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

Science.gov (United States)

Mathur, Sunil; Sadana, Ajit

2015-12-01

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

A tentative theory of large distance physics

International Nuclear Information System (INIS)

Friedan, Daniel

2003-01-01

A theoretical mechanism is devised to determine the large distance physics of spacetime. It is a two dimensional nonlinear model, the lambda model, set to govern the string world surface in an attempt to remedy the failure of string theory, as it stands. The lambda model is formulated to cancel the infrared divergent effects of handles at short distance on the world surface. The target manifold is the manifold of background spacetimes. The coupling strength is the spacetime coupling constant. The lambda model operates at 2d distance Δ -1 , very much shorter than the 2d distance μ -1 where the world surface is seen. A large characteristic spacetime distance L is given by L 2 ln(Δ/μ). Spacetime fields of wave number up to 1=L are the local coordinates for the manifold of spacetimes. The distribution of fluctuations at 2d distances shorter than Δ -1 gives the a priori measure on the target manifold, the manifold of spacetimes. If this measure concentrates at a macroscopic spacetime, then, nearby, it is a measure on the spacetime fields. The lambda model thereby constructs a spacetime quantum field theory, cutoff at ultraviolet distance L, describing physics at distances larger than L. The lambda model also constructs an effective string theory with infrared cutoff L, describing physics at distances smaller than L. The lambda model evolves outward from zero 2d distance, Δ -1 = 0, building spacetime physics starting from L ∞ and proceeding downward in L. L can be taken smaller than any distance practical for experiments, so the lambda model, if right, gives all actually observable physics. The harmonic surfaces in the manifold of spacetimes are expected to have novel nonperturbative effects at large distances. (author)

Designing a two-rank acceptance sampling plan for quality inspection of geospatial data products

Science.gov (United States)

Tong, Xiaohua; Wang, Zhenhua; Xie, Huan; Liang, Dan; Jiang, Zuoqin; Li, Jinchao; Li, Jun

2011-10-01

To address the disadvantages of classical sampling plans designed for traditional industrial products, we originally propose a two-rank acceptance sampling plan (TRASP) for the inspection of geospatial data outputs based on the acceptance quality level (AQL). The first rank sampling plan is to inspect the lot consisting of map sheets, and the second is to inspect the lot consisting of features in an individual map sheet. The TRASP design is formulated as an optimization problem with respect to sample size and acceptance number, which covers two lot size cases. The first case is for a small lot size with nonconformities being modeled by a hypergeometric distribution function, and the second is for a larger lot size with nonconformities being modeled by a Poisson distribution function. The proposed TRASP is illustrated through two empirical case studies. Our analysis demonstrates that: (1) the proposed TRASP provides a general approach for quality inspection of geospatial data outputs consisting of non-uniform items and (2) the proposed acceptance sampling plan based on TRASP performs better than other classical sampling plans. It overcomes the drawbacks of percent sampling, i.e., "strictness for large lot size, toleration for small lot size," and those of a national standard used specifically for industrial outputs, i.e., "lots with different sizes corresponding to the same sampling plan."

RANKED SET SAMPLING FOR ECOLOGICAL RESEARCH: ACCOUNTING FOR THE TOTAL COSTS OF SAMPLING

Science.gov (United States)

Researchers aim to design environmental studies that optimize precision and allow for generalization of results, while keeping the costs of associated field and laboratory work at a reasonable level. Ranked set sampling is one method to potentially increase precision and reduce ...

Ranking and selection of commercial off-the-shelf using fuzzy distance based approach

Directory of Open Access Journals (Sweden)

Rakesh Garg

2015-06-01

Full Text Available There is a tremendous growth of the use of the component based software engineering (CBSE approach for the development of software systems. The selection of the best suited COTS components which fulfils the necessary requirement for the development of software(s has become a major challenge for the software developers. The complexity of the optimal selection problem increases with an increase in alternative potential COTS components and the corresponding selection criteria. In this research paper, the problem of ranking and selection of Data Base Management Systems (DBMS components is modeled as a multi-criteria decision making problem. A ‘Fuzzy Distance Based Approach (FDBA’ method is proposed for the optimal ranking and selection of DBMS COTS components of an e-payment system based on 14 selection criteria grouped under three major categories i.e. ‘Vendor Capabilities’, ‘Business Issues’ and ‘Cost’. The results of this method are compared with other Analytical Hierarchy Process (AHP which is termed as a typical multi-criteria decision making approach. The proposed methodology is explained with an illustrated example.

A spinner magnetometer for large Apollo lunar samples

Science.gov (United States)

Uehara, M.; Gattacceca, J.; Quesnel, Y.; Lepaulard, C.; Lima, E. A.; Manfredi, M.; Rochette, P.

2017-10-01

We developed a spinner magnetometer to measure the natural remanent magnetization of large Apollo lunar rocks in the storage vault of the Lunar Sample Laboratory Facility (LSLF) of NASA. The magnetometer mainly consists of a commercially available three-axial fluxgate sensor and a hand-rotating sample table with an optical encoder recording the rotation angles. The distance between the sample and the sensor is adjustable according to the sample size and magnetization intensity. The sensor and the sample are placed in a two-layer mu-metal shield to measure the sample natural remanent magnetization. The magnetic signals are acquired together with the rotation angle to obtain stacking of the measured signals over multiple revolutions. The developed magnetometer has a sensitivity of 5 × 10-7 Am2 at the standard sensor-to-sample distance of 15 cm. This sensitivity is sufficient to measure the natural remanent magnetization of almost all the lunar basalt and breccia samples with mass above 10 g in the LSLF vault.

A spinner magnetometer for large Apollo lunar samples.

Science.gov (United States)

Uehara, M; Gattacceca, J; Quesnel, Y; Lepaulard, C; Lima, E A; Manfredi, M; Rochette, P

2017-10-01

We developed a spinner magnetometer to measure the natural remanent magnetization of large Apollo lunar rocks in the storage vault of the Lunar Sample Laboratory Facility (LSLF) of NASA. The magnetometer mainly consists of a commercially available three-axial fluxgate sensor and a hand-rotating sample table with an optical encoder recording the rotation angles. The distance between the sample and the sensor is adjustable according to the sample size and magnetization intensity. The sensor and the sample are placed in a two-layer mu-metal shield to measure the sample natural remanent magnetization. The magnetic signals are acquired together with the rotation angle to obtain stacking of the measured signals over multiple revolutions. The developed magnetometer has a sensitivity of 5 × 10 -7 Am 2 at the standard sensor-to-sample distance of 15 cm. This sensitivity is sufficient to measure the natural remanent magnetization of almost all the lunar basalt and breccia samples with mass above 10 g in the LSLF vault.

Study of probe-sample distance for biomedical spectra measurement

Directory of Open Access Journals (Sweden)

Li Lei

2011-11-01

Full Text Available Abstract Background Fiber-based optical spectroscopy has been widely used for biomedical applications. However, the effect of probe-sample distance on the collection efficiency has not been well investigated. Method In this paper, we presented a theoretical model to maximize the illumination and collection efficiency in designing fiber optic probes for biomedical spectra measurement. This model was in general applicable to probes with single or multiple fibers at an arbitrary incident angle. In order to demonstrate the theory, a fluorescence spectrometer was used to measure the fluorescence of human finger skin at various probe-sample distances. The fluorescence spectrum and the total fluorescence intensity were recorded. Results The theoretical results show that for single fiber probes, contact measurement always provides the best results. While for multi-fiber probes, there is an optimal probe distance. When a 400- μm excitation fiber is used to deliver the light to the skin and another six 400- μm fibers surrounding the excitation fiber are used to collect the fluorescence signal, the experimental results show that human finger skin has very strong fluorescence between 475 nm and 700 nm under 450 nm excitation. The fluorescence intensity is heavily dependent on the probe-sample distance and there is an optimal probe distance. Conclusions We investigated a number of probe-sample configurations and found that contact measurement could be the primary choice for single-fiber probes, but was very inefficient for multi-fiber probes. There was an optimal probe-sample distance for multi-fiber probes. By carefully choosing the probe-sample distance, the collection efficiency could be enhanced by 5-10 times. Our experiments demonstrated that the experimental results of the probe-sample distance dependence of collection efficiency in multi-fiber probes were in general agreement with our theory.

A Unimodal Model for Double Observer Distance Sampling Surveys.

Directory of Open Access Journals (Sweden)

Earl F Becker

Full Text Available Distance sampling is a widely used method to estimate animal population size. Most distance sampling models utilize a monotonically decreasing detection function such as a half-normal. Recent advances in distance sampling modeling allow for the incorporation of covariates into the distance model, and the elimination of the assumption of perfect detection at some fixed distance (usually the transect line with the use of double-observer models. The assumption of full observer independence in the double-observer model is problematic, but can be addressed by using the point independence assumption which assumes there is one distance, the apex of the detection function, where the 2 observers are assumed independent. Aerially collected distance sampling data can have a unimodal shape and have been successfully modeled with a gamma detection function. Covariates in gamma detection models cause the apex of detection to shift depending upon covariate levels, making this model incompatible with the point independence assumption when using double-observer data. This paper reports a unimodal detection model based on a two-piece normal distribution that allows covariates, has only one apex, and is consistent with the point independence assumption when double-observer data are utilized. An aerial line-transect survey of black bears in Alaska illustrate how this method can be applied.

Low rank approximation methods for MR fingerprinting with large scale dictionaries.

Science.gov (United States)

Yang, Mingrui; Ma, Dan; Jiang, Yun; Hamilton, Jesse; Seiberlich, Nicole; Griswold, Mark A; McGivney, Debra

2018-04-01

This work proposes new low rank approximation approaches with significant memory savings for large scale MR fingerprinting (MRF) problems. We introduce a compressed MRF with randomized singular value decomposition method to significantly reduce the memory requirement for calculating a low rank approximation of large sized MRF dictionaries. We further relax this requirement by exploiting the structures of MRF dictionaries in the randomized singular value decomposition space and fitting them to low-degree polynomials to generate high resolution MRF parameter maps. In vivo 1.5T and 3T brain scan data are used to validate the approaches. T 1 , T 2 , and off-resonance maps are in good agreement with that of the standard MRF approach. Moreover, the memory savings is up to 1000 times for the MRF-fast imaging with steady-state precession sequence and more than 15 times for the MRF-balanced, steady-state free precession sequence. The proposed compressed MRF with randomized singular value decomposition and dictionary fitting methods are memory efficient low rank approximation methods, which can benefit the usage of MRF in clinical settings. They also have great potentials in large scale MRF problems, such as problems considering multi-component MRF parameters or high resolution in the parameter space. Magn Reson Med 79:2392-2400, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

Transformational leadership in the local police in Spain: a leader-follower distance approach.

Science.gov (United States)

Álvarez, Octavio; Lila, Marisol; Tomás, Inés; Castillo, Isabel

2014-01-01

Based on the transformational leadership theory (Bass, 1985), the aim of the present study was to analyze the differences in leadership styles according to the various leading ranks and the organizational follower-leader distance reported by a representative sample of 975 local police members (828 male and 147 female) from Valencian Community (Spain). Results showed differences by rank (p leadership in all the variables examined (transformational-leadership behaviors, transactional-leadership behaviors, laissez-faire behaviors, satisfaction with the leader, extra effort by follower, and perceived leadership effectiveness). By contrast, the least optimal profiles were presented by intendents. Finally, the maximum distance (five ranks) generally yielded the most optimal profiles, whereas the 3-rank distance generally produced the least optimal profiles for all variables examined. Outcomes and practical implications for the workforce dimensioning are also discussed.

Sampling and Low-Rank Tensor Approximation of the Response Surface

KAUST Repository

Litvinenko, Alexander; Matthies, Hermann Georg; El-Moselhy, Tarek A.

2013-01-01

Most (quasi)-Monte Carlo procedures can be seen as computing some integral over an often high-dimensional domain. If the integrand is expensive to evaluate-we are thinking of a stochastic PDE (SPDE) where the coefficients are random fields and the integrand is some functional of the PDE-solution-there is the desire to keep all the samples for possible later computations of similar integrals. This obviously means a lot of data. To keep the storage demands low, and to allow evaluation of the integrand at points which were not sampled, we construct a low-rank tensor approximation of the integrand over the whole integration domain. This can also be viewed as a representation in some problem-dependent basis which allows a sparse representation. What one obtains is sometimes called a "surrogate" or "proxy" model, or a "response surface". This representation is built step by step or sample by sample, and can already be used for each new sample. In case we are sampling a solution of an SPDE, this allows us to reduce the number of necessary samples, namely in case the solution is already well-represented by the low-rank tensor approximation. This can be easily checked by evaluating the residuum of the PDE with the approximate solution. The procedure will be demonstrated in the computation of a compressible transonic Reynolds-averaged Navier-Strokes flow around an airfoil with random/uncertain data. © Springer-Verlag Berlin Heidelberg 2013.

Point process models for spatio-temporal distance sampling data from a large-scale survey of blue whales

KAUST Repository

Yuan, Yuan; Bachl, Fabian E.; Lindgren, Finn; Borchers, David L.; Illian, Janine B.; Buckland, Stephen T.; Rue, Haavard; Gerrodette, Tim

2017-01-01

Distance sampling is a widely used method for estimating wildlife population abundance. The fact that conventional distance sampling methods are partly design-based constrains the spatial resolution at which animal density can be estimated using these methods. Estimates are usually obtained at survey stratum level. For an endangered species such as the blue whale, it is desirable to estimate density and abundance at a finer spatial scale than stratum. Temporal variation in the spatial structure is also important. We formulate the process generating distance sampling data as a thinned spatial point process and propose model-based inference using a spatial log-Gaussian Cox process. The method adopts a flexible stochastic partial differential equation (SPDE) approach to model spatial structure in density that is not accounted for by explanatory variables, and integrated nested Laplace approximation (INLA) for Bayesian inference. It allows simultaneous fitting of detection and density models and permits prediction of density at an arbitrarily fine scale. We estimate blue whale density in the Eastern Tropical Pacific Ocean from thirteen shipboard surveys conducted over 22 years. We find that higher blue whale density is associated with colder sea surface temperatures in space, and although there is some positive association between density and mean annual temperature, our estimates are consistent with no trend in density across years. Our analysis also indicates that there is substantial spatially structured variation in density that is not explained by available covariates.

Point process models for spatio-temporal distance sampling data from a large-scale survey of blue whales

KAUST Repository

Yuan, Yuan

2017-12-28

Distance sampling is a widely used method for estimating wildlife population abundance. The fact that conventional distance sampling methods are partly design-based constrains the spatial resolution at which animal density can be estimated using these methods. Estimates are usually obtained at survey stratum level. For an endangered species such as the blue whale, it is desirable to estimate density and abundance at a finer spatial scale than stratum. Temporal variation in the spatial structure is also important. We formulate the process generating distance sampling data as a thinned spatial point process and propose model-based inference using a spatial log-Gaussian Cox process. The method adopts a flexible stochastic partial differential equation (SPDE) approach to model spatial structure in density that is not accounted for by explanatory variables, and integrated nested Laplace approximation (INLA) for Bayesian inference. It allows simultaneous fitting of detection and density models and permits prediction of density at an arbitrarily fine scale. We estimate blue whale density in the Eastern Tropical Pacific Ocean from thirteen shipboard surveys conducted over 22 years. We find that higher blue whale density is associated with colder sea surface temperatures in space, and although there is some positive association between density and mean annual temperature, our estimates are consistent with no trend in density across years. Our analysis also indicates that there is substantial spatially structured variation in density that is not explained by available covariates.

Geographically Modified PageRank Algorithms: Identifying the Spatial Concentration of Human Movement in a Geospatial Network.

Science.gov (United States)

Chin, Wei-Chien-Benny; Wen, Tzai-Hung

2015-01-01

A network approach, which simplifies geographic settings as a form of nodes and links, emphasizes the connectivity and relationships of spatial features. Topological networks of spatial features are used to explore geographical connectivity and structures. The PageRank algorithm, a network metric, is often used to help identify important locations where people or automobiles concentrate in the geographical literature. However, geographic considerations, including proximity and location attractiveness, are ignored in most network metrics. The objective of the present study is to propose two geographically modified PageRank algorithms-Distance-Decay PageRank (DDPR) and Geographical PageRank (GPR)-that incorporate geographic considerations into PageRank algorithms to identify the spatial concentration of human movement in a geospatial network. Our findings indicate that in both intercity and within-city settings the proposed algorithms more effectively capture the spatial locations where people reside than traditional commonly-used network metrics. In comparing location attractiveness and distance decay, we conclude that the concentration of human movement is largely determined by the distance decay. This implies that geographic proximity remains a key factor in human mobility.

PageRank tracker: from ranking to tracking.

Science.gov (United States)

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

2014-06-01

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

Pathway Relevance Ranking for Tumor Samples through Network-Based Data Integration.

Directory of Open Access Journals (Sweden)

Lieven P C Verbeke

Full Text Available The study of cancer, a highly heterogeneous disease with different causes and clinical outcomes, requires a multi-angle approach and the collection of large multi-omics datasets that, ideally, should be analyzed simultaneously. We present a new pathway relevance ranking method that is able to prioritize pathways according to the information contained in any combination of tumor related omics datasets. Key to the method is the conversion of all available data into a single comprehensive network representation containing not only genes but also individual patient samples. Additionally, all data are linked through a network of previously identified molecular interactions. We demonstrate the performance of the new method by applying it to breast and ovarian cancer datasets from The Cancer Genome Atlas. By integrating gene expression, copy number, mutation and methylation data, the method's potential to identify key pathways involved in breast cancer development shared by different molecular subtypes is illustrated. Interestingly, certain pathways were ranked equally important for different subtypes, even when the underlying (epi-genetic disturbances were diverse. Next to prioritizing universally high-scoring pathways, the pathway ranking method was able to identify subtype-specific pathways. Often the score of a pathway could not be motivated by a single mutation, copy number or methylation alteration, but rather by a combination of genetic and epi-genetic disturbances, stressing the need for a network-based data integration approach. The analysis of ovarian tumors, as a function of survival-based subtypes, demonstrated the method's ability to correctly identify key pathways, irrespective of tumor subtype. A differential analysis of survival-based subtypes revealed several pathways with higher importance for the bad-outcome patient group than for the good-outcome patient group. Many of the pathways exhibiting higher importance for the bad

Communities in Large Networks: Identification and Ranking

DEFF Research Database (Denmark)

Olsen, Martin

2008-01-01

show that the problem of deciding whether a non trivial community exists is NP complete. Nevertheless, experiments show that a very simple greedy approach can identify members of a community in the Danish part of the web graph with time complexity only dependent on the size of the found community...... and its immediate surroundings. The members are ranked with a “local” variant of the PageRank algorithm. Results are reported from successful experiments on identifying and ranking Danish Computer Science sites and Danish Chess pages using only a few representatives....

RANK and RANK ligand expression in primary human osteosarcoma

Directory of Open Access Journals (Sweden)

Daniel Branstetter

2015-09-01

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

Convolutional Codes with Maximum Column Sum Rank for Network Streaming

OpenAIRE

Mahmood, Rafid; Badr, Ahmed; Khisti, Ashish

2015-01-01

The column Hamming distance of a convolutional code determines the error correction capability when streaming over a class of packet erasure channels. We introduce a metric known as the column sum rank, that parallels column Hamming distance when streaming over a network with link failures. We prove rank analogues of several known column Hamming distance properties and introduce a new family of convolutional codes that maximize the column sum rank up to the code memory. Our construction invol...

Geographically Modified PageRank Algorithms: Identifying the Spatial Concentration of Human Movement in a Geospatial Network.

Directory of Open Access Journals (Sweden)

Wei-Chien-Benny Chin

Full Text Available A network approach, which simplifies geographic settings as a form of nodes and links, emphasizes the connectivity and relationships of spatial features. Topological networks of spatial features are used to explore geographical connectivity and structures. The PageRank algorithm, a network metric, is often used to help identify important locations where people or automobiles concentrate in the geographical literature. However, geographic considerations, including proximity and location attractiveness, are ignored in most network metrics. The objective of the present study is to propose two geographically modified PageRank algorithms-Distance-Decay PageRank (DDPR and Geographical PageRank (GPR-that incorporate geographic considerations into PageRank algorithms to identify the spatial concentration of human movement in a geospatial network. Our findings indicate that in both intercity and within-city settings the proposed algorithms more effectively capture the spatial locations where people reside than traditional commonly-used network metrics. In comparing location attractiveness and distance decay, we conclude that the concentration of human movement is largely determined by the distance decay. This implies that geographic proximity remains a key factor in human mobility.

Robustness of Distance-to-Default

DEFF Research Database (Denmark)

Jessen, Cathrine; Lando, David

2013-01-01

Distance-to-default is a remarkably robust measure for ranking firms according to their risk of default. The ranking seems to work despite the fact that the Merton model from which the measure is derived produces default probabilities that are far too small when applied to real data. We use...... simulations to investigate the robustness of the distance-to-default measure to different model specifications. Overall we find distance-to-default to be robust to a number of deviations from the simple Merton model that involve different asset value dynamics and different default triggering mechanisms....... A notable exception is a model with stochastic volatility of assets. In this case both the ranking of firms and the estimated default probabilities using distance-to-default perform significantly worse. We therefore propose a volatility adjustment of the distance-to-default measure, that significantly...

An open-population hierarchical distance sampling model

Science.gov (United States)

Sollmann, Rachel; Beth Gardner,; Richard B Chandler,; Royle, J. Andrew; T Scott Sillett,

2015-01-01

Modeling population dynamics while accounting for imperfect detection is essential to monitoring programs. Distance sampling allows estimating population size while accounting for imperfect detection, but existing methods do not allow for direct estimation of demographic parameters. We develop a model that uses temporal correlation in abundance arising from underlying population dynamics to estimate demographic parameters from repeated distance sampling surveys. Using a simulation study motivated by designing a monitoring program for island scrub-jays (Aphelocoma insularis), we investigated the power of this model to detect population trends. We generated temporally autocorrelated abundance and distance sampling data over six surveys, using population rates of change of 0.95 and 0.90. We fit the data generating Markovian model and a mis-specified model with a log-linear time effect on abundance, and derived post hoc trend estimates from a model estimating abundance for each survey separately. We performed these analyses for varying number of survey points. Power to detect population changes was consistently greater under the Markov model than under the alternatives, particularly for reduced numbers of survey points. The model can readily be extended to more complex demographic processes than considered in our simulations. This novel framework can be widely adopted for wildlife population monitoring.

An open-population hierarchical distance sampling model.

Science.gov (United States)

Sollmann, Rahel; Gardner, Beth; Chandler, Richard B; Royle, J Andrew; Sillett, T Scott

2015-02-01

Modeling population dynamics while accounting for imperfect detection is essential to monitoring programs. Distance sampling allows estimating population size while accounting for imperfect detection, but existing methods do not allow for estimation of demographic parameters. We develop a model that uses temporal correlation in abundance arising from underlying population dynamics to estimate demographic parameters from repeated distance sampling surveys. Using a simulation study motivated by designing a monitoring program for Island Scrub-Jays (Aphelocoma insularis), we investigated the power of this model to detect population trends. We generated temporally autocorrelated abundance and distance sampling data over six surveys, using population rates of change of 0.95 and 0.90. We fit the data generating Markovian model and a mis-specified model with a log-linear time effect on abundance, and derived post hoc trend estimates from a model estimating abundance for each survey separately. We performed these analyses for varying numbers of survey points. Power to detect population changes was consistently greater under the Markov model than under the alternatives, particularly for reduced numbers of survey points. The model can readily be extended to more complex demographic processes than considered in our simulations. This novel framework can be widely adopted for wildlife population monitoring.

Distance correlation methods for discovering associations in large astrophysical databases

International Nuclear Information System (INIS)

Martínez-Gómez, Elizabeth; Richards, Mercedes T.; Richards, Donald St. P.

2014-01-01

High-dimensional, large-sample astrophysical databases of galaxy clusters, such as the Chandra Deep Field South COMBO-17 database, provide measurements on many variables for thousands of galaxies and a range of redshifts. Current understanding of galaxy formation and evolution rests sensitively on relationships between different astrophysical variables; hence an ability to detect and verify associations or correlations between variables is important in astrophysical research. In this paper, we apply a recently defined statistical measure called the distance correlation coefficient, which can be used to identify new associations and correlations between astrophysical variables. The distance correlation coefficient applies to variables of any dimension, can be used to determine smaller sets of variables that provide equivalent astrophysical information, is zero only when variables are independent, and is capable of detecting nonlinear associations that are undetectable by the classical Pearson correlation coefficient. Hence, the distance correlation coefficient provides more information than the Pearson coefficient. We analyze numerous pairs of variables in the COMBO-17 database with the distance correlation method and with the maximal information coefficient. We show that the Pearson coefficient can be estimated with higher accuracy from the corresponding distance correlation coefficient than from the maximal information coefficient. For given values of the Pearson coefficient, the distance correlation method has a greater ability than the maximal information coefficient to resolve astrophysical data into highly concentrated horseshoe- or V-shapes, which enhances classification and pattern identification. These results are observed over a range of redshifts beyond the local universe and for galaxies from elliptical to spiral.

Low-rank quadratic semidefinite programming

KAUST Repository

Yuan, Ganzhao

2013-04-01

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

Low-rank quadratic semidefinite programming

KAUST Repository

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

2013-01-01

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

Global network centrality of university rankings

Science.gov (United States)

Guo, Weisi; Del Vecchio, Marco; Pogrebna, Ganna

2017-10-01

Universities and higher education institutions form an integral part of the national infrastructure and prestige. As academic research benefits increasingly from international exchange and cooperation, many universities have increased investment in improving and enabling their global connectivity. Yet, the relationship of university performance and its global physical connectedness has not been explored in detail. We conduct, to our knowledge, the first large-scale data-driven analysis into whether there is a correlation between university relative ranking performance and its global connectivity via the air transport network. The results show that local access to global hubs (as measured by air transport network betweenness) strongly and positively correlates with the ranking growth (statistical significance in different models ranges between 5% and 1% level). We also found that the local airport's aggregate flight paths (degree) and capacity (weighted degree) has no effect on university ranking, further showing that global connectivity distance is more important than the capacity of flight connections. We also examined the effect of local city economic development as a confounding variable and no effect was observed suggesting that access to global transportation hubs outweighs economic performance as a determinant of university ranking. The impact of this research is that we have determined the importance of the centrality of global connectivity and, hence, established initial evidence for further exploring potential connections between university ranking and regional investment policies on improving global connectivity.

Quantum chromodynamics at large distances

International Nuclear Information System (INIS)

Arbuzov, B.A.

1987-01-01

Properties of QCD at large distances are considered in the framework of traditional quantum field theory. An investigation of asymptotic behaviour of lower Green functions in QCD is the starting point of the approach. The recent works are reviewed which confirm the singular infrared behaviour of gluon propagator M 2 /(k 2 ) 2 at least under some gauge conditions. A special covariant gauge comes out to be the most suitable for description of infrared region due to absence of ghost contributions to infrared asymptotics of Green functions. Solutions of Schwinger-Dyson equation for quark propagator are obtained in this special gauge and are shown to possess desirable properties: spontaneous breaking of chiral invariance and nonperturbative character. The infrared asymptotics of lower Green functions are used for calculation of vacuum expectation values of gluon and quark fields. These vacuum expectation values are obtained in a good agreement with the corresponding phenomenological values which are needed in the method of sum rules in QCD, that confirms adequacy of the infrared region description. The consideration of a behaviour of QCD at large distances leads to the conclusion that at contemporary stage of theory development one may consider two possibilities. The first one is the well-known confinement hypothesis and the second one is called incomplete confinement and stipulates for open color to be observable. Possible manifestations of incomplete confinement are discussed

Distance matters! Cumulative proximity expansions for ranking documents

NARCIS (Netherlands)

J.B.P. Vuurens (Jeroen); A.P. de Vries (Arjen)

2014-01-01

htmlabstractIn the information retrieval process, functions that rank documents according to their estimated relevance to a query typically regard query terms as being independent. However, it is often the joint presence of query terms that is of interest to the user, which is overlooked when

Monte Carlo methods for top-k personalized PageRank lists and name disambiguation

NARCIS (Netherlands)

Avrachenkov, Konstatin; Litvak, Nelli; Nemirovsky, Danil; Smirnova, Elena; Sokol, Marina

We study a problem of quick detection of top-k Personalized PageRank lists. This problem has a number of important applications such as finding local cuts in large graphs, estimation of similarity distance and name disambiguation. In particular, we apply our results to construct efficient algorithms

Different goodness of fit tests for Rayleigh distribution in ranked set sampling

Directory of Open Access Journals (Sweden)

Amer Al-Omari

2016-03-01

Full Text Available In this paper, different goodness of fit tests for the Rayleigh distribution are considered based on simple random sampling (SRS and ranked set sampling (RSS techniques. The performance of the suggested estimators is evaluated in terms of the power of the tests by using Monte Carlo simulation. It is found that the suggested RSS tests perform better than their counterparts  in SRS.

A Case-Based Reasoning Method with Rank Aggregation

Science.gov (United States)

Sun, Jinhua; Du, Jiao; Hu, Jian

2018-03-01

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

Minkowski metrics in creating universal ranking algorithms

Directory of Open Access Journals (Sweden)

Andrzej Ameljańczyk

2014-06-01

Full Text Available The paper presents a general procedure for creating the rankings of a set of objects, while the relation of preference based on any ranking function. The analysis was possible to use the ranking functions began by showing the fundamental drawbacks of commonly used functions in the form of a weighted sum. As a special case of the ranking procedure in the space of a relation, the procedure based on the notion of an ideal element and generalized Minkowski distance from the element was proposed. This procedure, presented as universal ranking algorithm, eliminates most of the disadvantages of ranking functions in the form of a weighted sum.[b]Keywords[/b]: ranking functions, preference relation, ranking clusters, categories, ideal point, universal ranking algorithm

QV modal distance displacement - a criterion for contingency ranking

Energy Technology Data Exchange (ETDEWEB)

Rios, M.A.; Sanchez, J.L.; Zapata, C.J. [Universidad de Los Andes (Colombia). Dept. of Electrical Engineering], Emails: mrios@uniandes.edu.co, josesan@uniandes.edu.co, cjzapata@utp.edu.co

2009-07-01

This paper proposes a new methodology using concepts of fast decoupled load flow, modal analysis and ranking of contingencies, where the impact of each contingency is measured hourly taking into account the influence of each contingency over the mathematical model of the system, i.e. the Jacobian Matrix. This method computes the displacement of the reduced Jacobian Matrix eigenvalues used in voltage stability analysis, as a criterion of contingency ranking, considering the fact that the lowest eigenvalue in the normal operation condition is not the same lowest eigenvalue in N-1 contingency condition. It is made using all branches in the system and specific branches according to the IBPF index. The test system used is the IEEE 118 nodes. (author)

Statistical methods for ranking data

CERN Document Server

Alvo, Mayer

2014-01-01

This book introduces advanced undergraduate, graduate students and practitioners to statistical methods for ranking data. An important aspect of nonparametric statistics is oriented towards the use of ranking data. Rank correlation is defined through the notion of distance functions and the notion of compatibility is introduced to deal with incomplete data. Ranking data are also modeled using a variety of modern tools such as CART, MCMC, EM algorithm and factor analysis. This book deals with statistical methods used for analyzing such data and provides a novel and unifying approach for hypotheses testing. The techniques described in the book are illustrated with examples and the statistical software is provided on the authors’ website.

Automatic Samples Selection Using Histogram of Oriented Gradients (HOG Feature Distance

Directory of Open Access Journals (Sweden)

Inzar Salfikar

2018-01-01

Full Text Available Finding victims at a disaster site is the primary goal of Search-and-Rescue (SAR operations. Many technologies created from research for searching disaster victims through aerial imaging. but, most of them are difficult to detect victims at tsunami disaster sites with victims and backgrounds which are look similar. This research collects post-tsunami aerial imaging data from the internet to builds dataset and model for detecting tsunami disaster victims. Datasets are built based on distance differences from features every sample using Histogram-of-Oriented-Gradient (HOG method. We use the longest distance to collect samples from photo to generate victim and non-victim samples. We claim steps to collect samples by measuring HOG feature distance from all samples. the longest distance between samples will take as a candidate to build the dataset, then classify victim (positives and non-victim (negatives samples manually. The dataset of tsunami disaster victims was re-analyzed using cross-validation Leave-One-Out (LOO with Support-Vector-Machine (SVM method. The experimental results show the performance of two test photos with 61.70% precision, 77.60% accuracy, 74.36% recall and f-measure 67.44% to distinguish victim (positives and non-victim (negatives.

Distance Magic-Type and Distance Antimagic-Type Labelings of Graphs

Science.gov (United States)

Freyberg, Bryan J.

Generally speaking, a distance magic-type labeling of a graph G of order n is a bijection l from the vertex set of the graph to the first n natural numbers or to the elements of a group of order n, with the property that the weight of each vertex is the same. The weight of a vertex x is defined as the sum (or appropriate group operation) of all the labels of vertices adjacent to x. If instead we require that all weights differ, then we refer to the labeling as a distance antimagic-type labeling. This idea can be generalized for directed graphs; the weight will take into consideration the direction of the arcs. In this manuscript, we provide new results for d-handicap labeling, a distance antimagic-type labeling, and introduce a new distance magic-type labeling called orientable Gamma-distance magic labeling. A d-handicap distance antimagic labeling (or just d-handicap labeling for short) of a graph G = ( V,E) of order n is a bijection l from V to the set {1,2,...,n} with induced weight function [special characters omitted]. such that l(xi) = i and the sequence of weights w(x 1),w(x2),...,w (xn) forms an arithmetic sequence with constant difference d at least 1. If a graph G admits a d-handicap labeling, we say G is a d-handicap graph. A d-handicap incomplete tournament, H(n,k,d ) is an incomplete tournament of n teams ranked with the first n natural numbers such that each team plays exactly k games and the strength of schedule of the ith ranked team is d more than the i + 1st ranked team. That is, strength of schedule increases arithmetically with strength of team. Constructing an H(n,k,d) is equivalent to finding a d-handicap labeling of a k-regular graph of order n.. In Chapter 2 we provide general constructions for every d for large classes of both n and k, providing breadfth and depth to the catalog of known H(n,k,d)'s. In Chapters 3 - 6, we introduce a new type of labeling called orientable Gamma-distance magic labeling. Let Gamma be an abelian group of order

An R package for analyzing and modeling ranking data.

Science.gov (United States)

Lee, Paul H; Yu, Philip L H

2013-05-14

In medical informatics, psychology, market research and many other fields, researchers often need to analyze and model ranking data. However, there is no statistical software that provides tools for the comprehensive analysis of ranking data. Here, we present pmr, an R package for analyzing and modeling ranking data with a bundle of tools. The pmr package enables descriptive statistics (mean rank, pairwise frequencies, and marginal matrix), Analytic Hierarchy Process models (with Saaty's and Koczkodaj's inconsistencies), probability models (Luce model, distance-based model, and rank-ordered logit model), and the visualization of ranking data with multidimensional preference analysis. Examples of the use of package pmr are given using a real ranking dataset from medical informatics, in which 566 Hong Kong physicians ranked the top five incentives (1: competitive pressures; 2: increased savings; 3: government regulation; 4: improved efficiency; 5: improved quality care; 6: patient demand; 7: financial incentives) to the computerization of clinical practice. The mean rank showed that item 4 is the most preferred item and item 3 is the least preferred item, and significance difference was found between physicians' preferences with respect to their monthly income. A multidimensional preference analysis identified two dimensions that explain 42% of the total variance. The first can be interpreted as the overall preference of the seven items (labeled as "internal/external"), and the second dimension can be interpreted as their overall variance of (labeled as "push/pull factors"). Various statistical models were fitted, and the best were found to be weighted distance-based models with Spearman's footrule distance. In this paper, we presented the R package pmr, the first package for analyzing and modeling ranking data. The package provides insight to users through descriptive statistics of ranking data. Users can also visualize ranking data by applying a thought

Automatic setting of the distance between sample and detector in gamma-ray spectroscopy

International Nuclear Information System (INIS)

Andeweg, A.H.

1980-01-01

An apparatus has been developed that automatically sets the distance from the sample to the detector according to the radioactivity of the sample. The distance-setting unit works in conjuction with an automatic sample changer, and is interconnected with other components so that the counting head automatically moves to the optimum distance for the analysis of a particular sample. The distance, which is indicated digitally in increments of 0,01 mm, can be set between 18 and 995 mm at count rates that can be preset between 1000 and 10 000 counts per second. On being tested, the instrument performed well within the desired range and accuracy. Under routine conditions, the spectra were much more accurate than before, especially when samples of different radioactivity were counted

Weighted Discriminative Dictionary Learning based on Low-rank Representation

International Nuclear Information System (INIS)

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. (paper)

Chiral dynamics and partonic structure at large transverse distances

Energy Technology Data Exchange (ETDEWEB)

Strikman, M. [Pennsylvania State Univ., University Park, PA (United States). Dept. of Physics; Weiss, C. [Thomas Jefferson National Accelerator Facility (TJNAF), Newport News, VA (United States). Theory Center

2009-12-30

In this paper, we study large-distance contributions to the nucleon’s parton densities in the transverse coordinate (impact parameter) representation based on generalized parton distributions (GPDs). Chiral dynamics generates a distinct component of the partonic structure, located at momentum fractions x≲M_π/M_N and transverse distances b~1/M_π. We calculate this component using phenomenological pion exchange with a physical lower limit in b (the transverse “core” radius estimated from the nucleon’s axial form factor, R_core=0.55 fm) and demonstrate its universal character. This formulation preserves the basic picture of the “pion cloud” model of the nucleon’s sea quark distributions, while restricting its application to the region actually governed by chiral dynamics. It is found that (a) the large-distance component accounts for only ~1/3 of the measured antiquark flavor asymmetry d¯-u¯ at x~0.1; (b) the strange sea quarks s and s¯ are significantly more localized than the light antiquark sea; (c) the nucleon’s singlet quark size for x<0.1 is larger than its gluonic size, (b²)_q+q¯>(b²)_g, as suggested by the t-slopes of deeply-virtual Compton scattering and exclusive J/ψ production measured at HERA and FNAL. We show that our approach reproduces the general N_c-scaling of parton densities in QCD, thanks to the degeneracy of N and Δ intermediate states in the large-N_c limit. Finally, we also comment on the role of pionic configurations at large longitudinal distances and the limits of their applicability at small x.

Small Sample Properties of the Wilcoxon Signed Rank Test with Discontinuous and Dependent Observations

OpenAIRE

Nadine Chlass; Jens J. Krueger

2007-01-01

This Monte-Carlo study investigates sensitivity of the Wilcoxon signed rank test to certain assumption violations in small samples. Emphasis is put on within-sample-dependence, between-sample dependence, and the presence of ties. Our results show that both assumption violations induce severe size distortions and entail power losses. Surprisingly, these consequences do vary substantially with other properties the data may display. Results provided are particularly relevant for experimental set...

DISTANCES TO DARK CLOUDS: COMPARING EXTINCTION DISTANCES TO MASER PARALLAX DISTANCES

International Nuclear Information System (INIS)

Foster, Jonathan B.; Jackson, James M.; Stead, Joseph J.; Hoare, Melvin G.; Benjamin, Robert A.

2012-01-01

We test two different methods of using near-infrared extinction to estimate distances to dark clouds in the first quadrant of the Galaxy using large near-infrared (Two Micron All Sky Survey and UKIRT Infrared Deep Sky Survey) surveys. Very long baseline interferometry parallax measurements of masers around massive young stars provide the most direct and bias-free measurement of the distance to these dark clouds. We compare the extinction distance estimates to these maser parallax distances. We also compare these distances to kinematic distances, including recent re-calibrations of the Galactic rotation curve. The extinction distance methods agree with the maser parallax distances (within the errors) between 66% and 100% of the time (depending on method and input survey) and between 85% and 100% of the time outside of the crowded Galactic center. Although the sample size is small, extinction distance methods reproduce maser parallax distances better than kinematic distances; furthermore, extinction distance methods do not suffer from the kinematic distance ambiguity. This validation gives us confidence that these extinction methods may be extended to additional dark clouds where maser parallaxes are not available.

Model selection with multiple regression on distance matrices leads to incorrect inferences.

Directory of Open Access Journals (Sweden)

Ryan P Franckowiak

Full Text Available In landscape genetics, model selection procedures based on Information Theoretic and Bayesian principles have been used with multiple regression on distance matrices (MRM to test the relationship between multiple vectors of pairwise genetic, geographic, and environmental distance. Using Monte Carlo simulations, we examined the ability of model selection criteria based on Akaike's information criterion (AIC, its small-sample correction (AICc, and the Bayesian information criterion (BIC to reliably rank candidate models when applied with MRM while varying the sample size. The results showed a serious problem: all three criteria exhibit a systematic bias toward selecting unnecessarily complex models containing spurious random variables and erroneously suggest a high level of support for the incorrectly ranked best model. These problems effectively increased with increasing sample size. The failure of AIC, AICc, and BIC was likely driven by the inflated sample size and different sum-of-squares partitioned by MRM, and the resulting effect on delta values. Based on these findings, we strongly discourage the continued application of AIC, AICc, and BIC for model selection with MRM.

Perihelion asymmetry in the photometric parameters of long-period comets at large heliocentric distances

International Nuclear Information System (INIS)

Svoren, J.

1982-01-01

The present statistical analysis is based on a sample of long-period comets selected according to two criteria: (1) availability of photometric observations made at large distances from the Sun and covering an orbital arc long enough for a reliable determination of the photometric parameters, and (2) availability of a well determined orbit making it possible to classify the comet as new or old in Oort's (1950) sense. The selection was confined to comets with nearly parabolic orbits. 67 objects were found to satisfy the selection criteria. Photometric data referring to heliocentric distances of r > 2.5 AU were only used, yielding a total of 2,842 individual estimates and measurements. (Auth.)

Optimizing distance-based methods for large data sets

Science.gov (United States)

Scholl, Tobias; Brenner, Thomas

2015-10-01

Distance-based methods for measuring spatial concentration of industries have received an increasing popularity in the spatial econometrics community. However, a limiting factor for using these methods is their computational complexity since both their memory requirements and running times are in {{O}}(n^2). In this paper, we present an algorithm with constant memory requirements and shorter running time, enabling distance-based methods to deal with large data sets. We discuss three recent distance-based methods in spatial econometrics: the D&O-Index by Duranton and Overman (Rev Econ Stud 72(4):1077-1106, 2005), the M-function by Marcon and Puech (J Econ Geogr 10(5):745-762, 2010) and the Cluster-Index by Scholl and Brenner (Reg Stud (ahead-of-print):1-15, 2014). Finally, we present an alternative calculation for the latter index that allows the use of data sets with millions of firms.

A ring test of in vitro neutral detergent fiber digestibility: analytical variability and sample ranking.

Science.gov (United States)

Hall, M B; Mertens, D R

2012-04-01

difference between samples that were not declared different by means separation was 4.4% NDFD. Although the values did not have great precision, GVS labs were able to reliably rank sample data in order of 30-h NDFD (Spearman correlation coefficient = 0.93) with 80% of the rankings correct or off by only 1 ranking. A relative ranking system for NDFD could reduce the effect of within- and among-lab variation in numeric values. Such a system could give a more accurate portrayal of the comparative values of samples than current numeric values imply. Copyright © 2012 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

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

KAUST Repository

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

2017-01-01

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

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

KAUST Repository

Akbudak, Kadir

2017-05-11

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

Jackknife Variance Estimator for Two Sample Linear Rank Statistics

Science.gov (United States)

1988-11-01

Accesion For - - ,NTIS GPA&I "TIC TAB Unann c, nc .. [d Keywords: strong consistency; linear rank test’ influence function . i , at L By S- )Distribut...reverse if necessary and identify by block number) FIELD IGROUP SUB-GROUP Strong consistency; linear rank test; influence function . 19. ABSTRACT

VaRank: a simple and powerful tool for ranking genetic variants

Directory of Open Access Journals (Sweden)

Véronique Geoffroy

2015-03-01

Full Text Available Background. Most genetic disorders are caused by single nucleotide variations (SNVs or small insertion/deletions (indels. High throughput sequencing has broadened the catalogue of human variation, including common polymorphisms, rare variations or disease causing mutations. However, identifying one variation among hundreds or thousands of others is still a complex task for biologists, geneticists and clinicians.Results. We have developed VaRank, a command-line tool for the ranking of genetic variants detected by high-throughput sequencing. VaRank scores and prioritizes variants annotated either by Alamut Batch or SnpEff. A barcode allows users to quickly view the presence/absence of variants (with homozygote/heterozygote status in analyzed samples. VaRank supports the commonly used VCF input format for variants analysis thus allowing it to be easily integrated into NGS bioinformatics analysis pipelines. VaRank has been successfully applied to disease-gene identification as well as to molecular diagnostics setup for several hundred patients.Conclusions. VaRank is implemented in Tcl/Tk, a scripting language which is platform-independent but has been tested only on Unix environment. The source code is available under the GNU GPL, and together with sample data and detailed documentation can be downloaded from http://www.lbgi.fr/VaRank/.

Power and sample-size estimation for microbiome studies using pairwise distances and PERMANOVA.

Science.gov (United States)

Kelly, Brendan J; Gross, Robert; Bittinger, Kyle; Sherrill-Mix, Scott; Lewis, James D; Collman, Ronald G; Bushman, Frederic D; Li, Hongzhe

2015-08-01

The variation in community composition between microbiome samples, termed beta diversity, can be measured by pairwise distance based on either presence-absence or quantitative species abundance data. PERMANOVA, a permutation-based extension of multivariate analysis of variance to a matrix of pairwise distances, partitions within-group and between-group distances to permit assessment of the effect of an exposure or intervention (grouping factor) upon the sampled microbiome. Within-group distance and exposure/intervention effect size must be accurately modeled to estimate statistical power for a microbiome study that will be analyzed with pairwise distances and PERMANOVA. We present a framework for PERMANOVA power estimation tailored to marker-gene microbiome studies that will be analyzed by pairwise distances, which includes: (i) a novel method for distance matrix simulation that permits modeling of within-group pairwise distances according to pre-specified population parameters; (ii) a method to incorporate effects of different sizes within the simulated distance matrix; (iii) a simulation-based method for estimating PERMANOVA power from simulated distance matrices; and (iv) an R statistical software package that implements the above. Matrices of pairwise distances can be efficiently simulated to satisfy the triangle inequality and incorporate group-level effects, which are quantified by the adjusted coefficient of determination, omega-squared (ω2). From simulated distance matrices, available PERMANOVA power or necessary sample size can be estimated for a planned microbiome study. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Pairing call-response surveys and distance sampling for a mammalian carnivore

Science.gov (United States)

Hansen, Sara J. K.; Frair, Jacqueline L.; Underwood, Harold B.; Gibbs, James P.

2015-01-01

Density estimates accounting for differential animal detectability are difficult to acquire for wide-ranging and elusive species such as mammalian carnivores. Pairing distance sampling with call-response surveys may provide an efficient means of tracking changes in populations of coyotes (Canis latrans), a species of particular interest in the eastern United States. Blind field trials in rural New York State indicated 119-m linear error for triangulated coyote calls, and a 1.8-km distance threshold for call detectability, which was sufficient to estimate a detection function with precision using distance sampling. We conducted statewide road-based surveys with sampling locations spaced ≥6 km apart from June to August 2010. Each detected call (be it a single or group) counted as a single object, representing 1 territorial pair, because of uncertainty in the number of vocalizing animals. From 524 survey points and 75 detections, we estimated the probability of detecting a calling coyote to be 0.17 ± 0.02 SE, yielding a detection-corrected index of 0.75 pairs/10 km2 (95% CI: 0.52–1.1, 18.5% CV) for a minimum of 8,133 pairs across rural New York State. Importantly, we consider this an index rather than true estimate of abundance given the unknown probability of coyote availability for detection during our surveys. Even so, pairing distance sampling with call-response surveys provided a novel, efficient, and noninvasive means of monitoring populations of wide-ranging and elusive, albeit reliably vocal, mammalian carnivores. Our approach offers an effective new means of tracking species like coyotes, one that is readily extendable to other species and geographic extents, provided key assumptions of distance sampling are met.

Power and sample-size estimation for microbiome studies using pairwise distances and PERMANOVA

OpenAIRE

Kelly, Brendan J.; Gross, Robert; Bittinger, Kyle; Sherrill-Mix, Scott; Lewis, James D.; Collman, Ronald G.; Bushman, Frederic D.; Li, Hongzhe

2015-01-01

Motivation: The variation in community composition between microbiome samples, termed beta diversity, can be measured by pairwise distance based on either presence–absence or quantitative species abundance data. PERMANOVA, a permutation-based extension of multivariate analysis of variance to a matrix of pairwise distances, partitions within-group and between-group distances to permit assessment of the effect of an exposure or intervention (grouping factor) upon the sampled microbiome. Within-...

A comprehensive comparison of perpendicular distance sampling methods for sampling downed coarse woody debris

Science.gov (United States)

Jeffrey H. Gove; Mark J. Ducey; Harry T. Valentine; Michael S. Williams

2013-01-01

Many new methods for sampling down coarse woody debris have been proposed in the last dozen or so years. One of the most promising in terms of field application, perpendicular distance sampling (PDS), has several variants that have been progressively introduced in the literature. In this study, we provide an overview of the different PDS variants and comprehensive...

Research of Subgraph Estimation Page Rank Algorithm for Web Page Rank

Directory of Open Access Journals (Sweden)

LI Lan-yin

2017-04-01

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

Model of Decision Making through Consensus in Ranking Case

Science.gov (United States)

Tarigan, Gim; Darnius, Open

2018-01-01

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

Robustness of Distance-to-Default

DEFF Research Database (Denmark)

Jessen, Cathrine; Lando, David

2013-01-01

. A notable exception is a model with stochastic volatility of assets. In this case both the ranking of firms and the estimated default probabilities using distance-to-default perform significantly worse. We therefore propose a volatility adjustment of the distance-to-default measure, that significantly...

A distance limited method for sampling downed coarse woody debris

Science.gov (United States)

Jeffrey H. Gove; Mark J. Ducey; Harry T. Valentine; Michael S. Williams

2012-01-01

A new sampling method for down coarse woody debris is proposed based on limiting the perpendicular distance from individual pieces to a randomly chosen sample point. Two approaches are presented that allow different protocols to be used to determine field measurements; estimators for each protocol are also developed. Both protocols are compared via simulation against...

Direct comparison of observed magnitude-redshift relations in complete galaxy samples with systematic predictions of alternative redshift-distance laws

International Nuclear Information System (INIS)

Segal, I.E.

1989-01-01

The directly observed average apparent magnitude (or in one case, angular diameter) as a function of redshift in each of a number of large complete galaxy samples is compared with the predictions of hypothetical redshift-distance power laws, as a systematic statistical question. Due account is taken of observational flux limits by an entirely objective and reproducible optimal statistical procedure, and no assumptions are made regarding the distribution of the galaxies in space. The laws considered are of the form z varies as r p , where r denotes the distance, for p = 1, 2 and 3. The comparative fits of the various redshift-distance laws are similar in all the samples. Overall, the cubic law fits better than the linear law, but each shows substantial systematic deviations from observation. The quadratic law fits extremely well except at high redshifts in some of the samples, where no power law fits closely and the correlation of apparent magnitude with redshift is small or negative. In all cases, the luminosity function required for theoretical prediction was estimated from the sample by the non-parametric procedure ROBUST, whose intrinsic neutrality as programmed was checked by comprehensive computer simulations. (author)

How to Rank Journals.

Science.gov (United States)

Bradshaw, Corey J A; Brook, Barry W

2016-01-01

There are now many methods available to assess the relative citation performance of peer-reviewed journals. Regardless of their individual faults and advantages, citation-based metrics are used by researchers to maximize the citation potential of their articles, and by employers to rank academic track records. The absolute value of any particular index is arguably meaningless unless compared to other journals, and different metrics result in divergent rankings. To provide a simple yet more objective way to rank journals within and among disciplines, we developed a κ-resampled composite journal rank incorporating five popular citation indices: Impact Factor, Immediacy Index, Source-Normalized Impact Per Paper, SCImago Journal Rank and Google 5-year h-index; this approach provides an index of relative rank uncertainty. We applied the approach to six sample sets of scientific journals from Ecology (n = 100 journals), Medicine (n = 100), Multidisciplinary (n = 50); Ecology + Multidisciplinary (n = 25), Obstetrics & Gynaecology (n = 25) and Marine Biology & Fisheries (n = 25). We then cross-compared the κ-resampled ranking for the Ecology + Multidisciplinary journal set to the results of a survey of 188 publishing ecologists who were asked to rank the same journals, and found a 0.68-0.84 Spearman's ρ correlation between the two rankings datasets. Our composite index approach therefore approximates relative journal reputation, at least for that discipline. Agglomerative and divisive clustering and multi-dimensional scaling techniques applied to the Ecology + Multidisciplinary journal set identified specific clusters of similarly ranked journals, with only Nature & Science separating out from the others. When comparing a selection of journals within or among disciplines, we recommend collecting multiple citation-based metrics for a sample of relevant and realistic journals to calculate the composite rankings and their relative uncertainty windows.

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

Science.gov (United States)

Meyer, Karin; Kirkpatrick, Mark

2008-10-01

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

A probabilistic sampling method (PSM for estimating geographic distance to health services when only the region of residence is known

Directory of Open Access Journals (Sweden)

Peek-Asa Corinne

2011-01-01

Full Text Available Abstract Background The need to estimate the distance from an individual to a service provider is common in public health research. However, estimated distances are often imprecise and, we suspect, biased due to a lack of specific residential location data. In many cases, to protect subject confidentiality, data sets contain only a ZIP Code or a county. Results This paper describes an algorithm, known as "the probabilistic sampling method" (PSM, which was used to create a distribution of estimated distances to a health facility for a person whose region of residence was known, but for which demographic details and centroids were known for smaller areas within the region. From this distribution, the median distance is the most likely distance to the facility. The algorithm, using Monte Carlo sampling methods, drew a probabilistic sample of all the smaller areas (Census blocks within each participant's reported region (ZIP Code, weighting these areas by the number of residents in the same age group as the participant. To test the PSM, we used data from a large cross-sectional study that screened women at a clinic for intimate partner violence (IPV. We had data on each woman's age and ZIP Code, but no precise residential address. We used the PSM to select a sample of census blocks, then calculated network distances from each census block's centroid to the closest IPV facility, resulting in a distribution of distances from these locations to the geocoded locations of known IPV services. We selected the median distance as the most likely distance traveled and computed confidence intervals that describe the shortest and longest distance within which any given percent of the distance estimates lie. We compared our results to those obtained using two other geocoding approaches. We show that one method overestimated the most likely distance and the other underestimated it. Neither of the alternative methods produced confidence intervals for the distance

A probabilistic sampling method (PSM) for estimating geographic distance to health services when only the region of residence is known

Science.gov (United States)

2011-01-01

Background The need to estimate the distance from an individual to a service provider is common in public health research. However, estimated distances are often imprecise and, we suspect, biased due to a lack of specific residential location data. In many cases, to protect subject confidentiality, data sets contain only a ZIP Code or a county. Results This paper describes an algorithm, known as "the probabilistic sampling method" (PSM), which was used to create a distribution of estimated distances to a health facility for a person whose region of residence was known, but for which demographic details and centroids were known for smaller areas within the region. From this distribution, the median distance is the most likely distance to the facility. The algorithm, using Monte Carlo sampling methods, drew a probabilistic sample of all the smaller areas (Census blocks) within each participant's reported region (ZIP Code), weighting these areas by the number of residents in the same age group as the participant. To test the PSM, we used data from a large cross-sectional study that screened women at a clinic for intimate partner violence (IPV). We had data on each woman's age and ZIP Code, but no precise residential address. We used the PSM to select a sample of census blocks, then calculated network distances from each census block's centroid to the closest IPV facility, resulting in a distribution of distances from these locations to the geocoded locations of known IPV services. We selected the median distance as the most likely distance traveled and computed confidence intervals that describe the shortest and longest distance within which any given percent of the distance estimates lie. We compared our results to those obtained using two other geocoding approaches. We show that one method overestimated the most likely distance and the other underestimated it. Neither of the alternative methods produced confidence intervals for the distance estimates. The algorithm

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

Science.gov (United States)

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

2018-01-01

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

Universal emergence of PageRank

Energy Technology Data Exchange (ETDEWEB)

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

2011-11-18

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

Universal emergence of PageRank

International Nuclear Information System (INIS)

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

2011-01-01

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

Efficient Similarity Search Using the Earth Mover's Distance for Large Multimedia Databases

DEFF Research Database (Denmark)

Assent, Ira; Wichterich, Marc; Meisen, Tobias

2008-01-01

Multimedia similarity search in large databases requires efficient query processing. The Earth mover's distance, introduced in computer vision, is successfully used as a similarity model in a number of small-scale applications. Its computational complexity hindered its adoption in large multimedia...... databases. We enable directly indexing the Earth mover's distance in structures such as the R-tree and the VA-file by providing the accurate 'MinDist' function to any bounding rectangle in the index. We exploit the computational structure of the new MinDist to derive a new lower bound for the EMD Min...

In silico sampling reveals the effect of clustering and shows that the log-normal rank abundance curve is an artefact

NARCIS (Netherlands)

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

2005-01-01

The impact of clustering on rank abundance, species-individual (S-N)and species-area curves was investigated using a computer programme for in silico sampling. In a rank abundance curve the abundances of species are plotted on log-scale against species sequence. In an S-N curve the number of species

Evaluation of single and two-stage adaptive sampling designs for estimation of density and abundance of freshwater mussels in a large river

Science.gov (United States)

Smith, D.R.; Rogala, J.T.; Gray, B.R.; Zigler, S.J.; Newton, T.J.

2011-01-01

Reliable estimates of abundance are needed to assess consequences of proposed habitat restoration and enhancement projects on freshwater mussels in the Upper Mississippi River (UMR). Although there is general guidance on sampling techniques for population assessment of freshwater mussels, the actual performance of sampling designs can depend critically on the population density and spatial distribution at the project site. To evaluate various sampling designs, we simulated sampling of populations, which varied in density and degree of spatial clustering. Because of logistics and costs of large river sampling and spatial clustering of freshwater mussels, we focused on adaptive and non-adaptive versions of single and two-stage sampling. The candidate designs performed similarly in terms of precision (CV) and probability of species detection for fixed sample size. Both CV and species detection were determined largely by density, spatial distribution and sample size. However, designs did differ in the rate that occupied quadrats were encountered. Occupied units had a higher probability of selection using adaptive designs than conventional designs. We used two measures of cost: sample size (i.e. number of quadrats) and distance travelled between the quadrats. Adaptive and two-stage designs tended to reduce distance between sampling units, and thus performed better when distance travelled was considered. Based on the comparisons, we provide general recommendations on the sampling designs for the freshwater mussels in the UMR, and presumably other large rivers.

The dipole-dipole dispersion forces for small, intermediate and large distances

International Nuclear Information System (INIS)

Antonio, J.C.

1986-10-01

An improved expression is obtained for the dipole-dipole London dispersion force between closed shell atoms for small, intermediate and large distances compared with their linear dimensions. (Author) [pt

Survey of sampling-based methods for uncertainty and sensitivity analysis

International Nuclear Information System (INIS)

Helton, J.C.; Johnson, J.D.; Sallaberry, C.J.; Storlie, C.B.

2006-01-01

Sampling-based methods for uncertainty and sensitivity analysis are reviewed. The following topics are considered: (i) definition of probability distributions to characterize epistemic uncertainty in analysis inputs (ii) generation of samples from uncertain analysis inputs (iii) propagation of sampled inputs through an analysis (iv) presentation of uncertainty analysis results, and (v) determination of sensitivity analysis results. Special attention is given to the determination of sensitivity analysis results, with brief descriptions and illustrations given for the following procedures/techniques: examination of scatterplots, correlation analysis, regression analysis, partial correlation analysis, rank transformations, statistical tests for patterns based on gridding, entropy tests for patterns based on gridding, nonparametric regression analysis, squared rank differences/rank correlation coefficient test, two-dimensional Kolmogorov-Smirnov test, tests for patterns based on distance measures, top down coefficient of concordance, and variance decomposition

Survey of sampling-based methods for uncertainty and sensitivity analysis.

Energy Technology Data Exchange (ETDEWEB)

Johnson, Jay Dean; Helton, Jon Craig; Sallaberry, Cedric J. PhD. (.; .); Storlie, Curt B. (Colorado State University, Fort Collins, CO)

2006-06-01

Sampling-based methods for uncertainty and sensitivity analysis are reviewed. The following topics are considered: (1) Definition of probability distributions to characterize epistemic uncertainty in analysis inputs, (2) Generation of samples from uncertain analysis inputs, (3) Propagation of sampled inputs through an analysis, (4) Presentation of uncertainty analysis results, and (5) Determination of sensitivity analysis results. Special attention is given to the determination of sensitivity analysis results, with brief descriptions and illustrations given for the following procedures/techniques: examination of scatterplots, correlation analysis, regression analysis, partial correlation analysis, rank transformations, statistical tests for patterns based on gridding, entropy tests for patterns based on gridding, nonparametric regression analysis, squared rank differences/rank correlation coefficient test, two dimensional Kolmogorov-Smirnov test, tests for patterns based on distance measures, top down coefficient of concordance, and variance decomposition.

Exact distributions of two-sample rank statistics and block rank statistics using computer algebra

NARCIS (Netherlands)

Wiel, van de M.A.

1998-01-01

We derive generating functions for various rank statistics and we use computer algebra to compute the exact null distribution of these statistics. We present various techniques for reducing time and memory space used by the computations. We use the results to write Mathematica notebooks for

Linear Subspace Ranking Hashing for Cross-Modal Retrieval.

Science.gov (United States)

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

2017-09-01

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

Estimating the encounter rate variance in distance sampling

Science.gov (United States)

Fewster, R.M.; Buckland, S.T.; Burnham, K.P.; Borchers, D.L.; Jupp, P.E.; Laake, J.L.; Thomas, L.

2009-01-01

The dominant source of variance in line transect sampling is usually the encounter rate variance. Systematic survey designs are often used to reduce the true variability among different realizations of the design, but estimating the variance is difficult and estimators typically approximate the variance by treating the design as a simple random sample of lines. We explore the properties of different encounter rate variance estimators under random and systematic designs. We show that a design-based variance estimator improves upon the model-based estimator of Buckland et al. (2001, Introduction to Distance Sampling. Oxford: Oxford University Press, p. 79) when transects are positioned at random. However, if populations exhibit strong spatial trends, both estimators can have substantial positive bias under systematic designs. We show that poststratification is effective in reducing this bias. ?? 2008, The International Biometric Society.

Perturbative QCD Lagrangian at large distances and stochastic dimensionality reduction. Pt. 2

International Nuclear Information System (INIS)

Shintani, M.

1986-11-01

Using the method of stochastic dimensional reduction, we derive a four-dimensional quantum effective Lagrangian for the classical Yang-Mills system coupled to the Gaussian white noise. It is found that the Lagrangian coincides with the perturbative QCD at large distances constructed in our previous paper. That formalism is based on the local covariant operator formalism which maintains the unitarity of the S-matrix. Furthermore, we show the non-perturbative equivalence between super-Lorentz invariant sectors of the effective Lagrangian and two dimensional QCD coupled to the adjoint pseudo-scalars. This implies that stochastic dimensionality reduction by two is approximately operative in QCD at large distances. (orig.)

Finite sample performance of the E-M algorithm for ranks data modelling

Directory of Open Access Journals (Sweden)

Angela D'Elia

2007-10-01

Full Text Available We check the finite sample performance of the maximum likelihood estimators of the parameters of a mixture distribution recently introduced for modelling ranks/preference data. The estimates are derived by the E-M algorithm and the performance is evaluated both from an univariate and bivariate points of view. While the results are generally acceptable as far as it concerns the bias, the Monte Carlo experiment shows a different behaviour of the estimators efficiency for the two parameters of the mixture, mainly depending upon their location in the admissible parametric space. Some operative suggestions conclude the paer.

The average number of critical rank-one approximations to a tensor

NARCIS (Netherlands)

Draisma, J.; Horobet, E.

2014-01-01

Motivated by the many potential applications of low-rank multi-way tensor approximations, we set out to count the rank-one tensors that are critical points of the distance function to a general tensor v. As this count depends on v, we average over v drawn from a Gaussian distribution, and find

Clustering for high-dimension, low-sample size data using distance vectors

OpenAIRE

Terada, Yoshikazu

2013-01-01

In high-dimension, low-sample size (HDLSS) data, it is not always true that closeness of two objects reflects a hidden cluster structure. We point out the important fact that it is not the closeness, but the "values" of distance that contain information of the cluster structure in high-dimensional space. Based on this fact, we propose an efficient and simple clustering approach, called distance vector clustering, for HDLSS data. Under the assumptions given in the work of Hall et al. (2005), w...

Relationship between Sampling Distance and Carbon Dioxide Emission under Oil Palm Plantation

Directory of Open Access Journals (Sweden)

Ai Dariah

2013-05-01

Full Text Available A carbon dioxide emission on peatland under oil palm plantation was highly varied due to many factors involved. The objectives of the research were to evaluate the effect of sampling distance from center of oil palm tree on Carbon dioxide flux, and to study the factors that cause variability of carbon dioxide flux on peatland under oil palm plantation. The study was conducted on peatland at Arang-Arang Village, Kumpek Ulu Sub-District, Muaro Jambi District, Jambi Province, on six-years old oil palm plantation. The study was conducted in the form of observational exploratory. Emission measurements were performed on 5 selected oil palm trees at points within 100, 150, 200, 250, 300, 350, and 400 cm from the center of trunk. Carbon dioxide flux was measured using (IRGA, Li-COR 820. The results showed that there was significant correlation between the distance of sampling from center of oil palm tree and Carbon dioxide flux. The farther distance from the tree, the more decreased of Carbon dioxide flux . Before applying fertilizer, variability of soil fertility was not significantly correlated with the flux of Carbon dioxide, so the difference of Carbon dioxide flux based on distance sampling can be caused by root distribution factor. After fertilizer application, variability of Carbon dioxide flux under the oil palm tree were not only affected by differences in root distribution but also greatly influenced by fertilization.

PageRank of integers

International Nuclear Information System (INIS)

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

2012-01-01

We up a directed network tracing links from a given integer to its divisors and analyze the properties of the Google matrix of this network. The PageRank vector of this matrix is computed numerically and it is shown that its probability is approximately inversely proportional to the PageRank index thus being similar to the Zipf law and the dependence established for the World Wide Web. The spectrum of the Google matrix of integers is characterized by a large gap and a relatively small number of nonzero eigenvalues. A simple semi-analytical expression for the PageRank of integers is derived that allows us to find this vector for matrices of billion size. This network provides a new PageRank order of integers. (paper)

HADRONS-94: Soft interactions at large distances

International Nuclear Information System (INIS)

Atkinson, David; Jenkovszky, Laszlo

1994-01-01

Ten years ago the Institute for Theoretical Physics (known since 1992 as the Bogolubov Institute after its founder) of the Academy of Science of the Ukraine initiated what has become a very successful series of annual meetings on strong interactions at large distances. Although sometimes overshadowed by the successes of the Standard Model isotope dilutions and the theoretical enticements of supertheories; the Hadrons series has overcome political barriers and financial chaos to bring together physicists from diverse backgrounds to discuss central physics issues. The latest workshop in the series was held from September 7-11 in Uzhgorod (Ungvar), a small university town in the westernmost reaches of the Ukraine, bordering on Hungary, Poland, Romania and Slovakia.

Association between Metabolic Syndrome and Job Rank.

Science.gov (United States)

Mehrdad, Ramin; Pouryaghoub, Gholamreza; Moradi, Mahboubeh

2018-01-01

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

Hierarchical partial order ranking

International Nuclear Information System (INIS)

Carlsen, Lars

2008-01-01

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

Co-integration Rank Testing under Conditional Heteroskedasticity

DEFF Research Database (Denmark)

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

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

The contribution of social rank and attachment theory to depression in a non clinical sample of adolescents.

Science.gov (United States)

Puissant, Sylvia Pinna; Gauthier, Jean-Marie; Van Oirbeek, Robin

2011-11-01

This study explores the relative contribution of the overall quality of attachment to the mother, to the father and to peers (Inventory of Parent and Peer Attachment scales), the style of attachment towards peers (Attachment Questionnaire for Children scale), the social rank variables (submissive behavior and social comparison), and sex and age variables in predicting the depression score (Center of Epidemiological Studies Depression Scale) on a non-psychiatric sample of 13-18 year old adolescents (n = 225). Results of our integrated model (adjusted R-Square of .50) show that attachment variables (overall quality of attachment to the father and to the mother), social rank variables (social comparison and submissive behavior), age and sex are important in predicting depressive symptoms during adolescence. Moreover, the attachment to peers variables (quality of attachment to peers, secure and ambivalent style of attachment) and sex are mediated by the social rank variables (social comparison and submissive behavior).

Reachable Distance Space: Efficient Sampling-Based Planning for Spatially Constrained Systems

KAUST Repository

Xinyu Tang,; Thomas, S.; Coleman, P.; Amato, N. M.

2010-01-01

reachable distance space (RD-space), in which all configurations lie in the set of constraint-satisfying subspaces. This enables us to directly sample the constrained subspaces with complexity linear in the number of the robot's degrees of freedom

Perturbative QCD lagrangian at large distances and stochastic dimensionality reduction

International Nuclear Information System (INIS)

Shintani, M.

1986-10-01

We construct a Lagrangian for perturbative QCD at large distances within the covariant operator formalism which explains the color confinement of quarks and gluons while maintaining unitarity of the S-matrix. It is also shown that when interactions are switched off, the mechanism of stochastic dimensionality reduction is operative in the system due to exact super-Lorentz symmetries. (orig.)

A large catalog of accurate distances to molecular clouds from PS1 photometry

Energy Technology Data Exchange (ETDEWEB)

Schlafly, E. F.; Rix, H.-W.; Martin, N. F. [Max Planck Institute for Astronomy, Königstuhl 17, D-69117 Heidelberg (Germany); Green, G.; Finkbeiner, D. P. [Harvard-Smithsonian Center for Astrophysics, 60 Garden Street, Cambridge, MA 02138 (United States); Bell, E. F. [Department of Astronomy, University of Michigan, 500 Church Street, Ann Arbor, MI 48109 (United States); Burgett, W. S.; Chambers, K. C.; Hodapp, K. W.; Kaiser, N.; Magnier, E. A.; Tonry, J. L. [Institute for Astronomy, University of Hawaii, 2680 Woodlawn Drive, Honolulu, HI 96822 (United States); Draper, P. W.; Metcalfe, N. [Department of Physics, Durham University, South Road, Durham DH1 3LE (United Kingdom); Price, P. A. [Department of Astrophysical Sciences, Princeton University, Princeton, NJ 08544 (United States)

2014-05-01

Distance measurements to molecular clouds are important but are often made separately for each cloud of interest, employing very different data and techniques. We present a large, homogeneous catalog of distances to molecular clouds, most of which are of unprecedented accuracy. We determine distances using optical photometry of stars along lines of sight toward these clouds, obtained from PanSTARRS-1. We simultaneously infer the reddenings and distances to these stars, tracking the full probability distribution function using a technique presented in Green et al. We fit these star-by-star measurements using a simple dust screen model to find the distance to each cloud. We thus estimate the distances to almost all of the clouds in the Magnani et al. catalog, as well as many other well-studied clouds, including Orion, Perseus, Taurus, Cepheus, Polaris, California, and Monoceros R2, avoiding only the inner Galaxy. Typical statistical uncertainties in the distances are 5%, though the systematic uncertainty stemming from the quality of our stellar models is about 10%. The resulting catalog is the largest catalog of accurate, directly measured distances to molecular clouds. Our distance estimates are generally consistent with available distance estimates from the literature, though in some cases the literature estimates are off by a factor of more than two.

Practical method of calculating time-integrated concentrations at medium and large distances

International Nuclear Information System (INIS)

Cagnetti, P.; Ferrara, V.

1980-01-01

Previous reports have covered the possibility of calculating time-integrated concentrations (TICs) for a prolonged release, based on concentration estimates for a brief release. This study proposes a simple method of evaluating concentrations in the air at medium and large distances, for a brief release. It is known that the stability of the atmospheric layers close to ground level influence diffusion only over short distances. Beyond some tens of kilometers, as the pollutant cloud progressively reaches higher layers, diffusion is affected by factors other than the stability at ground level, such as wind shear for intermediate distances and the divergence and rotational motion of air masses towards the upper limit of the mesoscale and on the synoptic scale. Using the data available in the literature, expressions for sigmasub(y) and sigmasub(z) are proposed for transfer times corresponding to those for up to distances of several thousand kilometres, for two initial diffusion situations (up to distances of 10 - 20 km), those characterized by stable and neutral conditions respectively. Using this method simple hand calculations can be made for any problem relating to the diffusion of radioactive pollutants over long distances

Low rank magnetic resonance fingerprinting.

Science.gov (United States)

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

2016-08-01

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

Ranking Fuzzy Numbers with a Distance Method using Circumcenter of Centroids and an Index of Modality

Directory of Open Access Journals (Sweden)

P. Phani Bushan Rao

2011-01-01

Full Text Available Ranking fuzzy numbers are an important aspect of decision making in a fuzzy environment. Since their inception in 1965, many authors have proposed different methods for ranking fuzzy numbers. However, there is no method which gives a satisfactory result to all situations. Most of the methods proposed so far are nondiscriminating and counterintuitive. This paper proposes a new method for ranking fuzzy numbers based on the Circumcenter of Centroids and uses an index of optimism to reflect the decision maker's optimistic attitude and also an index of modality that represents the neutrality of the decision maker. This method ranks various types of fuzzy numbers which include normal, generalized trapezoidal, and triangular fuzzy numbers along with crisp numbers with the particularity that crisp numbers are to be considered particular cases of fuzzy numbers.

Data envelopment analysis of randomized ranks

Directory of Open Access Journals (Sweden)

Sant'Anna Annibal P.

2002-01-01

Full Text Available Probabilities and odds, derived from vectors of ranks, are here compared as measures of efficiency of decision-making units (DMUs. These measures are computed with the goal of providing preliminary information before starting a Data Envelopment Analysis (DEA or the application of any other evaluation or composition of preferences methodology. Preferences, quality and productivity evaluations are usually measured with errors or subject to influence of other random disturbances. Reducing evaluations to ranks and treating the ranks as estimates of location parameters of random variables, we are able to compute the probability of each DMU being classified as the best according to the consumption of each input and the production of each output. Employing the probabilities of being the best as efficiency measures, we stretch distances between the most efficient units. We combine these partial probabilities in a global efficiency score determined in terms of proximity to the efficiency frontier.

Neurobiology of Maternal Stress: Role of Social Rank and Central Oxytocin in Hypothalamic-Pituitary Adrenal Axis Modulation

Directory of Open Access Journals (Sweden)

Jeremy D Coplan

2015-07-01

Full Text Available Background: Chronic stress may conceivably require plasticity of maternal physiology and behavior to cope with the conflicting primary demands of infant rearing and foraging for food. In addition, social rank may play a pivotal role in mandating divergent homeostatic adaptations in cohesive social groups. We examined cerebrospinal fluid (CSF oxytocin (OT levels and hypothalamic pituitary adrenal (HPA axis regulation in the context of maternal social stress and assessed the contribution of social rank to dyadic-distance as reflective of distraction from normative maternal-infant interaction. Methods: Twelve socially-housed mother-infant bonnet macaque dyads were studied after variable foraging demand (VFD exposure compared to 11 unstressed dyads. Dyadic-distance was determined by behavioral observation. Social ranking was performed blindly by two observers. Post-VFD maternal plasma cortisol and CSF OT were compared to corresponding measures in non-VFD exposed mothers. Results: High social rank was associated with increased dyadic-distance only in VFD-exposed dyads and not in control dyads. In mothers unexposed to VFD, social rank was not related to maternal cortisol levels whereas VFD-exposed dominant versus subordinate mothers exhibited increased plasma cortisol. Maternal CSF OT directly predicted maternal cortisol only in VFD-exposed mothers. CSF OT was higher in dominant versus subordinate mothers. VFD-exposed mothers with high cortisol specifically exhibited CSF OT elevations in comparison to control groups. Conclusions: Pairing of maternal social rank to dyadic-distance in VFD presumably reduces maternal contingent responsivity, with ensuing long-term sequelae. VFD-exposure dichotomizes maternal HPA axis response as a function of social rank with relatively reduced cortisol in subordinates. OT may serve as a homeostatic buffer during maternal stress exposure.

The Euclidean distance degree

NARCIS (Netherlands)

Draisma, J.; Horobet, E.; Ottaviani, G.; Sturmfels, B.; Thomas, R.R.; Zhi, L.; Watt, M.

2014-01-01

The nearest point map of a real algebraic variety with respect to Euclidean distance is an algebraic function. For instance, for varieties of low rank matrices, the Eckart-Young Theorem states that this map is given by the singular value decomposition. This article develops a theory of such nearest

Large sample neutron activation analysis of a reference inhomogeneous sample

International Nuclear Information System (INIS)

Vasilopoulou, T.; Athens National Technical University, Athens; Tzika, F.; Stamatelatos, I.E.; Koster-Ammerlaan, M.J.J.

2011-01-01

A benchmark experiment was performed for Neutron Activation Analysis (NAA) of a large inhomogeneous sample. The reference sample was developed in-house and consisted of SiO 2 matrix and an Al-Zn alloy 'inhomogeneity' body. Monte Carlo simulations were employed to derive appropriate correction factors for neutron self-shielding during irradiation as well as self-attenuation of gamma rays and sample geometry during counting. The large sample neutron activation analysis (LSNAA) results were compared against reference values and the trueness of the technique was evaluated. An agreement within ±10% was observed between LSNAA and reference elemental mass values, for all matrix and inhomogeneity elements except Samarium, provided that the inhomogeneity body was fully simulated. However, in cases that the inhomogeneity was treated as not known, the results showed a reasonable agreement for most matrix elements, while large discrepancies were observed for the inhomogeneity elements. This study provided a quantification of the uncertainties associated with inhomogeneity in large sample analysis and contributed to the identification of the needs for future development of LSNAA facilities for analysis of inhomogeneous samples. (author)

Distribution of hadron intranuclear cascade for large distance from a source

International Nuclear Information System (INIS)

Bibin, V.L.; Kazarnovskij, M.V.; Serezhnikov, S.V.

1985-01-01

Analytical solution of the problem of three-component hadron cascade development for large distances from a source is obtained in the framework of a series of simplifying assumptions. It makes possible to understand physical mechanisms of the process studied and to obtain approximate asymptotic expressions for hadron distribution functions

Using mark-recapture distance sampling methods on line transect surveys

Science.gov (United States)

Burt, Louise M.; Borchers, David L.; Jenkins, Kurt J.; Marques, Tigao A

2014-01-01

Mark–recapture distance sampling (MRDS) methods are widely used for density and abundance estimation when the conventional DS assumption of certain detection at distance zero fails, as they allow detection at distance zero to be estimated and incorporated into the overall probability of detection to better estimate density and abundance. However, incorporating MR data in DS models raises survey and analysis issues not present in conventional DS. Conversely, incorporating DS assumptions in MR models raises issues not present in conventional MR. As a result, being familiar with either conventional DS methods or conventional MR methods does not on its own put practitioners in good a position to apply MRDS methods appropriately. This study explains the sometimes subtly different varieties of MRDS survey methods and the associated concepts underlying MRDS models. This is done as far as possible without giving mathematical details – in the hope that this will make the key concepts underlying the methods accessible to a wider audience than if we were to present the concepts via equations.

Microseismic Event Relocation and Focal Mechanism Estimation Based on PageRank Linkage

Science.gov (United States)

Aguiar, A. C.; Myers, S. C.

2017-12-01

Microseismicity associated with enhanced geothermal systems (EGS) is key in understanding how subsurface stimulation can modify stress, fracture rock, and increase permeability. Large numbers of microseismic events are commonly associated with hydroshearing an EGS, making data mining methods useful in their analysis. We focus on PageRank, originally developed as Google's search engine, and subsequently adapted for use in seismology to detect low-frequency earthquakes by linking events directly and indirectly through cross-correlation (Aguiar and Beroza, 2014). We expand on this application by using PageRank to define signal-correlation topology for micro-earthquakes from the Newberry Volcano EGS in Central Oregon, which has been stimulated two times using high-pressure fluid injection. We create PageRank signal families from both data sets and compare these to the spatial and temporal proximity of associated earthquakes. PageRank families are relocated using differential travel times measured by waveform cross-correlation (CC) and the Bayesloc approach (Myers et al., 2007). Prior to relocation events are loosely clustered with events at a distance from the cluster. After relocation, event families are found to be tightly clustered. Indirect linkage of signals using PageRank is a reliable way to increase the number of events confidently determined to be similar, suggesting an efficient and effective grouping of earthquakes with similar physical characteristics (ie. location, focal mechanism, stress drop). We further explore the possibility of using PageRank families to identify events with similar relative phase polarities and estimate focal mechanisms following Shelly et al. (2016) method, where CC measurements are used to determine individual polarities within event clusters. Given a positive result, PageRank might be a useful tool in adaptive approaches to enhance production at well-instrumented geothermal sites. Prepared by LLNL under Contract DE-AC52-07NA27344

In-situ high resolution particle sampling by large time sequence inertial spectrometry

International Nuclear Information System (INIS)

Prodi, V.; Belosi, F.

1990-09-01

In situ sampling is always preferred, when possible, because of the artifacts that can arise when the aerosol has to flow through long sampling lines. On the other hand, the amount of possible losses can be calculated with some confidence only when the size distribution can be measured with a sufficient precision and the losses are not too large. This makes it desirable to sample directly in the vicinity of the aerosol source or containment. High temperature sampling devices with a detailed aerodynamic separation are extremely useful to this purpose. Several measurements are possible with the inertial spectrometer (INSPEC), but not with cascade impactors or cyclones. INSPEC - INertial SPECtrometer - has been conceived to measure the size distribution of aerosols by separating the particles while airborne according to their size and collecting them on a filter. It consists of a channel of rectangular cross-section with a 90 degree bend. Clean air is drawn through the channel, with a thin aerosol sheath injected close to the inner wall. Due to the bend, the particles are separated according to their size, leaving the original streamline by a distance which is a function of particle inertia and resistance, i.e. of aerodynamic diameter. The filter collects all the particles of the same aerodynamic size at the same distance from the inlet, in a continuous distribution. INSPEC particle separation at high temperature (up to 800 C) has been tested with Zirconia particles as calibration aerosols. The feasibility study has been concerned with resolution and time sequence sampling capabilities under high temperature (700 C)

Phenomenological dynamics in QCD at large distances

International Nuclear Information System (INIS)

Gogohia, V.Sh.; Kluge, Gy.

1991-07-01

A gauge-invariant, nonperturbative approach to QCD at large distances in the context of the Schwinger-Dyson equations and corresponding Slavnov-Taylor identities in the quark sector is presented. Making only one widely accepted assumption that the full gluon propagator becomes an infrared singular like (q 2 ) -2 in the covariant gauge, we find three and only three confinement-type solutions for the quark propagator (quark confinement theorem.) The approach is free from ghost complications. Also show that multiplication by the quark infrared renormalization constant only, would make all the Green's functions infrared finite (multiplicative renormalizability). The bound-state problem in framework of Bethe-Salpeter equation is discussed as well. Some basic physical parameters of chiral QCD as pion decay constant and quark condensate, have been calculated within our approach. (author) 75 refs.; 14 figs

Reference interval for the disc-macula distance to disc diameter ratio in a large population of healthy Japanese adults

Science.gov (United States)

Sato, Ken-ichi

2017-01-01

Abstract This study presents the calculated reference interval for the disc-to-macula distance to disc diameter ratio (DM:DD) based on a large population of healthy Japanese adults. A total of 308 consecutive, healthy Japanese adults were examined in this prospective observational study. Eighteen subjects were also excluded because of poor quality of the fundus photograph of one or both eyes; 290 (161 men and 129 women) were included in this study. For each subject, a color fundus photograph of one eye, either the right or left, was randomly selected and used for analysis. On the photograph, the distances between the fovea and the nearest temporal margin of the optic disc (Dft), and the two kinds of disc diameters (D1 and D2), which bisected at right angles and one of which was directed to the fovea (D1), were measured. DM:DD was estimated using the formula: (2Dft + D1)/(D1 + D2). The mean ± standard deviation of DM:DD was 2.91 ± 0.49 for men and 2.96 ± 0.54 for women; there was no sex difference (P = .78, Mann–Whitney U test). Also, almost no relationship was found between DM:DD and age (ρ = −.12, P = .04, Spearman's rank correlation coefficient). The data did not fit a normal distribution (P < .001, Kolmogorov–Smirnov test). The estimated reference interval for DM:DD corresponding to the 2.5th and 97.5th percentiles was 2.12 to 4.18. Using a nonparametric approach, the reference interval for DM:DD of a large population of healthy Japanese adults was calculated to be 2.12 to 4.18, regardless of age or sex. PMID:28403107

Large Sample Neutron Activation Analysis of Heterogeneous Samples

International Nuclear Information System (INIS)

Stamatelatos, I.E.; Vasilopoulou, T.; Tzika, F.

2018-01-01

A Large Sample Neutron Activation Analysis (LSNAA) technique was developed for non-destructive analysis of heterogeneous bulk samples. The technique incorporated collimated scanning and combining experimental measurements and Monte Carlo simulations for the identification of inhomogeneities in large volume samples and the correction of their effect on the interpretation of gamma-spectrometry data. Corrections were applied for the effect of neutron self-shielding, gamma-ray attenuation, geometrical factor and heterogeneous activity distribution within the sample. A benchmark experiment was performed to investigate the effect of heterogeneity on the accuracy of LSNAA. Moreover, a ceramic vase was analyzed as a whole demonstrating the feasibility of the technique. The LSNAA results were compared against results obtained by INAA and a satisfactory agreement between the two methods was observed. This study showed that LSNAA is a technique capable to perform accurate non-destructive, multi-elemental compositional analysis of heterogeneous objects. It also revealed the great potential of the technique for the analysis of precious objects and artefacts that need to be preserved intact and cannot be damaged for sampling purposes. (author)

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

Science.gov (United States)

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

2016-02-01

Phylogenetic analysis of extinction threat is an emerging tool in the field of conservation. However, there are problems with the methods and data as commonly used. Phylogenetic sampling usually extends to the level of family or genus, but International Union for Conservation of Nature (IUCN) rankings are available only for individual species, and, although different species within a taxonomic group may have the same IUCN rank, the species may have been ranked as such for different reasons. Therefore, IUCN rank may not reflect evolutionary history and thus may not be appropriate for use in a phylogenetic context. To be used appropriately, threat-risk data should reflect the cause of extinction threat rather than the IUCN threat ranking. In a case study of the toad genus Incilius, with phylogenetic sampling at the species level (so that the resolution of the phylogeny matches character data from the IUCN Red List), we analyzed causes of decline and IUCN threat rankings by calculating metrics of phylogenetic signal (such as Fritz and Purvis' D). We also analyzed the extent to which cause of decline and threat ranking overlap by calculating phylogenetic correlation between these 2 types of character data. Incilius species varied greatly in both threat ranking and cause of decline; this variability would be lost at a coarser taxonomic resolution. We found far more phylogenetic signal, likely correlated with evolutionary history, for causes of decline than for IUCN threat ranking. Individual causes of decline and IUCN threat rankings were largely uncorrelated on the phylogeny. Our results demonstrate the importance of character selection and taxonomic resolution when extinction threat is analyzed in a phylogenetic context. © 2015 Society for Conservation Biology.

Pearson's chi-square test and rank correlation inferences for clustered data.

Science.gov (United States)

Shih, Joanna H; Fay, Michael P

2017-09-01

Pearson's chi-square test has been widely used in testing for association between two categorical responses. Spearman rank correlation and Kendall's tau are often used for measuring and testing association between two continuous or ordered categorical responses. However, the established statistical properties of these tests are only valid when each pair of responses are independent, where each sampling unit has only one pair of responses. When each sampling unit consists of a cluster of paired responses, the assumption of independent pairs is violated. In this article, we apply the within-cluster resampling technique to U-statistics to form new tests and rank-based correlation estimators for possibly tied clustered data. We develop large sample properties of the new proposed tests and estimators and evaluate their performance by simulations. The proposed methods are applied to a data set collected from a PET/CT imaging study for illustration. Published 2017. This article is a U.S. Government work and is in the public domain in the USA.

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

Science.gov (United States)

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

2018-07-01

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

A New Paradigm for Supergranulation Derived from Large-Distance Time-Distance Helioseismology: Pancakes

Science.gov (United States)

Duvall, Thomas L.; Hanasoge, Shravan M.

2012-01-01

With large separations (10-24 deg heliocentric), it has proven possible to cleanly separate the horizontal and vertical components of supergranular flow with time-distance helioseismology. These measurements require very broad filters in the k-$\\omega$ power spectrum as apparently supergranulation scatters waves over a large area of the power spectrum. By picking locations of supergranulation as peaks in the horizontal divergence signal derived from f-mode waves, it is possible to simultaneously obtain average properties of supergranules and a high signal/noise ratio by averaging over many cells. By comparing ray-theory forward modeling with HMI measurements, an average supergranule model with a peak upflow of 240 m/s at cell center at a depth of 2.3 Mm and a peak horizontal outflow of 700 m/s at a depth of 1.6 Mm. This upflow is a factor of 20 larger than the measured photospheric upflow. These results may not be consistent with earlier measurements using much shorter separations (<5 deg heliocentric). With a 30 Mm horizontal extent and a few Mm in depth, the cells might be characterized as thick pancakes.

How Many Alternatives Can Be Ranked? A Comparison of the Paired Comparison and Ranking Methods.

Science.gov (United States)

Ock, Minsu; Yi, Nari; Ahn, Jeonghoon; Jo, Min-Woo

2016-01-01

To determine the feasibility of converting ranking data into paired comparison (PC) data and suggest the number of alternatives that can be ranked by comparing a PC and a ranking method. Using a total of 222 health states, a household survey was conducted in a sample of 300 individuals from the general population. Each respondent performed a PC 15 times and a ranking method 6 times (two attempts of ranking three, four, and five health states, respectively). The health states of the PC and the ranking method were constructed to overlap each other. We converted the ranked data into PC data and examined the consistency of the response rate. Applying probit regression, we obtained the predicted probability of each method. Pearson correlation coefficients were determined between the predicted probabilities of those methods. The mean absolute error was also assessed between the observed and the predicted values. The overall consistency of the response rate was 82.8%. The Pearson correlation coefficients were 0.789, 0.852, and 0.893 for ranking three, four, and five health states, respectively. The lowest mean absolute error was 0.082 (95% confidence interval [CI] 0.074-0.090) in ranking five health states, followed by 0.123 (95% CI 0.111-0.135) in ranking four health states and 0.126 (95% CI 0.113-0.138) in ranking three health states. After empirically examining the consistency of the response rate between a PC and a ranking method, we suggest that using five alternatives in the ranking method may be superior to using three or four alternatives. Copyright © 2016 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

The "Tracked Roaming Transect" and distance sampling methods increase the efficiency of underwater visual censuses.

Directory of Open Access Journals (Sweden)

Alejo J Irigoyen

total abundance with those estimated by divers using FW3, FW10, and DS estimators. Density estimates differed by 13% (range 0.1-31% from the actual values (average = 13.09%; median = 14.16%. Based on our results we encourage the use of the Tracked Roaming Transect with Distance Sampling (TRT+DS method for improving density estimates of species occurring at low densities and/or highly aggregated, as well as for exploratory rapid-assessment surveys in which divers could gather spatial ecological and ecosystem information on large areas during UVC.

Universal scaling in sports ranking

International Nuclear Information System (INIS)

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

2012-01-01

Ranking is a ubiquitous phenomenon in human society. On the web pages of Forbes, one may find all kinds of rankings, such as the world's most powerful people, the world's richest people, the highest-earning tennis players, and so on and so forth. Herewith, we study a specific kind—sports ranking systems in which players' scores and/or prize money are accrued based on their performances in different matches. By investigating 40 data samples which span 12 different sports, we find that the distributions of scores and/or prize money follow universal power laws, with exponents nearly identical for most sports. In order to understand the origin of this universal scaling we focus on the tennis ranking systems. By checking the data we find that, for any pair of players, the probability that the higher-ranked player tops the lower-ranked opponent is proportional to the rank difference between the pair. Such a dependence can be well fitted to a sigmoidal function. By using this feature, we propose a simple toy model which can simulate the competition of players in different matches. The simulations yield results consistent with the empirical findings. Extensive simulation studies indicate that the model is quite robust with respect to the modifications of some parameters. (paper)

Real-Time Pathogen Detection in the Era of Whole-Genome Sequencing and Big Data: Comparison of k-mer and Site-Based Methods for Inferring the Genetic Distances among Tens of Thousands of Salmonella Samples.

Science.gov (United States)

Pettengill, James B; Pightling, Arthur W; Baugher, Joseph D; Rand, Hugh; Strain, Errol

2016-01-01

The adoption of whole-genome sequencing within the public health realm for molecular characterization of bacterial pathogens has been followed by an increased emphasis on real-time detection of emerging outbreaks (e.g., food-borne Salmonellosis). In turn, large databases of whole-genome sequence data are being populated. These databases currently contain tens of thousands of samples and are expected to grow to hundreds of thousands within a few years. For these databases to be of optimal use one must be able to quickly interrogate them to accurately determine the genetic distances among a set of samples. Being able to do so is challenging due to both biological (evolutionary diverse samples) and computational (petabytes of sequence data) issues. We evaluated seven measures of genetic distance, which were estimated from either k-mer profiles (Jaccard, Euclidean, Manhattan, Mash Jaccard, and Mash distances) or nucleotide sites (NUCmer and an extended multi-locus sequence typing (MLST) scheme). When analyzing empirical data (whole-genome sequence data from 18,997 Salmonella isolates) there are features (e.g., genomic, assembly, and contamination) that cause distances inferred from k-mer profiles, which treat absent data as informative, to fail to accurately capture the distance between samples when compared to distances inferred from differences in nucleotide sites. Thus, site-based distances, like NUCmer and extended MLST, are superior in performance, but accessing the computing resources necessary to perform them may be challenging when analyzing large databases.

Real-Time Pathogen Detection in the Era of Whole-Genome Sequencing and Big Data: Comparison of k-mer and Site-Based Methods for Inferring the Genetic Distances among Tens of Thousands of Salmonella Samples.

Directory of Open Access Journals (Sweden)

James B Pettengill

Full Text Available The adoption of whole-genome sequencing within the public health realm for molecular characterization of bacterial pathogens has been followed by an increased emphasis on real-time detection of emerging outbreaks (e.g., food-borne Salmonellosis. In turn, large databases of whole-genome sequence data are being populated. These databases currently contain tens of thousands of samples and are expected to grow to hundreds of thousands within a few years. For these databases to be of optimal use one must be able to quickly interrogate them to accurately determine the genetic distances among a set of samples. Being able to do so is challenging due to both biological (evolutionary diverse samples and computational (petabytes of sequence data issues. We evaluated seven measures of genetic distance, which were estimated from either k-mer profiles (Jaccard, Euclidean, Manhattan, Mash Jaccard, and Mash distances or nucleotide sites (NUCmer and an extended multi-locus sequence typing (MLST scheme. When analyzing empirical data (whole-genome sequence data from 18,997 Salmonella isolates there are features (e.g., genomic, assembly, and contamination that cause distances inferred from k-mer profiles, which treat absent data as informative, to fail to accurately capture the distance between samples when compared to distances inferred from differences in nucleotide sites. Thus, site-based distances, like NUCmer and extended MLST, are superior in performance, but accessing the computing resources necessary to perform them may be challenging when analyzing large databases.

Error analysis of stochastic gradient descent ranking.

Science.gov (United States)

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

2013-06-01

Ranking is always an important task in machine learning and information retrieval, e.g., collaborative filtering, recommender systems, drug discovery, etc. A kernel-based stochastic gradient descent algorithm with the least squares loss is proposed for ranking in this paper. The implementation of this algorithm is simple, and an expression of the solution is derived via a sampling operator and an integral operator. An explicit convergence rate for leaning a ranking function is given in terms of the suitable choices of the step size and the regularization parameter. The analysis technique used here is capacity independent and is novel in error analysis of ranking learning. Experimental results on real-world data have shown the effectiveness of the proposed algorithm in ranking tasks, which verifies the theoretical analysis in ranking error.

Robust haptic large distance telemanipulation for ITER

International Nuclear Information System (INIS)

Heck, D.J.F.; Heemskerk, C.J.M.; Koning, J.F.; Abbasi, A.; Nijmeijer, H.

2013-01-01

Highlights: • ITER remote handling maintenance can be controlled safely over a large distance. • Bilateral teleoperation experiments were performed in a local network. • Wave variables make the controller robust against constant communication delays. • Master and slave position synchronization guaranteed by proportional action. -- Abstract: During shutdowns, maintenance crews are expected to work in 24/6 shifts to perform critical remote handling maintenance tasks on the ITER system. In this article, we investigate the possibility to safely perform these haptic maintenance tasks remotely from control stations located anywhere around the world. To guarantee stability in time delayed bilateral teleoperation, the symmetric position tracking controller using wave variables is selected. This algorithm guarantees robustness against communication delays, can eliminate wave reflections and provide position synchronization of the master and slave devices. Experiments have been conducted under realistic local network bandwidth, latency and jitter constraints. They show sufficient transparency even for substantial communication delays

Robust haptic large distance telemanipulation for ITER

Energy Technology Data Exchange (ETDEWEB)

Heck, D.J.F., E-mail: d.j.f.heck@tue.nl [Eindhoven University of Technology, Department of Mechanical Engineering, Eindhoven (Netherlands); Heemskerk, C.J.M.; Koning, J.F. [Heemskerk Innovative Technologies, Sassenheim (Netherlands); Abbasi, A.; Nijmeijer, H. [Eindhoven University of Technology, Department of Mechanical Engineering, Eindhoven (Netherlands)

2013-10-15

Highlights: • ITER remote handling maintenance can be controlled safely over a large distance. • Bilateral teleoperation experiments were performed in a local network. • Wave variables make the controller robust against constant communication delays. • Master and slave position synchronization guaranteed by proportional action. -- Abstract: During shutdowns, maintenance crews are expected to work in 24/6 shifts to perform critical remote handling maintenance tasks on the ITER system. In this article, we investigate the possibility to safely perform these haptic maintenance tasks remotely from control stations located anywhere around the world. To guarantee stability in time delayed bilateral teleoperation, the symmetric position tracking controller using wave variables is selected. This algorithm guarantees robustness against communication delays, can eliminate wave reflections and provide position synchronization of the master and slave devices. Experiments have been conducted under realistic local network bandwidth, latency and jitter constraints. They show sufficient transparency even for substantial communication delays.

Gene coexpression measures in large heterogeneous samples using count statistics.

Science.gov (United States)

Wang, Y X Rachel; Waterman, Michael S; Huang, Haiyan

2014-11-18

With the advent of high-throughput technologies making large-scale gene expression data readily available, developing appropriate computational tools to process these data and distill insights into systems biology has been an important part of the "big data" challenge. Gene coexpression is one of the earliest techniques developed that is still widely in use for functional annotation, pathway analysis, and, most importantly, the reconstruction of gene regulatory networks, based on gene expression data. However, most coexpression measures do not specifically account for local features in expression profiles. For example, it is very likely that the patterns of gene association may change or only exist in a subset of the samples, especially when the samples are pooled from a range of experiments. We propose two new gene coexpression statistics based on counting local patterns of gene expression ranks to take into account the potentially diverse nature of gene interactions. In particular, one of our statistics is designed for time-course data with local dependence structures, such as time series coupled over a subregion of the time domain. We provide asymptotic analysis of their distributions and power, and evaluate their performance against a wide range of existing coexpression measures on simulated and real data. Our new statistics are fast to compute, robust against outliers, and show comparable and often better general performance.

The prevalence, diagnostic significance and demographic characteristics of Schneiderian first-rank symptoms in an epidemiological sample of first-episode psychoses.

LENUS (Irish Health Repository)

Ihara, Kazushige

2009-01-01

The diagnostic significance of first-rank symptoms (FRSs) remains uncertain. Ethnic differences in FRSs may account for high rates of schizophrenia in minority groups. This study aims to examine the prevalence of FRSs in an epidemiological sample of first-episode psychoses stratified by relevant demographic variables. SAMPLING AND METHOD: We identified everyone aged 16-64 presenting with their first psychosis over 2 years in 3 UK centres.

Monte Carlo methods of PageRank computation

NARCIS (Netherlands)

Litvak, Nelli

2004-01-01

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

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

International Nuclear Information System (INIS)

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

2009-01-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2009-01-15

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

Optimal sampling designs for large-scale fishery sample surveys in Greece

Directory of Open Access Journals (Sweden)

G. BAZIGOS

2007-12-01

The paper deals with the optimization of the following three large scale sample surveys: biological sample survey of commercial landings (BSCL, experimental fishing sample survey (EFSS, and commercial landings and effort sample survey (CLES.

Adiabatic quantum algorithm for search engine ranking.

Science.gov (United States)

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

2012-06-08

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

Reactive sputtering of TiN films at large substrate to target distances

International Nuclear Information System (INIS)

Musil, J.; Kadlec, S.

1990-01-01

This paper is a critical review of the present status of the magnetron ion sputter plating of thin CiN films. Thus different possibilities of extracting high ion currents 1 s from the magnetron discharge to substrates located not only at standard target to substrate distances d S-T of about 50 mm but also at larger distances d S-T are discussed in detail. Special attention is devoted to magnetron sputtering systems with enhanced ionization, to plasma confinement in the magnetron sputtering systems and to the discharge characteristics of an unbalanced magnetron (UM). It is shown that a UM can be operated in the regime of a double-site-sustained discharge (DSSD) and in this case large 1 s can be extracted to substrates located in large D S-T of about 200 mm and even at high pressures p = 5 Pa. A physical comparison of the conventional magnetron (CM), UM and DSSD is also given. Considerable attention is also devoted to the effect of ion bombardment on properties of TiN films created in the sputtering system using DSSD. (author)

Identification of significant features by the Global Mean Rank test.

Science.gov (United States)

Klammer, Martin; Dybowski, J Nikolaj; Hoffmann, Daniel; Schaab, Christoph

2014-01-01

With the introduction of omics-technologies such as transcriptomics and proteomics, numerous methods for the reliable identification of significantly regulated features (genes, proteins, etc.) have been developed. Experimental practice requires these tests to successfully deal with conditions such as small numbers of replicates, missing values, non-normally distributed expression levels, and non-identical distributions of features. With the MeanRank test we aimed at developing a test that performs robustly under these conditions, while favorably scaling with the number of replicates. The test proposed here is a global one-sample location test, which is based on the mean ranks across replicates, and internally estimates and controls the false discovery rate. Furthermore, missing data is accounted for without the need of imputation. In extensive simulations comparing MeanRank to other frequently used methods, we found that it performs well with small and large numbers of replicates, feature dependent variance between replicates, and variable regulation across features on simulation data and a recent two-color microarray spike-in dataset. The tests were then used to identify significant changes in the phosphoproteomes of cancer cells induced by the kinase inhibitors erlotinib and 3-MB-PP1 in two independently published mass spectrometry-based studies. MeanRank outperformed the other global rank-based methods applied in this study. Compared to the popular Significance Analysis of Microarrays and Linear Models for Microarray methods, MeanRank performed similar or better. Furthermore, MeanRank exhibits more consistent behavior regarding the degree of regulation and is robust against the choice of preprocessing methods. MeanRank does not require any imputation of missing values, is easy to understand, and yields results that are easy to interpret. The software implementing the algorithm is freely available for academic and commercial use.

Rank Dynamics

Science.gov (United States)

Gershenson, Carlos

Studies of rank distributions have been popular for decades, especially since the work of Zipf. For example, if we rank words of a given language by use frequency (most used word in English is 'the', rank 1; second most common word is 'of', rank 2), the distribution can be approximated roughly with a power law. The same applies for cities (most populated city in a country ranks first), earthquakes, metabolism, the Internet, and dozens of other phenomena. We recently proposed ``rank diversity'' to measure how ranks change in time, using the Google Books Ngram dataset. Studying six languages between 1800 and 2009, we found that the rank diversity curves of languages are universal, adjusted with a sigmoid on log-normal scale. We are studying several other datasets (sports, economies, social systems, urban systems, earthquakes, artificial life). Rank diversity seems to be universal, independently of the shape of the rank distribution. I will present our work in progress towards a general description of the features of rank change in time, along with simple models which reproduce it

The large sample size fallacy.

Science.gov (United States)

Lantz, Björn

2013-06-01

Significance in the statistical sense has little to do with significance in the common practical sense. Statistical significance is a necessary but not a sufficient condition for practical significance. Hence, results that are extremely statistically significant may be highly nonsignificant in practice. The degree of practical significance is generally determined by the size of the observed effect, not the p-value. The results of studies based on large samples are often characterized by extreme statistical significance despite small or even trivial effect sizes. Interpreting such results as significant in practice without further analysis is referred to as the large sample size fallacy in this article. The aim of this article is to explore the relevance of the large sample size fallacy in contemporary nursing research. Relatively few nursing articles display explicit measures of observed effect sizes or include a qualitative discussion of observed effect sizes. Statistical significance is often treated as an end in itself. Effect sizes should generally be calculated and presented along with p-values for statistically significant results, and observed effect sizes should be discussed qualitatively through direct and explicit comparisons with the effects in related literature. © 2012 Nordic College of Caring Science.

Ranking Queries on Uncertain Data

CERN Document Server

Hua, Ming

2011-01-01

Uncertain data is inherent in many important applications, such as environmental surveillance, market analysis, and quantitative economics research. Due to the importance of those applications and rapidly increasing amounts of uncertain data collected and accumulated, analyzing large collections of uncertain data has become an important task. Ranking queries (also known as top-k queries) are often natural and useful in analyzing uncertain data. Ranking Queries on Uncertain Data discusses the motivations/applications, challenging problems, the fundamental principles, and the evaluation algorith

Non-uniform sampling and wide range angular spectrum method

International Nuclear Information System (INIS)

Kim, Yong-Hae; Byun, Chun-Won; Oh, Himchan; Lee, JaeWon; Pi, Jae-Eun; Heon Kim, Gi; Lee, Myung-Lae; Ryu, Hojun; Chu, Hye-Yong; Hwang, Chi-Sun

2014-01-01

A novel method is proposed for simulating free space field propagation from a source plane to a destination plane that is applicable for both small and large propagation distances. The angular spectrum method (ASM) was widely used for simulating near field propagation, but it caused a numerical error when the propagation distance was large because of aliasing due to under sampling. Band limited ASM satisfied the Nyquist condition on sampling by limiting a bandwidth of a propagation field to avoid an aliasing error so that it could extend the applicable propagation distance of the ASM. However, the band limited ASM also made an error due to the decrease of an effective sampling number in a Fourier space when the propagation distance was large. In the proposed wide range ASM, we use a non-uniform sampling in a Fourier space to keep a constant effective sampling number even though the propagation distance is large. As a result, the wide range ASM can produce simulation results with high accuracy for both far and near field propagation. For non-paraxial wave propagation, we applied the wide range ASM to a shifted destination plane as well. (paper)

Patient Characteristics and Comorbidities Influence Walking Distances in Symptomatic Peripheral Arterial Disease: A Large One-Year Physiotherapy Cohort Study.

Science.gov (United States)

Dörenkamp, Sarah; Mesters, Ilse; de Bie, Rob; Teijink, Joep; van Breukelen, Gerard

2016-01-01

The aim of this study is to investigate the association between age, gender, body-mass index, smoking behavior, orthopedic comorbidity, neurologic comorbidity, cardiac comorbidity, vascular comorbidity, pulmonic comorbidity, internal comorbidity and Initial Claudication Distance during and after Supervised Exercise Therapy at 1, 3, 6 and 12 months in a large sample of patients with Intermittent Claudication. Data was prospectively collected in standard physiotherapy care. Patients received Supervised Exercise Therapy according to the guideline Intermittent Claudication of the Royal Dutch Society for Physiotherapy. Three-level mixed linear regression analysis was carried out to analyze the association between patient characteristics, comorbidities and Initial Claudication Distance at 1, 3, 6 and 12 months. Data from 2995 patients was analyzed. Results showed that being female, advanced age and a high body-mass index were associated with lower Initial Claudication Distance at all-time points (p = 0.000). Besides, a negative association between cardiac comorbidity and Initial Claudication Distance was revealed (p = 0.011). The interaction time by age, time by body-mass index and time by vascular comorbidity were significantly associated with Initial Claudication Distance (p≤ 0.05). Per year increase in age (range: 33-93 years), the reduction in Initial Claudication Distance was 8m after 12 months of Supervised Exercise Therapy. One unit increase in body-mass index (range: 16-44 kg/m2) led to 10 m less improvement in Initial Claudication Distance after 12 months and for vascular comorbidity the reduction in improvement was 85 m after 12 months. This study reveals that females, patients at advanced age, patients with a high body-mass index and cardiac comorbidity are more likely to show less improvement in Initial Claudication Distances (ICD) after 1, 3, 6 and 12 months of Supervised Exercise Therapy. Further research should elucidate treatment adaptations that

Very Large Distance Education Systems: The Case of China. ZIFF Papiere 94.

Science.gov (United States)

Keegan, Desmond

One answer to the magnitude of the world education crisis is the provision of very large education systems, capable of enrolling 100,000 students or more. The largest distance system is the Dianda or Chinese Radio and Television University (CRTVU) system. Dianda is best described as a network of one central open university that does not enroll…

Design of a fuzzy ranking system for admission processes in higher ...

African Journals Online (AJOL)

specific knowledge, as well as the knowledge and analytical skills of one or more human experts and reasons with ... In this paper we introduced fuzzy harming distance function into candidates ranking and implemented it with Java Netbean IDE 6.0.

PageRank, HITS and a unified framework for link analysis

Energy Technology Data Exchange (ETDEWEB)

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

2001-10-01

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

A least square support vector machine-based approach for contingency classification and ranking in a large power system

Directory of Open Access Journals (Sweden)

Bhanu Pratap Soni

2016-12-01

Full Text Available This paper proposes an effective supervised learning approach for static security assessment of a large power system. Supervised learning approach employs least square support vector machine (LS-SVM to rank the contingencies and predict the system severity level. The severity of the contingency is measured by two scalar performance indices (PIs: line MVA performance index (PIMVA and Voltage-reactive power performance index (PIVQ. SVM works in two steps. Step I is the estimation of both standard indices (PIMVA and PIVQ that is carried out under different operating scenarios and Step II contingency ranking is carried out based on the values of PIs. The effectiveness of the proposed methodology is demonstrated on IEEE 39-bus (New England system. The approach can be beneficial tool which is less time consuming and accurate security assessment and contingency analysis at energy management center.

A LDA-based approach to promoting ranking diversity for genomics information retrieval.

Science.gov (United States)

Chen, Yan; Yin, Xiaoshi; Li, Zhoujun; Hu, Xiaohua; Huang, Jimmy Xiangji

2012-06-11

In the biomedical domain, there are immense data and tremendous increase of genomics and biomedical relevant publications. The wealth of information has led to an increasing amount of interest in and need for applying information retrieval techniques to access the scientific literature in genomics and related biomedical disciplines. In many cases, the desired information of a query asked by biologists is a list of a certain type of entities covering different aspects that are related to the question, such as cells, genes, diseases, proteins, mutations, etc. Hence, it is important of a biomedical IR system to be able to provide relevant and diverse answers to fulfill biologists' information needs. However traditional IR model only concerns with the relevance between retrieved documents and user query, but does not take redundancy between retrieved documents into account. This will lead to high redundancy and low diversity in the retrieval ranked lists. In this paper, we propose an approach which employs a topic generative model called Latent Dirichlet Allocation (LDA) to promoting ranking diversity for biomedical information retrieval. Different from other approaches or models which consider aspects on word level, our approach assumes that aspects should be identified by the topics of retrieved documents. We present LDA model to discover topic distribution of retrieval passages and word distribution of each topic dimension, and then re-rank retrieval results with topic distribution similarity between passages based on N-size slide window. We perform our approach on TREC 2007 Genomics collection and two distinctive IR baseline runs, which can achieve 8% improvement over the highest Aspect MAP reported in TREC 2007 Genomics track. The proposed method is the first study of adopting topic model to genomics information retrieval, and demonstrates its effectiveness in promoting ranking diversity as well as in improving relevance of ranked lists of genomics search

Superwind Outflows in Seyfert Galaxies? : Large-Scale Radio Maps of an Edge-On Sample

Science.gov (United States)

Colbert, E.; Gallimore, J.; Baum, S.; O'Dea, C.

1995-03-01

Large-scale galactic winds (superwinds) are commonly found flowing out of the nuclear region of ultraluminous infrared and powerful starburst galaxies. Stellar winds and supernovae from the nuclear starburst provide the energy to drive these superwinds. The outflowing gas escapes along the rotation axis, sweeping up and shock-heating clouds in the halo, which produces optical line emission, radio synchrotron emission, and X-rays. These features can most easily be studied in edge-on systems, so that the wind emission is not confused by that from the disk. We have begun a systematic search for superwind outflows in Seyfert galaxies. In an earlier optical emission-line survey, we found extended minor axis emission and/or double-peaked emission line profiles in >~30% of the sample objects. We present here large-scale (6cm VLA C-config) radio maps of 11 edge-on Seyfert galaxies, selected (without bias) from a distance-limited sample of 23 edge-on Seyferts. These data have been used to estimate the frequency of occurrence of superwinds. Preliminary results indicate that four (36%) of the 11 objects observed and six (26%) of the 23 objects in the distance-limited sample have extended radio emission oriented perpendicular to the galaxy disk. This emission may be produced by a galactic wind blowing out of the disk. Two (NGC 2992 and NGC 5506) of the nine objects for which we have both radio and optical data show good evidence for a galactic wind in both datasets. We suggest that galactic winds occur in >~30% of all Seyferts. A goal of this work is to find a diagnostic that can be used to distinguish between large-scale outflows that are driven by starbursts and those that are driven by an AGN. The presence of starburst-driven superwinds in Seyferts, if established, would have important implications for the connection between starburst galaxies and AGN.

Implementing Distance Education: Issues Impacting Administration

Science.gov (United States)

Schauer, Jolene; Rockwell, S. Kay; Fritz, Susan M.; Marx, Dave B.

2005-01-01

Through a modified Delphi study, an expert panel identified 62 concepts organized in eight issue categories that impact administrative decisions as higher education institutions commit to implementing distance education courses and programs. Using a mail survey, 62 department chairs in Colleges of Agriculture in Land-Grant Universities ranked the…

Ranking independent timber investments by alternative investment criteria

Science.gov (United States)

Thomas J. Mills; Gary E. Dixon

1982-01-01

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

Nonnegative Matrix Factorization with Rank Regularization and Hard Constraint.

Science.gov (United States)

Shang, Ronghua; Liu, Chiyang; Meng, Yang; Jiao, Licheng; Stolkin, Rustam

2017-09-01

Nonnegative matrix factorization (NMF) is well known to be an effective tool for dimensionality reduction in problems involving big data. For this reason, it frequently appears in many areas of scientific and engineering literature. This letter proposes a novel semisupervised NMF algorithm for overcoming a variety of problems associated with NMF algorithms, including poor use of prior information, negative impact on manifold structure of the sparse constraint, and inaccurate graph construction. Our proposed algorithm, nonnegative matrix factorization with rank regularization and hard constraint (NMFRC), incorporates label information into data representation as a hard constraint, which makes full use of prior information. NMFRC also measures pairwise similarity according to geodesic distance rather than Euclidean distance. This results in more accurate measurement of pairwise relationships, resulting in more effective manifold information. Furthermore, NMFRC adopts rank constraint instead of norm constraints for regularization to balance the sparseness and smoothness of data. In this way, the new data representation is more representative and has better interpretability. Experiments on real data sets suggest that NMFRC outperforms four other state-of-the-art algorithms in terms of clustering accuracy.

Development of digital gamma-activation autoradiography for analysis of samples of large area

International Nuclear Information System (INIS)

Kolotov, V.P.; Grozdov, D.S.; Dogadkin, N.N.; Korobkov, V.I.

2011-01-01

Gamma-activation autoradiography is a prospective method for screening detection of inclusions of precious metals in geochemical samples. Its characteristics allow analysis of thin sections of large size (tens of cm2), that favourably distinguishes it among the other methods for local analysis. At the same time, the activating field of the accelerator bremsstrahlung, displays a sharp intensity decrease relative to the distance along the axis. A method for activation dose ''equalization'' during irradiation of the large size thin sections has been developed. The method is based on the usage of a hardware-software system. This includes a device for moving the sample during the irradiation, a program for computer modelling of the acquired activating dose for the chosen kinematics of the sample movement and a program for pixel-by pixel correction of the autoradiographic images. For detection of inclusions of precious metals, a method for analysis of the acquired dose dynamics during sample decay has been developed. The method is based on the software processing pixel by pixel a time-series of coaxial autoradiographic images and generation of the secondary meta-images allowing interpretation regarding the presence of interesting inclusions based on half-lives. The method is tested for analysis of copper-nickel polymetallic ores. The developed solutions considerably expand the possible applications of digital gamma-activation autoradiography. (orig.)

Development of digital gamma-activation autoradiography for analysis of samples of large area

Energy Technology Data Exchange (ETDEWEB)

Kolotov, V.P.; Grozdov, D.S.; Dogadkin, N.N.; Korobkov, V.I. [Russian Academy of Sciences, Moscow (Russian Federation). Vernadsky Inst. of Geochemistry and Analytical Chemistry

2011-07-01

Gamma-activation autoradiography is a prospective method for screening detection of inclusions of precious metals in geochemical samples. Its characteristics allow analysis of thin sections of large size (tens of cm2), that favourably distinguishes it among the other methods for local analysis. At the same time, the activating field of the accelerator bremsstrahlung, displays a sharp intensity decrease relative to the distance along the axis. A method for activation dose ''equalization'' during irradiation of the large size thin sections has been developed. The method is based on the usage of a hardware-software system. This includes a device for moving the sample during the irradiation, a program for computer modelling of the acquired activating dose for the chosen kinematics of the sample movement and a program for pixel-by pixel correction of the autoradiographic images. For detection of inclusions of precious metals, a method for analysis of the acquired dose dynamics during sample decay has been developed. The method is based on the software processing pixel by pixel a time-series of coaxial autoradiographic images and generation of the secondary meta-images allowing interpretation regarding the presence of interesting inclusions based on half-lives. The method is tested for analysis of copper-nickel polymetallic ores. The developed solutions considerably expand the possible applications of digital gamma-activation autoradiography. (orig.)

Constant-Distance Mode Nanospray Desorption Electrospray Ionization Mass Spectrometry Imaging of Biological Samples with Complex Topography

Energy Technology Data Exchange (ETDEWEB)

Nguyen, Son N.; Liyu, Andrey V.; Chu, Rosalie K.; Anderton, Christopher R.; Laskin, Julia

2017-01-17

A new approach for constant distance mode mass spectrometry imaging of biological samples using nanospray desorption electrospray ionization (nano-DESI MSI) was developed by integrating a shear-force probe with nano-DESI probe. The technical concept and basic instrumental setup as well as general operation of the system are described. Mechanical dampening of resonant oscillations due to the presence of shear forces between the probe and the sample surface enables constant-distance imaging mode via a computer controlled closed feedback loop. The capability of simultaneous chemical and topographic imaging of complex biological samples is demonstrated using living Bacillus Subtilis ATCC 49760 colonies on agar plates. The constant-distance mode nano-DESI MSI enabled imaging of many metabolites including non-ribosomal peptides (surfactin, plipastatin and iturin) and iron-bound heme on the surface of living bacterial colonies ranging in diameter from 10 mm to 13 mm with height variations of up to 0.8 mm above the agar plate. Co-registration of ion images to topographic images provided higher-contrast images. Constant-mode nano-DESI MSI is ideally suited for imaging biological samples of complex topography in their native state.

When the Web meets the cell: using personalized PageRank for analyzing protein interaction networks.

Science.gov (United States)

Iván, Gábor; Grolmusz, Vince

2011-02-01

Enormous and constantly increasing quantity of biological information is represented in metabolic and in protein interaction network databases. Most of these data are freely accessible through large public depositories. The robust analysis of these resources needs novel technologies, being developed today. Here we demonstrate a technique, originating from the PageRank computation for the World Wide Web, for analyzing large interaction networks. The method is fast, scalable and robust, and its capabilities are demonstrated on metabolic network data of the tuberculosis bacterium and the proteomics analysis of the blood of melanoma patients. The Perl script for computing the personalized PageRank in protein networks is available for non-profit research applications (together with sample input files) at the address: http://uratim.com/pp.zip.

Sampling Large Graphs for Anticipatory Analytics

Science.gov (United States)

2015-05-15

low. C. Random Area Sampling Random area sampling [8] is a “ snowball ” sampling method in which a set of random seed vertices are selected and areas... Sampling Large Graphs for Anticipatory Analytics Lauren Edwards, Luke Johnson, Maja Milosavljevic, Vijay Gadepally, Benjamin A. Miller Lincoln...systems, greater human-in-the-loop involvement, or through complex algorithms. We are investigating the use of sampling to mitigate these challenges

An Efficient Monte Carlo Approach to Compute PageRank for Large Graphs on a Single PC

Directory of Open Access Journals (Sweden)

Sonobe Tomohiro

2016-03-01

Full Text Available This paper describes a novel Monte Carlo based random walk to compute PageRanks of nodes in a large graph on a single PC. The target graphs of this paper are ones whose size is larger than the physical memory. In such an environment, memory management is a difficult task for simulating the random walk among the nodes. We propose a novel method that partitions the graph into subgraphs in order to make them fit into the physical memory, and conducts the random walk for each subgraph. By evaluating the walks lazily, we can conduct the walks only in a subgraph and approximate the random walk by rotating the subgraphs. In computational experiments, the proposed method exhibits good performance for existing large graphs with several passes of the graph data.

It's all relative: ranking the diversity of aquatic bacterial communities.

Science.gov (United States)

Shaw, Allison K; Halpern, Aaron L; Beeson, Karen; Tran, Bao; Venter, J Craig; Martiny, Jennifer B H

2008-09-01

The study of microbial diversity patterns is hampered by the enormous diversity of microbial communities and the lack of resources to sample them exhaustively. For many questions about richness and evenness, however, one only needs to know the relative order of diversity among samples rather than total diversity. We used 16S libraries from the Global Ocean Survey to investigate the ability of 10 diversity statistics (including rarefaction, non-parametric, parametric, curve extrapolation and diversity indices) to assess the relative diversity of six aquatic bacterial communities. Overall, we found that the statistics yielded remarkably similar rankings of the samples for a given sequence similarity cut-off. This correspondence, despite the different underlying assumptions of the statistics, suggests that diversity statistics are a useful tool for ranking samples of microbial diversity. In addition, sequence similarity cut-off influenced the diversity ranking of the samples, demonstrating that diversity statistics can also be used to detect differences in phylogenetic structure among microbial communities. Finally, a subsampling analysis suggests that further sequencing from these particular clone libraries would not have substantially changed the richness rankings of the samples.

Imaging a Large Sample with Selective Plane Illumination Microscopy Based on Multiple Fluorescent Microsphere Tracking

Science.gov (United States)

Ryu, Inkeon; Kim, Daekeun

2018-04-01

A typical selective plane illumination microscopy (SPIM) image size is basically limited by the field of view, which is a characteristic of the objective lens. If an image larger than the imaging area of the sample is to be obtained, image stitching, which combines step-scanned images into a single panoramic image, is required. However, accurately registering the step-scanned images is very difficult because the SPIM system uses a customized sample mount where uncertainties for the translational and the rotational motions exist. In this paper, an image registration technique based on multiple fluorescent microsphere tracking is proposed in the view of quantifying the constellations and measuring the distances between at least two fluorescent microspheres embedded in the sample. Image stitching results are demonstrated for optically cleared large tissue with various staining methods. Compensation for the effect of the sample rotation that occurs during the translational motion in the sample mount is also discussed.

Hyper-local, directions-based ranking of places

DEFF Research Database (Denmark)

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

2011-01-01

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

Current correlators in QCD: Operator product expansion versus large distance dynamics

International Nuclear Information System (INIS)

Shevchenko, V.I.; Simonov, Yu.A.

2004-01-01

We analyze the structure of current-current correlators in coordinate space in the large N c limit when the corresponding spectral density takes the form of an infinite sum over hadron poles. The latter are computed in the QCD string model with quarks at the ends, including the lowest states, for all channels. The corresponding correlators demonstrate reasonable qualitative agreement with the lattice data without any additional fits. Different issues concerning the structure of the short-distance operator product expansion are discussed

Texture Repairing by Unified Low Rank Optimization

Institute of Scientific and Technical Information of China (English)

Xiao Liang; Xiang Ren; Zhengdong Zhang; Yi Ma

2016-01-01

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

Sparse Contextual Activation for Efficient Visual Re-Ranking.

Science.gov (United States)

Bai, Song; Bai, Xiang

2016-03-01

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

Limitations to mapping habitat-use areas in changing landscapes using the Mahalanobis distance statistic

Science.gov (United States)

Knick, Steven T.; Rotenberry, J.T.

1998-01-01

We tested the potential of a GIS mapping technique, using a resource selection model developed for black-tailed jackrabbits (Lepus californicus) and based on the Mahalanobis distance statistic, to track changes in shrubsteppe habitats in southwestern Idaho. If successful, the technique could be used to predict animal use areas, or those undergoing change, in different regions from the same selection function and variables without additional sampling. We determined the multivariate mean vector of 7 GIS variables that described habitats used by jackrabbits. We then ranked the similarity of all cells in the GIS coverage from their Mahalanobis distance to the mean habitat vector. The resulting map accurately depicted areas where we sighted jackrabbits on verification surveys. We then simulated an increase in shrublands (which are important habitats). Contrary to expectation, the new configurations were classified as lower similarity relative to the original mean habitat vector. Because the selection function is based on a unimodal mean, any deviation, even if biologically positive, creates larger Malanobis distances and lower similarity values. We recommend the Mahalanobis distance technique for mapping animal use areas when animals are distributed optimally, the landscape is well-sampled to determine the mean habitat vector, and distributions of the habitat variables does not change.

Bayesian Plackett-Luce Mixture Models for Partially Ranked Data.

Science.gov (United States)

Mollica, Cristina; Tardella, Luca

2017-06-01

The elicitation of an ordinal judgment on multiple alternatives is often required in many psychological and behavioral experiments to investigate preference/choice orientation of a specific population. The Plackett-Luce model is one of the most popular and frequently applied parametric distributions to analyze rankings of a finite set of items. The present work introduces a Bayesian finite mixture of Plackett-Luce models to account for unobserved sample heterogeneity of partially ranked data. We describe an efficient way to incorporate the latent group structure in the data augmentation approach and the derivation of existing maximum likelihood procedures as special instances of the proposed Bayesian method. Inference can be conducted with the combination of the Expectation-Maximization algorithm for maximum a posteriori estimation and the Gibbs sampling iterative procedure. We additionally investigate several Bayesian criteria for selecting the optimal mixture configuration and describe diagnostic tools for assessing the fitness of ranking distributions conditionally and unconditionally on the number of ranked items. The utility of the novel Bayesian parametric Plackett-Luce mixture for characterizing sample heterogeneity is illustrated with several applications to simulated and real preference ranked data. We compare our method with the frequentist approach and a Bayesian nonparametric mixture model both assuming the Plackett-Luce model as a mixture component. Our analysis on real datasets reveals the importance of an accurate diagnostic check for an appropriate in-depth understanding of the heterogenous nature of the partial ranking data.

Using incomplete citation data for MEDLINE results ranking.

Science.gov (United States)

Herskovic, Jorge R; Bernstam, Elmer V

2005-01-01

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

Revised Distances to 21 Supernova Remnants

Science.gov (United States)

Ranasinghe, S.; Leahy, D. A.

2018-05-01

We carry out a comprehensive study of H I 21 cm line observations and 13CO line observations of 21 supernova remnants (SNRs). The aim of the study is to search for H I absorption features to obtain kinematic distances in a consistent manner. The 21 SNRs are in the region of sky covered by the Very Large Array Galactic Plane Survey (H I 21 cm observations) and Galactic Ring Survey (13CO line observations). We obtain revised distances for 10 SNRs based on new evidence in the H I and 13CO observations. We revise distances for the other 11 SNRs based on an updated rotation curve and new error analysis. The mean change in distance for the 21 SNRs is ≃25%, i.e., a change of 1.5 kpc compared to a mean distance for the sample of 6.4 kpc. This has a significant impact on interpretation of the physical state of these SNRs. For example, using a Sedov model, age and explosion energy scale as the square of distance, and inferred ISM density scales as distance.

A Rank Test on Equality of Population Medians

OpenAIRE

Pooi Ah Hin

2012-01-01

The Kruskal-Wallis test is a non-parametric test for the equality of K population medians. The test statistic involved is a measure of the overall closeness of the K average ranks in the individual samples to the average rank in the combined sample. The resulting acceptance region of the test however may not be the smallest region with the required acceptance probability under the null hypothesis. Presently an alternative acceptance region is constructed such that it has the smallest size, ap...

Grooming-at-a-distance by exchanging calls in non-human primates.

Science.gov (United States)

Arlet, Malgorzata; Jubin, Ronan; Masataka, Nobuo; Lemasson, Alban

2015-10-01

The 'social bonding hypothesis' predicts that, in large social groups, functions of gestural grooming should be partially transferred to vocal interactions. Hence, vocal exchanges would have evolved in primates to play the role of grooming-at-a-distance in order to facilitate the maintenance of social cohesion. However, there are few empirical studies testing this hypothesis. To address this point, we compared the rate of contact call exchanges between females in two captive groups of Japanese macaques as a function of female age, dominance rank, genetic relatedness and social affinity measured by spatial proximity and grooming interactions. We found a significant positive relationship between the time spent on grooming by two females and the frequency with which they exchanged calls. Our results conform to the predictions of the social bonding hypothesis, i.e. vocal exchanges can be interpreted as grooming-at-a-distance. © 2015 The Author(s).

Assessing distances and consistency of kinematics in Gaia/TGAS

Science.gov (United States)

Schönrich, Ralph; Aumer, Michael

2017-12-01

We apply the statistical methods by Schönrich, Binney & Asplund to assess the quality of distances and kinematics in the Radial Velocity Experiment (RAVE)-Tycho-Gaia Astrometric Solution (TGAS) and Large Sky Area Multiobject Fiber Spectroscopic Telescope (LAMOST)-TGAS samples of Solar neighbourhood stars. These methods yield a nominal distance accuracy of 1-2 per cent. Other than common tests on parallax accuracy, they directly test distance estimations including the effects of distance priors. We show how to construct these priors including the survey selection functions (SSFs) directly from the data. We demonstrate that neglecting the SSFs causes severe distance biases. Due to the decline of the SSFs in distance, the simple 1/parallax estimate only mildly underestimates distances. We test the accuracy of measured line-of-sight velocities (vlos) by binning the samples in the nominal vlos uncertainties. We find: (i) the LAMOST vlos have a ∼-5 km s-1 offset; (ii) the average LAMOST measurement error for vlos is ∼7 km s-1, significantly smaller than, and nearly uncorrelated with the nominal LAMOST estimates. The RAVE sample shows either a moderate distance underestimate, or an unaccounted source of vlos dispersion (e∥) from measurement errors and binary stars. For a subsample of suspected binary stars in RAVE, our methods indicate significant distance underestimates. Separating a sample in metallicity or kinematics to select thick-disc/halo stars, discriminates between distance bias and e∥. For LAMOST, this separation yields consistency with pure vlos measurement errors. We find an anomaly near longitude l ∼ (300 ± 60)° and distance s ∼ (0.32 ± 0.03) kpc on both sides of the galactic plane, which could be explained by either a localized distance error or a breathing mode.

A tilting approach to ranking influence

KAUST Repository

Genton, Marc G.

2014-12-01

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

LARGE MAGELLANIC CLOUD DISTANCE AND STRUCTURE FROM NEAR-INFRARED RED CLUMP OBSERVATIONS

International Nuclear Information System (INIS)

Koerwer, Joel F.

2009-01-01

We have applied the Infrared Survey Facility Magellanic Clouds Point-Source Catalog to the mapping of the red clump (RC) distance modulus across the Large Magellanic Cloud (LMC). Using the J- (1.25 μm) and H- (1.63 μm) band data to derive a reddening free luminosity function and a theoretical RC absolute magnitude from stellar evolution libraries, we estimate a distance modulus to the LMC of μ = 18.54 ± 0.06. The best fitting plane inclination, i, and the position angle of the line of nodes, φ, have little dependence on the assumed RC absolute magnitude; we find i = 23. 0 5 ± 0. 0 4 and φ = 154. 0 6 ± 1. 0 2. It was also noted that many fields included a significant asymptotic giant branch bump population that must be accounted for.

Large Magellanic Cloud Distance and Structure from Near-Infrared Red Clump Observations

Science.gov (United States)

Koerwer, Joel F.

2009-07-01

We have applied the Infrared Survey Facility Magellanic Clouds Point-Source Catalog to the mapping of the red clump (RC) distance modulus across the Large Magellanic Cloud (LMC). Using the J- (1.25 μm) and H- (1.63 μm) band data to derive a reddening free luminosity function and a theoretical RC absolute magnitude from stellar evolution libraries, we estimate a distance modulus to the LMC of μ = 18.54 ± 0.06. The best fitting plane inclination, i, and the position angle of the line of nodes, phi, have little dependence on the assumed RC absolute magnitude; we find i = 23fdg5 ± 0fdg4 and phi = 154fdg6 ± 1fdg2. It was also noted that many fields included a significant asymptotic giant branch bump population that must be accounted for.

PageRank and rank-reversal dependence on the damping factor

Science.gov (United States)

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

2012-12-01

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

PageRank and rank-reversal dependence on the damping factor.

Science.gov (United States)

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

2012-12-01

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

Large distance modification of Newtonian potential and structure formation in universe

Science.gov (United States)

Hameeda, Mir; Upadhyay, Sudhaker; Faizal, Mir; Ali, Ahmed F.; Pourhassan, Behnam

2018-03-01

In this paper, we study the effects of super-light brane world perturbative modes on structure formation in our universe. As these modes modify the large distance behavior of Newtonian potential, they effect the clustering of a system of galaxies. So, we explicitly calculate the clustering of galaxies interacting through such a modified Newtonian potential. We use a suitable approximation for analyzing this system of galaxies, and discuss the validity of such approximations. We observe that such corrections also modify the virial theorem for such a system of galaxies.

Consistent ranking of volatility models

DEFF Research Database (Denmark)

Hansen, Peter Reinhard; Lunde, Asger

2006-01-01

We show that the empirical ranking of volatility models can be inconsistent for the true ranking if the evaluation is based on a proxy for the population measure of volatility. For example, the substitution of a squared return for the conditional variance in the evaluation of ARCH-type models can...... variance in out-of-sample evaluations rather than the squared return. We derive the theoretical results in a general framework that is not specific to the comparison of volatility models. Similar problems can arise in comparisons of forecasting models whenever the predicted variable is a latent variable....

Reference interval for the disc-macula distance to disc diameter ratio in a large population of healthy Japanese adults: A prospective, observational study.

Science.gov (United States)

Sato, Ken-Ichi

2017-04-01

This study presents the calculated reference interval for the disc-to-macula distance to disc diameter ratio (DM:DD) based on a large population of healthy Japanese adults.A total of 308 consecutive, healthy Japanese adults were examined in this prospective observational study. Eighteen subjects were also excluded because of poor quality of the fundus photograph of one or both eyes; 290 (161 men and 129 women) were included in this study. For each subject, a color fundus photograph of one eye, either the right or left, was randomly selected and used for analysis. On the photograph, the distances between the fovea and the nearest temporal margin of the optic disc (Dft), and the two kinds of disc diameters (D1 and D2), which bisected at right angles and one of which was directed to the fovea (D1), were measured. DM:DD was estimated using the formula: (2Dft + D1)/(D1 + D2).The mean ± standard deviation of DM:DD was 2.91 ± 0.49 for men and 2.96 ± 0.54 for women; there was no sex difference (P = .78, Mann-Whitney U test). Also, almost no relationship was found between DM:DD and age (ρ = -.12, P = .04, Spearman's rank correlation coefficient). The data did not fit a normal distribution (P < .001, Kolmogorov-Smirnov test). The estimated reference interval for DM:DD corresponding to the 2.5th and 97.5th percentiles was 2.12 to 4.18.Using a nonparametric approach, the reference interval for DM:DD of a large population of healthy Japanese adults was calculated to be 2.12 to 4.18, regardless of age or sex.

Reachable Distance Space: Efficient Sampling-Based Planning for Spatially Constrained Systems

KAUST Repository

Xinyu Tang,

2010-01-25

Motion planning for spatially constrained robots is difficult due to additional constraints placed on the robot, such as closure constraints for closed chains or requirements on end-effector placement for articulated linkages. It is usually computationally too expensive to apply sampling-based planners to these problems since it is difficult to generate valid configurations. We overcome this challenge by redefining the robot\\'s degrees of freedom and constraints into a new set of parameters, called reachable distance space (RD-space), in which all configurations lie in the set of constraint-satisfying subspaces. This enables us to directly sample the constrained subspaces with complexity linear in the number of the robot\\'s degrees of freedom. In addition to supporting efficient sampling of configurations, we show that the RD-space formulation naturally supports planning and, in particular, we design a local planner suitable for use by sampling-based planners. We demonstrate the effectiveness and efficiency of our approach for several systems including closed chain planning with multiple loops, restricted end-effector sampling, and on-line planning for drawing/sculpting. We can sample single-loop closed chain systems with 1,000 links in time comparable to open chain sampling, and we can generate samples for 1,000-link multi-loop systems of varying topologies in less than a second. © 2010 The Author(s).

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

Science.gov (United States)

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

2014-04-01

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

Global sensitivity analysis using low-rank tensor approximations

International Nuclear Information System (INIS)

Konakli, Katerina; Sudret, Bruno

2016-01-01

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

Coming close to the ideal alternative: The concordant-ranks strategy

Directory of Open Access Journals (Sweden)

Neda Kerimi

2011-04-01

Full Text Available We present the Concordant-Ranks (CR strategy that decision makers use to quickly find an alternative that is proximate to an ideal alternative in a multi-attribute decision space. CR implies that decision makers prefer alternatives that exhibit concordant ranks between attribute values and attribute weights. We show that, in situations where the alternatives are equal in multi-attribute utility (MAU, minimization of the weighted Euclidean distance (WED to an ideal alternative implies the choice of a CR alternative. In two experiments, participants chose among, as well as evaluated, alternatives that were constructed to be equal in MAU. In Experiment 1, four alternatives were designed in such a way that the choice of each alternative would be consistent with one particular choice strategy, one of which was the CR strategy. In Experiment 2, participants were presented with a CR alternative and a number of arbitrary alternatives. In both experiments, participants tended to choose the CR alternative. The CR alternative was on average evaluated as more attractive than other alternatives. In addition, measures of WED, between given alternatives and the ideal alternative, by and large agreed with the preference order for choices and attractiveness evaluations of the different types of alternatives. These findings indicate that both choices and attractiveness evaluations are guided by proximity of alternatives to an ideal alternative.

Cointegration rank testing under conditional heteroskedasticity

DEFF Research Database (Denmark)

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

2010-01-01

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

Model assessment using a multi-metric ranking technique

Science.gov (United States)

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

2017-12-01

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

Advanced Neutron Source Reactor (ANSR) phenomena identification and ranking (PIR) for large break loss of coolant accidents (LBLOCA)

International Nuclear Information System (INIS)

Ruggles, A.E.; Cheng, L.Y.; Dimenna, R.A.; Griffith, P.; Wilson, G.E.

1994-06-01

A team of experts in reactor analysis conducted a phenomena identification and ranking (PIR) exercise for a large break loss-of-coolant accident (LBLOCA) in the Advanced Neutron source Reactor (ANSR). The LBLOCA transient is broken into two separate parts for the PIR exercise. The first part considers the initial depressurization of the system that follows the opening of the break. The second part of the transient includes long-term decay heat removal after the reactor is shut down and the system is depressurized. A PIR is developed for each part of the LBLOCA. The ranking results are reviewed to establish if models in the RELAP5-MOD3 thermalhydraulic code are adequate for use in ANSR LBLOCA simulations. Deficiencies in the RELAP5-MOD3 code are identified and existing data or models are recommended to improve the code for this application. Experiments were also suggested to establish models for situations judged to be beyond current knowledge. The applicability of the ANSR PIR results is reviewed for the entire set of transients important to the ANSR safety analysis

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

Science.gov (United States)

Shams, Bita; Haratizadeh, Saman

2016-09-01

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

Ten year rank-order stability of personality traits and disorders in a clinical sample

Science.gov (United States)

Hopwood, Christopher J.; Morey, Leslie C.; Donnellan, M. Brent; Samuel, Douglas B.; Grilo, Carlos M.; McGlashan, Thomas H.; Shea, M. Tracie; Zanarini, Mary C.; Gunderson, John G.; Skodol, Andrew E.

2012-01-01

Objective To compare the 10-year retest stability of normal traits, pathological traits, and personality disorder dimensions in a clinical sample. Method Ten-year rank order stability estimates for the Revised NEO Personality Inventory, Schedule for Nonadaptive and Adaptive Personality, and Diagnostic Interview for DSM-IV Personality Disorders were evaluated before and after correcting for test-retest dependability and internal consistency in a clinical sample (N = 266). Results Dependability corrected stability estimates were generally in the range of .60–.90 for traits and .25–.65 for personality disorders. Conclusions The relatively lower stability of personality disorder symptoms may indicate important differences between pathological behaviors and relatively more stable self-attributed traits and imply that a full understanding of personality and personality pathology needs to take both traits and symptoms into account. The Five-Factor Theory distinction between basic tendencies and characteristic adaptations provides a theoretical framework for the separation of traits and disorders in terms of stability in which traits reflect basic tendencies that are stable and pervasive across situations, whereas personality disorder symptoms reflect characteristic maladaptations that are a function of both basic tendencies and environmental dynamics. PMID:22812532

Low-Rank Sparse Coding for Image Classification

KAUST Repository

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

2013-01-01

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

Low-Rank Sparse Coding for Image Classification

KAUST Repository

Zhang, Tianzhu

2013-12-01

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

The Euclidean distance degree of an algebraic variety

NARCIS (Netherlands)

Draisma, J.; Horobet, E.; Ottaviani, G.; Sturmfels, B.; Thomas, R.R.

2013-01-01

The nearest point map of a real algebraic variety with respect to Euclidean distance is an algebraic function. For instance, for varieties of low rank matrices, the Eckart-Young Theorem states that this map is given by the singular value decomposition. This article develops a theory of such nearest

The Euclidean distance degree of an algebraic variety

NARCIS (Netherlands)

Draisma, J.; Horobet, E.; Ottaviani, G.; Sturmfels, B.; Thomas, R.R.

The nearest point map of a real algebraic variety with respect to Euclidean distance is an algebraic function. For instance, for varieties of low-rank matrices, the Eckart–Young Theorem states that this map is given by the singular value decomposition. This article develops a theory of such nearest

Comparing two distance measures in the spatial mapping of food deserts: The case of Petržalka, Slovakia

Directory of Open Access Journals (Sweden)

Bilková Kristína

2017-06-01

Full Text Available Over the last twenty years or so, researchers’ attention to the issue of food deserts has increased in the geographical literature. Accessibility to large-scale retail units is one of the essential and frequently-used indicators leading to the identification and mapping of food deserts. Numerous accessibility measures of various types are available for this purpose. Euclidean distance and street network distance rank among the most frequently-used approaches, although they may lead to slightly different results. The aim of this paper is to compare various approaches to the accessibility to food stores and to assess the differences in the results gained by these methods. Accessibility was measured for residential block centroids, with applications of various accessibility measures in a GIS environment. The results suggest a strong correspondence between Euclidean distance and a little more accurate street network distance approach, applied in the case of the urban environment of Bratislava-Petržalka, Slovakia.

Ranking nodes in growing networks: When PageRank fails.

Science.gov (United States)

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

2015-11-10

PageRank is arguably the most popular ranking algorithm which is being applied in real systems ranging from information to biological and infrastructure networks. Despite its outstanding popularity and broad use in different areas of science, the relation between the algorithm's efficacy and properties of the network on which it acts has not yet been fully understood. We study here PageRank's performance on a network model supported by real data, and show that realistic temporal effects make PageRank fail in individuating the most valuable nodes for a broad range of model parameters. Results on real data are in qualitative agreement with our model-based findings. This failure of PageRank reveals that the static approach to information filtering is inappropriate for a broad class of growing systems, and suggest that time-dependent algorithms that are based on the temporal linking patterns of these systems are needed to better rank the nodes.

Role Overload, Role Self Distance, Role Stagnation as Determinants of Job Satisfaction and Turnover Intention in Banking Sector

OpenAIRE

Kunte, Monica; Gupta, Priya; Bhattacharya, Sonali; Neelam, Netra

2017-01-01

Purpose: This study examined the relationship of the organizational role stress: Role overload, role self-distance, and role stagnation with job satisfaction and turnover intention with a sample of banking employees in India. Methodology: In this research, we used the RODS scale developed by Prohit and Pareek (2010) for measuring occupational role scale. The reliability of the scale came out to be 0.71. Findings: The majority of employees of all ranks, in both private and public sector banks,...

Reduced Rank Regression

DEFF Research Database (Denmark)

Johansen, Søren

2008-01-01

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

RankProdIt: A web-interactive Rank Products analysis tool

Directory of Open Access Journals (Sweden)

Laing Emma

2010-08-01

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

LogDet Rank Minimization with Application to Subspace Clustering

Directory of Open Access Journals (Sweden)

Zhao Kang

2015-01-01

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

Temporal focus, temporal distance, and mind-wandering valence: Results from an experience sampling and an experimental study.

Science.gov (United States)

Spronken, Maitta; Holland, Rob W; Figner, Bernd; Dijksterhuis, Ap

2016-04-01

When mind-wandering, people may think about events that happened in the past, or events that may happen in the future. Using experience sampling, we first aimed to replicate the finding that future-oriented thoughts show a greater positivity bias than past-oriented thoughts. Furthermore, we investigated whether there is a relation between the temporal distance of past- and future-oriented thoughts and the frequency of positive thoughts, a factor that has received little attention in previous work. Second, we experimentally investigated the relation between temporal focus, temporal distance, and thought valence. Both studies showed that future-oriented thoughts were more positive compared to past-oriented thoughts. Regarding temporal distance, thoughts about the distant past and future were more positive than thoughts about the near past and future in the experiment. However, the experience sampling study did not provide clear insight into this relation. Potential theoretical and methodological explanations for these findings are discussed. Copyright © 2016 Elsevier Inc. All rights reserved.

A human fecal contamination index for ranking impaired ...

Science.gov (United States)

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

Per tree estimates with n-tree distance sampling: an application to increment core data

Science.gov (United States)

Thomas B. Lynch; Robert F. Wittwer

2002-01-01

Per tree estimates using the n trees nearest a point can be obtained by using a ratio of per unit area estimates from n-tree distance sampling. This ratio was used to estimate average age by d.b.h. classes for cottonwood trees (Populus deltoides Bartr. ex Marsh.) on the Cimarron National Grassland. Increment...

PageRank as a method to rank biomedical literature by importance.

Science.gov (United States)

Yates, Elliot J; Dixon, Louise C

2015-01-01

Optimal ranking of literature importance is vital in overcoming article overload. Existing ranking methods are typically based on raw citation counts, giving a sum of 'inbound' links with no consideration of citation importance. PageRank, an algorithm originally developed for ranking webpages at the search engine, Google, could potentially be adapted to bibliometrics to quantify the relative importance weightings of a citation network. This article seeks to validate such an approach on the freely available, PubMed Central open access subset (PMC-OAS) of biomedical literature. On-demand cloud computing infrastructure was used to extract a citation network from over 600,000 full-text PMC-OAS articles. PageRanks and citation counts were calculated for each node in this network. PageRank is highly correlated with citation count (R = 0.905, P PageRank can be trivially computed on commodity cluster hardware and is linearly correlated with citation count. Given its putative benefits in quantifying relative importance, we suggest it may enrich the citation network, thereby overcoming the existing inadequacy of citation counts alone. We thus suggest PageRank as a feasible supplement to, or replacement of, existing bibliometric ranking methods.

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

Science.gov (United States)

Soh, Kay Cheng

2012-01-01

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

Compressed Sensing with Rank Deficient Dictionaries

DEFF Research Database (Denmark)

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

2012-01-01

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

Is a gene important for bone resorption a candidate for obesity? An association and linkage study on the RANK (receptor activator of nuclear factor-kappaB) gene in a large Caucasian sample.

Science.gov (United States)

Zhao, Lan-Juan; Guo, Yan-Fang; Xiong, Dong-Hai; Xiao, Peng; Recker, Robert R; Deng, Hong-Wen

2006-11-01

In light of findings that osteoporosis and obesity may share some common genetic determination and previous reports that RANK (receptor activator of nuclear factor-kappaB) is expressed in skeletal muscles which are important for energy metabolism, we hypothesize that RANK, a gene essential for osteoclastogenesis, is also important for obesity. In order to test the hypothesis with solid data we first performed a linkage analysis around the RANK gene in 4,102 Caucasian subjects from 434 pedigrees, then we genotyped 19 SNPs in or around the RANK gene. A family-based association test (FBAT) was performed with both a quantitative measure of obesity [fat mass, lean mass, body mass index (BMI), and percentage fat mass (PFM)] and a dichotomously defined obesity phenotype-OB (OB if BMI > or = 30 kg/m(2)). In the linkage analysis, an empirical P = 0.004 was achieved at the location of the RANK gene for BMI. Family-based association analysis revealed significant associations of eight SNPs with at least one obesity-related phenotype (P obesity phenotype. The P value is 0.126 for OB, 0.033 for fat mass, 0.021 for lean mass, 0.016 for BMI, and 0.006 for PFM. The haplotype data analyses provide further association evidence. In conclusion, for the first time, our results suggest that RANK is a novel candidate for determination of obesity.

A tilting approach to ranking influence

KAUST Repository

Genton, Marc G.; Hall, Peter

2014-01-01

We suggest a new approach, which is applicable for general statistics computed from random samples of univariate or vector-valued or functional data, to assessing the influence that individual data have on the value of a statistic, and to ranking

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

Science.gov (United States)

Jackson, Brian

2015-01-01

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

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

Science.gov (United States)

Nagasinghe, Iranga

2010-01-01

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

Functional Multiplex PageRank

Science.gov (United States)

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

2016-10-01

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

Ranking nodes in growing networks: When PageRank fails

Science.gov (United States)

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

2015-11-01

PageRank is arguably the most popular ranking algorithm which is being applied in real systems ranging from information to biological and infrastructure networks. Despite its outstanding popularity and broad use in different areas of science, the relation between the algorithm’s efficacy and properties of the network on which it acts has not yet been fully understood. We study here PageRank’s performance on a network model supported by real data, and show that realistic temporal effects make PageRank fail in individuating the most valuable nodes for a broad range of model parameters. Results on real data are in qualitative agreement with our model-based findings. This failure of PageRank reveals that the static approach to information filtering is inappropriate for a broad class of growing systems, and suggest that time-dependent algorithms that are based on the temporal linking patterns of these systems are needed to better rank the nodes.

Development of the table of initial isolation distances and protective action distances for the 2004 emergency response guidebook.

Energy Technology Data Exchange (ETDEWEB)

Brown, D. F.; Freeman, W. A.; Carhart, R. A.; Krumpolc, M.; Decision and Information Sciences; Univ. of Illinois at Chicago

2005-09-23

This report provides technical documentation for values in the Table of Initial Isolation and Protective Action Distances (PADs) in the 2004 Emergency Response Guidebook (ERG2004). The objective for choosing the PADs specified in the ERG2004 is to balance the need to adequately protect the public from exposure to potentially harmful substances against the risks and expenses that could result from overreacting to a spill. To quantify this balance, a statistical approach is adopted, whereby the best available information is used to conduct an accident scenario analysis and develop a set of up to 1,000,000 hypothetical incidents. The set accounts for differences in containers types, incident types, accident severity (i.e., amounts released), locations, times of day, times of year, and meteorological conditions. Each scenario is analyzed using detailed emission rate and atmospheric dispersion models to calculate the downwind chemical concentrations from which a 'safe distance' is determined. The safe distance is defined as the distance downwind from the source at which the chemical concentration falls below health protection criteria. The American Industrial Hygiene Association's Emergency Response Planning Guideline Level 2 (ERPG-2) or equivalent is the health criteria used. The statistical sample of safe distance values for all incidents considered in the analysis are separated into four categories: small spill/daytime release, small spill/nighttime release, large spill/daytime release, and large spill/nighttime release. The 90th-percentile safe distance values for each of these groups became the PADs that appear in the ERG2004.

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

Directory of Open Access Journals (Sweden)

Preisinger E

2007-01-01

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

Bootstrap Determination of the Co-integration Rank in Heteroskedastic VAR Models

DEFF Research Database (Denmark)

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

In a recent paper Cavaliere et al. (2012) develop bootstrap implementations of the (pseudo-) likelihood ratio [PLR] co-integration rank test and associated sequential rank determination procedure of Johansen (1996). The bootstrap samples are constructed using the restricted parameter estimates...... of the underlying VAR model which obtain under the reduced rank null hypothesis. They propose methods based on an i.i.d. bootstrap re-sampling scheme and establish the validity of their proposed bootstrap procedures in the context of a co-integrated VAR model with i.i.d. innovations. In this paper we investigate...... the properties of their bootstrap procedures, together with analogous procedures based on a wild bootstrap re-sampling scheme, when time-varying behaviour is present in either the conditional or unconditional variance of the innovations. We show that the bootstrap PLR tests are asymptotically correctly sized and...

Bootstrap Determination of the Co-Integration Rank in Heteroskedastic VAR Models

DEFF Research Database (Denmark)

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

In a recent paper Cavaliere et al. (2012) develop bootstrap implementations of the (pseudo-) likelihood ratio [PLR] co-integration rank test and associated sequential rank determination procedure of Johansen (1996). The bootstrap samples are constructed using the restricted parameter estimates...... of the underlying VAR model which obtain under the reduced rank null hypothesis. They propose methods based on an i.i.d. bootstrap re-sampling scheme and establish the validity of their proposed bootstrap procedures in the context of a co-integrated VAR model with i.i.d. innovations. In this paper we investigate...... the properties of their bootstrap procedures, together with analogous procedures based on a wild bootstrap re-sampling scheme, when time-varying behaviour is present in either the conditional or unconditional variance of the innovations. We show that the bootstrap PLR tests are asymptotically correctly sized and...

The parallel volume at large distances

DEFF Research Database (Denmark)

Kampf, Jürgen

In this paper we examine the asymptotic behavior of the parallel volume of planar non-convex bodies as the distance tends to infinity. We show that the difference between the parallel volume of the convex hull of a body and the parallel volume of the body itself tends to . This yields a new proof...... for the fact that a planar body can only have polynomial parallel volume, if it is convex. Extensions to Minkowski spaces and random sets are also discussed....

The parallel volume at large distances

DEFF Research Database (Denmark)

Kampf, Jürgen

In this paper we examine the asymptotic behavior of the parallel volume of planar non-convex bodies as the distance tends to infinity. We show that the difference between the parallel volume of the convex hull of a body and the parallel volume of the body itself tends to 0. This yields a new proof...... for the fact that a planar body can only have polynomial parallel volume, if it is convex. Extensions to Minkowski spaces and random sets are also discussed....

International Conference on Robust Rank-Based and Nonparametric Methods

CERN Document Server

McKean, Joseph

2016-01-01

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

A novel application of PageRank and user preference algorithms for assessing the relative performance of track athletes in competition.

Science.gov (United States)

Beggs, Clive B; Shepherd, Simon J; Emmonds, Stacey; Jones, Ben

2017-01-01

Ranking enables coaches, sporting authorities, and pundits to determine the relative performance of individual athletes and teams in comparison to their peers. While ranking is relatively straightforward in sports that employ traditional leagues, it is more difficult in sports where competition is fragmented (e.g. athletics, boxing, etc.), with not all competitors competing against each other. In such situations, complex points systems are often employed to rank athletes. However, these systems have the inherent weakness that they frequently rely on subjective assessments in order to gauge the calibre of the competitors involved. Here we show how two Internet derived algorithms, the PageRank (PR) and user preference (UP) algorithms, when utilised with a simple 'who beat who' matrix, can be used to accurately rank track athletes, avoiding the need for subjective assessment. We applied the PR and UP algorithms to the 2015 IAAF Diamond League men's 100m competition and compared their performance with the Keener, Colley and Massey ranking algorithms. The top five places computed by the PR and UP algorithms, and the Diamond League '2016' points system were all identical, with the Kendall's tau distance between the PR standings and '2016' points system standings being just 15, indicating that only 5.9% of pairs differed in their order between these two lists. By comparison, the UP and '2016' standings displayed a less strong relationship, with a tau distance of 95, indicating that 37.6% of the pairs differed in their order. When compared with the standings produced using the Keener, Colley and Massey algorithms, the PR standings appeared to be closest to the Keener standings (tau distance = 67, 26.5% pair order disagreement), whereas the UP standings were more similar to the Colley and Massey standings, with the tau distances between these ranking lists being only 48 (19.0% pair order disagreement) and 59 (23.3% pair order disagreement) respectively. In particular, the

A novel application of PageRank and user preference algorithms for assessing the relative performance of track athletes in competition.

Directory of Open Access Journals (Sweden)

Clive B Beggs

Full Text Available Ranking enables coaches, sporting authorities, and pundits to determine the relative performance of individual athletes and teams in comparison to their peers. While ranking is relatively straightforward in sports that employ traditional leagues, it is more difficult in sports where competition is fragmented (e.g. athletics, boxing, etc., with not all competitors competing against each other. In such situations, complex points systems are often employed to rank athletes. However, these systems have the inherent weakness that they frequently rely on subjective assessments in order to gauge the calibre of the competitors involved. Here we show how two Internet derived algorithms, the PageRank (PR and user preference (UP algorithms, when utilised with a simple 'who beat who' matrix, can be used to accurately rank track athletes, avoiding the need for subjective assessment. We applied the PR and UP algorithms to the 2015 IAAF Diamond League men's 100m competition and compared their performance with the Keener, Colley and Massey ranking algorithms. The top five places computed by the PR and UP algorithms, and the Diamond League '2016' points system were all identical, with the Kendall's tau distance between the PR standings and '2016' points system standings being just 15, indicating that only 5.9% of pairs differed in their order between these two lists. By comparison, the UP and '2016' standings displayed a less strong relationship, with a tau distance of 95, indicating that 37.6% of the pairs differed in their order. When compared with the standings produced using the Keener, Colley and Massey algorithms, the PR standings appeared to be closest to the Keener standings (tau distance = 67, 26.5% pair order disagreement, whereas the UP standings were more similar to the Colley and Massey standings, with the tau distances between these ranking lists being only 48 (19.0% pair order disagreement and 59 (23.3% pair order disagreement respectively. In

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

Science.gov (United States)

Astivia, Oscar L Olvera; Zumbo, Bruno D

2017-11-01

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. © 2017 The British Psychological Society.

Handling missing data in ranked set sampling

CERN Document Server

Bouza-Herrera, Carlos N

2013-01-01

The existence of missing observations is a very important aspect to be considered in the application of survey sampling, for example. In human populations they may be caused by a refusal of some interviewees to give the true value for the variable of interest. Traditionally, simple random sampling is used to select samples. Most statistical models are supported by the use of samples selected by means of this design. In recent decades, an alternative design has started being used, which, in many cases, shows an improvement in terms of accuracy compared with traditional sampling. It is called R

Elitism, Sharing and Ranking Choices in Evolutionary Multi-Criterion Optimisation

OpenAIRE

Pursehouse, R.C.; Fleming, P.J.

2002-01-01

Elitism and sharing are two mechanisms that are believed to improve the performance of an evolutionary multi-criterion optimiser. The relative performance of of the two most popular ranking strategies is largely unknown. Using a new empirical inquiry framework, this report studies the effect of elitism, sharing and ranking design choices using a benchmark suite of two-criterion problems.........

Comparing survival curves using rank tests

NARCIS (Netherlands)

Albers, Willem/Wim

1990-01-01

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

Fast Tree: Computing Large Minimum-Evolution Trees with Profiles instead of a Distance Matrix

Energy Technology Data Exchange (ETDEWEB)

N. Price, Morgan; S. Dehal, Paramvir; P. Arkin, Adam

2009-07-31

Gene families are growing rapidly, but standard methods for inferring phylogenies do not scale to alignments with over 10,000 sequences. We present FastTree, a method for constructing large phylogenies and for estimating their reliability. Instead of storing a distance matrix, FastTree stores sequence profiles of internal nodes in the tree. FastTree uses these profiles to implement neighbor-joining and uses heuristics to quickly identify candidate joins. FastTree then uses nearest-neighbor interchanges to reduce the length of the tree. For an alignment with N sequences, L sites, and a different characters, a distance matrix requires O(N^2) space and O(N^2 L) time, but FastTree requires just O( NLa + N sqrt(N) ) memory and O( N sqrt(N) log(N) L a ) time. To estimate the tree's reliability, FastTree uses local bootstrapping, which gives another 100-fold speedup over a distance matrix. For example, FastTree computed a tree and support values for 158,022 distinct 16S ribosomal RNAs in 17 hours and 2.4 gigabytes of memory. Just computing pairwise Jukes-Cantor distances and storing them, without inferring a tree or bootstrapping, would require 17 hours and 50 gigabytes of memory. In simulations, FastTree was slightly more accurate than neighbor joining, BIONJ, or FastME; on genuine alignments, FastTree's topologies had higher likelihoods. FastTree is available at http://microbesonline.org/fasttree.

Observations of the Earth's polar cleft at large radial distances with the Hawkeye 1 magnetometer

International Nuclear Information System (INIS)

Farrell, W.M.; Van Allen, J.A.

1990-01-01

Based on 364-spacecraft passes through the dayside region, the position of the polar cleft at large redial distances was determined with the magnetometer flown on Hawkeye 1. This data set represents one of the largest to investigate the high-latitude region at large radial distances, making it ideal for the study of the cusp and cleft region. Identification of the cleft depended on noting strong negative deviations of the magnetic field strength in the region from that of the dipole field. In solar magnetic coordinates, cleft observations were found between 40 degree and 70 degree latitude and ±75 degree longitude, while in geocentric magnetospheric coordinates, these observations were found between 20 degree and 75 degree latitude and ± 75 degree longitude. The extreme longitudinal extent of 150 degree is larger than those reported in some previous studies. Large magnetic depressions associated with the cleft extend out to 12 R E . Beyond this point, low model dipole field strengths make the determination of the cleft based on magnetic depressions unreliable. The cleft occurrences fall within an oval in magnetic latitude and longitude, but this oval is of a statistical nature and cannot be interpreted as the shape of the region at a given moment. As reported in other studies, the cleft was observed to shift to lower latitudes as compared to its quiet time geometry during periods when Kp was large and when the interplanetary magnetic field (IMF) pointed in a southerly direction. A southerly shift was also observed when th solar wind bulk flow speed, V sw , was large (>450 km/s), and the region might have enlarged when solar wind pressure, P sw , was large. The variation of the cleft latitude with V sw and P sw has not been thoroughly examined in previous studies

Optical method for distance and displacement measurements of the probe-sample separation in a scanning near-field optical microscope

International Nuclear Information System (INIS)

Santamaria, L.; Siller, H. R.; Garcia-Ortiz, C. E.; Cortes, R.; Coello, V.

2016-01-01

In this work, we present an alternative optical method to determine the probe-sample separation distance in a scanning near-field optical microscope. The experimental method is based in a Lloyd’s mirror interferometer and offers a measurement precision deviation of ∼100 nm using digital image processing and numerical analysis. The technique can also be strategically combined with the characterization of piezoelectric actuators and stability evaluation of the optical system. It also opens the possibility for the development of an automatic approximation control system valid for probe-sample distances from 5 to 500 μm.

Optical method for distance and displacement measurements of the probe-sample separation in a scanning near-field optical microscope

Energy Technology Data Exchange (ETDEWEB)

Santamaria, L.; Siller, H. R. [Tecnológico de Monterrey, Eugenio Garza Sada 2501 Sur, Monterrey, N.L., 64849 (Mexico); Garcia-Ortiz, C. E., E-mail: cegarcia@cicese.mx [CONACYT Research Fellow – CICESE, Unidad Monterrey, Alianza Centro 504, Apodaca, NL, 66629 (Mexico); Cortes, R.; Coello, V. [CICESE, Unidad Monterrey, PIIT, Alianza Centro 504, Apodaca, NL, 66629 (Mexico)

2016-04-15

In this work, we present an alternative optical method to determine the probe-sample separation distance in a scanning near-field optical microscope. The experimental method is based in a Lloyd’s mirror interferometer and offers a measurement precision deviation of ∼100 nm using digital image processing and numerical analysis. The technique can also be strategically combined with the characterization of piezoelectric actuators and stability evaluation of the optical system. It also opens the possibility for the development of an automatic approximation control system valid for probe-sample distances from 5 to 500 μm.

A Simple Device for Lens-to-Sample Distance Adjustment in Laser-Induced Breakdown Spectroscopy (LIBS).

Science.gov (United States)

Cortez, Juliana; Farias Filho, Benedito B; Fontes, Laiane M; Pasquini, Celio; Raimundo, Ivo M; Pimentel, Maria Fernanda; de Souza Lins Borba, Flávia

2017-04-01

A simple device based on two commercial laser pointers is described to assist in the analysis of samples that present uneven surfaces and/or irregular shapes using laser-induced breakdown spectroscopy (LIBS). The device allows for easy positioning of the sample surface at a reproducible distance from the focusing lens that conveys the laser pulse to generate the micro-plasma in a LIBS system, with reproducibility better than ±0.2 mm. In this way, fluctuations in the fluence (J cm -2 ) are minimized and the LIBS analytical signals can be obtained with a better precision even when samples with irregular surfaces are probed.

Sign rank versus Vapnik-Chervonenkis dimension

Science.gov (United States)

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

2017-12-01

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

Web page sorting algorithm based on query keyword distance relation

Science.gov (United States)

Yang, Han; Cui, Hong Gang; Tang, Hao

2017-08-01

In order to optimize the problem of page sorting, according to the search keywords in the web page in the relationship between the characteristics of the proposed query keywords clustering ideas. And it is converted into the degree of aggregation of the search keywords in the web page. Based on the PageRank algorithm, the clustering degree factor of the query keyword is added to make it possible to participate in the quantitative calculation. This paper proposes an improved algorithm for PageRank based on the distance relation between search keywords. The experimental results show the feasibility and effectiveness of the method.

Discriminative Multi-View Interactive Image Re-Ranking.

Science.gov (United States)

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

2017-07-01

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

Relationships between nurse- and physician-to-population ratios and state health rankings.

Science.gov (United States)

Bigbee, Jeri L

2008-01-01

To evaluate the relationship between nurse-to-population ratios and population health, as indicated by state health ranking, and to compare the findings with physician-to-population ratios. Secondary analysis correlational design. The sample consisted of all 50 states in the United States. Data sources included the United Health Foundation's 2006 state health rankings, the 2004 National Sample Survey for Registered Nurses, and the U.S. Health Workforce Profile from the New York Center for Health Workforce Studies. Significant relationships between nurse-to-population ratio and overall state health ranking (rho=-.446, p tf?>=.001) and 11 of the 18 components of that ranking were found. Significant components included motor vehicle death rate, high school graduation rate, violent crime rate, infectious disease rate, percentage of children in poverty, percentage of uninsured residents, immunization rate, adequacy of prenatal care, number of poor mental health days, number of poor physical health days, and premature death rate, with higher nurse-to-population ratios associated with higher health rankings. Specialty (public health and school) nurse-to-population ratios were not as strongly related to state health ranking. Physician-to-population ratios were also significantly related to state health ranking, but were associated with different components than nurses. These findings suggest that greater nurses per capita may be uniquely associated with healthier communities; however, further multivariate research is needed.

Calculating PageRank in a changing network with added or removed edges

Science.gov (United States)

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.

Learning Global-Local Distance Metrics for Signature-Based Biometric Cryptosystems

Directory of Open Access Journals (Sweden)

George S. Eskander Ekladious

2017-11-01

Full Text Available Biometric traits, such as fingerprints, faces and signatures have been employed in bio-cryptosystems to secure cryptographic keys within digital security schemes. Reliable implementations of these systems employ error correction codes formulated as simple distance thresholds, although they may not effectively model the complex variability of behavioral biometrics like signatures. In this paper, a Global-Local Distance Metric (GLDM framework is proposed to learn cost-effective distance metrics, which reduce within-class variability and augment between-class variability, so that simple error correction thresholds of bio-cryptosystems provide high classification accuracy. First, a large number of samples from a development dataset are used to train a global distance metric that differentiates within-class from between-class samples of the population. Then, once user-specific samples are available for enrollment, the global metric is tuned to a local user-specific one. Proof-of-concept experiments on two reference offline signature databases confirm the viability of the proposed approach. Distance metrics are produced based on concise signature representations consisting of about 20 features and a single prototype. A signature-based bio-cryptosystem is designed using the produced metrics and has shown average classification error rates of about 7% and 17% for the PUCPR and the GPDS-300 databases, respectively. This level of performance is comparable to that obtained with complex state-of-the-art classifiers.

Sparse structure regularized ranking

KAUST Repository

Wang, Jim Jing-Yan

2014-04-17

Learning ranking scores is critical for the multimedia database retrieval problem. In this paper, we propose a novel ranking score learning algorithm by exploring the sparse structure and using it to regularize ranking scores. To explore the sparse structure, we assume that each multimedia object could be represented as a sparse linear combination of all other objects, and combination coefficients are regarded as a similarity measure between objects and used to regularize their ranking scores. Moreover, we propose to learn the sparse combination coefficients and the ranking scores simultaneously. A unified objective function is constructed with regard to both the combination coefficients and the ranking scores, and is optimized by an iterative algorithm. Experiments on two multimedia database retrieval data sets demonstrate the significant improvements of the propose algorithm over state-of-the-art ranking score learning algorithms.

Learning to Recommend Point-of-Interest with the Weighted Bayesian Personalized Ranking Method in LBSNs

Directory of Open Access Journals (Sweden)

Lei Guo

2017-02-01

Full Text Available Point-of-interest (POI recommendation has been well studied in recent years. However, most of the existing methods focus on the recommendation scenarios where users can provide explicit feedback. In most cases, however, the feedback is not explicit, but implicit. For example, we can only get a user’s check-in behaviors from the history of what POIs she/he has visited, but never know how much she/he likes and why she/he does not like them. Recently, some researchers have noticed this problem and began to learn the user preferences from the partial order of POIs. However, these works give equal weight to each POI pair and cannot distinguish the contributions from different POI pairs. Intuitively, for the two POIs in a POI pair, the larger the frequency difference of being visited and the farther the geographical distance between them, the higher the contribution of this POI pair to the ranking function. Based on the above observations, we propose a weighted ranking method for POI recommendation. Specifically, we first introduce a Bayesian personalized ranking criterion designed for implicit feedback to POI recommendation. To fully utilize the partial order of POIs, we then treat the cost function in a weighted way, that is give each POI pair a different weight according to their frequency of being visited and the geographical distance between them. Data analysis and experimental results on two real-world datasets demonstrate the existence of user preference on different POI pairs and the effectiveness of our weighted ranking method.

Fast Tree: Computing Large Minimum-Evolution Trees with Profiles instead of a Distance Matrix

OpenAIRE

N. Price, Morgan

2009-01-01

Gene families are growing rapidly, but standard methods for inferring phylogenies do not scale to alignments with over 10,000 sequences. We present FastTree, a method for constructing large phylogenies and for estimating their reliability. Instead of storing a distance matrix, FastTree stores sequence profiles of internal nodes in the tree. FastTree uses these profiles to implement neighbor-joining and uses heuristics to quickly identify candidate joins. FastTree then uses nearest-neighbor i...

FastTree: Computing Large Minimum Evolution Trees with Profiles instead of a Distance Matrix

OpenAIRE

Price, Morgan N.; Dehal, Paramvir S.; Arkin, Adam P.

2009-01-01

Gene families are growing rapidly, but standard methods for inferring phylogenies do not scale to alignments with over 10,000 sequences. We present FastTree, a method for constructing large phylogenies and for estimating their reliability. Instead of storing a distance matrix, FastTree stores sequence profiles of internal nodes in the tree. FastTree uses these profiles to implement Neighbor-Joining and uses heuristics to quickly identify candidate joins. FastTree then uses nearest neighbor in...

Low-rank coal research

Energy Technology Data Exchange (ETDEWEB)

Weber, G. F.; Laudal, D. L.

1989-01-01

This work is a compilation of reports on ongoing research at the University of North Dakota. Topics include: Control Technology and Coal Preparation Research (SO{sub x}/NO{sub x} control, waste management), Advanced Research and Technology Development (turbine combustion phenomena, combustion inorganic transformation, coal/char reactivity, liquefaction reactivity of low-rank coals, gasification ash and slag characterization, fine particulate emissions), Combustion Research (fluidized bed combustion, beneficiation of low-rank coals, combustion characterization of low-rank coal fuels, diesel utilization of low-rank coals), Liquefaction Research (low-rank coal direct liquefaction), and Gasification Research (hydrogen production from low-rank coals, advanced wastewater treatment, mild gasification, color and residual COD removal from Synfuel wastewaters, Great Plains Gasification Plant, gasifier optimization).

Sampling large random knots in a confined space

International Nuclear Information System (INIS)

Arsuaga, J; Blackstone, T; Diao, Y; Hinson, K; Karadayi, E; Saito, M

2007-01-01

DNA knots formed under extreme conditions of condensation, as in bacteriophage P4, are difficult to analyze experimentally and theoretically. In this paper, we propose to use the uniform random polygon model as a supplementary method to the existing methods for generating random knots in confinement. The uniform random polygon model allows us to sample knots with large crossing numbers and also to generate large diagrammatically prime knot diagrams. We show numerically that uniform random polygons sample knots with large minimum crossing numbers and certain complicated knot invariants (as those observed experimentally). We do this in terms of the knot determinants or colorings. Our numerical results suggest that the average determinant of a uniform random polygon of n vertices grows faster than O(e n 2 )). We also investigate the complexity of prime knot diagrams. We show rigorously that the probability that a randomly selected 2D uniform random polygon of n vertices is almost diagrammatically prime goes to 1 as n goes to infinity. Furthermore, the average number of crossings in such a diagram is at the order of O(n 2 ). Therefore, the two-dimensional uniform random polygons offer an effective way in sampling large (prime) knots, which can be useful in various applications

Sampling large random knots in a confined space

Science.gov (United States)

Arsuaga, J.; Blackstone, T.; Diao, Y.; Hinson, K.; Karadayi, E.; Saito, M.

2007-09-01

DNA knots formed under extreme conditions of condensation, as in bacteriophage P4, are difficult to analyze experimentally and theoretically. In this paper, we propose to use the uniform random polygon model as a supplementary method to the existing methods for generating random knots in confinement. The uniform random polygon model allows us to sample knots with large crossing numbers and also to generate large diagrammatically prime knot diagrams. We show numerically that uniform random polygons sample knots with large minimum crossing numbers and certain complicated knot invariants (as those observed experimentally). We do this in terms of the knot determinants or colorings. Our numerical results suggest that the average determinant of a uniform random polygon of n vertices grows faster than O(e^{n^2}) . We also investigate the complexity of prime knot diagrams. We show rigorously that the probability that a randomly selected 2D uniform random polygon of n vertices is almost diagrammatically prime goes to 1 as n goes to infinity. Furthermore, the average number of crossings in such a diagram is at the order of O(n2). Therefore, the two-dimensional uniform random polygons offer an effective way in sampling large (prime) knots, which can be useful in various applications.

Sampling large random knots in a confined space

Energy Technology Data Exchange (ETDEWEB)

Arsuaga, J [Department of Mathematics, San Francisco State University, 1600 Holloway Ave, San Francisco, CA 94132 (United States); Blackstone, T [Department of Computer Science, San Francisco State University, 1600 Holloway Ave., San Francisco, CA 94132 (United States); Diao, Y [Department of Mathematics and Statistics, University of North Carolina at Charlotte, Charlotte, NC 28223 (United States); Hinson, K [Department of Mathematics and Statistics, University of North Carolina at Charlotte, Charlotte, NC 28223 (United States); Karadayi, E [Department of Mathematics, University of South Florida, 4202 E Fowler Avenue, Tampa, FL 33620 (United States); Saito, M [Department of Mathematics, University of South Florida, 4202 E Fowler Avenue, Tampa, FL 33620 (United States)

2007-09-28

DNA knots formed under extreme conditions of condensation, as in bacteriophage P4, are difficult to analyze experimentally and theoretically. In this paper, we propose to use the uniform random polygon model as a supplementary method to the existing methods for generating random knots in confinement. The uniform random polygon model allows us to sample knots with large crossing numbers and also to generate large diagrammatically prime knot diagrams. We show numerically that uniform random polygons sample knots with large minimum crossing numbers and certain complicated knot invariants (as those observed experimentally). We do this in terms of the knot determinants or colorings. Our numerical results suggest that the average determinant of a uniform random polygon of n vertices grows faster than O(e{sup n{sup 2}}). We also investigate the complexity of prime knot diagrams. We show rigorously that the probability that a randomly selected 2D uniform random polygon of n vertices is almost diagrammatically prime goes to 1 as n goes to infinity. Furthermore, the average number of crossings in such a diagram is at the order of O(n{sup 2}). Therefore, the two-dimensional uniform random polygons offer an effective way in sampling large (prime) knots, which can be useful in various applications.

A Rank-Constrained Matrix Representation for Hypergraph-Based Subspace Clustering

Directory of Open Access Journals (Sweden)

Yubao Sun

2015-01-01

Full Text Available This paper presents a novel, rank-constrained matrix representation combined with hypergraph spectral analysis to enable the recovery of the original subspace structures of corrupted data. Real-world data are frequently corrupted with both sparse error and noise. Our matrix decomposition model separates the low-rank, sparse error, and noise components from the data in order to enhance robustness to the corruption. In order to obtain the desired rank representation of the data within a dictionary, our model directly utilizes rank constraints by restricting the upper bound of the rank range. An alternative projection algorithm is proposed to estimate the low-rank representation and separate the sparse error from the data matrix. To further capture the complex relationship between data distributed in multiple subspaces, we use hypergraph to represent the data by encapsulating multiple related samples into one hyperedge. The final clustering result is obtained by spectral decomposition of the hypergraph Laplacian matrix. Validation experiments on the Extended Yale Face Database B, AR, and Hopkins 155 datasets show that the proposed method is a promising tool for subspace clustering.

Importance sampling large deviations in nonequilibrium steady states. I

Science.gov (United States)

Ray, Ushnish; Chan, Garnet Kin-Lic; Limmer, David T.

2018-03-01

Large deviation functions contain information on the stability and response of systems driven into nonequilibrium steady states and in such a way are similar to free energies for systems at equilibrium. As with equilibrium free energies, evaluating large deviation functions numerically for all but the simplest systems is difficult because by construction they depend on exponentially rare events. In this first paper of a series, we evaluate different trajectory-based sampling methods capable of computing large deviation functions of time integrated observables within nonequilibrium steady states. We illustrate some convergence criteria and best practices using a number of different models, including a biased Brownian walker, a driven lattice gas, and a model of self-assembly. We show how two popular methods for sampling trajectory ensembles, transition path sampling and diffusion Monte Carlo, suffer from exponentially diverging correlations in trajectory space as a function of the bias parameter when estimating large deviation functions. Improving the efficiencies of these algorithms requires introducing guiding functions for the trajectories.

Importance sampling large deviations in nonequilibrium steady states. I.

Science.gov (United States)

Ray, Ushnish; Chan, Garnet Kin-Lic; Limmer, David T

2018-03-28

Large deviation functions contain information on the stability and response of systems driven into nonequilibrium steady states and in such a way are similar to free energies for systems at equilibrium. As with equilibrium free energies, evaluating large deviation functions numerically for all but the simplest systems is difficult because by construction they depend on exponentially rare events. In this first paper of a series, we evaluate different trajectory-based sampling methods capable of computing large deviation functions of time integrated observables within nonequilibrium steady states. We illustrate some convergence criteria and best practices using a number of different models, including a biased Brownian walker, a driven lattice gas, and a model of self-assembly. We show how two popular methods for sampling trajectory ensembles, transition path sampling and diffusion Monte Carlo, suffer from exponentially diverging correlations in trajectory space as a function of the bias parameter when estimating large deviation functions. Improving the efficiencies of these algorithms requires introducing guiding functions for the trajectories.

INTERPRETING THE DISTANCE CORRELATION RESULTS FOR THE COMBO-17 SURVEY

International Nuclear Information System (INIS)

Richards, Mercedes T.; Richards, Donald St. P.; Martínez-Gómez, Elizabeth

2014-01-01

The accurate classification of galaxies in large-sample astrophysical databases of galaxy clusters depends sensitively on the ability to distinguish between morphological types, especially at higher redshifts. This capability can be enhanced through a new statistical measure of association and correlation, called the distance correlation coefficient, which has more statistical power to detect associations than does the classical Pearson measure of linear relationships between two variables. The distance correlation measure offers a more precise alternative to the classical measure since it is capable of detecting nonlinear relationships that may appear in astrophysical applications. We showed recently that the comparison between the distance and Pearson correlation coefficients can be used effectively to isolate potential outliers in various galaxy data sets, and this comparison has the ability to confirm the level of accuracy associated with the data. In this work, we elucidate the advantages of distance correlation when applied to large databases. We illustrate how the distance correlation measure can be used effectively as a tool to confirm nonlinear relationships between various variables in the COMBO-17 database, including the lengths of the major and minor axes, and the alternative redshift distribution. For these outlier pairs, the distance correlation coefficient is routinely higher than the Pearson coefficient since it is easier to detect nonlinear relationships with distance correlation. The V-shaped scatter plots of Pearson versus distance correlation coefficients also reveal the patterns with increasing redshift and the contributions of different galaxy types within each redshift range

Rank Dynamics of Word Usage at Multiple Scales

Directory of Open Access Journals (Sweden)

José A. Morales

2018-05-01

Full Text Available The recent dramatic increase in online data availability has allowed researchers to explore human culture with unprecedented detail, such as the growth and diversification of language. In particular, it provides statistical tools to explore whether word use is similar across languages, and if so, whether these generic features appear at different scales of language structure. Here we use the Google Books N-grams dataset to analyze the temporal evolution of word usage in several languages. We apply measures proposed recently to study rank dynamics, such as the diversity of N-grams in a given rank, the probability that an N-gram changes rank between successive time intervals, the rank entropy, and the rank complexity. Using different methods, results show that there are generic properties for different languages at different scales, such as a core of words necessary to minimally understand a language. We also propose a null model to explore the relevance of linguistic structure across multiple scales, concluding that N-gram statistics cannot be reduced to word statistics. We expect our results to be useful in improving text prediction algorithms, as well as in shedding light on the large-scale features of language use, beyond linguistic and cultural differences across human populations.

Exact fast computation of band depth for large functional datasets: How quickly can one million curves be ranked?

KAUST Repository

Sun, Ying

2012-10-01

© 2012 John Wiley & Sons, Ltd. Band depth is an important nonparametric measure that generalizes order statistics and makes univariate methods based on order statistics possible for functional data. However, the computational burden of band depth limits its applicability when large functional or image datasets are considered. This paper proposes an exact fast method to speed up the band depth computation when bands are defined by two curves. Remarkable computational gains are demonstrated through simulation studies comparing our proposal with the original computation and one existing approximate method. For example, we report an experiment where our method can rank one million curves, evaluated at fifty time points each, in 12.4 seconds with Matlab.

RANKING ENTERPRISES IN TERMS OF COMPETENCES INSIDE REGIONAL PRODUCTION NETWORK

Directory of Open Access Journals (Sweden)

Marko Mladineo

2013-02-01

Full Text Available Today's economic crisis has led to bankruptcy of many successful, but usually large-sized enterprises. This brought into question the future of large-sized enterprises. However, the only alternative to largesized enterprises (LEs is networking of small and medium-sized enterprises (SMEs into Regional Production Networks (RPNet. RPNet is non-hierarchical organizational form in which every SME is autonomous. Hence, every SME of production network is capable and wiling to be part of special cooperation inside network called Virtual Enterprise (VE. For each new product a new virtual enterprise is formed from different SMEs. The question is: which SMEs will be part of new virtual enterprise? If it is possible to evaluate SME's competences, it is also possible to rank SMEs. Ranking of SMEs according to technical, organizational and human competences is multi-criteria decision analysis (MCDA problem. So, in this paper PROMETHEE method is selected to perform a ranking of SMEs.

Health Risk Ranking of Lead Contaminated Sites in Bagega Community, Zamfara State, Nigeria

Directory of Open Access Journals (Sweden)

Alaba Olanreaju Clement

2017-09-01

Full Text Available Background: The release of lead dust during the processing of lead-gold ore has become an environmental threat. Therefore the protection of miners’ health and their environment required remediation which can be achieved by ranking the risk posed by lead in order to prioritize the allocation of resources during remediation. Methods: Soil and water samples were collected at BRC, BRG, BVC, BPA and BFA; BWE, BBH and BPO using stratified random and grab sampling methods. Lead concentrations in the samples were determined using AAS while health risk index (HRI via ingestion was estimated using USEPA equations. The ranking of HRI was done using Detailed Quantitative Risk Assessment while the difference between the HRI and USEPA standard were determined using one sample t test. Results: The result showed that BRC/10, BRG/03, BVC/11, BPA/02 and BFA/08 were ranked highest in soil samples, while BWE/02, BBH/09 and BPO/04 were ranked highest in water samples as they posed elevated health risk effects to miners. One sample t test established that the BRC, BPA, BFA and BPO were significantly different from United States Environmental Protection Agency (US EPA standard. Conclusion: The study discovered that the users of both the lead contaminated soil and water were seriously exposed to potential health risk. It therefore suggested that decision makers should give priority in allocating resources to those sites with elevated lead concentrations during the remediation.

Ranking environmental liabilities at a petroleum refinery

International Nuclear Information System (INIS)

Lupo, M.

1995-01-01

A new computer model is available to allow the management of a petroleum refinery to prioritize environmental action and construct a holistic approach to remediation. A large refinery may have numerous solid waste management units regulated by the Resource Conservation and Recovery Act (RCRA), as well as process units that emit hazardous chemicals into the environment. These sources can impact several environmental media, potentially including the air, the soil, the groundwater, the unsaturated zone water, and surface water. The number of chemicals of concern may be large. The new model is able to rank the sources by considering the impact of each chemical in each medium from each source in terms of concentration, release rate, and a weighted index based on toxicity. In addition to environmental impact, the sources can be ranked in three other ways: (1) by cost to remediate, (2) by environmental risk reduction caused by the remediation in terms of the decreases in release rate, concentration, and weighted index, and (3) by cost-benefit, which is the environmental risk reduction for each source divided by the cost of the remedy. Ranking each unit in the refinery allows management to use its limited environmental resources in a pro-active strategic manner that produces long-term results, rather than in reactive, narrowly focused, costly, regulatory-driven campaigns that produce only short-term results

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

Science.gov (United States)

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

2017-05-12

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

On Normalized Compression Distance and Large Malware

OpenAIRE

Borbely, Rebecca Schuller

2015-01-01

Normalized Compression Distance (NCD) is a popular tool that uses compression algorithms to cluster and classify data in a wide range of applications. Existing discussions of NCD's theoretical merit rely on certain theoretical properties of compression algorithms. However, we demonstrate that many popular compression algorithms don't seem to satisfy these theoretical properties. We explore the relationship between some of these properties and file size, demonstrating that this theoretical pro...

Ranking online quality and reputation via the user activity

Science.gov (United States)

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

2015-10-01

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

A new method to determine large scale structure from the luminosity distance

International Nuclear Information System (INIS)

Romano, Antonio Enea; Chiang, Hsu-Wen; Chen, Pisin

2014-01-01

The luminosity distance can be used to determine the properties of large scale structure around the observer. To this purpose we develop a new inversion method to map luminosity distance to a Lemaitre–Tolman–Bondi (LTB) metric based on the use of the exact analytical solution for Einstein equations. The main advantages of this approach are an improved numerical accuracy and stability, an exact analytical setting of the initial conditions for the differential equations which need to be solved and the validity for any sign of the functions determining the LTB geometry. Given the fully analytical form of the differential equations, this method also simplifies the calculation of the red-shift expansion around the apparent horizon point where the numerical solution becomes unstable. We test the method by inverting the supernovae Ia luminosity distance function corresponding to the best fit ΛCDM model. We find that only a limited range of initial conditions is compatible with observations, or a transition from red to blue-shift can occur at relatively low red-shift. Despite LTB solutions without a cosmological constant have been shown not to be compatible with all different set of available observational data, those studies normally fit data assuming a special functional ansatz for the inhomogeneity profile, which often depend only on few parameters. Inversion methods on the contrary are able to fully explore the freedom in fixing the functions which determine a LTB solution. Another important possible application is not about LTB solutions as cosmological models, but rather as tools to study the effects on the observations made by a generic observer located in an inhomogeneous region of the Universe where a fully non perturbative treatment involving exact solutions of Einstein equations is required. (paper)

Observation of the activity of selected Oort Cloud comets with perihelia at large distances from the Sun

Science.gov (United States)

Kulyk, Iryna; Rousselot, Philippe; Korsun, Pavlo

2016-10-01

Many comets exhibit considerable level of activity at large distances from the Sun, where sublimation of crystalline water ice cannot account for observable comae. Different patterns of physical activity already observed at large heliocentric distances may be related to the primordial differences in the composition of comet nuclei. Therefore, monitoring of physical activity in the wide range of heliocentric distances can potentially contribute to understanding of internal structure of comet-like bodies. We have observed ten long periodic comets with orbital perihelia lying beyond the "water ice sublimation zone" to quantify the level of physical activity in the wide range of heliocentric distances. Pre-perihelion observations were made when targets moved between 16.7 and 6.5 au from the Sun; post perihelion activity was monitored between 5.2 and 10.6 au. The bulk of the data were gathered with the 2-m Robotic Liverpool Telescope (Observatorio del Roque de Los Muchachos, La Palma, Spain). Some targets were observed with the 2-m RC Telescope located at Peak Terskol Observatory and the 6-m Telescope of the Special Astrophysical Observatory (Northern Caucasus, Russia). Since most of recently obtained spectra of distant active objects are continuum dominated, we use B, V, R images to estimate dust production rates, an upper limit on nucleus radii, and color indices of near nucleus region. The comets C/2005 L3 (McNaught) and C/2006 S3 (Boattini), which exhibit the considerable level of activity, have been repeatedly observed. This enables us to infer the heliocentric dependence of dust production rates, perihelion brightness asymmetries, and color variations over the comae caused possibly by small changes in dust particle properties.

Estimation of rank correlation for clustered data.

Science.gov (United States)

Rosner, Bernard; Glynn, Robert J

2017-06-30

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

Teachers' Educational Qualification, Rank Level, Working Duration, Age, Work Motivation and Work Effectiveness

OpenAIRE

Wiyono, Bambang Budi

2009-01-01

Teachers’ Educational Qualification, Rank Level, Working Duration, Age, Working Mo­tivation, and Working Effectiveness The study investigated the effects of educational qualification, rank level, working duration and age on the elementary school teachers’ working motivation and working ef­fectiveness. The sample of the study consisted of 438 elementary school teachers in Malang which were selected through cluster sampling technique. The study was conducted using explanatory design in the form...

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

Directory of Open Access Journals (Sweden)

Rakić Mia

2013-01-01

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

Sparse structure regularized ranking

KAUST Repository

Wang, Jim Jing-Yan; Sun, Yijun; Gao, Xin

2014-01-01

Learning ranking scores is critical for the multimedia database retrieval problem. In this paper, we propose a novel ranking score learning algorithm by exploring the sparse structure and using it to regularize ranking scores. To explore the sparse

TWO MEASURES OF THE DEPENDENCE OF PREFERENTIAL RANKINGS ON CATEGORICAL VARIABLES

Directory of Open Access Journals (Sweden)

Lissowski Grzegorz

2017-06-01

Full Text Available The aim of this paper is to apply a general methodology for constructing statistical methods, which is based on decision theory, to give a statistical description of preferential rankings, with a focus on the rankings’ dependence on categorical variables. In the paper, I use functions of description errors that are based on the Kemeny and Hamming distances between preferential orderings, but the proposed methodology can also be applied to other methods of estimating description errors.

On the viability of rank-six superstring models

International Nuclear Information System (INIS)

Campbell, B.A.; Olive, K.A.; Reiss, D.B.

1988-01-01

We consider the possibility of breaking a rank-six superstring model to the rank-four standard model. In particular, we point out the difficulties in generating two vacuum expectation values for the two standard model singlets contained in the 27 of E 6 . Although one expectation value is compatible with low energy phenomenology, a vev for ν c is problematic because of the absence of large neutrino masses and/or flavor changing neutral currents. We show that even simple models containing extra fields from incomplete multiplets or E 6 singlets do not resolve these problems. (orig.)

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

Science.gov (United States)

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

2017-04-27

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

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

Directory of Open Access Journals (Sweden)

Yuze Huang

2017-04-01

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

Incorporating the surfing behavior of web users into PageRank

OpenAIRE

Ashyralyyev, Shatlyk

2013-01-01

Ankara : The Department of Computer Engineering and the Graduate School of Engineering and Science of Bilkent University, 2013. Thesis (Master's) -- Bilkent University, 2013. Includes bibliographical references leaves 68-73 One of the most crucial factors that determines the effectiveness of a large-scale commercial web search engine is the ranking (i.e., order) in which web search results are presented to the end user. In modern web search engines, the skeleton for the rank...

Low-rank matrix approximation with manifold regularization.

Science.gov (United States)

Zhang, Zhenyue; Zhao, Keke

2013-07-01

This paper proposes a new model of low-rank matrix factorization that incorporates manifold regularization to the matrix factorization. Superior to the graph-regularized nonnegative matrix factorization, this new regularization model has globally optimal and closed-form solutions. A direct algorithm (for data with small number of points) and an alternate iterative algorithm with inexact inner iteration (for large scale data) are proposed to solve the new model. A convergence analysis establishes the global convergence of the iterative algorithm. The efficiency and precision of the algorithm are demonstrated numerically through applications to six real-world datasets on clustering and classification. Performance comparison with existing algorithms shows the effectiveness of the proposed method for low-rank factorization in general.

Development and first application of an operating events ranking tool

International Nuclear Information System (INIS)

Šimić, Zdenko; Zerger, Benoit; Banov, Reni

2015-01-01

Highlights: • A method using analitycal hierarchy process for ranking operating events is developed and tested. • The method is applied for 5 years of U.S. NRC Licensee Event Reports (1453 events). • Uncertainty and sensitivity of the ranking results are evaluated. • Real events assessment shows potential of the method for operating experience feedback. - Abstract: The operating experience feedback is important for maintaining and improving safety and availability in nuclear power plants. Detailed investigation of all events is challenging since it requires excessive resources, especially in case of large event databases. This paper presents an event groups ranking method to complement the analysis of individual operating events. The basis for the method is the use of an internationally accepted events characterization scheme that allows different ways of events grouping and ranking. The ranking method itself consists of implementing the analytical hierarchy process (AHP) by means of a custom developed tool which allows events ranking based on ranking indexes pre-determined by expert judgment. Following the development phase, the tool was applied to analyze a complete set of 5 years of real nuclear power plants operating events (1453 events). The paper presents the potential of this ranking method to identify possible patterns throughout the event database and therefore to give additional insights into the events as well as to give quantitative input for the prioritization of further more detailed investigation of selected event groups

Measuring and testing dependence by correlation of distances

OpenAIRE

Székely, Gábor J.; Rizzo, Maria L.; Bakirov, Nail K.

2007-01-01

Distance correlation is a new measure of dependence between random vectors. Distance covariance and distance correlation are analogous to product-moment covariance and correlation, but unlike the classical definition of correlation, distance correlation is zero only if the random vectors are independent. The empirical distance dependence measures are based on certain Euclidean distances between sample elements rather than sample moments, yet have a compact representation analogous to the clas...

Time evolution of Wikipedia network ranking

Science.gov (United States)

Eom, Young-Ho; Frahm, Klaus M.; Benczúr, András; Shepelyansky, Dima L.

2013-12-01

We study the time evolution of ranking and spectral properties of the Google matrix of English Wikipedia hyperlink network during years 2003-2011. The statistical properties of ranking of Wikipedia articles via PageRank and CheiRank probabilities, as well as the matrix spectrum, are shown to be stabilized for 2007-2011. A special emphasis is done on ranking of Wikipedia personalities and universities. We show that PageRank selection is dominated by politicians while 2DRank, which combines PageRank and CheiRank, gives more accent on personalities of arts. The Wikipedia PageRank of universities recovers 80% of top universities of Shanghai ranking during the considered time period.

Sampling based uncertainty analysis of 10% hot leg break LOCA in large scale test facility

International Nuclear Information System (INIS)

Sengupta, Samiran; Kraina, V.; Dubey, S. K.; Rao, R. S.; Gupta, S. K.

2010-01-01

Sampling based uncertainty analysis was carried out to quantify uncertainty in predictions of best estimate code RELAP5/MOD3.2 for a thermal hydraulic test (10% hot leg break LOCA) performed in the Large Scale Test Facility (LSTF) as a part of an IAEA coordinated research project. The nodalisation of the test facility was qualified for both steady state and transient level by systematically applying the procedures led by uncertainty methodology based on accuracy extrapolation (UMAE); uncertainty analysis was carried out using the Latin hypercube sampling (LHS) method to evaluate uncertainty for ten input parameters. Sixteen output parameters were selected for uncertainty evaluation and uncertainty band between 5 th and 95 th percentile of the output parameters were evaluated. It was observed that the uncertainty band for the primary pressure during two phase blowdown is larger than that of the remaining period. Similarly, a larger uncertainty band is observed relating to accumulator injection flow during reflood phase. Importance analysis was also carried out and standard rank regression coefficients were computed to quantify the effect of each individual input parameter on output parameters. It was observed that the break discharge coefficient is the most important uncertain parameter relating to the prediction of all the primary side parameters and that the steam generator (SG) relief pressure setting is the most important parameter in predicting the SG secondary pressure

SUPPLEMENT: “GOING THE DISTANCE: MAPPING HOST GALAXIES OF LIGO AND VIRGO SOURCES IN THREE DIMENSIONS USING LOCAL COSMOGRAPHY AND TARGETED FOLLOW-UP” (2016, ApJL, 829, L15)

Energy Technology Data Exchange (ETDEWEB)

Singer, Leo P.; Cenko, S. Bradley; Gehrels, Neil; Cannizzo, John [Astroparticle Physics Laboratory, NASA Goddard Space Flight Center, Mail Code 661, Greenbelt, MD 20771 (United States); Chen, Hsin-Yu; Holz, Daniel E.; Farr, Ben [Department of Physics, Enrico Fermi Institute, and Kavli Institute for Cosmological Physics, University of Chicago, Chicago, IL 60637 (United States); Farr, Will M.; Veitch, John; Berry, Christopher P. L.; Mandel, Ilya [School of Physics and Astronomy, University of Birmingham, Birmingham B15 2TT (United Kingdom); Price, Larry R.; Raymond, Vivien [LIGO Laboratory, California Institute of Technology, Pasadena, CA 91125 (United States); Kasliwal, Mansi M. [Cahill Center for Astrophysics, California Institute of Technology, Pasadena, CA 91125 (United States); Nissanke, Samaya [Institute of Mathematics, Astrophysics and Particle Physics, Radboud University, Heyendaalseweg 135, 6525 AJ Nijmegen (Netherlands); Coughlin, Michael [Department of Physics and Astronomy, Harvard University, Cambridge, MA 02138 (United States); Urban, Alex L. [Leonard E. Parker Center for Gravitation, Cosmology, and Astrophysics, University of Wisconsin–Milwaukee, Milwaukee, WI 53201 (United States); Vitale, Salvatore; Mohapatra, Satya [LIGO Laboratory, Massachusetts Institute of Technology, 185 Albany Street, Cambridge, MA 02139 (United States); Graff, Philip [Department of Physics, University of Maryland, College Park, MD 20742 (United States)

2016-09-01

This is a supplement to the Letter of Singer et al., in which we demonstrated a rapid algorithm for obtaining joint 3D estimates of sky location and luminosity distance from observations of binary neutron star mergers with Advanced LIGO and Virgo. We argued that combining the reconstructed volumes with positions and redshifts of possible host galaxies can provide large-aperture but small field of view instruments with a manageable list of targets to search for optical or infrared emission. In this Supplement, we document the new HEALPix-based file format for 3D localizations of gravitational-wave transients. We include Python sample code to show the reader how to perform simple manipulations of the 3D sky maps and extract ranked lists of likely host galaxies. Finally, we include mathematical details of the rapid volume reconstruction algorithm.

Physical activity of the selected nearly isotropic comets with perihelia at large heliocentric distance

Science.gov (United States)

Kulyk, I.; Rousselot, P.; Korsun, P. P.; Afanasiev, V. L.; Sergeev, A. V.; Velichko, S. F.

2018-03-01

Context. The systematic investigation of comets in a wide range of heliocentric distances can contribute to a better understanding of the physical mechanisms that trigger activity at large distances from the Sun and reveals possible differences in the composition of outer solar system bodies belonging to various dynamical groups. Aims: We seek to analyze the dust environment of the selected nearly isotropic comets with a perihelion distance between 4.5 and 9.1 au, where sublimation of water ice is considered to be negligible. Methods: We present results of multicolor broadband photometric observations for 14 distant active objects conducted between 2008 and 2015 with various telescopes. Images obtained with broadband filters were used to investigate optical colors of the cometary comae and to quantify physical activity of the comet nuclei. Results: The activity level was estimated with Afρ parameters ranging between 95 ± 10 cm and 9600 ± 300 cm. Three returning comets were less active than the dynamically new comets. Dust production rates of the comet nuclei were estimated between 1 and 100 kg s-1 based on some assumptions about the physical properties of dust particles populating comae. The measured colors point out reddening of the continuum for all the comets. The mean values of a normalized reflectivity gradient within the group of the comets amount to 14 ± 2% per 1000 Å and 3 ± 2% per 1000 Å in the BV and VR spectral domains, respectively. The comae of the dynamically new comets, which were observed on their inbound legs, may be slightly redder in the blue spectral interval than comae of the comets observed after the perihelion passages. The dynamically new comets observed both pre- and post-perihelion, seem to have higher production rates post-perihelion than pre-perihelion for similar heliocentric distances.

I-distance and separability coefficient in business evaluation of SME's in agribusiness

Directory of Open Access Journals (Sweden)

Popović Blaženka

2016-01-01

Full Text Available Systematic and continuous process of measuring and comparing business results of companies regarding to business results of leaders, in order to obtain information that will help the company to take action to improve its performance, is in a function of improving business operations. Accordingly, the first objective of this paper is, based on the coefficient of separability, to determine which indicators of business conditions and business results have the greatest impact on differences in the business operations of the observed SMEs operating in the food industry. The second objective of this work is to make the ranking of companies based on the business conditions and business results using discriminant analysis (I-distance, and then, to determine the overall rank of companies using general ranking coefficient (Ker. The results show that companies are significantly separated according to business results rather than to business conditions, and in addition, the business results also had a crucial impact on the overall rank of each company.

Analysis of large soil samples for actinides

Science.gov (United States)

Maxwell, III; Sherrod, L [Aiken, SC

2009-03-24

A method of analyzing relatively large soil samples for actinides by employing a separation process that includes cerium fluoride precipitation for removing the soil matrix and precipitates plutonium, americium, and curium with cerium and hydrofluoric acid followed by separating these actinides using chromatography cartridges.

Multiple graph regularized protein domain ranking.

Science.gov (United States)

Wang, Jim Jing-Yan; Bensmail, Halima; Gao, Xin

2012-11-19

Protein domain ranking is a fundamental task in structural biology. Most protein domain ranking methods rely on the pairwise comparison of protein domains while neglecting the global manifold structure of the protein domain database. Recently, graph regularized ranking that exploits the global structure of the graph defined by the pairwise similarities has been proposed. However, the existing graph regularized ranking methods are very sensitive to the choice of the graph model and parameters, and this remains a difficult problem for most of the protein domain ranking methods. To tackle this problem, we have developed the Multiple Graph regularized Ranking algorithm, MultiG-Rank. Instead of using a single graph to regularize the ranking scores, MultiG-Rank approximates the intrinsic manifold of protein domain distribution by combining multiple initial graphs for the regularization. Graph weights are learned with ranking scores jointly and automatically, by alternately minimizing an objective function in an iterative algorithm. Experimental results on a subset of the ASTRAL SCOP protein domain database demonstrate that MultiG-Rank achieves a better ranking performance than single graph regularized ranking methods and pairwise similarity based ranking methods. The problem of graph model and parameter selection in graph regularized protein domain ranking can be solved effectively by combining multiple graphs. This aspect of generalization introduces a new frontier in applying multiple graphs to solving protein domain ranking applications.

Characterizing the zenithal night sky brightness in large territories: how many samples per square kilometre are needed?

Science.gov (United States)

Bará, Salvador

2018-01-01

A recurring question arises when trying to characterize, by means of measurements or theoretical calculations, the zenithal night sky brightness throughout a large territory: how many samples per square kilometre are needed? The optimum sampling distance should allow reconstructing, with sufficient accuracy, the continuous zenithal brightness map across the whole region, whilst at the same time avoiding unnecessary and redundant oversampling. This paper attempts to provide some tentative answers to this issue, using two complementary tools: the luminance structure function and the Nyquist-Shannon spatial sampling theorem. The analysis of several regions of the world, based on the data from the New world atlas of artificial night sky brightness, suggests that, as a rule of thumb, about one measurement per square kilometre could be sufficient for determining the zenithal night sky brightness of artificial origin at any point in a region to within ±0.1 magV arcsec-2 (in the root-mean-square sense) of its true value in the Johnson-Cousins V band. The exact reconstruction of the zenithal night sky brightness maps from samples taken at the Nyquist rate seems to be considerably more demanding.

Eating disorders and health in elite women distance runners.

Science.gov (United States)

Hulley, A J; Hill, A J

2001-11-01

To examine the presence of eating disorder syndromes in elite women distance runners in the United Kingdom and any associated differences in training, dieting, general health, and well-being. Athletes were selected from the top of their respective ranking lists for all middle and long-distance races in 1996/1997. All running disciplines were included (track, road, cross-country, and fell/mountain running). Athletes were sent the Eating Disorders Examination Questionnaire and a questionnaire on demographics, athletic training, diet, and health. Of the 226 athletes identified, 181 (81%) completed and returned the questionnaires. Twenty-nine athletes (16%) had an eating disorder at the time of the study (7 had anorexia nervosa [AN], 2 had bulimia nervosa [BN], and 20 had eating disorders not otherwise specified [EDNOS]) and a further 6 had received previous treatment. Comparing the eating disorder group with the rest of the sample showed no difference in age, height, preferred race distance, or the number of hours/week spent training. However, they had a significantly lower body mass index (BMI), lower self-esteem, and poorer mental health. Current and past dieting were significantly more common in the eating disorder group. The levels of AN and EDNOS are higher than would be expected in similarly aged, nonathletic women. The demands for leanness rather than exercise intensity appear to be the main risk in these elite runners. The early detection and prevention of eating disorders in women athletes should have high priority. Copyright 2001 by John Wiley & Sons, Inc.

Environmental and health hazard ranking and assessment of plastic polymers based on chemical composition

Energy Technology Data Exchange (ETDEWEB)

Lithner, Delilah, E-mail: delilah.lithner@gmail.com; Larsson, Ake; Dave, Goeran

2011-08-15

Plastics constitute a large material group with a global annual production that has doubled in 15 years (245 million tonnes in 2008). Plastics are present everywhere in society and the environment, especially the marine environment, where large amounts of plastic waste accumulate. The knowledge of human and environmental hazards and risks from chemicals associated with the diversity of plastic products is very limited. Most chemicals used for producing plastic polymers are derived from non-renewable crude oil, and several are hazardous. These may be released during the production, use and disposal of the plastic product. In this study the environmental and health hazards of chemicals used in 55 thermoplastic and thermosetting polymers were identified and compiled. A hazard ranking model was developed for the hazard classes and categories in the EU classification and labelling (CLP) regulation which is based on the UN Globally Harmonized System. The polymers were ranked based on monomer hazard classifications, and initial assessments were made. The polymers that ranked as most hazardous are made of monomers classified as mutagenic and/or carcinogenic (category 1A or 1B). These belong to the polymer families of polyurethanes, polyacrylonitriles, polyvinyl chloride, epoxy resins, and styrenic copolymers. All have a large global annual production (1-37 million tonnes). A considerable number of polymers (31 out of 55) are made of monomers that belong to the two worst of the ranking model's five hazard levels, i.e. levels IV-V. The polymers that are made of level IV monomers and have a large global annual production (1-5 million tonnes) are phenol formaldehyde resins, unsaturated polyesters, polycarbonate, polymethyl methacrylate, and urea-formaldehyde resins. This study has identified hazardous substances used in polymer production for which the risks should be evaluated for decisions on the need for risk reduction measures, substitution, or even phase out

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

Science.gov (United States)

Tian, Yuling; Zhang, Hongxian

2016-01-01

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

Multiplex PageRank.

Directory of Open Access Journals (Sweden)

Arda Halu

Full Text Available Many complex systems can be described as multiplex networks in which the same nodes can interact with one another in different layers, thus forming a set of interacting and co-evolving networks. Examples of such multiplex systems are social networks where people are involved in different types of relationships and interact through various forms of communication media. The ranking of nodes in multiplex networks is one of the most pressing and challenging tasks that research on complex networks is currently facing. When pairs of nodes can be connected through multiple links and in multiple layers, the ranking of nodes should necessarily reflect the importance of nodes in one layer as well as their importance in other interdependent layers. In this paper, we draw on the idea of biased random walks to define the Multiplex PageRank centrality measure in which the effects of the interplay between networks on the centrality of nodes are directly taken into account. In particular, depending on the intensity of the interaction between layers, we define the Additive, Multiplicative, Combined, and Neutral versions of Multiplex PageRank, and show how each version reflects the extent to which the importance of a node in one layer affects the importance the node can gain in another layer. We discuss these measures and apply them to an online multiplex social network. Findings indicate that taking the multiplex nature of the network into account helps uncover the emergence of rankings of nodes that differ from the rankings obtained from one single layer. Results provide support in favor of the salience of multiplex centrality measures, like Multiplex PageRank, for assessing the prominence of nodes embedded in multiple interacting networks, and for shedding a new light on structural properties that would otherwise remain undetected if each of the interacting networks were analyzed in isolation.

Multiplex PageRank.

Science.gov (United States)

Halu, Arda; Mondragón, Raúl J; Panzarasa, Pietro; Bianconi, Ginestra

2013-01-01

Many complex systems can be described as multiplex networks in which the same nodes can interact with one another in different layers, thus forming a set of interacting and co-evolving networks. Examples of such multiplex systems are social networks where people are involved in different types of relationships and interact through various forms of communication media. The ranking of nodes in multiplex networks is one of the most pressing and challenging tasks that research on complex networks is currently facing. When pairs of nodes can be connected through multiple links and in multiple layers, the ranking of nodes should necessarily reflect the importance of nodes in one layer as well as their importance in other interdependent layers. In this paper, we draw on the idea of biased random walks to define the Multiplex PageRank centrality measure in which the effects of the interplay between networks on the centrality of nodes are directly taken into account. In particular, depending on the intensity of the interaction between layers, we define the Additive, Multiplicative, Combined, and Neutral versions of Multiplex PageRank, and show how each version reflects the extent to which the importance of a node in one layer affects the importance the node can gain in another layer. We discuss these measures and apply them to an online multiplex social network. Findings indicate that taking the multiplex nature of the network into account helps uncover the emergence of rankings of nodes that differ from the rankings obtained from one single layer. Results provide support in favor of the salience of multiplex centrality measures, like Multiplex PageRank, for assessing the prominence of nodes embedded in multiple interacting networks, and for shedding a new light on structural properties that would otherwise remain undetected if each of the interacting networks were analyzed in isolation.

Multiple graph regularized protein domain ranking

KAUST Repository

Wang, Jim Jing-Yan

2012-11-19

Background: Protein domain ranking is a fundamental task in structural biology. Most protein domain ranking methods rely on the pairwise comparison of protein domains while neglecting the global manifold structure of the protein domain database. Recently, graph regularized ranking that exploits the global structure of the graph defined by the pairwise similarities has been proposed. However, the existing graph regularized ranking methods are very sensitive to the choice of the graph model and parameters, and this remains a difficult problem for most of the protein domain ranking methods.Results: To tackle this problem, we have developed the Multiple Graph regularized Ranking algorithm, MultiG-Rank. Instead of using a single graph to regularize the ranking scores, MultiG-Rank approximates the intrinsic manifold of protein domain distribution by combining multiple initial graphs for the regularization. Graph weights are learned with ranking scores jointly and automatically, by alternately minimizing an objective function in an iterative algorithm. Experimental results on a subset of the ASTRAL SCOP protein domain database demonstrate that MultiG-Rank achieves a better ranking performance than single graph regularized ranking methods and pairwise similarity based ranking methods.Conclusion: The problem of graph model and parameter selection in graph regularized protein domain ranking can be solved effectively by combining multiple graphs. This aspect of generalization introduces a new frontier in applying multiple graphs to solving protein domain ranking applications. 2012 Wang et al; licensee BioMed Central Ltd.

Multiple graph regularized protein domain ranking

KAUST Repository

Wang, Jim Jing-Yan; Bensmail, Halima; Gao, Xin

2012-01-01

Background: Protein domain ranking is a fundamental task in structural biology. Most protein domain ranking methods rely on the pairwise comparison of protein domains while neglecting the global manifold structure of the protein domain database. Recently, graph regularized ranking that exploits the global structure of the graph defined by the pairwise similarities has been proposed. However, the existing graph regularized ranking methods are very sensitive to the choice of the graph model and parameters, and this remains a difficult problem for most of the protein domain ranking methods.Results: To tackle this problem, we have developed the Multiple Graph regularized Ranking algorithm, MultiG-Rank. Instead of using a single graph to regularize the ranking scores, MultiG-Rank approximates the intrinsic manifold of protein domain distribution by combining multiple initial graphs for the regularization. Graph weights are learned with ranking scores jointly and automatically, by alternately minimizing an objective function in an iterative algorithm. Experimental results on a subset of the ASTRAL SCOP protein domain database demonstrate that MultiG-Rank achieves a better ranking performance than single graph regularized ranking methods and pairwise similarity based ranking methods.Conclusion: The problem of graph model and parameter selection in graph regularized protein domain ranking can be solved effectively by combining multiple graphs. This aspect of generalization introduces a new frontier in applying multiple graphs to solving protein domain ranking applications. 2012 Wang et al; licensee BioMed Central Ltd.

Multiple graph regularized protein domain ranking

Directory of Open Access Journals (Sweden)

Wang Jim

2012-11-01

Full Text Available Abstract Background Protein domain ranking is a fundamental task in structural biology. Most protein domain ranking methods rely on the pairwise comparison of protein domains while neglecting the global manifold structure of the protein domain database. Recently, graph regularized ranking that exploits the global structure of the graph defined by the pairwise similarities has been proposed. However, the existing graph regularized ranking methods are very sensitive to the choice of the graph model and parameters, and this remains a difficult problem for most of the protein domain ranking methods. Results To tackle this problem, we have developed the Multiple Graph regularized Ranking algorithm, MultiG-Rank. Instead of using a single graph to regularize the ranking scores, MultiG-Rank approximates the intrinsic manifold of protein domain distribution by combining multiple initial graphs for the regularization. Graph weights are learned with ranking scores jointly and automatically, by alternately minimizing an objective function in an iterative algorithm. Experimental results on a subset of the ASTRAL SCOP protein domain database demonstrate that MultiG-Rank achieves a better ranking performance than single graph regularized ranking methods and pairwise similarity based ranking methods. Conclusion The problem of graph model and parameter selection in graph regularized protein domain ranking can be solved effectively by combining multiple graphs. This aspect of generalization introduces a new frontier in applying multiple graphs to solving protein domain ranking applications.

Improving Ranking Using Quantum Probability

OpenAIRE

Melucci, Massimo

2011-01-01

The paper shows that ranking information units by quantum probability differs from ranking them by classical probability provided the same data used for parameter estimation. As probability of detection (also known as recall or power) and probability of false alarm (also known as fallout or size) measure the quality of ranking, we point out and show that ranking by quantum probability yields higher probability of detection than ranking by classical probability provided a given probability of ...

Ranking Thinning Potential of Lodgepole Pine Stands

OpenAIRE

United States Department of Agriculture, Forest Service

1987-01-01

This paper presents models for predicting edge-response of dominant and codominant trees to clearing. Procedures are given for converting predictions to a thinning response index, for ranking stands for thinning priority. Data requirements, sampling suggestions, examples of application, and suggestions for management use are included to facilitate use as a field guide.

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

Science.gov (United States)

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

2011-03-15

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

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

Directory of Open Access Journals (Sweden)

Hsieh Fushing

2011-03-01

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

Power and sample size evaluation for the Cochran-Mantel-Haenszel mean score (Wilcoxon rank sum) test and the Cochran-Armitage test for trend.

Science.gov (United States)

Lachin, John M

2011-11-10

The power of a chi-square test, and thus the required sample size, are a function of the noncentrality parameter that can be obtained as the limiting expectation of the test statistic under an alternative hypothesis specification. Herein, we apply this principle to derive simple expressions for two tests that are commonly applied to discrete ordinal data. The Wilcoxon rank sum test for the equality of distributions in two groups is algebraically equivalent to the Mann-Whitney test. The Kruskal-Wallis test applies to multiple groups. These tests are equivalent to a Cochran-Mantel-Haenszel mean score test using rank scores for a set of C-discrete categories. Although various authors have assessed the power function of the Wilcoxon and Mann-Whitney tests, herein it is shown that the power of these tests with discrete observations, that is, with tied ranks, is readily provided by the power function of the corresponding Cochran-Mantel-Haenszel mean scores test for two and R > 2 groups. These expressions yield results virtually identical to those derived previously for rank scores and also apply to other score functions. The Cochran-Armitage test for trend assesses whether there is an monotonically increasing or decreasing trend in the proportions with a positive outcome or response over the C-ordered categories of an ordinal independent variable, for example, dose. Herein, it is shown that the power of the test is a function of the slope of the response probabilities over the ordinal scores assigned to the groups that yields simple expressions for the power of the test. Copyright © 2011 John Wiley & Sons, Ltd.

Neophilia Ranking of Scientific Journals.

Science.gov (United States)

Packalen, Mikko; Bhattacharya, Jay

2017-01-01

The ranking of scientific journals is important because of the signal it sends to scientists about what is considered most vital for scientific progress. Existing ranking systems focus on measuring the influence of a scientific paper (citations)-these rankings do not reward journals for publishing innovative work that builds on new ideas. We propose an alternative ranking based on the proclivity of journals to publish papers that build on new ideas, and we implement this ranking via a text-based analysis of all published biomedical papers dating back to 1946. In addition, we compare our neophilia ranking to citation-based (impact factor) rankings; this comparison shows that the two ranking approaches are distinct. Prior theoretical work suggests an active role for our neophilia index in science policy. Absent an explicit incentive to pursue novel science, scientists underinvest in innovative work because of a coordination problem: for work on a new idea to flourish, many scientists must decide to adopt it in their work. Rankings that are based purely on influence thus do not provide sufficient incentives for publishing innovative work. By contrast, adoption of the neophilia index as part of journal-ranking procedures by funding agencies and university administrators would provide an explicit incentive for journals to publish innovative work and thus help solve the coordination problem by increasing scientists' incentives to pursue innovative work.

GLOBALIZATION, INFORMATION AND COMMUNICATION TECHNOLOGIES (ICTs AND OPEN/DISTANCE LEARNING IN NIGERIA: Trends, Issues and Solution

Directory of Open Access Journals (Sweden)

Akande Joshua OLUSOLA

2011-07-01

Full Text Available The main thrust of this paper is to discuss the development of open and distance education in Nigeria and the major manifestations of the use of information and communication technologies (ICTs in education in open and distance learning. This study further discusses the importance and use of ICTs in open and distance learning in making education accessible to a larger population of students. From that vantage point this paper reviews the phenomenon of ICTs in open and distance learning in developing countries such as Nigeria. The paper identifies a number of issues that impede the effective optimization of ICTs in open and distance learning in developing countries. Prominent among the issues highlighted are poverty, intermittent supply of electricity and language barrier. The paper argues that these problems are to be tackled if the objective of enhancing the potentials of ICTs in open and distance learning in developing countries were to be achieved. On that note the current paper makes some humble suggestions on how to curtail the problems. The study employed descriptive method. An intact class of students that registered for the Bachelor of Education distance learning programme of the Faculty of Education of the Obafemi Awolowo University,Ile-Ife formed the samples used for the study. This was done to collect information on the factors affecting usage of ICT. The result shows that lack of skills rank highest (46.1%, following this is non availability of ICT at home (18.8%, costs (11.3% and non familiarity with ICT (10.6%.

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

International Nuclear Information System (INIS)

Pollock, D.

1992-01-01

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

Ranking prediction model using the competition record of Ladies Professional Golf Association players.

Science.gov (United States)

Chae, Jin Seok; Park, Jin; So, Wi-Young

2017-07-28

The purpose of this study was to suggest a ranking prediction model using the competition record of the Ladies Professional Golf Association (LPGA) players. The top 100 players on the tour money list from the 2013-2016 US Open were analyzed in this model. Stepwise regression analysis was conducted to examine the effect of performance and independent variables (i.e., driving accuracy, green in regulation, putts per round, driving distance, percentage of sand saves, par-3 average, par-4 average, par-5 average, birdies average, and eagle average) on dependent variables (i.e., scoring average, official money, top-10 finishes, winning percentage, and 60-strokes average). The following prediction model was suggested:Y (Scoring average) = 55.871 - 0.947 (Birdies average) + 4.576 (Par-4 average) - 0.028 (Green in regulation) - 0.012 (Percentage of sand saves) + 2.088 (Par-3 average) - 0.026 (Driving accuracy) - 0.017 (Driving distance) + 0.085 (Putts per round)Y (Official money) = 6628736.723 + 528557.907 (Birdies average) - 1831800.821 (Par-4 average) + 11681.739 (Green in regulation) + 6476.344 (Percentage of sand saves) - 688115.074 (Par-3 average) + 7375.971 (Driving accuracy)Y (Top-10 finish%) = 204.462 + 12.562 (Birdies average) - 47.745 (Par-4 average) + 1.633 (Green in regulation) - 5.151 (Putts per round) + 0.132 (Percentage of sand saves)Y (Winning percentage) = 49.949 + 3.191 (Birdies average) - 15.023 (Par-4 average) + 0.043 (Percentage of sand saves)Y (60-strokes average) = 217.649 + 13.978 (Birdies average) - 44.855 (Par-4 average) - 22.433 (Par-3 average) + 0.16 (Green in regulation)Scoring of the above five prediction models and the prediction of golf ranking in the 2016 Women's Golf Olympic competition in Rio revealed a significant correlation between the predicted and real ranking (r = 0.689, p ranking prediction model using LPGA data may help coaches and players to identify which players are likely to participate in Olympic and World competitions, based

Control charts for location based on different sampling schemes

NARCIS (Netherlands)

Mehmood, R.; Riaz, M.; Does, R.J.M.M.

2013-01-01

Control charts are the most important statistical process control tool for monitoring variations in a process. A number of articles are available in the literature for the X̄ control chart based on simple random sampling, ranked set sampling, median-ranked set sampling (MRSS), extreme-ranked set

Desirability of Outcome Ranking (DOOR) and Response Adjusted for Duration of Antibiotic Risk (RADAR).

Science.gov (United States)

Evans, Scott R; Rubin, Daniel; Follmann, Dean; Pennello, Gene; Huskins, W Charles; Powers, John H; Schoenfeld, David; Chuang-Stein, Christy; Cosgrove, Sara E; Fowler, Vance G; Lautenbach, Ebbing; Chambers, Henry F

2015-09-01

Clinical trials that compare strategies to optimize antibiotic use are of critical importance but are limited by competing risks that distort outcome interpretation, complexities of noninferiority trials, large sample sizes, and inadequate evaluation of benefits and harms at the patient level. The Antibacterial Resistance Leadership Group strives to overcome these challenges through innovative trial design. Response adjusted for duration of antibiotic risk (RADAR) is a novel methodology utilizing a superiority design and a 2-step process: (1) categorizing patients into an overall clinical outcome (based on benefits and harms), and (2) ranking patients with respect to a desirability of outcome ranking (DOOR). DOORs are constructed by assigning higher ranks to patients with (1) better overall clinical outcomes and (2) shorter durations of antibiotic use for similar overall clinical outcomes. DOOR distributions are compared between antibiotic use strategies. The probability that a randomly selected patient will have a better DOOR if assigned to the new strategy is estimated. DOOR/RADAR represents a new paradigm in assessing the risks and benefits of new strategies to optimize antibiotic use. © The Author 2015. Published by Oxford University Press on behalf of the Infectious Diseases Society of America. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

France ranked first for the quality of its electrical power

International Nuclear Information System (INIS)

Anon.

2013-01-01

France has been ranked first among 146 countries for the quality and availability of its electrical power by the Choiseul Institute and KMPG. This classification is made according to 3 categories: first, the quality of the energy mix, secondly quality and availability of the electrical power, and thirdly the environmental footprint. France ranks first for the second category because of its important fleet of nuclear reactors, but ranks 93 for the quality of its energy mix, its poor performance is due to its large dependence on oil as primary energy. The performance of France for the environment footprint is only in the world average for despite is low-carbon electricity production, French households release great quantities of CO 2 . (A.C.)

A Survey on PageRank Computing

OpenAIRE

Berkhin, Pavel

2005-01-01

This survey reviews the research related to PageRank computing. Components of a PageRank vector serve as authority weights for web pages independent of their textual content, solely based on the hyperlink structure of the web. PageRank is typically used as a web search ranking component. This defines the importance of the model and the data structures that underly PageRank processing. Computing even a single PageRank is a difficult computational task. Computing many PageRanks is a much mor...

Multicriterial ranking approach for evaluating bank branch performance

NARCIS (Netherlands)

Aleskerov, F; Ersel, H; Yolalan, R

14 ranking methods based on multiple criteria are suggested for evaluating the performance of the bank branches. The methods are explained via an illustrative example, and some of them are applied to a real-life data for 23 retail bank branches in a large-scale private Turkish commercial bank.

Gibbs sampling on large lattice with GMRF

Science.gov (United States)

Marcotte, Denis; Allard, Denis

2018-02-01

Gibbs sampling is routinely used to sample truncated Gaussian distributions. These distributions naturally occur when associating latent Gaussian fields to category fields obtained by discrete simulation methods like multipoint, sequential indicator simulation and object-based simulation. The latent Gaussians are often used in data assimilation and history matching algorithms. When the Gibbs sampling is applied on a large lattice, the computing cost can become prohibitive. The usual practice of using local neighborhoods is unsatisfying as it can diverge and it does not reproduce exactly the desired covariance. A better approach is to use Gaussian Markov Random Fields (GMRF) which enables to compute the conditional distributions at any point without having to compute and invert the full covariance matrix. As the GMRF is locally defined, it allows simultaneous updating of all points that do not share neighbors (coding sets). We propose a new simultaneous Gibbs updating strategy on coding sets that can be efficiently computed by convolution and applied with an acceptance/rejection method in the truncated case. We study empirically the speed of convergence, the effect of choice of boundary conditions, of the correlation range and of GMRF smoothness. We show that the convergence is slower in the Gaussian case on the torus than for the finite case studied in the literature. However, in the truncated Gaussian case, we show that short scale correlation is quickly restored and the conditioning categories at each lattice point imprint the long scale correlation. Hence our approach enables to realistically apply Gibbs sampling on large 2D or 3D lattice with the desired GMRF covariance.

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

Science.gov (United States)

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

2012-12-01

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

Wikipedia ranking of world universities

Science.gov (United States)

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

2016-03-01

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

Ultra-large distance modification of gravity from Lorentz symmetry breaking at the Planck scale

International Nuclear Information System (INIS)

Gorbunov, Dmitry S.; Sibiryakov, Sergei M.

2005-01-01

We present an extension of the Randall-Sundrum model in which, due to spontaneous Lorentz symmetry breaking, graviton mixes with bulk vector fields and becomes quasilocalized. The masses of KK modes comprising the four-dimensional graviton are naturally exponentially small. This allows to push the Lorentz breaking scale to as high as a few tenth of the Planck mass. The model does not contain ghosts or tachyons and does not exhibit the van Dam-Veltman-Zakharov discontinuity. The gravitational attraction between static point masses becomes gradually weaker with increasing of separation and gets replaced by repulsion (antigravity) at exponentially large distances

Ultra-large distance modification of gravity from Lorentz symmetry breaking at the Planck scale

Energy Technology Data Exchange (ETDEWEB)

Gorbunov, Dmitry S. [Institute for Nuclear Research of the Russian Academy of Sciences, 60th October Anniversary prospect, 7a, 117312 Moscow (Russian Federation); Sibiryakov, Sergei M. [Institute for Nuclear Research of the Russian Academy of Sciences, 60th October Anniversary prospect, 7a, 117312 Moscow (Russian Federation)

2005-09-15

We present an extension of the Randall-Sundrum model in which, due to spontaneous Lorentz symmetry breaking, graviton mixes with bulk vector fields and becomes quasilocalized. The masses of KK modes comprising the four-dimensional graviton are naturally exponentially small. This allows to push the Lorentz breaking scale to as high as a few tenth of the Planck mass. The model does not contain ghosts or tachyons and does not exhibit the van Dam-Veltman-Zakharov discontinuity. The gravitational attraction between static point masses becomes gradually weaker with increasing of separation and gets replaced by repulsion (antigravity) at exponentially large distances.

Does the patient's inherent rating tendency influence reported satisfaction scores and affect division ranking?

Science.gov (United States)

Francis, Patricia; Agoritsas, Thomas; Chopard, Pierre; Perneger, Thomas

2016-04-01

To determine the impact of adjusting for rating tendency (RT) on patient satisfaction scores in a large teaching hospital and to assess the impact of adjustment on the ranking of divisions. Cross-sectional survey. Large 2200-bed university teaching hospital. All adult patients hospitalized during a 1-month period in one of 20 medical divisions. None. Patient experience of care measured by the Picker Patient Experience questionnaire and RT scores. Problem scores were weakly but significantly associated with RT. Division ranking was slightly modified in RT adjusted models. Division ranking changed substantially in case-mix adjusted models. Adjusting patient self-reported problem scores for RT did impact ranking of divisions, although marginally. Further studies are needed to determine the impact of RT when comparing different institutions, particularly across inter-cultural settings, where the difference in RT may be more substantial. © The Author 2016. Published by Oxford University Press in association with the International Society for Quality in Health Care; all rights reserved.

On the dimension of subspaces with bounded Schmidt rank

International Nuclear Information System (INIS)

Cubitt, Toby; Montanaro, Ashley; Winter, Andreas

2008-01-01

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

Wilcoxon's signed-rank statistic: what null hypothesis and why it matters.

Science.gov (United States)

Li, Heng; Johnson, Terri

2014-01-01

In statistical literature, the term 'signed-rank test' (or 'Wilcoxon signed-rank test') has been used to refer to two distinct tests: a test for symmetry of distribution and a test for the median of a symmetric distribution, sharing a common test statistic. To avoid potential ambiguity, we propose to refer to those two tests by different names, as 'test for symmetry based on signed-rank statistic' and 'test for median based on signed-rank statistic', respectively. The utility of such terminological differentiation should become evident through our discussion of how those tests connect and contrast with sign test and one-sample t-test. Published 2014. This article is a U.S. Government work and is in the public domain in the USA. Published 2014. This article is a U.S. Government work and is in the public domain in the USA.

Re-Ranking Sequencing Variants in the Post-GWAS Era for Accurate Causal Variant Identification

Science.gov (United States)

Faye, Laura L.; Machiela, Mitchell J.; Kraft, Peter; Bull, Shelley B.; Sun, Lei

2013-01-01

Next generation sequencing has dramatically increased our ability to localize disease-causing variants by providing base-pair level information at costs increasingly feasible for the large sample sizes required to detect complex-trait associations. Yet, identification of causal variants within an established region of association remains a challenge. Counter-intuitively, certain factors that increase power to detect an associated region can decrease power to localize the causal variant. First, combining GWAS with imputation or low coverage sequencing to achieve the large sample sizes required for high power can have the unintended effect of producing differential genotyping error among SNPs. This tends to bias the relative evidence for association toward better genotyped SNPs. Second, re-use of GWAS data for fine-mapping exploits previous findings to ensure genome-wide significance in GWAS-associated regions. However, using GWAS findings to inform fine-mapping analysis can bias evidence away from the causal SNP toward the tag SNP and SNPs in high LD with the tag. Together these factors can reduce power to localize the causal SNP by more than half. Other strategies commonly employed to increase power to detect association, namely increasing sample size and using higher density genotyping arrays, can, in certain common scenarios, actually exacerbate these effects and further decrease power to localize causal variants. We develop a re-ranking procedure that accounts for these adverse effects and substantially improves the accuracy of causal SNP identification, often doubling the probability that the causal SNP is top-ranked. Application to the NCI BPC3 aggressive prostate cancer GWAS with imputation meta-analysis identified a new top SNP at 2 of 3 associated loci and several additional possible causal SNPs at these loci that may have otherwise been overlooked. This method is simple to implement using R scripts provided on the author's website. PMID:23950724

Distance Education Programs: The Technical Support to Be Successful.

Science.gov (United States)

McNew, Ryan E; Gordon, Jeffry S; Weiner, Elizabeth E; Trangenstein, Patricia

2016-01-01

Academic success requires support on a variety of levels as well as access to contemporary tools and services. Supporting students enrolled in a successful higher education distance learning program, requires a strong, properly trained IT support staff in addition to a stable IT environment. Our distance education program began with a regional market but has grown significantly over the past few years. This is primarily due to the success of our distance education tools and support which have contributed to achieving a ranking of eleventh of best graduate schools in nursing according to the U.S. News and World Report. The entire student population is "Bring Your Own Devices" (BYOD). Critical to this support is the initial configuration and loading of needed software during the first week of orientation. All of this success requires a robust team of members prepared in a range of skill sets from networking to instructional design.

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

DEFF Research Database (Denmark)

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

2013-01-01

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

Bayesian CP Factorization of Incomplete Tensors with Automatic Rank Determination.

Science.gov (United States)

Zhao, Qibin; Zhang, Liqing; Cichocki, Andrzej

2015-09-01

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

TEACHERS’ EDUCATIONAL QUALIFICATION, RANK LEVEL, WORKING DURATION, AGE, WORK MOTIVATION AND WORK EFFECTIVENESS

Directory of Open Access Journals (Sweden)

Bambang Budi Wiyono

2016-02-01

Full Text Available Teachers’ Educational Qualification, Rank Level, Working Duration, Age, Working Mo­tivation, and Working Effectiveness The study investigated the effects of educational qualification, rank level, working duration and age on the elementary school teachers’ working motivation and working ef­fectiveness. The sample of the study consisted of 438 elementary school teachers in Malang which were selected through cluster sampling technique. The study was conducted using explanatory design in the form of causal model. The data were collected using questionnaire and documentation, and were analyzed descrip­tively employing structural equation technique. The study revealed that that the effect of the educational qualification, rank level, working duration and age on teachers’ working motivation and working effec­tiveness, both directly and indirectly, was not significant.

Distance determinations to shield galaxies from Hubble space telescope imaging

Energy Technology Data Exchange (ETDEWEB)

McQuinn, Kristen B. W.; Skillman, Evan D. [Minnesota Institute for Astrophysics, School of Physics and Astronomy, University of Minnesota, 116 Church Street, S.E., Minneapolis, MN 55455 (United States); Cannon, John M.; Cave, Ian [Department of Physics and Astronomy, Macalester College, 1600 Grand Avenue, Saint Paul, MN 55105 (United States); Dolphin, Andrew E. [Raytheon Company, 1151 E. Hermans Road, Tucson, AZ 85756 (United States); Salzer, John J. [Department of Astronomy, Indiana University, 727 East 3rd Street, Bloomington, IN 47405 (United States); Haynes, Martha P.; Adams, Elizabeth; Giovanelli, Riccardo [Center for Radiophysics and Space Research, Space Sciences Building, Cornell University, Ithaca, NY 14853 (United States); Elson, Ed C. [Astrophysics, Cosmology and Gravity Centre (ACGC), Department of Astronomy, University of Cape Town, Private Bag X3, Rondebosch 7701 (South Africa); Ott, Juërgen [National Radio Astronomy Observatory, P.O. Box O, 1003 Lopezville Road, Socorro, NM 87801 (United States); Saintonge, Amélie, E-mail: kmcquinn@astro.umn.edu [Max-Planck-Institute for Astrophysics, D-85741 Garching (Germany)

2014-04-10

The Survey of H I in Extremely Low-mass Dwarf (SHIELD) galaxies is an ongoing multi-wavelength program to characterize the gas, star formation, and evolution in gas-rich, very low-mass galaxies. The galaxies were selected from the first ∼10% of the H I Arecibo Legacy Fast ALFA (ALFALFA) survey based on their inferred low H I mass and low baryonic mass, and all systems have recent star formation. Thus, the SHIELD sample probes the faint end of the galaxy luminosity function for star-forming galaxies. Here, we measure the distances to the 12 SHIELD galaxies to be between 5 and 12 Mpc by applying the tip of the red giant method to the resolved stellar populations imaged by the Hubble Space Telescope. Based on these distances, the H I masses in the sample range from 4 × 10{sup 6} to 6 × 10{sup 7} M {sub ☉}, with a median H I mass of 1 × 10{sup 7} M {sub ☉}. The tip of the red giant branch distances are up to 73% farther than flow-model estimates in the ALFALFA catalog. Because of the relatively large uncertainties of flow-model distances, we are biased toward selecting galaxies from the ALFALFA catalog where the flow model underestimates the true distances. The measured distances allow for an assessment of the native environments around the sample members. Five of the galaxies are part of the NGC 672 and NGC 784 groups, which together constitute a single structure. One galaxy is part of a larger linear ensemble of nine systems that stretches 1.6 Mpc from end to end. Three galaxies reside in regions with 1-9 neighbors, and four galaxies are truly isolated with no known system identified within a radius of 1 Mpc.

On low-rank updates to the singular value and Tucker decompositions

Energy Technology Data Exchange (ETDEWEB)

O' Hara, M J

2009-10-06

The singular value decomposition is widely used in signal processing and data mining. Since the data often arrives in a stream, the problem of updating matrix decompositions under low-rank modification has been widely studied. Brand developed a technique in 2006 that has many advantages. However, the technique does not directly approximate the updated matrix, but rather its previous low-rank approximation added to the new update, which needs justification. Further, the technique is still too slow for large information processing problems. We show that the technique minimizes the change in error per update, so if the error is small initially it remains small. We show that an updating algorithm for large sparse matrices should be sub-linear in the matrix dimension in order to be practical for large problems, and demonstrate a simple modification to the original technique that meets the requirements.

Using Bibliographic Knowledge for Ranking in Scientific Publication Databases

CERN Document Server

Vesely, Martin; Le Meur, Jean-Yves

2008-01-01

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

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

Science.gov (United States)

Eisinga, Rob; Breitling, Rainer; Heskes, Tom

2013-03-18

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

Large Sample Neutron Activation Analysis: A Challenge in Cultural Heritage Studies

International Nuclear Information System (INIS)

Stamatelatos, I.E.; Tzika, F.

2007-01-01

Large sample neutron activation analysis compliments and significantly extends the analytical tools available for cultural heritage and authentication studies providing unique applications of non-destructive, multi-element analysis of materials that are too precious to damage for sampling purposes, representative sampling of heterogeneous materials or even analysis of whole objects. In this work, correction factors for neutron self-shielding, gamma-ray attenuation and volume distribution of the activity in large volume samples composed of iron and ceramic material were derived. Moreover, the effect of inhomogeneity on the accuracy of the technique was examined

University Rankings and Social Science

OpenAIRE

Marginson, S.

2014-01-01

University rankings widely affect the behaviours of prospective students and their families, university executive leaders, academic faculty, governments and investors in higher education. Yet the social science foundations of global rankings receive little scrutiny. Rankings that simply recycle reputation without any necessary connection to real outputs are of no common value. It is necessary that rankings be soundly based in scientific terms if a virtuous relationship between performance and...

Charting taxonomic knowledge through ontologies and ranking algorithms

Science.gov (United States)

Huber, Robert; Klump, Jens

2009-04-01

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

Inflation of type I error rates by unequal variances associated with parametric, nonparametric, and Rank-Transformation Tests

Directory of Open Access Journals (Sweden)

Donald W. Zimmerman

2004-01-01

Full Text Available It is well known that the two-sample Student t test fails to maintain its significance level when the variances of treatment groups are unequal, and, at the same time, sample sizes are unequal. However, introductory textbooks in psychology and education often maintain that the test is robust to variance heterogeneity when sample sizes are equal. The present study discloses that, for a wide variety of non-normal distributions, especially skewed distributions, the Type I error probabilities of both the t test and the Wilcoxon-Mann-Whitney test are substantially inflated by heterogeneous variances, even when sample sizes are equal. The Type I error rate of the t test performed on ranks replacing the scores (rank-transformed data is inflated in the same way and always corresponds closely to that of the Wilcoxon-Mann-Whitney test. For many probability densities, the distortion of the significance level is far greater after transformation to ranks and, contrary to known asymptotic properties, the magnitude of the inflation is an increasing function of sample size. Although nonparametric tests of location also can be sensitive to differences in the shape of distributions apart from location, the Wilcoxon-Mann-Whitney test and rank-transformation tests apparently are influenced mainly by skewness that is accompanied by specious differences in the means of ranks.

24 CFR 599.401 - Ranking of applications.

Science.gov (United States)

2010-04-01

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

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

Science.gov (United States)

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

2016-11-01

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

On Page Rank

NARCIS (Netherlands)

Hoede, C.

In this paper the concept of page rank for the world wide web is discussed. The possibility of describing the distribution of page rank by an exponential law is considered. It is shown that the concept is essentially equal to that of status score, a centrality measure discussed already in 1953 by

Citation graph based ranking in Invenio

CERN Document Server

Marian, Ludmila; Rajman, Martin; Vesely, Martin

2010-01-01

Invenio is the web-based integrated digital library system developed at CERN. Within this framework, we present four types of ranking models based on the citation graph that complement the simple approach based on citation counts: time-dependent citation counts, a relevancy ranking which extends the PageRank model, a time-dependent ranking which combines the freshness of citations with PageRank and a ranking that takes into consideration the external citations. We present our analysis and results obtained on two main data sets: Inspire and CERN Document Server. Our main contributions are: (i) a study of the currently available ranking methods based on the citation graph; (ii) the development of new ranking methods that correct some of the identified limitations of the current methods such as treating all citations of equal importance, not taking time into account or considering the citation graph complete; (iii) a detailed study of the key parameters for these ranking methods. (The original publication is ava...

Equivalence of massive propagator distance and mathematical distance on graphs

International Nuclear Information System (INIS)

Filk, T.

1992-01-01

It is shown in this paper that the assignment of distance according to the massive propagator method and according to the mathematical definition (length of minimal path) on arbitrary graphs with a bound on the degree leads to equivalent large scale properties of the graph. Especially, the internal scaling dimension is the same for both definitions. This result holds for any fixed, non-vanishing mass, so that a really inequivalent definition of distance requires the limit m → 0

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

KAUST Repository

Wang, Jim Jing-Yan

2017-06-28

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

University Rankings: The Web Ranking

Science.gov (United States)

Aguillo, Isidro F.

2012-01-01

The publication in 2003 of the Ranking of Universities by Jiao Tong University of Shanghai has revolutionized not only academic studies on Higher Education, but has also had an important impact on the national policies and the individual strategies of the sector. The work gathers the main characteristics of this and other global university…

A guide to the use of distance sampling to estimate abundance of Karner blue butterflies

Science.gov (United States)

Grundel, Ralph

2015-01-01

This guide is intended to describe the use of distance sampling as a method for evaluating the abundance of Karner blue butterflies at a location. Other methods for evaluating abundance exist, including mark-release-recapture and index counts derived from Pollard-Yates surveys, for example. Although this guide is not intended to be a detailed comparison of the pros and cons of each type of method, there are important preliminary considerations to think about before selecting any method for evaluating the abundance of Karner blue butterflies.

Ranking Specific Sets of Objects.

Science.gov (United States)

Maly, Jan; Woltran, Stefan

2017-01-01

Ranking sets of objects based on an order between the single elements has been thoroughly studied in the literature. In particular, it has been shown that it is in general impossible to find a total ranking - jointly satisfying properties as dominance and independence - on the whole power set of objects. However, in many applications certain elements from the entire power set might not be required and can be neglected in the ranking process. For instance, certain sets might be ruled out due to hard constraints or are not satisfying some background theory. In this paper, we treat the computational problem whether an order on a given subset of the power set of elements satisfying different variants of dominance and independence can be found, given a ranking on the elements. We show that this problem is tractable for partial rankings and NP-complete for total rankings.

Identifying multiple influential spreaders in term of the distance-based coloring

Energy Technology Data Exchange (ETDEWEB)

Guo, Lei; Lin, Jian-Hong; Guo, Qiang [Research Center of Complex Systems Science, University of Shanghai for Science and Technology, Shanghai 200093 (China); Liu, Jian-Guo, E-mail: liujg004@ustc.edu.cn [Research Center of Complex Systems Science, University of Shanghai for Science and Technology, Shanghai 200093 (China); Data Science and Cloud Service Research Centre, Shanghai University of Finance and Economics, Shanghai 200433 (China)

2016-02-22

Identifying influential nodes is of significance for understanding the dynamics of information diffusion process in complex networks. In this paper, we present an improved distance-based coloring method to identify the multiple influential spreaders. In our method, each node is colored by a kind of color with the rule that the distance between initial nodes is close to the average distance of a network. When all nodes are colored, nodes with the same color are sorted into an independent set. Then we choose the nodes at the top positions of the ranking list according to their centralities. The experimental results for an artificial network and three empirical networks show that, comparing with the performance of traditional coloring method, the improvement ratio of our distance-based coloring method could reach 12.82%, 8.16%, 4.45%, 2.93% for the ER, Erdős, Polblogs and Routers networks respectively. - Highlights: • We present an improved distance-based coloring method to identify the multiple influential spreaders. • Each node is colored by a kind of color where the distance between initial nodes is close to the average distance. • For three empirical networks show that the improvement ratio of our distance-based coloring method could reach 8.16% for the Erdos network.

Identifying multiple influential spreaders in term of the distance-based coloring

International Nuclear Information System (INIS)

Guo, Lei; Lin, Jian-Hong; Guo, Qiang; Liu, Jian-Guo

2016-01-01

Identifying influential nodes is of significance for understanding the dynamics of information diffusion process in complex networks. In this paper, we present an improved distance-based coloring method to identify the multiple influential spreaders. In our method, each node is colored by a kind of color with the rule that the distance between initial nodes is close to the average distance of a network. When all nodes are colored, nodes with the same color are sorted into an independent set. Then we choose the nodes at the top positions of the ranking list according to their centralities. The experimental results for an artificial network and three empirical networks show that, comparing with the performance of traditional coloring method, the improvement ratio of our distance-based coloring method could reach 12.82%, 8.16%, 4.45%, 2.93% for the ER, Erdős, Polblogs and Routers networks respectively. - Highlights: • We present an improved distance-based coloring method to identify the multiple influential spreaders. • Each node is colored by a kind of color where the distance between initial nodes is close to the average distance. • For three empirical networks show that the improvement ratio of our distance-based coloring method could reach 8.16% for the Erdos network.

Does Distance to Subsidiaries affect Headquarters Value Added?

DEFF Research Database (Denmark)

Nell, Phillip C.; Beugelsdijk, Sjoerd; Ambos, Björn

2014-01-01

How does distance between MNC headquarters and their subsidiaries affect the value added generated by headquarters? Integrating theories on spatial transaction costs with the headquarter view of the MNC, we link two types of distances, geographic distance and contextual distance, with headquarters...... value added. We test our hypotheses on an original dataset of 124 manufacturing subsidiaries in Europe. We find that the relation between distance and headquarters value added is conditional on the degree of subsidiaries’ external embeddedness. We find no direct effect of distance. The value added...... of headquarters is highest for subsidiaries that are not externally embedded in the host country and that operate at a large distance. It is lowest for locally responsive subsidiaries with high external embeddedness operating at a large distance. We discuss implications for the literature on headquarters-subsidiaries...

Rank Order Coding: a Retinal Information Decoding Strategy Revealed by Large-Scale Multielectrode Array Retinal Recordings.

Science.gov (United States)

Portelli, Geoffrey; Barrett, John M; Hilgen, Gerrit; Masquelier, Timothée; Maccione, Alessandro; Di Marco, Stefano; Berdondini, Luca; Kornprobst, Pierre; Sernagor, Evelyne

2016-01-01

How a population of retinal ganglion cells (RGCs) encodes the visual scene remains an open question. Going beyond individual RGC coding strategies, results in salamander suggest that the relative latencies of a RGC pair encode spatial information. Thus, a population code based on this concerted spiking could be a powerful mechanism to transmit visual information rapidly and efficiently. Here, we tested this hypothesis in mouse by recording simultaneous light-evoked responses from hundreds of RGCs, at pan-retinal level, using a new generation of large-scale, high-density multielectrode array consisting of 4096 electrodes. Interestingly, we did not find any RGCs exhibiting a clear latency tuning to the stimuli, suggesting that in mouse, individual RGC pairs may not provide sufficient information. We show that a significant amount of information is encoded synergistically in the concerted spiking of large RGC populations. Thus, the RGC population response described with relative activities, or ranks, provides more relevant information than classical independent spike count- or latency- based codes. In particular, we report for the first time that when considering the relative activities across the whole population, the wave of first stimulus-evoked spikes is an accurate indicator of stimulus content. We show that this coding strategy coexists with classical neural codes, and that it is more efficient and faster. Overall, these novel observations suggest that already at the level of the retina, concerted spiking provides a reliable and fast strategy to rapidly transmit new visual scenes.

Ranking Support Vector Machine with Kernel Approximation.

Science.gov (United States)

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

2017-01-01

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

Ranking Support Vector Machine with Kernel Approximation

Directory of Open Access Journals (Sweden)

Kai Chen

2017-01-01

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

University Rankings and Social Science

Science.gov (United States)

Marginson, Simon

2014-01-01

University rankings widely affect the behaviours of prospective students and their families, university executive leaders, academic faculty, governments and investors in higher education. Yet the social science foundations of global rankings receive little scrutiny. Rankings that simply recycle reputation without any necessary connection to real…

General correlation and partial correlation analysis in finding interactions: with Spearman rank correlation and proportion correlation as correlation measures

OpenAIRE

WenJun Zhang; Xin Li

2015-01-01

Between-taxon interactions can be detected by calculating the sampling data of taxon sample type. In present study, Spearman rank correlation and proportion correlation are chosen as the general correlation measures, and their partial correlations are calculated and compared. The results show that for Spearman rank correlation measure, in all predicted candidate direct interactions by partial correlation, about 16.77% (x, 0-45.4%) of them are not successfully detected by Spearman rank correla...

Two-dimensional ranking of Wikipedia articles

Science.gov (United States)

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

2010-10-01

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

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

Directory of Open Access Journals (Sweden)

Breitling Rainer

2005-09-01

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

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

Science.gov (United States)

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

2005-09-21

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

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

Science.gov (United States)

Wicke, Kristina; Fischer, Mareike

2017-10-07

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

Hazard-ranking of agricultural pesticides for chronic health effects in Yuma County, Arizona.

Science.gov (United States)

Sugeng, Anastasia J; Beamer, Paloma I; Lutz, Eric A; Rosales, Cecilia B

2013-10-01

With thousands of pesticides registered by the United States Environmental Protection Agency, it not feasible to sample for all pesticides applied in agricultural communities. Hazard-ranking pesticides based on use, toxicity, and exposure potential can help prioritize community-specific pesticide hazards. This study applied hazard-ranking schemes for cancer, endocrine disruption, and reproductive/developmental toxicity in Yuma County, Arizona. An existing cancer hazard-ranking scheme was modified, and novel schemes for endocrine disruption and reproductive/developmental toxicity were developed to rank pesticide hazards. The hazard-ranking schemes accounted for pesticide use, toxicity, and exposure potential based on chemical properties of each pesticide. Pesticides were ranked as hazards with respect to each health effect, as well as overall chronic health effects. The highest hazard-ranked pesticides for overall chronic health effects were maneb, metam-sodium, trifluralin, pronamide, and bifenthrin. The relative pesticide rankings were unique for each health effect. The highest hazard-ranked pesticides differed from those most heavily applied, as well as from those previously detected in Yuma homes over a decade ago. The most hazardous pesticides for cancer in Yuma County, Arizona were also different from a previous hazard-ranking applied in California. Hazard-ranking schemes that take into account pesticide use, toxicity, and exposure potential can help prioritize pesticides of greatest health risk in agricultural communities. This study is the first to provide pesticide hazard-rankings for endocrine disruption and reproductive/developmental toxicity based on use, toxicity, and exposure potential. These hazard-ranking schemes can be applied to other agricultural communities for prioritizing community-specific pesticide hazards to target decreasing health risk. Copyright © 2013 Elsevier B.V. All rights reserved.

Hazard-Ranking of Agricultural Pesticides for Chronic Health Effects in Yuma County, Arizona

Science.gov (United States)

Sugeng, Anastasia J.; Beamer, Paloma I.; Lutz, Eric A.; Rosales, Cecilia B.

2013-01-01

With thousands of pesticides registered by the United States Environmental Protection Agency, it not feasible to sample for all pesticides applied in agricultural communities. Hazard-ranking pesticides based on use, toxicity, and exposure potential can help prioritize community-specific pesticide hazards. This study applied hazard-ranking schemes for cancer, endocrine disruption, and reproductive/developmental toxicity in Yuma County, Arizona. An existing cancer hazard-ranking scheme was modified, and novel schemes for endocrine disruption and reproductive/developmental toxicity were developed to rank pesticide hazards. The hazard-ranking schemes accounted for pesticide use, toxicity, and exposure potential based on chemical properties of each pesticide. Pesticides were ranked as hazards with respect to each health effect, as well as overall chronic health effects. The highest hazard-ranked pesticides for overall chronic health effects were maneb, metam sodium, trifluralin, pronamide, and bifenthrin. The relative pesticide rankings were unique for each health effect. The highest hazard-ranked pesticides differed from those most heavily applied, as well as from those previously detected in Yuma homes over a decade ago. The most hazardous pesticides for cancer in Yuma County, Arizona were also different from a previous hazard-ranking applied in California. Hazard-ranking schemes that take into account pesticide use, toxicity, and exposure potential can help prioritize pesticides of greatest health risk in agricultural communities. This study is the first to provide pesticide hazard-rankings for endocrine disruption and reproductive/developmental toxicity based on use, toxicity, and exposure potential. These hazard-ranking schemes can be applied to other agricultural communities for prioritizing community-specific pesticide hazards to target decreasing health risk. PMID:23783270

Text mixing shapes the anatomy of rank-frequency distributions

Science.gov (United States)

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

2015-05-01

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

Learning of Rule Ensembles for Multiple Attribute Ranking Problems

Science.gov (United States)

Dembczyński, Krzysztof; Kotłowski, Wojciech; Słowiński, Roman; Szeląg, Marcin

In this paper, we consider the multiple attribute ranking problem from a Machine Learning perspective. We propose two approaches to statistical learning of an ensemble of decision rules from decision examples provided by the Decision Maker in terms of pairwise comparisons of some objects. The first approach consists in learning a preference function defining a binary preference relation for a pair of objects. The result of application of this function on all pairs of objects to be ranked is then exploited using the Net Flow Score procedure, giving a linear ranking of objects. The second approach consists in learning a utility function for single objects. The utility function also gives a linear ranking of objects. In both approaches, the learning is based on the boosting technique. The presented approaches to Preference Learning share good properties of the decision rule preference model and have good performance in the massive-data learning problems. As Preference Learning and Multiple Attribute Decision Aiding share many concepts and methodological issues, in the introduction, we review some aspects bridging these two fields. To illustrate the two approaches proposed in this paper, we solve with them a toy example concerning the ranking of a set of cars evaluated by multiple attributes. Then, we perform a large data experiment on real data sets. The first data set concerns credit rating. Since recent research in the field of Preference Learning is motivated by the increasing role of modeling preferences in recommender systems and information retrieval, we chose two other massive data sets from this area - one comes from movie recommender system MovieLens, and the other concerns ranking of text documents from 20 Newsgroups data set.

CT Image Sequence Restoration Based on Sparse and Low-Rank Decomposition

Science.gov (United States)

Gou, Shuiping; Wang, Yueyue; Wang, Zhilong; Peng, Yong; Zhang, Xiaopeng; Jiao, Licheng; Wu, Jianshe

2013-01-01

Blurry organ boundaries and soft tissue structures present a major challenge in biomedical image restoration. In this paper, we propose a low-rank decomposition-based method for computed tomography (CT) image sequence restoration, where the CT image sequence is decomposed into a sparse component and a low-rank component. A new point spread function of Weiner filter is employed to efficiently remove blur in the sparse component; a wiener filtering with the Gaussian PSF is used to recover the average image of the low-rank component. And then we get the recovered CT image sequence by combining the recovery low-rank image with all recovery sparse image sequence. Our method achieves restoration results with higher contrast, sharper organ boundaries and richer soft tissue structure information, compared with existing CT image restoration methods. The robustness of our method was assessed with numerical experiments using three different low-rank models: Robust Principle Component Analysis (RPCA), Linearized Alternating Direction Method with Adaptive Penalty (LADMAP) and Go Decomposition (GoDec). Experimental results demonstrated that the RPCA model was the most suitable for the small noise CT images whereas the GoDec model was the best for the large noisy CT images. PMID:24023764

Estimation bias and bias correction in reduced rank autoregressions

DEFF Research Database (Denmark)

Nielsen, Heino Bohn

2017-01-01

This paper characterizes the finite-sample bias of the maximum likelihood estimator (MLE) in a reduced rank vector autoregression and suggests two simulation-based bias corrections. One is a simple bootstrap implementation that approximates the bias at the MLE. The other is an iterative root...

Obstructions to the realization of distance graphs with large chromatic numbers on spheres of small radii

Energy Technology Data Exchange (ETDEWEB)

Kupavskii, A B; Raigorodskii, A M [M. V. Lomonosov Moscow State University, Faculty of Mechanics and Mathematics, Moscow (Russian Federation)

2013-10-31

We investigate in detail some properties of distance graphs constructed on the integer lattice. Such graphs find wide applications in problems of combinatorial geometry, in particular, such graphs were employed to answer Borsuk's question in the negative and to obtain exponential estimates for the chromatic number of the space. This work is devoted to the study of the number of cliques and the chromatic number of such graphs under certain conditions. Constructions of sequences of distance graphs are given, in which the graphs have unit length edges and contain a large number of triangles that lie on a sphere of radius 1/√3 (which is the minimum possible). At the same time, the chromatic numbers of the graphs depend exponentially on their dimension. The results of this work strengthen and generalize some of the results obtained in a series of papers devoted to related issues. Bibliography: 29 titles.

A review of methods for sampling large airborne particles and associated radioactivity

International Nuclear Information System (INIS)

Garland, J.A.; Nicholson, K.W.

1990-01-01

Radioactive particles, tens of μm or more in diameter, are unlikely to be emitted directly from nuclear facilities with exhaust gas cleansing systems, but may arise in the case of an accident or where resuspension from contaminated surfaces is significant. Such particles may dominate deposition and, according to some workers, may contribute to inhalation doses. Quantitative sampling of large airborne particles is difficult because of their inertia and large sedimentation velocities. The literature describes conditions for unbiased sampling and the magnitude of sampling errors for idealised sampling inlets in steady winds. However, few air samplers for outdoor use have been assessed for adequacy of sampling. Many size selective sampling methods are found in the literature but few are suitable at the low concentrations that are often encountered in the environment. A number of approaches for unbiased sampling of large particles have been found in the literature. Some are identified as meriting further study, for application in the measurement of airborne radioactivity. (author)

Bootstrap Sequential Determination of the Co-integration Rank in VAR Models

DEFF Research Database (Denmark)

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

with empirical rejection frequencies often very much in excess of the nominal level. As a consequence, bootstrap versions of these tests have been developed. To be useful, however, sequential procedures for determining the co-integrating rank based on these bootstrap tests need to be consistent, in the sense...... in the literature by proposing a bootstrap sequential algorithm which we demonstrate delivers consistent cointegration rank estimation for general I(1) processes. Finite sample Monte Carlo simulations show the proposed procedure performs well in practice....

Sampling from complex networks with high community structures.

Science.gov (United States)

Salehi, Mostafa; Rabiee, Hamid R; Rajabi, Arezo

2012-06-01

In this paper, we propose a novel link-tracing sampling algorithm, based on the concepts from PageRank vectors, to sample from networks with high community structures. Our method has two phases; (1) Sampling the closest nodes to the initial nodes by approximating personalized PageRank vectors and (2) Jumping to a new community by using PageRank vectors and unknown neighbors. Empirical studies on several synthetic and real-world networks show that the proposed method improves the performance of network sampling compared to the popular link-based sampling methods in terms of accuracy and visited communities.

SpikeTemp: An Enhanced Rank-Order-Based Learning Approach for Spiking Neural Networks With Adaptive Structure.

Science.gov (United States)

Wang, Jinling; Belatreche, Ammar; Maguire, Liam P; McGinnity, Thomas Martin

2017-01-01

This paper presents an enhanced rank-order-based learning algorithm, called SpikeTemp, for spiking neural networks (SNNs) with a dynamically adaptive structure. The trained feed-forward SNN consists of two layers of spiking neurons: 1) an encoding layer which temporally encodes real-valued features into spatio-temporal spike patterns and 2) an output layer of dynamically grown neurons which perform spatio-temporal classification. Both Gaussian receptive fields and square cosine population encoding schemes are employed to encode real-valued features into spatio-temporal spike patterns. Unlike the rank-order-based learning approach, SpikeTemp uses the precise times of the incoming spikes for adjusting the synaptic weights such that early spikes result in a large weight change and late spikes lead to a smaller weight change. This removes the need to rank all the incoming spikes and, thus, reduces the computational cost of SpikeTemp. The proposed SpikeTemp algorithm is demonstrated on several benchmark data sets and on an image recognition task. The results show that SpikeTemp can achieve better classification performance and is much faster than the existing rank-order-based learning approach. In addition, the number of output neurons is much smaller when the square cosine encoding scheme is employed. Furthermore, SpikeTemp is benchmarked against a selection of existing machine learning algorithms, and the results demonstrate the ability of SpikeTemp to classify different data sets after just one presentation of the training samples with comparable classification performance.

14 CFR 1214.1105 - Final ranking.

Science.gov (United States)

2010-01-01

... 14 Aeronautics and Space 5 2010-01-01 2010-01-01 false Final ranking. 1214.1105 Section 1214.1105... Recruitment and Selection Program § 1214.1105 Final ranking. Final rankings will be based on a combination of... preference will be included in this final ranking in accordance with applicable regulations. ...

Solar cosmic ray events at large radial distances from the sun

International Nuclear Information System (INIS)

Zwickl, R.; Webber, W.R.; McDonald, F.B.; Teegarden, B.; Trainor, J.

1975-01-01

Using the GSFC-UNH cosmic ray telescope on Pioneer 10 and 11 we have examined solar cosmic ray events out to a distance approximately 5 AU from the sun. Here we consider two aspects of this work, both related to our anisotropy studies. First, a detailed error analysis of the cosine fit to the anisotropy is presented. Second, we look at the anisotropy and intensity time characteristics during solar events as a function of radial distance. (orig.) [de

Monte Carlo estimation of total variation distance of Markov chains on large spaces, with application to phylogenetics.

Science.gov (United States)

Herbei, Radu; Kubatko, Laura

2013-03-26

Markov chains are widely used for modeling in many areas of molecular biology and genetics. As the complexity of such models advances, it becomes increasingly important to assess the rate at which a Markov chain converges to its stationary distribution in order to carry out accurate inference. A common measure of convergence to the stationary distribution is the total variation distance, but this measure can be difficult to compute when the state space of the chain is large. We propose a Monte Carlo method to estimate the total variation distance that can be applied in this situation, and we demonstrate how the method can be efficiently implemented by taking advantage of GPU computing techniques. We apply the method to two Markov chains on the space of phylogenetic trees, and discuss the implications of our findings for the development of algorithms for phylogenetic inference.

Ranking transmission projects in large scale systems using an AC power flow model; Priorizacao de obras em sistemas de grande porte usando um modelo AC da rede

Energy Technology Data Exchange (ETDEWEB)

Melo, A C.G. [Centro de Pesquisas de Energia Eletrica (CEPEL), Rio de Janeiro, RJ (Brazil); Fontoura Filho, R N [ELETROBRAS, Rio de Janeiro, RJ (Brazil); Peres, L A.P. Pecorelli [FURNAS, Rio de Janeiro, RJ (Brazil); Morozowski Filho, M [Santa Catarina Univ., Florianopolis, SC (Brazil)

1994-12-31

Initially, this paper summarizes the approach developed by the Brazilian Planning Criteria Working Group (GTCP/ELETROBRAS) for identifying which subset of transmission investments should be postponed to meet a pre-stablished budget constraint with the least possible impact on system performance. Next, this paper presents the main features of the computational model PRIO, which allows the application of the ranking process to large scale power systems (2,000 buses and 3,000 circuits), with as many as 100 projects to be ranked. In this model, the adequacy analysis of each system state is carried out through an AC power flow coupled to a successive linear programming based remedial actions model. Case studies with the IEEE-RTS system and a configuration of the Brazilian Southeastern are presented and discussed. (author) 7 refs., 6 figs., 5 tabs.

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

NARCIS (Netherlands)

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

2012-01-01

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

Social Distance and Intergenerational Relations

Science.gov (United States)

Kidwell, I. Jane; Booth, Alan

1977-01-01

Questionnaires were administered to a sample of adults to assess the extent of social distance between people of different ages. The findings suggest that the greater the age difference (younger or older) between people, the greater the social distance they feel. (Author)

Distance of Sample Measurement Points to Prototype Catalog Curve

DEFF Research Database (Denmark)

Hjorth, Poul G.; Karamehmedovic, Mirza; Perram, John

2006-01-01

We discuss strategies for comparing discrete data points to a catalog (reference) curve by means of the Euclidean distance from each point to the curve in a pump's head H vs. flow Qdiagram. In particular we find that a method currently in use is inaccurate. We propose several alternatives...

"I can do perfectly well without a car!": An exploration of stated preferences for middle-distance travel

OpenAIRE

Exel, Job; Graaf, G.; Rietveld, Piet

2011-01-01

textabstractThis article presents the results of a study exploring travellers' preferences for middle-distance travel using Q-methodology. Respondents rank-ordered 42 opinion statements regarding travel choice and motivations for travel in general and for car and public transport as alternative travel modes. By-person factor analysis revealed four distinct preference segments for middle-distance travel: (1) choice travellers with a preference for public transport, (2) deliberate-choice travel...

Batched Tile Low-Rank GEMM on GPUs

KAUST Repository

Charara, Ali

2018-02-01

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

Evaluation of gene-expression clustering via mutual information distance measure

Directory of Open Access Journals (Sweden)

Maimon Oded

2007-03-01

Full Text Available Abstract Background The definition of a distance measure plays a key role in the evaluation of different clustering solutions of gene expression profiles. In this empirical study we compare different clustering solutions when using the Mutual Information (MI measure versus the use of the well known Euclidean distance and Pearson correlation coefficient. Results Relying on several public gene expression datasets, we evaluate the homogeneity and separation scores of different clustering solutions. It was found that the use of the MI measure yields a more significant differentiation among erroneous clustering solutions. The proposed measure was also used to analyze the performance of several known clustering algorithms. A comparative study of these algorithms reveals that their "best solutions" are ranked almost oppositely when using different distance measures, despite the found correspondence between these measures when analysing the averaged scores of groups of solutions. Conclusion In view of the results, further attention should be paid to the selection of a proper distance measure for analyzing the clustering of gene expression data.

Rankings, creatividad y urbanismo

Directory of Open Access Journals (Sweden)

JOAQUÍN SABATÉ

2008-08-01

Full Text Available La competencia entre ciudades constituye uno de los factores impulsores de procesos de renovación urbana y los rankings han devenido instrumentos de medida de la calidad de las ciudades. Nos detendremos en el caso de un antiguo barrio industrial hoy en vías de transformación en distrito "creativo" por medio de una intervención urbanística de gran escala. Su análisis nos descubre tres claves críticas. En primer lugar, nos obliga a plantearnos la definición de innovación urbana y cómo se integran el pasado, la identidad y la memoria en la construcción del futuro. Nos lleva a comprender que la innovación y el conocimiento no se "dan" casualmente, sino que son el fruto de una larga y compleja red en la que participan saberes, espacios, actores e instituciones diversas en naturaleza, escala y magnitud. Por último nos obliga a reflexionar sobre el valor que se le otorga a lo local en los procesos de renovación urbana.Competition among cities constitutes one ofthe main factors o furban renewal, and rankings have become instruments to indícate cities quality. Studying the transformation of an old industrial quarter into a "creative district" by the means ofa large scale urban project we highlight three main conclusions. First, itasks us to reconsider the notion ofurban innovation and hoto past, identity and memory should intégrate the future development. Second, it shows that innovation and knowledge doesn't yield per chance, but are the result ofa large and complex grid of diverse knowledges, spaces, agents and institutions. Finally itforces us to reflect about the valué attributed to the "local" in urban renewalprocesses.

Tensor Rank Preserving Discriminant Analysis for Facial Recognition.

Science.gov (United States)

Tao, Dapeng; Guo, Yanan; Li, Yaotang; Gao, Xinbo

2017-10-12

Facial recognition, one of the basic topics in computer vision and pattern recognition, has received substantial attention in recent years. However, for those traditional facial recognition algorithms, the facial images are reshaped to a long vector, thereby losing part of the original spatial constraints of each pixel. In this paper, a new tensor-based feature extraction algorithm termed tensor rank preserving discriminant analysis (TRPDA) for facial image recognition is proposed; the proposed method involves two stages: in the first stage, the low-dimensional tensor subspace of the original input tensor samples was obtained; in the second stage, discriminative locality alignment was utilized to obtain the ultimate vector feature representation for subsequent facial recognition. On the one hand, the proposed TRPDA algorithm fully utilizes the natural structure of the input samples, and it applies an optimization criterion that can directly handle the tensor spectral analysis problem, thereby decreasing the computation cost compared those traditional tensor-based feature selection algorithms. On the other hand, the proposed TRPDA algorithm extracts feature by finding a tensor subspace that preserves most of the rank order information of the intra-class input samples. Experiments on the three facial databases are performed here to determine the effectiveness of the proposed TRPDA algorithm.

105-DR Large Sodium Fire Facility decontamination, sampling, and analysis plan

International Nuclear Information System (INIS)

Knaus, Z.C.

1995-01-01

This is the decontamination, sampling, and analysis plan for the closure activities at the 105-DR Large Sodium Fire Facility at Hanford Reservation. This document supports the 105-DR Large Sodium Fire Facility Closure Plan, DOE-RL-90-25. The 105-DR LSFF, which operated from about 1972 to 1986, was a research laboratory that occupied the former ventilation supply room on the southwest side of the 105-DR Reactor facility in the 100-D Area of the Hanford Site. The LSFF was established to investigate fire fighting and safety associated with alkali metal fires in the liquid metal fast breeder reactor facilities. The decontamination, sampling, and analysis plan identifies the decontamination procedures, sampling locations, any special handling requirements, quality control samples, required chemical analysis, and data validation needed to meet the requirements of the 105-DR Large Sodium Fire Facility Closure Plan in compliance with the Resource Conservation and Recovery Act

Multivariate statistics high-dimensional and large-sample approximations

CERN Document Server

Fujikoshi, Yasunori; Shimizu, Ryoichi

2010-01-01

A comprehensive examination of high-dimensional analysis of multivariate methods and their real-world applications Multivariate Statistics: High-Dimensional and Large-Sample Approximations is the first book of its kind to explore how classical multivariate methods can be revised and used in place of conventional statistical tools. Written by prominent researchers in the field, the book focuses on high-dimensional and large-scale approximations and details the many basic multivariate methods used to achieve high levels of accuracy. The authors begin with a fundamental presentation of the basic

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

Science.gov (United States)

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

2010-04-16

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

Recurrent fuzzy ranking methods

Science.gov (United States)

Hajjari, Tayebeh

2012-11-01

With the increasing development of fuzzy set theory in various scientific fields and the need to compare fuzzy numbers in different areas. Therefore, Ranking of fuzzy numbers plays a very important role in linguistic decision-making, engineering, business and some other fuzzy application systems. Several strategies have been proposed for ranking of fuzzy numbers. Each of these techniques has been shown to produce non-intuitive results in certain case. In this paper, we reviewed some recent ranking methods, which will be useful for the researchers who are interested in this area.

Large sample NAA facility and methodology development

International Nuclear Information System (INIS)

Roth, C.; Gugiu, D.; Barbos, D.; Datcu, A.; Aioanei, L.; Dobrea, D.; Taroiu, I. E.; Bucsa, A.; Ghinescu, A.

2013-01-01

A Large Sample Neutron Activation Analysis (LSNAA) facility has been developed at the TRIGA- Annular Core Pulsed Reactor (ACPR) operated by the Institute for Nuclear Research in Pitesti, Romania. The central irradiation cavity of the ACPR core can accommodate a large irradiation device. The ACPR neutron flux characteristics are well known and spectrum adjustment techniques have been successfully applied to enhance the thermal component of the neutron flux in the central irradiation cavity. An analysis methodology was developed by using the MCNP code in order to estimate counting efficiency and correction factors for the major perturbing phenomena. Test experiments, comparison with classical instrumental neutron activation analysis (INAA) methods and international inter-comparison exercise have been performed to validate the new methodology. (authors)

Ranking Operations Management conferences

NARCIS (Netherlands)

Steenhuis, H.J.; de Bruijn, E.J.; Gupta, Sushil; Laptaned, U

2007-01-01

Several publications have appeared in the field of Operations Management which rank Operations Management related journals. Several ranking systems exist for journals based on , for example, perceived relevance and quality, citation, and author affiliation. Many academics also publish at conferences

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

Energy Technology Data Exchange (ETDEWEB)

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.

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

International Nuclear Information System (INIS)

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

THE GREEN BANK TELESCOPE H II REGION DISCOVERY SURVEY. III. KINEMATIC DISTANCES

Energy Technology Data Exchange (ETDEWEB)

Anderson, L. D. [Department of Physics, West Virginia University, Morgantown, WV 26506 (United States); Bania, T. M. [Institute for Astrophysical Research, Department of Astronomy, Boston University, 725 Commonwealth Avenue, Boston, MA 02215 (United States); Balser, Dana S. [National Radio Astronomy Observatory, 520 Edgemont Road, Charlottesville, VA 22903-2475 (United States); Rood, Robert T., E-mail: Loren.Anderson@mail.wvu.edu [Astronomy Department, University of Virginia, P.O. Box 3818, Charlottesville, VA 22903-0818 (United States)

2012-07-20

Using the H I emission/absorption method, we resolve the kinematic distance ambiguity and derive distances for 149 of 182 (82%) H II regions discovered by the Green Bank Telescope H II Region Discovery Survey (GBT HRDS). The HRDS is an X-band (9 GHz, 3 cm) GBT survey of 448 previously unknown H II regions in radio recombination line and radio continuum emission. Here, we focus on HRDS sources from 67 Degree-Sign {>=} l {>=} 18 Degree-Sign , where kinematic distances are more reliable. The 25 HRDS sources in this zone that have negative recombination line velocities are unambiguously beyond the orbit of the Sun, up to 20 kpc distant. They are the most distant H II regions yet discovered. We find that 61% of HRDS sources are located at the far distance, 31% at the tangent-point distance, and only 7% at the near distance. 'Bubble' H II regions are not preferentially located at the near distance (as was assumed previously) but average 10 kpc from the Sun. The HRDS nebulae, when combined with a large sample of H II regions with previously known distances, show evidence of spiral structure in two circular arc segments of mean Galactocentric radii of 4.25 and 6.0 kpc. We perform a thorough uncertainty analysis to analyze the effect of using different rotation curves, streaming motions, and a change to the solar circular rotation speed. The median distance uncertainty for our sample of H II regions is only 0.5 kpc, or 5%. This is significantly less than the median difference between the near and far kinematic distances, 6 kpc. The basic Galactic structure results are unchanged after considering these sources of uncertainty.

Modified Phenomena Identification and Ranking Table (PIRT) for Uncertainty Analysis

International Nuclear Information System (INIS)

Gol-Mohamad, Mohammad P.; Modarres, Mohammad; Mosleh, Ali

2006-01-01

This paper describes a methodology of characterizing important phenomena, which is also part of a broader research by the authors called 'Modified PIRT'. The methodology provides robust process of phenomena identification and ranking process for more precise quantification of uncertainty. It is a two-step process of identifying and ranking methodology based on thermal-hydraulics (TH) importance as well as uncertainty importance. Analytical Hierarchical Process (AHP) has been used for as a formal approach for TH identification and ranking. Formal uncertainty importance technique is used to estimate the degree of credibility of the TH model(s) used to represent the important phenomena. This part uses subjective justification by evaluating available information and data from experiments, and code predictions. The proposed methodology was demonstrated by developing a PIRT for large break loss of coolant accident LBLOCA for the LOFT integral facility with highest core power (test LB-1). (authors)

Distance education student accompaniment: IPGN course, an experience in large scale capacitation

Directory of Open Access Journals (Sweden)

Sônia Inez Grüdtner Floriano

2005-06-01

Full Text Available One of the most difficulties found by the providersinstitution of courses on the distance education modality, since its beginning until nowadays, is to accompany the development of its students. Today there are too much possibilities brought up by the new technologies of communication and information. Although it is known that those one are only a thru, once the difference is exactly in the pedagogical proposal of the course. For this, this paper intens to present the pedagogical proposal, the methodology and the technological resourles utilized to accompany, orient and support on de systematic way, permanent and proactive the students of a e-learning course of large scale, free with two months lenght, and 30 hours/class charge. It is a result of a partnership between SEBRAE (Serviço Brasileiro de Micro e Pequenas Empresas and IEA(Instituto de Estudos Avançados. This course has begun in 2001 and til the present moment has capacited 216.648 students.

Sample preparation method for ICP-MS measurement of 99Tc in a large amount of environmental samples

International Nuclear Information System (INIS)

Kondo, M.; Seki, R.

2002-01-01

Sample preparation for measurement of 99 Tc in a large amount of soil and water samples by ICP-MS has been developed using 95m Tc as a yield tracer. This method is based on the conventional method for a small amount of soil samples using incineration, acid digestion, extraction chromatography (TEVA resin) and ICP-MS measurement. Preliminary concentration of Tc has been introduced by co-precipitation with ferric oxide. The matrix materials in a large amount of samples were more sufficiently removed with keeping the high recovery of Tc than previous method. The recovery of Tc was 70-80% for 100 g soil samples and 60-70% for 500 g of soil and 500 L of water samples. The detection limit of this method was evaluated as 0.054 mBq/kg in 500 g soil and 0.032 μBq/L in 500 L water. The determined value of 99 Tc in the IAEA-375 (soil sample collected near the Chernobyl Nuclear Reactor) was 0.25 ± 0.02 Bq/kg. (author)

Aspects of analysis of small-sample right censored data using generalized Wilcoxon rank tests

OpenAIRE

Öhman, Marie-Louise

1994-01-01

The estimated bias and variance of commonly applied and jackknife variance estimators and observed significance level and power of standardised generalized Wilcoxon linear rank sum test statistics and tests, respectively, of Gehan and Prentice are compared in a Monte Carlo simulation study. The variance estimators are the permutational-, the conditional permutational- and the jackknife variance estimators of the test statistic of Gehan, and the asymptotic- and the jackknife variance estimator...

Country-specific determinants of world university rankings

OpenAIRE

Pietrucha, Jacek

2017-01-01

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

On the dependency of the decay of ground motion peak values with distance for small and large earthquakes

Science.gov (United States)

Dujardin, Alain; Courboulex, Françoise; Causse, Matthieu; Traversa, Paola; Monfret, Tony

2013-04-01

Ground motion decay with distance presents a clear magnitude dependence, PGA values of small events decreasing faster than those of larger events. This observation is now widely accepted and often taken into account in recent ground motion prediction equations (Anderson 2005, Akkar & Bommer 2010). The aim of this study is to investigate the origin of this dependence, which has not been clearly identified yet. Two main hypotheses are considered. On one hand the difference of ground motion decay is related to an attenuation effect, on the other hand the difference is related to an effect of extended fault (Anderson 2000). To study the role of attenuation, we realized synthetic tests using the stochastic simulation program SMSIM from Boore (2005). We build a set of simulations from several magnitudes and epicentral distances, and observe that the decay in PGA values is strongly dependent on the spectral shape of the Fourier spectra, which in turn strongly depends on the attenuation factor (Q(f) or kappa). We found that, for a point source approximation and an infinite value of Q (no attenuation) there is no difference between small and large events and that this difference increases when Q decreases. Theses results show that the influence of attenuation on spectral shape is different for earthquakes of different magnitude. In fact the influence of attenuation, which is more important at higher frequency, is larger for small earthquakes, whose Fourier acceleration spectrum has predominantly higher frequencies. We then study the effect of extended source using complete waveform simulations in a 1D model. We find that when the duration of the source time function increases, there is a larger probability to obtain large PGA values at equivalent distances. This effect could also play an important role in the PGA decay with magnitude and distance. Finally we compare these results with real datasets from the Japanese accelerometric network KIK-net.

THE DISTANCE MEASUREMENT OF NGC 1313 WITH CEPHEIDS

International Nuclear Information System (INIS)

Qing, Gao; Wang, Wei; Liu, Ji-Feng; Yoachim, Peter

2015-01-01

We present the detection of Cepheids in the barred spiral galaxy NGC 1313, using the Wide Field and Planetary Camera 2 on the Hubble Space Telescope. Twenty B(F450W) and V(F555W) epochs of observations spanning over three weeks were obtained, on which the profile-fitting photometry of all stars in the monitored field was performed using the package HSTphot. A sample of 26 variable stars have been identified to be Cepheids, with periods between 3 and 14 days. Based on the derived period-luminosity relations in B- and V-bands, we obtain an extinction-corrected distance modulus of μ NGC 1313 = 28.32 ± 0.08 (random) ± 0.06 (systematic), employing the Large Magellanic Cloud as the distance zero point calibrator. The above moduli correspond to a distance of 4.61 ± 0.17 (random) ±0.13 (systematic) Mpc, consistent with previous measurements reported in the literature within uncertainties. In addition, the reddening to NGC 1313 is found to be small

THE DISTANCE TO M51

Energy Technology Data Exchange (ETDEWEB)

McQuinn, Kristen B. W. [University of Texas at Austin, McDonald Observatory, 2515 Speedway, Stop C1400 Austin, TX 78712 (United States); Skillman, Evan D. [Minnesota Institute for Astrophysics, School of Physics and Astronomy, 116 Church Street, S.E., University of Minnesota, Minneapolis, MN 55455 (United States); Dolphin, Andrew E. [Raytheon Company, 1151 E. Hermans Road, Tucson, AZ 85756 (United States); Berg, Danielle [Center for Gravitation, Cosmology and Astrophysics, Department of Physics, University of Wisconsin Milwaukee, 1900 East Kenwood Boulevard, Milwaukee, WI 53211 (United States); Kennicutt, Robert, E-mail: kmcquinn@astro.as.utexas.edu [Institute for Astronomy, University of Cambridge, Madingley Road, Cambridge CB3 0HA (United Kingdom)

2016-07-20

Great investments of observing time have been dedicated to the study of nearby spiral galaxies with diverse goals ranging from understanding the star formation process to characterizing their dark matter distributions. Accurate distances are fundamental to interpreting observations of these galaxies, yet many of the best studied nearby galaxies have distances based on methods with relatively large uncertainties. We have started a program to derive accurate distances to these galaxies. Here we measure the distance to M51—the Whirlpool galaxy—from newly obtained Hubble Space Telescope optical imaging using the tip of the red giant branch method. We measure the distance modulus to be 8.58 ± 0.10 Mpc (statistical), corresponding to a distance modulus of 29.67 ± 0.02 mag. Our distance is an improvement over previous results as we use a well-calibrated, stable distance indicator, precision photometry in a optimally selected field of view, and a Bayesian Maximum Likelihood technique that reduces measurement uncertainties.

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

Science.gov (United States)

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

2017-06-15

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

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

Directory of Open Access Journals (Sweden)

P. Dhanalakshmi

2017-12-01

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

Large-distance and long-time asymptotic behavior of the reduced density matrix in the non-linear Schroedinger model

Energy Technology Data Exchange (ETDEWEB)

Kozlowski, K.K.

2010-12-15

Starting from the form factor expansion in finite volume, we derive the multidimensional generalization of the so-called Natte series for the zero-temperature, time and distance dependent reduced density matrix in the non-linear Schroedinger model. This representation allows one to read-off straightforwardly the long-time/large-distance asymptotic behavior of this correlator. Our method of analysis reduces the complexity of the computation of the asymptotic behavior of correlation functions in the so-called interacting integrable models, to the one appearing in free fermion equivalent models. We compute explicitly the first few terms appearing in the asymptotic expansion. Part of these terms stems from excitations lying away from the Fermi boundary, and hence go beyond what can be obtained by using the CFT/Luttinger liquid based predictions. (orig.)

Distance matrix-based approach to protein structure prediction.

Science.gov (United States)

Kloczkowski, Andrzej; Jernigan, Robert L; Wu, Zhijun; Song, Guang; Yang, Lei; Kolinski, Andrzej; Pokarowski, Piotr

2009-03-01

Much structural information is encoded in the internal distances; a distance matrix-based approach can be used to predict protein structure and dynamics, and for structural refinement. Our approach is based on the square distance matrix D = [r(ij)(2)] containing all square distances between residues in proteins. This distance matrix contains more information than the contact matrix C, that has elements of either 0 or 1 depending on whether the distance r (ij) is greater or less than a cutoff value r (cutoff). We have performed spectral decomposition of the distance matrices D = sigma lambda(k)V(k)V(kT), in terms of eigenvalues lambda kappa and the corresponding eigenvectors v kappa and found that it contains at most five nonzero terms. A dominant eigenvector is proportional to r (2)--the square distance of points from the center of mass, with the next three being the principal components of the system of points. By predicting r (2) from the sequence we can approximate a distance matrix of a protein with an expected RMSD value of about 7.3 A, and by combining it with the prediction of the first principal component we can improve this approximation to 4.0 A. We can also explain the role of hydrophobic interactions for the protein structure, because r is highly correlated with the hydrophobic profile of the sequence. Moreover, r is highly correlated with several sequence profiles which are useful in protein structure prediction, such as contact number, the residue-wise contact order (RWCO) or mean square fluctuations (i.e. crystallographic temperature factors). We have also shown that the next three components are related to spatial directionality of the secondary structure elements, and they may be also predicted from the sequence, improving overall structure prediction. We have also shown that the large number of available HIV-1 protease structures provides a remarkable sampling of conformations, which can be viewed as direct structural information about the

Estimating HIES Data through Ratio and Regression Methods for Different Sampling Designs

Directory of Open Access Journals (Sweden)

Faqir Muhammad

2007-01-01

Full Text Available In this study, comparison has been made for different sampling designs, using the HIES data of North West Frontier Province (NWFP for 2001-02 and 1998-99 collected from the Federal Bureau of Statistics, Statistical Division, Government of Pakistan, Islamabad. The performance of the estimators has also been considered using bootstrap and Jacknife. A two-stage stratified random sample design is adopted by HIES. In the first stage, enumeration blocks and villages are treated as the first stage Primary Sampling Units (PSU. The sample PSU’s are selected with probability proportional to size. Secondary Sampling Units (SSU i.e., households are selected by systematic sampling with a random start. They have used a single study variable. We have compared the HIES technique with some other designs, which are: Stratified Simple Random Sampling. Stratified Systematic Sampling. Stratified Ranked Set Sampling. Stratified Two Phase Sampling. Ratio and Regression methods were applied with two study variables, which are: Income (y and Household sizes (x. Jacknife and Bootstrap are used for variance replication. Simple Random Sampling with sample size (462 to 561 gave moderate variances both by Jacknife and Bootstrap. By applying Systematic Sampling, we received moderate variance with sample size (467. In Jacknife with Systematic Sampling, we obtained variance of regression estimator greater than that of ratio estimator for a sample size (467 to 631. At a sample size (952 variance of ratio estimator gets greater than that of regression estimator. The most efficient design comes out to be Ranked set sampling compared with other designs. The Ranked set sampling with jackknife and bootstrap, gives minimum variance even with the smallest sample size (467. Two Phase sampling gave poor performance. Multi-stage sampling applied by HIES gave large variances especially if used with a single study variable.

Ranking Highlights in Personal Videos by Analyzing Edited Videos.

Science.gov (United States)

Sun, Min; Farhadi, Ali; Chen, Tseng-Hung; Seitz, Steve

2016-11-01

We present a fully automatic system for ranking domain-specific highlights in unconstrained personal videos by analyzing online edited videos. A novel latent linear ranking model is proposed to handle noisy training data harvested online. Specifically, given a targeted domain such as "surfing," our system mines the YouTube database to find pairs of raw and their corresponding edited videos. Leveraging the assumption that an edited video is more likely to contain highlights than the trimmed parts of the raw video, we obtain pair-wise ranking constraints to train our model. The learning task is challenging due to the amount of noise and variation in the mined data. Hence, a latent loss function is incorporated to mitigate the issues caused by the noise. We efficiently learn the latent model on a large number of videos (about 870 min in total) using a novel EM-like procedure. Our latent ranking model outperforms its classification counterpart and is fairly competitive compared with a fully supervised ranking system that requires labels from Amazon Mechanical Turk. We further show that a state-of-the-art audio feature mel-frequency cepstral coefficients is inferior to a state-of-the-art visual feature. By combining both audio-visual features, we obtain the best performance in dog activity, surfing, skating, and viral video domains. Finally, we show that impressive highlights can be detected without additional human supervision for seven domains (i.e., skating, surfing, skiing, gymnastics, parkour, dog activity, and viral video) in unconstrained personal videos.

Rank-based model selection for multiple ions quantum tomography

International Nuclear Information System (INIS)

Guţă, Mădălin; Kypraios, Theodore; Dryden, Ian

2012-01-01

The statistical analysis of measurement data has become a key component of many quantum engineering experiments. As standard full state tomography becomes unfeasible for large dimensional quantum systems, one needs to exploit prior information and the ‘sparsity’ properties of the experimental state in order to reduce the dimensionality of the estimation problem. In this paper we propose model selection as a general principle for finding the simplest, or most parsimonious explanation of the data, by fitting different models and choosing the estimator with the best trade-off between likelihood fit and model complexity. We apply two well established model selection methods—the Akaike information criterion (AIC) and the Bayesian information criterion (BIC)—two models consisting of states of fixed rank and datasets such as are currently produced in multiple ions experiments. We test the performance of AIC and BIC on randomly chosen low rank states of four ions, and study the dependence of the selected rank with the number of measurement repetitions for one ion states. We then apply the methods to real data from a four ions experiment aimed at creating a Smolin state of rank 4. By applying the two methods together with the Pearson χ 2 test we conclude that the data can be suitably described with a model whose rank is between 7 and 9. Additionally we find that the mean square error of the maximum likelihood estimator for pure states is close to that of the optimal over all possible measurements. (paper)

Bootstrap Determination of the Co-Integration Rank in Heteroskedastic VAR Models

DEFF Research Database (Denmark)

Cavaliere, G.; Rahbek, Anders; Taylor, A.M.R.

2014-01-01

In a recent paper Cavaliere et al. (2012) develop bootstrap implementations of the (pseudo-) likelihood ratio (PLR) co-integration rank test and associated sequential rank determination procedure of Johansen (1996). The bootstrap samples are constructed using the restricted parameter estimates...... of the underlying vector autoregressive (VAR) model which obtain under the reduced rank null hypothesis. They propose methods based on an independent and individual distributed (i.i.d.) bootstrap resampling scheme and establish the validity of their proposed bootstrap procedures in the context of a co......-integrated VAR model with i.i.d. innovations. In this paper we investigate the properties of their bootstrap procedures, together with analogous procedures based on a wild bootstrap resampling scheme, when time-varying behavior is present in either the conditional or unconditional variance of the innovations. We...

Using spatiotemporal models and distance sampling to map the space use and abundance of newly metamorphosed Western Toads (Anaxyrus boreas)

Science.gov (United States)

Chelgren, Nathan D.; Samora, Barbara; Adams, Michael J.; McCreary, Brome

2011-01-01

High variability in abundance, cryptic coloration, and small body size of newly metamorphosed anurans have limited demographic studies of this life-history stage. We used line-transect distance sampling and Bayesian methods to estimate the abundance and spatial distribution of newly metamorphosed Western Toads (Anaxyrus boreas) in terrestrial habitat surrounding a montane lake in central Washington, USA. We completed 154 line-transect surveys from the commencement of metamorphosis (15 September 2009) to the date of first snow accumulation in fall (1 October 2009), and located 543 newly metamorphosed toads. After accounting for variable detection probability associated with the extent of barren habitats, estimates of total surface abundance ranged from a posterior median of 3,880 (95% credible intervals from 2,235 to 12,600) in the first week of sampling to 12,150 (5,543 to 51,670) during the second week of sampling. Numbers of newly metamorphosed toads dropped quickly with increasing distance from the lakeshore in a pattern that differed over the three weeks of the study and contradicted our original hypotheses. Though we hypothesized that the spatial distribution of toads would initially be concentrated near the lake shore and then spread outward from the lake over time, we observed the opposite. Ninety-five percent of individuals occurred within 20, 16, and 15 m of shore during weeks one, two, and three respectively, probably reflecting continued emergence of newly metamorphosed toads from the lake and mortality or burrow use of dispersed individuals. Numbers of toads were highest near the inlet stream of the lake. Distance sampling may provide a useful method for estimating the surface abundance of newly metamorphosed toads and relating their space use to landscape variables despite uncertain and variable probability of detection. We discuss means of improving the precision of estimates of total abundance.

Synthesis of Partial Rankings of Points of Interest Using Crowdsourcing

DEFF Research Database (Denmark)

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

2015-01-01

The web is increasingly being accessed from mobile devices, and studies suggest that a large fraction of keyword-based search engine queries have local intent, meaning that users are interested in local content and that the underlying ranking function should take into account both relevance...

RANKING THE SPECTATORS’ DIFFICULTIES IN PURCHASING ELECTRONIC TICKETS OF FOOTBALL PREMIER LEAGUE

Directory of Open Access Journals (Sweden)

Ahmad Narimani

2017-04-01

Full Text Available This study aimed to rank the spectators’ difficulties in buying electronic tickets of football premier league matches at Azadi stadium. The population consisted of all spectators of Esteghlal-Persepolis match in the fifteenth league at Azadi stadium (N= 100000. According to Morgan table and using simple random sampling method, 500 participants were selected as sample. A researcher-made questionnaire was used for collecting the data; its face validity was confirmed by 15 experts and performing a pilot study on 30 subjects, its Cronbach’s alpha was calculated to be 0.86. Using SPSS 22, the descriptive and inferential (including Friedman test statistics was applied for analyzing the data. The findings showed that there was a significant difference between rankings of difficulties in buying electronic tickets of Football premier league matches at Azadi Stadium. The difficulties were ranked as: problem in ticket systems, early selling out of electronic tickets, lack of confidence to electronic ticket sale, lack of skill to work with the internet, low speed of internet, and lack of access to the internet

Distant Supervision for Relation Extraction with Ranking-Based Methods

Directory of Open Access Journals (Sweden)

Yang Xiang

2016-05-01

Full Text Available Relation extraction has benefited from distant supervision in recent years with the development of natural language processing techniques and data explosion. However, distant supervision is still greatly limited by the quality of training data, due to its natural motivation for greatly reducing the heavy cost of data annotation. In this paper, we construct an architecture called MIML-sort (Multi-instance Multi-label Learning with Sorting Strategies, which is built on the famous MIML framework. Based on MIML-sort, we propose three ranking-based methods for sample selection with which we identify relation extractors from a subset of the training data. Experiments are set up on the KBP (Knowledge Base Propagation corpus, one of the benchmark datasets for distant supervision, which is large and noisy. Compared with previous work, the proposed methods produce considerably better results. Furthermore, the three methods together achieve the best F1 on the official testing set, with an optimal enhancement of F1 from 27.3% to 29.98%.

Biodesulfurization of coals of different rank: Effect on combustion behavior

Energy Technology Data Exchange (ETDEWEB)

Rubiera, F.; Arenillas, A.; Fuente, E.; Pis, J.J. [CSIC, Oviedo (Spain). Inst. Nacional del Carbon; Marteinz, O.; Moran, A. [Univ. de Leon (Spain). Escuela de Ingenieria Tecnica Minera

1999-02-01

The emission of sulfur oxides during the combustion of coal is one of the causes, among other air pollution problems, of acid rain. The contribution of coal as the mainstay of power production will be determined by whether its environmental performance is equal or superior to other supply options. In this context, desulfurization of coal before combustion by biological methods was studied. Four Spanish high-sulfur content coals of different rank were inoculated with bacteria isolated from mine-drainage waters and with naturally occurring bacteria inherent in the coals to be treated. Higher levels of desulfurization were obtained in the case of the samples treated with their own accompanying bacteria and when aeration was increased. All the samples were amenable to the biodepyritization processes. However, it is of little value to achieve large sulfur reductions if a decrease in coal combustion performance is obtained in the process. For this reason, a comparison was made between the combustibility characteristics of the original coals and those of the biodesulfurized samples. Results indicated that combustibility was not substantially modified by the overall biological treatment. The benefits of reduced sulfur emissions into the atmosphere ought to be taken into account as part of the general evaluation of the processes.

The Roles of Socioeconomic Status, Occupational Health and Job Rank on the Epidemiology of Different Psychiatric Symptoms in a Sample of UK Workers.

Science.gov (United States)

Lopes, B; Kamau, C; Jaspal, R

2018-03-06

There is a considerable gap in epidemiological literature about community mental health showing how psychiatric symptoms are associated with job rank, socioeconomic status, and occupational health. We examine data from 4596 employees collected in the United Kingdom's Psychiatric Morbidity among Adults Living in Private Households Survey. There were 939 workers in managerial jobs, 739 in supervisory jobs and 2918 employees in lower ranking jobs. Of the 4596 workers, 2463 had depressive symptoms and 2133 no depressive symptoms. Job rank, household gross income, social class, personal gross income and socio-economic group were significantly associated with general health, occupational health and depressive and avoidant symptoms. Job rank, occupational and physical health also explained the variance in paranoid and avoidant symptoms among the employees. This study shows that severe psychopathology is related to workers' job rank.

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

Directory of Open Access Journals (Sweden)

Cándida Gago García

2017-03-01

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

Investigating Faculty Members' Beliefs about Distance Education: The Case of Sultan Qaboos University, Oman

Science.gov (United States)

Saleem, Naifa Eid; Al-Suqri, Mohammed Nasser

2015-01-01

This research paper aims to investigate the beliefs (perceptions) about distance education(DE) held by the faculty members of Sultan Qaboos Uuniversity (SQU) at the Sultanate of Oman as well as the differences between their beliefs (perceptions) with regards to gender, teaching experience, college academic rank, nationality, etc. This study used a…

National Student Feedback Surveys in Distance Education: An Investigation at the UK Open University

Science.gov (United States)

Ashby, Alison; Richardson, John T. E.; Woodley, Alan

2011-01-01

National student feedback surveys are administered in a number of countries, and several of these encompass both campus-based and distance learning students. The UK Open University achieves a high ranking in the annual National Student Survey (NSS), but there are some anomalies in the results. The NSS questionnaire was administered to three…

Quasi-periodic variations of cometary ion fluxes at large distances from comet Halley

Energy Technology Data Exchange (ETDEWEB)

Richter, A.K.; Daly, P.W.; Verigin, M.I.; Gringauz, K.I.; Erdos, G.; Kecskemety, K.; Somogyi, A.J.; Szego, K.; Varga, A.; McKenna-Lawlor, S.

1989-04-01

Large variations, with a period of about 4 h, in the energetic ion fluxes have been observed far upstream (between 2 and 10 million kilometers) of comet Halley on both the Vega-1 and Giotto spacecraft. We have fitted the cometocentric distances of the occurrences to a simple model of expanding shells of neutral particles, the production of which is modulated by the spin of the comet nucleus, and have achieved excellent agreement between the two spacecraft. We derive an expansion speed for the neutrals of 6.18 +- 0.14 km s/sup -1/. Possible candidates for the neutrals are hydrogen atoms, created by the photo-dissociation of OH with a speed of 8 km s/sup -1/, or oxygen atoms, produced from the photo-dissociation of CO/sub 2/ with a speed of 6.5 km s/sup -1/.

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

Science.gov (United States)

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.

A Ranking Approach to Genomic Selection.

Science.gov (United States)

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

2015-01-01

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

High-efficiency wavefunction updates for large scale Quantum Monte Carlo

Science.gov (United States)

Kent, Paul; McDaniel, Tyler; Li, Ying Wai; D'Azevedo, Ed

Within ab intio Quantum Monte Carlo (QMC) simulations, the leading numerical cost for large systems is the computation of the values of the Slater determinants in the trial wavefunctions. The evaluation of each Monte Carlo move requires finding the determinant of a dense matrix, which is traditionally iteratively evaluated using a rank-1 Sherman-Morrison updating scheme to avoid repeated explicit calculation of the inverse. For calculations with thousands of electrons, this operation dominates the execution profile. We propose a novel rank- k delayed update scheme. This strategy enables probability evaluation for multiple successive Monte Carlo moves, with application of accepted moves to the matrices delayed until after a predetermined number of moves, k. Accepted events grouped in this manner are then applied to the matrices en bloc with enhanced arithmetic intensity and computational efficiency. This procedure does not change the underlying Monte Carlo sampling or the sampling efficiency. For large systems and algorithms such as diffusion Monte Carlo where the acceptance ratio is high, order of magnitude speedups can be obtained on both multi-core CPU and on GPUs, making this algorithm highly advantageous for current petascale and future exascale computations.

Dynamic Matrix Rank

DEFF Research Database (Denmark)

Frandsen, Gudmund Skovbjerg; Frandsen, Peter Frands

2009-01-01

We consider maintaining information about the rank of a matrix under changes of the entries. For n×n matrices, we show an upper bound of O(n1.575) arithmetic operations and a lower bound of Ω(n) arithmetic operations per element change. The upper bound is valid when changing up to O(n0.575) entries...... in a single column of the matrix. We also give an algorithm that maintains the rank using O(n2) arithmetic operations per rank one update. These bounds appear to be the first nontrivial bounds for the problem. The upper bounds are valid for arbitrary fields, whereas the lower bound is valid for algebraically...... closed fields. The upper bound for element updates uses fast rectangular matrix multiplication, and the lower bound involves further development of an earlier technique for proving lower bounds for dynamic computation of rational functions....

Collective frequency variation in network synchronization and reverse PageRank.

Science.gov (United States)

Skardal, Per Sebastian; Taylor, Dane; Sun, Jie; Arenas, Alex

2016-04-01

A wide range of natural and engineered phenomena rely on large networks of interacting units to reach a dynamical consensus state where the system collectively operates. Here we study the dynamics of self-organizing systems and show that for generic directed networks the collective frequency of the ensemble is not the same as the mean of the individuals' natural frequencies. Specifically, we show that the collective frequency equals a weighted average of the natural frequencies, where the weights are given by an outflow centrality measure that is equivalent to a reverse PageRank centrality. Our findings uncover an intricate dependence of the collective frequency on both the structural directedness and dynamical heterogeneity of the network, and also reveal an unexplored connection between synchronization and PageRank, which opens the possibility of applying PageRank optimization to synchronization. Finally, we demonstrate the presence of collective frequency variation in real-world networks by considering the UK and Scandinavian power grids.

Collective frequency variation in network synchronization and reverse PageRank

Science.gov (United States)

Skardal, Per Sebastian; Taylor, Dane; Sun, Jie; Arenas, Alex

2016-04-01

A wide range of natural and engineered phenomena rely on large networks of interacting units to reach a dynamical consensus state where the system collectively operates. Here we study the dynamics of self-organizing systems and show that for generic directed networks the collective frequency of the ensemble is not the same as the mean of the individuals' natural frequencies. Specifically, we show that the collective frequency equals a weighted average of the natural frequencies, where the weights are given by an outflow centrality measure that is equivalent to a reverse PageRank centrality. Our findings uncover an intricate dependence of the collective frequency on both the structural directedness and dynamical heterogeneity of the network, and also reveal an unexplored connection between synchronization and PageRank, which opens the possibility of applying PageRank optimization to synchronization. Finally, we demonstrate the presence of collective frequency variation in real-world networks by considering the UK and Scandinavian power grids.

A Model-Free Scheme for Meme Ranking in Social Media.

Science.gov (United States)

He, Saike; Zheng, Xiaolong; Zeng, Daniel

2016-01-01

The prevalence of social media has greatly catalyzed the dissemination and proliferation of online memes (e.g., ideas, topics, melodies, tags, etc.). However, this information abundance is exceeding the capability of online users to consume it. Ranking memes based on their popularities could promote online advertisement and content distribution. Despite such importance, few existing work can solve this problem well. They are either daunted by unpractical assumptions or incapability of characterizing dynamic information. As such, in this paper, we elaborate a model-free scheme to rank online memes in the context of social media. This scheme is capable to characterize the nonlinear interactions of online users, which mark the process of meme diffusion. Empirical studies on two large-scale, real-world datasets (one in English and one in Chinese) demonstrate the effectiveness and robustness of the proposed scheme. In addition, due to its fine-grained modeling of user dynamics, this ranking scheme can also be utilized to explain meme popularity through the lens of social influence.

Effects of reproductive status, social rank, sex and group size on vigilance patterns in Przewalski's gazelle.

Directory of Open Access Journals (Sweden)

Chunlin Li

Full Text Available Quantifying vigilance and exploring the underlying mechanisms has been the subject of numerous studies. Less attention has focused on the complex interplay between contributing factors such as reproductive status, social rank, sex and group size. Reproductive status and social rank are of particular interest due to their association with mating behavior. Mating activities in rutting season may interfere with typical patterns of vigilance and possibly interact with social rank. In addition, balancing the tradeoff between vigilance and life maintenance may represent a challenge for gregarious ungulate species rutting under harsh winter conditions. We studied vigilance patterns in the endangered Przewalski's gazelle (Procapra przewalskii during both the rutting and non-rutting seasons to examine these issues.Field observations were carried out with focal sampling during rutting and non-rutting season in 2008-2009. Results indicated a complex interplay between reproductive status, social rank, sex and group size in determining vigilance in this species. Vigilance decreased with group size in female but not in male gazelles. Males scanned more frequently and thus spent more time vigilant than females. Compared to non-rutting season, gazelles increased time spent scanning at the expense of bedding in rutting season. During the rutting season, territorial males spent a large proportion of time on rutting activities and were less vigilant than non-territorial males. Although territorial males may share collective risk detection with harem females, we suggest that they are probably more vulnerable to predation because they seemed reluctant to leave rut stands under threats.Vigilance behavior in Przewalski's gazelle was significantly affected by reproductive status, social rank, sex, group size and their complex interactions. These findings shed light on the mechanisms underlying vigilance patterns and the tradeoff between vigilance and other crucial

Sparse reduced-rank regression with covariance estimation

KAUST Repository

Chen, Lisha

2014-12-08

Improving the predicting performance of the multiple response regression compared with separate linear regressions is a challenging question. On the one hand, it is desirable to seek model parsimony when facing a large number of parameters. On the other hand, for certain applications it is necessary to take into account the general covariance structure for the errors of the regression model. We assume a reduced-rank regression model and work with the likelihood function with general error covariance to achieve both objectives. In addition we propose to select relevant variables for reduced-rank regression by using a sparsity-inducing penalty, and to estimate the error covariance matrix simultaneously by using a similar penalty on the precision matrix. We develop a numerical algorithm to solve the penalized regression problem. In a simulation study and real data analysis, the new method is compared with two recent methods for multivariate regression and exhibits competitive performance in prediction and variable selection.

Sparse reduced-rank regression with covariance estimation

KAUST Repository

Chen, Lisha; Huang, Jianhua Z.

2014-01-01

Improving the predicting performance of the multiple response regression compared with separate linear regressions is a challenging question. On the one hand, it is desirable to seek model parsimony when facing a large number of parameters. On the other hand, for certain applications it is necessary to take into account the general covariance structure for the errors of the regression model. We assume a reduced-rank regression model and work with the likelihood function with general error covariance to achieve both objectives. In addition we propose to select relevant variables for reduced-rank regression by using a sparsity-inducing penalty, and to estimate the error covariance matrix simultaneously by using a similar penalty on the precision matrix. We develop a numerical algorithm to solve the penalized regression problem. In a simulation study and real data analysis, the new method is compared with two recent methods for multivariate regression and exhibits competitive performance in prediction and variable selection.

Utilization of AHWR critical facility for research and development work on large sample NAA

International Nuclear Information System (INIS)

Acharya, R.; Dasari, K.B.; Pujari, P.K.; Swain, K.K.; Reddy, A.V.R.; Verma, S.K.; De, S.K.

2014-01-01

The graphite reflector position of AHWR critical facility (CF) was utilized for analysis of large size (g-kg scale) samples using internal mono standard neutron activation analysis (IM-NAA). The reactor position was characterized by cadmium ratio method using In monitor for total flux and sub cadmium to epithermal flux ratio (f). Large sample neutron activation analysis (LSNAA) work was carried out for samples of stainless steel, ancient and new clay potteries and dross. Large as well as non-standard geometry samples (1 g - 0.5 kg) were irradiated. Radioactive assay was carried out using high resolution gamma ray spectrometry. Concentration ratios obtained by IM-NAA were used for provenance study of 30 clay potteries, obtained from excavated Buddhist sites of AP, India. Concentrations of Au and Ag were determined in not so homogeneous three large size samples of dross. An X-Z rotary scanning unit has been installed for counting large and not so homogeneous samples. (author)

Marine Hydrokinetic Energy Site Identification and Ranking Methodology Part I: Wave Energy

Energy Technology Data Exchange (ETDEWEB)

Kilcher, Levi [National Renewable Energy Lab. (NREL), Golden, CO (United States); Thresher, Robert [National Renewable Energy Lab. (NREL), Golden, CO (United States)

2016-10-01

, Hawaii and the Pacific Northwest (northern California, Oregon, and Washington) rank at the top of the lists. Hawaii ranks highest in the near-term scenario because it has high energy costs. In the long-term scenario, Oregon ranks highest because it has a large market and an energetic resource. Several East Coast states and Puerto Rico are also identified as potential wave energy deployment sites if technological innovations make it possible to efficiently generate electricity from the modest resource there. There are also several small-market sites in Alaska and U.S. Pacific Islands that rank particularly well in the near-term analysis due to their high energy prices. These locations may represent opportunities to demonstrate economical wave energy conversion as a stepping-stone to larger markets. Several factors that will affect wave project costs and siting have not been considered here -- including permitting constraints, conflicting use, seasonal resource variability, extreme event likelihood, and distance to ports -- because consistent data are unavailable or technology-independent scoring could not be identified. As the industry continues to mature and converge around a subset of device archetypes with well-defined costs, more precise investigations of project siting that include these factors will be possible. For now, these results provide a high-level guide pointing to the regions where markets and resource will one day support commercial wave energy projects.

ORDERED WEIGHTED DISTANCE MEASURE

Institute of Scientific and Technical Information of China (English)

Zeshui XU; Jian CHEN

2008-01-01

The aim of this paper is to develop an ordered weighted distance (OWD) measure, which is thegeneralization of some widely used distance measures, including the normalized Hamming distance, the normalized Euclidean distance, the normalized geometric distance, the max distance, the median distance and the min distance, etc. Moreover, the ordered weighted averaging operator, the generalized ordered weighted aggregation operator, the ordered weighted geometric operator, the averaging operator, the geometric mean operator, the ordered weighted square root operator, the square root operator, the max operator, the median operator and the min operator axe also the special cases of the OWD measure. Some methods depending on the input arguments are given to determine the weights associated with the OWD measure. The prominent characteristic of the OWD measure is that it can relieve (or intensify) the influence of unduly large or unduly small deviations on the aggregation results by assigning them low (or high) weights. This desirable characteristic makes the OWD measure very suitable to be used in many actual fields, including group decision making, medical diagnosis, data mining, and pattern recognition, etc. Finally, based on the OWD measure, we develop a group decision making approach, and illustrate it with a numerical example.

Hitting the Rankings Jackpot

Science.gov (United States)

Chapman, David W.

2008-01-01

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

Extended self-ordering regime in hard anodization and its application to make asymmetric AAO membranes for large pitch-distance nanostructures

Science.gov (United States)

Kim, Minwoo; Ha, Yoon-Cheol; Nhat Nguyen, Truong; Choi, Hae Young; Kim, Doohun

2013-12-01

We report here a fast and reliable hard anodization process to make asymmetric anodic aluminum oxide (AAO) membranes which can serve as a template for large pitch-distance nanostructures. In order to make larger pitch distances possible, the common burning failure associated with the high current density during the conventional constant voltage hard anodization, especially at a voltage higher than a known limit, i.e., 155 V for oxalic acid, was effectively suppressed by using a burning-protective agent. A new self-ordering regime beyond the voltage limit was observed with a different voltage-interpore distance relationship of 2.2 nm V-1 compared to the reported 2.0 nm V-1 for hard anodization. Combining a sulfuric acid mild anodization with this new regime of hard anodization, we further demonstrate a scalable process to make an asymmetric membrane with size up to ˜47 mm in diameter and ˜60 μm in thickness. This free-standing membrane can be used as a template for novel nanopatterned structures such as arrays of quantum dots, nanowires or nanotubes with diameters of a few tens of nanometers and pitch distance of over 400 nm.

Social rank and inhalant drug use: the case of lança perfume use in São Paulo, Brazil.

Science.gov (United States)

Sanchez, Zila M; Noto, Ana R; Anthony, James C

2013-07-01

Lanca perfume (chloroform/ether) is an inhalant used mainly by higher social class students in Brazil. In light of the social and epidemiological features of lanca use, supply, and distribution, this investigation tests hypotheses about the degree to which use of inhalant lanca might be occurring in clusters, consistent with social sharing and diffusion, and might show a direct association with social rank even within the relatively privileged social context of private schools in a large mega-city of Latin America. Epidemiologic self-report survey data were from a large representative sample of urban post-primary private school students in São Paulo city, Brazil, in 2008. Newly incident lanca use was studied, first with estimates of clustering from the alternating logistic regressions (ALR) and then with conditional logistic regressions to probe into the hypothesized direct social rank association. ALR disclosed a clustering of newly incident lanca users within private school classrooms (pairwise odds ratio (PWOR)=2.1; 95% CI=1.3, 3.3; p=0.002) as well as clusters of recently active lanca use (PWOR=1.9; 95% CI=1.1, 3.3; p=0.02). Occurrence of lanca use within private school classrooms was directly associated with social rank (odds ratio (OR)=0.2; 95% CI=0.1, 0.8; p=0.03 in the contrast of lowest socio-economic status (SES) versus highest SES strata within classrooms). Thereafter, study of other drugs disclosed similar patterns. The clustering estimates are consistent with concepts of person-to-person sharing of lanca within private school classrooms as well as other dynamic processes that might promote lanca clusters in this context. An observed direct association with social rank is not specific to lanca use. Direct SES estimates across a broad profile of drug compounds suggests causal processes over and above the more specific initially hypothesized social rank gradients in the lanca diffusion process. A novel facet of the evidence is greater occurrence of drug

Social Rank and Inhalant Drug Use: The Case of Lança Perfume Use in São Paulo, Brazil*

Science.gov (United States)

Sanchez, Zila M.; Noto, Ana R.; Anthony, James C.

2016-01-01

Background Lanca perfume (chloroform/ether) is an inhalant used mainly by higher social class students in Brazil. In light of the social and epidemiological features of lanca use, supply, and distribution, this investigation tests hypotheses about the degree to which use of inhalant lanca might be occurring in clusters, consistent with social sharing and diffusion, and might show a direct association with social rank even within the relatively privileged social context of private schools in a large mega-city of Latin America. Methods Epidemiologic self-report survey data were from a large representative sample of urban post-primary private school students in São Paulo city, Brazil, in 2008. Newly incident lanca use was studied, first with estimates of clustering from the alternating logistic regressions (ALR) and then with conditional logistic regressions to probe into the hypothesized direct social rank association. Results ALR disclosed a clustering of newly incident lanca users within private school classrooms (pairwise odds ratio (PWOR) = 2.1; 95% CI = 1.3, 3.3; p = 0.002) as well as clusters of recently active lanca use (PWOR = 1.9; 95% CI = 1.1, 3.3; p = 0.02). Occurrence of lanca use within private school classrooms was directly associated with social rank (odds ratio (OR) = 0.2; 95% CI=0.1, 0.8; p=0.03 in the contrast of lowest socio-economic status (SES) versus highest SES strata within classrooms). Thereafter, study of other drugs disclosed similar patterns. Conclusions The clustering estimates are consistent with concepts of person-to-person sharing of lanca within private school classrooms as well as other dynamic processes that might promote lanca clusters in this context. An observed direct association with social rank is not specific to lanca use. Direct SES estimates across a broad profile of drug compounds suggests causal processes over and above the more specific initially hypothesized social rank gradients in the lanca diffusion process. A novel

SU-G-IeP1-13: Sub-Nyquist Dynamic MRI Via Prior Rank, Intensity and Sparsity Model (PRISM)

International Nuclear Information System (INIS)

Jiang, B; Gao, H

2016-01-01

Purpose: Accelerated dynamic MRI is important for MRI guided radiotherapy. Inspired by compressive sensing (CS), sub-Nyquist dynamic MRI has been an active research area, i.e., sparse sampling in k-t space for accelerated dynamic MRI. This work is to investigate sub-Nyquist dynamic MRI via a previously developed CS model, namely Prior Rank, Intensity and Sparsity Model (PRISM). Methods: The proposed method utilizes PRISM with rank minimization and incoherent sampling patterns for sub-Nyquist reconstruction. In PRISM, the low-rank background image, which is automatically calculated by rank minimization, is excluded from the L1 minimization step of the CS reconstruction to further sparsify the residual image, thus allowing for higher acceleration rates. Furthermore, the sampling pattern in k-t space is made more incoherent by sampling a different set of k-space points at different temporal frames. Results: Reconstruction results from L1-sparsity method and PRISM method with 30% undersampled data and 15% undersampled data are compared to demonstrate the power of PRISM for dynamic MRI. Conclusion: A sub- Nyquist MRI reconstruction method based on PRISM is developed with improved image quality from the L1-sparsity method.

Representing distance, consuming distance

DEFF Research Database (Denmark)

Larsen, Gunvor Riber

Title: Representing Distance, Consuming Distance Abstract: Distance is a condition for corporeal and virtual mobilities, for desired and actual travel, but yet it has received relatively little attention as a theoretical entity in its own right. Understandings of and assumptions about distance...... are being consumed in the contemporary society, in the same way as places, media, cultures and status are being consumed (Urry 1995, Featherstone 2007). An exploration of distance and its representations through contemporary consumption theory could expose what role distance plays in forming...

"I can do perfectly well without a car!": An exploration of stated preferences for middle-distance travel

NARCIS (Netherlands)

N.J.A. van Exel (Job); G. de Graaf; P. Rietveld (Piet)

2011-01-01

textabstractThis article presents the results of a study exploring travellers' preferences for middle-distance travel using Q-methodology. Respondents rank-ordered 42 opinion statements regarding travel choice and motivations for travel in general and for car and public transport as alternative

Exploring Technostress: Results of a Large Sample Factor Analysis