, indicated the contrary. Three hypotheses were postulated to account for the discrepancy. In a matched group of similar libraries: (1) the rankings of an individual library would differ from the national rankings; (2) clustering the variables would change the rankings; and (3) libraries with similar staff size would tend to rank in the same quartile in service and resource variables. All hypotheses were invalidated. Further tests led to the conclusion that the Annual Statistics and other traditional measures of quality are inappropriate and inaccurate methods for evaluating library programs, since they only measure resource allocations and not the effectiveness of those allocations. Alternative evaluation methods are suggested. PMID:7248592

  1. A fast rank-reduction algorithm for three-dimensional seismic data interpolation

    NASA Astrophysics Data System (ADS)

    Jia, Yongna; Yu, Siwei; Liu, Lina; Ma, Jianwei

    2016-09-01

    Rank-reduction methods have been successfully used for seismic data interpolation and noise attenuation. However, highly intense computation is required for singular value decomposition (SVD) in most rank-reduction methods. In this paper, we propose a simple yet efficient interpolation algorithm, which is based on the Hankel matrix, for randomly missing traces. Following the multichannel singular spectrum analysis (MSSA) technique, we first transform the seismic data into a low-rank block Hankel matrix for each frequency slice. Then, a fast orthogonal rank-one matrix pursuit (OR1MP) algorithm is employed to minimize the low-rank constraint of the block Hankel matrix. In the new algorithm, only the left and right top singular vectors are needed to be computed, thereby, avoiding the complexity of computation required for SVD. Thus, we improve the calculation efficiency significantly. Finally, we anti-average the rank-reduction block Hankel matrix and obtain the reconstructed data in the frequency domain. Numerical experiments on 3D seismic data show that the proposed interpolation algorithm provides much better performance than the traditional MSSA algorithm in computational speed, especially for large-scale data processing.

  2. Retraction policies of top scientific journals ranked by impact factor

    PubMed Central

    Resnik, David B.; Wager, Elizabeth; Kissling, Grace E.

    2015-01-01

    Objective This study gathered information about the retraction policies of the top 200 scientific journals, ranked by impact factor. Methods Editors of the top 200 science journals for the year 2012 were contacted by email. Results One hundred forty-seven journals (74%) responded to a request for information. Of these, 95 (65%) had a retraction policy. Of journals with a retraction policy, 94% had a policy that allows the editors to retract articles without authors’ consent. Conclusions The majority of journals in this sample had a retraction policy, and almost all of them would retract an article without the authors’ permission. PMID:26213505

  3. Denoising of hyperspectral images by best multilinear rank approximation of a tensor

    NASA Astrophysics Data System (ADS)

    Marin-McGee, Maider; Velez-Reyes, Miguel

    2010-04-01

    The hyperspectral image cube can be modeled as a three dimensional array. Tensors and the tools of multilinear algebra provide a natural framework to deal with this type of mathematical object. Singular value decomposition (SVD) and its variants have been used by the HSI community for denoising of hyperspectral imagery. Denoising of HSI using SVD is achieved by finding a low rank approximation of a matrix representation of the hyperspectral image cube. This paper investigates similar concepts in hyperspectral denoising by using a low multilinear rank approximation the given HSI tensor representation. The Best Multilinear Rank Approximation (BMRA) of a given tensor A is to find a lower multilinear rank tensor B that is as close as possible to A in the Frobenius norm. Different numerical methods to compute the BMRA using Alternating Least Square (ALS) method and Newton's Methods over product of Grassmann manifolds are presented. The effect of the multilinear rank, the numerical method used to compute the BMRA, and different parameter choices in those methods are studied. Results show that comparable results are achievable with both ALS and Newton type methods. Also, classification results using the filtered tensor are better than those obtained either with denoising using SVD or MNF.

  4. RANK-RANKL signalling in cancer.

    PubMed

    Renema, Nathalie; Navet, Benjamin; Heymann, Marie-Françoise; Lezot, Frédéric; Heymann, Dominique

    2016-08-01

    Oncogenic events combined with a favourable environment are the two main factors in the oncological process. The tumour microenvironment is composed of a complex, interconnected network of protagonists, including soluble factors such as cytokines, extracellular matrix components, interacting with fibroblasts, endothelial cells, immune cells and various specific cell types depending on the location of the cancer cells (e.g. pulmonary epithelium, osteoblasts). This diversity defines specific "niches" (e.g. vascular, immune, bone niches) involved in tumour growth and the metastatic process. These actors communicate together by direct intercellular communications and/or in an autocrine/paracrine/endocrine manner involving cytokines and growth factors. Among these glycoproteins, RANKL (receptor activator nuclear factor-κB ligand) and its receptor RANK (receptor activator nuclear factor), members of the TNF and TNFR superfamilies, have stimulated the interest of the scientific community. RANK is frequently expressed by cancer cells in contrast with RANKL which is frequently detected in the tumour microenvironment and together they participate in every step in cancer development. Their activities are markedly regulated by osteoprotegerin (OPG, a soluble decoy receptor) and its ligands, and by LGR4, a membrane receptor able to bind RANKL. The aim of the present review is to provide an overview of the functional implication of the RANK/RANKL system in cancer development, and to underline the most recent clinical studies. PMID:27279652

  5. Rank-frequency relation for Chinese characters

    NASA Astrophysics Data System (ADS)

    Deng, Weibing; Allahverdyan, Armen E.; Li, Bo; Wang, Qiuping A.

    2014-02-01

    We show that the Zipf's law for Chinese characters perfectly holds for sufficiently short texts (few thousand different characters). The scenario of its validity is similar to the Zipf's law for words in short English texts. For long Chinese texts (or for mixtures of short Chinese texts), rank-frequency relations for Chinese characters display a two-layer, hierarchic structure that combines a Zipfian power-law regime for frequent characters (first layer) with an exponential-like regime for less frequent characters (second layer). For these two layers we provide different (though related) theoretical descriptions that include the range of low-frequency characters (hapax legomena). We suggest that this hierarchic structure of the rank-frequency relation connects to semantic features of Chinese characters (number of different meanings and homographies). The comparative analysis of rank-frequency relations for Chinese characters versus English words illustrates the extent to which the characters play for Chinese writers the same role as the words for those writing within alphabetical systems.

  6. [Ranke and modern surgery in Groningen].

    PubMed

    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. PMID:23171562

  7. Sorting protein decoys by machine-learning-to-rank

    PubMed Central

    Jing, Xiaoyang; Wang, Kai; Lu, Ruqian; Dong, Qiwen

    2016-01-01

    Much progress has been made in Protein structure prediction during the last few decades. As the predicted models can span a broad range of accuracy spectrum, the accuracy of quality estimation becomes one of the key elements of successful protein structure prediction. Over the past years, a number of methods have been developed to address this issue, and these methods could be roughly divided into three categories: the single-model methods, clustering-based methods and quasi single-model methods. In this study, we develop a single-model method MQAPRank based on the learning-to-rank algorithm firstly, and then implement a quasi single-model method Quasi-MQAPRank. The proposed methods are benchmarked on the 3DRobot and CASP11 dataset. The five-fold cross-validation on the 3DRobot dataset shows the proposed single model method outperforms other methods whose outputs are taken as features of the proposed method, and the quasi single-model method can further enhance the performance. On the CASP11 dataset, the proposed methods also perform well compared with other leading methods in corresponding categories. In particular, the Quasi-MQAPRank method achieves a considerable performance on the CASP11 Best150 dataset. PMID:27530967

  8. Sorting protein decoys by machine-learning-to-rank.

    PubMed

    Jing, Xiaoyang; Wang, Kai; Lu, Ruqian; Dong, Qiwen

    2016-01-01

    Much progress has been made in Protein structure prediction during the last few decades. As the predicted models can span a broad range of accuracy spectrum, the accuracy of quality estimation becomes one of the key elements of successful protein structure prediction. Over the past years, a number of methods have been developed to address this issue, and these methods could be roughly divided into three categories: the single-model methods, clustering-based methods and quasi single-model methods. In this study, we develop a single-model method MQAPRank based on the learning-to-rank algorithm firstly, and then implement a quasi single-model method Quasi-MQAPRank. The proposed methods are benchmarked on the 3DRobot and CASP11 dataset. The five-fold cross-validation on the 3DRobot dataset shows the proposed single model method outperforms other methods whose outputs are taken as features of the proposed method, and the quasi single-model method can further enhance the performance. On the CASP11 dataset, the proposed methods also perform well compared with other leading methods in corresponding categories. In particular, the Quasi-MQAPRank method achieves a considerable performance on the CASP11 Best150 dataset. PMID:27530967

  9. Automatic Ranked Output from Boolean Searches in SIRE

    ERIC Educational Resources Information Center

    Noreault, Terry; And Others

    1977-01-01

    This study examined the effectiveness using an automatic algorithm to rank the results of Boolean searches of an inverted file design document retrieval system. Relevant documents were ranked significantly higher than nonrelevant documents on output lists. (Author/KP)

  10. Technical Innovation: The Automated Residency Match Rank List.

    PubMed

    Strickland, Colin; Rubinstein, David

    2016-01-01

    The creation of the final rank list for the National Residency Matching Program every year is a laborious task requiring the time and input of numerous faculty members and residents. This article describes the creation of an automated visual rank list to efficiently organize and guide discussion at the yearly rank meeting so that the task may be efficiently and fairly completed. The rank list was created using a PowerPoint (Microsoft) macro that can pull information directly from a spreadsheet to generate a visual rank list that can be modified on-the-fly during the final rank list meeting. An automatically created visual rank list helps facilitate an efficient meeting and creates an open and transparent process leading to the final ranking. PMID:26778579

  11. Rings whose p-ranks do not exceed 1

    SciTech Connect

    Guseva, O. S.; Tsarev, A. V. E-mail: an-tsarev@yandex.ru

    2014-04-30

    We consider associative torsion-free rings of finite rank whose p-ranks do not exceed 1. For these rings, certain analogues of Wedderburn's theorem on finite-dimensional algebras are found. Bibliography: 11 titles. (paper)

  12. Higher rank numerical ranges and low rank perturbations of quantum channels

    NASA Astrophysics Data System (ADS)

    Li, Chi-Kwong; Poon, Yiu-Tung; Sze, Nung-Sing

    2008-12-01

    For a positive integer k, the rank-k numerical range [Lambda]k(A) of an operator A acting on a Hilbert space of dimension at least k is the set of scalars [lambda] such that PAP=[lambda]P for some rank k orthogonal projection P. In this paper, a close connection between low rank perturbation of an operator A and [Lambda]k(A) is established. In particular, for 1[less-than-or-equals, slant]rrank(F)[less-than-or-equals, slant]r. In quantum computing, this result implies that a quantum channel with a k-dimensional error correcting code under a perturbation of rank at most r will still have a (k-r)-dimensional error correcting code. Moreover, it is shown that if A is normal or if the dimension of A is finite, then [Lambda]k(A) can be obtained as the intersection of [Lambda]k-r(A+F) for a collection of rank r operators F. Examples are given to show that the result fails if A is a general operator. The closure and the interior of the convex set [Lambda]k(A) are completely determined. Analogous results are obtained for [Lambda][infinity](A) defined as the set of scalars [lambda] such that PAP=[lambda]P for an infinite rank orthogonal projection P. It is shown that [Lambda][infinity](A) is the intersection of all [Lambda]k(A) for k=1,2,.... If A-[mu]I is not compact for all , then the closure and the interior of [Lambda][infinity](A) coincide with those of the essential numerical range of A. The situation for the special case when A-[mu]I is compact for some is also studied.

  13. Integrated Low-Rank-Based Discriminative Feature Learning for Recognition.

    PubMed

    Zhou, Pan; Lin, Zhouchen; Zhang, Chao

    2016-05-01

    Feature learning plays a central role in pattern recognition. In recent years, many representation-based feature learning methods have been proposed and have achieved great success in many applications. However, these methods perform feature learning and subsequent classification in two separate steps, which may not be optimal for recognition tasks. In this paper, we present a supervised low-rank-based approach for learning discriminative features. By integrating latent low-rank representation (LatLRR) with a ridge regression-based classifier, our approach combines feature learning with classification, so that the regulated classification error is minimized. In this way, the extracted features are more discriminative for the recognition tasks. Our approach benefits from a recent discovery on the closed-form solutions to noiseless LatLRR. When there is noise, a robust Principal Component Analysis (PCA)-based denoising step can be added as preprocessing. When the scale of a problem is large, we utilize a fast randomized algorithm to speed up the computation of robust PCA. Extensive experimental results demonstrate the effectiveness and robustness of our method. PMID:26080387

  14. Network-based target ranking for polypharmacological therapies.

    PubMed

    Vitali, Francesca; Mulas, Francesca; Marini, Pietro; Bellazzi, Riccardo

    2013-10-01

    With the growing understanding of complex diseases, the focus of drug discovery has shifted from the well-accepted "one target, one drug" model, to a new "multi-target, multi-drug" model, aimed at systemically modulating multiple targets. In this context, polypharmacology has emerged as a new paradigm to overcome the recent decline in productivity of pharmaceutical research. However, finding methods to evaluate multicomponent therapeutics and ranking synergistic agent combinations is still a demanding task. At the same time, the data gathered on complex diseases has been progressively collected in public data and knowledge repositories, such as protein-protein interaction (PPI) databases. The PPI networks are increasingly used as universal platforms for data integration and analysis. A novel computational network-based approach for feasible and efficient identification of multicomponent synergistic agents is proposed in this paper. Given a complex disease, the method exploits the topological features of the related PPI network to identify possible combinations of hit targets. The best ranked combinations are subsequently computed on the basis of a synergistic score. We illustrate the potential of the method through a study on Type 2 Diabetes Mellitus. The results highlight its ability to retrieve novel target candidates, which role is also confirmed by the analysis of the related literature. PMID:23850841

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

    PubMed

    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/. PMID:27446133

  16. Annihilating Filter-Based Low-Rank Hankel Matrix Approach for Image Inpainting.

    PubMed

    Jin, Kyong Hwan; Ye, Jong Chul

    2015-11-01

    In this paper, we propose a patch-based image inpainting method using a low-rank Hankel structured matrix completion approach. The proposed method exploits the annihilation property between a shift-invariant filter and image data observed in many existing inpainting algorithms. In particular, by exploiting the commutative property of the convolution, the annihilation property results in a low-rank block Hankel structure data matrix, and the image inpainting problem becomes a low-rank structured matrix completion problem. The block Hankel structured matrices are obtained patch-by-patch to adapt to the local changes in the image statistics. To solve the structured low-rank matrix completion problem, we employ an alternating direction method of multipliers with factorization matrix initialization using the low-rank matrix fitting algorithm. As a side product of the matrix factorization, locally adaptive dictionaries can be also easily constructed. Despite the simplicity of the algorithm, the experimental results using irregularly subsampled images as well as various images with globally missing patterns showed that the proposed method outperforms existing state-of-the-art image inpainting methods. PMID:26087492

  17. Identification of essential proteins based on ranking edge-weights in protein-protein interaction networks.

    PubMed

    Wang, Yan; Sun, Huiyan; Du, Wei; Blanzieri, Enrico; Viero, Gabriella; Xu, Ying; Liang, Yanchun

    2014-01-01

    Essential proteins are those that are indispensable to cellular survival and development. Existing methods for essential protein identification generally rely on knock-out experiments and/or the relative density of their interactions (edges) with other proteins in a Protein-Protein Interaction (PPI) network. Here, we present a computational method, called EW, to first rank protein-protein interactions in terms of their Edge Weights, and then identify sub-PPI-networks consisting of only the highly-ranked edges and predict their proteins as essential proteins. We have applied this method to publicly-available PPI data on Saccharomyces cerevisiae (Yeast) and Escherichia coli (E. coli) for essential protein identification, and demonstrated that EW achieves better performance than the state-of-the-art methods in terms of the precision-recall and Jackknife measures. The highly-ranked protein-protein interactions by our prediction tend to be biologically significant in both the Yeast and E. coli PPI networks. Further analyses on systematically perturbed Yeast and E. coli PPI networks through randomly deleting edges demonstrate that the proposed method is robust and the top-ranked edges tend to be more associated with known essential proteins than the lowly-ranked edges. PMID:25268881

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

    PubMed Central

    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/. PMID:27446133

  19. Expanding the landscape of {N} = 2 rank 1 SCFTs

    NASA Astrophysics Data System (ADS)

    Argyres, Philip C.; Lotito, Matteo; Lü, Yongchao; Martone, Mario

    2016-05-01

    We refine our previous proposal [1-3] for systematically classifying 4d rank-1 {N} = 2 SCFTs by constructing their possible Coulomb branch geometries. Four new recently discussed rank-1 theories [4, 5], including novel {N} = 3 SCFTs, sit beautifully in our refined classification framework. By arguing for the consistency of their RG flows we can make a strong case for the existence of at least four additional rank-1 SCFTs, nearly doubling the number of known rank-1 SCFTs.

  20. Ranking of Prokaryotic Genomes Based on Maximization of Sortedness of Gene Lengths

    PubMed Central

    Bolshoy, A; Salih, B; Cohen, I; Tatarinova, T

    2014-01-01

    How variations of gene lengths (some genes become longer than their predecessors, while other genes become shorter and the sizes of these factions are randomly different from organism to organism) depend on organismal evolution and adaptation is still an open question. We propose to rank the genomes according to lengths of their genes, and then find association between the genome rank and variousproperties, such as growth temperature, nucleotide composition, and pathogenicity. This approach reveals evolutionary driving factors. The main purpose of this study is to test effectiveness and robustness of several ranking methods. The selected method of evaluation is measuring of overall sortedness of the data. We have demonstrated that all considered methods give consistent results and Bubble Sort and Simulated Annealing achieve the highest sortedness. Also, Bubble Sort is considerably faster than the Simulated Annealing method. PMID:26146586

  1. Calibrating Canadian Universities: Rankings for Sale Once Again

    ERIC Educational Resources Information Center

    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 of…

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

    ERIC Educational Resources Information Center

    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. World University Rankings: Ambiguous Signals. Go8 Backgrounder 30

    ERIC Educational Resources Information Center

    Group of Eight (NJ1), 2012

    2012-01-01

    The current main world university rankings broadly group the leading research universities of nations. Australia's Go8 universities are generally within the top 250 ranked universities, with several institutions in the top 50-100 on some measures. This recognition is commendable, however imperfect the individual rankings may be. Use is made of…

  4. Academic Ranking--From Its Genesis to Its International Expansion

    ERIC Educational Resources Information Center

    Vieira, Rosilene C.; Lima, Manolita C.

    2015-01-01

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

  5. The Importance of Rank Position. CEP Discussion Paper No. 1241

    ERIC Educational Resources Information Center

    Murphy, Richard; Weinhardt, Felix

    2013-01-01

    We find an individual's rank within their reference group has effects on later objective outcomes. To evaluate the impact of local rank, we use a large administrative dataset tracking over two million students in England from primary through to secondary school. Academic rank within primary school has sizable, robust and significant effects…

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

    ERIC Educational Resources Information Center

    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…

  7. 14 CFR § 1214.1105 - Final ranking.

    Code of Federal Regulations, 2014 CFR

    2014-01-01

    ... 14 Aeronautics and Space 5 2014-01-01 2014-01-01 false Final ranking. § 1214.1105 Section § 1214.1105 Aeronautics and Space NATIONAL AERONAUTICS AND SPACE ADMINISTRATION SPACE FLIGHT NASA Astronaut Candidate Recruitment and Selection Program § 1214.1105 Final ranking. Final rankings will be based on...

  8. Ranking Quality in Higher Education: Guiding or Misleading?

    ERIC Educational Resources Information Center

    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…

  9. University Rankings 2.0: New Frontiers in Institutional Comparisons

    ERIC Educational Resources Information Center

    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…

  10. Control by Numbers: New Managerialism and Ranking in Higher Education

    ERIC Educational Resources Information Center

    Lynch, Kathleen

    2015-01-01

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

  11. Academic Ranking of World Universities by Broad Subject Fields

    ERIC Educational Resources Information Center

    Cheng, Ying; Liu, Nian Cai

    2007-01-01

    Upon numerous requests to provide ranking of world universities by broad subject fields/schools/colleges and by subject fields/programs/departments, the authors present the ranking methodologies and problems that arose from the research by the Institute of Higher Education, Shanghai Jiao Tong University on the Academic Ranking of World…

  12. Sum of ranking differences to rank stationary phases used in packed column supercritical fluid chromatography.

    PubMed

    West, Caroline; Khalikova, Maria A; Lesellier, Eric; Héberger, Károly

    2015-08-28

    The identification of a suitable stationary phase in supercritical fluid chromatography (SFC) is a major source of difficulty for those with little experience in this technique. Several protocols have been suggested for column classification in high-performance liquid chromatography (HPLC), gas chromatography (GC), and SFC. However, none of the proposed classification schemes received general acceptance. A fair way to compare columns was proposed with the sum of ranking differences (SRD). In this project, we used the retention data obtained for 86 test compounds with varied polarity and structure, analyzed on 71 different stationary phases encompassing the full range in polarity of commercial packed columns currently available to the SFC chromatographer, with a single set of mobile phase and operating conditions (carbon dioxide-methanol mobile phase, 25°C, 150bar outlet pressure, 3ml/min). First, a reference column was selected and the 70 remaining columns were ranked based on this reference column and the retention data obtained on the 86 analytes. As these analytes previously served for the calculation of linear solvation energy relationships (LSER) on the 71 columns, SRD ranks were compared to LSER methodology. Finally, an external comparison based on the analysis of 10 other analytes (UV filters) related the observed selectivity to SRD ranking. Comparison of elution orders of the UV filters to the SRD rankings is highly supportive of the adequacy of SRD methodology to select similar and dissimilar columns. PMID:26228853

  13. Experimental congruence of interval scale production from paired comparisons and ranking for image evaluation

    NASA Astrophysics Data System (ADS)

    Handley, John C.; Babcock, Jason S.; Pelz, Jeff B.

    2003-12-01

    Image evaluation tasks are often conducted using paired comparisons or ranking. To elicit interval scales, both methods rely on Thurstone's Law of Comparative Judgment in which objects closer in psychological space are more often confused in preference comparisons by a putative discriminal random process. It is often debated whether paired comparisons and ranking yield the same interval scales. An experiment was conducted to assess scale production using paired comparisons and ranking. For this experiment a Pioneer Plasma Display and Apple Cinema Display were used for stimulus presentation. Observers performed rank order and paired comparisons tasks on both displays. For each of five scenes, six images were created by manipulating attributes such as lightness, chroma, and hue using six different settings. The intention was to simulate the variability from a set of digital cameras or scanners. Nineteen subjects, (5 females, 14 males) ranging from 19-51 years of age participated in this experiment. Using a paired comparison model and a ranking model, scales were estimated for each display and image combination yielding ten scale pairs, ostensibly measuring the same psychological scale. The Bradley-Terry model was used for the paired comparisons data and the Bradley-Terry-Mallows model was used for the ranking data. Each model was fit using maximum likelihood estimation and assessed using likelihood ratio tests. Approximate 95% confidence intervals were also constructed using likelihood ratios. Model fits for paired comparisons were satisfactory for all scales except those from two image/display pairs; the ranking model fit uniformly well on all data sets. Arguing from overlapping confidence intervals, we conclude that paired comparisons and ranking produce no conflicting decisions regarding ultimate ordering of treatment preferences, but paired comparisons yield greater precision at the expense of lack-of-fit.

  14. Web document ranking via active learning and kernel principal component analysis

    NASA Astrophysics Data System (ADS)

    Cai, Fei; Chen, Honghui; Shu, Zhen

    2015-09-01

    Web document ranking arises in many information retrieval (IR) applications, such as the search engine, recommendation system and online advertising. A challenging issue is how to select the representative query-document pairs and informative features as well for better learning and exploring new ranking models to produce an acceptable ranking list of candidate documents of each query. In this study, we propose an active sampling (AS) plus kernel principal component analysis (KPCA) based ranking model, viz. AS-KPCA Regression, to study the document ranking for a retrieval system, i.e. how to choose the representative query-document pairs and features for learning. More precisely, we fill those documents gradually into the training set by AS such that each of which will incur the highest expected DCG loss if unselected. Then, the KPCA is performed via projecting the selected query-document pairs onto p-principal components in the feature space to complete the regression. Hence, we can cut down the computational overhead and depress the impact incurred by noise simultaneously. To the best of our knowledge, we are the first to perform the document ranking via dimension reductions in two dimensions, namely, the number of documents and features simultaneously. Our experiments demonstrate that the performance of our approach is better than that of the baseline methods on the public LETOR 4.0 datasets. Our approach brings an improvement against RankBoost as well as other baselines near 20% in terms of MAP metric and less improvements using P@K and NDCG@K, respectively. Moreover, our approach is particularly suitable for document ranking on the noisy dataset in practice.

  15. Novel RANK antagonists for the treatment of bone-resorptive disease: theoretical predictions and experimental validation.

    PubMed

    Téletchéa, Stéphane; Stresing, Verena; Hervouet, Soizic; Baud'huin, Marc; Heymann, Marie-Françoise; Bertho, Gildas; Charrier, Céline; Ando, Kosei; Heymann, Dominique

    2014-06-01

    Receptor activator of nuclear factor-κB (RANK) and RANK ligand (RANKL) play a pivotal role in bone metabolism, and selective targeting of RANK signaling has become a promising therapeutic strategy in the management of resorptive bone diseases. Existing antibody-based therapies and novel inhibitors currently in development were designed to target the ligand, rather than the membrane receptor expressed on osteoclast precursors. We describe here an alternative approach to designing small peptides able to specifically bind to the hinge region of membrane RANK responsible for the conformational change upon RANKL association. A nonapeptide generated by this method was validated for its biological activity in vitro and in vivo and served as a lead compound for the generation of a series of peptide RANK antagonists derived from the original sequence. Our study presents a structure- and knowledge-based strategy for the design of novel effective and affordable small peptide inhibitors specifically targeting the receptor RANK and opens a new therapeutic opportunity for the treatment of resorptive bone disease. PMID:24390798

  16. Interval analysis approach to rank determination in linear least squares problems

    SciTech Connect

    Manteuffel, T.A.

    1980-06-01

    The linear least-squares problem Ax approx. = b has a unique solution only if the matrix A has full column rank. Numerical rank determination is difficult, especially in the presence of uncertainties in the elements of A. This paper proposes an interval analysis approach. A set of matrices A/sup I/ is defined that contains all possible perturbations of A due to uncertainties; A/sup I/ is said to be rank deficient if any member of A/sup I/ is rank deficient. A modification to the Q-R decomposition method of solution of the least-squares problem allows a determination of the rank of A/sup I/ and a partial interval analysis of the solution vector x. This procedure requires the computation of R/sup -1/. Another modification is proposed which determines the rank of A/sup I/ without computing R/sup -1/. The additional computational effort is O(N/sup 2/), where N is the column dimension of A. 4 figures.

  17. Robust visual tracking via L 0 regularized local low-rank feature learning

    NASA Astrophysics Data System (ADS)

    Liu, Risheng; Bai, Shanshan; Su, Zhixun; Zhang, Changcheng; Sun, Chunhai

    2015-05-01

    Visual tracking is a fundamental task and has many applications in computer vision. We incorporate local dictionary and L0 regularized low-rank features into the particle filter framework to address this problem. Specifically, by developing an efficient L0 regularized sparse coding model to incrementally learn low-rank features for the tracking target and incorporating a local dictionary into low-rank features to build the observation model, we establish a robust online object tracking system. As a nontrivial byproduct, we also develop numerical algorithms to efficiently solve the resulting nonconvex optimization problems. Compared with conventional methods, which often directly use corrupted observations to form the dictionary, our low-rank feature-based dictionary successfully removes occlusions and exactly represents the intrinsic structure of the object. Furthermore, in contrast to the traditional holistic methods, the local strategy contains abundant partial and spatial information, thus enhancing the discrimination of our observation model. More importantly, the L0 norm-based hard sparse coding can successfully reduce the redundant information while preserving the intrinsic low-rank features of the target object, leading to a better appearance subspace updating scheme. Experimental results on challenging sequences show that our method consistently outperforms several state-of-the-art methods.

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

    PubMed Central

    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

  19. Rank and order: evaluating the performance of SNPs for individual assignment in a non-model organism.

    PubMed

    Storer, Caroline G; Pascal, Carita E; Roberts, Steven B; Templin, William D; Seeb, Lisa W; Seeb, James E

    2012-01-01

    Single nucleotide polymorphisms (SNPs) are valuable tools for ecological and evolutionary studies. In non-model species, the use of SNPs has been limited by the number of markers available. However, new technologies and decreasing technology costs have facilitated the discovery of a constantly increasing number of SNPs. With hundreds or thousands of SNPs potentially available, there is interest in comparing and developing methods for evaluating SNPs to create panels of high-throughput assays that are customized for performance, research questions, and resources. Here we use five different methods to rank 43 new SNPs and 71 previously published SNPs for sockeye salmon: F(ST), informativeness (I(n)), average contribution to principal components (LC), and the locus-ranking programs BELS and WHICHLOCI. We then tested the performance of these different ranking methods by creating 48- and 96-SNP panels of the top-ranked loci for each method and used empirical and simulated data to obtain the probability of assigning individuals to the correct population using each panel. All 96-SNP panels performed similarly and better than the 48-SNP panels except for the 96-SNP BELS panel. Among the 48-SNP panels, panels created from F(ST), I(n), and LC ranks performed better than panels formed using the top-ranked loci from the programs BELS and WHICHLOCI. The application of ranking methods to optimize panel performance will become more important as more high-throughput assays become available. PMID:23185290

  20. Community centrality for node's influential ranking in complex network

    NASA Astrophysics Data System (ADS)

    Cai, Biao; Tuo, Xian-Guo; Yang, Kai-Xue; Liu, Ming-Zhe

    2014-10-01

    Some tiny party of influential nodes may highly affect spread of information in complex networks. For the case of very high time complexity in the shortest path computation of global centralities, making use of local community centrality to identify influential nodes is an open and possible problem. Compared to degree and local centralities, a five-heartbeat forward community centrality is proposed in this paper, in which a five-step induced sub-graph of certain node in the network will be achieved. Next, we induce the minimal spanning tree (MMT) of the sub-graph. Finally, we take the sum of all weights of the MMT as community centrality measurement that needs to be the influential ranking of the node. We use the susceptible, infected and recovered (SIR) model to evaluate the performance of this method on several public test network data and explore the forward steps of community centrality by experiments. Simulative results show that our method with five steps can identify the influential ranking of nodes in complex network as well.

  1. Speaker-sensitive emotion recognition via ranking: Studies on acted and spontaneous speech☆

    PubMed Central

    Cao, Houwei; Verma, Ragini; Nenkova, Ani

    2014-01-01

    We introduce a ranking approach for emotion recognition which naturally incorporates information about the general expressivity of speakers. We demonstrate that our approach leads to substantial gains in accuracy compared to conventional approaches. We train ranking SVMs for individual emotions, treating the data from each speaker as a separate query, and combine the predictions from all rankers to perform multi-class prediction. The ranking method provides two natural benefits. It captures speaker specific information even in speaker-independent training/testing conditions. It also incorporates the intuition that each utterance can express a mix of possible emotion and that considering the degree to which each emotion is expressed can be productively exploited to identify the dominant emotion. We compare the performance of the rankers and their combination to standard SVM classification approaches on two publicly available datasets of acted emotional speech, Berlin and LDC, as well as on spontaneous emotional data from the FAU Aibo dataset. On acted data, ranking approaches exhibit significantly better performance compared to SVM classification both in distinguishing a specific emotion from all others and in multi-class prediction. On the spontaneous data, which contains mostly neutral utterances with a relatively small portion of less intense emotional utterances, ranking-based classifiers again achieve much higher precision in identifying emotional utterances than conventional SVM classifiers. In addition, we discuss the complementarity of conventional SVM and ranking-based classifiers. On all three datasets we find dramatically higher accuracy for the test items on whose prediction the two methods agree compared to the accuracy of individual methods. Furthermore on the spontaneous data the ranking and standard classification are complementary and we obtain marked improvement when we combine the two classifiers by late-stage fusion. PMID:25422534

  2. Denoised Wigner distribution deconvolution via low-rank matrix completion.

    PubMed

    Lee, Justin; Barbastathis, George

    2016-09-01

    Wigner distribution deconvolution (WDD) is a decades-old method for recovering phase from intensity measurements. Although the technique offers an elegant linear solution to the quadratic phase retrieval problem, it has seen limited adoption due to its high computational/memory requirements and the fact that the technique often exhibits high noise sensitivity. Here, we propose a method for noise suppression in WDD via low-rank noisy matrix completion. Our technique exploits the redundancy of an object's phase space to denoise its WDD reconstruction. We show in model calculations that our technique outperforms other WDD algorithms as well as modern iterative methods for phase retrieval such as ptychography. Our results suggest that a class of phase retrieval techniques relying on regularized direct inversion of ptychographic datasets (instead of iterative reconstruction techniques) can provide accurate quantitative phase information in the presence of high levels of noise. PMID:27607616

  3. Partial Kernelization for Rank Aggregation: Theory and Experiments

    NASA Astrophysics Data System (ADS)

    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.

  4. A Non-Local Low-Rank Approach to Enforce Integrability.

    PubMed

    Badri, Hicham; Yahia, Hussein

    2016-08-01

    We propose a new approach to enforce integrability using recent advances in non-local methods. Our formulation consists in a sparse gradient data-fitting term to handle outliers together with a gradient-domain non-local low-rank prior. This regularization has two main advantages: 1) the low-rank prior ensures similarity between non-local gradient patches, which helps recovering high-quality clean patches from severe outliers corruption and 2) the low-rank prior efficiently reduces dense noise as it has been shown in recent image restoration works. We propose an efficient solver for the resulting optimization formulation using alternate minimization. Experiments show that the new method leads to an important improvement compared with previous optimization methods and is able to efficiently handle both outliers and dense noise mixed together. PMID:27214898

  5. Thoracic response targets for a computational model: a hierarchical approach to assess the biofidelity of a 50th-percentile occupant male finite element model.

    PubMed

    Poulard, David; Kent, Richard W; Kindig, Matthew; Li, Zuoping; Subit, Damien

    2015-05-01

    Current finite element human thoracic models are typically evaluated against a limited set of loading conditions; this is believed to limit their capability to predict accurate responses. In this study, a 50th-percentile male finite element model (GHBMC v4.1) was assessed under various loading environments (antero-posterior rib bending, point loading of the denuded ribcage, omnidirectional pendulum impact and table top) through a correlation metric tool (CORA) based on linearly independent signals. The load cases were simulated with the GHBMC model and response corridors were developed from published experimental data. The model was found to be in close agreement with the experimental data both qualitatively and quantitatively (CORA ratings above 0.75) and the response of the thorax was overall deemed biofidelic. This study also provides relevant corridors and an objective rating framework that can be used for future evaluation of thoracic models. PMID:25681717

  6. A logical framework for ranking landslide inventory maps

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  8. DebtRank: A Microscopic Foundation for Shock Propagation

    PubMed Central

    Bardoscia, Marco; Battiston, Stefano; Caccioli, Fabio; Caldarelli, Guido

    2015-01-01

    The DebtRank algorithm has been increasingly investigated as a method to estimate the impact of shocks in financial networks, as it overcomes the limitations of the traditional default-cascade approaches. Here we formulate a dynamical “microscopic” theory of instability for financial networks by iterating balance sheet identities of individual banks and by assuming a simple rule for the transfer of shocks from borrowers to lenders. By doing so, we generalise the DebtRank formulation, both providing an interpretation of the effective dynamics in terms of basic accounting principles and preventing the underestimation of losses on certain network topologies. Depending on the structure of the interbank leverage matrix the dynamics is either stable, in which case the asymptotic state can be computed analytically, or unstable, meaning that at least one bank will default. We apply this framework to a dataset of the top listed European banks in the period 2008–2013. We find that network effects can generate an amplification of exogenous shocks of a factor ranging between three (in normal periods) and six (during the crisis) when we stress the system with a 0.5% shock on external (i.e. non-interbank) assets for all banks. PMID:26091013

  9. Low-rank coal thermal properties and diffusivity: Final report

    SciTech Connect

    Ramirez, W.F.

    1987-06-01

    This project developed techniques for measuring thermal properties and mass diffusivities of low-rank coals and coal powders. Using the concept of volume averaging, predictive models have been developed for these porous media properties. The Hot Wire Method was used for simultaneously measuring the thermal conductivity and thermal diffusivity of both consolidated and unconsolidated low-rank coals. A new computer-interfaced experiment is presented and sample container designs developed for both coal powders and consolidated coals. A new mathematical model, based upon volume averaging, is presented for the prediction of these porous media properties. Velocity and temperature effects on liquid-phase dispersion through unconsolidated coal were determined. Radioactive tracer data were used to determine mass diffusivities. A new predictive mathematical model is presented based upon volume averaging. Vapor-phase diffusivity measurements of organic solvents in consolidated lignite coal are reported. An unsteady-state pressure response experiment with microcomputed-based data acquisition was developed to estimate dispersion coefficients through consolidated lignite coals. The mathematical analysis of the pressure response data provides the dispersion coefficient and the adsorption coefficient. 48 refs., 59 figs., 17 tabs.

  10. Military rank and AIDS proportionate mortality in the Brazilian Navy.

    PubMed

    Silva, Marlene; Santana, Vilma; Dourado, Inês

    2007-02-01

    This study describes AIDS mortality and occupational factors among servicemen in the Brazilian Navy. This is a proportional mortality study of 2,586 servicemen's death certificates (20-72 years of age) recorded from 1991 to 1995. Death certificates and occupational histories came from the Brazilian Navy Insurance System archives. Association was measured using proportionate mortality odds ratios obtained with unconditional logistic regression. AIDS proportionate mortality was estimated at 4.8% (n = 125) and increased during the study period, particularly among servicemen under 50 years of age and those with low rank. As compared to other occupations, there was relative excess AIDS in the "management" (proportionate mortality odds ratio, PMORage-adjusted = 2.45; 95%CI: 1.27-4.71), "secretarial" (PMORage-adjusted = 2.49; 95%CI: 1.22-5.08), and "janitorial" (PMORage-adjusted = 2.61; 95%CI: 1.10-6.16) occupational groups. AIDS proportionate mortality was higher among male than female military members. Higher rates were observed in some occupational groups when the members were low ranking. Power distribution, gender issues, and low socioeconomic status require further investigation using more appropriate methods. PMID:17221091

  11. Influence analysis for the factor analysis model with ranking data.

    PubMed

    Xu, Liang; Poon, Wai-Yin; Lee, Sik-Yum

    2008-05-01

    Influence analysis is an important component of data analysis, and the local influence approach has been widely applied to many statistical models to identify influential observations and assess minor model perturbations since the pioneering work of Cook (1986). The approach is often adopted to develop influence analysis procedures for factor analysis models with ranking data. However, as this well-known approach is based on the observed data likelihood, which involves multidimensional integrals, directly applying it to develop influence analysis procedures for the factor analysis models with ranking data is difficult. To address this difficulty, a Monte Carlo expectation and maximization algorithm (MCEM) is used to obtain the maximum-likelihood estimate of the model parameters, and measures for influence analysis on the basis of the conditional expectation of the complete data log likelihood at the E-step of the MCEM algorithm are then obtained. Very little additional computation is needed to compute the influence measures, because it is possible to make use of the by-products of the estimation procedure. Influence measures that are based on several typical perturbation schemes are discussed in detail, and the proposed method is illustrated with two real examples and an artificial example. PMID:18482479

  12. DebtRank: A Microscopic Foundation for Shock Propagation.

    PubMed

    Bardoscia, Marco; Battiston, Stefano; Caccioli, Fabio; Caldarelli, Guido

    2015-01-01

    The DebtRank algorithm has been increasingly investigated as a method to estimate the impact of shocks in financial networks, as it overcomes the limitations of the traditional default-cascade approaches. Here we formulate a dynamical "microscopic" theory of instability for financial networks by iterating balance sheet identities of individual banks and by assuming a simple rule for the transfer of shocks from borrowers to lenders. By doing so, we generalise the DebtRank formulation, both providing an interpretation of the effective dynamics in terms of basic accounting principles and preventing the underestimation of losses on certain network topologies. Depending on the structure of the interbank leverage matrix the dynamics is either stable, in which case the asymptotic state can be computed analytically, or unstable, meaning that at least one bank will default. We apply this framework to a dataset of the top listed European banks in the period 2008-2013. We find that network effects can generate an amplification of exogenous shocks of a factor ranging between three (in normal periods) and six (during the crisis) when we stress the system with a 0.5% shock on external (i.e. non-interbank) assets for all banks. PMID:26091013

  13. Ranking Schools' Academic Performance Using a Fuzzy VIKOR

    NASA Astrophysics Data System (ADS)

    Musani, Suhaina; Aziz Jemain, Abdul

    2015-06-01

    Determination rank is structuring alternatives in order of priority. It is based on the criteria determined for each alternative involved. Evaluation criteria are performed and then a composite index composed of each alternative for the purpose of arranging in order of preference alternatives. This practice is known as multiple criteria decision making (MCDM). There are several common approaches to MCDM, one of the practice is known as VIKOR (Multi-criteria Optimization and Compromise Solution). The objective of this study is to develop a rational method for school ranking based on linguistic information of a criterion. The school represents an alternative, while the results for a number of subjects as the criterion. The results of the examination for a course, is given according to the student percentage of each grade. Five grades of excellence, honours, average, pass and fail is used to indicate a level of achievement in linguistics. Linguistic variables are transformed to fuzzy numbers to form a composite index of school performance. Results showed that fuzzy set theory can solve the limitations of using MCDM when there is uncertainty problems exist in the data.

  14. Rank-Based Similarity Search: Reducing the Dimensional Dependence.

    PubMed

    Houle, Michael E; Nett, Michael

    2015-01-01

    This paper introduces a data structure for k-NN search, the Rank Cover Tree (RCT), whose pruning tests rely solely on the comparison of similarity values; other properties of the underlying space, such as the triangle inequality, are not employed. Objects are selected according to their ranks with respect to the query object, allowing much tighter control on the overall execution costs. A formal theoretical analysis shows that with very high probability, the RCT returns a correct query result in time that depends very competitively on a measure of the intrinsic dimensionality of the data set. The experimental results for the RCT show that non-metric pruning strategies for similarity search can be practical even when the representational dimension of the data is extremely high. They also show that the RCT is capable of meeting or exceeding the level of performance of state-of-the-art methods that make use of metric pruning or other selection tests involving numerical constraints on distance values. PMID:26353214

  15. Rank preserving sparse learning for Kinect based scene classification.

    PubMed

    Tao, Dapeng; Jin, Lianwen; Yang, Zhao; Li, Xuelong

    2013-10-01

    With the rapid development of the RGB-D sensors and the promptly growing population of the low-cost Microsoft Kinect sensor, scene classification, which is a hard, yet important, problem in computer vision, has gained a resurgence of interest recently. That is because the depth of information provided by the Kinect sensor opens an effective and innovative way for scene classification. In this paper, we propose a new scheme for scene classification, which applies locality-constrained linear coding (LLC) to local SIFT features for representing the RGB-D samples and classifies scenes through the cooperation between a new rank preserving sparse learning (RPSL) based dimension reduction and a simple classification method. RPSL considers four aspects: 1) it preserves the rank order information of the within-class samples in a local patch; 2) it maximizes the margin between the between-class samples on the local patch; 3) the L1-norm penalty is introduced to obtain the parsimony property; and 4) it models the classification error minimization by utilizing the least-squares error minimization. Experiments are conducted on the NYU Depth V1 dataset and demonstrate the robustness and effectiveness of RPSL for scene classification. PMID:23846511

  16. Rank-3 root systems induce root systems of rank 4 via a new Clifford spinor construction

    NASA Astrophysics Data System (ADS)

    Dechant, Pierre-Philippe

    2015-04-01

    In this paper, we show that via a novel construction every rank-3 root system induces a root system of rank 4. Via the Cartan-Dieudonné theorem, an even number of successive Coxeter reflections yields rotations that in a Clifford algebra framework are described by spinors. In three dimensions these spinors themselves have a natural four-dimensional Euclidean structure, and discrete spinor groups can therefore be interpreted as 4D polytopes. In fact, we show that these polytopes have to be root systems, thereby inducing Coxeter groups of rank 4, and that their automorphism groups include two factors of the respective discrete spinor groups trivially acting on the left and on the right by spinor multiplication. Special cases of this general theorem include the exceptional 4D groups D4, F4 and H4, which therefore opens up a new understanding of applications of these structures in terms of spinorial geometry. In particular, 4D groups are ubiquitous in high energy physics. For the corresponding case in two dimensions, the groups I2(n) are shown to be self-dual, whilst via a similar construction in terms of octonions each rank-3 root system induces a root system in dimension 8; this root system is in fact the direct sum of two copies of the corresponding induced 4D root system.

  17. An Empirical Study on Credibility of China's University Rankings: A Case Study of Three Rankings

    ERIC Educational Resources Information Center

    Ying, Yu; Jingao, Zhang

    2009-01-01

    A university ranking with credibility may provide proper guidance to students and parents in university choice, lead to rational flow of educational resources, promote competition among universities and evaluation mechanism in society, and inform the government in decision making. However, there are quite some disputes and doubts from the public…

  18. Rankings & Estimates: Rankings of the States 2010 and Estimates of School Statistics 2011

    ERIC Educational Resources Information Center

    National Education Association Research Department, 2010

    2010-01-01

    The data presented in this combined report--"Rankings & Estimates"--provide facts about the extent to which local, state, and national governments commit resources to public education. As one might expect in a nation as diverse as the United States--with respect to economics, geography, and politics--the level of commitment to education varies on…

  19. Rankings & Estimates: Rankings of the States 2009 and Estimates of School Statistics 2010

    ERIC Educational Resources Information Center

    National Education Association Research Department, 2009

    2009-01-01

    The data presented in this combined report--"Rankings & Estimates"--provide facts about the extent to which local, state, and national governments commit resources to public education. As one might expect in a nation as diverse as the United States--with respect to economics, geography, and politics--the level of commitment to education varies on…

  20. Rankings & Estimates: Rankings of the States 2008 and Estimates of School Statistics 2009

    ERIC Educational Resources Information Center

    National Education Association Research Department, 2008

    2008-01-01

    The data presented in this combined report--"Rankings & Estimates"--provide facts about the extent to which local, state, and national governments commit resources to public education. As one might expect in a nation as diverse as the United States--with respect to economics, geography, and politics--the level of commitment to education varies on…

  1. Rankings & Estimates: Rankings of the States 2004 and Estimates of School Statistics 2005

    ERIC Educational Resources Information Center

    National Education Association Research Department, 2005

    2005-01-01

    The data presented in this combined report--"Rankings & Estimates"--provide facts about the extent to which local, state, and national governments commit resources to public education. As one might expect in a nation as diverse as the United States--with respect to economics, geography, and politics--the level of commitment to education varies on…

  2. Abdominal Organ Location, Morphology, and Rib Coverage for the 5th, 50th, and 95th Percentile Males and Females in the Supine and Seated Posture using Multi-Modality Imaging

    PubMed Central

    Hayes, Ashley R.; Gayzik, F. Scott; Moreno, Daniel P.; Martin, R. Shayn; Stitzel, Joel D.

    2013-01-01

    The purpose of this study was to use data from a multi-modality image set of males and females representing the 5th, 50th, and 95th percentile (n=6) to examine abdominal organ location, morphology, and rib coverage variations between supine and seated postures. Medical images were acquired from volunteers in three image modalities including Computed Tomography (CT), Magnetic Resonance Imaging (MRI), and upright MRI (uMRI). A manual and semi-automated segmentation method was used to acquire data and a registration technique was employed to conduct a comparative analysis between abdominal organs (liver, spleen, and kidneys) in both postures. Location of abdominal organs, defined by center of gravity movement, varied between postures and was found to be significant (p=0.002 to p=0.04) in multiple directions for each organ. In addition, morphology changes, including compression and expansion, were seen in each organ as a result of postural changes. Rib coverage, defined as the projected area of the ribs onto the abdominal organs, was measured in frontal, lateral, and posterior projections, and also varied between postures. A significant change in rib coverage between postures was measured for the spleen and right kidney (p=0.03 and p=0.02). The results indicate that posture affects the location, morphology and rib coverage area of abdominal organs and these implications should be noted in computational modeling efforts focused on a seated posture. PMID:24406951

  3. Censored Rank Independence Screening for High-dimensional Survival Data

    PubMed Central

    Song, Rui; Lu, Wenbin; Ma, Shuangge; Jeng, X. Jessie

    2014-01-01

    Summary In modern statistical applications, the dimension of covariates can be much larger than the sample size. In the context of linear models, correlation screening (Fan and Lv, 2008) has been shown to reduce the dimension of such data effectively while achieving the sure screening property, i.e., all of the active variables can be retained with high probability. However, screening based on the Pearson correlation does not perform well when applied to contaminated covariates and/or censored outcomes. In this paper, we study censored rank independence screening of high-dimensional survival data. The proposed method is robust to predictors that contain outliers, works for a general class of survival models, and enjoys the sure screening property. Simulations and an analysis of real data demonstrate that the proposed method performs competitively on survival data sets of moderate size and high-dimensional predictors, even when these are contaminated. PMID:25663709

  4. Retrieving handwriting by combining word spotting and manifold ranking

    NASA Astrophysics Data System (ADS)

    Peña Saldarriaga, Sebastián; Morin, Emmanuel; Viard-Gaudin, Christian

    2012-01-01

    Online handwritten data, produced with Tablet PCs or digital pens, consists in a sequence of points (x, y). As the amount of data available in this form increases, algorithms for retrieval of online data are needed. Word spotting is a common approach used for the retrieval of handwriting. However, from an information retrieval (IR) perspective, word spotting is a primitive keyword based matching and retrieval strategy. We propose a framework for handwriting retrieval where an arbitrary word spotting method is used, and then a manifold ranking algorithm is applied on the initial retrieval scores. Experimental results on a database of more than 2,000 handwritten newswires show that our method can improve the performances of a state-of-the-art word spotting system by more than 10%.

  5. Dynamic programming re-ranking for PPI interactor and pair extraction in full-text articles

    PubMed Central

    2011-01-01

    Background Experimentally verified protein-protein interactions (PPIs) cannot be easily retrieved by researchers unless they are stored in PPI databases. The curation of such databases can be facilitated by employing text-mining systems to identify genes which play the interactor role in PPIs and to map these genes to unique database identifiers (interactor normalization task or INT) and then to return a list of interaction pairs for each article (interaction pair task or IPT). These two tasks are evaluated in terms of the area under curve of the interpolated precision/recall (AUC iP/R) score because the order of identifiers in the output list is important for ease of curation. Results Our INT system developed for the BioCreAtIvE II.5 INT challenge achieved a promising AUC iP/R of 43.5% by using a support vector machine (SVM)-based ranking procedure. Using our new re-ranking algorithm, we have been able to improve system performance (AUC iP/R) by 1.84%. Our experimental results also show that with the re-ranked INT results, our unsupervised IPT system can achieve a competitive AUC iP/R of 23.86%, which outperforms the best BC II.5 INT system by 1.64%. Compared to using only SVM ranked INT results, using re-ranked INT results boosts AUC iP/R by 7.84%. Statistical significance t-test results show that our INT/IPT system with re-ranking outperforms that without re-ranking by a statistically significant difference. Conclusions In this paper, we present a new re-ranking algorithm that considers co-occurrence among identifiers in an article to improve INT and IPT ranking results. Combining the re-ranked INT results with an unsupervised approach to find associations among interactors, the proposed method can boost the IPT performance. We also implement score computation using dynamic programming, which is faster and more efficient than traditional approaches. PMID:21342534

  6. Low-Rank Modeling of Local k-Space Neighborhoods (LORAKS) for Constrained MRI

    PubMed Central

    Haldar, Justin P.

    2014-01-01

    Recent theoretical results on low-rank matrix reconstruction have inspired significant interest in low-rank modeling of MRI images. Existing approaches have focused on higher-dimensional scenarios with data available from multiple channels, timepoints, or image contrasts. The present work demonstrates that single-channel, single-contrast, single-timepoint k-space data can also be mapped to low-rank matrices when the image has limited spatial support or slowly varying phase. Based on this, we develop a novel and flexible framework for constrained image reconstruction that uses low-rank matrix modeling of local k-space neighborhoods (LORAKS). A new regularization penalty and corresponding algorithm for promoting low-rank are also introduced. The potential of LORAKS is demonstrated with simulated and experimental data for a range of denoising and sparse-sampling applications. LORAKS is also compared against state-of-the-art methods like homodyne reconstruction, ℓ1-norm minimization, and total variation minimization, and is demonstrated to have distinct features and advantages. In addition, while calibration-based support and phase constraints are commonly used in existing methods, the LORAKS framework enables calibrationless use of these constraints. PMID:24595341

  7. A New Route for Unburned Carbon Concentration Measurements Eliminating Mineral Content and Coal Rank Effects

    PubMed Central

    Liu, Dong; Duan, Yuan-Yuan; Yang, Zhen; Yu, Hai-Tong

    2014-01-01

    500 million tons of coal fly ash are produced worldwide every year with only 16% of the total amount utilized. Therefore, potential applications using fly ash have both environmental and industrial interests. Unburned carbon concentration measurements are fundamental to effective fly ash applications. Current on-line measurement accuracies are strongly affected by the mineral content and coal rank. This paper describes a char/ash particle cluster spectral emittance method for unburned carbon concentration measurements. The char/ash particle cluster spectral emittance is predicted theoretically here for various unburned carbon concentrations to show that the measurements are sensitive to unburned carbon concentration but insensitive to the mineral content and coal rank at short wavelengths. The results show that the char/ash particle cluster spectral emittance method is a novel and promising route for unburned carbon concentration on-line measurements without being influenced by mineral content or coal rank effects. PMID:24691496

  8. An automated approach for ranking journals to help in clinician decision support.

    PubMed

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

    2014-01-01

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

  9. Low-Rank and Eigenface Based Sparse Representation for Face Recognition

    PubMed Central

    Hou, Yi-Fu; Sun, Zhan-Li; Chong, Yan-Wen; Zheng, Chun-Hou

    2014-01-01

    In this paper, based on low-rank representation and eigenface extraction, we present an improvement to the well known Sparse Representation based Classification (SRC). Firstly, the low-rank images of the face images of each individual in training subset are extracted by the Robust Principal Component Analysis (Robust PCA) to alleviate the influence of noises (e.g., illumination difference and occlusions). Secondly, Singular Value Decomposition (SVD) is applied to extract the eigenfaces from these low-rank and approximate images. Finally, we utilize these eigenfaces to construct a compact and discriminative dictionary for sparse representation. We evaluate our method on five popular databases. Experimental results demonstrate the effectiveness and robustness of our method. PMID:25334027

  10. Image restoration via patch orientation-based low-rank matrix approximation and nonlocal means

    NASA Astrophysics Data System (ADS)

    Zhang, Di; He, Jiazhong; Du, Minghui

    2016-03-01

    Low-rank matrix approximation and nonlocal means (NLM) are two popular techniques for image restoration. Although the basic principle for applying these two techniques is the same, i.e., similar image patches are abundant in the image, previously published related algorithms use either low-rank matrix approximation or NLM because they manipulate the information of similar patches in different ways. We propose a method for image restoration by jointly using low-rank matrix approximation and NLM in a unified minimization framework. To improve the accuracy of determining similar patches, we also propose a patch similarity measurement based on curvelet transform. Extensive experiments on image deblurring and compressive sensing image recovery validate that the proposed method achieves better results than many state-of-the-art algorithms in terms of both quantitative measures and visual perception.

  11. Ranking Geochemical Energy Availability in Hydrothermal Ecosystems

    NASA Astrophysics Data System (ADS)

    Holland, M. E.; Shock, E. L.; Meyer-Dombard, D.; Amend, J. P.

    2004-12-01

    The energy available to hyperthermophilic microorganisms in hot springs can be theoretically estimated using thermodynamic calculations based on geochemical measurements. The relative abundance of different geochemical energy sources (the "ranking" of these reactions) in particular hot springs may provide one explanation for the differences in hot spring microbial communities and also facilitate the culture of ecologically-relevant microorganisms. Geochemical sampling of seven Yellowstone National Park hot springs was repeated five times from 1999 to 2004 with the intent to compare the geochemistry and geochemical energy available to microorganisms. These seven hot springs were located in three separate regions of Yellowstone National Park: three hot springs, including Obsidian Pool, were sampled in the Mud Volcano area; two in the Sylvan Springs area (Gibbon Meadows); and one each in Imperial Meadows and Sentinel Meadows (Lower Geyser Basin). The hot springs were 75 to 93° C (with one 65° C exception) and spanned the bulk of the pH range at Yellowstone (pH 1.8 to 7.6). Geochemical measurements made on hot springs included redox-active species containing C, N, O, H, S, and Fe; these species were measured by field spectrophotometry and ion chromatography of fluid samples and gas chromatographic analysis of gas samples. From these measurements chemical affinities were calculated for 179 inorganic reactions which encompass the suite of autotrophic energy sources potentially available in each pool. Composite affinities for each reaction were compiled for each of the seven primary pools. The composite for each pool was assembled from repeat measurements from the primary pool as well as nearby pools with similar geochemistry. Calculations show that over half of these inorganic reactions could provide enough energy for a microorganism to survive, based on the threshold value of energy required by {it E. coli} (20 kJ per mole of electron pairs). Some microorganisms

  12. FTA Basic Event & Cut Set Ranking.

    Energy Science and Technology Software Center (ESTSC)

    1999-05-04

    Version 00 IMPORTANCE computes various measures of probabilistic importance of basic events and minimal cut sets to a fault tree or reliability network diagram. The minimal cut sets, the failure rates and the fault duration times (i.e., the repair times) of all basic events contained in the minimal cut sets are supplied as input data. The failure and repair distributions are assumed to be exponential. IMPORTANCE, a quantitative evaluation code, then determines the probability ofmore » the top event and computes the importance of minimal cut sets and basic events by a numerical ranking. Two measures are computed. The first describes system behavior at one point in time; the second describes sequences of failures that cause the system to fail in time. All measures are computed assuming statistical independence of basic events. In addition, system unavailability and expected number of system failures are computed by the code.« less

  13. Incidence of q statistics in rank distributions

    PubMed Central

    Yalcin, G. Cigdem; Robledo, Alberto; Gell-Mann, Murray

    2014-01-01

    We show that size-rank distributions with power-law decay (often only over a limited extent) observed in a vast number of instances in a widespread family of systems obey Tsallis statistics. The theoretical framework for these distributions is analogous to that of a nonlinear iterated map near a tangent bifurcation for which the Lyapunov exponent is negligible or vanishes. The relevant statistical–mechanical expressions associated with these distributions are derived from a maximum entropy principle with the use of two different constraints, and the resulting duality of entropy indexes is seen to portray physically relevant information. Whereas the value of the index α fixes the distribution’s power-law exponent, that for the dual index 2 − α ensures the extensivity of the deformed entropy. PMID:25189773

  14. Randomized parallel speedups for list ranking

    SciTech Connect

    Vishkin, U.

    1987-06-01

    The following problem is considered: given a linked list of length n, compute the distance of each element of the linked list from the end of the list. The problem has two standard deterministic algorithms: a linear time serial algorithm, and an O(n log n)/ rho + log n) time parallel algorithm using rho processors. The authors present a randomized parallel algorithm for the problem. The algorithm is designed for an exclusive-read exclusive-write parallel random access machine (EREW PRAM). It runs almost surely in time O(n/rho + log n log* n) using rho processors. Using a recently published parallel prefix sums algorithm the list-ranking algorithm can be adapted to run on a concurrent-read concurrent-write parallel random access machine (CRCW PRAM) almost surely in time O(n/rho + log n) using rho processors.

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

    NASA Astrophysics Data System (ADS)

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

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

  16. CO2 Sequestration Potential of Texas Low-Rank Coals

    SciTech Connect

    Duane McVay; Walter Ayers, Jr.; Jerry Jensen; Jorge Garduno; Gonzola Hernandez; Rasheed Bello; Rahila Ramazanova

    2006-08-31

    Injection of CO{sub 2} in coalbeds is a plausible method of reducing atmospheric emissions of CO{sub 2}, and it can have the additional benefit of enhancing methane recovery from coal. Most previous studies have evaluated the merits of CO{sub 2} disposal in high-rank coals. The objective of this research was to determine the technical and economic feasibility of CO{sub 2} sequestration in, and enhanced coalbed methane (ECBM) recovery from, low-rank coals in the Texas Gulf Coast area. Our research included an extensive coal characterization program, including acquisition and analysis of coal core samples and well transient test data. We conducted deterministic and probabilistic reservoir simulation and economic studies to evaluate the effects of injectant fluid composition (pure CO{sub 2} and flue gas), well spacing, injection rate, and dewatering on CO{sub 2} sequestration and ECBM recovery in low-rank coals of the Calvert Bluff formation of the Texas Wilcox Group. Shallow and deep Calvert Bluff coals occur in two, distinct, coalbed gas petroleum systems that are separated by a transition zone. Calvert Bluff coals < 3,500 ft deep are part of a biogenic coalbed gas system. They have low gas content and are part of a freshwater aquifer. In contrast, Wilcox coals deeper than 3,500 ft are part of a thermogenic coalbed gas system. They have high gas content and are part of a saline aquifer. CO{sub 2} sequestration and ECBM projects in Calvert Bluff low-rank coals of East-Central Texas must be located in the deeper, unmineable coals, because shallow Wilcox coals are part of a protected freshwater aquifer. Probabilistic simulation of 100% CO{sub 2} injection into 20 feet of Calvert Bluff coal in an 80-acre 5-spot pattern indicates that these coals can store 1.27 to 2.25 Bcf of CO{sub 2} at depths of 6,200 ft, with an ECBM recovery of 0.48 to 0.85 Bcf. Simulation results of flue gas injection (87% N{sub 2}-13% CO{sub 2}) indicate that these same coals can store 0.34 to 0

  17. Discovering Motifs in Ranked Lists of DNA Sequences

    PubMed Central

    Eden, Eran; Lipson, Doron; Yogev, Sivan; Yakhini, Zohar

    2007-01-01

    Computational methods for discovery of sequence elements that are enriched in a target set compared with a background set are fundamental in molecular biology research. One example is the discovery of transcription factor binding motifs that are inferred from ChIP–chip (chromatin immuno-precipitation on a microarray) measurements. Several major challenges in sequence motif discovery still require consideration: (i) the need for a principled approach to partitioning the data into target and background sets; (ii) the lack of rigorous models and of an exact p-value for measuring motif enrichment; (iii) the need for an appropriate framework for accounting for motif multiplicity; (iv) the tendency, in many of the existing methods, to report presumably significant motifs even when applied to randomly generated data. In this paper we present a statistical framework for discovering enriched sequence elements in ranked lists that resolves these four issues. We demonstrate the implementation of this framework in a software application, termed DRIM (discovery of rank imbalanced motifs), which identifies sequence motifs in lists of ranked DNA sequences. We applied DRIM to ChIP–chip and CpG methylation data and obtained the following results. (i) Identification of 50 novel putative transcription factor (TF) binding sites in yeast ChIP–chip data. The biological function of some of them was further investigated to gain new insights on transcription regulation networks in yeast. For example, our discoveries enable the elucidation of the network of the TF ARO80. Another finding concerns a systematic TF binding enhancement to sequences containing CA repeats. (ii) Discovery of novel motifs in human cancer CpG methylation data. Remarkably, most of these motifs are similar to DNA sequence elements bound by the Polycomb complex that promotes histone methylation. Our findings thus support a model in which histone methylation and CpG methylation are mechanistically linked. Overall

  18. Deep Ranking for Person Re-Identification via Joint Representation Learning

    NASA Astrophysics Data System (ADS)

    Chen, Shi-Zhe; Guo, Chun-Chao; Lai, Jian-Huang

    2016-05-01

    This paper proposes a novel approach to person re-identification, a fundamental task in distributed multi-camera surveillance systems. Although a variety of powerful algorithms have been presented in the past few years, most of them usually focus on designing hand-crafted features and learning metrics either individually or sequentially. Different from previous works, we formulate a unified deep ranking framework that jointly tackles both of these key components to maximize their strengths. We start from the principle that the correct match of the probe image should be positioned in the top rank within the whole gallery set. An effective learning-to-rank algorithm is proposed to minimize the cost corresponding to the ranking disorders of the gallery. The ranking model is solved with a deep convolutional neural network (CNN) that builds the relation between input image pairs and their similarity scores through joint representation learning directly from raw image pixels. The proposed framework allows us to get rid of feature engineering and does not rely on any assumption. An extensive comparative evaluation is given, demonstrating that our approach significantly outperforms all state-of-the-art approaches, including both traditional and CNN-based methods on the challenging VIPeR, CUHK-01 and CAVIAR4REID datasets. Additionally, our approach has better ability to generalize across datasets without fine-tuning.

  19. Deep Ranking for Person Re-Identification via Joint Representation Learning.

    PubMed

    Chen, Shi-Zhe; Guo, Chun-Chao; Lai, Jian-Huang

    2016-05-01

    This paper proposes a novel approach to person re-identification, a fundamental task in distributed multi-camera surveillance systems. Although a variety of powerful algorithms have been presented in the past few years, most of them usually focus on designing hand-crafted features and learning metrics either individually or sequentially. Different from previous works, we formulate a unified deep ranking framework that jointly tackles both of these key components to maximize their strengths. We start from the principle that the correct match of the probe image should be positioned in the top rank within the whole gallery set. An effective learning-to-rank algorithm is proposed to minimize the cost corresponding to the ranking disorders of the gallery. The ranking model is solved with a deep convolutional neural network (CNN) that builds the relation between input image pairs and their similarity scores through joint representation learning directly from raw image pixels. The proposed framework allows us to get rid of feature engineering and does not rely on any assumption. An extensive comparative evaluation is given, demonstrating that our approach significantly outperforms all the state-of-the-art approaches, including both traditional and CNN-based methods on the challenging VIPeR, CUHK-01, and CAVIAR4REID datasets. In addition, our approach has better ability to generalize across datasets without fine-tuning. PMID:27019494

  20. Different ranking approaches defining association and agreement measures of paired ordinal data.

    PubMed

    Svensson, Elisabeth

    2012-11-20

    Rating scales are common for self-assessments of qualitative variables and also for expert-rating of the severity of disability, outcomes, etc. Scale assessments and other ordered classifications generate ordinal data having rank-invariant properties only. Hence, statistical methods are often based on ranks. The aim is to focus at the differences in ranking approaches between measures of association and of disagreement in paired ordinal data. The Spearman correlation coefficient is a measure of association between two variables, when each data set is transformed to ranks. The augmented ranking approach to evaluate disagreement takes account of the information given by the pairs of data, and provides identification and measures of systematic disagreement, when present, separately from measures of additional individual variability in assessments. The two approaches were applied to empirical data regarding relationship between perceived pain and physical health and reliability in pain assessments made by patients. The art of disagreement between the patients' perceived levels of outcome after treatment and the doctor's criterion-based scoring was also evaluated. The comprehensive evaluation of observed disagreement in terms of systematic and individual disagreement provides valuable interpretable information of their sources. The presence of systematic disagreement can be adjusted for and/or understood. Large individual variability could be a sign of poor quality of a scale or heterogeneity among raters. It was also demonstrated that a measure of association must not be used as a measure of agreement, even though such misuse of correlation coefficients is common. PMID:22714677