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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. 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…

  3. 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.

  4. Comparisons of infant mortality using a percentile-based method of standardization for birthweight or gestational age.

    PubMed

    Hertz-Picciotto, I; Din-Dzietham, R

    1998-01-01

    Comparisons of infant, perinatal, or neonatal mortality across populations with different birthweight or gestational age distributions are problematic. Summary measures with adjustment for birthweight or gestational age frequently are invalid or lack interpretability. We propose a percentile-based method of standardization for comparing infant, perinatal, or neonatal mortality across populations that have different distributions of birthweight and/or gestational age. The underlying concept is a simple one: comparable health for two population groups will be expressed as equal rates of disease or mortality at equal quantiles in the two distributions of birthweight or gestational age. We describe this method mathematically and present an example comparing mortality rates for African-American vs European-American infants in North Carolina. When gestational age is transformed to its rank, the well-known crossover in mortality rates, in which preterm African-American infants die at lower rates but term infants at higher rates, disappears: African-Americans show higher mortality rates at any percentile of gestational age. With homogeneous mortality rate ratios, a summary statistic becomes meaningful. We also demonstrate adjustment for percentile-transformed gestational age or birthweight in multiple logistic regression models. Percentile standardization is easily implemented, has advantages over other methods of internal standardization such as that of Wilcox and Russell, and communicates an intuitive public health-based concept of equality of mortality across populations.

  5. 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.

  6. Contrasting OLS and Quantile Regression Approaches to Student "Growth" Percentiles

    ERIC Educational Resources Information Center

    Castellano, Katherine Elizabeth; Ho, Andrew Dean

    2013-01-01

    Regression methods can locate student test scores in a conditional distribution, given past scores. This article contrasts and clarifies two approaches to describing these locations in terms of readily interpretable percentile ranks or "conditional status percentile ranks." The first is Betebenner's quantile regression approach that results in…

  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. The rank product method with two samples.

    PubMed

    Koziol, James A

    2010-11-05

    Breitling et al. (2004) introduced a statistical technique, the rank product method, for detecting differentially regulated genes in replicated microarray experiments. The technique has achieved widespread acceptance and is now used more broadly, in such diverse fields as RNAi analysis, proteomics, and machine learning. In this note, we extend the rank product method to the two sample setting, provide distribution theory attending the rank product method in this setting, and give numerical details for implementing the method.

  9. 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.

  10. Covariate Measurement Error Correction for Student Growth Percentiles Using the SIMEX Method

    ERIC Educational Resources Information Center

    Shang, Yi; VanIwaarden, Adam; Betebenner, Damian W.

    2015-01-01

    In this study, we examined the impact of covariate measurement error (ME) on the estimation of quantile regression and student growth percentiles (SGPs), and find that SGPs tend to be overestimated among students with higher prior achievement and underestimated among those with lower prior achievement, a problem we describe as ME endogeneity in…

  11. Testing for Correlation between Two Journal Ranking Methods: A Comparison of Citation Rankings and Expert Opinion Rankings.

    ERIC Educational Resources Information Center

    Russell, Robert Lowell, Jr.

    This study tests for correlation between two journal ranking methods--citation rankings and expert opinion surveys. Political science professors from four major universities were asked to rank a list of the 20 most highly cited political science journals. Citation data were taken from the "Social Sciences Citation Index Journal Citation…

  12. 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.

  13. Comments on the rank product method for analyzing replicated experiments.

    PubMed

    Koziol, James A

    2010-03-05

    Breitling et al. introduced a statistical technique, the rank product method, for detecting differentially regulated genes in replicated microarray experiments. The technique has achieved widespread acceptance and is now used more broadly, in such diverse fields as RNAi analysis, proteomics, and machine learning. In this note, we relate the rank product method to linear rank statistics and provide an alternative derivation of distribution theory attending the rank product method.

  14. 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

  15. 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.

  16. 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…

  17. Method for stabilizing dried low rank coals

    SciTech Connect

    Yan, T.Y.

    1987-03-17

    A method is described for protection of heated and dried pyrophoric particles, such as low rank coals, containing a reduced moisture content by treating the particles with a pyrophoric protection fluid within a vessel having a gas-solid separator in combination with a cooling fluid comprising: (a) introducing the heated and dried pyrophoric particles into a vessel which vessel lacks a means for supporting the particles during cooling thereof; (b) fluidizing the particles with the cooling fluid at ambient temperature; (c) applying a pyrophoric protection fluid to the fluidized particles thereby coating the particles sufficiently to cause at least a substantial portion of the particles to agglomerate and fall while simultaneously cooling the agglomerated particles; and (d) removing continuously the agglomerated cooled particles and the cooling fluid from the vessel. The method is also described where in step (b) the pyrophoric protection fluid is at least one member selected from the group consisting of petroleum residual oil, heavy oil, a mixture of tall oil and rosin, and gelatinized starch, in an amount of from about 0.01 weight percent to about 5 weight percent of the particles.

  18. 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…

  19. A Trust Ranking Method to Prevent IM Spam

    NASA Astrophysics Data System (ADS)

    Bi, Jun

    The problem of IM (Instant Messaging) SPAM, also known as SPIM, has become a challenge in recent years. The current anti-SPAM methods are not quite suitable for SPIM because of the differences in system infrastructures and characteristics between IM and email service. In order to effectively eliminate SPIM, we propose a trust ranking method in this paper. The mechanism to build up reputation network, global reputation and local trust ranking algorithms, reputation management, and SPIM filtering methods are presented. The experiments under five treat modes and algorithms enhancement are also introduced. The experiment shows that the proposed method is resilient to deal with SPIM attacks under several threat models.

  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. A Survey and Empirical Comparison of Object Ranking Methods

    NASA Astrophysics Data System (ADS)

    Kamishima, Toshihiro; Kazawa, Hideto; Akaho, Shotaro

    Ordered lists of objects are widely used as representational forms. Such ordered objects include Web search results or bestseller lists. In spite of their importance, methods of processing orders have received little attention. However, research concerning orders has recently become common; in particular, researchers have developed various methods for the task of Object Ranking to acquire functions for object sorting from example orders. Here, we give a unified view of these methods and compare their merits and demerits.

  2. 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

  3. Network selection: a method for ranked lists selection.

    PubMed

    Cutillo, Luisa; Carissimo, Annamaria; 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.

  4. Methods for Ranking and Selection in Large-Scale Inference

    NASA Astrophysics Data System (ADS)

    Henderson, Nicholas C.

    This thesis addresses two distinct problems: one related to ranking and selection for large-scale inference and another related to latent class modeling of longitudinal count data. The first part of the thesis focuses on the problem of identifying leading measurement units from a large collection with a focus on settings with differing levels of estimation precision across measurement units. The main approach presented is a Bayesian ranking procedure that populates the list of top units in a way that maximizes the expected overlap between the true and reported top lists for all list sizes. This procedure relates unit-specific posterior upper tail probabilities with their empirical distribution to yield a ranking variable. It discounts high-variance units less than other common methods and thus achieves improved operating characteristics in the models considered. In the second part of the thesis, we introduce and describe a finite mixture model for longitudinal count data where, conditional on the class label, the subject-specific observations are assumed to arise from a discrete autoregressive process. This approach offers notable computational advantages over related methods due to the within-class closed form of the likelihood function and, as we describe, has a within-class correlation structure which improves model identifiability. We also outline computational strategies for estimating model parameters, and we describe a novel measure of the underlying separation between latent classes and discuss its relation to posterior classification.

  5. 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.

  6. 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.

  7. Note: A manifold ranking based saliency detection method for camera

    NASA Astrophysics Data System (ADS)

    Zhang, Libo; Sun, Yihan; Luo, Tiejian; Rahman, Mohammad Muntasir

    2016-09-01

    Research focused on salient object region in natural scenes has attracted a lot in computer vision and has widely been used in many applications like object detection and segmentation. However, an accurate focusing on the salient region, while taking photographs of the real-world scenery, is still a challenging task. In order to deal with the problem, this paper presents a novel approach based on human visual system, which works better with the usage of both background prior and compactness prior. In the proposed method, we eliminate the unsuitable boundary with a fixed threshold to optimize the image boundary selection which can provide more precise estimations. Then, the object detection, which is optimized with compactness prior, is obtained by ranking with background queries. Salient objects are generally grouped together into connected areas that have compact spatial distributions. The experimental results on three public datasets demonstrate that the precision and robustness of the proposed algorithm have been improved obviously.

  8. 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)

  9. ContrastRank: a new method for ranking putative cancer driver genes and classification of tumor samples

    PubMed Central

    Tian, Rui; Basu, Malay K.; Capriotti, Emidio

    2014-01-01

    Motivation: The recent advance in high-throughput sequencing technologies is generating a huge amount of data that are becoming an important resource for deciphering the genotype underlying a given phenotype. Genome sequencing has been extensively applied to the study of the cancer genomes. Although a few methods have been already proposed for the detection of cancer-related genes, their automatic identification is still a challenging task. Using the genomic data made available by The Cancer Genome Atlas Consortium (TCGA), we propose a new prioritization approach based on the analysis of the distribution of putative deleterious variants in a large cohort of cancer samples. Results: In this paper, we present ContastRank, a new method for the prioritization of putative impaired genes in cancer. The method is based on the comparison of the putative defective rate of each gene in tumor versus normal and 1000 genome samples. We show that the method is able to provide a ranked list of putative impaired genes for colon, lung and prostate adenocarcinomas. The list significantly overlaps with the list of known cancer driver genes previously published. More importantly, by using our scoring approach, we can successfully discriminate between TCGA normal and tumor samples. A binary classifier based on ContrastRank score reaches an overall accuracy >90% and the area under the curve (AUC) of receiver operating characteristics (ROC) >0.95 for all the three types of adenocarcinoma analyzed in this paper. In addition, using ContrastRank score, we are able to discriminate the three tumor types with a minimum overall accuracy of 77% and AUC of 0.83. Conclusions: We describe ContrastRank, a method for prioritizing putative impaired genes in cancer. The method is based on the comparison of exome sequencing data from different cohorts and can detect putative cancer driver genes. ContrastRank can also be used to estimate a global score for an individual genome about the risk of

  10. Method or Madness? Inside the "SNWR" College Rankings.

    ERIC Educational Resources Information Center

    Ehrenberg, Ronald G.

    This paper examines why Americans are so preoccupied with the "U.S. News and World Report" ("USNWR") annual rankings of colleges and universities and why higher education institutions have become equally preoccupied with them. It discusses the rankings categories (academic reputation, student selectivity, faculty resources,…

  11. New methods to identify and rank high pedestrian crash zones: an illustration.

    PubMed

    Pulugurtha, Srinivas S; Krishnakumar, Vanjeeswaran K; Nambisan, Shashi S

    2007-07-01

    Identifying and ranking high pedestrian crash zones plays a key role in developing efficient and effective strategies to enhance pedestrian safety. This paper presents (1) a Geographical Information Systems (GIS) methodology to study the spatial patterns of pedestrian crashes in order to identify high pedestrian crash zones, and (2) an evaluation of methods to rank these high pedestrian crash zones. The GIS based methodology to identify high pedestrian crash zones includes geocoding crash data, creating crash concentration maps, and then identifying high pedestrian crash zones. Two methods generally used to create crash concentration maps based on density values are the Simple Method and the Kernel Method. Ranking methods such as crash frequency, crash density, and crash rate, as well as composite methods such as the sum-of-the-ranks and the crash score methods are used to rank the selected high pedestrian crash zones. The use of this methodology and ranking methods for high pedestrian crash zones are illustrated using the Las Vegas metropolitan area as the study area. Crash data collected for a 5-year period (1998-2002) were address matched using the street name/reference street name intersection location reference system. A crash concentration map was then created using the Kernel Method as it facilitates the creation of a smooth density surface when compared to the Simple Method. Twenty-two linear high crash zones and seven circular high crash zones were then identified. The GIS based methodology reduced the subjectivity in the analysis process. Results obtained from the evaluation of methods to rank high pedestrian crash zones show a significant variation in ranking when individual methods were considered. However, rankings of high pedestrian crash zones were relatively consistent with little to no variation when the sum-of-the-ranks method and the crash score method were used. Thus, these composite methods are recommended for use in ranking high pedestrian

  12. 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.

  13. 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

  14. Methods to rank traffic rule violations resulting in crashes for allocation of funds.

    PubMed

    Penmetsa, Praveena; Pulugurtha, Srinivas S

    2017-02-01

    Education, enforcement and engineering countermeasures are implemented to make road users comply with the traffic rules. Not all the traffic rule violations can be addressed nor countermeasures be implemented at all unsafe locations, at once, due to limited funds. Therefore, this study aims at ranking the traffic rule violations resulting in crashes based on individual ranks, such as 1) frequency (expressed as a function of the number of drivers violating a traffic rule and involved in crashes), 2) crash severity, 3) total crash cost, and, 4) cost severity index, to assist transportation system managers in prioritizing the allocation of funds and improving safety on roads. Crash data gathered for the state of North Carolina was processed and used in this study. Variations in the ranks of traffic rule violations were observed when individual ranking methods are used. As an example, exceeding authorized speed limit and driving under the influence of alcohol are ranked 1st and 2nd based on crash severity while failure to reduce speed and failure to yield the right-of-way are ranked 1st and 2nd based on frequency. To minimize the variations and capture the merits of individual ranking methods, four different composite ranks were computed by combining selected individual ranks. The computed averages and standard deviations of absolute rank differences between composite ranks is lower than those obtained from individual ranks. The weights to combine the selected individual ranks have a marginal effect on the computed averages and standard deviations of absolute rank differences. Combining frequency and crash severity or cost severity index, using equal weights, is recommended for prioritization and allocation of funds.

  15. 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.

  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. 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.

  18. 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.

  19. 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.

  20. 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.

  1. Development of geopolitically relevant ranking criteria for geoengineering methods

    NASA Astrophysics Data System (ADS)

    Boyd, Philip W.

    2016-11-01

    A decade has passed since Paul Crutzen published his editorial essay on the potential for stratospheric geoengineering to cool the climate in the Anthropocene. He synthesized the effects of the 1991 Pinatubo eruption on the planet's radiative budget and used this large-scale event to broaden and deepen the debate on the challenges and opportunities of large-scale geoengineering. Pinatubo had pronounced effects, both in the short and longer term (months to years), on the ocean, land, and the atmosphere. This rich set of data on how a large-scale natural event influences many regional and global facets of the Earth System provides a comprehensive viewpoint to assess the wider ramifications of geoengineering. Here, I use the Pinatubo archives to develop a range of geopolitically relevant ranking criteria for a suite of different geoengineering approaches. The criteria focus on the spatial scales needed for geoengineering and whether large-scale dispersal is a necessary requirement for a technique to deliver significant cooling or carbon dioxide reductions. These categories in turn inform whether geoengineering approaches are amenable to participation (the "democracy of geoengineering") and whether they will lead to transboundary issues that could precipitate geopolitical conflicts. The criteria provide the requisite detail to demarcate different geoengineering approaches in the context of geopolitics. Hence, they offer another tool that can be used in the development of a more holistic approach to the debate on geoengineering.

  2. 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.

  3. 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.

  4. A novel document ranking method using the discrete cosine transform.

    PubMed

    Park, Laurence A F; Palaniswami, Marimuthu; Ramamohanarao, Kotagiri

    2005-01-01

    We propose a new Spectral text retrieval method using the Discrete Cosine Transform (DCT). By taking advantage of the properties of the DCT and by employing the fast query and compression techniques found in vector space methods (VSM), we show that we can process queries as fast as VSM and achieve a much higher precision.

  5. 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

  6. Assessment of Entrepreneurial Territorial Attractiveness by the Ranking Method

    ERIC Educational Resources Information Center

    Gavrilova, Marina A.; Shepelev, Victor M.; Kosyakova, Inessa V.; Belikova, Lyudmila F.; Chistik, Olga F.

    2016-01-01

    The relevance of the researched problem is caused by existence of differentiation in development of separate regional units (urban districts and municipalities) within the region. The aim of this article is to offer a method, which determines the level of differentiation in development of various components of the region, and also in producing a…

  7. Ranking filter methods for concentrating pathogens in lake water

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Accurately comparing filtration methods for concentrating waterborne pathogens is difficult because of two important water matrix effects on recovery measurements, the effect on PCR quantification and the effect on filter performance. Regarding the first effect, we show how to create a control water...

  8. Low-rank approximations with sparse factors II: Penalized methods with discrete Newton-like iterations

    SciTech Connect

    Zhang, Zhenyue; Zha, Hongyuan; Simon, Horst

    2006-07-31

    In this paper, we developed numerical algorithms for computing sparse low-rank approximations of matrices, and we also provided a detailed error analysis of the proposed algorithms together with some numerical experiments. The low-rank approximations are constructed in a certain factored form with the degree of sparsity of the factors controlled by some user-specified parameters. In this paper, we cast the sparse low-rank approximation problem in the framework of penalized optimization problems. We discuss various approximation schemes for the penalized optimization problem which are more amenable to numerical computations. We also include some analysis to show the relations between the original optimization problem and the reduced one. We then develop a globally convergent discrete Newton-like iterative method for solving the approximate penalized optimization problems. We also compare the reconstruction errors of the sparse low-rank approximations computed by our new methods with those obtained using the methods in the earlier paper and several other existing methods for computing sparse low-rank approximations. Numerical examples show that the penalized methods are more robust and produce approximations with factors which have fewer columns and are sparser.

  9. 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}).

  10. 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)

  11. 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.

  12. 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.

  13. Using the Friedman Method of Ranks for Model Comparison in Structural Equation Modeling.

    ERIC Educational Resources Information Center

    Rigdon, Edward E.

    1999-01-01

    Explores the use of the Friedman method of ranks (H. Friedman, 1937) as an inferential procedure for evaluating competing models in structural-equation modeling. Describes the attractive features of this approach, but raises important issues regarding the lack of independence of observations and the power of the test. (SLD)

  14. An Optimization-Based Method for Feature Ranking in Nonlinear Regression Problems.

    PubMed

    Bravi, Luca; Piccialli, Veronica; Sciandrone, Marco

    2016-02-03

    In this paper, we consider the feature ranking problem, where, given a set of training instances, the task is to associate a score with the features in order to assess their relevance. Feature ranking is a very important tool for decision support systems, and may be used as an auxiliary step of feature selection to reduce the high dimensionality of real-world data. We focus on regression problems by assuming that the process underlying the generated data can be approximated by a continuous function (for instance, a feedforward neural network). We formally state the notion of relevance of a feature by introducing a minimum zero-norm inversion problem of a neural network, which is a nonsmooth, constrained optimization problem. We employ a concave approximation of the zero-norm function, and we define a smooth, global optimization problem to be solved in order to assess the relevance of the features. We present the new feature ranking method based on the solution of instances of the global optimization problem depending on the available training data. Computational experiments on both artificial and real data sets are performed, and point out that the proposed feature ranking method is a valid alternative to existing methods in terms of effectiveness. The obtained results also show that the method is costly in terms of CPU time, and this may be a limitation in the solution of large-dimensional problems.

  15. 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…

  16. The application of low-rank and sparse decomposition method in the field of climatology

    NASA Astrophysics Data System (ADS)

    Gupta, Nitika; Bhaskaran, Prasad K.

    2017-03-01

    The present study reports a low-rank and sparse decomposition method that separates the mean and the variability of a climate data field. Until now, the application of this technique was limited only in areas such as image processing, web data ranking, and bioinformatics data analysis. In climate science, this method exactly separates the original data into a set of low-rank and sparse components, wherein the low-rank components depict the linearly correlated dataset (expected or mean behavior), and the sparse component represents the variation or perturbation in the dataset from its mean behavior. The study attempts to verify the efficacy of this proposed technique in the field of climatology with two examples of real world. The first example attempts this technique on the maximum wind-speed (MWS) data for the Indian Ocean (IO) region. The study brings to light a decadal reversal pattern in the MWS for the North Indian Ocean (NIO) during the months of June, July, and August (JJA). The second example deals with the sea surface temperature (SST) data for the Bay of Bengal region that exhibits a distinct pattern in the sparse component. The study highlights the importance of the proposed technique used for interpretation and visualization of climate data.

  17. 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.

  18. 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.

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

    PubMed

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

    2015-07-01

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

  20. 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.

  1. Method for producing a dried coal fuel having a reduced tendency to spontaneously ignite from a low rank coal

    SciTech Connect

    Li, Y.H.; Bonnecaze, B.F.; Matthews, J.D.; Skinner, J.L.; Wunderlich, D.K.

    1983-08-02

    A method is disclosed for producing a dried coal fuel having a reduced tendency to spontaneously ignite from a low rank coal by drying the low rank coal and thereafter cooling the dried coal to a temperature below about 100/sup 0/F. Optionally the dried coal is partially oxidized prior to cooling and optionally the dried coal is mixed with a deactivating fluid.

  2. 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)

  3. Fold change rank ordering statistics: a new method for detecting differentially expressed genes

    PubMed Central

    2014-01-01

    Background Different methods have been proposed for analyzing differentially expressed (DE) genes in microarray data. Methods based on statistical tests that incorporate expression level variability are used more commonly than those based on fold change (FC). However, FC based results are more reproducible and biologically relevant. Results We propose a new method based on fold change rank ordering statistics (FCROS). We exploit the variation in calculated FC levels using combinatorial pairs of biological conditions in the datasets. A statistic is associated with the ranks of the FC values for each gene, and the resulting probability is used to identify the DE genes within an error level. The FCROS method is deterministic, requires a low computational runtime and also solves the problem of multiple tests which usually arises with microarray datasets. Conclusion We compared the performance of FCROS with those of other methods using synthetic and real microarray datasets. We found that FCROS is well suited for DE gene identification from noisy datasets when compared with existing FC based methods. PMID:24423217

  4. 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

  5. Ranking: a closer look on globalisation methods for normalisation of gene expression arrays

    PubMed Central

    Kroll, Torsten C.; Wölfl, Stefan

    2002-01-01

    Data from gene expression arrays are influenced by many experimental parameters that lead to variations not simply accessible by standard quantification methods. To compare measurements from gene expression array experiments, quantitative data are commonly normalised using reference genes or global normalisation methods based on mean or median values. These methods are based on the assumption that (i) selected reference genes are expressed at a standard level in all experiments or (ii) that mean or median signal of expression will give a quantitative reference for each individual experiment. We introduce here a new ranking diagram, with which we can show how the different normalisation methods compare, and how they are influenced by variations in measurements (noise) that occur in every experiment. Furthermore, we show that an upper trimmed mean provides a simple and robust method for normalisation of larger sets of experiments by comparative analysis. PMID:12034851

  6. 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

  7. 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

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

    PubMed

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

    2015-01-01

    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 Co-occurrence 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.

  9. Application of the rank-based method to DNA methylation for cancer diagnosis.

    PubMed

    Li, Hongdong; Hong, Guini; Xu, Hui; Guo, Zheng

    2015-01-25

    Detecting aberrant DNA methylation as diagnostic or prognostic biomarkers for cancer has been a topic of considerable interest recently. However, current classifiers based on absolute methylation values detected from a cohort of samples are typically difficult to be transferable to other cohorts of samples. Here, focusing on relative methylation levels, we employed a modified rank-based method to extract reversal pairs of CpG sites whose relative methylation level orderings differ between disease samples and normal controls for cancer diagnosis. The reversal pairs identified for five cancer types respectively show excellent prediction performance with the accuracy above 95%. Furthermore, when evaluating the reversal pairs identified for one cancer type in an independent cohorts of samples, we found that they could distinguish different subtypes of this cancer or different malignant stages including early stage of this cancer from normal controls. The identified reversal pairs also appear to be specific to cancer type. In conclusion, the reversal pairs detected by the rank-based method could be used for accurate cancer diagnosis, which are transferable to independent cohorts of samples.

  10. Evaluation of an automatic dry eye test using MCDM methods and rank correlation.

    PubMed

    Peteiro-Barral, Diego; Remeseiro, Beatriz; Méndez, Rebeca; Penedo, Manuel G

    2017-04-01

    Dry eye is an increasingly common disease in modern society which affects a wide range of population and has a negative impact on their daily activities, such as working with computers or driving. It can be diagnosed through an automatic clinical test for tear film lipid layer classification based on color and texture analysis. Up to now, researchers have mainly focused on the improvement of the image analysis step. However, there is still large room for improvement on the machine learning side. This paper presents a methodology to optimize this problem by means of class binarization, feature selection, and classification. The methodology can be used as a baseline in other classification problems to provide several solutions and evaluate their performance using a set of representative metrics and decision-making methods. When several decision-making methods are used, they may offer disagreeing rankings that will be solved by conflict handling in which rankings are merged into a single one. The experimental results prove the effectiveness of the proposed methodology in this domain. Also, its general purpose allows to adapt it to other classification problems in different fields such as medicine and biology.

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

    PubMed

    Kitsiou, Dimitra; Coccossis, Harry; Karydis, Michael

    2002-02-04

    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.

  12. 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.

  13. 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.

  14. PPIRank - an advanced method for ranking protein-protein interations in TAP/MS data

    PubMed Central

    2013-01-01

    Background Tandem affinity purification coupled with mass-spectrometry (TAP/MS) analysis is a popular method for the identification of novel endogenous protein-protein interactions (PPIs) in large-scale. Computational analysis of TAP/MS data is a critical step, particularly for high-throughput datasets, yet it remains challenging due to the noisy nature of TAP/MS data. Results We investigated several major TAP/MS data analysis methods for identifying PPIs, and developed an advanced method, which incorporates an improved statistical method to filter out false positives from the negative controls. Our method is named PPIRank that stands for PPI ranking in TAP/MS data. We compared PPIRank with several other existing methods in analyzing two pathway-specific TAP/MS PPI datasets from Drosophila. Conclusion Experimental results show that PPIRank is more capable than other approaches in terms of identifying known interactions collected in the BioGRID PPI database. Specifically, PPIRank is able to capture more true interactions and simultaneously less false positives in both Insulin and Hippo pathways of Drosophila Melanogaster. PMID:24565074

  15. Critical review of methods for risk ranking of food related hazards, based on risks for human health.

    PubMed

    van der Fels-Klerx, H J; van Asselt, E D; Raley, M; Poulsen, M; Korsgaard, H; Bredsdorff, L; Nauta, M; D'Agostino, M; Coles, D; Marvin, H J P; Frewer, L J

    2016-02-08

    This study aimed to critically review methods for ranking risks related to food safety and dietary hazards on the basis of their anticipated human health impacts. A literature review was performed to identify and characterize methods for risk ranking from the fields of food, environmental science and socio-economic sciences. The review used a predefined search protocol, and covered the bibliographic databases Scopus, CAB Abstracts, Web of Sciences, and PubMed over the period 1993-2013. All references deemed relevant, on the basis of of predefined evaluation criteria, were included in the review, and the risk ranking method characterized. The methods were then clustered - based on their characteristics - into eleven method categories. These categories included: risk assessment, comparative risk assessment, risk ratio method, scoring method, cost of illness, health adjusted life years, multi-criteria decision analysis, risk matrix, flow charts/decision trees, stated preference techniques and expert synthesis. Method categories were described by their characteristics, weaknesses and strengths, data resources, and fields of applications. It was concluded there is no single best method for risk ranking. The method to be used should be selected on the basis of risk manager/assessor requirements, data availability, and the characteristics of the method. Recommendations for future use and application are provided.

  16. Bias and imprecision in posture percentile variables estimated from short exposure samples

    PubMed Central

    2012-01-01

    Background Upper arm postures are believed to be an important risk determinant for musculoskeletal disorder development in the neck and shoulders. The 10th and 90th percentiles of the angular elevation distribution have been reported in many studies as measures of neutral and extreme postural exposures, and variation has been quantified by the 10th-90th percentile range. Further, the 50th percentile is commonly reported as a measure of "average" exposure. These four variables have been estimated using samples of observed or directly measured postures, typically using sampling durations between 5 and 120 min. Methods The present study examined the statistical properties of estimated full-shift values of the 10th, 50th and 90th percentile and the 10th-90th percentile range of right upper arm elevation obtained from samples of seven different durations, ranging from 5 to 240 min. The sampling strategies were realized by simulation, using a parent data set of 73 full-shift, continuous inclinometer recordings among hairdressers. For each shift, sampling duration and exposure variable, the mean, standard deviation and sample dispersion limits (2.5% and 97.5%) of all possible sample estimates obtained at one minute intervals were calculated and compared to the true full-shift exposure value. Results Estimates of the 10th percentile proved to be upward biased with limited sampling, and those of the 90th percentile and the percentile range, downward biased. The 50th percentile was also slightly upwards biased. For all variables, bias was more severe with shorter sampling durations, and it correlated significantly with the true full-shift value for the 10th and 90th percentiles and the percentile range. As expected, shorter samples led to decreased precision of the estimate; sample standard deviations correlated strongly with true full-shift exposure values. Conclusions The documented risk of pronounced bias and low precision of percentile estimates obtained from short

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

    PubMed

    Astivia, Oscar L Olvera; Zumbo, Bruno D

    2017-01-31

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

  18. Comparisons of methods for determining dominance rank in male and female prairie voles (Microtus ochrogastor)

    USGS Publications Warehouse

    Lanctot, Richard B.; Best, Louis B.

    2000-01-01

    Dominance ranks in male and female prairie voles (Microtus ochrogaster) were determined from 6 measurements that mimicked environmental situations that might be encountered by prairie voles in communal groups, including agonistic interactions resulting from competition for food and water and encounters in burrows. Male and female groups of 6 individuals each were tested against one another in pairwise encounters (i.e., dyads) for 5 of the measurements and together as a group in a 6th measurement. Two types of response variables, aggressive behaviors and possession time of a limiting resource, were collected during trials, and those data were used to determine cardinal ranks and principal component ranks for all animals within each group. Cardinal ranks and principal component ranks seldom yielded similar rankings for each animal across measurements. However, dominance measurements that were conducted in similar environmental contexts, regardless of the response variable recorded, ranked animals similarly. Our results suggest that individual dominance measurements assessed situation- or resource-specific responses. Our study demonstrates problems inherent in determining dominance rankings of individuals within groups, including choosing measurements, response variables, and statistical techniques. Researchers should avoid using a single measurement to represent social dominance until they have first demonstrated that a dominance relationship between 2 individuals has been learned (i.e., subsequent interactions show a reduced response rather than an escalation), that this relationship is relatively constant through time, and that the relationship is not context dependent. Such assessments of dominance status between all dyads then can be used to generate dominance rankings within social groups.

  19. Consistency of dominance rank order: a comparison of David's Scores with I&SI and Bayesian methods in macaques.

    PubMed

    Balasubramaniam, K N; Berman, C M; De Marco, A; Dittmar, K; Majolo, B; Ogawa, H; Thierry, B; De Vries, H

    2013-09-01

    In nonhuman primate social groups, dominance ranks are usually assigned to individuals based on outcomes of dyadic agonistic encounters. Multiple approaches have been used, but currently there is no consensus. One approach, David's Scores (DS), offers dual advantages of yielding cardinal scores that may in turn be used to compute hierarchical steepness. Here we correlate rank orders yielded by DS with those yielded by both the traditionally used I&SI approach and the recently proposed parametric Bayesian approach. We use six datasets for female macaques (three despotic and three tolerant groups), and 90 artificially generated datasets modeling macaque groups. We also use the artificial datasets to determine the impact of three characteristics (group size, interaction frequency, and directional asymmetry of aggression) on the magnitude of correlation coefficients, and assess the relative utility of two indices used to compute DS: Dij versus Pij. DS-based rank orders were strongly positively correlated with those yielded by the other two approaches for five out of the six macaque datasets, and for the majority of artificial datasets. Magnitudes of correlation coefficients were unrelated to group size or interaction frequency, but increased with directional asymmetry, suggesting methodological inconsistencies were more likely when dyads had more frequent reversals in directions of aggression. Finally, rank orders calculated using the Dij and Pij indices were similarly consistent with orders from other methods. We conclude that DS offers consistent estimates of rank orders, except perhaps in groups with very low levels of aggression asymmetry. In such "tolerant" groups, we suggest that the relatively greater methodological variability in rank orders may reflect behavioral characteristics of tolerant groups rather than computational inconsistencies between methods. We hypothesize that this quality may be quantified using posterior probability scores of Bayesian rank

  20. 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.

  1. Improved Parker's method for topographic models using Chebyshev series and low rank approximation

    NASA Astrophysics Data System (ADS)

    Wu, Leyuan; Lin, Qiang

    2017-03-01

    We present a new method to improve the convergence of the well-known Parker's formula for the modelling of gravity and magnetic fields caused by sources with complex topography. In the original Parker's formula, two approximations are made, which may cause considerable numerical errors and instabilities: 1) the approximation of the forward and inverse continuous Fourier transforms using their discrete counterparts, the forward and inverse Fast Fourier Transform (FFT) algorithms; 2) the approximation of the exponential function with its Taylor series expansion. In a previous paper of ours, we have made an effort addressing the first problem by applying the Gauss-FFT method instead of the standard FFT algorithm. The new Gauss-FFT based method shows improved numerical efficiency and agrees well with space-domain analytical or hybrid analytical-numerical algorithms. However, even under the simplifying assumption of a calculation surface being a level plane above all topographic sources, the method may still fail or become inaccurate under certain circumstances. When the peaks of the topography approach the observation surface too closely, the number of terms of the Taylor series expansion needed to reach a suitable precision becomes large and slows the calculation. We show in this paper that this problem is caused by the second approximation mentioned above, and it is due to the convergence property of the Taylor series expansion that the algorithm becomes inaccurate for certain topographic models with large amplitudes. Based on this observation, we present a modified Parker's method using low rank approximation (LRA) of the exponential function in virtue of the Chebfun software system. In this way, the optimal rate of convergence is achieved. Some pre-computation is needed but will not cause significant computational overheads. Synthetic and real model tests show that the method now works well for almost any practical topographic model, provided that the assumption

  2. 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.

  3. 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

  4. Patch-based denoising method using low-rank technique and targeted database for optical coherence tomography image.

    PubMed

    Liu, Xiaoming; Yang, Zhou; Wang, Jia; Liu, Jun; Zhang, Kai; Hu, Wei

    2017-01-01

    Image denoising is a crucial step before performing segmentation or feature extraction on an image, which affects the final result in image processing. In recent years, utilizing the self-similarity characteristics of the images, many patch-based image denoising methods have been proposed, but most of them, named the internal denoising methods, utilized the noisy image only where the performances are constrained by the limited information they used. We proposed a patch-based method, which uses a low-rank technique and targeted database, to denoise the optical coherence tomography (OCT) image. When selecting the similar patches for the noisy patch, our method combined internal and external denoising, utilizing the other images relevant to the noisy image, in which our targeted database is made up of these two kinds of images and is an improvement compared with the previous methods. Next, we leverage the low-rank technique to denoise the group matrix consisting of the noisy patch and the corresponding similar patches, for the fact that a clean image can be seen as a low-rank matrix and rank of the noisy image is much larger than the clean image. After the first-step denoising is accomplished, we take advantage of Gabor transform, which considered the layer characteristic of the OCT retinal images, to construct a noisy image before the second step. Experimental results demonstrate that our method compares favorably with the existing state-of-the-art methods.

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

    SciTech Connect

    Carson, Susan D.; Hunter, Regina L.; Link, Madison D.; Browitt, Robert D.

    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.

  6. Using weight-for-age percentiles to screen for overweight and obese children and adolescents.

    PubMed

    Gamliel, Adir; Ziv-Baran, Tomer; Siegel, Robert M; Fogelman, Yacov; Dubnov-Raz, Gal

    2015-12-01

    There are relatively low rates of screening for overweight and obesity among children and adolescents in primary care. A simplified method for such screening is needed. The study objective was to examine if weight-for-age percentiles are sufficiently sensitive in identifying overweight and obesity in children and adolescents. We used data from two distinct sources: four consecutive cycles of the National Health and Nutrition Examination Surveys (NHANES) from the years 2005 to 2012, using participants aged 2-17.9 years for whom data on age, sex, weight, and height were available (n=12,884), and primary care clinic measurements (n=15,152). Primary outcomes were the threshold values of weight-for-age percentiles which best discriminated between normal weight, overweight, and obesity status. Receiver operating characteristic analyses demonstrated that weight-for-age percentiles well discriminated between normal weight and overweight and between non-obese and obese individuals (area under curve=0.956 and 0.977, respectively, both p<0.001). Following Classification and Regression Trees analysis, the 90th and 75th weight-for-age percentiles were chosen as appropriate cutoffs for obesity and overweight, respectively. These cutoffs had high sensitivity and negative predictive value in identifying obese participants (94.3% and 98.6%, respectively, for the 90th percentile) and in identifying overweight participants (93.2% and 95.9%, respectively, for the 75th percentile). The sensitivities and specificities were nearly identical across race and sex, and in the validation data from NHANES 2011 to 2012 and primary care. We conclude that weight-for-age percentiles can discriminate between normal weight, overweight and obese children, and adolescents. The 75th and 90th weight-for-age percentiles correspond well with the BMI cutoffs for pediatric overweight and obesity, respectively.

  7. Reference percentiles for FEV1 and BMI in European children and adults with cystic fibrosis

    PubMed Central

    2012-01-01

    Background The clinical course of Cystic Fibrosis (CF) is usually measured using the percent predicted FEV1 and BMI Z-score referenced against a healthy population, since achieving normality is the ultimate goal of CF care. Referencing against age and sex matched CF peers may provide valuable information for patients and for comparison between CF centers or populations. Here, we used a large database of European CF patients to compute CF specific reference equations for FEV1 and BMI, derived CF-specific percentile charts and compared these European data to their nearest international equivalents. Methods 34859 FEV1 and 40947 BMI observations were used to compute European CF specific percentiles. Quantile regression was applied to raw measurements as a function of sex, age and height. Results were compared with the North American equivalent for FEV1 and with the WHO 2007 normative values for BMI. Results FEV1 and BMI percentiles illustrated the large variability between CF patients receiving the best current care. The European CF specific percentiles for FEV1 were significantly different from those in the USA from an earlier era, with higher lung function in Europe. The CF specific percentiles for BMI declined relative to the WHO standard in older children. Lung function and BMI were similar in the two largest contributing European Countries (France and Germany). Conclusion The CF specific percentile approach applied to FEV1 and BMI allows referencing patients with respect to their peers. These data allow peer to peer and population comparisons in CF patients. PMID:22958330

  8. The sensitivity of relative toxicity rankings by the USF/NASA test method to some test variables

    NASA Technical Reports Server (NTRS)

    Hilado, C. J.; Labossiere, L. A.; Leon, H. A.; Kourtides, D. A.; Parker, J. A.; Hsu, M.-T. S.

    1976-01-01

    Pyrolysis temperature and the distance between the source and sensor of effluents are two important variables in tests for relative toxicity. Modifications of the USF/NASA toxicity screening test method to increase the upper temperature limit of pyrolysis, reduce the distance between the sample and the test animals, and increase the chamber volume available for animal occupancy, did not significantly alter rankings of relative toxicity of four representative materials. The changes rendered some differences no longer significant, but did not reverse any rankings. The materials studied were cotton, wool, aromatic polyamide, and polybenzimidazole.

  9. Application of the Simplified Dow Chemical Company Relative Ranking Hazard Assessment Method for Air Combat Command Bases

    DTIC Science & Technology

    1993-09-01

    Superfund ( CERCLA ) requirement that parties report to the NRC hazardous substance releases exceeding specified reportable quantities. The Accidental...ranking hazard assessment method. Hazard assessment includes both the identification and evaluation of the hazards. Title III of the Superfund Amendments...accident has changed how the United States industry prepares for accidents. Because of this accident the United States passed the Superfund Amendments

  10. Outlier detection for the Generalized Rank Annihilation Method in HPLC-DAD analysis.

    PubMed

    Ferré, Joan; Comas, Enric

    2011-01-30

    The Generalized Rank Annihilation Method (GRAM) is a second-order calibration method that is used in chromatography to quantify analytes that coelute with interferences. For a correct quantification, the peak of the analyte in the standard and in the test sample must be aligned and have the same shape (i.e., have a trilinear structure). Variations in retention time and shape between the two peaks may cause the test sample to behave as an outlier and produce an incorrect prediction. This situation cannot be detected by checking the coincidence of the recovered spectrum with the known spectrum of the analyte because the spectral domain is not affected. It cannot be detected either by checking if the recovered profile is correct (i.e., unimodal and positive). Several plots are presented to detect such outliers. The first plot compares the particular elution profiles in the standard and in the test sample that are recovered by least-squares regression from the spectra estimated by GRAM. The calculated elution profiles from both peaks should coincide. A second plot uses the elution profiles and spectra calculated by GRAM to define the vector space spanned by the interferences. The measured peaks in the standard and in the test sample are projected onto the space that is orthogonal to the space spanned by the interferences. These projections are proportional (up to the noise) if data are trilinear. The proportionality is checked graphically from the first singular vector of the projected peaks, or from the plot of the orthogonal signal versus the net sensitivity. The use of these graphs is shown for simulated data and for the determination of 4-nitrophenol in river water samples with liquid chromatography/UV-Vis detection.

  11. A Value and Ambiguity-Based Ranking Method of Trapezoidal Intuitionistic Fuzzy Numbers and Application to Decision Making

    PubMed Central

    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

  12. 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

  13. 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.

  14. 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…

  15. A Data-Based Method of Ranking Department, Faculty and Journals in Professional Impact.

    ERIC Educational Resources Information Center

    Matson, Johnny L.; Lott, Julia D.; Bielecki, JoAnne

    2003-01-01

    Reviewed current popular rankings of clinical psychology schools and journals. Overall publication and citation records for full-time faculty at the top institutions were tabulated. Faculty members from the Department of Psychology at Louisiana State University were asked to list the most highly regarded journals in their specialty area. Rankings…

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

    PubMed

    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.

  17. 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

  18. Comparison of Document Index Graph Using TextRank and HITS Weighting Method in Automatic Text Summarization

    NASA Astrophysics Data System (ADS)

    Hadyan, Fadhlil; Shaufiah; Arif Bijaksana, Moch.

    2017-01-01

    Automatic summarization is a system that can help someone to take the core information of a long text instantly. The system can help by summarizing text automatically. there’s Already many summarization systems that have been developed at this time but there are still many problems in those system. In this final task proposed summarization method using document index graph. This method utilizes the PageRank and HITS formula used to assess the web page, adapted to make an assessment of words in the sentences in a text document. The expected outcome of this final task is a system that can do summarization of a single document, by utilizing document index graph with TextRank and HITS to improve the quality of the summary results automatically.

  19. Relationship between Small Animal Intern Rank and Performance at a University Teaching Hospital.

    PubMed

    Hofmeister, Erik H; Saba, Corey; Kent, Marc; Creevy, Kate E

    2015-01-01

    The purpose of this study was to determine if there is a relationship between selection committee rankings of internship applicants and the performance of small animal interns. The hypothesis was that there would be a relationship between selection committee rank order and intern performance; the more highly an application was ranked, the better the intern's performance scores would be. In 2007, the Department of Small Animal Medicine and Surgery instituted a standardized approach to its intern selection process both to streamline the process and to track its effectiveness. At the end of intern years 2010-2014, every faculty member in the department was provided an intern assessment form for that year's class. There was no relationship between an individual intern's final rank by the selection committee and his/her performance either as a percentile score or a Likert-type score (p=.25, R2=0.04; p=0.31, R2=0.03, respectively). Likewise, when interns were divided into the top and bottom quartile based on their final rank by the selection committee, there was no relationship between their rank and their performance as a percentile score (median rank 15 vs. 20; p=.14) or Likert-type score (median rank 14 vs. 19; p=.27). Institutions that use a similar intern selection method may need to reconsider the time and effort being expended for an outcome that does not predict performance. Alternatively, specific criteria more predictive of performance outcomes should be identified and employed in the internship selection process.

  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.

  1. Ranking experts' preferences regarding measures and methods of assessment of welfare in dairy herds using Adaptive Conjoint Analysis.

    PubMed

    Lievaart, J J; Noordhuizen, J P T M

    2011-07-01

    Welfare in dairy herds can be addressed using different concepts. The difficulty is to extract which measures are the most important to practically address welfare at the herd level and the methods to assess traits considered most important. Therefore, the preferences of 24 acknowledged European welfare experts were ranked regarding 70 measures suitable to assess dairy cattle welfare at herd level using the Adaptive Conjoint Analysis (ACA; Sawtooth Software, Inc., Sequim, WA) technique. The experts were selected on the basis of 3 criteria: at least 5 yr experience in animal welfare research; recent scientific publications in the field of animal welfare; and, at the most, 3 animal species including dairy cattle as their field of expertise. The 70 traits were ranked by using the median ACA questionnaire utility scores and the range between the answers of the 24 experts. A high utility score with a low range between the answers of the experts was considered as suitable to assess welfare at farm level. Measures meeting these criteria were prevalence of lameness cases (107.3±11.7), competition for feed and water (96.4±13.9), and number of freestalls per 10 cows (84.8±13.3). Based on the utility score alone, these former measures were replaced by stereotypic behavior (111.7±17.1), prevalence of lameness cases (107.3±11.7), body condition score (108.0±18.9), and hock lesions (104.7±16.1). Subsequently, to demonstrate that the ACA technique can be used to rank either well-known or inconclusive methods of assessment, the methods for the traits lameness cases and the hygiene of the calving pen were ranked using another 2 ACA questionnaires. The results are based on the opinions of selected, internationally acknowledged dairy cattle welfare experts within the European Union. In the future, other parties like dairy farmers and farmers' organization should be included to achieve consensus about the most suitable traits applicable in practice. The currently investigated

  2. Creating Composite Age Groups to Smooth Percentile Rank Distributions of Small Samples

    ERIC Educational Resources Information Center

    Lopez, Francesca; Olson, Amy; Bansal, Naveen

    2011-01-01

    Individually administered tests are often normed on small samples, a process that may result in irregularities within and across various age or grade distributions. Test users often smooth distributions guided by Thurstone assumptions (normality and linearity) to result in norms that adhere to assumptions made about how the data should look. Test…

  3. Individual variability in preference for energy-dense foods fails to predict child BMI percentile.

    PubMed

    Potter, Christina; Griggs, Rebecca L; Ferriday, Danielle; Rogers, Peter J; Brunstrom, Jeffrey M

    2017-04-01

    Many studies show that higher dietary energy density is associated with greater body weight. Here we explored two propositions: i) that child BMI percentile is associated with individual differences in children's relative preference for energy-dense foods, ii) that child BMI percentile is associated with the same individual differences between their parents. Child-parent dyads were recruited from a local interactive science center in Bristol (UK). Using computerized tasks, participants ranked their preference and rated their liking for a range of snack foods that varied in energy density. Children (aged 3-14years, N=110) and parents completed the tasks for themselves. Parents also completed two further tasks in which they ranked the foods in the order that they would prioritize for their child, and again, in the order that they thought their child would choose. Children preferred (t(109)=3.91, p<0.001) and better liked the taste of (t(109)=3.28, p=0.001) higher energy-dense foods, and parents correctly estimated this outcome (t(109)=7.18, p<0.001). Conversely, lower energy-dense foods were preferred (t(109)=-4.63, p<0.001), better liked (t(109)=-2.75, p=0.007) and served (t(109)=-15.06, p<0.001) by parents. However, we found no evidence that child BMI percentile was associated with child or parent preference for, or liking of, energy-dense foods. Therefore, we suggest that the observed relationship between dietary energy density and body weight is not explained by individual differences in preference for energy density.

  4. Chronic dietary risk characterization for pesticide residues: a ranking and scoring method integrating agricultural uses and food contamination data.

    PubMed

    Nougadère, Alexandre; Reninger, Jean-Cédric; Volatier, Jean-Luc; Leblanc, Jean-Charles

    2011-07-01

    A method has been developed to identify pesticide residues and foodstuffs for inclusion in national monitoring programs with different priority levels. It combines two chronic dietary intake indicators: ATMDI based on maximum residue levels and agricultural uses, and EDI on food contamination data. The mean and 95th percentile of exposure were calculated for 490 substances using individual and national consumption data. The results show that mean ATMDI exceeds the acceptable daily intake (ADI) for 10% of the pesticides, and the mean upper-bound EDI is above the ADI for 1.8% of substances. A seven-level risk scale is presented for substances already analyzed in food in France and substances not currently sought. Of 336 substances analyzed, 70 pesticides of concern (levels 2-5) should be particularly monitored, 22 of which are priority pesticides (levels 4 and 5). Of 154 substances not sought, 36 pesticides of concern (levels 2-4) should be included in monitoring programs, including 8 priority pesticides (level 4). In order to refine exposure assessment, analytical improvements and developments are needed to lower the analytical limits for priority pesticide/commodity combinations. Developed nationally, this method could be applied at different geographic scales.

  5. A comparison of methods of ranking the provision of periodontal services by dental practices in south Australia.

    PubMed

    Brown, L F

    1995-03-01

    Wide variations documented in the provision of periodontal services have raised concerns about possible under- and over-servicing. The aim of this study was to compare various methods used to measure the provision of periodontal services. The methods compared were procedure logs to measure service mix, audits of patients' records and patients' recall of treatment received at their last series of dental visits. The study was conducted among private general dental practices in Adelaide, South Australia. The first aspect of the study compared 2,290 patients' recall of receiving periodontal information, including oral hygiene instruction, or periodontal treatment at their last dental visit(s) with notations of their dental records. Discordance was high, with disagreement occurring in 71.5 per cent of cases for patient education, and 42.2 per cent of cases for periodontal treatment. Comparison of the ranking of the provision of periodontally-related services by 24 dental practices according to the three data collection methods showed that the ranking of a practice was significantly related to the data collection method used (Friedman's two-way ANOVA; P < 0.05). It was concluded that methods used to measure the provision of periodontal care are fallible, and that more than one method may be needed to record the full range of preventive and treatment services.

  6. 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…

  7. 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.

  8. 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

  9. 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.

  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. In vitro to in vivo extrapolation for drug-induced liver injury using a pair ranking method.

    PubMed

    Liu, Zhichao; Fang, Hong; Borlak, Jürgen; Roberts, Ruth; Tong, Weida

    2017-01-11

    Preclinical animal toxicity studies may not accurately predict human toxicity. In light of this, in vitro systems have been developed that have the potential to supplement or even replace animal use. We examined in vitro to in vivo extrapolation (IVIVE) of gene expression data obtained from The Open Japanese Toxicogenomics Project-Genomics Assisted Toxicity Evaluation System (Open TG-GATEs) for 131 compounds given to rats for 28 days, and to human or rat hepatocytes for 24 hours. Notably, a Pair Ranking (PRank) method was developed to assess IVIVE potential with a PRank score based on the preservation of the order of similarity rankings of compound pairs between the platforms using a receiver operating characteristic (ROC) curve analysis to measure area under the curve (AUC). A high IVIVE potential was noted for rat primary hepatocytes when compared to rat 28-day studies (PRank score = 0.71) whereas the IVIVE potential for human primary hepatocytes compared to rat 28-day studies was lower (PRank score = 0.58), indicating that species difference plays a critical role in IVIVE. When limiting the analysis to only those drugs causing drug-induced liver injury, the IVIVE potential was slightly improved both for rats (from 0.71 to 0.76) and for humans (from 0.58 to 0.62). Similarly, PRank scores were improved when the analyses focused on specific hepatotoxic endpoints such as hepatocellular injury, or cholestatic injury. In conclusion, toxicogenomic data generated in vitro yields a ranking of drugs in their potential to cause toxicity as generated from in vivo analyses.

  12. 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…

  13. Reply to “Ranking filter methods for concentrating pathogens in lake water”

    USGS Publications Warehouse

    Bushon, Rebecca N.; Francy, Donna S.; Gallardo, Vicente J.; Lindquist, H.D. Alan; Villegas, Eric N.; Ware, Michael W.

    2013-01-01

    Accurately comparing filtration methods is indeed difficult. Our method (1) and the method described by Borchardt et al. for determining recoveries are both acceptable approaches; however, each is designed to achieve a different research goal. Our study was designed to compare recoveries of multiple microorganisms in surface-water samples. Because, in practice, water-matrix effects come into play throughout filtration, concentration, and detection processes, we felt it important to incorporate those effects into the recovery results.

  14. Method for ranking biological habitats in oil spill response planning and impact assessment

    SciTech Connect

    Adams, J.K.; Benkert, K.A.; Keller, C.; White, R.

    1984-08-01

    The report describes a method that enables oil spill response planners to minimize the ecological impacts of oil spills by determining protection priorites for biological habitats. The objective of the method is to allow persons responding to an oil spill to quickly identify areas that should be protected first, second, and on to the extent that personnel and equipment are available. The first part of the report describes the rationale and general components of the method. The last part presents an application of the method to the Louisana Offshore Oil Port (LOOP) spill response planning area. 28 references, 9 tables.

  15. 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.

  16. 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.

  17. 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.

  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 chemical risk ranking and scoring method for the selection of harmful substances to be specially controlled in occupational environments.

    PubMed

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

    2014-11-20

    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.

  20. Should we use customized fetal growth percentiles in urban Canada?

    PubMed

    Melamed, Nir; Ray, Joel G; Shah, Prakesh S; Berger, Howard; Kingdom, John C

    2014-02-01

    An increasingly common challenge in antenatal care of the small for gestational age (SGA) fetus is the distinction between the constitutionally (physiologically) small fetus and the fetus affected by pathological intrauterine growth restriction (IUGR). We discuss here the rationale and the evidence for the use of customized growth percentiles for the purpose of distinguishing between the fetus with true IUGR and the fetus with constitutional SGA. We also provide estimates of the potential effects of adopting ethnicity-specific birth weight curves on the rates of SGA and large for gestational age status in multi-ethnic metropolitan cities in North America and Europe, such as the City of Toronto. Using customized growth percentiles would result in a considerable decline in the rate of a false-positive diagnosis of SGA among visible minorities, and improve the detection rate of true large for gestational age fetuses among these groups.

  1. An automated method for identification and ranking of hyperspectral target detections

    NASA Astrophysics Data System (ADS)

    Basener, Bill

    2011-06-01

    In this paper we present a new methodology for automated target detection and identification in hyperspectral imagery. The standard paradigm for target detection in hyperspectral imagery is to run a detection algorithm, typically statistical in nature, and visually inspect each high-scoring pixel to decide whether it is a true detection or a false alarm. Detection filters have constant false alarm rates (CFARs) approaching 10-5, but these can still result in a large number of false alarms given multiple images and a large number of target materials. Here we introduce a new methodology for target detection and identification in hyperspectral imagery that shows promise for hard targets. The result is a greatly reduced false alarm rate and a practical methodology for aiding an analyst in quantitatively evaluating detected pixels. We demonstrate the utility of the method with results on data from the HyMap sensor over the Cooke City, MT.

  2. Rank-based methods as a non-parametric alternative of the T-statistic for the analysis of biological microarray data.

    PubMed

    Breitling, Rainer; Herzyk, Pawel

    2005-10-01

    We have recently introduced a rank-based test statistic, RankProducts (RP), as a new non-parametric method for detecting differentially expressed genes in microarray experiments. It has been shown to generate surprisingly good results with biological datasets. The basis for this performance and the limits of the method are, however, little understood. Here we explore the performance of such rank-based approaches under a variety of conditions using simulated microarray data, and compare it with classical Wilcoxon rank sums and t-statistics, which form the basis of most alternative differential gene expression detection techniques. We show that for realistic simulated microarray datasets, RP is more powerful and accurate for sorting genes by differential expression than t-statistics or Wilcoxon rank sums - in particular for replicate numbers below 10, which are most commonly used in biological experiments. Its relative performance is particularly strong when the data are contaminated by non-normal random noise or when the samples are very inhomogenous, e.g. because they come from different time points or contain a mixture of affected and unaffected cells. However, RP assumes equal measurement variance for all genes and tends to give overly optimistic p-values when this assumption is violated. It is therefore essential that proper variance stabilizing normalization is performed on the data before calculating the RP values. Where this is impossible, another rank-based variant of RP (average ranks) provides a useful alternative with very similar overall performance. The Perl scripts implementing the simulation and evaluation are available upon request. Implementations of the RP method are available for download from the authors website (http://www.brc.dcs.gla.ac.uk/glama).

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

    PubMed

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

    2015-11-16

    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.

  4. Wingate Anaerobic Test Percentile Norms in Colombian Healthy Adults.

    PubMed

    Ramírez-Vélez, Robinson; López-Albán, Carlos A; La Rotta-Villamizar, Diego R; Romero-García, Jesús A; Alonso-Martinez, Alicia M; Izquierdo, Mikel

    2016-01-01

    The Wingate Anaerobic Test (WAnT) became one of the most convenient tests used to evaluate anaerobic capacity and the effectiveness of anaerobic training programs for a variety of power sports. However, its use and interpretation as an evaluative measurement are limited because there are few published reference values derived from large numbers of subjects in nonathletic populations. We present reference values for the WAnT in Colombian healthy adults (aged 20-80 years old). The sample comprised 1,873 subjects (64% men) from Cali, Colombia, who were recruited for the study between 2002 and 2012. The 30-second WAnT was performed on a Monark ergometer. The WAnT resistance was set at 0.075 kp · kg(-1) body mass (BM). The mean absolute peak power (PP), relative PP normalized to the BM, and the fatigue index (FI%) were calculated using the LMS method (L [curve Box-Cox], M [curve median], and S [curve coefficient of variation]) and expressed as tabulated percentiles from 3 to 97 and as smoothed centile curves (P3, P10, P25, P50, P75, P90, P97). Mean ± SD values for the patients' anthropometric data were 38.1 ± 11.7 years of age, 72.7 ± 14.2 kg weight, 1.68 ± 0.09 m height, and 25.6 ± 4.2 body mass index. Our results show that mean absolute PP value, relative PP relative values normalized to BM, and FI were 527.4 ± 131.7 W, 7.6 ± 2.3 W · kg(-1), and 29.0 ± 15.7%, respectively. Men performed better than women in terms of PP and FI values. Nevertheless, the mean PP decreased with age and sex. Age-specific PP and FI normative values among healthy Colombian adults are defined. A more specific set of reference values is useful for clinicians and researchers studying anaerobic capacity in healthy adults.

  5. 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

  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. A New Method for Assessing the Statistical Significance in the Differential Functioning of Items and Tests (DFIT) Framework

    ERIC Educational Resources Information Center

    Oshima, T. C.; Raju, Nambury S.; Nanda, Alice O.

    2006-01-01

    A new item parameter replication method is proposed for assessing the statistical significance of the noncompensatory differential item functioning (NCDIF) index associated with the differential functioning of items and tests framework. In this new method, a cutoff score for each item is determined by obtaining a (1-alpha ) percentile rank score…

  8. 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.

  9. Ranking Support Vector Machine with Kernel Approximation

    PubMed Central

    Dou, Yong

    2017-01-01

    Learning to rank algorithm has become important in recent years due to its successful application in information retrieval, recommender system, and computational biology, and so forth. Ranking support vector machine (RankSVM) is one of the state-of-art ranking models and has been favorably used. Nonlinear RankSVM (RankSVM with nonlinear kernels) can give higher accuracy than linear RankSVM (RankSVM with a linear kernel) for complex nonlinear ranking problem. However, the learning methods for nonlinear RankSVM are still time-consuming because of the calculation of kernel matrix. In this paper, we propose a fast ranking algorithm based on kernel approximation to avoid computing the kernel matrix. We explore two types of kernel approximation methods, namely, the Nyström method and random Fourier features. Primal truncated Newton method is used to optimize the pairwise L2-loss (squared Hinge-loss) objective function of the ranking model after the nonlinear kernel approximation. Experimental results demonstrate that our proposed method gets a much faster training speed than kernel RankSVM and achieves comparable or better performance over state-of-the-art ranking algorithms. PMID:28293256

  10. Ranking Support Vector Machine with Kernel Approximation.

    PubMed

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

    2017-01-01

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

  11. University Rankings in China

    ERIC Educational Resources Information Center

    Liu, Nian Cai; Liu, Li

    2005-01-01

    Since the mid 1990s of last Century, university rankings have become very popular in China. Six institutions have published such rankings; some of them have also detailed their ranking methodologies. This paper features a general introduction to university ranking in China, and to the methodologies of each ranking discussed. The paper also…

  12. Comparing Alternative Kernels for the Kernel Method of Test Equating: Gaussian, Logistic, and Uniform Kernels. Research Report. ETS RR-08-12

    ERIC Educational Resources Information Center

    Lee, Yi-Hsuan; von Davier, Alina A.

    2008-01-01

    The kernel equating method (von Davier, Holland, & Thayer, 2004) is based on a flexible family of equipercentile-like equating functions that use a Gaussian kernel to continuize the discrete score distributions. While the classical equipercentile, or percentile-rank, equating method carries out the continuization step by linear interpolation,…

  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

    2016-06-09

    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.

  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. A rank-based nonparametric method for mapping quantitative trait loci in outbred half-sib pedigrees: application to milk production in a granddaughter design.

    PubMed Central

    Coppieters, W; Kvasz, A; Farnir, F; Arranz, J J; Grisart, B; Mackinnon, M; Georges, M

    1998-01-01

    We describe the development of a multipoint nonparametric quantitative trait loci mapping method based on the Wilcoxon rank-sum test applicable to outbred half-sib pedigrees. The method has been evaluated on a simulated dataset and its efficiency compared with interval mapping by using regression. It was shown that the rank-based approach is slightly inferior to regression when the residual variance is homoscedastic normal; however, in three out of four other scenarios envisaged, i.e., residual variance heteroscedastic normal, homoscedastic skewed, and homoscedastic positively kurtosed, the latter outperforms the former one. Both methods were applied to a real data set analyzing the effect of bovine chromosome 6 on milk yield and composition by using a 125-cM map comprising 15 microsatellites and a granddaughter design counting 1158 Holstein-Friesian sires. PMID:9649541

  16. 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

  17. Waist circumference percentiles among Turkish children under the age of 6 years.

    PubMed

    Hatipoglu, Nihal; Mazicioglu, M Mumtaz; Poyrazoglu, Serpil; Borlu, Arda; Horoz, Duygu; Kurtoglu, Selim

    2013-01-01

    Waist circumference, a proxy measure of abdominal obesity, is associated with cardio-metabolic risk factors in childhood and adolescence. Although there are numerous studies about waist circumference percentiles in children, only a few studies cover preschool children. The aim of this study was to develop age- and gender-specific waist circumference smoothed reference curves in Turkish preschool children to determine abdominal obesity prevalence and to compare them with reference curves obtained from different countries. The design of the study was cross-sectional. A total of 2,947 children (1,471 boys and 1,476 girls) aged 0-6 years were included in the study. The subjects were divided according to their gender. Waist circumference was measured by using a standardized procedure. The age- and gender-specific waist circumference reference curves were constructed and smoothed with LMS method. The reference values of waist circumference, including 3rd, 10th 25th, 50th, 75th, 90th, and 97th percentiles, and standard deviations were given for preschool children. Waist circumference values increased with age, and there were differences between genders. The prevalence of abdominal obesity was calculated as 10.1 % for boys and 10.7 % for girls. Having compared our data with two other countries' data, we found that our waist circumference data were significantly lower. This is the first cross-sectional study for age- and gender-specific references of 0- to 6-year-old Turkish children. The gender- and age-specific waist circumference percentiles can be used to determine the risk of central obesity.

  18. Dimension Reduction for Object Ranking

    NASA Astrophysics Data System (ADS)

    Kamishima, Toshihiro; Akaho, Shotaro

    Ordered lists of objects are widely used as representational forms. Such ordered objects include Web search results and bestseller lists. Techniques for processing such ordinal data are being developed, particularly methods for an object ranking task: i.e., learning functions used to sort objects from sample orders. In this article, we propose two dimension reduction methods specifically designed to improve prediction performance in an object ranking task.

  19. Multi-stage classification method oriented to aerial image based on low-rank recovery and multi-feature fusion sparse representation.

    PubMed

    Ma, Xu; Cheng, Yongmei; Hao, Shuai

    2016-12-10

    Automatic classification of terrain surfaces from an aerial image is essential for an autonomous unmanned aerial vehicle (UAV) landing at an unprepared site by using vision. Diverse terrain surfaces may show similar spectral properties due to the illumination and noise that easily cause poor classification performance. To address this issue, a multi-stage classification algorithm based on low-rank recovery and multi-feature fusion sparse representation is proposed. First, color moments and Gabor texture feature are extracted from training data and stacked as column vectors of a dictionary. Then we perform low-rank matrix recovery for the dictionary by using augmented Lagrange multipliers and construct a multi-stage terrain classifier. Experimental results on an aerial map database that we prepared verify the classification accuracy and robustness of the proposed method.

  20. 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

  1. Evaluation of the growth percentiles of children with congenital heart disease.

    PubMed

    Martins da Silva, Viviane; de Oliveira Lopes, Marcos Venícios; Leite de Araujo, Thelma

    2007-01-01

    The purpose of this study was to evaluate the correlation between anthropometric measures of children with congenital heart disease with percentiles that represent their growth indicators. Anthropometric evaluations of 135 hospitalized children with congenital heart disease were performed in a hospital specialized in cardiac diseases in Fortaleza, CE, Brazil. For the growth evaluation, percentiles of height by age, weight by height and weight by age were calculated. Children's average age was 4.74 months (+ 3.78) and 66.7% of the children were male. The medians of the three percentiles presented values below percentile 10, indicating a high proportion of values considered of risk. The subscapular thickness presented positive correlation with the three percentiles. The values of percentiles studied indicated growth delay.

  2. Ranking targets in structure-based virtual screening of three-dimensional protein libraries: methods and problems.

    PubMed

    Kellenberger, Esther; Foata, Nicolas; Rognan, Didier

    2008-05-01

    Structure-based virtual screening is a promising tool to identify putative targets for a specific ligand. Instead of docking multiple ligands into a single protein cavity, a single ligand is docked in a collection of binding sites. In inverse screening, hits are in fact targets which have been prioritized within the pool of best ranked proteins. The target rate depends on specificity and promiscuity in protein-ligand interactions and, to a considerable extent, on the effectiveness of the scoring function, which still is the Achilles' heel of molecular docking. In the present retrospective study, virtual screening of the sc-PDB target library by GOLD docking was carried out for four compounds (biotin, 4-hydroxy-tamoxifen, 6-hydroxy-1,6-dihydropurine ribonucleoside, and methotrexate) of known sc-PDB targets and, several ranking protocols based on GOLD fitness score and topological molecular interaction fingerprint (IFP) comparison were evaluated. For the four investigated ligands, the fusion of GOLD fitness and two IFP scores allowed the recovery of most targets, including the rare proteins which are not readily suitable for statistical analysis, while significantly filtering out most false positive entries. The current survey suggests that selecting a small number of targets (<20) for experimental evaluation is achievable with a pure structure-based approach.

  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

    2016-03-05

    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.

  4. 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.

  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.

  6. Rank Pooling for Action Recognition.

    PubMed

    Fernando, Basura; Gavves, Efstratios; Oramas M, Jose Oramas; Ghodrati, Amir; Tuytelaars, Tinne

    2017-04-01

    We propose a function-based temporal pooling method that captures the latent structure of the video sequence data - e.g., how frame-level features evolve over time in a video. We show how the parameters of a function that has been fit to the video data can serve as a robust new video representation. As a specific example, we learn a pooling function via ranking machines. By learning to rank the frame-level features of a video in chronological order, we obtain a new representation that captures the video-wide temporal dynamics of a video, suitable for action recognition. Other than ranking functions, we explore different parametric models that could also explain the temporal changes in videos. The proposed functional pooling methods, and rank pooling in particular, is easy to interpret and implement, fast to compute and effective in recognizing a wide variety of actions. We evaluate our method on various benchmarks for generic action, fine-grained action and gesture recognition. Results show that rank pooling brings an absolute improvement of 7-10 average pooling baseline. At the same time, rank pooling is compatible with and complementary to several appearance and local motion based methods and features, such as improved trajectories and deep learning features.

  7. A combined molecular docking-based and pharmacophore-based target prediction strategy with a probabilistic fusion method for target ranking.

    PubMed

    Li, Guo-Bo; Yang, Ling-Ling; Xu, Yong; Wang, Wen-Jing; Li, Lin-Li; Yang, Sheng-Yong

    2013-07-01

    Herein, a combined molecular docking-based and pharmacophore-based target prediction strategy is presented, in which a probabilistic fusion method is suggested for target ranking. Establishment and validation of the combined strategy are described. A target database, termed TargetDB, was firstly constructed, which contains 1105 drug targets. Based on TargetDB, the molecular docking-based target prediction and pharmacophore-based target prediction protocols were established. A probabilistic fusion method was then developed by constructing probability assignment curves (PACs) against a set of selected targets. Finally the workflow for the combined molecular docking-based and pharmacophore-based target prediction strategy was established. Evaluations of the performance of the combined strategy were carried out against a set of structurally different single-target compounds and a well-known multi-target drug, 4H-tamoxifen, which results showed that the combined strategy consistently outperformed the sole use of docking-based and pharmacophore-based methods. Overall, this investigation provides a possible way for improving the accuracy of in silico target prediction and a method for target ranking.

  8. Robust rankings: Review of multivariate assessments illustrated by the Shanghai rankings.

    PubMed

    Freyer, Leo

    2014-01-01

    Defined errors are entered into data collections in order to test their influence on the reliability of multivariate rankings. Random numbers and real ranking data serve as data origins. In the course of data collection small random errors often lead to a switch in ranking, which can influence the general ranking picture considerably. For stabilisation an objective weighting method is evaluated. The robustness of these rankings is then compared to the original forms. Robust forms of the published Shanghai top 100 rankings are calculated and compared to each other. As a result, the possibilities and restrictions of this type of weighting become recognisable.

  9. 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…

  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.

  11. Rank 4 Premodular Categories

    SciTech Connect

    Bruillard, Paul J.; Galindo, Cesar; Ng, Siu Hung; Plavnik, Julia; Rowell, Eric; Wang, Zhenghan

    2016-09-01

    We consider the classification problem for rank 4 premodular categories. We uncover a formula for the 2nd Frobenius-Schur indicator of a premodular category is determined and the classification of rank 4 premodular categories (up to Grothendieck equivalence) is completed. In the appendix we show rank finiteness for premodular categories.

  12. On Classification of Modular Categories by Rank: Table A.1

    SciTech Connect

    Bruillard, Paul; Ng, Siu-Hung; Rowell, Eric C.; Wang, Zhenghan

    2016-04-10

    The feasibility of a classification-by-rank program for modular categories follows from the Rank-Finiteness Theorem. We develop arithmetic, representation theoretic and algebraic methods for classifying modular categories by rank. As an application, we determine all possible fusion rules for all rank=5 modular categories and describe the corresponding monoidal equivalence classes.

  13. 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.

  14. 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

  15. Ranking species in mutualistic networks.

    PubMed

    Domínguez-García, Virginia; Muñoz, Miguel A

    2015-02-02

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

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

    PubMed

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

    2012-12-01

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

  17. Centrality based Document Ranking

    DTIC Science & Technology

    2014-11-01

    approach. We model the documents to be ranked as nodes in a graph and place edges between documents based on their similarity. Given a query, we compute...similarity of the query with respect to every document in the graph . Based on these similarity values, documents are ranked for a given query...clinical documents using centrality based approach. We model the documents to be ranked as nodes in a graph and place edges between documents based on their

  18. Waist circumference percentile thresholds for identifying adolescents with insulin resistance in clinical practice.

    PubMed

    Lee, Joyce M; Davis, Matthew M; Woolford, Susan J; Gurney, James G

    2009-08-01

    We formally evaluated waist circumference (WC) percentile cutoffs for predicting insulin resistance (IR) and whether different cutoffs should be used for adolescents of different race/ethnicities. Analysis was performed for 1575 adolescents aged 12-18 yr from the National Health and Nutrition Examination Survey 1999-2002. Adolescents were classified as having IR if they had a homeostasis model assessment-insulin resistance level, a validated measure of IR, of >4.39, and WC percentile was classified according to previously published universal (all races combined) and race/ethnicity-specific WC percentile cutoffs. Receiver operating characteristic curves for predicting IR were constructed comparing the race/ethnicity-specific vs. universal WC percentile cutoffs, and area under the curve (AUC) was calculated. Comparing universal with race/ethnicity-specific WC percentiles, there were no significant differences in AUC for Black, Mexican-American, or White adolescents. Because race/ethnicity-specific thresholds did not discriminate better than universal WC thresholds, universal WC thresholds may be used effectively to identify adolescents with IR in primary care practices. A WC > or =75th or > or =90th percentile for all race/ethnicities combined would be appropriate to apply in clinical practice for identification of adolescents with IR, a risk factor for development of type 2 diabetes.

  19. 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.

  20. 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…

  1. 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.

  2. Hierarchical partial order ranking.

    PubMed

    Carlsen, Lars

    2008-09-01

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

  3. Statistical Optimality in Multipartite Ranking and Ordinal Regression.

    PubMed

    Uematsu, Kazuki; Lee, Yoonkyung

    2015-05-01

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

  4. Precision of Student Growth Percentiles with Small Sample Sizes

    ERIC Educational Resources Information Center

    Culbertson, Michael J.

    2016-01-01

    States in the Regional Educational Laboratory (REL) Central region serve a largely rural population with many states enrolling fewer than 350,000 students. A common challenge identified among REL Central educators is identifying appropriate methods for analyzing data with small samples of students. In particular, members of the REL Central…

  5. 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

  6. Ranking of Scientists: A New Approach.

    ERIC Educational Resources Information Center

    Sen, B. K.; Pandalai, T. A.; Karanjai, Aruna

    1998-01-01

    Proposes a formula for the ranking of scientists based on diachronous citation counts. Generalizes the fact that the citation-generation potential is not the same for all papers, and states that the proposed method of ranking does not replace peer review, but rather acts as an aid for them. (Author/LRW)

  7. Use of Pearson's Chi-Square for Testing Equality of Percentile Profiles across Multiple Populations.

    PubMed

    Johnson, William D; Beyl, Robbie A; Burton, Jeffrey H; Johnson, Callie M; Romer, Jacob E; Zhang, Lei

    2015-08-01

    In large sample studies where distributions may be skewed and not readily transformed to symmetry, it may be of greater interest to compare different distributions in terms of percentiles rather than means. For example, it may be more informative to compare two or more populations with respect to their within population distributions by testing the hypothesis that their corresponding respective 10(th), 50(th), and 90(th) percentiles are equal. As a generalization of the median test, the proposed test statistic is asymptotically distributed as Chi-square with degrees of freedom dependent upon the number of percentiles tested and constraints of the null hypothesis. Results from simulation studies are used to validate the nominal 0.05 significance level under the null hypothesis, and asymptotic power properties that are suitable for testing equality of percentile profiles against selected profile discrepancies for a variety of underlying distributions. A pragmatic example is provided to illustrate the comparison of the percentile profiles for four body mass index distributions.

  8. 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.

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

    DTIC Science & Technology

    2015-04-28

    computer vision, and machine learning . We formulate the above problem of ranking with incomplete noisy information as an instance of the group...occur in numerous applications in data analysis (e.g., ranking teams in sports data), computer vision, and machine learning . We formulate the above...his estimated score and the associated level of confidence, and in doing so, it learns the underlying inherent skill parameters each player is

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

    ERIC Educational Resources Information Center

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

    2010-01-01

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

  11. Comparison of Updated Weight and Height Percentiles with Previous References in 6-17-Year-Old Children in Kayseri, Turkey

    PubMed Central

    Zararsız, Gökmen; Çiçek, Betül; Kondolot, Meda; Mazıcıoğlu, M. Mümtaz; Öztürk, Ahmet; Kurtoğlu, Selim

    2017-01-01

    Objective: To compare updated weight and height percentiles of 6-17-year-old children from all socio-economic levels in Kayseri with previous local references and other national/international data. Methods: The second study “Determination of Anthropometric Measurements of Turkish Children and Adolescents study (DAMTCA II)” was conducted in Kayseri, between October 2007 and April 2008. Weight and height measurements from 4321 (1926 boys, 2395 girls) school children aged between 6 to 17 years were included in this cross-sectional study. Using these data, weight and height percentile curves were produced with generalized additive models for location, scale and shape (GAMLSS) and compared with the most recent references. Results: Smoothed percentile curves including the 3rd, 5th, 10th, 15th, 25th, 50th, 75th, 85th, 90th, 95th, and 97th percentiles were obtained for boys and girls. These results were compared with DAMTCA I study and with two national (İstanbul and Ankara) and international data from Asia and from Europe. Conclusion: This study provides updated weight and height references for Turkish school children aged between 6 and 17 years residing in Kayseri. PMID:27507256

  12. Using Percentile Schedules to Increase Eye Contact in Children With Fragile X Syndrome

    PubMed Central

    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. Results showed that although aversion to eye contact is often thought to be unamenable to change in FXS, it can be shaped in some individuals using percentile schedules either alone or in combination with overcorrection. PMID:19721738

  13. Using percentile schedules to increase eye contact in children with Fragile X syndrome.

    PubMed

    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. Results showed that although aversion to eye contact is often thought to be unamenable to change in FXS, it can be shaped in some individuals using percentile schedules either alone or in combination with overcorrection.

  14. 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.

  15. 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.

  16. Using reduced rank regression methods to identify dietary patterns associated with obesity: a cross-country study among European and Australian adolescents.

    PubMed

    Huybrechts, Inge; Lioret, Sandrine; Mouratidou, Theodora; Gunter, Marc J; Manios, Yannis; Kersting, Mathilde; Gottrand, Frederic; Kafatos, Anthony; De Henauw, Stefaan; Cuenca-García, Magdalena; Widhalm, Kurt; Gonzales-Gross, Marcela; Molnar, Denes; Moreno, Luis A; McNaughton, Sarah A

    2017-01-01

    This study aims to examine repeatability of reduced rank regression (RRR) methods in calculating dietary patterns (DP) and cross-sectional associations with overweight (OW)/obesity across European and Australian samples of adolescents. Data from two cross-sectional surveys in Europe (2006/2007 Healthy Lifestyle in Europe by Nutrition in Adolescence study, including 1954 adolescents, 12-17 years) and Australia (2007 National Children's Nutrition and Physical Activity Survey, including 1498 adolescents, 12-16 years) were used. Dietary intake was measured using two non-consecutive, 24-h recalls. RRR was used to identify DP using dietary energy density, fibre density and percentage of energy intake from fat as the intermediate variables. Associations between DP scores and body mass/fat were examined using multivariable linear and logistic regression as appropriate, stratified by sex. The first DP extracted (labelled 'energy dense, high fat, low fibre') explained 47 and 31 % of the response variation in Australian and European adolescents, respectively. It was similar for European and Australian adolescents and characterised by higher consumption of biscuits/cakes, chocolate/confectionery, crisps/savoury snacks, sugar-sweetened beverages, and lower consumption of yogurt, high-fibre bread, vegetables and fresh fruit. DP scores were inversely associated with BMI z-scores in Australian adolescent boys and borderline inverse in European adolescent boys (so as with %BF). Similarly, a lower likelihood for OW in boys was observed with higher DP scores in both surveys. No such relationships were observed in adolescent girls. In conclusion, the DP identified in this cross-country study was comparable for European and Australian adolescents, demonstrating robustness of the RRR method in calculating DP among populations. However, longitudinal designs are more relevant when studying diet-obesity associations, to prevent reverse causality.

  17. Stature-for-Age and Weight-for-Age Percentiles: Boys, 2 to 20 Years

    MedlinePlus

    2 to 20 years: Boys NAME Stature-for-age and Weight-for-age percentiles RECORD # Mother’s Stature Date Age in cm 160 62 S 155 60 T 150 ... 14 15 16 17 18 19 20 BMI* AGE (YEARS) cm 95 190 90 185 75 180 ...

  18. 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…

  19. 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…

  20. Empirical Percentile Growth Curves with Z-scores Considering Seasonal Compensatory Growths for Japanese Thoroughbred Horses

    PubMed Central

    ONODA, Tomoaki; YAMAMOTO, Ryuta; SAWAMURA, Kyohei; MURASE, Harutaka; NAMBO, Yasuo; INOUE, Yoshinobu; MATSUI, Akira; MIYAKE, Takeshi; HIRAI, Nobuhiro

    2013-01-01

    Percentile growth curves are often used as a clinical indicator to evaluate variations of children’s growth status. In this study, we propose empirical percentile growth curves using Z-scores adapted for Japanese Thoroughbred horses, with considerations of the seasonal compensatory growth that is a typical characteristic of seasonal breeding animals. We previously developed new growth curve equations for Japanese Thoroughbreds adjusting for compensatory growth. Individual horses and residual effects were included as random effects in the growth curve equation model and their variance components were estimated. Based on the Z-scores of the estimated variance components, empirical percentile growth curves were constructed. A total of 5,594 and 5,680 body weight and age measurements of male and female Thoroughbreds, respectively, and 3,770 withers height and age measurements were used in the analyses. The developed empirical percentile growth curves using Z-scores are computationally feasible and useful for monitoring individual growth parameters of body weight and withers height of young Thoroughbred horses, especially during compensatory growth periods. PMID:24834004

  1. 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.…

  2. Ranking Information in Networks

    NASA Astrophysics Data System (ADS)

    Eliassi-Rad, Tina; Henderson, Keith

    Given a network, we are interested in ranking sets of nodes that score highest on user-specified criteria. For instance in graphs from bibliographic data (e.g. PubMed), we would like to discover sets of authors with expertise in a wide range of disciplines. We present this ranking task as a Top-K problem; utilize fixed-memory heuristic search; and present performance of both the serial and distributed search algorithms on synthetic and real-world data sets.

  3. Acculturation determines BMI percentile and noncore food intake in Hispanic children.

    PubMed

    Wiley, James F; Cloutier, Michelle M; Wakefield, Dorothy B; Hernandez, Dominica B; Grant, Autherene; Beaulieu, Annamarie; Gorin, Amy A

    2014-03-01

    Hispanic children in the United States are disproportionately affected by obesity. The role of acculturation in obesity is unclear. This study examined the relation between child obesity, dietary intake, and maternal acculturation in Hispanic children. We hypothesized that children of more acculturated mothers would consume more unhealthy foods and would have higher body mass index (BMI) percentiles. A total of 209 Hispanic mothers of children aged 2-4 y (50% female, 35.3 ± 8.7 mo, BMI percentile: 73.1 ± 27.8, 30% obese, 19% overweight) were recruited for an obesity prevention/reversal study. The associations between baseline maternal acculturation [Brief Acculturation Rating Scale for Mexican Americans-II (Brief ARSMA-II)], child BMI percentile, and child diet were examined. Factor analysis of the Brief ARSMA-II in Puerto Rican mothers resulted in 2 new factors, which were named the Hispanic Orientation Score (4 items, loadings: 0.64-0.81) and U.S. Mainland Orientation Score (6 items, loadings: -0.61-0.92). In the total sample, children who consumed more noncore foods were more likely to be overweight or obese (P < 0.01). Additionally, children of mothers with greater acculturation to the United States consumed more noncore foods (P < 0.0001) and had higher BMI percentiles (P < 0.04). However, mothers with greater Hispanic acculturation served fewer noncore foods (P < 0.0001). In the Puerto Rican subgroup of mothers, Puerto Rican mothers with greater acculturation to the United States served more noncore foods (P < 0.0001), but there was no association between acculturation and child BMI percentile in this subgroup. These mothers, however, served fewer sugar-sweetened beverages (P < 0.01) compared with non-Puerto Rican mothers, and this may have negated the effect of noncore food consumption on BMI percentile. These data suggest a complex relation between acculturation, noncore food consumption, and child BMI percentile in Puerto Rican and non-Puerto Rican

  4. 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.

  5. Playing the Rankings Game

    ERIC Educational Resources Information Center

    Farrell, Elizabeth F.; Van Der Werf, Martin

    2007-01-01

    While some colleges claim not to care what "U.S. News & World Report" says, and experts cite problems in the way its annual rankings are done, many institutions scramble to improve their positions. There are well-documented examples of institutions that have solicited nominal donations from alumni to boost their percentage of giving, encouraged…

  6. 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…

  7. 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.…

  8. 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

  9. Quantum Navigation and Ranking in Complex Networks

    NASA Astrophysics Data System (ADS)

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

    2012-08-01

    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.

  10. Generalization Performance of Regularized Ranking With Multiscale Kernels.

    PubMed

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

    2016-05-01

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

  11. Different actuarial risk measures produce different risk rankings for sexual offenders.

    PubMed

    Barbaree, Howard E; Langton, Calvin M; Peacock, Edward J

    2006-10-01

    Percentile ranks were computed for N=262 sex offenders using each of 5 actuarial risk instruments commonly used with adult sex offenders (RRASOR, Static-99, VRAG, SORAG, and MnSOST-R). Mean differences between percentile ranks obtained by different actuarial measures were found to vary inversely with the correlation between the actuarial scores. Following studies of factor analyses of actuarial items, we argue that the discrepancies among actuarial instruments can be substantially accounted for by the way in which the factor Antisocial Behavior and various factors reflecting sexual deviance are represented among the items contained in each instrument. In the discussion, we provide guidance to clinicians in resolving discrepancies between instruments and we discuss implications for future developments in sex offender risk assessment.

  12. Ranking community health status to stimulate discussion of local public health issues: the Wisconsin County Health Rankings.

    PubMed

    Peppard, Paul E; Kindig, David A; Dranger, Elizabeth; Jovaag, Amanda; Remington, Patrick L

    2008-02-01

    United Health Foundation's America's Health Rankings, which ranks the states from "least healthy" to "healthiest," receives wide press coverage and promotes discussion of public health issues. The University of Wisconsin Population Health Institute used the United Health Foundation's model to develop the Wisconsin County Health Rankings ("Health Rankings") from existing county-level data. The institute first released the rankings in 2004. A survey of the Wisconsin county health officers indicated that they intend to use the rankings for needs assessment, program planning, and discussion with county health boards. The institute implemented many of the health officers' suggestions for improvement of the rankings in subsequent editions. The methods employed to create the rankings should be applicable in other states.

  13. A note on rank reduction in sparse multivariate regression.

    PubMed

    Chen, Kun; Chan, Kung-Sik

    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.

  14. Plotting equation for gaussian percentiles and a spreadsheet program for generating probability plots

    USGS Publications Warehouse

    Balsillie, J.H.; Donoghue, J.F.; Butler, K.M.; Koch, J.L.

    2002-01-01

    Two-dimensional plotting tools can be of invaluable assistance in analytical scientific pursuits, and have been widely used in the analysis and interpretation of sedimentologic data. We consider, in this work, the use of arithmetic probability paper (APP). Most statistical computer applications do not allow for the generation of APP plots, because of apparent intractable nonlinearity of the percentile (or probability) axis of the plot. We have solved this problem by identifying an equation(s) for determining plotting positions of Gaussian percentiles (or probabilities), so that APP plots can easily be computer generated. An EXCEL example is presented, and a programmed, simple-to-use EXCEL application template is hereby made publicly available, whereby a complete granulometric analysis including data listing, moment measure calculations, and frequency and cumulative APP plots, is automatically produced.

  15. Percentile Analysis for Goodness-of-Fit Comparisons of Models to Data

    DTIC Science & Technology

    2014-07-01

    Science, 1, 11-38. Roberts, S., & Pashler, H. (2000). How persuasive is a good fit ? A comment on theory testing . Psychological Review, 107, 358-367...Percentile analysis for goodness -of- fit comparisons of models to data Sangeet Khemlani and J. Gregory Trafton skhemlani@gmail.com, trafton...modeling, it is routine to report a goodness -of- fit index (e.g., R2 or RMSE) between a putative model’s predictions and an observed dataset

  16. 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.

  17. Resulting Shifts in Percentile and Standard Placements after Comparison of the BOD POD and DXA

    PubMed Central

    HEDEN, TIMOTHY; SHEPARD, STEVE; SMITH, JOHN; COVINGTON, KAY; LECHEMINANT, JAMES

    2008-01-01

    The purpose of this study was to determine the validity of the BOD POD® when compared to the DXA and if placement on a percentile chart and standard table is affected by any differences between the two measures. A total of 244 (27.7 ± 10.8 yrs, 77.3 ± 16.1 kg, 171.4 ± 10.1 cm, 26.31 ± 5.42 BMI) males and females between the ages of 18 and 52 were recruited to participate in this study. The participant’s body fat percentage (%BF) was tested in random order on the BOD POD® and DXA during a 30-minute session following manufacturer’s guidelines and procedures. Dependent t-test indicated the %BF measured by the BOD POD® (23.4% ± 12.8) was significantly lower when compared to the DXA (29.5% ± 12.1), p = .001. The Pearson’s Product moment correlation was 0.95 (p = .001), indicating a very strong relationship between the two instruments. Using estimates of %BF from the BOD POD® also resulted in more favorable shifts on a percentile chart and standard table. Since a high correlation was evident between the two, the BOD POD® can be used as an instrument to track %BF changes over time during a diet and/or exercise intervention. However, caution should be made when classifying %BF with percentile charts or standard tables using the BOD POD® %BF estimates. PMID:27182302

  18. Adaptive urn designs for estimating several percentiles of a dose--response curve.

    PubMed

    Mugno, Raymond; Zhus, Wei; Rosenberger, William F

    2004-07-15

    Dose--response experiments are crucial in biomedical studies. There are usually multiple objectives in such experiments and among the goals is the estimation of several percentiles on the dose--response curve. Here we present the first non-parametric adaptive design approach to estimate several percentiles simultaneously via generalized Pólya urns. Theoretical properties of these designs are investigated and their performance is gaged by the locally compound optimal designs. As an example, we re-investigated a psychophysical experiment where one of the goals was to estimate the three quartiles. We show that these multiple-objective adaptive designs are more efficient than the original single-objective adaptive design targeting the median only. We also show that urn designs which target the optimal designs are slightly more efficient than those which target the desired percentiles directly. Guidelines are given as to when to use which type of design. Overall we are pleased with the efficiency results and hope compound adaptive designs proposed in this work or their variants may prove to be a viable non-parametric alternative in multiple-objective dose--response studies.

  19. 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.

  20. 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…

  1. 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

  2. Measurement Error Adjustment Using the SIMEX Method: An Application to Student Growth Percentiles

    ERIC Educational Resources Information Center

    Shang, Yi

    2012-01-01

    Growth models are used extensively in the context of educational accountability to evaluate student-, class-, and school-level growth. However, when error-prone test scores are used as independent variables or right-hand-side controls, the estimation of such growth models can be substantially biased. This article introduces a…

  3. Model diagnostics in reduced-rank estimation

    PubMed Central

    Chen, Kun

    2016-01-01

    Reduced-rank methods are very popular in high-dimensional multivariate analysis for conducting simultaneous dimension reduction and model estimation. However, the commonly-used reduced-rank methods are not robust, as the underlying reduced-rank structure can be easily distorted by only a few data outliers. Anomalies are bound to exist in big data problems, and in some applications they themselves could be of the primary interest. While naive residual analysis is often inadequate for outlier detection due to potential masking and swamping, robust reduced-rank estimation approaches could be computationally demanding. Under Stein's unbiased risk estimation framework, we propose a set of tools, including leverage score and generalized information score, to perform model diagnostics and outlier detection in large-scale reduced-rank estimation. The leverage scores give an exact decomposition of the so-called model degrees of freedom to the observation level, which lead to exact decomposition of many commonly-used information criteria; the resulting quantities are thus named information scores of the observations. The proposed information score approach provides a principled way of combining the residuals and leverage scores for anomaly detection. Simulation studies confirm that the proposed diagnostic tools work well. A pattern recognition example with hand-writing digital images and a time series analysis example with monthly U.S. macroeconomic data further demonstrate the efficacy of the proposed approaches. PMID:28003860

  4. 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

  5. On the ranking of chemicals based on their PBT characteristics: comparison of different ranking methodologies using selected POPs as an illustrative example.

    PubMed

    Sailaukhanuly, Yerbolat; Zhakupbekova, Arai; Amutova, Farida; Carlsen, Lars

    2013-01-01

    Knowledge of the environmental behavior of chemicals is a fundamental part of the risk assessment process. The present paper discusses various methods of ranking of a series of persistent organic pollutants (POPs) according to the persistence, bioaccumulation and toxicity (PBT) characteristics. Traditionally ranking has been done as an absolute (total) ranking applying various multicriteria data analysis methods like simple additive ranking (SAR) or various utility functions (UFs) based rankings. An attractive alternative to these ranking methodologies appears to be partial order ranking (POR). The present paper compares different ranking methods like SAR, UF and POR. Significant discrepancies between the rankings are noted and it is concluded that partial order ranking, as a method without any pre-assumptions concerning possible relation between the single parameters, appears as the most attractive ranking methodology. In addition to the initial ranking partial order methodology offers a wide variety of analytical tools to elucidate the interplay between the objects to be ranked and the ranking parameters. In the present study is included an analysis of the relative importance of the single P, B and T parameters.

  6. Ranking efficient DMUs using minimizing distance in DEA

    NASA Astrophysics Data System (ADS)

    Ziari, Shokrollah; Raissi, Sadigh

    2016-01-01

    In many applications, ranking of decision making units (DMUs) is a problematic technical task procedure to decision makers in data envelopment analysis (DEA), especially when there are extremely efficient DMUs. In such cases, many DEA models may usually get the same efficiency score for different DMUs. Hence, there is a growing interest in ranking techniques yet. The main purpose of this paper is to overcome the lack of infeasibility and unboundedness in some DEA ranking methods. The proposed method is for ranking extreme efficient DMUs in DEA based on exploiting the leave-one out and minimizing distance between DMU under evaluation and virtual DMU.

  7. Low-Rank Matrix Factorization With Adaptive Graph Regularizer.

    PubMed

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

    2016-05-01

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

  8. 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).

  9. 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.

  10. Evaluation of short neck: new neck length percentiles and linear correlations with height and sitting height.

    PubMed

    Mahajan, P V; Bharucha, B A

    1994-10-01

    Qualitative impressions of neck length are often used as aids to dysmorphology in syndromes like Turner, Noonan, Klippel-Feil and in craniovertebral anomalies, some of which have serious neurological implications. There are no national or international standards for neck length. The present study attempted to create standards and percentile charts for Indian children and compute age-independent correlations of neck length with linear measurements such as standing and sitting height. A total of 2724 children of both sexes between 3 and 15 years, whose heights and weights conformed to ICMR standards were inducted. Neck length was measured by a modified two-point discriminator between two fixed bony points-inion and spinous process of C7 with the head held in neutral position. Percentiles (5th-95th) were constructed for both sexes. Growth was rapid from 3 to 6 years. Neck length formed a mean of 12.7 +/- 4.58% of height and 20.1 +/- 6.73% of sitting height. Age independent linear regression equations: Neck length = 10 + (0.035 x height) and Neck length = 9.65 + (0.07 x sitting height) were highly significant (p < 0.001). Neck length relationships of 30 randomly selected normal children clustered around the regression lines and 16 with genetic syndromes fell below the regression lines.

  11. Bayesian Thurstonian models for ranking data using JAGS.

    PubMed

    Johnson, Timothy R; Kuhn, Kristine M

    2013-09-01

    A Thurstonian model for ranking data assumes that observed rankings are consistent with those of a set of underlying continuous variables. This model is appealing since it renders ranking data amenable to familiar models for continuous response variables-namely, linear regression models. To date, however, the use of Thurstonian models for ranking data has been very rare in practice. One reason for this may be that inferences based on these models require specialized technical methods. These methods have been developed to address computational challenges involved in these models but are not easy to implement without considerable technical expertise and are not widely available in software packages. To address this limitation, we show that Bayesian Thurstonian models for ranking data can be very easily implemented with the JAGS software package. We provide JAGS model files for Thurstonian ranking models for general use, discuss their implementation, and illustrate their use in analyses.

  12. The effects of percentile versus fixed criterion schedules on smoking with equal incentive magnitude for initial abstinence.

    PubMed

    Romanowich, Paul; Lamb, R J

    2014-08-01

    Incentives have been successfully used to reduce smoking in hard-to-treat (HTT) smokers by progressively reinforcing lower levels of breath carbon monoxide (CO). When compared with schedules only providing incentives for smoking abstinence, using a progressive (percentile) criterion facilitates longer periods of smoking abstinence. However, participants receiving incentives for lower breath CO levels on percentile schedules typically earn more for their first abstinent breath CO sample relative to participants receiving incentives only for smoking abstinence. Many studies show that larger incentive magnitude increases abstinence rates. The present study tested the effects of different incentive schedules on rates of abstinence maintenance while holding the initial incentive magnitude constant for 93 HTT smokers to eliminate initial abstinence incentive magnitude as a potential confound. Smokers were randomized to percentile, fixed criterion, or random incentive schedules. The incentive magnitude for the first abstinent breath CO sample (<3 ppm) was $5 for percentile and fixed criterion incentive participants, and then increased by $0.50 for each consecutive abstinent breath CO sample. All groups had similar patterns of meeting the abstinence criterion for at least 1 visit. However, once this abstinence criterion was met, abstinence was more likely to be maintained by fixed criterion incentive participants. Unlike previous studies comparing percentile and fixed criterion schedules, percentile incentive schedules were not associated with longer periods of abstinence relative to fixed criterion incentive schedules. Further studies that manipulate initial incentive magnitude are needed to test whether the difference between the current and previous studies was due to initial incentive magnitude.

  13. Semi-quantitative spectrographic analysis and rank correlation in geochemistry

    USGS Publications Warehouse

    Flanagan, F.J.

    1957-01-01

    The rank correlation coefficient, rs, which involves less computation than the product-moment correlation coefficient, r, can be used to indicate the degree of relationship between two elements. The method is applicable in situations where the assumptions underlying normal distribution correlation theory may not be satisfied. Semi-quantitative spectrographic analyses which are reported as grouped or partly ranked data can be used to calculate rank correlations between elements. ?? 1957.

  14. Associated Factors and Standard Percentiles of Blood Pressure among the Adolescents of Jahrom City of Iran, 2014

    PubMed Central

    Sarikhani, Yaser; Emamghorashi, Fatemeh; Jafari, Fatemeh; Tabrizi, Reza; Karimpour, Saeed; Kalateh sadati, Ahmad; Akbari, Maryam

    2017-01-01

    Background. High blood pressure in adults is directly correlated with increased risk of cardiovascular diseases. Hypertension in childhood and adolescence could be considered among the major causes of this problem in adults. This study aimed to investigate the factors associated with hypertension among the adolescents of Jahrom city in Iran and also standard percentiles of blood pressure were estimated for this group. Methods. In this community-based cross-sectional study 983 high school students from different areas of the city were included using a multistage random cluster sampling method in 2014. Blood pressure, weight, and height of each student measured using standard methods. Data were analyzed by statistical software SPSS 16. Results. In total, 498 male and 454 female students were included in this study. Average systolic blood pressure of students was 110.27 mmHg with a variation range of 80.6–151.3. Average diastolic blood pressure was 71.76 mmHg with the variation range of 49.3–105. Results of this study indicated that there was a significant relationship between gender, body mass index, and parental education level with systolic and diastolic blood pressure of the students (P < 0.05). Conclusions. Body mass index was one of the most important changeable factors associated with blood pressure in adolescents. Paying attention to this factor in adolescence could be effective in prevention of cardiovascular diseases in adulthood. PMID:28191019

  15. Associated Factors and Standard Percentiles of Blood Pressure among the Adolescents of Jahrom City of Iran, 2014.

    PubMed

    Sarikhani, Yaser; Heydari, Seyed Taghi; Emamghorashi, Fatemeh; Jafari, Fatemeh; Tabrizi, Reza; Karimpour, Saeed; Kalateh Sadati, Ahmad; Akbari, Maryam

    2017-01-01

    Background. High blood pressure in adults is directly correlated with increased risk of cardiovascular diseases. Hypertension in childhood and adolescence could be considered among the major causes of this problem in adults. This study aimed to investigate the factors associated with hypertension among the adolescents of Jahrom city in Iran and also standard percentiles of blood pressure were estimated for this group. Methods. In this community-based cross-sectional study 983 high school students from different areas of the city were included using a multistage random cluster sampling method in 2014. Blood pressure, weight, and height of each student measured using standard methods. Data were analyzed by statistical software SPSS 16. Results. In total, 498 male and 454 female students were included in this study. Average systolic blood pressure of students was 110.27 mmHg with a variation range of 80.6-151.3. Average diastolic blood pressure was 71.76 mmHg with the variation range of 49.3-105. Results of this study indicated that there was a significant relationship between gender, body mass index, and parental education level with systolic and diastolic blood pressure of the students (P < 0.05). Conclusions. Body mass index was one of the most important changeable factors associated with blood pressure in adolescents. Paying attention to this factor in adolescence could be effective in prevention of cardiovascular diseases in adulthood.

  16. State Report Appendix: Arizona Student Achievement Program, Spring 1997. Individual Percentile Rank Scores by School, District, County, and State, Grades 3 through 12. Stanford Achievement Test, Ninth Edition.

    ERIC Educational Resources Information Center

    Arizona State Dept. of Education, Phoenix.

    This is the 17th year of statewide student testing under the Arizona Student Achievement Program. To fulfill the requirements of Arizona law, a nationally standardized, norm-referenced achievement test in the subjects of reading, language, and mathematics must be adopted and implemented for Arizona schools. For the 1996-97 school year, the State…

  17. 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.

  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. 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…

  1. 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…

  2. 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…

  3. 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…

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

    PubMed

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

    2014-05-01

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

  5. US dermatology residency program rankings.

    PubMed

    Aquino, Lisa L; Wen, Ge; Wu, Jashin J

    2014-10-01

    Unlike many other adult specialties, US News & World Report does not rank dermatology residency programs annually. We conducted a study to rank individual US dermatology residency programs based on set criteria. For each residency program, data from 2008 related to a number of factors were collected, including annual amount of National Institutes of Health (NIH) and Dermatology Foundation (DF) funding received; number of publications from full-time faculty members; number of faculty lectures given at 5 annual society meetings; and number of full-time faculty members who were on the editorial boards of 6 dermatology journals with the highest impact factors. Most of the data were obtained through extensive Internet searches, and missing data were obtained by contacting individual residency programs. The programs were ranked based on the prior factors according to a weighted ranking algorithm. A list of overall rankings also was created.

  6. Quantum probability ranking principle for ligand-based virtual screening.

    PubMed

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

    2017-04-01

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

  7. Quantum probability ranking principle for ligand-based virtual screening

    NASA Astrophysics Data System (ADS)

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

    2017-02-01

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

  8. Regression Equations for Monthly and Annual Mean and Selected Percentile Streamflows for Ungaged Rivers in Maine

    USGS Publications Warehouse

    Dudley, Robert W.

    2015-12-03

    The largest average errors of prediction are associated with regression equations for the lowest streamflows derived for months during which the lowest streamflows of the year occur (such as the 5 and 1 monthly percentiles for August and September). The regression equations have been derived on the basis of streamflow and basin characteristics data for unregulated, rural drainage basins without substantial streamflow or drainage modifications (for example, diversions and (or) regulation by dams or reservoirs, tile drainage, irrigation, channelization, and impervious paved surfaces), therefore using the equations for regulated or urbanized basins with substantial streamflow or drainage modifications will yield results of unknown error. Input basin characteristics derived using techniques or datasets other than those documented in this report or using values outside the ranges used to develop these regression equations also will yield results of unknown error.

  9. Development of a simplified finite element model of the 50th percentile male occupant lower extremity.

    PubMed

    Schwartz, Doron; Moreno, Daniel P; Stitzel, Joel D; Gayzik, F Scott

    2014-01-01

    A simplified lower extremity model was developed using the geometry from the Global Human Body Models Consortium (GHBMC) 50th percentile male occupant model v4.1.1 (M50) as a base. This simplified model contains 31.4x103 elements and has structures that represent bone (assumed rigid) and soft tissue. This element total is substantially reduced compared to 117.7x103 elements in the original M50 lower extremity. The purpose of this simplified computational model is to output rapid kinematic and kinetic data when detailed structural response or injury prediction data is not required. The development process included evaluating the effects of element size, material properties, and contact definitions on total run time and response. Two simulations were performed to analyze this model; a 4.9 m/s knee bolster impact and a 6.9 m/s lateral knee impact using LS-DYNA R6.1.1. The 40 ms knee bolster impact and lateral knee impact tests required 5 and 7 minutes to run, respectively on 4 cores. The original detailed M50 lower extremity model required 94 and 112 minutes to run the same boundary conditions, on the same hardware, representing a reduction in run time of on average 94%. A quantitative comparison was made by comparing the peak force of the impacts between the two models. This simplified leg model will become a component in a simplified full body model of the seated, 50th percentile male occupant. The significantly reduced run time will be valuable for parametric studies with a full body finite element model.

  10. Optimal ranking regime analysis of TreeFlow dendrohydrological reconstructions

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  11. 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.

  12. 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.

  13. 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…

  14. Control over response number by a targeted percentile schedule: reinforcement loss and the acute effects of d-amphetamine.

    PubMed Central

    Galbicka, G; Fowler, K P; Ritch, Z J

    1991-01-01

    Two fixed-consecutive-number-like procedures were used to examine effects of acute d-amphetamine administration on control over response number. In both procedures, rats were required to press the left lever at least once and then press the right lever to complete a trial. The consecutive left-lever presses on each trial comprised a "run." Under the targeted percentile schedule, reinforcement was provided if the current run length was closer to the target length (16) than half of the most recent 24 runs. This differentially reinforced run length while holding reinforcement probability constant at .5. A second group acquired the differentiation under the targeted percentile schedule, but were then shifted to a procedure that yoked reinforcement probability by subject and run length to that obtained under the targeted percentile schedule. The two procedures generated practically identical control run lengths, response rates, reinforcement probabilities, and reinforcement rates. Administration of d-amphetamine disrupted percentile responding to a greater degree than yoked control responding. This disruption decreased reinforcement frequency less in the former than the latter procedure. The similar baseline responding under these two procedures suggests that this difference in sensitivity was due to behavioral adjustments to drug prompted by reduction of reinforcement density in the yoked control but not the percentile schedule. These adjustments attenuate the drug's effects under the former, but not the latter, procedure. PMID:1955813

  15. 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.

  16. Ranking Theory and Conditional Reasoning.

    PubMed

    Skovgaard-Olsen, Niels

    2016-05-01

    Ranking theory is a formal epistemology that has been developed in over 600 pages in Spohn's recent book The Laws of Belief, which aims to provide a normative account of the dynamics of beliefs that presents an alternative to current probabilistic approaches. It has long been received in the AI community, but it has not yet found application in experimental psychology. The purpose of this paper is to derive clear, quantitative predictions by exploiting a parallel between ranking theory and a statistical model called logistic regression. This approach is illustrated by the development of a model for the conditional inference task using Spohn's (2013) ranking theoretic approach to conditionals.

  17. 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

  18. An Analysis of the Differences between Density-of-Use Ranking and Raw-Use Ranking of Library Journal Use.

    ERIC Educational Resources Information Center

    Mankin, Carole J.; Bastille, Jacqueline D.

    1981-01-01

    Compares raw-use ranking of journal titles held in libraries with dividing the raw-use frequency of titles by the actual linear shelf space of the title's file to obtain a density-of-use rank. The quality of the differences between the two methods is evaluated. Thirteen references are cited. (FM)

  19. 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)

  20. Parental Activity as Influence on Children`s BMI Percentiles and Physical Activity.

    PubMed

    Erkelenz, Nanette; Kobel, Susanne; Kettner, Sarah; Drenowatz, Clemens; Steinacker, Jürgen M

    2014-09-01

    Parents play a crucial role in the development of their children's lifestyle and health behaviour. This study aims to examine associations between parental physical activity (PA) and children's BMI percentiles (BMIPCT), moderate to vigorous PA (MVPA) as well as participation in organised sports. Height and body weight was measured in 1615 in German children (7.1 ± 0.6 years, 50.3% male) and converted to BMIPCT. Parental BMI was calculated based on self-reported height and body weight. Children's MVPA and sports participation as well as parental PA were assessed via parental questionnaire. Analysis of covariance (ANCOVA), controlling for age and family income was used to examine the association between parental and children's PA levels as well as BMIPCT. 39.7% of the parents classified themselves as physically active and 8.3% of children were classified as overweight or obese. Lower BMIPCT were observed with both parents being physically active (44.5 ± 26.3 vs. 50.2 ± 26.9 and 52.0 ± 28.4, respectively). There was no association between parental and children's PA levels but children with at least one active parent displayed a higher participation in organised sports (102.0 ± 96.6 and 117.7 ± 123.6 vs. 73.7 ± 100.0, respectively). Children of active parents were less likely to be overweight and obese. The lack of association between subjectively assessed parental PA and child MVPA suggests that parental support for PA in children is more important than parents being a role model. More active parents, however, may be more likely to facilitate participation in organised sports. These results underline the importance of the inclusion of parents in health promotion and obesity prevention programmes in children. Key pointsA higher prevalence of overweight or obese children was found with inactive parents.Children's BMI percentiles were lower if both parents were physically active compared to children whose parents were both inactive or only had one physically

  1. Parental Activity as Influence on Childrenˋs BMI Percentiles and Physical Activity

    PubMed Central

    Erkelenz, Nanette; Kobel, Susanne; Kettner, Sarah; Drenowatz, Clemens; Steinacker, Jürgen M.

    2014-01-01

    Parents play a crucial role in the development of their children’s lifestyle and health behaviour. This study aims to examine associations between parental physical activity (PA) and children’s BMI percentiles (BMIPCT), moderate to vigorous PA (MVPA) as well as participation in organised sports. Height and body weight was measured in 1615 in German children (7.1 ± 0.6 years, 50.3% male) and converted to BMIPCT. Parental BMI was calculated based on self-reported height and body weight. Children’s MVPA and sports participation as well as parental PA were assessed via parental questionnaire. Analysis of covariance (ANCOVA), controlling for age and family income was used to examine the association between parental and children’s PA levels as well as BMIPCT. 39.7% of the parents classified themselves as physically active and 8.3% of children were classified as overweight or obese. Lower BMIPCT were observed with both parents being physically active (44.5 ± 26.3 vs. 50.2 ± 26.9 and 52.0 ± 28.4, respectively). There was no association between parental and children’s PA levels but children with at least one active parent displayed a higher participation in organised sports (102.0 ± 96.6 and 117.7 ± 123.6 vs. 73.7 ± 100.0, respectively). Children of active parents were less likely to be overweight and obese. The lack of association between subjectively assessed parental PA and child MVPA suggests that parental support for PA in children is more important than parents being a role model. More active parents, however, may be more likely to facilitate participation in organised sports. These results underline the importance of the inclusion of parents in health promotion and obesity prevention programmes in children. Key points A higher prevalence of overweight or obese children was found with inactive parents. Children’s BMI percentiles were lower if both parents were physically active compared to children whose parents were both inactive or only had one

  2. Label Ranking Algorithms: A Survey

    NASA Astrophysics Data System (ADS)

    Vembu, Shankar; Gärtner, Thomas

    Label ranking is a complex prediction task where the goal is to map instances to a total order over a finite set of predefined labels. An interesting aspect of this problem is that it subsumes several supervised learning problems, such as multiclass prediction, multilabel classification, and hierarchical classification. Unsurprisingly, there exists a plethora of label ranking algorithms in the literature due, in part, to this versatile nature of the problem. In this paper, we survey these algorithms.

  3. Pregnancy prognosis in women with anti-Müllerian hormone below the tenth percentile.

    PubMed

    Koshy, Aby Kottal; Gudi, Anil; Shah, Amit; Bhide, Priya; Timms, Peter; Homburg, Roy

    2013-07-01

    Although serum anti-Müllerian hormone (AMH) is considered a good predictor of ovarian response during in vitro fertilisation (IVF), pregnancies have been reported with low values, questioning its usefulness as a predictor of treatment outcome. A retrospective study was therefore carried out to assess the IVF treatment outcomes in women with AMH below the tenth percentile of the study population. In all, 134 women with AMH ≤ 3 pmol/L underwent 180 IVF cycles. The mean age at the time of treatment was 37 ± 5 years. Fifty-three (29.4%) cycles were abandoned because of poor response to gonadotrophins, 12 (6.7%) due to absence of eggs at oocyte retrieval and 18 (10%) due to fertilisation failure. Seven (3.8%) had a biochemical pregnancy, 4 (2.2%) had a missed miscarriage and 8 (4.4%) had a live birth. When stratified by age, women older than 42 years had less number of follicles (p < 0.05) and those older than 39 years had less oocytes (p < 0.01) compared to those 35 years and younger. Live births declined with increasing age, when age was assessed as a continuous variable (p = 0.023). Women with low AMH levels have a high probability of treatment cancellation, failure to proceed to embryo transfer and a low chance of achieving a viable pregnancy.

  4. Percentile benchmarks in patients with rheumatoid arthritis: Health Assessment Questionnaire as a quality indicator (QI)

    PubMed Central

    Krishnan, Eswar; Tugwell, Peter; Fries, James F

    2004-01-01

    Physicians are in need of a simple objective, standardized tool to compare their patients with rheumatoid arthritis, as a group and individually, with national standards. The Disability Index of the Health Assessment Questionnaire (HAQ-DI) is a simple, robust tool that can fulfill these needs. However, use of this tool as a quality indicator (QI) is hampered by the unavailability of national reference values or benchmarks based on large, multicentric, heterogenous longitudinal patient cohorts. We utilized the 20-year longitudinal prospective data from 11 data banks of Arthritis Rheumatism and Aging Medical Information to calculate reference values for HAQ-DI. Overall, 6436 patients with rheumatoid arthritis were longitudinally followed for 32,324 person-years over the 20 years from 1981 to 2000. There were 64,647 HAQ-DI measurements, with an average of 19 measurements per person. Overall, 75% of patients were women and 89% were Caucasian; the median baseline age was 58.4 years and the median baseline HAQ-DI was 1.13. Few patients were treated with biologics. The HAQ-DI values had a Gaussian distribution except for the approximately 10% of observations showing no disability. Percentile benchmarks allow disability outcomes to be compared and contrasted between different patient populations. Reference values for the HAQ-DI, presented here numerically and graphically, can be used in clinical practice as a QI measure to track functional disability outcomes and to measure response to therapy, and by arthritis patients in self-management programs. PMID:15535828

  5. 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

  6. Estimation of rank correlation for clustered data.

    PubMed

    Rosner, Bernard; Glynn, Robert J

    2017-04-11

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

  7. 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.

  8. 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.

  9. Bayesian Inference of Natural Rankings in Incomplete Competition Networks

    NASA Astrophysics Data System (ADS)

    Park, Juyong; Yook, Soon-Hyung

    2014-08-01

    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.

  10. Body fat percentile curves for Korean children and adolescents: a data from the Korea National Health and Nutrition Examination Survey 2009-2010.

    PubMed

    Kim, Kirang; Yun, Sung Ha; Jang, Myoung Jin; Oh, Kyung Won

    2013-03-01

    A valid assessment of obesity in children and adolescents is important due to significant change in body composition during growth. This study aimed to develop percentile curves of body fat and fat free mass using the Lambda, Mu, and Sigma method, and to examine the relationship among body mass index (BMI), fat mass and fat free mass in Korean children and adolescents, using the Korea National Health and Nutrition Examination Survey (KNHANES) 2009-2010. The study subjects were 834 for boys and 745 for girls aged between 10 and 18 yr. Fat mass and fat free mass were measured by dual-energy x-ray absorptiometry. The patterns of development in body fat percentage, fat mass and fat free mass differed for boys and girls, showing a decreased fat mass with an increased fat free mass in boys but gradual increases with age in girls. The considerable proportion of boys and girls with relatively normal fat mass appeared to be misclassified to be at risk of overweight based on the BMI criteria. Therefore, the information on the percentiles of body fat and fat free mass with their patterns would be helpful to complement assessment of overweight and obesity based on BMI for Korean children and adolescents.

  11. 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…

  12. Development of THOR-FLx: A Biofidelic Lower Extremity for Use with 5th Percentile Female Crash Test Dummies.

    PubMed

    Shams, Tariq; Beach, David; Huang, Tsai-Jeon; Rangarajan, N; Haffner, Mark

    2002-11-01

    A new lower leg/ankle/foot system has been designed and fabricated to assess the potential for lower limb injuries to small females in the automotive crash environment. The new lower extremity can be retrofitted at present to the distal femur of the 5th percentile female Hybrid III dummy. Future plans are for integration of this design into the 5th percentile female THOR dummy now under development. The anthropometry of the lower leg and foot is based mainly on data developed by Robbins for the 5th percentile female, while the biomechanical response requirements are based upon scaling of 50th percentile male THOR-Lx responses. The design consists of the knee, tibia, ankle joints, foot, a representation of the Achilles tendon, and associated flesh/skins. The new lower extremity, known as THOR-FLx, is designed to be biofidelic under dynamic axial loading of the tibia, static and dynamic dorsiflexion, static plantarflexion and inversion/eversion. Instrumentation includes accelerometers, load cells, and rotary potentiometers to capture relevant kinematic and dynamic information from the foot and tibia. This paper will describe the performance requirements for THOR-FLx, the methodology used in its' development, results of component tests, and the biofidelity tests conducted on the full assembly.

  13. Construction of hyperelliptic function fields of high three-rank

    NASA Astrophysics Data System (ADS)

    Bauer, M.; Jacobson, M. J., Jr.; Lee, Y.; Scheidler, R.

    2008-03-01

    We present several explicit constructions of hyperelliptic function fields whose Jacobian or ideal class group has large 3 -rank. Our focus is on finding examples for which the genus and the base field are as small as possible. Most of our methods are adapted from analogous techniques used for generating quadratic number fields whose ideal class groups have high 3 -rank, but one method, applicable to finding large l -ranks for odd primes l geq 3, is new and unique to function fields. Algorithms, examples, and numerical data are included.

  14. 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

  15. Waist-to-Height Ratio Percentiles and Cutoffs for Obesity: A Cross-sectional Study in Brazilian Adolescents

    PubMed Central

    Zanetti Passos, Maria Aparecida; dos Santos, Luana Caroline; da Costa Machado, Helymar; Fisberg, Mauro

    2014-01-01

    ABSTRACT This study aimed to describe the distribution of waist-to-height ratio (WHtR) percentiles and cutoffs for obesity in Brazilian adolescents. A cross-sectional study including adolescents aged 10 to 15 years was conducted in the city of São Paulo, Brazil; anthropometric measurements (weight, height, and waist-circumference) were taken, and WHtRs were calculated and then divided into percentiles derived by using Least Median of Squares (LMS) regression. The receiver operating characteristic (ROC) curve was used in determining cutoffs for obesity (BMI ≥97th percentile) and Mann-Whitney and Kruskal-Wallis tests were used for comparing variables. The study included 8,019 adolescents from 43 schools, of whom 54.5% were female, and 74.8% attended public schools. Boys had higher mean WHtR than girls (0.45±0.06 vs 0.44±0.05; p=0.002) and higher WHtR at the 95th percentile (0.56 vs 0.54; p<0.05). The WHtR cutoffs according to the WHO criteria ranged from 0.467 to 0.506 and 0.463 to 0.496 among girls and boys respectively, with high sensitivity (82.8-95%) and specificity (84-95.5%). The WHtR was significantly associated with body adiposity measured by BMI. Its age-specific percentiles and cutoffs may be used as additional surrogate markers of central obesity and its co-morbidities. PMID:25395904

  16. Ranking inter-relationships between clusters

    NASA Astrophysics Data System (ADS)

    Wang, Tingting; Chen, Feng; Phoebe Chen, Yi-Ping

    2011-12-01

    The evaluation of the relationships between clusters is important to identify vital unknown information in many real-life applications, such as in the fields of crime detection, evolution trees, metallurgical industry and biology engraftment. This article proposes a method called 'mode pattern + mutual information' to rank the inter-relationship between clusters. The idea of the mode pattern is used to find outstanding objects from each cluster, and the mutual information criterion measures the close proximity of a pair of clusters. Our approach is different from the conventional algorithms of classifying and clustering, because our focus is not to classify objects into different clusters, but instead, we aim to rank the inter-relationship between clusters when the clusters are given. We conducted experiments on a wide range of real-life datasets, including image data and cancer diagnosis data. The experimental results show that our algorithm is effective and promising.

  17. Compressive Sensing via Nonlocal Smoothed Rank Function

    PubMed Central

    Fan, Ya-Ru; 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

  18. 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.

  19. Ranking asteroid threats

    NASA Astrophysics Data System (ADS)

    Showstack, Randy

    “Kiss your asteroid goodbye,” read the March 13, 1998, New York Post headline, which was far more sensational than Asteroid 1997 XF11's feared encounter with the Earth turned out to be. Fortunately, many other asteroids also have proven to be duds. But our pock-marked planet provides proof that occasional chunks of rock do shake up things on the Earth. They also suggest that it might be prudent to have some sort of method for sizing up potential danger—a type of Richter scale for understanding the risks posed by asteroids and comets. A new scale devised for rating the potential for near-Earth object (NEO) collisions with the planet may help to better communicate risks to scientists and the general public, according to the scale's creator, Richard Binzel, professor of Earth, Atmospheric and Planetary Sciences at the Massachusetts Institute of Technology.

  20. 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…

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

    NASA Astrophysics Data System (ADS)

    Chang, Heyou; Zheng, Hao

    2017-01-01

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

  2. 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.

  3. 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.

  4. A Nonconvex Optimization Framework for Low Rank Matrix Estimation*

    PubMed Central

    Zhao, Tuo; Wang, Zhaoran; Liu, Han

    2016-01-01

    We study the estimation of low rank matrices via nonconvex optimization. Compared with convex relaxation, nonconvex optimization exhibits superior empirical performance for large scale instances of low rank matrix estimation. However, the understanding of its theoretical guarantees are limited. In this paper, we define the notion of projected oracle divergence based on which we establish sufficient conditions for the success of nonconvex optimization. We illustrate the consequences of this general framework for matrix sensing. In particular, we prove that a broad class of nonconvex optimization algorithms, including alternating minimization and gradient-type methods, geometrically converge to the global optimum and exactly recover the true low rank matrices under standard conditions. PMID:28316458

  5. 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…

  6. 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.

  7. 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

  8. An efficient and rapid method for cDNA cloning from difficult templates using codon optimization and SOE-PCR: with human RANK and TIMP2 gene as examples.

    PubMed

    Huang, Gang; Wen, Qianjun; Gao, Qiangguo; Zhang, Fang; Bai, Yun

    2011-10-01

    As gene cloning from difficult templates with regionalized high GC content is a long recognized problem, we have developed a novel and reliable method to clone such genes. Firstly, the high GC content region of the target cDNA was synthesized directly after codon optimization and the remaining cDNA fragment without high GC content was generated by routine RT-PCR. Then the entire redesigned coding sequence of the target gene was obtained by fusing the above available two cDNA fragments with SOE-PCR (splicing by overlapping extension-PCR). We have cloned the human RANK gene (ten exons; CDS 1851 bp) using this strategy. The redesigned cDNA was transfected into an eukaryotic expression system (A459 cells) to verify its expression. RT-PCR and western blotting confirmed this. To validate our method, we also successfully cloned human TIMP2 gene (five exons; CDS 660 bp) also having a regionalized high GC content. Our strategy for combining codon optimization and SOE-PCR to clone difficult genes is thus feasible and potentially universally applicable.

  9. 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…

  10. 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

  11. 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

  12. 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.

  13. 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

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

    PubMed

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

    2014-11-01

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

  15. 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.

  16. Functional Multiplex PageRank

    NASA Astrophysics Data System (ADS)

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

    2016-10-01

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

  17. 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.

  18. Robust Generalized Low Rank Approximations of Matrices.

    PubMed

    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.

  19. 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

  20. Ranking chemical structures for drug discovery: a new machine learning approach.

    PubMed

    Agarwal, Shivani; Dugar, Deepak; Sengupta, Shiladitya

    2010-05-24

    With chemical libraries increasingly containing millions of compounds or more, there is a fast-growing need for computational methods that can rank or prioritize compounds for screening. Machine learning methods have shown considerable promise for this task; indeed, classification methods such as support vector machines (SVMs), together with their variants, have been used in virtual screening to distinguish active compounds from inactive ones, while regression methods such as partial least-squares (PLS) and support vector regression (SVR) have been used in quantitative structure-activity relationship (QSAR) analysis for predicting biological activities of compounds. Recently, a new class of machine learning methods - namely, ranking methods, which are designed to directly optimize ranking performance - have been developed for ranking tasks such as web search that arise in information retrieval (IR) and other applications. Here we report the application of these new ranking methods in machine learning to the task of ranking chemical structures. Our experiments show that the new ranking methods give better ranking performance than both classification based methods in virtual screening and regression methods in QSAR analysis. We also make some interesting connections between ranking performance measures used in cheminformatics and those used in IR studies.

  1. 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…

  2. 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...

  3. 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...

  4. 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...

  5. 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...

  6. 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…

  7. 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;…

  8. 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…

  9. 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

  10. 24 CFR 599.401 - Ranking of applications.

    Code of Federal Regulations, 2010 CFR

    2010-04-01

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

  11. 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.

  12. Reduced rank regression via adaptive nuclear norm penalization

    PubMed Central

    Chen, Kun; Dong, Hongbo; Chan, Kung-Sik

    2014-01-01

    Summary We propose an adaptive nuclear norm penalization approach for low-rank matrix approximation, and use it to develop a new reduced rank estimation method for high-dimensional multivariate regression. The adaptive nuclear norm is defined as the weighted sum of the singular values of the matrix, and it is generally non-convex under the natural restriction that the weight decreases with the singular value. However, we show that the proposed non-convex penalized regression method has a global optimal solution obtained from an adaptively soft-thresholded singular value decomposition. The method is computationally efficient, and the resulting solution path is continuous. The rank consistency of and prediction/estimation performance bounds for the estimator are established for a high-dimensional asymptotic regime. Simulation studies and an application in genetics demonstrate its efficacy. PMID:25045172

  13. Issue Management Risk Ranking Systems

    SciTech Connect

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

    1999-06-01

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

  14. 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.

  15. Multimodal biometric system using rank-level fusion approach.

    PubMed

    Monwar, Md Maruf; Gavrilova, Marina L

    2009-08-01

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

  16. 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

  17. 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

  18. 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.

  19. 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.

  20. Ranking of simultaneously presented choice options in animal preference experiments.

    PubMed

    Halekoh, Ulrich; Jørgensen, Erik; Bak Jensen, Margit; Pedersen, Lene Juul; Studnitz, Merete; Højsgaard, Søren

    2007-08-01

    We considered experiments where animals chose one of all possible simultaneously presented options. The animals might be observed at repeated occasions. In the ethological literature the analysis is often focused on testing the global hypothesis of no difference in preferences by non-parametric methods. This fails to address the estimation of a ranking. Often this approach cannot adequately reflect the experimental setting and the repeated measurement structure. Therefore, we propose to model the choice probabilities for the options with a multinomial logistic model. The correlation induced by repeated measurements is incorporated by animal specific random intercepts. The ranking of the options is taken as the order of the choice probabilities. Adopting a Bayesian approach samples from the posterior distribution of the choice probabilities provide directly samples from the posterior of the rankings. Based on this an estimate of the ranking and description of its variability can be derived. The computation was performed via Markov chain Monte Carlo sampling and was implemented using WinBUGS. We illustrate our approach with an experiment to determine the preference of pigs for three different rooting materials. The proposed method allowed deriving an overall ranking for different combinations of the materials and the spatial positioning.

  1. 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.

  2. 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

  3. Error Analysis of Stochastic Gradient Descent Ranking.

    PubMed

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

    2012-12-31

    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.

  4. Dynamics of ranking processes in complex systems.

    PubMed

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

    2012-09-21

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

  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.

  6. Otto Rank: beginnings, endings, and current experience.

    PubMed

    Novey, R

    1983-01-01

    I have traced the theories of Otto Rank as they appeared in his major technical writings. Against this background, I have discussed references to Rank in past and contemporary psychoanalytic literature. This paper describes three important contributions of Rank--his birth trauma theory, leading to his theory of the birth of the self; his emphasis on present experience (forerunner of the current "here-and-now" theory); and his writings about the creative potential of the termination process.

  7. On Boolean matrices with full factor rank

    SciTech Connect

    Shitov, Ya

    2013-11-30

    It is demonstrated that every (0,1)-matrix of size n×m having Boolean rank n contains a column with at least √n/2−1 zero entries. This bound is shown to be asymptotically optimal. As a corollary, it is established that the size of a full-rank Boolean matrix is bounded from above by a function of its tropical and determinantal ranks. Bibliography: 16 titles.

  8. 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…

  9. 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…

  10. 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.

  11. 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.

  12. Triceps and Subscapular Skinfold Thickness Percentiles and Cut-Offs for Overweight and Obesity in a Population-Based Sample of Schoolchildren and Adolescents in Bogota, Colombia

    PubMed Central

    Ramírez-Vélez, Robinson; López-Cifuentes, Mario Ferney; Correa-Bautista, Jorge Enrique; González-Ruíz, Katherine; González-Jiménez, Emilio; Córdoba-Rodríguez, Diana Paola; Vivas, Andrés; Triana-Reina, Hector Reynaldo; Schmidt-RioValle, Jacqueline

    2016-01-01

    The assessment of skinfold thickness is an objective measure of adiposity. The aims of this study were to establish Colombian smoothed centile charts and LMS L (Box–Cox transformation), M (median), and S (coefficient of variation) tables for triceps, subscapular, and triceps + subscapular skinfolds; appropriate cut-offs were selected using receiver operating characteristic (ROC) analysis based on a population-based sample of children and adolescents in Bogotá, Colombia. A cross-sectional study was conducted in 9618 children and adolescents (55.7% girls; age range of 9–17.9 years). Triceps and subscapular skinfold measurements were obtained using standardized methods. We calculated the triceps + subscapular skinfold (T + SS) sum. Smoothed percentile curves for triceps and subscapular skinfold thickness were derived using the LMS method. ROC curve analyses were used to evaluate the optimal cut-off point of skinfold thickness for overweight and obesity, based on the International Obesity Task Force definitions. Subscapular and triceps skinfolds and T + SS were significantly higher in girls than in boys (p < 0.001). The ROC analysis showed that subscapular and triceps skinfolds and T + SS have a high discriminatory power in the identification of overweight and obesity in the sample population in this study. Our results provide sex- and age-specific normative reference standards for skinfold thickness values from a population from Bogotá, Colombia. PMID:27669294

  13. Triceps and Subscapular Skinfold Thickness Percentiles and Cut-Offs for Overweight and Obesity in a Population-Based Sample of Schoolchildren and Adolescents in Bogota, Colombia.

    PubMed

    Ramírez-Vélez, Robinson; López-Cifuentes, Mario Ferney; Correa-Bautista, Jorge Enrique; González-Ruíz, Katherine; González-Jiménez, Emilio; Córdoba-Rodríguez, Diana Paola; Vivas, Andrés; Triana-Reina, Hector Reynaldo; Schmidt-RioValle, Jacqueline

    2016-09-24

    The assessment of skinfold thickness is an objective measure of adiposity. The aims of this study were to establish Colombian smoothed centile charts and LMS L (Box-Cox transformation), M (median), and S (coefficient of variation) tables for triceps, subscapular, and triceps + subscapular skinfolds; appropriate cut-offs were selected using receiver operating characteristic (ROC) analysis based on a population-based sample of children and adolescents in Bogotá, Colombia. A cross-sectional study was conducted in 9618 children and adolescents (55.7% girls; age range of 9-17.9 years). Triceps and subscapular skinfold measurements were obtained using standardized methods. We calculated the triceps + subscapular skinfold (T + SS) sum. Smoothed percentile curves for triceps and subscapular skinfold thickness were derived using the LMS method. ROC curve analyses were used to evaluate the optimal cut-off point of skinfold thickness for overweight and obesity, based on the International Obesity Task Force definitions. Subscapular and triceps skinfolds and T + SS were significantly higher in girls than in boys (p < 0.001). The ROC analysis showed that subscapular and triceps skinfolds and T + SS have a high discriminatory power in the identification of overweight and obesity in the sample population in this study. Our results provide sex- and age-specific normative reference standards for skinfold thickness values from a population from Bogotá, Colombia.

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

    PubMed

    Schubert, András

    2015-08-09

    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.

  15. A Comparison of Teacher Rankings of Reading Readiness, Metropolitan Readiness Test Score Rankings, and Socioeconomic Status Rankings of First Graders.

    ERIC Educational Resources Information Center

    Elijah, David V., Jr.

    The purpose of this study was: (1) to determine to what extent teacher rankings of reading readiness compare with reading readiness test results, (2) to determine to what extent teacher rankings of reading readiness compare with pupil socioeconomic status, and (3) to determine to what extent readiness test results compare with pupil socioeconomic…

  16. 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.

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

    PubMed

    Zeng, Wenyi; Li, Junhong

    2014-01-01

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

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

    PubMed

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

    2016-03-10

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

  19. 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

  20. 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.

  1. Calculating PageRank in a changing network with added or removed edges

    NASA Astrophysics Data System (ADS)

    Engström, Christopher; Silvestrov, Sergei

    2017-01-01

    PageRank was initially developed by S. Brinn and L. Page in 1998 to rank homepages on the Internet using the stationary distribution of a Markov chain created using the web graph. Due to the large size of the web graph and many other real world networks fast methods to calculate PageRank is needed and even if the original way of calculating PageRank using a Power iterations is rather fast, many other approaches have been made to improve the speed further. In this paper we will consider the problem of recalculating PageRank of a changing network where the PageRank of a previous version of the network is known. In particular we will consider the special case of adding or removing edges to a single vertex in the graph or graph component.

  2. 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…

  3. 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…

  4. Gender Equity in Academic Rank and Salary.

    ERIC Educational Resources Information Center

    Smart, John C.

    1991-01-01

    Study of gender disparities in rank/salary of college faculty used causal model to examine variables commonly used in human capital and structural/functional perspectives that have guided most research on gender equity. More than 60 percent of total effect of gender on academic rank/salaries is indirect. Model's usefulness and implications for…

  5. 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…

  6. 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…

  7. Canadian University Rankings: Buyer Beware Once Again

    ERIC Educational Resources Information Center

    Page, Stewart; Cramer, Kenneth M.; Page, Laura

    2010-01-01

    We present a data-based perspective concerning recent (e.g., 2008) "Maclean's" magazine rankings of Canadian universities, including cluster analysis of the 2008 data. Canadian universities empirically resemble and relate to each other in a manner different from their formal classification and final rank ordering in the…

  8. 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…

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

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

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

  10. 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

  11. Downward percentile-crossing as an indicator of an adverse prenatal environment

    PubMed Central

    Lampl, Michelle; Gotsch, Francesca; Kusanovic, Juan Pedro; Espinoza, Jimmy; Goncalves, Luis; Gomez, Ricardo; Nien, Jyh Kae; Frongillo, Edward A.; Romero, Roberto

    2011-01-01

    Background Postnatal health sequelae associated with low birth weight have been attributed to ‘poor fetal growth’ from inferred adverse prenatal environments; risks augmented by infant growth rates. Identifying prenatal growth-restricting events is essential to clarify pathways and mechanisms of fetal growth. Aim The specific aim of this investigation was to examine whether an episode of preterm labor may compromise fetal growth. Subjects and methods Fetal size at the end of the second trimester and birth were compared among a sample of women with uncomplicated pregnancies (n=3167) and those who experienced preterm labor (<37 weeks) and subsequently delivered at term (>=37 weeks, n=147). Fetal weight was estimated from ultrasound measures and changes in weight standard scores across the third trimester investigated significant centile-crossing (> 0.67 standard deviation score change). Results Fetuses delivered at term after an episode of preterm labor were smaller at birth relative to their peers than at the end of the second trimester, and were 47% more likely to experience clinically significant downward centile crossing (p<0.05) than their peers (OR 1.47, 95% CI 1.04-2.07) Conclusion An episode of preterm labor may signal an adverse prenatal environment for term-delivered neonates. Epidemiologically silent events in the natural history of pregnancy are an understudied source of fetal growth compromise as inferred by small birth size among peers. PMID:18821324

  12. Comparing classical and quantum PageRanks

    NASA Astrophysics Data System (ADS)

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

    2017-01-01

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

  13. Boolean versus ranked querying for biomedical systematic reviews

    PubMed Central

    2010-01-01

    Background The process of constructing a systematic review, a document that compiles the published evidence pertaining to a specified medical topic, is intensely time-consuming, often taking a team of researchers over a year, with the identification of relevant published research comprising a substantial portion of the effort. The standard paradigm for this information-seeking task is to use Boolean search; however, this leaves the user(s) the requirement of examining every returned result. Further, our experience is that effective Boolean queries for this specific task are extremely difficult to formulate and typically require multiple iterations of refinement before being finalized. Methods We explore the effectiveness of using ranked retrieval as compared to Boolean querying for the purpose of constructing a systematic review. We conduct a series of experiments involving ranked retrieval, using queries defined methodologically, in an effort to understand the practicalities of incorporating ranked retrieval into the systematic search task. Results Our results show that ranked retrieval by itself is not viable for this search task requiring high recall. However, we describe a refinement of the standard Boolean search process and show that ranking within a Boolean result set can improve the overall search performance by providing early indication of the quality of the results, thereby speeding up the iterative query-refinement process. Conclusions Outcomes of experiments suggest that an interactive query-development process using a hybrid ranked and Boolean retrieval system has the potential for significant time-savings over the current search process in the systematic reviewing. PMID:20937152

  14. 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.

  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. 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)…

  17. 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...

  18. Ranking tributaries for setting remediation priorities in a TMDL context.

    PubMed

    Stringfellow, William T

    2008-05-01

    The San Joaquin River (SJR) in the Central Valley of California has been designated an impaired waterbody based on its loss of fisheries-related beneficial uses and the river is now subject to regulation under total maximum daily load (TMDL) rules. For impaired waterbodies, numeric standards alone may not be sufficient to establish remediation priorities and priorities must be established by comparing drainages to each other. Data collected as part of regional water quality (WQ) studies in the SJR Valley were not normally distributed, so nonparametric methods based on ranking were used to compare the WQ of individual tributaries and drainages. Normalized rank means (NRMs) were calculated from ranked data and NRMs were mapped to identify priority drainages for WQ improvement activities. NRMs for individual parameters were combined into indexes that are useful for examining the relative importance of different drainages for multiple parameters simultaneously. Indexes were developed for eutrophication and overall WQ. This ranking approach is being proposed as an easily understood, transparent, and scientifically rigorous method to assess the relative WQ impact of individual drainages and set watershed remediation priorities.

  19. A multiple shift QR-step for structured rank matrices

    NASA Astrophysics Data System (ADS)

    Vandebril, Raf; van Barel, Marc; Mastronardi, Nicola

    2010-01-01

    Eigenvalue computations for structured rank matrices are the subject of many investigations nowadays. There exist methods for transforming matrices into structured rank form, QR-algorithms for semiseparable and semiseparable plus diagonal form, methods for reducing structured rank matrices efficiently to Hessenberg form and so forth. Eigenvalue computations for the symmetric case, involving semiseparable and semiseparable plus diagonal matrices have been thoroughly explored. A first attempt for computing the eigenvalues of nonsymmetric matrices via intermediate Hessenberg-like matrices (i.e. a matrix having all subblocks in the lower triangular part of rank at most one) was restricted to the single shift strategy. Unfortunately this leads in general to the use of complex shifts switching thereby from real to complex operations. This paper will explain a general multishift implementation for Hessenberg-like matrices (semiseparable matrices are a special case and hence also admit this approach). Besides a general multishift QR-step, this will also admit restriction to real computations when computing the eigenvalues of arbitrary real matrices. Details on the implementation are provided as well as numerical experiments proving the viability of the presented approach.

  20. Inhibition effect of enteropeptidase on RANKL-RANK signalling by cleavage of RANK.

    PubMed

    Zhao, Yunfeng; Jin, Mengmeng; Ma, Juan; Zhang, Shiqian; Li, Wei; Chen, Yuan; Zhou, Yingsheng; Tao, Hong; Liu, Yu; Wang, Lei; Han, Huamin; Niu, Ge; Tao, Hua; Liu, Changzhen; Gao, Bin

    2013-09-17

    Enteropeptidase can cleave trypsinogen on the sequence of Asp-Asp-Asp-Asp-Lys and plays an important role in food digestion. The RANKL-RANK signalling pathway plays a pivotal role in bone remodelling. In this study, we reported that enteropeptidase can inhibit the RANKL-RANK signalling pathway through the cleavage of RANK. A surrogate peptide blocking assay indicated that enteropeptidase could specifically cleave RANK on the sequence NEEDK. Osteoclast differentiation assay and NF-κB activity assay confirmed that enteropeptidase could inhibit osteoclastogenesis in vitro through the cleavage of RANK. This is the first study to prove that the RANKL-RANK signalling pathway can be inhibited by cleavage of RANK instead of targeting RANKL.

  1. Adiabatic quantum algorithm for search engine ranking.

    PubMed

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

    2012-06-08

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

  2. 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.

  3. 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.

  4. Ranking important nodes in complex networks by simulated annealing

    NASA Astrophysics Data System (ADS)

    Sun, Yu; Yao, Pei-Yang; Wan, Lu-Jun; Shen, Jian; Zhong, Yun

    2017-02-01

    In this paper, based on simulated annealing a new method to rank important nodes in complex networks is presented. First, the concept of an importance sequence (IS) to describe the relative importance of nodes in complex networks is defined. Then, a measure used to evaluate the reasonability of an IS is designed. By comparing an IS and the measure of its reasonability to a state of complex networks and the energy of the state, respectively, the method finds the ground state of complex networks by simulated annealing. In other words, the method can construct a most reasonable IS. The results of experiments on real and artificial networks show that this ranking method not only is effective but also can be applied to different kinds of complex networks. Project supported by the National Natural Science Foundation of China (Grant No. 61573017) and the Natural Science Foundation of Shaanxi Province, China (Grant No. 2016JQ6062).

  5. A Universal Rank-Size Law

    PubMed Central

    2016-01-01

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

  6. Otto Rank and man's urge to immortality.

    PubMed

    Goldwert, M

    1985-04-01

    Otto Rank, one of Sigmund Freud's original followers, posited the existence of an "urge to immortality" as man's deepest drive. In his Psychology and the Soul, Rank traced the desire for immortality through four historical eras, with particular emphasis on the creativity of the hero and the artist. By the end of his life, Rank had not only repudiated orthodox psychoanalysis and developed then abandoned a psychology of the will, he had moved "beyond psychology" to a religious view of history and the nature of man.

  7. Ranked set sampling with unequal samples.

    PubMed

    Bhoj, D S

    2001-09-01

    A ranked set sampling procedure with unequal samples (RSSU) is proposed and used to estimate the population mean. This estimator is then compared with the estimators based on the ranked set sampling (RSS) and median ranked set sampling (MRSS) procedures. It is shown that the relative precisions of the estimator based on RSSU are higher than those of the estimators based on RSS and MRSS. An example of estimating the mean diameter at breast height of longleaf-pine trees on the Wade Tract in Thomas County, Georgia, is presented.

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

    PubMed

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

    2012-02-21

    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 ofmicrogravity, 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 UFHADMand UFHADF could be useful in designing dose reduction strategies through optimized positioning of an astronaut during encounters with solar particle events.

  9. A full ranking for decision making units using ideal and anti-ideal points in DEA.

    PubMed

    Barzegarinegad, A; Jahanshahloo, G; Rostamy-Malkhalifeh, M

    2014-01-01

    We propose a procedure for ranking decision making units in data envelopment analysis, based on ideal and anti-ideal points in the production possibility set. Moreover, a model has been introduced to compute the performance of a decision making unit for these two points through using common set of weights. One of the best privileges of this method is that we can make ranking for all decision making units by solving only three programs, and also solving these programs is not related to numbers of decision making units. One of the other advantages of this procedure is to rank all the extreme and nonextreme efficient decision making units. In other words, the suggested ranking method tends to seek a set of common weights for all units to make them fully ranked. Finally, it was applied for different sets holding real data, and then it can be compared with other procedures.

  10. Iterative resource allocation for ranking spreaders in complex networks

    NASA Astrophysics Data System (ADS)

    Ren, Zhuo-Ming; Zeng, An; Chen, Duan-Bing; Liao, Hao; Liu, Jian-Guo

    2014-05-01

    Ranking the spreading influence of nodes in networks is a very important issue with wide applications in many different fields. Various topology-based centrality measures have been proposed to identify influential spreaders. However, the spreading influence of a node is usually not only determined by its own centrality but also largely influenced by the centrality of neighbors. To incorporate the centrality information of neighbors in ranking spreaders, we design an iterative resource allocation (IRA) process in which the resource of nodes distributes to their neighbors according to neighbors' centrality. After iterations, the resource amount on each node will be stable and the final resources of nodes are used to rank their spreading influence. The iterative process can be applied to many traditional centrality measures including degree, K-shell, closeness, and betweenness. The validation of our method is based on the susceptible-infected-recovered (SIR) spreading in four representative real datasets. The results show that the ranking accuracy of the traditional centrality measures is remarkably enhanced by IRA.

  11. Denoising MR spectroscopic imaging data with low-rank approximations.

    PubMed

    Nguyen, Hien M; Peng, Xi; Do, Minh N; Liang, Zhi-Pei

    2013-01-01

    This paper addresses the denoising problem associated with magnetic resonance spectroscopic imaging (MRSI), where signal-to-noise ratio (SNR) has been a critical problem. A new scheme is proposed, which exploits two low-rank structures that exist in MRSI data, one due to partial separability and the other due to linear predictability. Denoising is performed by arranging the measured data in appropriate matrix forms (i.e., Casorati and Hankel) and applying low-rank approximations by singular value decomposition (SVD). The proposed method has been validated using simulated and experimental data, producing encouraging results. Specifically, the method can effectively denoise MRSI data in a wide range of SNR values while preserving spatial-spectral features. The method could prove useful for denoising MRSI data and other spatial-spectral and spatial-temporal imaging data as well.

  12. 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.

  13. Texas Students Rank Prestige of Careers.

    ERIC Educational Resources Information Center

    Hale, Dennis

    1979-01-01

    A survey of 701 Texas high school students revealed that they ranked the prestige of six careers in the following order: (1) minister, (2) television reporter, (3) accountant, (4) policeman, (5) high school teacher, (6) newspaper reporter. (GT)

  14. Superfund Hazard Ranking System Training Course

    EPA Pesticide Factsheets

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

  15. Green Power Partnership Top Partner Rankings

    EPA Pesticide Factsheets

    EPA's Green Power Partnership is a voluntary program designed to reduce the environmental impact of electricity generation by promoting renewable energy. Top Partner Rankings highlight the annual green power use of leading Green Power Partners.

  16. 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

  17. 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.

  18. 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.

  19. 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.

  20. Evaluation and ranking of enzyme designs

    PubMed Central

    Kiss, Gert; Röthlisberger, Daniela; Baker, David; Houk, KN

    2010-01-01

    In 2008, a successful computational design procedure was reported that yielded active enzyme catalysts for the Kemp elimination. Here, we studied these proteins together with a set of previously unpublished inactive designs to determine the sources of activity or lack thereof, and to predict which of the designed structures are most likely to be catalytic. Methods that range from quantum mechanics (QM) on truncated model systems to the treatment of the full protein with ONIOM QM/MM and AMBER molecular dynamics (MD) were explored. The most effective procedure involved molecular dynamics, and a general MD protocol was established. Substantial deviations from the ideal catalytic geometries were observed for a number of designs. Penetration of water into the catalytic site and insufficient residue-packing around the active site are the main factors that can cause enzyme designs to be inactive. Where in the past, computational evaluations of designed enzymes were too time-extensive for practical considerations, it has now become feasible to rank and refine candidates computationally prior to and in conjunction with experimentation, thus markedly increasing the efficiency of the enzyme design process. PMID:20665693

  1. 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.

  2. Accelerating Parameter Mapping with a Locally Low Rank Constraint

    PubMed Central

    Zhang, Tao; Pauly, John M.; Levesque, Ives R.

    2014-01-01

    Purpose To accelerate MR parameter mapping (MRPM) using a locally low rank (LLR) constraint, and the combination of parallel imaging (PI) and the LLR constraint. Theory and Methods An LLR method is developed for MRPM and compared with a globally low rank (GLR) method in a multi-echo spin-echo T2 mapping experiment. For acquisition with coil arrays, a combined LLR and PI method is proposed. The proposed method is evaluated in a variable flip angle T1 mapping experiment and compared with the LLR method and PI alone. Results In the multi-echo spin-echo T2 mapping experiment, the LLR method is more accurate than the GLR method for acceleration factors 2 and 3, especially for tissues with high T2 values. Variable flip angle T1 mapping is achieved by acquiring datasets with 10 flip angles, each dataset accelerated by a factor of 6, and reconstructed by the proposed method with a small normalized root mean square error of 0.025. Conclusion The LLR method is likely superior to the GLR method for MRPM. The proposed combined LLR and PI method has better performance than the two methods alone, especially with highly accelerated acquisition. PMID:24500817

  3. Iran Mortality and Measures of Risk: Rankings for Public policy

    PubMed Central

    Aalabaf-Sabaghi, M

    2010-01-01

    Background: This paper offers mortality risk rankings for Iranian mortality data. It extends methods to include mixed cohorts, tests changes in mortality risks, compares measures of risk and discusses public policy implications. Methods: The methodology used in risk measures takes current practice and extends it to include variations in population dynamics. The specification is presented and compared with existing literature. Results: Our findings confirm literature results in the re-ordering that takes place when different risk measures are used. In addition, we find there is consistency in risk rankings between 1999 and 2000 records of Iranian mortality data. Thus, these risk measures are stable, robust across time and relay risk information consistently. Conclusions: There are considerable implications in adopting particular risk measures for public policy. However, given properties of risk measures discussed here, it is clear that policy makers can select relevant risk measures depending on their priorities. PMID:23112989

  4. Direct liquefaction of low-rank coals

    SciTech Connect

    Rindt, J.R.; Hetland, M.D.; Knudson, C.L.; Willson, W.G.

    1988-04-01

    Co-processing of low-rank coals (LRCs) with petroleum resids under mild conditions may produce a product that extends petroleum refinery feeds with a partially coal-derived material. These co-processing products may also provide a lower-cost way to introduce coal-derived materials into the commercial market. In this staged process, the petroleum resid acts as a solvent, aiding in the solubilization of the coal during the first stage, and both the dissolved coal and the resid are upgraded during a second-stage catalytic hydrogenation. Another method of upgrading coal in a liquefaction process is the ChemCoal Process. The process uses chemical methods to transform coal into clean solid and liquid products. It features low-severity conversion of coal in a phenolic solvent, using an alkali promotor and carbon monoxide as the reductant. Oil agglomeration has been used to reduce the ash and mineral matter in bituminous coals to obtain a product with increased heating value, reduced moisture, and lower sulfur content. This method can be used to produce a clean coal feedstock for liquefaction. During agglomeration, an oil is used to preferentially wet the organic phases of the coal, and water is used to wet the minerals, resulting in a separation of ash and water from the coal. The primary objective of this project is to expand the scientific and engineering data base of LRC liquefaction by investigating direct liquefaction processes that will produce the most competitive feedstocks or liquid fuels. The work effort which was proposed for the second year of this cooperative agreement dealt primarily with co-processing and the ChemCoal Process.

  5. Assessment of reproducibility of thigh marker ranking during walking and landing tasks.

    PubMed

    Monnet, Tony; Thouzé, Arsène; Pain, Matt T G; Begon, Mickaël

    2012-10-01

    The aim of this paper is to analyse the repeatability of marker deformation and marker ranking across subjects and motor tasks. A method based on the solidification of the thigh with optimized rototranslation was applied which used 26 markers placed on the left thigh. During five trials of landing and five trials of walking for eight participants, the deformation between the actual positions of the 26 markers and the recalled positions from solidification were calculated. Markers were then sorted and ranked from the most deformed to the least deformed. Like previous studies, marker deformation found in this paper is subject and movement-dependant. The reproducibility of the marker rankings was assessed using Kendall's coefficient of concordance. Results highlighted that the marker ranking was similar between the trials of landing and between the trials of walking. Moreover, for walking and landing the rankings were consistent across the eight subjects.

  6. A heuristic biomarker selection approach based on professional tennis player ranking strategy.

    PubMed

    Han, Bin; Xie, Ruifei; Li, Lihua; Zhu, Lei; Wang, Shen

    2014-01-01

    Extracting significant features from high-dimension and small sample size biological data is a challenging problem. Recently, Michał Draminski proposed the Monte Carlo feature selection (MC) algorithm, which was able to search over large feature spaces and achieved better classification accuracies. However in MC the information of feature rank variations is not utilized and the ranks of features are not dynamically updated. Here, we propose a novel feature selection algorithm which integrates the ideas of the professional tennis players ranking, such as seed players and dynamic ranking, into Monte Carlo simulation. Seed players make the feature selection game more competitive and selective. The strategy of dynamic ranking ensures that it is always the current best players to take part in each competition. The proposed algorithm is tested on 8 biological datasets. Results demonstrate that the proposed method is computationally efficient, stable and has favorable performance in classification.

  7. Discriminant Context Information Analysis for Post-Ranking Person Re-Identification.

    PubMed

    Garcia, Jorge; Martinel, Niki; Gardel, Alfredo; Bravo, Ignacio; Foresti, Gian Luca; Micheloni, Christian

    2017-01-16

    Existing approaches for person re-identification are mainly based on creating distinctive representations or on learning optimal metrics. The achieved results are then provided in form of a list of ranked matching persons. It often happens that the true match is not ranked first but it is in the first positions. This is mostly due to the visual ambiguities shared between the true match and other "similar" persons. At the current state, there is a lack of a study of such visual ambiguities which limit the re-identification performance within the first ranks. We believe that an analysis of the similar appearances of the first ranks can be helpful in detecting, hence removing, such visual ambiguities. We propose to achieve such a goal by introducing an unsupervised post-ranking framework. Once the initial ranking is available, content and context sets are extracted. Then, these are exploited to remove the visual ambiguities and to obtain the discriminant feature space which is finally exploited to compute the new ranking. An in-depth analysis of the performance achieved on three public benchmark datasets support our believes. For every dataset, the proposed method remarkably improves the first ranks results and outperforms state-of-the-art approaches.

  8. Constrained low-rank gamut completion for robust illumination estimation

    NASA Astrophysics Data System (ADS)

    Zhou, Jianshen; Yuan, Jiazheng; Liu, Hongzhe

    2017-02-01

    Illumination estimation is an important component of color constancy and automatic white balancing. According to recent survey and evaluation work, the supervised methods with a learning phase are competitive for illumination estimation. However, the robustness and performance of any supervised algorithm suffer from an incomplete gamut in training image sets because of limited reflectance surfaces in a scene. In order to address this problem, we present a constrained low-rank gamut completion algorithm, which can replenish gamut from limited surfaces in an image, for robust illumination estimation. In the proposed algorithm, we first discuss why the gamut completion is actually a low-rank matrix completion problem. Then a constrained low-rank matrix completion framework is proposed by adding illumination similarities among the training images as an additional constraint. An optimization algorithm is also given out by extending the augmented Lagrange multipliers. Finally, the completed gamut based on the proposed algorithm is fed into the support vector regression (SVR)-based illumination estimation method to evaluate the effect of gamut completion. The experimental results on both synthetic and real-world image sets show that the proposed gamut completion model not only can effectively improve the performance of the original SVR method but is also robust to the surface insufficiency in training samples.

  9. 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.

  10. Ranking welding intensity in pyroclastic deposits

    NASA Astrophysics Data System (ADS)

    Quane, Steven L.; Russell, James K.

    2005-02-01

    Welding of pyroclastic deposits involves flattening of glassy pyroclasts under a compactional load at temperatures above the glass transition temperature. Progressive welding is recorded by changes in the petrographic (e.g., fabric) and physical (e.g., density) properties of the deposits. Mapping the intensity of welding can be integral to studies of pyroclastic deposits, but making systematic comparisons between deposits can be problematical. Here we develop a scheme for ranking welding intensity in pyroclastic deposits on the basis of petrographic textural observations (e.g., oblateness of pumice lapilli and micro-fabric orientation) and measurements of physical properties, including density, porosity, point load strength and uniaxial compressive strength. Our dataset comprises measurements on 100 samples collected from a single cooling unit of the Bandelier Tuff and parallel measurements on 8 samples of more densely welded deposits. The proposed classification comprises six ranks of welding intensity ranging from unconsolidated (Rank I) to obsidian-like vitrophyre (Rank VI) and should allow for reproducible mapping of subtle variations in welding intensity between different deposits. The application of the ranking scheme is demonstrated by using published physical property data on welded pyroclastic deposits to map the total accumulated strain and to reconstruct their pre-welding thicknesses.

  11. 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.

  12. 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.

  13. Higher-rank fields and currents

    NASA Astrophysics Data System (ADS)

    Gelfond, O. A.; Vasiliev, M. A.

    2016-10-01

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

  14. Ranking of facial profiles among Asians.

    PubMed

    Lew, K K; Soh, G; Loh, E

    1992-01-01

    The purpose of this study was to determine the facial profile preferences in a sample of 1,189 Asian teenagers (aged 15.3 +/- 3.2 years). Five facial profile types were computer-generated by trained personnel (orthodontists and oral maxillofacial surgeons) to represent distinct facial types. Subjects were asked to rank the profiles in descending order of attractiveness. The ranking was as follows: orthognathic profile, bimaxillary retrusive profile, bimaxillary protrusive profile, mandibular retrognathic profile, and mandibular prognathic profile. The differences in rank scores between all the profile types were statistically significant (p < 0.05). Assessment of profile types among lay personnel could provide clinicians an indication into the relative attractiveness among profile types and health care workers in treatment prioritization among dysmorphic facial types.

  15. Ranking and averaging independent component analysis by reproducibility (RAICAR).

    PubMed

    Yang, Zhi; LaConte, Stephen; Weng, Xuchu; Hu, Xiaoping

    2008-06-01

    Independent component analysis (ICA) is a data-driven approach that has exhibited great utility for functional magnetic resonance imaging (fMRI). Standard ICA implementations, however, do not provide the number and relative importance of the resulting components. In addition, ICA algorithms utilizing gradient-based optimization give decompositions that are dependent on initialization values, which can lead to dramatically different results. In this work, a new method, RAICAR (Ranking and Averaging Independent Component Analysis by Reproducibility), is introduced to address these issues for spatial ICA applied to fMRI. RAICAR utilizes repeated ICA realizations and relies on the reproducibility between them to rank and select components. Different realizations are aligned based on correlations, leading to aligned components. Each component is ranked and thresholded based on between-realization correlations. Furthermore, different realizations of each aligned component are selectively averaged to generate the final estimate of the given component. Reliability and accuracy of this method are demonstrated with both simulated and experimental fMRI data.

  16. 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.

  17. An accelerated procedure for recursive feature ranking on microarray data.

    PubMed

    Furlanello, C; Serafini, M; Merler, S; Jurman, G

    2003-01-01

    We describe a new wrapper algorithm for fast feature ranking in classification problems. The Entropy-based Recursive Feature Elimination (E-RFE) method eliminates chunks of uninteresting features according to the entropy of the weights distribution of a SVM classifier. With specific regard to DNA microarray datasets, the method is designed to support computationally intensive model selection in classification problems in which the number of features is much larger than the number of samples. We test E-RFE on synthetic and real data sets, comparing it with other SVM-based methods. The speed-up obtained with E-RFE supports predictive modeling on high dimensional microarray data.

  18. A Novel Database to Rank and Display Archeomagnetic Intensity Data

    NASA Astrophysics Data System (ADS)

    Donadini, F.; Korhonen, K.; Riisager, P.; Pesonen, L. J.; Kahma, K.

    2005-12-01

    To understand the content and the causes of the changes in the Earth's magnetic field beyond the observatory records one has to rely on archeomagnetic and lake sediment paleomagnetic data. The regional archeointensity curves are often of different quality and temporally variable which hampers the global analysis of the data in terms of dipole vs non-dipole field. We have developed a novel archeointensity database application utilizing MySQL, PHP (PHP Hypertext Preprocessor), and the Generic Mapping Tools (GMT) for ranking and displaying geomagnetic intensity data from the last 12000 years. Our application has the advantage that no specific software is required to query the database and view the results. Querying the database is performed using any Web browser; a fill-out form is used to enter the site location and a minimum ranking value to select the data points to be displayed. The form also features the possibility to select plotting of the data as an archeointensity curve with error bars, and a Virtual Axial Dipole Moment (VADM) or ancient field value (Ba) curve calculated using the CALS7K model (Continuous Archaeomagnetic and Lake Sediment geomagnetic model) of (Korte and Constable, 2005). The results of a query are displayed on a Web page containing a table summarizing the query parameters, a table showing the archeointensity values satisfying the query parameters, and a plot of VADM or Ba as a function of sample age. The database consists of eight related tables. The main one, INTENSITIES, stores the 3704 archeointensity measurements collected from 159 publications as VADM (and VDM when available) and Ba values, including their standard deviations and sampling locations. It also contains the number of samples and specimens measured from each site. The REFS table stores the references to a particular study. The names, latitudes, and longitudes of the regions where the samples were collected are stored in the SITES table. The MATERIALS, METHODS, SPECIMEN

  19. Rehabbing the Rankings: Fool's Errand or the Lord's Work?

    ERIC Educational Resources Information Center

    Kuh, George D.

    2011-01-01

    For better or worse, rankings shape public conceptions of collegiate quality. This paper reviews the history of rankings, analyzes what they represent, explores recent efforts to employ indicators in addition to institutional resources and reputation on which the most popular rankings are based, and evaluates the extent to which rankings serve…

  20. Ending the Reign of the Fraser Institute's School Rankings

    ERIC Educational Resources Information Center

    Raptis, Helen

    2012-01-01

    The Fraser Institute "Report Card" of school rankings has won the hearts of parents and the press. For over a decade, the rankings have been particularly burdensome for low-ranking (usually low socio-economic status, high-poverty) schools when parents of high-achieving children move them to higher-ranking schools. In February 2010, after…

  1. Examining Major Rankings According to the Berlin Principles

    ERIC Educational Resources Information Center

    Cheng, Ying; Liu, Nian Cai

    2008-01-01

    While the ranking of higher education institutions (HEIs) has become more and more popular, there are increasing concerns about the quality of such ranking. In response to such legitimate expectations, in May 2006, the International Ranking Expert Group (IREG) developed and endorsed a guideline document--the Berlin Principles on Ranking of Higher…

  2. 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…

  3. 5 CFR 451.302 - Ranks for senior career employees.

    Code of Federal Regulations, 2013 CFR

    2013-01-01

    ... 5 Administrative Personnel 1 2013-01-01 2013-01-01 false Ranks for senior career employees. 451... AWARDS Presidential Rank Awards § 451.302 Ranks for senior career employees. (a) The circumstances under... Professional to a senior career employee are set forth in 5 U.S.C. 4507a. (b) To be eligible for a rank...

  4. 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... AWARDS Presidential Rank Awards § 451.302 Ranks for senior career employees. (a) The circumstances under... Professional to a senior career employee are set forth in 5 U.S.C. 4507a. (b) To be eligible for a rank...

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

    Code of Federal Regulations, 2012 CFR

    2012-01-01

    ... 5 Administrative Personnel 1 2012-01-01 2012-01-01 false Ranks for senior career employees. 451... AWARDS Presidential Rank Awards § 451.302 Ranks for senior career employees. (a) The circumstances under... Professional to a senior career employee are set forth in 5 U.S.C. 4507a. (b) To be eligible for a rank...

  6. 5 CFR 451.302 - Ranks for senior career employees.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... 5 Administrative Personnel 1 2010-01-01 2010-01-01 false Ranks for senior career employees. 451... AWARDS Presidential Rank Awards § 451.302 Ranks for senior career employees. (a) The circumstances under... Professional to a senior career employee are set forth in 5 U.S.C. 4507a. (b) To be eligible for a rank...

  7. 5 CFR 451.302 - Ranks for senior career employees.

    Code of Federal Regulations, 2011 CFR

    2011-01-01

    ... 5 Administrative Personnel 1 2011-01-01 2011-01-01 false Ranks for senior career employees. 451... AWARDS Presidential Rank Awards § 451.302 Ranks for senior career employees. (a) The circumstances under... Professional to a senior career employee are set forth in 5 U.S.C. 4507a. (b) To be eligible for a rank...

  8. 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…

  9. 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.

  10. [Placental weight percentiles and its relationship with fetal weight according to gestational age in an urban area of Buenos Aires].

    PubMed

    Grandi, Carlos; Roman, Estela; Dipierri, Jose

    2015-01-01

    Antecedentes: El peso placentario (PP) y los índices de su relación con el peso al nacer (PN) (PN/PP, PP/PN) predicen morbi-mortalidad perinatal y resultados alejados de la salud. Objetivos: Calcular percentilos del PP e índices por sexo y edad gestacional correspondientes a 867 RNV de la Maternidad Sardá de Buenos Aires, Argentina y compararlos con referencias internacionales. Material y métodos: Se excluyeron feto muerto, embarazo múltiple, edad gestacional <22 y >42 semanas y PP<100g y >2500g. Características maternas y fetales: edad, educación, tabaco, paridad, diabetes, preeclampsia, corioamnionitis, restricción del crecimiento, malformación congénita y prematurez. Se calcularon estadísticos de resumen y percentilos con el método LMS. Las comparaciones se realizaron con test t-Student, ANOVA y referencias internacionales. Resultados: Edad materna media 24 años, educación 10.1 años, 24.5% primíparas, 12.6% fumadoras, 4.9% presentaron diabetes, 8.7% preeclampsia, 7.9% corioamnionitis y 13.0% restricción del crecimiento fetal. El 55.3% de los RN fueron varones, 51.6% prematuros, 18.9% PEG y 7.1% malformados. El PN y EG promedio fue de 2581g y 35.6 semanas respectivamente. Elevada correlación positiva de la EG con PP y PN/PP y negativa con PP/PN (p%lt;0.001); el peso de la placenta e índices fueron mayores en varones. Se presentan los percentiles de PP, PN/PP y PP/PN. Las diferencias con las referencias oscilaron de 0.46% -13%, 4.91% -12.1% y 5.81% -14% para el PP, PN/PP y PP/PN respectivamente. Conclusiones: los percentilos generados son aplicables en investigaciones sobre la relación de la placenta con resultados perinatales y la salud durante el ciclo vital.

  11. Monte Carlo simulations guided by imaging to predict the in vitro ranking of radiosensitizing nanoparticles

    PubMed Central

    Retif, Paul; Reinhard, Aurélie; Paquot, Héna; Jouan-Hureaux, Valérie; Chateau, Alicia; Sancey, Lucie; Barberi-Heyob, Muriel; Pinel, Sophie; Bastogne, Thierry

    2016-01-01

    This article addresses the in silico–in vitro prediction issue of organometallic nanoparticles (NPs)-based radiosensitization enhancement. The goal was to carry out computational experiments to quickly identify efficient nanostructures and then to preferentially select the most promising ones for the subsequent in vivo studies. To this aim, this interdisciplinary article introduces a new theoretical Monte Carlo computational ranking method and tests it using 3 different organometallic NPs in terms of size and composition. While the ranking predicted in a classical theoretical scenario did not fit the reference results at all, in contrast, we showed for the first time how our accelerated in silico virtual screening method, based on basic in vitro experimental data (which takes into account the NPs cell biodistribution), was able to predict a relevant ranking in accordance with in vitro clonogenic efficiency. This corroborates the pertinence of such a prior ranking method that could speed up the preclinical development of NPs in radiation therapy. PMID:27920524

  12. Monte Carlo simulations guided by imaging to predict the in vitro ranking of radiosensitizing nanoparticles.

    PubMed

    Retif, Paul; Reinhard, Aurélie; Paquot, Héna; Jouan-Hureaux, Valérie; Chateau, Alicia; Sancey, Lucie; Barberi-Heyob, Muriel; Pinel, Sophie; Bastogne, Thierry

    This article addresses the in silico-in vitro prediction issue of organometallic nanoparticles (NPs)-based radiosensitization enhancement. The goal was to carry out computational experiments to quickly identify efficient nanostructures and then to preferentially select the most promising ones for the subsequent in vivo studies. To this aim, this interdisciplinary article introduces a new theoretical Monte Carlo computational ranking method and tests it using 3 different organometallic NPs in terms of size and composition. While the ranking predicted in a classical theoretical scenario did not fit the reference results at all, in contrast, we showed for the first time how our accelerated in silico virtual screening method, based on basic in vitro experimental data (which takes into account the NPs cell biodistribution), was able to predict a relevant ranking in accordance with in vitro clonogenic efficiency. This corroborates the pertinence of such a prior ranking method that could speed up the preclinical development of NPs in radiation therapy.

  13. Efficiency improved scalar wave low-rank extrapolation with an effective perfectly matched layer

    NASA Astrophysics Data System (ADS)

    Chen, Hanming; Zhou, Hui; Xia, Muming

    2017-02-01

    Low-rank extrapolation is a relatively new method for seismic wave simulation. However, the low-rank method involved requires several fast Fourier transforms (FFTs) per time step, and the number of FFTs increases with the time-stepping size and complexity of the model, which leads to high computational cost at each step. To reduce the cost per time step, a more efficient low-rank extrapolation scheme is presented by splitting the original wave propagator into two parts. The first part represents the traditional pseudo-spectral operator, and is calculated by FFT directly. The residual part compensates the time-stepping error, and is approximated by low-rank decomposition. Compared with the conventional low-rank extrapolation scheme, the improved extrapolation scheme enables using a lower rank for the decomposition to attain similar approximation accuracy, which reduces the number of floating-point operations per time step, and thus reduces the total computational cost. To avoid the wraparound effect caused by FFTs, we develop an effective split perfectly matched layer (PML) to absorb outgoing waves near the boundary. Numerical examples verify the accuracy of the developed low-rank extrapolation scheme and the effectiveness of the PML.

  14. Learning to rank diversified results for biomedical information retrieval from multiple features

    PubMed Central

    2014-01-01

    Background Different from traditional information retrieval (IR), promoting diversity in IR takes consideration of relationship between documents in order to promote novelty and reduce redundancy thus to provide diversified results to satisfy various user intents. Diversity IR in biomedical domain is especially important as biologists sometimes want diversified results pertinent to their query. Methods A combined learning-to-rank (LTR) framework is learned through a general ranking model (gLTR) and a diversity-biased model. The former is learned from general ranking features by a conventional learning-to-rank approach; the latter is constructed with diversity-indicating features added, which are extracted based on the retrieved passages' topics detected using Wikipedia and ranking order produced by the general learning-to-rank model; final ranking results are given by combination of both models. Results Compared with baselines BM25 and DirKL on 2006 and 2007 collections, the gLTR has 0.2292 (+16.23% and +44.1% improvement over BM25 and DirKL respectively) and 0.1873 (+15.78% and +39.0% improvement over BM25 and DirKL respectively) in terms of aspect level of mean average precision (Aspect MAP). The LTR method outperforms gLTR on 2006 and 2007 collections with 4.7% and 2.4% improvement in terms of Aspect MAP. Conclusions The learning-to-rank method is an efficient way for biomedical information retrieval and the diversity-biased features are beneficial for promoting diversity in ranking results. PMID:25560088

  15. Comparison of changes in growth percentiles of US children on CDC 2000 growth charts with corresponding changes on WHO 2006 growth charts.

    PubMed

    Mei, Zuguo; Grummer-Strawn, Laurence M

    2011-05-01

    Longitudinal data with 37 964 length and weight measurements from 10 844 children who participated in the California Child Health and Development Study was used to compare the proportion of children aged ≤24 months who crossed major percentile lines on the Centers for Disease Control and Prevention (CDC) 2000 growth charts with the percentage who crossed corresponding lines on the World Health Organization (WHO) 2006 growth charts. Percentage of children aged ≤24 months who crossed at least 2 major percentile lines for length-for-age, weight-for-age, and weight-for-length according to CDC 2000 charts were compared with the percentage who did so according to WHO 2006 charts. The results from this analysis suggest that pediatricians who monitor children's growth on the basis of WHO 2006 growth charts may be more likely to refer children aged <6 months and less likely to refer those aged 6 to 12 months for further evaluation for failure to thrive.

  16. Gene Ranking of RNA-Seq Data via Discriminant Non-Negative Matrix Factorization

    PubMed Central

    Jia, Zhilong; Zhang, Xiang; Guan, Naiyang; Bo, Xiaochen; Barnes, Michael R.; Luo, Zhigang

    2015-01-01

    RNA-sequencing is rapidly becoming the method of choice for studying the full complexity of transcriptomes, however with increasing dimensionality, accurate gene ranking is becoming increasingly challenging. This paper proposes an accurate and sensitive gene ranking method that implements discriminant non-negative matrix factorization (DNMF) for RNA-seq data. To the best of our knowledge, this is the first work to explore the utility of DNMF for gene ranking. When incorporating Fisher’s discriminant criteria and setting the reduced dimension as two, DNMF learns two factors to approximate the original gene expression data, abstracting the up-regulated or down-regulated metagene by using the sample label information. The first factor denotes all the genes’ weights of two metagenes as the additive combination of all genes, while the second learned factor represents the expression values of two metagenes. In the gene ranking stage, all the genes are ranked as a descending sequence according to the differential values of the metagene weights. Leveraging the nature of NMF and Fisher’s criterion, DNMF can robustly boost the gene ranking performance. The Area Under the Curve analysis of differential expression analysis on two benchmarking tests of four RNA-seq data sets with similar phenotypes showed that our proposed DNMF-based gene ranking method outperforms other widely used methods. Moreover, the Gene Set Enrichment Analysis also showed DNMF outweighs others. DNMF is also computationally efficient, substantially outperforming all other benchmarked methods. Consequently, we suggest DNMF is an effective method for the analysis of differential gene expression and gene ranking for RNA-seq data. PMID:26348772

  17. Gene Ranking of RNA-Seq Data via Discriminant Non-Negative Matrix Factorization.

    PubMed

    Jia, Zhilong; Zhang, Xiang; Guan, Naiyang; Bo, Xiaochen; Barnes, Michael R; Luo, Zhigang

    2015-01-01

    RNA-sequencing is rapidly becoming the method of choice for studying the full complexity of transcriptomes, however with increasing dimensionality, accurate gene ranking is becoming increasingly challenging. This paper proposes an accurate and sensitive gene ranking method that implements discriminant non-negative matrix factorization (DNMF) for RNA-seq data. To the best of our knowledge, this is the first work to explore the utility of DNMF for gene ranking. When incorporating Fisher's discriminant criteria and setting the reduced dimension as two, DNMF learns two factors to approximate the original gene expression data, abstracting the up-regulated or down-regulated metagene by using the sample label information. The first factor denotes all the genes' weights of two metagenes as the additive combination of all genes, while the second learned factor represents the expression values of two metagenes. In the gene ranking stage, all the genes are ranked as a descending sequence according to the differential values of the metagene weights. Leveraging the nature of NMF and Fisher's criterion, DNMF can robustly boost the gene ranking performance. The Area Under the Curve analysis of differential expression analysis on two benchmarking tests of four RNA-seq data sets with similar phenotypes showed that our proposed DNMF-based gene ranking method outperforms other widely used methods. Moreover, the Gene Set Enrichment Analysis also showed DNMF outweighs others. DNMF is also computationally efficient, substantially outperforming all other benchmarked methods. Consequently, we suggest DNMF is an effective method for the analysis of differential gene expression and gene ranking for RNA-seq data.

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

    PubMed

    Eisinga, Rob; Breitling, Rainer; Heskes, Tom

    2013-03-18

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

  19. 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

  20. 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.

  1. 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…

  2. 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.

  3. George Wilbur: Otto Rank and Hanns Sachs.

    PubMed

    Roazen, Paul

    2006-01-01

    George Wilbur, a pioneering Cape Cod psychoanalytic psychiatrist, was a long-standing editor of the journal "American Imago," and an excellent source of information about the Viennese analysts Otto Rank and Hanns Sachs. Wilbur was also knowledgeable about the early reception of psychoanalysis in the Boston community.

  4. 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…

  5. 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

  6. 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…

  7. 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.

  8. 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…

  9. 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…

  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. 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.

  12. A human fecal contamination index for ranking impaired ...

    EPA Pesticide Factsheets

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

  13. 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.

  14. 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

  15. A ranking algorithm for spacelab crew and experiment scheduling

    NASA Technical Reports Server (NTRS)

    Grone, R. D.; Mathis, F. H.

    1980-01-01

    The problem of obtaining an optimal or near optimal schedule for scientific experiments to be performed on Spacelab missions is addressed. The current capabilities in this regard are examined and a method of ranking experiments in order of difficulty is developed to support the existing software. Experimental data is obtained from applying this method to the sets of experiments corresponding to Spacelab mission 1, 2, and 3. Finally, suggestions are made concerning desirable modifications and features of second generation software being developed for this problem.

  16. 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

  17. Reduced-rank technique for joint channel estimation in TD-SCDMA systems

    NASA Astrophysics Data System (ADS)

    Kamil Marzook, Ali; Ismail, Alyani; Mohd Ali, Borhanuddin; Sali, Adawati; Khatun, Sabira

    2013-02-01

    In time division-synchronous code division multiple access systems, increasing the system capacity by exploiting the inserting of the largest number of users in one time slot (TS) requires adding more estimation processes to estimate the joint channel matrix for the whole system. The increase in the number of channel parameters due the increase in the number of users in one TS directly affects the precision of the estimator's performance. This article presents a novel channel estimation with low complexity, which relies on reducing the rank order of the total channel matrix H. The proposed method exploits the rank deficiency of H to reduce the number of parameters that characterise this matrix. The adopted reduced-rank technique is based on truncated singular value decomposition algorithm. The algorithms for reduced-rank joint channel estimation (JCE) are derived and compared against traditional full-rank JCEs: least squares (LS) or Steiner and enhanced (LS or MMSE) algorithms. Simulation results of the normalised mean square error showed the superiority of reduced-rank estimators. In addition, the channel impulse responses founded by reduced-rank estimator for all active users offers considerable performance improvement over the conventional estimator along the channel window length.

  18. College and school of pharmacy characteristics associated with US News and World Report rankings.

    PubMed

    Schlesselman, Lauren; Coleman, Craig I

    2013-04-12

    OBJECTIVE. To determine the association between characteristics of colleges and schools of pharmacy and their rankings according to US News and World Report. METHODS. The 2008 US News and World Report, mean ranking scores (ranging from 2.0 to 5.0) for 78 US colleges and schools of pharmacy were compared with college and school characteristics, including academic program, students, faculty, and scholarship. The adjusted difference in mean ranking score associated with each characteristic was determined using a multivariate mixed linear regression model. RESULTS. The most powerful identified predictors of mean ranking score included the amount of grant funding (National Institutes of Health [NIH] and non-NIH funding) a college or school of pharmacy received and the yearly publication rates of its department of pharmacy (p≤0.001 for both). The adjusted mean ranking scores for colleges and schools receiving >$5 million and $1 million to $5 million in scholarly grant funding were respectively 0.77 and 0.26 points higher than those receiving none. Adjusted mean ranking scores for colleges and schools whose departments of pharmacy practice had publishing rates of >20 papers and 11 to 20 papers were respectively 0.40 and 0.17 points higher than those publishing ≤10 (p<0.05 for both). CONCLUSION. The characteristic of colleges and schools of pharmacy most associated with US News and World Report rankings appears to be their scholarly productivity.

  19. 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.

  20. Moving object detection via low-rank total variation regularization

    NASA Astrophysics Data System (ADS)

    Wang, Pengcheng; Chen, Qian; Shao, Na

    2016-09-01

    Moving object detection is a challenging task in video surveillance. Recently proposed Robust Principal Component Analysis (RPCA) can recover the outlier patterns from the low-rank data under some mild conditions. However, the l-penalty in RPCA doesn't work well in moving object detection because the irrepresentable condition is often not satisfied. In this paper, a method based on total variation (TV) regularization scheme is proposed. In our model, image sequences captured with a static camera are highly related, which can be described using a low-rank matrix. Meanwhile, the low-rank matrix can absorb background motion, e.g. periodic and random perturbation. The foreground objects in the sequence are usually sparsely distributed and drifting continuously, and can be treated as group outliers from the highly-related background scenes. Instead of l-penalty, we exploit the total variation of the foreground. By minimizing the total variation energy, the outliers tend to collapse and finally converge to be the exact moving objects. The TV-penalty is superior to the l-penalty especially when the outlier is in the majority for some pixels, and our method can estimate the outlier explicitly with less bias but higher variance. To solve the problem, a joint optimization function is formulated and can be effectively solved through the inexact Augmented Lagrange Multiplier (ALM) method. We evaluate our method along with several state-of-the-art approaches in MATLAB. Both qualitative and quantitative results demonstrate that our proposed method works effectively on a large range of complex scenarios.

  1. Clinical psychology Ph.D. program rankings: evaluating eminence on faculty publications and citations.

    PubMed

    Matson, Johnny L; Malone, Carrie J; González, 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 most frequently published core clinical faculty across 157 APA-approved clinical programs are listed. The implications of these data are discussed.

  2. 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.

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

    PubMed Central

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

    2016-01-01

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

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

    PubMed

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

    2016-01-01

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

  5. 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.

  6. On higher rank coisotropic A-branes

    NASA Astrophysics Data System (ADS)

    Herbst, Manfred

    2012-02-01

    This article is devoted to a world sheet analysis of A-type D-branes in N=(2,2) supersymmetric non-linear sigma models. In addition to the familiar Lagrangian submanifolds with flat connection we reproduce the rank one A-branes of Kapustin and Orlov, which are supported on coisotropic submanifolds. The main focus is however on gauge fields of higher rank and on tachyon profiles on brane-antibrane pairs. This will lead to the notion of a complex of coisotropic A-branes. A particular role is played by the noncommutative geometry on the brane world volume. It ensures that brane-antibrane pairs localize again on coisotropic submanifolds.

  7. A linear functional strategy for regularized ranking.

    PubMed

    Kriukova, Galyna; Panasiuk, Oleksandra; Pereverzyev, Sergei V; Tkachenko, Pavlo

    2016-01-01

    Regularization schemes are frequently used for performing ranking tasks. This topic has been intensively studied in recent years. However, to be effective a regularization scheme should be equipped with a suitable strategy for choosing a regularization parameter. In the present study we discuss an approach, which is based on the idea of a linear combination of regularized rankers corresponding to different values of the regularization parameter. The coefficients of the linear combination are estimated by means of the so-called linear functional strategy. We provide a theoretical justification of the proposed approach and illustrate them by numerical experiments. Some of them are related with ranking the risk of nocturnal hypoglycemia of diabetes patients.

  8. A ranking-theoretic approach to conditionals.

    PubMed

    Spohn, Wolfgang

    2013-08-01

    Conditionals somehow express conditional beliefs. However, conditional belief is a bi-propositional attitude that is generally not truth-evaluable, in contrast to unconditional belief. Therefore, this article opts for an expressivistic semantics for conditionals, grounds this semantics in the arguably most adequate account of conditional belief, that is, ranking theory, and dismisses probability theory for that purpose, because probabilities cannot represent belief. Various expressive options are then explained in terms of ranking theory, with the intention to set out a general interpretive scheme that is able to account for the most variegated usage of conditionals. The Ramsey test is only the first option. Relevance is another, familiar, but little understood item, which comes in several versions. This article adds a further family of expressive options, which is able to subsume also counterfactuals and causal conditionals, and indicates at the end how this family allows for partial recovery of truth conditions for conditionals.

  9. Tracking the performance of world-ranked swimmers.

    PubMed

    Costa, Mário J; Marinho, Daniel A; Reis, Victor M; Silva, António J; Marques, Mário C; Bragada, José A; Barbosa, Tiago M

    2010-01-01

    Tracking the swimming performance is important to analyze its progression and stability between competitions and help coaches to define realistic goals and to select appropriate training methods. The aim of this study was to track world-ranked male swimmer's performance during five consecutive seasons (from 2003/2004 to 2007/2008) in Olympic freestyle events. An overall of 477 swimmers and 2385 season best performances were analyzed. FINA's male top-150 rankings for long course in the 2007-2008 season were consulted in each event to identify the swimmers included. Best performances were collected from ranking tables provided by the National Swimming Federations or, when appropriate, through an internet database (www. swimranking.net). Longitudinal assessment was performed based on two approaches: (i) mean stability (descriptive statistics and ANOVA repeated measures, followed by a Bonferroni post-hoc test) and; (ii) normative stability (Pearson Correlation Coefficient and the Cohen's Kappa tracking index). Significant variations in the mean swimming performance were observed in all events between all seasons. Performance enhancement was approximately 0.6 to 1 % between seasons leading up to the Olympics and approximately 3 to 4 % for the overall time-frame analyzed. The performance stability based on overall time-frame was moderate for all freestyle events, except in the 50-m (K = 0.39 ± 0.05) where it was low. Self-correlations ranged between a moderate (0.30 ≤ r < 0.60) and a high (r ≥ 0.60) stability. There was also a performance enhancement during all five seasons analyzed. When more strict time frames were used, the analysis of swimming performance stability revealed an increase in the third season. So, coaches should have a long term view in what concerns training design and periodization of world-ranked swimmers, setting the third season of the Olympic Cycle as a determinant time frame, due to performance stability until Olympic Games season. Key pointsWorld-ranked

  10. 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…

  11. 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 six…

  12. Social Image Tag Ranking by Two-View Learning

    NASA Astrophysics Data System (ADS)

    Zhuang, Jinfeng; Hoi, Steven C. H.

    Tags play a central role in text-based social image retrieval and browsing. However, the tags annotated by web users could be noisy, irrelevant, and often incomplete for describing the image contents, which may severely deteriorate the performance of text-based image retrieval models. In order to solve this problem, researchers have proposed techniques to rank the annotated tags of a social image according to their relevance to the visual content of the image. In this paper, we aim to overcome the challenge of social image tag ranking for a corpus of social images with rich user-generated tags by proposing a novel two-view learning approach. It can effectively exploit both textual and visual contents of social images to discover the complicated relationship between tags and images. Unlike the conventional learning approaches that usually assumes some parametric models, our method is completely data-driven and makes no assumption about the underlying models, making the proposed solution practically more effective. We formulate our method as an optimization task and present an efficient algorithm to solve it. To evaluate the efficacy of our method, we conducted an extensive set of experiments by applying our technique to both text-based social image retrieval and automatic image annotation tasks. Our empirical results showed that the proposed method can be more effective than the conventional approaches.

  13. 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.

  14. 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

  15. 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

  16. 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.

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

    PubMed Central

    Matheson, N W; Grefsheim, S F

    1981-01-01

    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

  18. Ranking welding intensity in pyroclastic deposits

    NASA Astrophysics Data System (ADS)

    Quane, S. L.; Russell, J. K.

    2003-04-01

    Pyroclastic deposits emplaced at high temperatures and having sufficient thickness become welded. The welding process involves sintering, compaction and flattening of hot glassy pyroclastic material and is attended by systematic changes in physical properties. Historically, the terms nonwelded, incipiently welded, partially welded with pumice, partially welded with fiamme, moderately welded and densely welded have been used as field descriptors for welding intensity (e.g., Smith &Bailey, 1966; Smith, 1979; Ross &Smith, 1980; Streck &Grunder, 1995). While using these descriptive words is often effective for delineating variations of welding intensity within a single deposit, their qualitative character does not provide for consistency between field areas or workers, and inhibits accurate comparison between deposits. Hence, there is a need for a universal classification of welding intensity in pyroclastic deposits. Here we develop an objective ranking system. The system recognizes 8 ranks (I to VIII) based on measurements of physical properties and petrographic characteristics. The physical property measurements include both lab and field observations: density, porosity, uniaxial compressive strength, point load strength, fiamme elongation, and foliation/fabric. The values are normalized in order to make the system universal. The rank divisions are adaptations of a rock mass-rating scheme based on rock strength (Hoek &Brown, 1980) and previous divisions of welding degree based on physical properties (e.g., density: Ragan &Sheridan, 1972, Streck &Grunder, 1995; fiamme elongation: Peterson, 1979). Each rank comprises a range of normalized values for each of the physical properties and a corresponding set of petrographic characteristics. Our new ranking system provides a consistent, objective means by which each sample or section of welded tuff can be evaluated, thus providing a much needed uniformity in nomenclature for degree of welding. References: Hoek, E. &Brown, E

  19. 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.

  20. Chromatographic and computational assessment of lipophilicity using sum of ranking differences and generalized pair-correlation.

    PubMed

    Andrić, Filip; Héberger, Károly

    2015-02-06

    Lipophilicity (logP) represents one of the most studied and most frequently used fundamental physicochemical properties. At present there are several possibilities for its quantitative expression and many of them stems from chromatographic experiments. Numerous attempts have been made to compare different computational methods, chromatographic methods vs. computational approaches, as well as chromatographic methods and direct shake-flask procedure without definite results or these findings are not accepted generally. In the present work numerous chromatographically derived lipophilicity measures in combination with diverse computational methods were ranked and clustered using the novel variable discrimination and ranking approaches based on the sum of ranking differences and the generalized pair correlation method. Available literature logP data measured on HILIC, and classical reversed-phase combining different classes of compounds have been compared with most frequently used multivariate data analysis techniques (principal component and hierarchical cluster analysis) as well as with the conclusions in the original sources. Chromatographic lipophilicity measures obtained under typical reversed-phase conditions outperform the majority of computationally estimated logPs. Oppositely, in the case of HILIC none of the many proposed chromatographic indices overcomes any of the computationally assessed logPs. Only two of them (logkmin and kmin) may be selected as recommended chromatographic lipophilicity measures. Both ranking approaches, sum of ranking differences and generalized pair correlation method, although based on different backgrounds, provides highly similar variable ordering and grouping leading to the same conclusions.

  1. 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)

  2. An Algorithm for Improving Non-Local Means Operators via Low-Rank Approximation.

    PubMed

    May, Victor; Keller, Yosi; Sharon, Nir; Shkolnisky, Yoel

    2016-03-01

    We present a method for improving a non-local means (NLM) operator by computing its low-rank approximation. The low-rank operator is constructed by applying a filter to the spectrum of the original NLM operator. This results in an operator, which is less sensitive to noise while preserving important properties of the original operator. The method is efficiently implemented based on Chebyshev polynomials and is demonstrated on the application of natural images denoising. For this application, we provide a comparison of our method with other denoising methods.

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

    PubMed

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

    2016-08-02

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

  4. Low-rank spectral expansions of two electron excitations for the acceleration of quantum chemistry calculations

    NASA Astrophysics Data System (ADS)

    Schwerdtfeger, Christine A.; Mazziotti, David A.

    2012-12-01

    Treatment of two-electron excitations is a fundamental but computationally expensive part of ab initio calculations of many-electron correlation. In this paper we develop a low-rank spectral expansion of two-electron excitations for accelerated electronic-structure calculations. The spectral expansion differs from previous approaches by relying upon both (i) a sum of three expansions to increase the rank reduction of the tensor and (ii) a factorization of the tensor into geminal (rank-two) tensors rather than orbital (rank-one) tensors. We combine three spectral expansions from the three distinct forms of the two-electron reduced density matrix (2-RDM), (i) the two-particle 2D, (ii) the two-hole 2Q, and the (iii) particle-hole 2G matrices, to produce a single spectral expansion with significantly accelerated convergence. While the resulting expansion is applicable to any quantum-chemistry calculation with two-particle excitation amplitudes, it is employed here in the parametric 2-RDM method [D. A. Mazziotti, Phys. Rev. Lett. 101, 253002 (2008)], 10.1103/PhysRevLett.101.253002. The low-rank parametric 2-RDM method scales quartically with the basis-set size, but like its full-rank version it can capture multi-reference correlation effects that are difficult to treat efficiently by traditional single-reference wavefunction methods. Applications are made to computing potential energy curves of HF and triplet OH+, equilibrium bond distances and frequencies, the HCN-HNC isomerization, and the energies of hydrocarbon chains. Computed 2-RDMs nearly satisfy necessary N-representability conditions. The low-rank spectral expansion has the potential to expand the applicability of the parametric 2-RDM method as well as other ab initio methods to large-scale molecular systems that are often only treatable by mean-field or density functional theories.

  5. Sorting protein decoys by machine-learning-to-rank

    NASA Astrophysics Data System (ADS)

    Jing, Xiaoyang; Wang, Kai; Lu, Ruqian; Dong, Qiwen

    2016-08-01

    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.

  6. 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

  7. 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.

  8. Low-Rank Linear Dynamical Systems for Motor Imagery EEG

    PubMed Central

    Tan, Chuanqi; Liu, Shaobo

    2016-01-01

    The common spatial pattern (CSP) and other spatiospectral feature extraction methods have become the most effective and successful approaches to solve the problem of motor imagery electroencephalography (MI-EEG) pattern recognition from multichannel neural activity in recent years. However, these methods need a lot of preprocessing and postprocessing such as filtering, demean, and spatiospectral feature fusion, which influence the classification accuracy easily. In this paper, we utilize linear dynamical systems (LDSs) for EEG signals feature extraction and classification. LDSs model has lots of advantages such as simultaneous spatial and temporal feature matrix generation, free of preprocessing or postprocessing, and low cost. Furthermore, a low-rank matrix decomposition approach is introduced to get rid of noise and resting state component in order to improve the robustness of the system. Then, we propose a low-rank LDSs algorithm to decompose feature subspace of LDSs on finite Grassmannian and obtain a better performance. Extensive experiments are carried out on public dataset from “BCI Competition III Dataset IVa” and “BCI Competition IV Database 2a.” The results show that our proposed three methods yield higher accuracies compared with prevailing approaches such as CSP and CSSP. PMID:28096809

  9. Low-Rank Linear Dynamical Systems for Motor Imagery EEG.

    PubMed

    Zhang, Wenchang; Sun, Fuchun; Tan, Chuanqi; Liu, Shaobo

    2016-01-01

    The common spatial pattern (CSP) and other spatiospectral feature extraction methods have become the most effective and successful approaches to solve the problem of motor imagery electroencephalography (MI-EEG) pattern recognition from multichannel neural activity in recent years. However, these methods need a lot of preprocessing and postprocessing such as filtering, demean, and spatiospectral feature fusion, which influence the classification accuracy easily. In this paper, we utilize linear dynamical systems (LDSs) for EEG signals feature extraction and classification. LDSs model has lots of advantages such as simultaneous spatial and temporal feature matrix generation, free of preprocessing or postprocessing, and low cost. Furthermore, a low-rank matrix decomposition approach is introduced to get rid of noise and resting state component in order to improve the robustness of the system. Then, we propose a low-rank LDSs algorithm to decompose feature subspace of LDSs on finite Grassmannian and obtain a better performance. Extensive experiments are carried out on public dataset from "BCI Competition III Dataset IVa" and "BCI Competition IV Database 2a." The results show that our proposed three methods yield higher accuracies compared with prevailing approaches such as CSP and CSSP.

  10. Fourth-grade children's dietary recall accuracy for energy intake at school meals differs by social desirability and body mass index percentile in a study concerning retention interval.

    PubMed

    Guinn, Caroline H; Baxter, Suzanne D; Royer, Julie A; Hardin, James W; Mackelprang, Alyssa J; Smith, Albert F

    2010-05-01

    Data from a study concerning retention interval and school-meal observation on children's dietary recalls were used to investigate relationships of social desirability score (SDS) and body mass index percentile (BMI%) to recall accuracy for energy for observed (n = 327) children, and to reported energy for observed and unobserved (n = 152) children. Report rates (reported/observed) correlated negatively with SDS and BMI%. Correspondence rates (correctly reported/observed) correlated negatively with SDS. Inflation ratios (overreported/observed) correlated negatively with BMI%. The relationship between reported energy and each of SDS and BMI% did not depend on observation status. Studies utilizing children's dietary recalls should assess SDS and BMI%.

  11. 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.

  12. 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

  13. 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.

  14. 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…

  15. Rankings in Institutional Strategies and Processes: Impact or Illusion?

    ERIC Educational Resources Information Center

    Hazelkorn, Ellen; Loukkola, Tia; Zhang, Thérèse

    2014-01-01

    The "Rankings in Institutional Strategies and Processes" (RISP) project is the first pan-European study of the impact and influence of rankings on European higher education institutions. The project has sought to build understanding of how rankings impact and influence the development of institutional strategies and processes and its…

  16. 25 CFR 1001.3 - Priority ranking for negotiations.

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    ... 25 Indians 2 2010-04-01 2010-04-01 false Priority ranking for negotiations. 1001.3 Section 1001.3... PROGRAM § 1001.3 Priority ranking for negotiations. In addition to the eligibility criteria identified above, a tribe or consortium of tribes seeking priority ranking for negotiations must submit...

  17. 25 CFR 1001.3 - Priority ranking for negotiations.

    Code of Federal Regulations, 2011 CFR

    2011-04-01

    ... 25 Indians 2 2011-04-01 2011-04-01 false Priority ranking for negotiations. 1001.3 Section 1001.3... PROGRAM § 1001.3 Priority ranking for negotiations. In addition to the eligibility criteria identified above, a tribe or consortium of tribes seeking priority ranking for negotiations must submit...

  18. 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...

  19. 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…

  20. 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 on…

  1. 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…

  2. 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…

  3. 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…

  4. 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…

  5. 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…

  6. 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…

  7. Ranking of Prokaryotic Genomes Based on Maximization of Sortedness of Gene Lengths.

    PubMed

    Bolshoy, A; Salih, B; Cohen, I; Tatarinova, T

    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.

  8. 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

  9. 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.

  10. 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.

  11. Partitioned log-rank tests for the overall homogeneity of hazard rate functions.

    PubMed

    Liu, Yukun; Yin, Guosheng

    2016-03-19

    In survival analysis, it is routine to test equality of two survival curves, which is often conducted by using the log-rank test. Although it is optimal under the proportional hazards assumption, the log-rank test is known to have little power when the survival or hazard functions cross. To test the overall homogeneity of hazard rate functions, we propose a group of partitioned log-rank tests. By partitioning the time axis and taking the supremum of the sum of two partitioned log-rank statistics over different partitioning points, the proposed test gains enormous power for cases with crossing hazards. On the other hand, when the hazards are indeed proportional, our test still maintains high power close to that of the optimal log-rank test. Extensive simulation studies are conducted to compare the proposed test with existing methods, and three real data examples are used to illustrate the commonality of crossing hazards and the advantages of the partitioned log-rank tests.

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

    PubMed

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

    2015-12-01

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

  13. Beliefs about birth rank and their reflection in reality.

    PubMed

    Herrera, Nicholas C; Zajonc, R B; Wieczorkowska, Grazyna; Cichomski, Bogdan

    2003-07-01

    Beliefs about birth rank reflect what the society regards as social reality, and they may also influence that reality. Three studies found that people believe those with different birth ranks differ in their personalities, that higher birth ranks are likely to attain higher occupational prestige, and that the personality characteristics attributed to the various birth ranks favor the actual attainment of higher occupational prestige. In one example of such beliefs, firstborns were rated as most intelligent but least creative whereas the opposite was true of last-borns. The 4th study found that those with higher birth ranks in fact attain more prestigious occupations and actually do complete more years of schooling.

  14. Anthropometry of height, weight, arm, wrist, abdominal circumference and body mass index, for Bolivian adolescents 12 to 18 years: Bolivian adolescent percentile values from the MESA study.

    PubMed

    Baya Botti, A; Pérez-Cueto, F J A; Vasquez Monllor, P A; Kolsteren, P W

    2009-01-01

    Anthropometry is important as clinical tool for individual follow-up as well as for planning and health policy-making at population level. Recent references of Bolivian Adolescents are not available. The aim of this cross sectional study was to provide age and sex specific centile values and charts of Body Mass Index, height, weight, arm, wrist and abdominal circumference from Bolivian Adolescents. Data from the MEtabolic Syndrome in Adolescents (MESA) study was used. Thirty-two Bolivian clusters from urban and rural areas were selected randomly considering population proportions, 3445 school going adolescents, 12 to 18 y, 45% males; 55% females underwent anthropometric evaluation by trained personnel using standardized protocols for all interviews and examinations. Weight, height, wrist, arm and abdominal circumference data were collected. Body Mass Index was calculated. Smoothed age- and gender specific 3rd, 5th, 10th, 25th, 50th, 75th, 85th, 90th, 95th and 97th Bolivian adolescent percentiles(BAP) and Charts(BAC) where derived using LMS regression. Percentile-based reference data for the antropometrics of for Bolivian Adolescents are presented for the first time.

  15. Rank and Order: Evaluating the Performance of SNPs for Individual Assignment in a Non-Model Organism

    PubMed Central

    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: FST, informativeness (In), 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 FST, In, 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

  16. Speaker-sensitive emotion recognition via ranking: Studies on acted and spontaneous speech(☆)

    PubMed

    Cao, Houwei; Verma, Ragini; Nenkova, Ani

    2015-01-01

    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.

  17. 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

  18. Interim analysis based on the weighted log-rank test for delayed treatment effects under staggered patient entry.

    PubMed

    Yoshida, Mizuki; Matsuyama, Yutaka

    2016-01-01

    Fleming and Harrington's G(ρ,γ) class of weighted log-rank tests is appropriate for detecting delayed treatment effects such as those seen in cancer vaccines. A conditional power (CP) and an alpha spending function (ASF) approach are useful for interim analyses that are conducted with the aim of early termination due to futility and efficacy, respectively. However, calculation of the CP and the total Type I error probability are often not considered for delayed effects under the staggered patient entry. In this article, we first propose methods for calculating the CP analytically based on the weighted log-rank test. We compared the performances of the proposed methods with two other methods (i.e., usual log-rank test and optimal one) under the delayed alternatives. Our simulations demonstrated that the CP based on the weighted log-rank test was more powerful than that of the usual log-rank test and was comparable to the CP based on the optimal log-rank test. Second, we quantitatively evaluated the degree to which the Type I error probability was inflated when an ASF approach with forced independent increments assumption was applied to the weighted log-rank test. The proposed method will provide valuable tools in the decision-making stage of the interim analysis.

  19. 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…

  20. Low-Rank Positive Semidefinite Matrix Recovery From Corrupted Rank-One Measurements

    NASA Astrophysics Data System (ADS)

    Li, Yuanxin; Sun, Yue; Chi, Yuejie

    2017-01-01

    We study the problem of estimating a low-rank positive semidefinite (PSD) matrix from a set of rank-one measurements using sensing vectors composed of i.i.d. standard Gaussian entries, which are possibly corrupted by arbitrary outliers. This problem arises from applications such as phase retrieval, covariance sketching, quantum space tomography, and power spectrum estimation. We first propose a convex optimization algorithm that seeks the PSD matrix with the minimum $\\ell_1$-norm of the observation residual. The advantage of our algorithm is that it is free of parameters, therefore eliminating the need for tuning parameters and allowing easy implementations. We establish that with high probability, a low-rank PSD matrix can be exactly recovered as soon as the number of measurements is large enough, even when a fraction of the measurements are corrupted by outliers with arbitrary magnitudes. Moreover, the recovery is also stable against bounded noise. With the additional information of an upper bound of the rank of the PSD matrix, we propose another non-convex algorithm based on subgradient descent that demonstrates excellent empirical performance in terms of computational efficiency and accuracy.

  1. 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…

  2. Rankings & Estimates: Rankings of the States 2015 and Estimates of School Statistics 2016

    ERIC Educational Resources Information Center

    National Education Association, 2016

    2016-01-01

    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…

  3. Retrieving Records from a Gigabyte of Text on a Minicomputer Using Statistical Ranking.

    ERIC Educational Resources Information Center

    Harman, Donna; Candela, Gerald

    1990-01-01

    Describes the advantages of a prototype retrieval system that uses statistically based ranked retrieval of records rather than traditional boolean methods, especially for end users. Several new techniques are also discussed including bit mapping, pruning, methods of building inverted files, and types of search engine. (26 references) (EAM)

  4. 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...

  5. Evaluation and ranking of restoration strategies for radioactively contaminated sites.

    PubMed

    Zeevaert, T; Bousher, A; Brendler, V; Jensen, P H; Nordlinder, S

    2001-01-01

    An international project, whose aim was the development of a transparent and robust method for evaluating and ranking restoration strategies for radioactively contaminated sites (RESTRAT), was carried out under the Fourth Framework of the Nuclear Fission Safety Programme of the EU. The evaluation and ranking procedure used was based on the principles of justification and optimisation for radiation protection. A multi-attribute utility analysis was applied to allow for the inclusion of radiological health effects, economic costs and social factors. Values of these attributes were converted into utility values by applying linear utility functions and weighting factors, derived from scaling constants and expert judgement. The uncertainties and variabilities associated with these utility functions and weighting factors were dealt with by a probabilistic approach which utilised a Latin Hypercube Sampling technique. Potentially relevant restoration techniques were identified and their characteristics determined through a literature review. The methodology developed by this project has been illustrated by application to representative examples of different categories of contaminated sites; a waste disposal site, a uranium tailing site and a contaminated freshwater river.

  6. 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.

  7. 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.

  8. Integrative literature and data mining to rank disease candidate genes.

    PubMed

    Wu, Chao; Zhu, Cheng; Jegga, Anil G

    2014-01-01

    While the genomics-derived discoveries promise benefits to basic research and health care, the speed and affordability of sequencing following recent technological advances has further aggravated the data deluge. Seamless integration of the ever-increasing clinical, genomic, and experimental data and efficient mining for knowledge extraction, delivering actionable insight and generating testable hypotheses are therefore critical for the needs of biomedical research. For instance, high-throughput techniques are frequently applied to detect disease candidate genes. Experimental validation of these candidates however is both time-consuming and expensive. Hence, several computational approaches based on literature and data mining have been developed to identify the most promising candidates for follow-up studies. Based on "guilt by association" principle, most of these methods use prior knowledge about a disease of interest to discover and rank novel candidate genes. In this chapter, we provide a brief overview of recent advances made in literature- and data-mining-based approaches for candidate gene prioritization. As a case study, we focus on a Web-based computational approach that uses integrated heterogeneous data sources including gene-literature associations for ranking disease candidate genes and explain how to run typical queries using this system.

  9. Ranking the strongest ENSO events while incorporating SST uncertainty

    NASA Astrophysics Data System (ADS)

    Huang, Boyin; L'Heureux, Michelle; Hu, Zeng-Zhen; Zhang, Huai-Min

    2016-09-01

    The strength of El Niño-Southern Oscillation (ENSO) is often measured using a single, discrete value of the Niño index. However, this method does not consider the sea surface temperature (SST) uncertainty associated with the observations and data processing. On the basis of the Niño3.4 index and its uncertainty, we find that the strength of the three strongest ENSO events is not separable at 95% confidence level. The monthly peak SST anomalies in the most recent 2015-2016 El Niño is tied with 1997-1998 and 1982-1983 El Niño as the strongest. The three most negative monthly Niño values occur within the 1955-1956, 1973-1974, and 1975-1976 La Niña events, which cannot be discriminated by rank. The histograms of 1000-member ensemble analysis support the conclusion that the strength of the three strongest ENSO events is not separable. These results highlight that the ENSO ranking has to include the SST uncertainty.

  10. 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.

  11. 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.

  12. 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

  13. Rank-One and Transformed Sparse Decomposition for Dynamic Cardiac MRI

    PubMed Central

    Xiu, Xianchao; Kong, Lingchen

    2015-01-01

    It is challenging and inspiring for us to achieve high spatiotemporal resolutions in dynamic cardiac magnetic resonance imaging (MRI). In this paper, we introduce two novel models and algorithms to reconstruct dynamic cardiac MRI data from under-sampled k − t space data. In contrast to classical low-rank and sparse model, we use rank-one and transformed sparse model to exploit the correlations in the dataset. In addition, we propose projected alternative direction method (PADM) and alternative hard thresholding method (AHTM) to solve our proposed models. Numerical experiments of cardiac perfusion and cardiac cine MRI data demonstrate improvement in performance. PMID:26247010

  14. 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

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

    PubMed

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

    2012-12-01

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

  16. Quantile rank maps: a new tool for understanding individual brain development

    PubMed Central

    Chen, Huaihou; Kelly, Clare; Castellanos, Xavier; He, Ye; Zuo, Xi-Nian; Reiss, Philip T.

    2015-01-01

    We propose a novel method for neurodevelopmental brain mapping that displays how an individual’s values for a quantity of interest compare with age-specific norms. By estimating smoothly age-varying distributions at a set of brain regions of interest, we derive age-dependent region-wise quantile ranks for a given individual, which can be presented in the form of a brain map. Such quantile rank maps could potentially be used for clinical screening. Bootstrap-based confidence intervals are proposed for the quantile rank estimates. We also propose a recalibrated Kolmogorov-Smirnov test for detecting group differences in the age-varying distribution. This test is shown to be more robust to model misspecification than a linear regression-based test. The proposed methods are applied to brain imaging data from the Nathan Kline Institute Rockland Sample and from the Autism Brain Imaging Data Exchange (ABIDE) sample. PMID:25585020

  17. Low-rank and eigenface based sparse representation for face recognition.

    PubMed

    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.

  18. 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

  19. 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

  20. Permutational distribution of the log-rank statistic under random censorship with applications to carcinogenicity assays.

    PubMed

    Heimann, G; Neuhaus, G

    1998-03-01

    In the random censorship model, the log-rank test is often used for comparing a control group with different dose groups. If the number of tumors is small, so-called exact methods are often applied for computing critical values from a permutational distribution. Two of these exact methods are discussed and shown to be incorrect. The correct permutational distribution is derived and studied with respect to its behavior under unequal censoring in the light of recent results proving that the permutational version and the unconditional version of the log-rank test are asymptotically equivalent even under unequal censoring. The log-rank test is studied by simulations of a realistic scenario from a bioassay with small numbers of tumors.